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Each sensor node is equipped with an observer, which uses only local measurements and local interaction with neighbors for monitoring. The observability of said observer is analyzed where non-local observability of a sensor node is required in terms of the system state and faults. The distributed observers present features of H&amp;amp;infin; performance to constrain the influence of disturbances on the estimation errors, for which the global design condition is transformed into a linear matrix inequality (LMI). The LMI is proven to be solvable given collective observability of the system and a suitable H&amp;amp;infin; performance index. Moreover, in the case that no disturbances exist, fully distributed observers with adaptive gains are designed to asymptotically estimate the states and faults without using any global information from the network. Finally, the effectiveness of the proposed methods is verified through case studies on a spacecraft&amp;amp;rsquo;s attitude control system.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7589: Robust Distributed Observers for Simultaneous State and Fault Estimation over Sensor Networks</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7589">doi: 10.3390/s24237589</a></p> <p>Authors: Dingguo Liang Yunxiao Ren Yuezu Lv Silong Wang </p> <p>This paper focuses on simultaneous estimation of states and faults for a linear time-invariant (LTI) system observed by sensor networks. Each sensor node is equipped with an observer, which uses only local measurements and local interaction with neighbors for monitoring. The observability of said observer is analyzed where non-local observability of a sensor node is required in terms of the system state and faults. The distributed observers present features of H&amp;amp;infin; performance to constrain the influence of disturbances on the estimation errors, for which the global design condition is transformed into a linear matrix inequality (LMI). The LMI is proven to be solvable given collective observability of the system and a suitable H&amp;amp;infin; performance index. Moreover, in the case that no disturbances exist, fully distributed observers with adaptive gains are designed to asymptotically estimate the states and faults without using any global information from the network. Finally, the effectiveness of the proposed methods is verified through case studies on a spacecraft&amp;amp;rsquo;s attitude control system.</p> ]]></content:encoded> <dc:title>Robust Distributed Observers for Simultaneous State and Fault Estimation over Sensor Networks</dc:title> <dc:creator>Dingguo Liang</dc:creator> <dc:creator>Yunxiao Ren</dc:creator> <dc:creator>Yuezu Lv</dc:creator> <dc:creator>Silong Wang</dc:creator> <dc:identifier>doi: 10.3390/s24237589</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7589</prism:startingPage> <prism:doi>10.3390/s24237589</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7589</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7591"> <title>Sensors, Vol. 24, Pages 7591: Three-Dimensional Weld Pool Monitoring and Penetration State Recognition for Variable-Gap Keyhole Tungsten Inert Gas Welding Based on Stereo Vision</title> <link>https://www.mdpi.com/1424-8220/24/23/7591</link> <description>K-TIG welding offers the advantages of single-sided welding and double-sided formation, making it widely used for medium/thick-plate welding. The welding quality of K-TIG is closely linked to its penetration state. However, the assembly gap in medium/thick-plate workpieces can easily result in an unstable penetration state. In K-TIG welding, the geometric characteristics of the weld pool are closely related to the penetration state. Compared to arc voltage sensing and acoustic signal sensing, visual sensing is a method capable of obtaining the three-dimensional geometric features of the weld pool. To this end, a K-TIG weld pool three-dimensional monitoring algorithm based on a semantic segmentation network using a stereo vision system with a single High-Dynamic-Range (HDR) camera is proposed in this paper. In order to identify the assembly gap of medium/thick-plate workpieces, a gap width extraction algorithm based on the watershed method is proposed. Subsequently, a penetration state recognition model is constructed, taking the three-dimensional geometric features of the weld pool and the gap width as inputs, with the penetration state as the output. The relationship between the input features and the accuracy of penetration recognition is analyzed through feature ablation experiments. The findings reveal that gap width is the most critical feature influencing the accuracy of penetration recognition, while the area feature negatively affects this accuracy. After removing the area feature, the accuracy of the proposed penetration recognition model reaches 96.7%.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7591: Three-Dimensional Weld Pool Monitoring and Penetration State Recognition for Variable-Gap Keyhole Tungsten Inert Gas Welding Based on Stereo Vision</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7591">doi: 10.3390/s24237591</a></p> <p>Authors: Zishun Wang Yonghua Shi Yanxin Cui Wenqian Yan </p> <p>K-TIG welding offers the advantages of single-sided welding and double-sided formation, making it widely used for medium/thick-plate welding. The welding quality of K-TIG is closely linked to its penetration state. However, the assembly gap in medium/thick-plate workpieces can easily result in an unstable penetration state. In K-TIG welding, the geometric characteristics of the weld pool are closely related to the penetration state. Compared to arc voltage sensing and acoustic signal sensing, visual sensing is a method capable of obtaining the three-dimensional geometric features of the weld pool. To this end, a K-TIG weld pool three-dimensional monitoring algorithm based on a semantic segmentation network using a stereo vision system with a single High-Dynamic-Range (HDR) camera is proposed in this paper. In order to identify the assembly gap of medium/thick-plate workpieces, a gap width extraction algorithm based on the watershed method is proposed. Subsequently, a penetration state recognition model is constructed, taking the three-dimensional geometric features of the weld pool and the gap width as inputs, with the penetration state as the output. The relationship between the input features and the accuracy of penetration recognition is analyzed through feature ablation experiments. The findings reveal that gap width is the most critical feature influencing the accuracy of penetration recognition, while the area feature negatively affects this accuracy. After removing the area feature, the accuracy of the proposed penetration recognition model reaches 96.7%.</p> ]]></content:encoded> <dc:title>Three-Dimensional Weld Pool Monitoring and Penetration State Recognition for Variable-Gap Keyhole Tungsten Inert Gas Welding Based on Stereo Vision</dc:title> <dc:creator>Zishun Wang</dc:creator> <dc:creator>Yonghua Shi</dc:creator> <dc:creator>Yanxin Cui</dc:creator> <dc:creator>Wenqian Yan</dc:creator> <dc:identifier>doi: 10.3390/s24237591</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7591</prism:startingPage> <prism:doi>10.3390/s24237591</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7591</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7592"> <title>Sensors, Vol. 24, Pages 7592: New Design Scheme for and Application of Fresnel Lens for Broadband Photonics Terahertz Communication</title> <link>https://www.mdpi.com/1424-8220/24/23/7592</link> <description>In terahertz communication systems, lens antennas used in transceivers are basically plano-convex dielectric lenses. The size of a plano-convex lens increases as the aperture increases, and thinner lenses have longer focal lengths. Through theory and simulation, we designed a Fresnel lens suitable for the terahertz band to meet the requirements of large aperture and short focal length, and simulated the performance, advantages, and disadvantages of the terahertz Fresnel lens. A 300 GHz terahertz wireless communication system was built to verify the gain effect of the Fresnel lens antenna. The experimental results demonstrate that the Fresnel lens can be used for long-distance terahertz communication with larger aperture diameters, overcoming the limitations of traditional plano-convex lenses. The theoretical gain of a 30 cm Fresnel lens is 48.83 dB, while the actual measured gain is approximately 45 dB.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7592: New Design Scheme for and Application of Fresnel Lens for Broadband Photonics Terahertz Communication</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7592">doi: 10.3390/s24237592</a></p> <p>Authors: Peng Tian Yang Han Weiping Li Xiongwei Yang Mingxu Wang Jianjun Yu </p> <p>In terahertz communication systems, lens antennas used in transceivers are basically plano-convex dielectric lenses. The size of a plano-convex lens increases as the aperture increases, and thinner lenses have longer focal lengths. Through theory and simulation, we designed a Fresnel lens suitable for the terahertz band to meet the requirements of large aperture and short focal length, and simulated the performance, advantages, and disadvantages of the terahertz Fresnel lens. A 300 GHz terahertz wireless communication system was built to verify the gain effect of the Fresnel lens antenna. The experimental results demonstrate that the Fresnel lens can be used for long-distance terahertz communication with larger aperture diameters, overcoming the limitations of traditional plano-convex lenses. The theoretical gain of a 30 cm Fresnel lens is 48.83 dB, while the actual measured gain is approximately 45 dB.</p> ]]></content:encoded> <dc:title>New Design Scheme for and Application of Fresnel Lens for Broadband Photonics Terahertz Communication</dc:title> <dc:creator>Peng Tian</dc:creator> <dc:creator>Yang Han</dc:creator> <dc:creator>Weiping Li</dc:creator> <dc:creator>Xiongwei Yang</dc:creator> <dc:creator>Mingxu Wang</dc:creator> <dc:creator>Jianjun Yu</dc:creator> <dc:identifier>doi: 10.3390/s24237592</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7592</prism:startingPage> <prism:doi>10.3390/s24237592</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7592</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7590"> <title>Sensors, Vol. 24, Pages 7590: MGL-YOLO: A Lightweight Barcode Target Detection Algorithm</title> <link>https://www.mdpi.com/1424-8220/24/23/7590</link> <description>Due to the critical importance of one-dimensional barcode detection in logistics, retail, and manufacturing, which has become a key issue affecting operational efficiency, researchers have shown increasing interest in this area. However, deploying deep convolutional neural networks on embedded and some edge devices is very challenging due to limited storage space and computational resources. To address this issue, this paper proposes MGL-YOLO, a lightweight one-dimensional barcode detection network based on an improved YOLOv8, which aims to achieve a high detection accuracy at low computational cost. First, a new multi-scale group convolution (MSGConv) is designed and integrated into the C2f module to construct the MSG-C2f feature extraction module. By replacing the C2f module in the P5 layer of the backbone network, the ability to extract multi-scale feature information is enhanced. Secondly, a feature extraction module, Group RepConv Cross Stage Partial Efficient Long-Range Attention Network (GRCE), is designed to optimize the feature extraction capability of the C2f modules in the neck section, offering significant advantages in multi-scale characteristics and complexity adjustment. Finally, a Lightweight Shared Multi-Scale Detection Head (LSMD) is proposed, which improves the model&amp;amp;rsquo;s detection accuracy and adaptability while reducing the model&amp;amp;rsquo;s parameter size and computational complexity. Experimental results show that the proposed algorithm increases MAP50 and MAP50.95 by 2.57% and 2.31%, respectively, compared to YOLOv8, while reducing parameter size and computational cost by 36.21% and 34.15%, respectively. Moreover, it also demonstrates advantages in average precision compared to other object detection networks, proving the effectiveness of MGL-YOLO for one-dimensional barcode detection in complex backgrounds.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7590: MGL-YOLO: A Lightweight Barcode Target Detection Algorithm</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7590">doi: 10.3390/s24237590</a></p> <p>Authors: Yuanhao Qu Fengshou Zhang </p> <p>Due to the critical importance of one-dimensional barcode detection in logistics, retail, and manufacturing, which has become a key issue affecting operational efficiency, researchers have shown increasing interest in this area. However, deploying deep convolutional neural networks on embedded and some edge devices is very challenging due to limited storage space and computational resources. To address this issue, this paper proposes MGL-YOLO, a lightweight one-dimensional barcode detection network based on an improved YOLOv8, which aims to achieve a high detection accuracy at low computational cost. First, a new multi-scale group convolution (MSGConv) is designed and integrated into the C2f module to construct the MSG-C2f feature extraction module. By replacing the C2f module in the P5 layer of the backbone network, the ability to extract multi-scale feature information is enhanced. Secondly, a feature extraction module, Group RepConv Cross Stage Partial Efficient Long-Range Attention Network (GRCE), is designed to optimize the feature extraction capability of the C2f modules in the neck section, offering significant advantages in multi-scale characteristics and complexity adjustment. Finally, a Lightweight Shared Multi-Scale Detection Head (LSMD) is proposed, which improves the model&amp;amp;rsquo;s detection accuracy and adaptability while reducing the model&amp;amp;rsquo;s parameter size and computational complexity. Experimental results show that the proposed algorithm increases MAP50 and MAP50.95 by 2.57% and 2.31%, respectively, compared to YOLOv8, while reducing parameter size and computational cost by 36.21% and 34.15%, respectively. Moreover, it also demonstrates advantages in average precision compared to other object detection networks, proving the effectiveness of MGL-YOLO for one-dimensional barcode detection in complex backgrounds.</p> ]]></content:encoded> <dc:title>MGL-YOLO: A Lightweight Barcode Target Detection Algorithm</dc:title> <dc:creator>Yuanhao Qu</dc:creator> <dc:creator>Fengshou Zhang</dc:creator> <dc:identifier>doi: 10.3390/s24237590</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7590</prism:startingPage> <prism:doi>10.3390/s24237590</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7590</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7588"> <title>Sensors, Vol. 24, Pages 7588: Multi-Pilot Channel Estimation for Orthogonal Time&amp;ndash;Frequency Space Systems Based on Constant-Amplitude Zero-Autocorrelation Sequences</title> <link>https://www.mdpi.com/1424-8220/24/23/7588</link> <description>Future communication systems must support high-speed mobile scenarios, while the mainstream Orthogonal Frequency Division Multiplexing (OFDM) technology faces severe inter-carrier interference in such environments. Therefore, the adoption of Orthogonal Time&amp;amp;ndash;Frequency Space (OTFS) modulation in 6G systems is an effective solution. The widely used single-pilot channel estimation in OTFS systems is susceptible to path loss and inaccurate fading coefficient estimation, leading to reduced estimation accuracy, signal distortion, and degraded overall system communication quality. To address this problem, this paper proposes a Constant-Amplitude Zero-Autocorrelation (CAZAC) sequence-based multi-pilot OTFS channel estimation scheme. The proposed method inserts multiple low-power pilots in the delayed Doppler domain (DD) and employs joint signal processing at the receiver to effectively suppress noise, thereby significantly improving the accuracy and reliability of channel estimation. Additionally, this paper analyzes the impact of CAZAC sequence length on estimation performance and provides reasonable parameter selection recommendations. In summary, this work proposes an innovative solution to the channel estimation challenge in OTFS systems, laying a solid theoretical foundation for the realization of future high-speed mobile communication technologies such as 6G, with important academic value and application prospects.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7588: Multi-Pilot Channel Estimation for Orthogonal Time&amp;ndash;Frequency Space Systems Based on Constant-Amplitude Zero-Autocorrelation Sequences</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7588">doi: 10.3390/s24237588</a></p> <p>Authors: Ju Guo Hou He Li Lan Chou </p> <p>Future communication systems must support high-speed mobile scenarios, while the mainstream Orthogonal Frequency Division Multiplexing (OFDM) technology faces severe inter-carrier interference in such environments. Therefore, the adoption of Orthogonal Time&amp;amp;ndash;Frequency Space (OTFS) modulation in 6G systems is an effective solution. The widely used single-pilot channel estimation in OTFS systems is susceptible to path loss and inaccurate fading coefficient estimation, leading to reduced estimation accuracy, signal distortion, and degraded overall system communication quality. To address this problem, this paper proposes a Constant-Amplitude Zero-Autocorrelation (CAZAC) sequence-based multi-pilot OTFS channel estimation scheme. The proposed method inserts multiple low-power pilots in the delayed Doppler domain (DD) and employs joint signal processing at the receiver to effectively suppress noise, thereby significantly improving the accuracy and reliability of channel estimation. Additionally, this paper analyzes the impact of CAZAC sequence length on estimation performance and provides reasonable parameter selection recommendations. In summary, this work proposes an innovative solution to the channel estimation challenge in OTFS systems, laying a solid theoretical foundation for the realization of future high-speed mobile communication technologies such as 6G, with important academic value and application prospects.</p> ]]></content:encoded> <dc:title>Multi-Pilot Channel Estimation for Orthogonal Time&amp;amp;ndash;Frequency Space Systems Based on Constant-Amplitude Zero-Autocorrelation Sequences</dc:title> <dc:creator> Ju</dc:creator> <dc:creator> Guo</dc:creator> <dc:creator> Hou</dc:creator> <dc:creator> He</dc:creator> <dc:creator> Li</dc:creator> <dc:creator> Lan</dc:creator> <dc:creator> Chou</dc:creator> <dc:identifier>doi: 10.3390/s24237588</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7588</prism:startingPage> <prism:doi>10.3390/s24237588</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7588</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7587"> <title>Sensors, Vol. 24, Pages 7587: A Survey of the Magnetic Anisotropy Detection Technology of Ferromagnetic Materials Based on Magnetic Barkhausen Noise</title> <link>https://www.mdpi.com/1424-8220/24/23/7587</link> <description>Magnetic Barkhausen noise (MBN) is one of the most effective methods for determining the easy axis of ferromagnetic materials and for evaluating texture and residual stress in a nondestructive manner. MBN signals from multiple angles and different magnetization sections can be used to characterize magnetic anisotropy caused by various magnetization mechanisms. This paper reviews the development and application of magnetic anisotropy detection technology, and the MBN anisotropy models that take into account domain wall motion and magnetic domain rotation are analyzed thoroughly. Subsequently, the MBN anisotropy detection devices and detection methods are discussed, and the application of magnetic anisotropy detection technology in stress measurement and texture evaluation is reviewed. From the perspective of improving detection accuracy, the influence of composite mechanisms on magnetic anisotropy is analyzed. Finally, the opportunities and challenges faced by current magnetic anisotropy detection technology are summarized. The relevant conclusions obtained in this paper can be used to guide the MBN evaluation of magnetic anisotropy in ferromagnetic materials.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7587: A Survey of the Magnetic Anisotropy Detection Technology of Ferromagnetic Materials Based on Magnetic Barkhausen Noise</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7587">doi: 10.3390/s24237587</a></p> <p>Authors: Liting Wang Changjie Xu Libo Feng Wenjie Wang </p> <p>Magnetic Barkhausen noise (MBN) is one of the most effective methods for determining the easy axis of ferromagnetic materials and for evaluating texture and residual stress in a nondestructive manner. MBN signals from multiple angles and different magnetization sections can be used to characterize magnetic anisotropy caused by various magnetization mechanisms. This paper reviews the development and application of magnetic anisotropy detection technology, and the MBN anisotropy models that take into account domain wall motion and magnetic domain rotation are analyzed thoroughly. Subsequently, the MBN anisotropy detection devices and detection methods are discussed, and the application of magnetic anisotropy detection technology in stress measurement and texture evaluation is reviewed. From the perspective of improving detection accuracy, the influence of composite mechanisms on magnetic anisotropy is analyzed. Finally, the opportunities and challenges faced by current magnetic anisotropy detection technology are summarized. The relevant conclusions obtained in this paper can be used to guide the MBN evaluation of magnetic anisotropy in ferromagnetic materials.</p> ]]></content:encoded> <dc:title>A Survey of the Magnetic Anisotropy Detection Technology of Ferromagnetic Materials Based on Magnetic Barkhausen Noise</dc:title> <dc:creator>Liting Wang</dc:creator> <dc:creator>Changjie Xu</dc:creator> <dc:creator>Libo Feng</dc:creator> <dc:creator>Wenjie Wang</dc:creator> <dc:identifier>doi: 10.3390/s24237587</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Review</prism:section> <prism:startingPage>7587</prism:startingPage> <prism:doi>10.3390/s24237587</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7587</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7586"> <title>Sensors, Vol. 24, Pages 7586: Quantifying Arm and Leg Movements in 3-Month-Old Infants Using Pose Estimation: Proof of Concept</title> <link>https://www.mdpi.com/1424-8220/24/23/7586</link> <description>Background: Pose estimation (PE) has the promise to measure pediatric movement from a video recording. The purpose of this study was to quantify the accuracy of a PE model to detect arm and leg movements in 3-month-old infants with and without (TD, for typical development) complex congenital heart disease (CCHD). Methods: Data from 12 3-month-old infants (N = 6 TD and N = 6 CCHD) were used to assess MediaPipe&amp;amp;rsquo;s full-body model. Positive predictive value (PPV) and sensitivity assessed the model&amp;amp;rsquo;s accuracy with behavioral coding. Results: Overall, 499 leg and arm movements were identified, and the model had a PPV of 85% and a sensitivity of 94%. The model&amp;amp;rsquo;s PPV in TD was 84% and the sensitivity was 93%. The model&amp;amp;rsquo;s PPV in CCHD was 87% and the sensitivity was 98%. Movements per hour ranged from 399 to 4211 for legs and 236 to 3767 for arms for all participants, similar ranges to the literature on wearables. No group differences were detected. Conclusions: There is a strong promise for PE and models to describe infant movements with accessible and affordable resources&amp;amp;mdash;like a cell phone and curated video repositories. These models can be used to further improve developmental assessments of limb function, movement, and changes over time.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7586: Quantifying Arm and Leg Movements in 3-Month-Old Infants Using Pose Estimation: Proof of Concept</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7586">doi: 10.3390/s24237586</a></p> <p>Authors: Marcelo R. Rosales Janet Simsic Tondi Kneeland Jill Heathcock </p> <p>Background: Pose estimation (PE) has the promise to measure pediatric movement from a video recording. The purpose of this study was to quantify the accuracy of a PE model to detect arm and leg movements in 3-month-old infants with and without (TD, for typical development) complex congenital heart disease (CCHD). Methods: Data from 12 3-month-old infants (N = 6 TD and N = 6 CCHD) were used to assess MediaPipe&amp;amp;rsquo;s full-body model. Positive predictive value (PPV) and sensitivity assessed the model&amp;amp;rsquo;s accuracy with behavioral coding. Results: Overall, 499 leg and arm movements were identified, and the model had a PPV of 85% and a sensitivity of 94%. The model&amp;amp;rsquo;s PPV in TD was 84% and the sensitivity was 93%. The model&amp;amp;rsquo;s PPV in CCHD was 87% and the sensitivity was 98%. Movements per hour ranged from 399 to 4211 for legs and 236 to 3767 for arms for all participants, similar ranges to the literature on wearables. No group differences were detected. Conclusions: There is a strong promise for PE and models to describe infant movements with accessible and affordable resources&amp;amp;mdash;like a cell phone and curated video repositories. These models can be used to further improve developmental assessments of limb function, movement, and changes over time.</p> ]]></content:encoded> <dc:title>Quantifying Arm and Leg Movements in 3-Month-Old Infants Using Pose Estimation: Proof of Concept</dc:title> <dc:creator>Marcelo R. Rosales</dc:creator> <dc:creator>Janet Simsic</dc:creator> <dc:creator>Tondi Kneeland</dc:creator> <dc:creator>Jill Heathcock</dc:creator> <dc:identifier>doi: 10.3390/s24237586</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7586</prism:startingPage> <prism:doi>10.3390/s24237586</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7586</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7585"> <title>Sensors, Vol. 24, Pages 7585: Kolmogorov&amp;ndash;Arnold Network in the Fault Diagnosis of Oil-Immersed Power Transformers</title> <link>https://www.mdpi.com/1424-8220/24/23/7585</link> <description>Instabilities in energy supply caused by equipment failures, particularly in power transformers, can significantly impact efficiency and lead to shutdowns, which can affect the population. To address this, researchers have developed fault diagnosis strategies for oil-immersed power transformers using dissolved gas analysis (DGA) to enhance reliability and environmental responsibility. However, the fault diagnosis of oil-immersed power transformers has not been exhaustively investigated. There are gaps related to real scenarios with imbalanced datasets, such as the reliability and robustness of fault diagnosis modules. Strategies with more robust models increase the overall performance of the entire system. To address this issue, we propose a novel approach based on Kolmogorov&amp;amp;ndash;Arnold Network (KAN) for the fault diagnosis of power transformers. Our work is the first to employ a dedicated KAN in an imbalanced data real-world scenario, named KANDiag, while also applying the synthetic minority based on probabilistic distribution (SyMProD) technique for balancing the data in the fault diagnosis. Our findings reveal that this pioneering employment of KANDiag achieved the minimal value of Hamming loss&amp;amp;mdash;0.0323&amp;amp;mdash;which minimized the classification error, guaranteeing enhanced reliability for the whole system. This ground-breaking implementation of KANDiag achieved the highest value of weighted average F1-Score&amp;amp;mdash;96.8455%&amp;amp;mdash;ensuring the solidity of the approach in the real imbalanced data scenario. In addition, KANDiag gave the highest value for accuracy&amp;amp;mdash;96.7728%&amp;amp;mdash;demonstrating the robustness of the entire system. Some key outcomes revealed gains of 68.61 percentage points for KANDiag in the fault diagnosis. These advancements emphasize the efficiency and robustness of the proposed system.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7585: Kolmogorov&amp;ndash;Arnold Network in the Fault Diagnosis of Oil-Immersed Power Transformers</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7585">doi: 10.3390/s24237585</a></p> <p>Authors: Thales W. Cabral Felippe V. Gomes Eduardo R. de Lima Jos茅 C. S. S. Filho Lu铆s G. P. Meloni </p> <p>Instabilities in energy supply caused by equipment failures, particularly in power transformers, can significantly impact efficiency and lead to shutdowns, which can affect the population. To address this, researchers have developed fault diagnosis strategies for oil-immersed power transformers using dissolved gas analysis (DGA) to enhance reliability and environmental responsibility. However, the fault diagnosis of oil-immersed power transformers has not been exhaustively investigated. There are gaps related to real scenarios with imbalanced datasets, such as the reliability and robustness of fault diagnosis modules. Strategies with more robust models increase the overall performance of the entire system. To address this issue, we propose a novel approach based on Kolmogorov&amp;amp;ndash;Arnold Network (KAN) for the fault diagnosis of power transformers. Our work is the first to employ a dedicated KAN in an imbalanced data real-world scenario, named KANDiag, while also applying the synthetic minority based on probabilistic distribution (SyMProD) technique for balancing the data in the fault diagnosis. Our findings reveal that this pioneering employment of KANDiag achieved the minimal value of Hamming loss&amp;amp;mdash;0.0323&amp;amp;mdash;which minimized the classification error, guaranteeing enhanced reliability for the whole system. This ground-breaking implementation of KANDiag achieved the highest value of weighted average F1-Score&amp;amp;mdash;96.8455%&amp;amp;mdash;ensuring the solidity of the approach in the real imbalanced data scenario. In addition, KANDiag gave the highest value for accuracy&amp;amp;mdash;96.7728%&amp;amp;mdash;demonstrating the robustness of the entire system. Some key outcomes revealed gains of 68.61 percentage points for KANDiag in the fault diagnosis. These advancements emphasize the efficiency and robustness of the proposed system.</p> ]]></content:encoded> <dc:title>Kolmogorov&amp;amp;ndash;Arnold Network in the Fault Diagnosis of Oil-Immersed Power Transformers</dc:title> <dc:creator>Thales W. Cabral</dc:creator> <dc:creator>Felippe V. Gomes</dc:creator> <dc:creator>Eduardo R. de Lima</dc:creator> <dc:creator>Jos茅 C. S. S. Filho</dc:creator> <dc:creator>Lu铆s G. P. Meloni</dc:creator> <dc:identifier>doi: 10.3390/s24237585</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7585</prism:startingPage> <prism:doi>10.3390/s24237585</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7585</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7584"> <title>Sensors, Vol. 24, Pages 7584: EBFA-6D: End-to-End Transparent Object 6D Pose Estimation Based on a Boundary Feature Augmented Mechanism</title> <link>https://www.mdpi.com/1424-8220/24/23/7584</link> <description>Transparent objects, commonly encountered in everyday environments, present significant challenges for 6D pose estimation due to their unique optical properties. The lack of inherent texture and color complicates traditional vision methods, while the transparency prevents depth sensors from accurately capturing geometric details. We propose EBFA-6D, a novel end-to-end 6D pose estimation framework that directly predicts the 6D poses of transparent objects from a single RGB image. To overcome the challenges introduced by transparency, we leverage the high contrast at object boundaries inherent to transparent objects by proposing a boundary feature augmented mechanism. We further conduct a bottom-up feature fusion to enhance the location capability of EBFA-6D. EBFA-6D is evaluated on the ClearPose dataset, outperforming the existing methods in accuracy while achieving an inference speed near real-time. The results demonstrate that EBFA-6D provides an efficient and effective solution for accurate 6D pose estimation of transparent objects.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7584: EBFA-6D: End-to-End Transparent Object 6D Pose Estimation Based on a Boundary Feature Augmented Mechanism</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7584">doi: 10.3390/s24237584</a></p> <p>Authors: Xinbei Jiang Zichen Zhu Tianhan Gao Nan Guo </p> <p>Transparent objects, commonly encountered in everyday environments, present significant challenges for 6D pose estimation due to their unique optical properties. The lack of inherent texture and color complicates traditional vision methods, while the transparency prevents depth sensors from accurately capturing geometric details. We propose EBFA-6D, a novel end-to-end 6D pose estimation framework that directly predicts the 6D poses of transparent objects from a single RGB image. To overcome the challenges introduced by transparency, we leverage the high contrast at object boundaries inherent to transparent objects by proposing a boundary feature augmented mechanism. We further conduct a bottom-up feature fusion to enhance the location capability of EBFA-6D. EBFA-6D is evaluated on the ClearPose dataset, outperforming the existing methods in accuracy while achieving an inference speed near real-time. The results demonstrate that EBFA-6D provides an efficient and effective solution for accurate 6D pose estimation of transparent objects.</p> ]]></content:encoded> <dc:title>EBFA-6D: End-to-End Transparent Object 6D Pose Estimation Based on a Boundary Feature Augmented Mechanism</dc:title> <dc:creator>Xinbei Jiang</dc:creator> <dc:creator>Zichen Zhu</dc:creator> <dc:creator>Tianhan Gao</dc:creator> <dc:creator>Nan Guo</dc:creator> <dc:identifier>doi: 10.3390/s24237584</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7584</prism:startingPage> <prism:doi>10.3390/s24237584</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7584</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7583"> <title>Sensors, Vol. 24, Pages 7583: Research on High-Precision and Wide-Range Spacecraft Potential Measurement Method Based on Capacitive Voltage Division</title> <link>https://www.mdpi.com/1424-8220/24/23/7583</link> <description>The charging and discharging of satellite surfaces induced by the space plasma environment constitute a primary cause of spacecraft anomalies, particularly in geosynchronous orbits subject to geomagnetic substorms and hot plasma injections from the magnetotail, where satellites are prone to unequal high-potential charging, significantly impacting the safe and reliable operation of spacecraft. Addressing the need for measuring these unequal charge states, a high-precision, wide-range spacecraft potential measurement method based on capacitive voltage division was investigated. This study analyzed the mechanism of potential measurement and the factors contributing to errors during the measurement process, explored optimal design methodologies, and innovatively developed a fundamental charge zeroing method to resolve output drift issues caused by accumulated errors fundamentally. Consequently, a non-contact potential measurement system was developed, featuring a measurement range of up to &amp;amp;minus;15,000 V, a resolution below 15 V, and a nonlinear error of less than 0.1%. This system provides technical support for monitoring the potential state of spacecraft and ensuring their safety and protection.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7583: Research on High-Precision and Wide-Range Spacecraft Potential Measurement Method Based on Capacitive Voltage Division</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7583">doi: 10.3390/s24237583</a></p> <p>Authors: Hong Yin Haibo Liu Xiaogang Qin Qing Liu Jun Wang Xuan Wen Peng Wang Zixin Yu Shengsheng Yang </p> <p>The charging and discharging of satellite surfaces induced by the space plasma environment constitute a primary cause of spacecraft anomalies, particularly in geosynchronous orbits subject to geomagnetic substorms and hot plasma injections from the magnetotail, where satellites are prone to unequal high-potential charging, significantly impacting the safe and reliable operation of spacecraft. Addressing the need for measuring these unequal charge states, a high-precision, wide-range spacecraft potential measurement method based on capacitive voltage division was investigated. This study analyzed the mechanism of potential measurement and the factors contributing to errors during the measurement process, explored optimal design methodologies, and innovatively developed a fundamental charge zeroing method to resolve output drift issues caused by accumulated errors fundamentally. Consequently, a non-contact potential measurement system was developed, featuring a measurement range of up to &amp;amp;minus;15,000 V, a resolution below 15 V, and a nonlinear error of less than 0.1%. This system provides technical support for monitoring the potential state of spacecraft and ensuring their safety and protection.</p> ]]></content:encoded> <dc:title>Research on High-Precision and Wide-Range Spacecraft Potential Measurement Method Based on Capacitive Voltage Division</dc:title> <dc:creator>Hong Yin</dc:creator> <dc:creator>Haibo Liu</dc:creator> <dc:creator>Xiaogang Qin</dc:creator> <dc:creator>Qing Liu</dc:creator> <dc:creator>Jun Wang</dc:creator> <dc:creator>Xuan Wen</dc:creator> <dc:creator>Peng Wang</dc:creator> <dc:creator>Zixin Yu</dc:creator> <dc:creator>Shengsheng Yang</dc:creator> <dc:identifier>doi: 10.3390/s24237583</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7583</prism:startingPage> <prism:doi>10.3390/s24237583</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7583</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7582"> <title>Sensors, Vol. 24, Pages 7582: Structural Online Damage Identification and Dynamic Reliability Prediction Method Based on Unscented Kalman Filter</title> <link>https://www.mdpi.com/1424-8220/24/23/7582</link> <description>As sensor monitoring technology continues to evolve, structural online monitoring and health management have found numerous applications across various fields. However, challenges remain concerning the real-time diagnosis of structural damage and the accuracy of dynamic reliability predictions. In this paper, a structural online damage identification and dynamic reliability prediction method based on Unscented Kalman Filter (UKF) is presented. Specifically, in the Wiener degradation process with random effects on structural performance, the structural damage identification is initially realized using UKF. Following that, the EM algorithm is employed for estimating the performance model parameters. Eventually, dynamic reliability prediction is realized based on conditional probability. The simulation results indicate that the method effectively estimates the damage state during the structure&amp;amp;rsquo;s use while providing accurate, real-time, and dynamic reliability predictions for the system.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7582: Structural Online Damage Identification and Dynamic Reliability Prediction Method Based on Unscented Kalman Filter</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7582">doi: 10.3390/s24237582</a></p> <p>Authors: Yan Zhang Yongbo Zhang Jinhui Yu Fei Zhao Shihao Zhu </p> <p>As sensor monitoring technology continues to evolve, structural online monitoring and health management have found numerous applications across various fields. However, challenges remain concerning the real-time diagnosis of structural damage and the accuracy of dynamic reliability predictions. In this paper, a structural online damage identification and dynamic reliability prediction method based on Unscented Kalman Filter (UKF) is presented. Specifically, in the Wiener degradation process with random effects on structural performance, the structural damage identification is initially realized using UKF. Following that, the EM algorithm is employed for estimating the performance model parameters. Eventually, dynamic reliability prediction is realized based on conditional probability. The simulation results indicate that the method effectively estimates the damage state during the structure&amp;amp;rsquo;s use while providing accurate, real-time, and dynamic reliability predictions for the system.</p> ]]></content:encoded> <dc:title>Structural Online Damage Identification and Dynamic Reliability Prediction Method Based on Unscented Kalman Filter</dc:title> <dc:creator>Yan Zhang</dc:creator> <dc:creator>Yongbo Zhang</dc:creator> <dc:creator>Jinhui Yu</dc:creator> <dc:creator>Fei Zhao</dc:creator> <dc:creator>Shihao Zhu</dc:creator> <dc:identifier>doi: 10.3390/s24237582</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7582</prism:startingPage> <prism:doi>10.3390/s24237582</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7582</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7581"> <title>Sensors, Vol. 24, Pages 7581: Evaluation of Electrical Characteristics of Weft&amp;minus;Knitted Strain Sensors for Joint Motion Monitoring: Focus on Plating Stitch Structure</title> <link>https://www.mdpi.com/1424-8220/24/23/7581</link> <description>We developed a sensor optimized for joint motion monitoring by exploring the effects of the stitch pattern, yarn thickness, and NP number on the performance of knitted strain sensors. We conducted stretching experiments with basic weft&amp;amp;minus;knit patterns to select the optimal stitch pattern and analyze its sensitivity and reproducibility. The plain stitch with a conductive yarn located on the reverse side exhibited the highest gauge factor value (143.68) and achieved excellent performance, with a stable change in resistance even after repeated sensing. For an in&amp;amp;minus;depth analysis, we developed six sensors using the aforementioned pattern with different combinations of yarn thickness (1&amp;amp;minus;ply, 2&amp;amp;minus;ply) and NP numbers (12, 13, 14). Based on bending experiments, the GF across all sensors was 60.2&amp;amp;ndash;1092, indicating noticeable differences in sensitivity. However, no significant differences were observed in reproducibility, reliability, and responsiveness, confirming that all the sensors are capable of joint motion monitoring. Therefore, the plain&amp;amp;minus;patterned plating stitch structure with conductive yarn on the reverse side is optimal for joint motion monitoring, and the yarn thickness and NP numbers can be adjusted to suit different purposes. This study provides basic data for developing knitted strain sensors and offers insights into how knitting methods impact sensor performance.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7581: Evaluation of Electrical Characteristics of Weft&amp;minus;Knitted Strain Sensors for Joint Motion Monitoring: Focus on Plating Stitch Structure</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7581">doi: 10.3390/s24237581</a></p> <p>Authors: You-Kyung Oh Youn-Hee Kim </p> <p>We developed a sensor optimized for joint motion monitoring by exploring the effects of the stitch pattern, yarn thickness, and NP number on the performance of knitted strain sensors. We conducted stretching experiments with basic weft&amp;amp;minus;knit patterns to select the optimal stitch pattern and analyze its sensitivity and reproducibility. The plain stitch with a conductive yarn located on the reverse side exhibited the highest gauge factor value (143.68) and achieved excellent performance, with a stable change in resistance even after repeated sensing. For an in&amp;amp;minus;depth analysis, we developed six sensors using the aforementioned pattern with different combinations of yarn thickness (1&amp;amp;minus;ply, 2&amp;amp;minus;ply) and NP numbers (12, 13, 14). Based on bending experiments, the GF across all sensors was 60.2&amp;amp;ndash;1092, indicating noticeable differences in sensitivity. However, no significant differences were observed in reproducibility, reliability, and responsiveness, confirming that all the sensors are capable of joint motion monitoring. Therefore, the plain&amp;amp;minus;patterned plating stitch structure with conductive yarn on the reverse side is optimal for joint motion monitoring, and the yarn thickness and NP numbers can be adjusted to suit different purposes. This study provides basic data for developing knitted strain sensors and offers insights into how knitting methods impact sensor performance.</p> ]]></content:encoded> <dc:title>Evaluation of Electrical Characteristics of Weft&amp;amp;minus;Knitted Strain Sensors for Joint Motion Monitoring: Focus on Plating Stitch Structure</dc:title> <dc:creator>You-Kyung Oh</dc:creator> <dc:creator>Youn-Hee Kim</dc:creator> <dc:identifier>doi: 10.3390/s24237581</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7581</prism:startingPage> <prism:doi>10.3390/s24237581</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7581</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7580"> <title>Sensors, Vol. 24, Pages 7580: A Novel Technique for Monitoring Carbonate and Scale Precipitation Using a Batch-Process-Based Hetero-Core Fiber Optic Sensor</title> <link>https://www.mdpi.com/1424-8220/24/23/7580</link> <description>Techniques for monitoring calcium carbonate and silica deposits (scale) in geothermal power plants and hot spring facilities using fiber optic sensors have already been reported. These sensors continuously measure changes in light transmittance with a detector and, when applied to field tests, require the installation of a power supply and sensor monitoring equipment. However, on some sites, a power supply may not be available, or a specialist skilled in handling scale sensors is required. To overcome this problem, we have developed a method for evaluating scale formation that is based on a batch process that can be used by anyone. In brief, this method involves depositing scale on a section of the optical fiber sensor and then fusing this section to the optical fiber and measuring it. Using this sensor, a technician in the field can simply place the sensor in the desired location, collect the samples at any given time, and send them to the laboratory to measure their transmittance. This simple and easy method was achieved by using a hetero-core type of fiber optic. This evaluation method can measure with the same sensitivity as conventional real-time methods, while its transmittance response for the sensor corresponds to the saturation index (SI) changes in the scale components in the solution due to increases in temperature and concentration. In the field of carbon dioxide capture and storage (CCS), this evaluation method can be used to quantitatively measure the formation of carbonate minerals, and it can also be used as an indicator for determining the conditions for CO2 mineral fixation, as well as in experiments using batch-type autoclaves in laboratory testing. It is also expected to be used in geothermal power plants as a method for evaluating scale formation, such as that of amorphous silica, and to protect against agents that hinder stable operation.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7580: A Novel Technique for Monitoring Carbonate and Scale Precipitation Using a Batch-Process-Based Hetero-Core Fiber Optic Sensor</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7580">doi: 10.3390/s24237580</a></p> <p>Authors: Sakurako Satake Ai Hosoki Hideki Kuramitz Akira Ueda </p> <p>Techniques for monitoring calcium carbonate and silica deposits (scale) in geothermal power plants and hot spring facilities using fiber optic sensors have already been reported. These sensors continuously measure changes in light transmittance with a detector and, when applied to field tests, require the installation of a power supply and sensor monitoring equipment. However, on some sites, a power supply may not be available, or a specialist skilled in handling scale sensors is required. To overcome this problem, we have developed a method for evaluating scale formation that is based on a batch process that can be used by anyone. In brief, this method involves depositing scale on a section of the optical fiber sensor and then fusing this section to the optical fiber and measuring it. Using this sensor, a technician in the field can simply place the sensor in the desired location, collect the samples at any given time, and send them to the laboratory to measure their transmittance. This simple and easy method was achieved by using a hetero-core type of fiber optic. This evaluation method can measure with the same sensitivity as conventional real-time methods, while its transmittance response for the sensor corresponds to the saturation index (SI) changes in the scale components in the solution due to increases in temperature and concentration. In the field of carbon dioxide capture and storage (CCS), this evaluation method can be used to quantitatively measure the formation of carbonate minerals, and it can also be used as an indicator for determining the conditions for CO2 mineral fixation, as well as in experiments using batch-type autoclaves in laboratory testing. It is also expected to be used in geothermal power plants as a method for evaluating scale formation, such as that of amorphous silica, and to protect against agents that hinder stable operation.</p> ]]></content:encoded> <dc:title>A Novel Technique for Monitoring Carbonate and Scale Precipitation Using a Batch-Process-Based Hetero-Core Fiber Optic Sensor</dc:title> <dc:creator>Sakurako Satake</dc:creator> <dc:creator>Ai Hosoki</dc:creator> <dc:creator>Hideki Kuramitz</dc:creator> <dc:creator>Akira Ueda</dc:creator> <dc:identifier>doi: 10.3390/s24237580</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7580</prism:startingPage> <prism:doi>10.3390/s24237580</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7580</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7579"> <title>Sensors, Vol. 24, Pages 7579: Unified Multi-Abstraction-Level Functional Testing and Performance Measurements for Industrial IoT in Spatially Distributed Narrow Band-Wireless Wide Area Networks</title> <link>https://www.mdpi.com/1424-8220/24/23/7579</link> <description>Narrow Band-Wireless Wide Area Networking (NB-WWAN) technologies are becoming more popular across a wide range of application domains due to their ability to provide spatially distributed and reliable wireless connectivity in addition to offering low data rates, low bandwidth, long-range, and long battery life. For functional testing and performance assessments, the wide range of wireless technology alternatives within this category poses several difficulties. At the device level, it is necessary to address issues such as resource limitations, complex protocols, interoperability, and reliability, while at the network level, challenges include complex topologies and wireless channel/signal propagation problems. Testing the functionality and measuring the performance of spatially distributed NB-WWAN systems require a systematic approach to overcome these challenges. Furthermore, to provide a seamless test flow, it is also critical to test and compare the performance of wireless systems systematically and consistently across the different system development phases. To evaluate NB-WWAN technologies comprehensively across multiple abstraction levels&amp;amp;mdash;network simulators, emulated lab testbeds, and field test environments&amp;amp;mdash;we propose a unified multi-abstraction-level testing methodology. A detailed technical description of the prototype implementation and its evaluation is presented in this paper.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7579: Unified Multi-Abstraction-Level Functional Testing and Performance Measurements for Industrial IoT in Spatially Distributed Narrow Band-Wireless Wide Area Networks</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7579">doi: 10.3390/s24237579</a></p> <p>Authors: Jubin Sebastian E Fabian Sowieja Axel Sikora </p> <p>Narrow Band-Wireless Wide Area Networking (NB-WWAN) technologies are becoming more popular across a wide range of application domains due to their ability to provide spatially distributed and reliable wireless connectivity in addition to offering low data rates, low bandwidth, long-range, and long battery life. For functional testing and performance assessments, the wide range of wireless technology alternatives within this category poses several difficulties. At the device level, it is necessary to address issues such as resource limitations, complex protocols, interoperability, and reliability, while at the network level, challenges include complex topologies and wireless channel/signal propagation problems. Testing the functionality and measuring the performance of spatially distributed NB-WWAN systems require a systematic approach to overcome these challenges. Furthermore, to provide a seamless test flow, it is also critical to test and compare the performance of wireless systems systematically and consistently across the different system development phases. To evaluate NB-WWAN technologies comprehensively across multiple abstraction levels&amp;amp;mdash;network simulators, emulated lab testbeds, and field test environments&amp;amp;mdash;we propose a unified multi-abstraction-level testing methodology. A detailed technical description of the prototype implementation and its evaluation is presented in this paper.</p> ]]></content:encoded> <dc:title>Unified Multi-Abstraction-Level Functional Testing and Performance Measurements for Industrial IoT in Spatially Distributed Narrow Band-Wireless Wide Area Networks</dc:title> <dc:creator>Jubin Sebastian E</dc:creator> <dc:creator>Fabian Sowieja</dc:creator> <dc:creator>Axel Sikora</dc:creator> <dc:identifier>doi: 10.3390/s24237579</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7579</prism:startingPage> <prism:doi>10.3390/s24237579</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7579</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7578"> <title>Sensors, Vol. 24, Pages 7578: Enhancing LiDAR Mapping with YOLO-Based Potential Dynamic Object Removal in Autonomous Driving</title> <link>https://www.mdpi.com/1424-8220/24/23/7578</link> <description>In this study, we propose an enhanced LiDAR-based mapping and localization system that utilizes a camera-based YOLO (You Only Look Once) algorithm to detect and remove dynamic objects, such as vehicles, from the mapping process. GPS, while commonly used for localization, often fails in urban environments due to signal blockages. To address this limitation, our system integrates YOLOv4 with LiDAR, enabling the removal of dynamic objects to improve map accuracy and localization in high-traffic areas. Existing methods using LiDAR segmentation for map matching often suffer from missed detections and false positives, degrading performance. Our approach leverages YOLOv4&amp;amp;rsquo;s robust object detection capabilities to eliminate potentially dynamic objects while retaining static environmental features, such as buildings, to enhance map accuracy and reliability. The proposed system was validated using a mid-size SUV equipped with LiDAR and camera sensors. The experimental results demonstrate significant improvements in map-matching and localization performance, particularly in urban environments. The system achieved RMSE (Root Mean Square Error) reductions compared to conventional methods, with RMSE values decreasing from 0.9870 to 0.9724 in open areas and from 1.3874 to 1.1217 in urban areas. These findings highlight the ability of the Vision + LiDAR + NDT method to enhance localization performance in both simple and complex environments. By addressing the challenges of dynamic obstacles, the proposed system effectively improves the accuracy and robustness of autonomous navigation in high-traffic settings without relying on GPS.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7578: Enhancing LiDAR Mapping with YOLO-Based Potential Dynamic Object Removal in Autonomous Driving</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7578">doi: 10.3390/s24237578</a></p> <p>Authors: Seonghark Jeong Heeseok Shin Myeong-Jun Kim Dongwan Kang Seangwock Lee Sangki Oh </p> <p>In this study, we propose an enhanced LiDAR-based mapping and localization system that utilizes a camera-based YOLO (You Only Look Once) algorithm to detect and remove dynamic objects, such as vehicles, from the mapping process. GPS, while commonly used for localization, often fails in urban environments due to signal blockages. To address this limitation, our system integrates YOLOv4 with LiDAR, enabling the removal of dynamic objects to improve map accuracy and localization in high-traffic areas. Existing methods using LiDAR segmentation for map matching often suffer from missed detections and false positives, degrading performance. Our approach leverages YOLOv4&amp;amp;rsquo;s robust object detection capabilities to eliminate potentially dynamic objects while retaining static environmental features, such as buildings, to enhance map accuracy and reliability. The proposed system was validated using a mid-size SUV equipped with LiDAR and camera sensors. The experimental results demonstrate significant improvements in map-matching and localization performance, particularly in urban environments. The system achieved RMSE (Root Mean Square Error) reductions compared to conventional methods, with RMSE values decreasing from 0.9870 to 0.9724 in open areas and from 1.3874 to 1.1217 in urban areas. These findings highlight the ability of the Vision + LiDAR + NDT method to enhance localization performance in both simple and complex environments. By addressing the challenges of dynamic obstacles, the proposed system effectively improves the accuracy and robustness of autonomous navigation in high-traffic settings without relying on GPS.</p> ]]></content:encoded> <dc:title>Enhancing LiDAR Mapping with YOLO-Based Potential Dynamic Object Removal in Autonomous Driving</dc:title> <dc:creator>Seonghark Jeong</dc:creator> <dc:creator>Heeseok Shin</dc:creator> <dc:creator>Myeong-Jun Kim</dc:creator> <dc:creator>Dongwan Kang</dc:creator> <dc:creator>Seangwock Lee</dc:creator> <dc:creator>Sangki Oh</dc:creator> <dc:identifier>doi: 10.3390/s24237578</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7578</prism:startingPage> <prism:doi>10.3390/s24237578</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7578</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7577"> <title>Sensors, Vol. 24, Pages 7577: An Industrial Internet Security Assessment Model Based on a Selectable Confidence Rule Base</title> <link>https://www.mdpi.com/1424-8220/24/23/7577</link> <description>To mitigate the impact of network security on the production environment in the industrial internet, this paper proposes a confidence rule-based security assessment model for the industrial internet that uses selective modeling. First, a definition of selective modeling tailored to the characteristics of the industrial internet is provided. Based on this, the assessment process of the Selectable Belief Rule Base (BRB-s) model is introduced. Then, in combination with the Selection covariance matrix adaptive evolution strategy (S-CMA-ES) algorithm, a parameter optimization method for the BRB-s model is designed, which expands the selective constraints on expert knowledge. This model establishes a better unidirectional selection strategy among different subgroups, and while expanding the selection constraints on expert knowledge, it achieves better evaluation results. This effectively addresses the issue of reduced modeling accuracy caused by insufficient data and poor data quality. Finally, the experiments of different evaluation models on industrial data sets are compared, and good results are obtained, which verify the evaluation accuracy of the industrial Internet network security situation assessment model proposed in this paper and the feasibility and effectiveness of the S-CMA-ES optimization algorithm.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7577: An Industrial Internet Security Assessment Model Based on a Selectable Confidence Rule Base</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7577">doi: 10.3390/s24237577</a></p> <p>Authors: Qingqing Yang Shiming Li Yuhe Wang Guoxing Li Yanbin Yuan </p> <p>To mitigate the impact of network security on the production environment in the industrial internet, this paper proposes a confidence rule-based security assessment model for the industrial internet that uses selective modeling. First, a definition of selective modeling tailored to the characteristics of the industrial internet is provided. Based on this, the assessment process of the Selectable Belief Rule Base (BRB-s) model is introduced. Then, in combination with the Selection covariance matrix adaptive evolution strategy (S-CMA-ES) algorithm, a parameter optimization method for the BRB-s model is designed, which expands the selective constraints on expert knowledge. This model establishes a better unidirectional selection strategy among different subgroups, and while expanding the selection constraints on expert knowledge, it achieves better evaluation results. This effectively addresses the issue of reduced modeling accuracy caused by insufficient data and poor data quality. Finally, the experiments of different evaluation models on industrial data sets are compared, and good results are obtained, which verify the evaluation accuracy of the industrial Internet network security situation assessment model proposed in this paper and the feasibility and effectiveness of the S-CMA-ES optimization algorithm.</p> ]]></content:encoded> <dc:title>An Industrial Internet Security Assessment Model Based on a Selectable Confidence Rule Base</dc:title> <dc:creator>Qingqing Yang</dc:creator> <dc:creator>Shiming Li</dc:creator> <dc:creator>Yuhe Wang</dc:creator> <dc:creator>Guoxing Li</dc:creator> <dc:creator>Yanbin Yuan</dc:creator> <dc:identifier>doi: 10.3390/s24237577</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7577</prism:startingPage> <prism:doi>10.3390/s24237577</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7577</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7575"> <title>Sensors, Vol. 24, Pages 7575: Structural Damage Early Warning Method of Quayside Container Crane Based on Fuzzy Entropy Ratio Variation Deviation</title> <link>https://www.mdpi.com/1424-8220/24/23/7575</link> <description>Real-time monitoring and early warning of structures are essential for assessing structural health and ensuring safety maintenance. To improve the timeliness of early warnings for structural abnormal states in quayside container cranes (QCCs) with incomplete damage data, a structural abnormal state early warning method based on fuzzy entropy ratio variation deviation (FERVD) is proposed. First, monitoring data are subjected to dual-tree complex wavelet transform (DTCWT). The adaptive frequency bands obtained from the decomposition, combined with fuzzy entropy (FE), are used to extract response signal features and construct the FERVD warning indicator. Based on this indicator, dynamic thresholds for early warning are established to differentiate between structural health states and various damage conditions. Secondly, a finite element model of structure for QCCs is developed. By simulating damage at various locations and severities through the stiffness reduction of different elements, a comprehensive structural simulation monitoring dataset is generated. The efficacy of the proposed early warning method is validated through numerical experiments and engineering case studies. The numerical results demonstrate that the proposed method effectively distinguishes between different damage conditions and provides timely warnings for various damage states. Furthermore, engineering case analysis shows that when the structure is in a healthy state, the FERVD values at different monitoring points fluctuate within the threshold range, indicating the applicability of the proposed method in the structural health monitoring (SHM) of QCCs.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7575: Structural Damage Early Warning Method of Quayside Container Crane Based on Fuzzy Entropy Ratio Variation Deviation</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7575">doi: 10.3390/s24237575</a></p> <p>Authors: Jiahui Liu Jian Zhao Dong Zhao Xianrong Qin </p> <p>Real-time monitoring and early warning of structures are essential for assessing structural health and ensuring safety maintenance. To improve the timeliness of early warnings for structural abnormal states in quayside container cranes (QCCs) with incomplete damage data, a structural abnormal state early warning method based on fuzzy entropy ratio variation deviation (FERVD) is proposed. First, monitoring data are subjected to dual-tree complex wavelet transform (DTCWT). The adaptive frequency bands obtained from the decomposition, combined with fuzzy entropy (FE), are used to extract response signal features and construct the FERVD warning indicator. Based on this indicator, dynamic thresholds for early warning are established to differentiate between structural health states and various damage conditions. Secondly, a finite element model of structure for QCCs is developed. By simulating damage at various locations and severities through the stiffness reduction of different elements, a comprehensive structural simulation monitoring dataset is generated. The efficacy of the proposed early warning method is validated through numerical experiments and engineering case studies. The numerical results demonstrate that the proposed method effectively distinguishes between different damage conditions and provides timely warnings for various damage states. Furthermore, engineering case analysis shows that when the structure is in a healthy state, the FERVD values at different monitoring points fluctuate within the threshold range, indicating the applicability of the proposed method in the structural health monitoring (SHM) of QCCs.</p> ]]></content:encoded> <dc:title>Structural Damage Early Warning Method of Quayside Container Crane Based on Fuzzy Entropy Ratio Variation Deviation</dc:title> <dc:creator>Jiahui Liu</dc:creator> <dc:creator>Jian Zhao</dc:creator> <dc:creator>Dong Zhao</dc:creator> <dc:creator>Xianrong Qin</dc:creator> <dc:identifier>doi: 10.3390/s24237575</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7575</prism:startingPage> <prism:doi>10.3390/s24237575</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7575</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7576"> <title>Sensors, Vol. 24, Pages 7576: Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI</title> <link>https://www.mdpi.com/1424-8220/24/23/7576</link> <description>Early detection and precise characterization of brain tumors play a crucial role in improving patient outcomes and extending survival rates. Among neuroimaging modalities, magnetic resonance imaging (MRI) is the gold standard for brain tumor diagnostics due to its ability to produce high-contrast images across a variety of sequences, each highlighting distinct tissue characteristics. This study focuses on enabling multimodal MRI sequences to advance the automatic segmentation of low-grade astrocytomas, a challenging task due to their diffuse and irregular growth patterns. A novel mutual-attention deep learning framework is proposed, which integrates complementary information from multiple MRI sequences, including T2-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, to enhance the segmentation accuracy. Unlike conventional segmentation models, which treat each modality independently or simply concatenate them, our model introduces mutual attention mechanisms. This allows the network to dynamically focus on salient features across modalities by jointly learning interdependencies between imaging sequences, leading to more precise boundary delineations even in regions with subtle tumor signals. The proposed method is validated using the UCSF-PDGM dataset, which consists of 35 astrocytoma cases, presenting a realistic and clinically challenging dataset. The results demonstrate that T2w/FLAIR modalities contribute most significantly to the segmentation performance. The mutual-attention model achieves an average Dice coefficient of 0.87. This study provides an innovative pathway toward improving segmentation of low-grade tumors by enabling context-aware fusion across imaging sequences. Furthermore, the study showcases the clinical relevance of integrating AI with multimodal MRI, potentially improving non-invasive tumor characterization and guiding future research in radiological diagnostics.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7576: Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7576">doi: 10.3390/s24237576</a></p> <p>Authors: Hiroyuki Seshimo Essam A. Rashed </p> <p>Early detection and precise characterization of brain tumors play a crucial role in improving patient outcomes and extending survival rates. Among neuroimaging modalities, magnetic resonance imaging (MRI) is the gold standard for brain tumor diagnostics due to its ability to produce high-contrast images across a variety of sequences, each highlighting distinct tissue characteristics. This study focuses on enabling multimodal MRI sequences to advance the automatic segmentation of low-grade astrocytomas, a challenging task due to their diffuse and irregular growth patterns. A novel mutual-attention deep learning framework is proposed, which integrates complementary information from multiple MRI sequences, including T2-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, to enhance the segmentation accuracy. Unlike conventional segmentation models, which treat each modality independently or simply concatenate them, our model introduces mutual attention mechanisms. This allows the network to dynamically focus on salient features across modalities by jointly learning interdependencies between imaging sequences, leading to more precise boundary delineations even in regions with subtle tumor signals. The proposed method is validated using the UCSF-PDGM dataset, which consists of 35 astrocytoma cases, presenting a realistic and clinically challenging dataset. The results demonstrate that T2w/FLAIR modalities contribute most significantly to the segmentation performance. The mutual-attention model achieves an average Dice coefficient of 0.87. This study provides an innovative pathway toward improving segmentation of low-grade tumors by enabling context-aware fusion across imaging sequences. Furthermore, the study showcases the clinical relevance of integrating AI with multimodal MRI, potentially improving non-invasive tumor characterization and guiding future research in radiological diagnostics.</p> ]]></content:encoded> <dc:title>Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI</dc:title> <dc:creator>Hiroyuki Seshimo</dc:creator> <dc:creator>Essam A. Rashed</dc:creator> <dc:identifier>doi: 10.3390/s24237576</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7576</prism:startingPage> <prism:doi>10.3390/s24237576</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7576</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7574"> <title>Sensors, Vol. 24, Pages 7574: Digital Twin for a Frequency Mixer Used as a Phase Sensor</title> <link>https://www.mdpi.com/1424-8220/24/23/7574</link> <description>The Portuguese Institute for Quality is responsible for the realization and dissemination of the frequency standard in Portugal. There are several techniques for frequency transfer, but we use a frequency mixer to detect phase variations between two light signals with different wavelengths, traveling along an optical fibre. In this paper, we present the development of a digital twin (DT) that replicates the use of a frequency mixer to improve the frequency transfer problem. A setup was built to train and validate the technique: a frequency mixer was used to determine the phase difference between the two signals, which are caused by temperature gradients in the fibre, together with real-time temperature data from sensors placed along the fibre and on the mixer itself. The DT was trained with two machine learning algorithms, in particular, ARIMA and LSTM networks. To estimate the accuracy of the frequency mixer working as a phasemeter, several sources of uncertainty were considered and included in the DT model, with the goal of obtaining a phase value measurement and its uncertainty in real time. The JCGM 100:2008 and JCGM 101:2008 approaches were used for the estimation of the uncertainty budget. With this work, we merge DT technology with a frequency mixer used for phase detection to provide its value and uncertainty in real time.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7574: Digital Twin for a Frequency Mixer Used as a Phase Sensor</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7574">doi: 10.3390/s24237574</a></p> <p>Authors: Carlos Pires Manuel Abreu Isabel Godinho Rui Agostinho Jo茫o A. Sousa </p> <p>The Portuguese Institute for Quality is responsible for the realization and dissemination of the frequency standard in Portugal. There are several techniques for frequency transfer, but we use a frequency mixer to detect phase variations between two light signals with different wavelengths, traveling along an optical fibre. In this paper, we present the development of a digital twin (DT) that replicates the use of a frequency mixer to improve the frequency transfer problem. A setup was built to train and validate the technique: a frequency mixer was used to determine the phase difference between the two signals, which are caused by temperature gradients in the fibre, together with real-time temperature data from sensors placed along the fibre and on the mixer itself. The DT was trained with two machine learning algorithms, in particular, ARIMA and LSTM networks. To estimate the accuracy of the frequency mixer working as a phasemeter, several sources of uncertainty were considered and included in the DT model, with the goal of obtaining a phase value measurement and its uncertainty in real time. The JCGM 100:2008 and JCGM 101:2008 approaches were used for the estimation of the uncertainty budget. With this work, we merge DT technology with a frequency mixer used for phase detection to provide its value and uncertainty in real time.</p> ]]></content:encoded> <dc:title>Digital Twin for a Frequency Mixer Used as a Phase Sensor</dc:title> <dc:creator>Carlos Pires</dc:creator> <dc:creator>Manuel Abreu</dc:creator> <dc:creator>Isabel Godinho</dc:creator> <dc:creator>Rui Agostinho</dc:creator> <dc:creator>Jo茫o A. Sousa</dc:creator> <dc:identifier>doi: 10.3390/s24237574</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7574</prism:startingPage> <prism:doi>10.3390/s24237574</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7574</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7573"> <title>Sensors, Vol. 24, Pages 7573: Dynamic Response of Masonry Structures to Temperature Variations: Experimental Investigation of a Brick Masonry Wall</title> <link>https://www.mdpi.com/1424-8220/24/23/7573</link> <description>Structural health monitoring (SHM) is essential for preserving historical and modern infrastructure by tracking dynamic properties such as frequencies and mode shapes. Changes in these properties can indicate structural damage, but environmental factors like temperature can also cause similar variations, complicating damage detection. This study investigates from an experimental point of view the effect of temperature on the dynamic behaviour of masonry structures, focusing on a masonry wall subjected to thermal load variations within operational conditions. The experimental setup involved a masonry wall specimen tested at the Structural Laboratory of the University of Minho, Portugal. The mock-up was subjected to various boundary conditions and loading scenarios. The results showed that the natural frequencies of the masonry wall can be significantly influenced by temperature changes, variations strictly related to the boundary conditions and the stress acting on the mock-up. In contrast, mode shapes seem not to be affected by temperature variations. This study provides valuable insights into the temperature-induced variations in the dynamic properties of masonry structures, emphasising the need to consider environmental effects in SHM applications. By filtering out these environmental influences, more accurate damage detection and proactive maintenance strategies can be developed, enhancing the safety and longevity of both historical and modern structures.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7573: Dynamic Response of Masonry Structures to Temperature Variations: Experimental Investigation of a Brick Masonry Wall</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7573">doi: 10.3390/s24237573</a></p> <p>Authors: Daniele Pellegrini Alberto Barontini Nuno Mendes Paulo B. Louren莽o </p> <p>Structural health monitoring (SHM) is essential for preserving historical and modern infrastructure by tracking dynamic properties such as frequencies and mode shapes. Changes in these properties can indicate structural damage, but environmental factors like temperature can also cause similar variations, complicating damage detection. This study investigates from an experimental point of view the effect of temperature on the dynamic behaviour of masonry structures, focusing on a masonry wall subjected to thermal load variations within operational conditions. The experimental setup involved a masonry wall specimen tested at the Structural Laboratory of the University of Minho, Portugal. The mock-up was subjected to various boundary conditions and loading scenarios. The results showed that the natural frequencies of the masonry wall can be significantly influenced by temperature changes, variations strictly related to the boundary conditions and the stress acting on the mock-up. In contrast, mode shapes seem not to be affected by temperature variations. This study provides valuable insights into the temperature-induced variations in the dynamic properties of masonry structures, emphasising the need to consider environmental effects in SHM applications. By filtering out these environmental influences, more accurate damage detection and proactive maintenance strategies can be developed, enhancing the safety and longevity of both historical and modern structures.</p> ]]></content:encoded> <dc:title>Dynamic Response of Masonry Structures to Temperature Variations: Experimental Investigation of a Brick Masonry Wall</dc:title> <dc:creator>Daniele Pellegrini</dc:creator> <dc:creator>Alberto Barontini</dc:creator> <dc:creator>Nuno Mendes</dc:creator> <dc:creator>Paulo B. Louren莽o</dc:creator> <dc:identifier>doi: 10.3390/s24237573</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7573</prism:startingPage> <prism:doi>10.3390/s24237573</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7573</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7571"> <title>Sensors, Vol. 24, Pages 7571: A Dynamic Load Modulation Power Amplifier with Ferroelectric-Based Tunable Matching Network</title> <link>https://www.mdpi.com/1424-8220/24/23/7571</link> <description>Power amplifiers are crucial components that significantly influence the linearity and energy efficiency of next-generation communication system radio units. A key challenge in designing power amplifiers is managing high peak-to-average power ratio (PAPR) in order to achieve both high linearity and energy efficiency during back-off conditions. This paper presents simulation and measurement results for a dynamic load modulation power amplifier based on a ferroelectric tunable matching network to operate at 2.5 GHz. Experimental studies on a power amplifier with the tunable output matching network confirm its performance at 8 dB back-off while varying the control voltage applied to the ferroelectric element. Additionally, a bias modulator to adjust the transistor&amp;amp;rsquo;s load in relation to input power was designed. Measurement studies of the dynamic load modulation power amplifier have demonstrated an efficiency of at least 50% at 8 dB back-off and more than 60% at peak power at 2.5 GHz. Furthermore, it was found that the modulator output voltage adjustment function on input power of the bias modulator affects the linearity of the output power. Different bias responses were studied and, as a result, the optimal output voltage response was found. The proposed load modulation power amplifier is promising for operation with high PAPR digital signals.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7571: A Dynamic Load Modulation Power Amplifier with Ferroelectric-Based Tunable Matching Network</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7571">doi: 10.3390/s24237571</a></p> <p>Authors: Pavel Turalchuk Irina Filipiuk Bayazet Iskakov </p> <p>Power amplifiers are crucial components that significantly influence the linearity and energy efficiency of next-generation communication system radio units. A key challenge in designing power amplifiers is managing high peak-to-average power ratio (PAPR) in order to achieve both high linearity and energy efficiency during back-off conditions. This paper presents simulation and measurement results for a dynamic load modulation power amplifier based on a ferroelectric tunable matching network to operate at 2.5 GHz. Experimental studies on a power amplifier with the tunable output matching network confirm its performance at 8 dB back-off while varying the control voltage applied to the ferroelectric element. Additionally, a bias modulator to adjust the transistor&amp;amp;rsquo;s load in relation to input power was designed. Measurement studies of the dynamic load modulation power amplifier have demonstrated an efficiency of at least 50% at 8 dB back-off and more than 60% at peak power at 2.5 GHz. Furthermore, it was found that the modulator output voltage adjustment function on input power of the bias modulator affects the linearity of the output power. Different bias responses were studied and, as a result, the optimal output voltage response was found. The proposed load modulation power amplifier is promising for operation with high PAPR digital signals.</p> ]]></content:encoded> <dc:title>A Dynamic Load Modulation Power Amplifier with Ferroelectric-Based Tunable Matching Network</dc:title> <dc:creator>Pavel Turalchuk</dc:creator> <dc:creator>Irina Filipiuk</dc:creator> <dc:creator>Bayazet Iskakov</dc:creator> <dc:identifier>doi: 10.3390/s24237571</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Communication</prism:section> <prism:startingPage>7571</prism:startingPage> <prism:doi>10.3390/s24237571</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7571</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7572"> <title>Sensors, Vol. 24, Pages 7572: Performance Analysis of Cardioid and Omnidirectional Microphones in Spherical Sector Arrays for Coherent Source Localization</title> <link>https://www.mdpi.com/1424-8220/24/23/7572</link> <description>Traditional spherical sector microphone arrays using omnidirectional microphones face limitations in modal strength and spatial resolution, especially within spherical sector configurations. This study aims to enhance array performance by developing a spherical sector array employing first-order cardioid microphones. A model based on spherical sector harmonic (SSH) functions is introduced to extend the benefits of spherical harmonics to sector arrays. Modal strength analysis demonstrates that cardioid microphones in open spherical sectors enhance nonzero-order strengths and eliminate the nulls associated with spherical Bessel functions. We find that the spatial resolution of spherical cap arrays depends on the array&amp;amp;rsquo;s maximum order and the limiting polar angle, but is independent of the microphone gain pattern. We assess direction-of-arrival (DOA) estimation performance for coherent wideband sources using the array manifold interpolation method, and compare cardioid and omnidirectional arrays through simulations in both open and rigid hemispherical configurations. The results indicate that cardioid arrays outperform omnidirectional ones on DOA estimation tasks, with performance improving alongside increased microphone directivity in the open hemispherical configuration. Specifically, hypercardioid microphones yielded the best results in the open configuration, while subcardioid microphones (without nulls) were optimal in rigid configurations. These findings demonstrate that spherical sector arrays of first-order cardioid microphones offer improved modal strength and DOA estimation capabilities over traditional omnidirectional arrays, providing significantly enhancing performance in spherical sector array processing.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7572: Performance Analysis of Cardioid and Omnidirectional Microphones in Spherical Sector Arrays for Coherent Source Localization</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7572">doi: 10.3390/s24237572</a></p> <p>Authors: Chibuzo Joseph Nnonyelu Meng Jiang Marianthi Adamopoulou Jan Lundgren </p> <p>Traditional spherical sector microphone arrays using omnidirectional microphones face limitations in modal strength and spatial resolution, especially within spherical sector configurations. This study aims to enhance array performance by developing a spherical sector array employing first-order cardioid microphones. A model based on spherical sector harmonic (SSH) functions is introduced to extend the benefits of spherical harmonics to sector arrays. Modal strength analysis demonstrates that cardioid microphones in open spherical sectors enhance nonzero-order strengths and eliminate the nulls associated with spherical Bessel functions. We find that the spatial resolution of spherical cap arrays depends on the array&amp;amp;rsquo;s maximum order and the limiting polar angle, but is independent of the microphone gain pattern. We assess direction-of-arrival (DOA) estimation performance for coherent wideband sources using the array manifold interpolation method, and compare cardioid and omnidirectional arrays through simulations in both open and rigid hemispherical configurations. The results indicate that cardioid arrays outperform omnidirectional ones on DOA estimation tasks, with performance improving alongside increased microphone directivity in the open hemispherical configuration. Specifically, hypercardioid microphones yielded the best results in the open configuration, while subcardioid microphones (without nulls) were optimal in rigid configurations. These findings demonstrate that spherical sector arrays of first-order cardioid microphones offer improved modal strength and DOA estimation capabilities over traditional omnidirectional arrays, providing significantly enhancing performance in spherical sector array processing.</p> ]]></content:encoded> <dc:title>Performance Analysis of Cardioid and Omnidirectional Microphones in Spherical Sector Arrays for Coherent Source Localization</dc:title> <dc:creator>Chibuzo Joseph Nnonyelu</dc:creator> <dc:creator>Meng Jiang</dc:creator> <dc:creator>Marianthi Adamopoulou</dc:creator> <dc:creator>Jan Lundgren</dc:creator> <dc:identifier>doi: 10.3390/s24237572</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7572</prism:startingPage> <prism:doi>10.3390/s24237572</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7572</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7569"> <title>Sensors, Vol. 24, Pages 7569: CASSAD: Chroma-Augmented Semi-Supervised Anomaly Detection for Conveyor Belt Idlers</title> <link>https://www.mdpi.com/1424-8220/24/23/7569</link> <description>Idlers are essential to conveyor systems, as well as supporting and guiding belts to ensure production efficiency. Proper idler maintenance prevents failures, reduces downtime, cuts costs, and improves reliability. Most studies on idler fault detection rely on supervised methods, which depend on large labelled datasets for training. However, acquiring such labelled data is often challenging in industrial environments due to the rarity of faults and the labour-intensive nature of the labelling process. To address this, we propose the chroma-augmented semi-supervised anomaly detection (CASSAD) method, designed to perform effectively with limited labelled data. At the core of CASSAD is the one-class SVM (OC-SVM), a model specifically developed for anomaly detection in cases where labelled anomalies are scarce. We also compare CASSAD&amp;amp;rsquo;s performance with other common models like the local outlier factor (LOF) and isolation forest (iForest), evaluating each with the area under the curve (AUC) to assess their ability to distinguish between normal and anomalous data. CASSAD introduces chroma features, such as chroma energy normalised statistics (CENS), the constant-Q transform (CQT), and the chroma short-time Fourier transform (STFT), enhanced through filtering to capture rich harmonic information from idler sounds. To reduce feature complexity, we utilize the mean and standard deviation (std) across chroma features. The dataset is further augmented using additive white Gaussian noise (AWGN). Testing on an industrial dataset of idler sounds, CASSAD achieved an AUC of 96% and an accuracy of 91%, surpassing a baseline autoencoder and other traditional models. These results demonstrate the model&amp;amp;rsquo;s robustness in detecting anomalies with minimal dependence on labelled data, offering a practical solution for industries with limited labelled datasets.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7569: CASSAD: Chroma-Augmented Semi-Supervised Anomaly Detection for Conveyor Belt Idlers</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7569">doi: 10.3390/s24237569</a></p> <p>Authors: Fahad Alharbi Suhuai Luo Abdullah Alsaedi Sipei Zhao Guang Yang </p> <p>Idlers are essential to conveyor systems, as well as supporting and guiding belts to ensure production efficiency. Proper idler maintenance prevents failures, reduces downtime, cuts costs, and improves reliability. Most studies on idler fault detection rely on supervised methods, which depend on large labelled datasets for training. However, acquiring such labelled data is often challenging in industrial environments due to the rarity of faults and the labour-intensive nature of the labelling process. To address this, we propose the chroma-augmented semi-supervised anomaly detection (CASSAD) method, designed to perform effectively with limited labelled data. At the core of CASSAD is the one-class SVM (OC-SVM), a model specifically developed for anomaly detection in cases where labelled anomalies are scarce. We also compare CASSAD&amp;amp;rsquo;s performance with other common models like the local outlier factor (LOF) and isolation forest (iForest), evaluating each with the area under the curve (AUC) to assess their ability to distinguish between normal and anomalous data. CASSAD introduces chroma features, such as chroma energy normalised statistics (CENS), the constant-Q transform (CQT), and the chroma short-time Fourier transform (STFT), enhanced through filtering to capture rich harmonic information from idler sounds. To reduce feature complexity, we utilize the mean and standard deviation (std) across chroma features. The dataset is further augmented using additive white Gaussian noise (AWGN). Testing on an industrial dataset of idler sounds, CASSAD achieved an AUC of 96% and an accuracy of 91%, surpassing a baseline autoencoder and other traditional models. These results demonstrate the model&amp;amp;rsquo;s robustness in detecting anomalies with minimal dependence on labelled data, offering a practical solution for industries with limited labelled datasets.</p> ]]></content:encoded> <dc:title>CASSAD: Chroma-Augmented Semi-Supervised Anomaly Detection for Conveyor Belt Idlers</dc:title> <dc:creator>Fahad Alharbi</dc:creator> <dc:creator>Suhuai Luo</dc:creator> <dc:creator>Abdullah Alsaedi</dc:creator> <dc:creator>Sipei Zhao</dc:creator> <dc:creator>Guang Yang</dc:creator> <dc:identifier>doi: 10.3390/s24237569</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7569</prism:startingPage> <prism:doi>10.3390/s24237569</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7569</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7568"> <title>Sensors, Vol. 24, Pages 7568: Ultrasound Versus Elastography in the Diagnosis of Hepatic Steatosis: Evaluation of Traditional Machine Learning Versus Deep Learning</title> <link>https://www.mdpi.com/1424-8220/24/23/7568</link> <description>The prevalence of fatty liver disease is on the rise, posing a significant global health concern. If left untreated, it can progress into more serious liver diseases. Therefore, accurately diagnosing the condition at an early stage is essential for more effective intervention and management. This study uses images acquired via ultrasound and elastography to classify liver steatosis using classical machine learning classifiers, including random forest and support vector machine, as well as deep learning architectures, such as ResNet50V2 and DenseNet-201. The neural network demonstrated the most optimal performance, achieving an F1 score of 99.5% on the ultrasound dataset, 99.2% on the elastography dataset, and 98.9% on the mixed dataset. The results from the deep learning approach are comparable to those of machine learning, despite objectively not achieving the highest results. This research offers valuable insights into the domain of medical image classification and advocates the integration of advanced machine learning and deep learning technologies in diagnosing steatosis.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7568: Ultrasound Versus Elastography in the Diagnosis of Hepatic Steatosis: Evaluation of Traditional Machine Learning Versus Deep Learning</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7568">doi: 10.3390/s24237568</a></p> <p>Authors: Rodrigo Marques Jaime Santos Alexandra Andr茅 Jos茅 Silva </p> <p>The prevalence of fatty liver disease is on the rise, posing a significant global health concern. If left untreated, it can progress into more serious liver diseases. Therefore, accurately diagnosing the condition at an early stage is essential for more effective intervention and management. This study uses images acquired via ultrasound and elastography to classify liver steatosis using classical machine learning classifiers, including random forest and support vector machine, as well as deep learning architectures, such as ResNet50V2 and DenseNet-201. The neural network demonstrated the most optimal performance, achieving an F1 score of 99.5% on the ultrasound dataset, 99.2% on the elastography dataset, and 98.9% on the mixed dataset. The results from the deep learning approach are comparable to those of machine learning, despite objectively not achieving the highest results. This research offers valuable insights into the domain of medical image classification and advocates the integration of advanced machine learning and deep learning technologies in diagnosing steatosis.</p> ]]></content:encoded> <dc:title>Ultrasound Versus Elastography in the Diagnosis of Hepatic Steatosis: Evaluation of Traditional Machine Learning Versus Deep Learning</dc:title> <dc:creator>Rodrigo Marques</dc:creator> <dc:creator>Jaime Santos</dc:creator> <dc:creator>Alexandra Andr茅</dc:creator> <dc:creator>Jos茅 Silva</dc:creator> <dc:identifier>doi: 10.3390/s24237568</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7568</prism:startingPage> <prism:doi>10.3390/s24237568</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7568</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7570"> <title>Sensors, Vol. 24, Pages 7570: Electrical Bioimpedance-Based Monitoring of Intracochlear Tissue Changes After Cochlear Implantation</title> <link>https://www.mdpi.com/1424-8220/24/23/7570</link> <description>Background: This study examined electrical bioimpedance as a biomarker for intracochlear tissue changes after cochlear implant surgery, comparing monopolar, three-point, and four-point impedance measurements over time and evaluating different measurement systems and approaches. Methods: Impedance measurements were obtained from 21 participants during surgery and at four postoperative stages. Monopolar impedances were recorded using the Bionic Ear Data Collection System (BEDCS) and the Active Insertion Monitoring (AIM) system. Three- and four-point impedances were recorded directly using BEDCS, and indirect three-point impedances were additionally derived from Electrical Field Imaging matrices recorded using BEDCS or AIM. Results: There was an 11% relative error between monopolar measurements from BEDCS and AIM and a 25% discrepancy between direct and indirect three-point measurements. Despite this, direct and indirect measurements from both systems were useful for tracking postoperative impedance shifts. Three- and four-point measurements showed a strong relationship both during and after surgery. Our results suggest that three- and four-point measurements are more specific than monopolar impedances in capturing localized tissue changes. Conclusions: Three- and four-point impedance measurements are potential markers of intracochlear tissue changes over time. While direct three-point impedance measurements offer higher accuracy, indirect measurements provide a feasible alternative for monitoring intracochlear changes in clinical settings lacking the option of direct measurements.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7570: Electrical Bioimpedance-Based Monitoring of Intracochlear Tissue Changes After Cochlear Implantation</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7570">doi: 10.3390/s24237570</a></p> <p>Authors: Leanne Sijgers Marlies Geys Gunnar Geissler Patrick Boyle Alexander Huber Flurin Pfiffner </p> <p>Background: This study examined electrical bioimpedance as a biomarker for intracochlear tissue changes after cochlear implant surgery, comparing monopolar, three-point, and four-point impedance measurements over time and evaluating different measurement systems and approaches. Methods: Impedance measurements were obtained from 21 participants during surgery and at four postoperative stages. Monopolar impedances were recorded using the Bionic Ear Data Collection System (BEDCS) and the Active Insertion Monitoring (AIM) system. Three- and four-point impedances were recorded directly using BEDCS, and indirect three-point impedances were additionally derived from Electrical Field Imaging matrices recorded using BEDCS or AIM. Results: There was an 11% relative error between monopolar measurements from BEDCS and AIM and a 25% discrepancy between direct and indirect three-point measurements. Despite this, direct and indirect measurements from both systems were useful for tracking postoperative impedance shifts. Three- and four-point measurements showed a strong relationship both during and after surgery. Our results suggest that three- and four-point measurements are more specific than monopolar impedances in capturing localized tissue changes. Conclusions: Three- and four-point impedance measurements are potential markers of intracochlear tissue changes over time. While direct three-point impedance measurements offer higher accuracy, indirect measurements provide a feasible alternative for monitoring intracochlear changes in clinical settings lacking the option of direct measurements.</p> ]]></content:encoded> <dc:title>Electrical Bioimpedance-Based Monitoring of Intracochlear Tissue Changes After Cochlear Implantation</dc:title> <dc:creator>Leanne Sijgers</dc:creator> <dc:creator>Marlies Geys</dc:creator> <dc:creator>Gunnar Geissler</dc:creator> <dc:creator>Patrick Boyle</dc:creator> <dc:creator>Alexander Huber</dc:creator> <dc:creator>Flurin Pfiffner</dc:creator> <dc:identifier>doi: 10.3390/s24237570</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7570</prism:startingPage> <prism:doi>10.3390/s24237570</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7570</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7567"> <title>Sensors, Vol. 24, Pages 7567: RF Energy Harvesting and Wireless Power Transfer for IoT</title> <link>https://www.mdpi.com/1424-8220/24/23/7567</link> <description>The rapid proliferation of the Internet of Things (IoT) has transformed modern living by interconnecting billions of devices across industrial, commercial, and domestic sectors [...]</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7567: RF Energy Harvesting and Wireless Power Transfer for IoT</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7567">doi: 10.3390/s24237567</a></p> <p>Authors: Onel Luis Alcaraz L贸pez Katsuya Suto </p> <p>The rapid proliferation of the Internet of Things (IoT) has transformed modern living by interconnecting billions of devices across industrial, commercial, and domestic sectors [...]</p> ]]></content:encoded> <dc:title>RF Energy Harvesting and Wireless Power Transfer for IoT</dc:title> <dc:creator>Onel Luis Alcaraz L贸pez</dc:creator> <dc:creator>Katsuya Suto</dc:creator> <dc:identifier>doi: 10.3390/s24237567</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Editorial</prism:section> <prism:startingPage>7567</prism:startingPage> <prism:doi>10.3390/s24237567</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7567</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7566"> <title>Sensors, Vol. 24, Pages 7566: Activities of Daily Living Object Dataset: Advancing Assistive Robotic Manipulation with a Tailored Dataset</title> <link>https://www.mdpi.com/1424-8220/24/23/7566</link> <description>The increasing number of individuals with disabilities&amp;amp;mdash;over 61 million adults in the United States alone&amp;amp;mdash;underscores the urgent need for technologies that enhance autonomy and independence. Among these individuals, millions rely on wheelchairs and often require assistance from another person with activities of daily living (ADLs), such as eating, grooming, and dressing. Wheelchair-mounted assistive robotic arms offer a promising solution to enhance independence, but their complex control interfaces can be challenging for users. Automating control through deep learning-based object detection models presents a viable pathway to simplify operation, yet progress is impeded by the absence of specialized datasets tailored for ADL objects suitable for robotic manipulation in home environments. To bridge this gap, we present a novel ADL object dataset explicitly designed for training deep learning models in assistive robotic applications. We curated over 112,000 high-quality images from four major open-source datasets&amp;amp;mdash;COCO, Open Images, LVIS, and Roboflow Universe&amp;amp;mdash;focusing on objects pertinent to daily living tasks. Annotations were standardized to the YOLO Darknet format, and data quality was enhanced through a rigorous filtering process involving a pre-trained YOLOv5x model and manual validation. Our dataset provides a valuable resource that facilitates the development of more effective and user-friendly semi-autonomous control systems for assistive robots. By offering a focused collection of ADL-related objects, we aim to advance assistive technologies that empower individuals with mobility impairments, addressing a pressing societal need and laying the foundation for future innovations in human&amp;amp;ndash;robot interaction within home settings.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7566: Activities of Daily Living Object Dataset: Advancing Assistive Robotic Manipulation with a Tailored Dataset</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7566">doi: 10.3390/s24237566</a></p> <p>Authors: Md Tanzil Shahria Mohammad H. Rahman </p> <p>The increasing number of individuals with disabilities&amp;amp;mdash;over 61 million adults in the United States alone&amp;amp;mdash;underscores the urgent need for technologies that enhance autonomy and independence. Among these individuals, millions rely on wheelchairs and often require assistance from another person with activities of daily living (ADLs), such as eating, grooming, and dressing. Wheelchair-mounted assistive robotic arms offer a promising solution to enhance independence, but their complex control interfaces can be challenging for users. Automating control through deep learning-based object detection models presents a viable pathway to simplify operation, yet progress is impeded by the absence of specialized datasets tailored for ADL objects suitable for robotic manipulation in home environments. To bridge this gap, we present a novel ADL object dataset explicitly designed for training deep learning models in assistive robotic applications. We curated over 112,000 high-quality images from four major open-source datasets&amp;amp;mdash;COCO, Open Images, LVIS, and Roboflow Universe&amp;amp;mdash;focusing on objects pertinent to daily living tasks. Annotations were standardized to the YOLO Darknet format, and data quality was enhanced through a rigorous filtering process involving a pre-trained YOLOv5x model and manual validation. Our dataset provides a valuable resource that facilitates the development of more effective and user-friendly semi-autonomous control systems for assistive robots. By offering a focused collection of ADL-related objects, we aim to advance assistive technologies that empower individuals with mobility impairments, addressing a pressing societal need and laying the foundation for future innovations in human&amp;amp;ndash;robot interaction within home settings.</p> ]]></content:encoded> <dc:title>Activities of Daily Living Object Dataset: Advancing Assistive Robotic Manipulation with a Tailored Dataset</dc:title> <dc:creator>Md Tanzil Shahria</dc:creator> <dc:creator>Mohammad H. Rahman</dc:creator> <dc:identifier>doi: 10.3390/s24237566</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7566</prism:startingPage> <prism:doi>10.3390/s24237566</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7566</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7565"> <title>Sensors, Vol. 24, Pages 7565: Age-Related Differences in Cardiovascular and Cerebrovascular Responses During the Head-Up Tilt Test: An Exploratory Study Using Continuous Biosignal Data</title> <link>https://www.mdpi.com/1424-8220/24/23/7565</link> <description>The head-up tilt (HUT) test assesses both cardiovascular autonomic regulation and cerebral autoregulation. This exploratory study examined age-related changes in cardiovascular and cerebrovascular responses during the HUT test in three healthy cohorts (young, middle-aged, and elderly). We recruited 2342 neurologist-diagnosed &amp;amp;lsquo;normal&amp;amp;rsquo; individuals from 18 June 2014 to 25 February 2022. Cerebrovascular and cardiovascular responses were assessed during the HUT test, including cerebral blood flow velocity (CBFv) of the middle cerebral artery, systolic arterial pressure (SYS), diastolic arterial pressure (DIA), mean arterial pressure (MAP), pulse pressure (PP), heart rate (HR), stroke volume (SV), cardiac output (CO), and cerebrovascular conductance (CVCi). These variables were analyzed across three groups (young, middle-aged, and elderly) and three periods (resting, post-HUT, and recovery). Participants were stratified into three age groups: young (18&amp;amp;ndash;45 years; n = 384), middle-aged (46&amp;amp;ndash;59 years; n = 434), and elderly (&amp;amp;ge;60 years; n = 590). PP increased significantly with age, while CBFv and CVCi decreased significantly across the three periods. As measurements progressed, DIA and HR increased, and SV, CBFv, and CVCi decreased. This study enhances our understanding of age-related differences in cardiovascular and cerebrovascular responses to the HUT test. These insights may improve the clinical utility of the HUT test and guide outcome analysis across age groups.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7565: Age-Related Differences in Cardiovascular and Cerebrovascular Responses During the Head-Up Tilt Test: An Exploratory Study Using Continuous Biosignal Data</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7565">doi: 10.3390/s24237565</a></p> <p>Authors: Catherine Park Ji Man Hong </p> <p>The head-up tilt (HUT) test assesses both cardiovascular autonomic regulation and cerebral autoregulation. This exploratory study examined age-related changes in cardiovascular and cerebrovascular responses during the HUT test in three healthy cohorts (young, middle-aged, and elderly). We recruited 2342 neurologist-diagnosed &amp;amp;lsquo;normal&amp;amp;rsquo; individuals from 18 June 2014 to 25 February 2022. Cerebrovascular and cardiovascular responses were assessed during the HUT test, including cerebral blood flow velocity (CBFv) of the middle cerebral artery, systolic arterial pressure (SYS), diastolic arterial pressure (DIA), mean arterial pressure (MAP), pulse pressure (PP), heart rate (HR), stroke volume (SV), cardiac output (CO), and cerebrovascular conductance (CVCi). These variables were analyzed across three groups (young, middle-aged, and elderly) and three periods (resting, post-HUT, and recovery). Participants were stratified into three age groups: young (18&amp;amp;ndash;45 years; n = 384), middle-aged (46&amp;amp;ndash;59 years; n = 434), and elderly (&amp;amp;ge;60 years; n = 590). PP increased significantly with age, while CBFv and CVCi decreased significantly across the three periods. As measurements progressed, DIA and HR increased, and SV, CBFv, and CVCi decreased. This study enhances our understanding of age-related differences in cardiovascular and cerebrovascular responses to the HUT test. These insights may improve the clinical utility of the HUT test and guide outcome analysis across age groups.</p> ]]></content:encoded> <dc:title>Age-Related Differences in Cardiovascular and Cerebrovascular Responses During the Head-Up Tilt Test: An Exploratory Study Using Continuous Biosignal Data</dc:title> <dc:creator>Catherine Park</dc:creator> <dc:creator>Ji Man Hong</dc:creator> <dc:identifier>doi: 10.3390/s24237565</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7565</prism:startingPage> <prism:doi>10.3390/s24237565</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7565</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7564"> <title>Sensors, Vol. 24, Pages 7564: Fractional Fourier Transform-Based Signal Separation for Ultrasonic Guided Wave Inspection of Plates</title> <link>https://www.mdpi.com/1424-8220/24/23/7564</link> <description>Detecting defects in plates is crucial across various industries due to safety risks. While ultrasonic bulk waves offer point-by-point inspections, they are time-consuming and limited in coverage. In contrast, guided waves enable the rapid inspection of larger areas. Array transducers are typically used for more efficient coverage, but conventional excitation methods require sufficient time delays between the excitation of array elements that prolong inspection time, necessitating data acquisition time optimization. Reducing time delays can lead to signal overlapping, complicating signal separation. Conventional frequency domain or time-domain filtering methods often yield unsatisfactory separation results due to the signal overlapping in both domains. This study focuses on the application of the Fractional Fourier Transform (FrFT) for separating overlapping ultrasonic signals, leveraging the FrFT&amp;amp;rsquo;s ability to distinguish signals that overlap in both the time and frequency domains. Numerical simulations and experiments were conducted to investigate the FrFT&amp;amp;rsquo;s separation performance for guided waves inspection with array transducers. Results showed that a smaller time delay worsened separation, while using a chirp signal with a broader bandwidth improved separation for signals of fixed duration. Additionally, the effect of signal dispersion on the results was minimal. The findings confirm that the FrFT can effectively separate overlapping signals, enhancing time efficiency in guided wave inspections using array transducers.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7564: Fractional Fourier Transform-Based Signal Separation for Ultrasonic Guided Wave Inspection of Plates</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7564">doi: 10.3390/s24237564</a></p> <p>Authors: Chengxiang Peng Paul Annus Marek Rist Raul Land Madis Ratassepp </p> <p>Detecting defects in plates is crucial across various industries due to safety risks. While ultrasonic bulk waves offer point-by-point inspections, they are time-consuming and limited in coverage. In contrast, guided waves enable the rapid inspection of larger areas. Array transducers are typically used for more efficient coverage, but conventional excitation methods require sufficient time delays between the excitation of array elements that prolong inspection time, necessitating data acquisition time optimization. Reducing time delays can lead to signal overlapping, complicating signal separation. Conventional frequency domain or time-domain filtering methods often yield unsatisfactory separation results due to the signal overlapping in both domains. This study focuses on the application of the Fractional Fourier Transform (FrFT) for separating overlapping ultrasonic signals, leveraging the FrFT&amp;amp;rsquo;s ability to distinguish signals that overlap in both the time and frequency domains. Numerical simulations and experiments were conducted to investigate the FrFT&amp;amp;rsquo;s separation performance for guided waves inspection with array transducers. Results showed that a smaller time delay worsened separation, while using a chirp signal with a broader bandwidth improved separation for signals of fixed duration. Additionally, the effect of signal dispersion on the results was minimal. The findings confirm that the FrFT can effectively separate overlapping signals, enhancing time efficiency in guided wave inspections using array transducers.</p> ]]></content:encoded> <dc:title>Fractional Fourier Transform-Based Signal Separation for Ultrasonic Guided Wave Inspection of Plates</dc:title> <dc:creator>Chengxiang Peng</dc:creator> <dc:creator>Paul Annus</dc:creator> <dc:creator>Marek Rist</dc:creator> <dc:creator>Raul Land</dc:creator> <dc:creator>Madis Ratassepp</dc:creator> <dc:identifier>doi: 10.3390/s24237564</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7564</prism:startingPage> <prism:doi>10.3390/s24237564</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7564</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7559"> <title>Sensors, Vol. 24, Pages 7559: Automated Stock Volume Estimation Using UAV-RGB Imagery</title> <link>https://www.mdpi.com/1424-8220/24/23/7559</link> <description>Forests play a critical role in the global carbon cycle, with carbon storage being an important carbon pool in the terrestrial ecosystem with tree crown size serving as a versatile ecological indicator influencing factors such as tree growth, wind resistance, shading, and carbon sequestration. They help with habitat function, herbicide application, temperature regulation, etc. Understanding the relationship between tree crown area and stock volume is crucial, as it provides a key metric for assessing the impact of land-use changes on ecological processes. Traditional ground-based stock volume estimation using DBH (Diameter at Breast Height) is labor-intensive and often impractical. However, high-resolution UAV (unmanned aerial vehicle) imagery has revolutionized remote sensing and computer-based tree analysis, making forest studies more efficient and interpretable. Previous studies have established correlations between DBH, stock volume and above-ground biomass, as well as between tree crown area and DBH. This research aims to explore the correlation between tree crown area and stock volume and automate stock volume and above-ground biomass estimation by developing an empirical model using UAV-RGB data, making forest assessments more convenient and time-efficient. The study site included a significant number of training and testing sites to ensure the performance level of the developed model. The findings underscore a significant association, demonstrating the potential of integrating drone technology with traditional forestry techniques for efficient stock volume estimation. The results highlight a strong exponential correlation between crown area and stem stock volume, with a coefficient of determination of 0.67 and mean squared error (MSE) of 0.0015. The developed model, when applied to estimate cumulative stock volume using drone imagery, demonstrated a strong correlation with an R2 of 0.75. These results emphasize the effectiveness of combining drone technology with traditional forestry methods to achieve more precise and efficient stock volume estimation and, hence, automate the process.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7559: Automated Stock Volume Estimation Using UAV-RGB Imagery</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7559">doi: 10.3390/s24237559</a></p> <p>Authors: Anurupa Goswami Unmesh Khati Ishan Goyal Anam Sabir Sakshi Jain </p> <p>Forests play a critical role in the global carbon cycle, with carbon storage being an important carbon pool in the terrestrial ecosystem with tree crown size serving as a versatile ecological indicator influencing factors such as tree growth, wind resistance, shading, and carbon sequestration. They help with habitat function, herbicide application, temperature regulation, etc. Understanding the relationship between tree crown area and stock volume is crucial, as it provides a key metric for assessing the impact of land-use changes on ecological processes. Traditional ground-based stock volume estimation using DBH (Diameter at Breast Height) is labor-intensive and often impractical. However, high-resolution UAV (unmanned aerial vehicle) imagery has revolutionized remote sensing and computer-based tree analysis, making forest studies more efficient and interpretable. Previous studies have established correlations between DBH, stock volume and above-ground biomass, as well as between tree crown area and DBH. This research aims to explore the correlation between tree crown area and stock volume and automate stock volume and above-ground biomass estimation by developing an empirical model using UAV-RGB data, making forest assessments more convenient and time-efficient. The study site included a significant number of training and testing sites to ensure the performance level of the developed model. The findings underscore a significant association, demonstrating the potential of integrating drone technology with traditional forestry techniques for efficient stock volume estimation. The results highlight a strong exponential correlation between crown area and stem stock volume, with a coefficient of determination of 0.67 and mean squared error (MSE) of 0.0015. The developed model, when applied to estimate cumulative stock volume using drone imagery, demonstrated a strong correlation with an R2 of 0.75. These results emphasize the effectiveness of combining drone technology with traditional forestry methods to achieve more precise and efficient stock volume estimation and, hence, automate the process.</p> ]]></content:encoded> <dc:title>Automated Stock Volume Estimation Using UAV-RGB Imagery</dc:title> <dc:creator>Anurupa Goswami</dc:creator> <dc:creator>Unmesh Khati</dc:creator> <dc:creator>Ishan Goyal</dc:creator> <dc:creator>Anam Sabir</dc:creator> <dc:creator>Sakshi Jain</dc:creator> <dc:identifier>doi: 10.3390/s24237559</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7559</prism:startingPage> <prism:doi>10.3390/s24237559</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7559</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7563"> <title>Sensors, Vol. 24, Pages 7563: Analysis of Resistance in Magnetic Flux Leakage (MFL) Detectors for Natural Gas Pipelines</title> <link>https://www.mdpi.com/1424-8220/24/23/7563</link> <description>This study systematically explores the sources and influencing factors of resistance encountered by magnetic flux leakage (MFL) detectors in natural gas pipelines through a theoretical analysis, experimental investigation, and numerical simulation. The research methodology involves the development of a fluid&amp;amp;ndash;structure interaction model using ABAQUS 2023 finite element software, complemented by the design and implementation of a pull-testing platform for MFL detectors. This platform simulates detector operation under various interference conditions and quantifies the resulting frictional resistance. The findings reveal that the primary source of frictional resistance is the contact interaction between the MFL detector and the pipeline wall. Key factors influencing the magnitude of this resistance include the detector&amp;amp;rsquo;s mass, the structural design and materials of the sealing cups and support plates, as well as the surface roughness of the pipeline. Both experimental results and numerical simulations demonstrate a pronounced increase in frictional resistance with heightened interference levels. The theoretical model exhibits strong agreement with experimental data, though deviations are observed under conditions of severe interference. This study provides a detailed understanding of frictional resistance patterns under diverse structural and operational scenarios, offering both theoretical guidance and practical recommendations for the design of low-resistance MFL detectors.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7563: Analysis of Resistance in Magnetic Flux Leakage (MFL) Detectors for Natural Gas Pipelines</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7563">doi: 10.3390/s24237563</a></p> <p>Authors: Zenggang Zhang Xiangjun Chen Chuanmin Tai Guansan Tian Guozhao Han </p> <p>This study systematically explores the sources and influencing factors of resistance encountered by magnetic flux leakage (MFL) detectors in natural gas pipelines through a theoretical analysis, experimental investigation, and numerical simulation. The research methodology involves the development of a fluid&amp;amp;ndash;structure interaction model using ABAQUS 2023 finite element software, complemented by the design and implementation of a pull-testing platform for MFL detectors. This platform simulates detector operation under various interference conditions and quantifies the resulting frictional resistance. The findings reveal that the primary source of frictional resistance is the contact interaction between the MFL detector and the pipeline wall. Key factors influencing the magnitude of this resistance include the detector&amp;amp;rsquo;s mass, the structural design and materials of the sealing cups and support plates, as well as the surface roughness of the pipeline. Both experimental results and numerical simulations demonstrate a pronounced increase in frictional resistance with heightened interference levels. The theoretical model exhibits strong agreement with experimental data, though deviations are observed under conditions of severe interference. This study provides a detailed understanding of frictional resistance patterns under diverse structural and operational scenarios, offering both theoretical guidance and practical recommendations for the design of low-resistance MFL detectors.</p> ]]></content:encoded> <dc:title>Analysis of Resistance in Magnetic Flux Leakage (MFL) Detectors for Natural Gas Pipelines</dc:title> <dc:creator>Zenggang Zhang</dc:creator> <dc:creator>Xiangjun Chen</dc:creator> <dc:creator>Chuanmin Tai</dc:creator> <dc:creator>Guansan Tian</dc:creator> <dc:creator>Guozhao Han</dc:creator> <dc:identifier>doi: 10.3390/s24237563</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7563</prism:startingPage> <prism:doi>10.3390/s24237563</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7563</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7562"> <title>Sensors, Vol. 24, Pages 7562: First Stability Characterization for a CZT Detection System in an e+e&amp;minus; Collider Environment</title> <link>https://www.mdpi.com/1424-8220/24/23/7562</link> <description>The SIDDHARTA-2 collaboration has developed a novel X-ray detection system based on cadmium-zinc-telluride (CZT, CdZnTe), marking the first application of this technology at the DA&amp;amp;Phi;NE electron-positron collider at INFN-LNF. This work aims to demonstrate the stability of the detectors&amp;amp;rsquo; performance in terms of linearity and resolution over short and long periods, thereby establishing their suitability for precise spectroscopic measurements within a collider environment. A reference calibration spectrum is presented in association with findings from assessments of linearity and resolution stability. Additionally, this study introduces a validated model of the response function of the detector. The relative deviations from the nominal values for the source transitions, obtained by fitting the entire spectrum with a background function and the previously introduced response function, are reported. Finally, a comparison of the calibration performance with and without beams circulating in the collider&amp;amp;rsquo;s rings is presented. These promising results pave the way for applying CZT detectors in kaonic atom studies and, more generally, in particle and nuclear physics spectroscopy.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7562: First Stability Characterization for a CZT Detection System in an e+e&amp;minus; Collider Environment</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7562">doi: 10.3390/s24237562</a></p> <p>Authors: Leonardo Abbene Francesco Artibani Manuele Bettelli Antonino Buttacavoli Fabio Principato Andrea Zappettini Massimiliano Bazzi Giacomo Borghi Mario Bragadireanu Michael Cargnelli Marco Carminati Alberto Clozza Francesco Clozza Luca De Paolis Raffaele Del Grande Kamil Dulski Laura Fabbietti Carlo Fiorini Carlo Guaraldo Mihail Iliescu Masahiko Iwasaki Aleksander Khreptak Simone Manti Johann Marton Pawel Moskal Fabrizio Napolitano Szymon Nied藕wiecki Hiroaki Ohnishi Kristian Piscicchia Yuta Sada Francesco Sgaramella Diana Laura Sirghi Florin Sirghi Magdalena Skurzok Michal Silarski Antonio Spallone Kairo Toho Lorenzo Toscano Marlene T眉chler Oton Vasquez Doce Johann Zmeskal Catalina Curceanu Alessandro Scordo </p> <p>The SIDDHARTA-2 collaboration has developed a novel X-ray detection system based on cadmium-zinc-telluride (CZT, CdZnTe), marking the first application of this technology at the DA&amp;amp;Phi;NE electron-positron collider at INFN-LNF. This work aims to demonstrate the stability of the detectors&amp;amp;rsquo; performance in terms of linearity and resolution over short and long periods, thereby establishing their suitability for precise spectroscopic measurements within a collider environment. A reference calibration spectrum is presented in association with findings from assessments of linearity and resolution stability. Additionally, this study introduces a validated model of the response function of the detector. The relative deviations from the nominal values for the source transitions, obtained by fitting the entire spectrum with a background function and the previously introduced response function, are reported. Finally, a comparison of the calibration performance with and without beams circulating in the collider&amp;amp;rsquo;s rings is presented. These promising results pave the way for applying CZT detectors in kaonic atom studies and, more generally, in particle and nuclear physics spectroscopy.</p> ]]></content:encoded> <dc:title>First Stability Characterization for a CZT Detection System in an e+e&amp;amp;minus; Collider Environment</dc:title> <dc:creator>Leonardo Abbene</dc:creator> <dc:creator>Francesco Artibani</dc:creator> <dc:creator>Manuele Bettelli</dc:creator> <dc:creator>Antonino Buttacavoli</dc:creator> <dc:creator>Fabio Principato</dc:creator> <dc:creator>Andrea Zappettini</dc:creator> <dc:creator>Massimiliano Bazzi</dc:creator> <dc:creator>Giacomo Borghi</dc:creator> <dc:creator>Mario Bragadireanu</dc:creator> <dc:creator>Michael Cargnelli</dc:creator> <dc:creator>Marco Carminati</dc:creator> <dc:creator>Alberto Clozza</dc:creator> <dc:creator>Francesco Clozza</dc:creator> <dc:creator>Luca De Paolis</dc:creator> <dc:creator>Raffaele Del Grande</dc:creator> <dc:creator>Kamil Dulski</dc:creator> <dc:creator>Laura Fabbietti</dc:creator> <dc:creator>Carlo Fiorini</dc:creator> <dc:creator>Carlo Guaraldo</dc:creator> <dc:creator>Mihail Iliescu</dc:creator> <dc:creator>Masahiko Iwasaki</dc:creator> <dc:creator>Aleksander Khreptak</dc:creator> <dc:creator>Simone Manti</dc:creator> <dc:creator>Johann Marton</dc:creator> <dc:creator>Pawel Moskal</dc:creator> <dc:creator>Fabrizio Napolitano</dc:creator> <dc:creator>Szymon Nied藕wiecki</dc:creator> <dc:creator>Hiroaki Ohnishi</dc:creator> <dc:creator>Kristian Piscicchia</dc:creator> <dc:creator>Yuta Sada</dc:creator> <dc:creator>Francesco Sgaramella</dc:creator> <dc:creator>Diana Laura Sirghi</dc:creator> <dc:creator>Florin Sirghi</dc:creator> <dc:creator>Magdalena Skurzok</dc:creator> <dc:creator>Michal Silarski</dc:creator> <dc:creator>Antonio Spallone</dc:creator> <dc:creator>Kairo Toho</dc:creator> <dc:creator>Lorenzo Toscano</dc:creator> <dc:creator>Marlene T眉chler</dc:creator> <dc:creator>Oton Vasquez Doce</dc:creator> <dc:creator>Johann Zmeskal</dc:creator> <dc:creator>Catalina Curceanu</dc:creator> <dc:creator>Alessandro Scordo</dc:creator> <dc:identifier>doi: 10.3390/s24237562</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7562</prism:startingPage> <prism:doi>10.3390/s24237562</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7562</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7561"> <title>Sensors, Vol. 24, Pages 7561: Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation</title> <link>https://www.mdpi.com/1424-8220/24/23/7561</link> <description>As maximum power point tracking (MPPT) algorithms have developed towards multi-task intelligent computing, processors in photovoltaic power generation control systems must be capable of achieving a higher performance. However, the challenges posed by the complex environment of photovoltaic fields with regard to processor reliability cannot be overlooked. To address these issues, we proposed a novel approach. Our approach uses error rate and performance as switching metrics and performs joint statistics to achieve efficient adaptive switching. Based on this, our work designed a redundancy-mode switchable three-core processor system to balance performance and reliability. Additionally, by analyzing the relationship between performance and reliability, we proposed optimization methods to improve reliability while ensuring a high performance was maintained. Finally, we designed an error injection method and verified the system&amp;amp;rsquo;s reliability by analyzing the error rate probability model in different scenarios. The results of the analysis show that compared with the traditional MPPT controller, the redundancy mode switchable multi-core processor system proposed in this paper exhibits a reliability approximately 5.58 times that of a non-fault-tolerant system. Furthermore, leveraging the feature of module switching, the system&amp;amp;rsquo;s performance has been enhanced by 26% compared to a highly reliable triple modular redundancy systems, significantly improving the system&amp;amp;rsquo;s reliability while ensuring a good performance is maintained.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7561: Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7561">doi: 10.3390/s24237561</a></p> <p>Authors: Liang Liu Xige Zhang Jiahui Zhou Kai Niu Zixuan Guo Yawen Zhao Meng Zhang </p> <p>As maximum power point tracking (MPPT) algorithms have developed towards multi-task intelligent computing, processors in photovoltaic power generation control systems must be capable of achieving a higher performance. However, the challenges posed by the complex environment of photovoltaic fields with regard to processor reliability cannot be overlooked. To address these issues, we proposed a novel approach. Our approach uses error rate and performance as switching metrics and performs joint statistics to achieve efficient adaptive switching. Based on this, our work designed a redundancy-mode switchable three-core processor system to balance performance and reliability. Additionally, by analyzing the relationship between performance and reliability, we proposed optimization methods to improve reliability while ensuring a high performance was maintained. Finally, we designed an error injection method and verified the system&amp;amp;rsquo;s reliability by analyzing the error rate probability model in different scenarios. The results of the analysis show that compared with the traditional MPPT controller, the redundancy mode switchable multi-core processor system proposed in this paper exhibits a reliability approximately 5.58 times that of a non-fault-tolerant system. Furthermore, leveraging the feature of module switching, the system&amp;amp;rsquo;s performance has been enhanced by 26% compared to a highly reliable triple modular redundancy systems, significantly improving the system&amp;amp;rsquo;s reliability while ensuring a good performance is maintained.</p> ]]></content:encoded> <dc:title>Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation</dc:title> <dc:creator>Liang Liu</dc:creator> <dc:creator>Xige Zhang</dc:creator> <dc:creator>Jiahui Zhou</dc:creator> <dc:creator>Kai Niu</dc:creator> <dc:creator>Zixuan Guo</dc:creator> <dc:creator>Yawen Zhao</dc:creator> <dc:creator>Meng Zhang</dc:creator> <dc:identifier>doi: 10.3390/s24237561</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7561</prism:startingPage> <prism:doi>10.3390/s24237561</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7561</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7560"> <title>Sensors, Vol. 24, Pages 7560: Non-Destructive Monitoring of External Quality of Date Palm Fruit (Phoenix dactylifera L.) During Frozen Storage Using Digital Camera and Flatbed Scanner</title> <link>https://www.mdpi.com/1424-8220/24/23/7560</link> <description>The emergence of new technologies focusing on &amp;amp;ldquo;computer vision&amp;amp;rdquo; has contributed significantly to the assessment of fruit quality. In this study, an innovative approach based on image analysis was used to assess the external quality of fresh and frozen &amp;amp;ldquo;Mejhoul&amp;amp;rdquo; and &amp;amp;ldquo;Boufeggous&amp;amp;rdquo; date palm cultivars stored for 6 months at &amp;amp;minus;10 &amp;amp;deg;C and &amp;amp;minus;18 &amp;amp;deg;C. Their quality was evaluated, in a non-destructive manner, based on texture features extracted from images acquired using a digital camera and flatbed scanner. The whole process of image processing was carried out using MATLAB R2024a and Q-MAZDA 23.10 software. Then, extracted features were used as inputs for pre-established algorithms&amp;amp;ndash;groups within WEKA 3.9 software to classify frozen date fruit samples after 0, 2, 4, and 6 months of storage. Among 599 features, only 5 to 36 attributes were selected as powerful predictors to build desired classification models based on the &amp;amp;ldquo;Functions-Logistic&amp;amp;rdquo; classifier. The general architecture exhibited clear differences in classification accuracy depending mainly on the frozen storage period and imaging device. Accordingly, confusion matrices showed high classification accuracy (CA), which could reach 0.84 at M0 for both cultivars at the two frozen storage temperatures. This CA indicated a remarkable decrease at M2 and M4 before re-increasing by M6, confirming slight changes in external quality before the end of storage. Moreover, the developed models on the basis of flatbed scanner use allowed us to obtain a high correctness rate that could attain 97.7% correctness in comparison to the digital camera, which did not exceed 85.5%. In conclusion, physicochemical attributes can be added to developed models to establish correlation with image features and predict the behavior of date fruit under storage.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7560: Non-Destructive Monitoring of External Quality of Date Palm Fruit (Phoenix dactylifera L.) During Frozen Storage Using Digital Camera and Flatbed Scanner</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7560">doi: 10.3390/s24237560</a></p> <p>Authors: Younes Noutfia Ewa Ropelewska Zbigniew J贸藕wiak Krzysztof Rutkowski </p> <p>The emergence of new technologies focusing on &amp;amp;ldquo;computer vision&amp;amp;rdquo; has contributed significantly to the assessment of fruit quality. In this study, an innovative approach based on image analysis was used to assess the external quality of fresh and frozen &amp;amp;ldquo;Mejhoul&amp;amp;rdquo; and &amp;amp;ldquo;Boufeggous&amp;amp;rdquo; date palm cultivars stored for 6 months at &amp;amp;minus;10 &amp;amp;deg;C and &amp;amp;minus;18 &amp;amp;deg;C. Their quality was evaluated, in a non-destructive manner, based on texture features extracted from images acquired using a digital camera and flatbed scanner. The whole process of image processing was carried out using MATLAB R2024a and Q-MAZDA 23.10 software. Then, extracted features were used as inputs for pre-established algorithms&amp;amp;ndash;groups within WEKA 3.9 software to classify frozen date fruit samples after 0, 2, 4, and 6 months of storage. Among 599 features, only 5 to 36 attributes were selected as powerful predictors to build desired classification models based on the &amp;amp;ldquo;Functions-Logistic&amp;amp;rdquo; classifier. The general architecture exhibited clear differences in classification accuracy depending mainly on the frozen storage period and imaging device. Accordingly, confusion matrices showed high classification accuracy (CA), which could reach 0.84 at M0 for both cultivars at the two frozen storage temperatures. This CA indicated a remarkable decrease at M2 and M4 before re-increasing by M6, confirming slight changes in external quality before the end of storage. Moreover, the developed models on the basis of flatbed scanner use allowed us to obtain a high correctness rate that could attain 97.7% correctness in comparison to the digital camera, which did not exceed 85.5%. In conclusion, physicochemical attributes can be added to developed models to establish correlation with image features and predict the behavior of date fruit under storage.</p> ]]></content:encoded> <dc:title>Non-Destructive Monitoring of External Quality of Date Palm Fruit (Phoenix dactylifera L.) During Frozen Storage Using Digital Camera and Flatbed Scanner</dc:title> <dc:creator>Younes Noutfia</dc:creator> <dc:creator>Ewa Ropelewska</dc:creator> <dc:creator>Zbigniew J贸藕wiak</dc:creator> <dc:creator>Krzysztof Rutkowski</dc:creator> <dc:identifier>doi: 10.3390/s24237560</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7560</prism:startingPage> <prism:doi>10.3390/s24237560</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7560</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7558"> <title>Sensors, Vol. 24, Pages 7558: Time Efficiency and Ergonomic Assessment of a Robotic Wheelchair Transfer System</title> <link>https://www.mdpi.com/1424-8220/24/23/7558</link> <description>Background: Caregivers experience high rates of occupational injuries, especially during wheelchair transfers, which often result in back pain and musculoskeletal disorders due to the physical demands of lifting and repositioning. While mechanical floor lifts, the current standard, reduce back strain, they are time-consuming and require handling techniques that subject caregivers to prolonged and repeated non-neutral trunk postures, increasing the risk of long-term back injuries. Aims: The aim was to assess the time efficiency and ergonomics of the powered personal transfer system (PPTS), a robotic transfer device designed for bed-to/from-wheelchair transfers. Methods: We evaluated transfers with the PPTS and mechanical lift with eight able-bodied participants who assisted with transfers between a bed and a wheelchair. Inertial measurement units (IMUs) were placed on participants to track their motion and assess trunk joint angles during transfers. Results: The PPTS significantly reduced the transfer time (144.31 s vs. 525.82 s, p &amp;amp;lt; 0.001) and required significantly less range of motion for trunk flexion (p &amp;amp;lt; 0.001), lateral bending (p = 0.008), and axial rotation (p = 0.001), all of which have been associated with back injuries. Additionally, the PPTS significantly reduced the time caregivers spent in non-neutral trunk postures, potentially lowering injury risks. Conclusions: These findings suggest that the PPTS improves transfer efficiency and caregiver safety, offering a promising alternative to the current standard of care for wheelchair-to/from-bed transfers.</description> <pubDate>2024-11-27</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7558: Time Efficiency and Ergonomic Assessment of a Robotic Wheelchair Transfer System</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7558">doi: 10.3390/s24237558</a></p> <p>Authors: Shantanu A. Satpute Kaylee J. Uribe Oluwatofunmi O. Olaore Minori Iizuka Ian C. McCumber Gandara William J. Schoy Rutuja A. Kulkarni Rosemarie Cooper Alicia M. Koontz Owen Flaugh Rory A. Cooper </p> <p>Background: Caregivers experience high rates of occupational injuries, especially during wheelchair transfers, which often result in back pain and musculoskeletal disorders due to the physical demands of lifting and repositioning. While mechanical floor lifts, the current standard, reduce back strain, they are time-consuming and require handling techniques that subject caregivers to prolonged and repeated non-neutral trunk postures, increasing the risk of long-term back injuries. Aims: The aim was to assess the time efficiency and ergonomics of the powered personal transfer system (PPTS), a robotic transfer device designed for bed-to/from-wheelchair transfers. Methods: We evaluated transfers with the PPTS and mechanical lift with eight able-bodied participants who assisted with transfers between a bed and a wheelchair. Inertial measurement units (IMUs) were placed on participants to track their motion and assess trunk joint angles during transfers. Results: The PPTS significantly reduced the transfer time (144.31 s vs. 525.82 s, p &amp;amp;lt; 0.001) and required significantly less range of motion for trunk flexion (p &amp;amp;lt; 0.001), lateral bending (p = 0.008), and axial rotation (p = 0.001), all of which have been associated with back injuries. Additionally, the PPTS significantly reduced the time caregivers spent in non-neutral trunk postures, potentially lowering injury risks. Conclusions: These findings suggest that the PPTS improves transfer efficiency and caregiver safety, offering a promising alternative to the current standard of care for wheelchair-to/from-bed transfers.</p> ]]></content:encoded> <dc:title>Time Efficiency and Ergonomic Assessment of a Robotic Wheelchair Transfer System</dc:title> <dc:creator>Shantanu A. Satpute</dc:creator> <dc:creator>Kaylee J. Uribe</dc:creator> <dc:creator>Oluwatofunmi O. Olaore</dc:creator> <dc:creator>Minori Iizuka</dc:creator> <dc:creator>Ian C. McCumber Gandara</dc:creator> <dc:creator>William J. Schoy</dc:creator> <dc:creator>Rutuja A. Kulkarni</dc:creator> <dc:creator>Rosemarie Cooper</dc:creator> <dc:creator>Alicia M. Koontz</dc:creator> <dc:creator>Owen Flaugh</dc:creator> <dc:creator>Rory A. Cooper</dc:creator> <dc:identifier>doi: 10.3390/s24237558</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-27</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-27</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7558</prism:startingPage> <prism:doi>10.3390/s24237558</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7558</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7557"> <title>Sensors, Vol. 24, Pages 7557: Defect Detection and 3D Reconstruction of Complex Urban Underground Pipeline Scenes for Sewer Robots</title> <link>https://www.mdpi.com/1424-8220/24/23/7557</link> <description>Detecting defects in complex urban sewer scenes is crucial for urban underground structure health monitoring. However, most image-based sewer defect detection models are complex, have high resource consumption, and fail to provide detailed damage information. To increase defect detection efficiency, visualize pipelines, and enable deployment on edge devices, this paper proposes a computer vision-based robotic defect detection framework for sewers. The framework encompasses positioning, defect detection, model deployment, 3D reconstruction, and the measurement of realistic pipelines. A lightweight Sewer-YOLO-Slim model is introduced, which reconstructs the YOLOv7-tiny network by adjusting its backbone, neck, and head. Channel pruning is applied to further reduce the model&amp;amp;rsquo;s complexity. Additionally, a multiview reconstruction technique is employed to build a 3D model of the pipeline from images captured by the sewer robot, allowing for accurate measurements. The Sewer-YOLO-Slim model achieves reductions of 60.2%, 60.0%, and 65.9% in model size, parameters, and floating-point operations (FLOPs), respectively, while improving the mean average precision (mAP) by 1.5%, reaching 93.5%. Notably, the pruned model is only 4.9 MB in size. Comprehensive comparisons and analyses are conducted with 12 mainstream detection algorithms to validate the superiority of the proposed model. The model is deployed on edge devices with the aid of TensorRT for acceleration, and the detection speed reaches 15.3 ms per image. For a real section of the pipeline, the maximum measurement error of the 3D reconstruction model is 0.57 m. These results indicate that the proposed sewer inspection framework is effective, with the detection model exhibiting advanced performance in terms of accuracy, low computational demand, and real-time capability. The 3D modeling approach offers valuable insights for underground pipeline data visualization and defect measurement.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7557: Defect Detection and 3D Reconstruction of Complex Urban Underground Pipeline Scenes for Sewer Robots</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7557">doi: 10.3390/s24237557</a></p> <p>Authors: Ruihao Liu Zhongxi Shao Qiang Sun Zhenzhong Yu </p> <p>Detecting defects in complex urban sewer scenes is crucial for urban underground structure health monitoring. However, most image-based sewer defect detection models are complex, have high resource consumption, and fail to provide detailed damage information. To increase defect detection efficiency, visualize pipelines, and enable deployment on edge devices, this paper proposes a computer vision-based robotic defect detection framework for sewers. The framework encompasses positioning, defect detection, model deployment, 3D reconstruction, and the measurement of realistic pipelines. A lightweight Sewer-YOLO-Slim model is introduced, which reconstructs the YOLOv7-tiny network by adjusting its backbone, neck, and head. Channel pruning is applied to further reduce the model&amp;amp;rsquo;s complexity. Additionally, a multiview reconstruction technique is employed to build a 3D model of the pipeline from images captured by the sewer robot, allowing for accurate measurements. The Sewer-YOLO-Slim model achieves reductions of 60.2%, 60.0%, and 65.9% in model size, parameters, and floating-point operations (FLOPs), respectively, while improving the mean average precision (mAP) by 1.5%, reaching 93.5%. Notably, the pruned model is only 4.9 MB in size. Comprehensive comparisons and analyses are conducted with 12 mainstream detection algorithms to validate the superiority of the proposed model. The model is deployed on edge devices with the aid of TensorRT for acceleration, and the detection speed reaches 15.3 ms per image. For a real section of the pipeline, the maximum measurement error of the 3D reconstruction model is 0.57 m. These results indicate that the proposed sewer inspection framework is effective, with the detection model exhibiting advanced performance in terms of accuracy, low computational demand, and real-time capability. The 3D modeling approach offers valuable insights for underground pipeline data visualization and defect measurement.</p> ]]></content:encoded> <dc:title>Defect Detection and 3D Reconstruction of Complex Urban Underground Pipeline Scenes for Sewer Robots</dc:title> <dc:creator>Ruihao Liu</dc:creator> <dc:creator>Zhongxi Shao</dc:creator> <dc:creator>Qiang Sun</dc:creator> <dc:creator>Zhenzhong Yu</dc:creator> <dc:identifier>doi: 10.3390/s24237557</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7557</prism:startingPage> <prism:doi>10.3390/s24237557</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7557</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7556"> <title>Sensors, Vol. 24, Pages 7556: Rolling Resistance Evaluation of Pavements Using Embedded Transducers on a Semi-Trailer Suspension</title> <link>https://www.mdpi.com/1424-8220/24/23/7556</link> <description>Road agency initiatives to reduce traffic-related greenhouse gas emissions are limited by the inability of current experimental methods to assess pavement impacts on vehicle energy consumption. This study addresses this by examining the rolling resistance of a semi-trailer suspension under highway conditions using a precise measurement system with embedded transducers. Data were collected over 174 km of highway, covering various pavement types under mild summer conditions. The analysis revealed notable differences in rolling resistance due to pavement characteristics, with more pronounced variations observed within pavement types than between them. For instance, geographically consecutive jointed rigid pavements showed a 34% variation in rolling resistance, likely correlated with harmonic excitations generated by slab presence, while flexible pavements exhibited up to a 21% variation under similar tire operating conditions. Composite pavements generally performed the worst, possibly due to interactions between bituminous materials and older cement-based foundations. The study also highlighted the critical role of tire operating conditions, showing a decrease of 0.09 kg/tonne in rolling resistance for every 1 &amp;amp;deg;C increase in temperature. This research shows that precisely measuring the rolling resistance (&amp;amp;plusmn;0.1 kg/tonne) in situ for heavy vehicles is feasible and underscores the need for additional data in diverse weather scenarios to better align laboratory results with on-road realities.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7556: Rolling Resistance Evaluation of Pavements Using Embedded Transducers on a Semi-Trailer Suspension</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7556">doi: 10.3390/s24237556</a></p> <p>Authors: William Levesque Andr茅 B茅gin-Drolet Julien L茅pine </p> <p>Road agency initiatives to reduce traffic-related greenhouse gas emissions are limited by the inability of current experimental methods to assess pavement impacts on vehicle energy consumption. This study addresses this by examining the rolling resistance of a semi-trailer suspension under highway conditions using a precise measurement system with embedded transducers. Data were collected over 174 km of highway, covering various pavement types under mild summer conditions. The analysis revealed notable differences in rolling resistance due to pavement characteristics, with more pronounced variations observed within pavement types than between them. For instance, geographically consecutive jointed rigid pavements showed a 34% variation in rolling resistance, likely correlated with harmonic excitations generated by slab presence, while flexible pavements exhibited up to a 21% variation under similar tire operating conditions. Composite pavements generally performed the worst, possibly due to interactions between bituminous materials and older cement-based foundations. The study also highlighted the critical role of tire operating conditions, showing a decrease of 0.09 kg/tonne in rolling resistance for every 1 &amp;amp;deg;C increase in temperature. This research shows that precisely measuring the rolling resistance (&amp;amp;plusmn;0.1 kg/tonne) in situ for heavy vehicles is feasible and underscores the need for additional data in diverse weather scenarios to better align laboratory results with on-road realities.</p> ]]></content:encoded> <dc:title>Rolling Resistance Evaluation of Pavements Using Embedded Transducers on a Semi-Trailer Suspension</dc:title> <dc:creator>William Levesque</dc:creator> <dc:creator>Andr茅 B茅gin-Drolet</dc:creator> <dc:creator>Julien L茅pine</dc:creator> <dc:identifier>doi: 10.3390/s24237556</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7556</prism:startingPage> <prism:doi>10.3390/s24237556</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7556</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7555"> <title>Sensors, Vol. 24, Pages 7555: Research Advances in Marine Aquaculture Net-Cleaning Robots</title> <link>https://www.mdpi.com/1424-8220/24/23/7555</link> <description>In the realm of marine aquaculture, the netting of cages frequently accumulates marine fouling, which impedes water circulation and poses safety hazards. Traditional manual cleaning methods are marked by inefficiency, high labor demands, substantial costs, and considerable environmental degradation. This paper initially presents the current utilization of net-cleaning robots in the cleaning, underwater inspection, and monitoring of aquaculture cages, highlighting their benefits in enhancing operational efficiency and minimizing costs. Subsequently, it reviews key technologies such as underwater image acquisition, visual recognition, adhesion-based movement, efficient fouling removal, motion control, and positioning navigation. Ultimately, it anticipates the future trajectory of net-cleaning robots, emphasizing their potential for intelligence and sustainability, which could drive the marine aquaculture industry towards a more efficient and eco-friendly era.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7555: Research Advances in Marine Aquaculture Net-Cleaning Robots</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7555">doi: 10.3390/s24237555</a></p> <p>Authors: Heng Liu Chuhua Jiang Junhua Chen Hao Li Yongqi Chen </p> <p>In the realm of marine aquaculture, the netting of cages frequently accumulates marine fouling, which impedes water circulation and poses safety hazards. Traditional manual cleaning methods are marked by inefficiency, high labor demands, substantial costs, and considerable environmental degradation. This paper initially presents the current utilization of net-cleaning robots in the cleaning, underwater inspection, and monitoring of aquaculture cages, highlighting their benefits in enhancing operational efficiency and minimizing costs. Subsequently, it reviews key technologies such as underwater image acquisition, visual recognition, adhesion-based movement, efficient fouling removal, motion control, and positioning navigation. Ultimately, it anticipates the future trajectory of net-cleaning robots, emphasizing their potential for intelligence and sustainability, which could drive the marine aquaculture industry towards a more efficient and eco-friendly era.</p> ]]></content:encoded> <dc:title>Research Advances in Marine Aquaculture Net-Cleaning Robots</dc:title> <dc:creator>Heng Liu</dc:creator> <dc:creator>Chuhua Jiang</dc:creator> <dc:creator>Junhua Chen</dc:creator> <dc:creator>Hao Li</dc:creator> <dc:creator>Yongqi Chen</dc:creator> <dc:identifier>doi: 10.3390/s24237555</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Review</prism:section> <prism:startingPage>7555</prism:startingPage> <prism:doi>10.3390/s24237555</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7555</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7554"> <title>Sensors, Vol. 24, Pages 7554: Position-Constrained Calibration Compensation for Hand&amp;ndash;Eye Calibration in Industrial Robots</title> <link>https://www.mdpi.com/1424-8220/24/23/7554</link> <description>The hand&amp;amp;ndash;eye calibration of laser profilers and industrial robots is a critical component of the laser vision system in welding applications. To improve calibration accuracy and efficiency, this study proposes a position-constrained calibration compensation algorithm aimed at optimizing the hand&amp;amp;ndash;eye transformation matrix. Initially, the laser profiler is mounted on the robot and used to scan a standard sphere from various poses to obtain the theoretical center coordinates of the sphere, which are then utilized to compute the hand&amp;amp;ndash;eye transformation matrix. Subsequently, the positional data of the standard sphere&amp;amp;rsquo;s surface are collected at different poses using the welding gun tip mounted on the robot, allowing for the fitting of the sphere&amp;amp;rsquo;s center coordinates as calibration values. Finally, by minimizing the error between the theoretical and calibrated sphere center coordinates, the optimal hand&amp;amp;ndash;eye transformation matrix is derived. Experimental results demonstrate that, following error compensation, the average distance error in hand&amp;amp;ndash;eye calibration decreased from 4.5731 mm to 0.7069 mm, indicating that the proposed calibration method is both reliable and effective.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7554: Position-Constrained Calibration Compensation for Hand&amp;ndash;Eye Calibration in Industrial Robots</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7554">doi: 10.3390/s24237554</a></p> <p>Authors: Jinsong Lin Yuxing Feng Wenze Ren Jiahui Feng Jun Zheng </p> <p>The hand&amp;amp;ndash;eye calibration of laser profilers and industrial robots is a critical component of the laser vision system in welding applications. To improve calibration accuracy and efficiency, this study proposes a position-constrained calibration compensation algorithm aimed at optimizing the hand&amp;amp;ndash;eye transformation matrix. Initially, the laser profiler is mounted on the robot and used to scan a standard sphere from various poses to obtain the theoretical center coordinates of the sphere, which are then utilized to compute the hand&amp;amp;ndash;eye transformation matrix. Subsequently, the positional data of the standard sphere&amp;amp;rsquo;s surface are collected at different poses using the welding gun tip mounted on the robot, allowing for the fitting of the sphere&amp;amp;rsquo;s center coordinates as calibration values. Finally, by minimizing the error between the theoretical and calibrated sphere center coordinates, the optimal hand&amp;amp;ndash;eye transformation matrix is derived. Experimental results demonstrate that, following error compensation, the average distance error in hand&amp;amp;ndash;eye calibration decreased from 4.5731 mm to 0.7069 mm, indicating that the proposed calibration method is both reliable and effective.</p> ]]></content:encoded> <dc:title>Position-Constrained Calibration Compensation for Hand&amp;amp;ndash;Eye Calibration in Industrial Robots</dc:title> <dc:creator>Jinsong Lin</dc:creator> <dc:creator>Yuxing Feng</dc:creator> <dc:creator>Wenze Ren</dc:creator> <dc:creator>Jiahui Feng</dc:creator> <dc:creator>Jun Zheng</dc:creator> <dc:identifier>doi: 10.3390/s24237554</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7554</prism:startingPage> <prism:doi>10.3390/s24237554</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7554</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7553"> <title>Sensors, Vol. 24, Pages 7553: Design, Fabrication and Characterization of Disk Resonator Gyroscope with Vibration and Shock Resistance</title> <link>https://www.mdpi.com/1424-8220/24/23/7553</link> <description>This paper presents a comprehensive optimization of an outer frame anchor disk resonator gyroscope (DRG) with enhanced resistance to vibration and shock, achieved by increasing the resonant frequency of the tub and translation modes. Furthermore, the wineglass mode retains a high quality factor, enhancing sensitivity and reducing the angle random walk (ARW). The performance of the proposed DRG is analyzed using dynamic equations, and its structural parameters are optimized through finite element analysis (FEA). The prototype device was fabricated using a two-mask silicon-on-insulator (SOI) process on (100) single-crystal silicon (SCS), which is better suited for complementary metal-oxide&amp;amp;ndash;semiconductor (CMOS) integration compared to (111) SCS. Experimental results show an ARW of and a bias instability (BI) of , with no significant performance degradation observed under vibrational environments, indicating potential for tactical-grade performance.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7553: Design, Fabrication and Characterization of Disk Resonator Gyroscope with Vibration and Shock Resistance</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7553">doi: 10.3390/s24237553</a></p> <p>Authors: Zhaoyang Zhai Xiaorui Bie Bingchen Zhu Zhenxiang Qi Bowen Wang Kunfeng Wang Xudong Zou </p> <p>This paper presents a comprehensive optimization of an outer frame anchor disk resonator gyroscope (DRG) with enhanced resistance to vibration and shock, achieved by increasing the resonant frequency of the tub and translation modes. Furthermore, the wineglass mode retains a high quality factor, enhancing sensitivity and reducing the angle random walk (ARW). The performance of the proposed DRG is analyzed using dynamic equations, and its structural parameters are optimized through finite element analysis (FEA). The prototype device was fabricated using a two-mask silicon-on-insulator (SOI) process on (100) single-crystal silicon (SCS), which is better suited for complementary metal-oxide&amp;amp;ndash;semiconductor (CMOS) integration compared to (111) SCS. Experimental results show an ARW of and a bias instability (BI) of , with no significant performance degradation observed under vibrational environments, indicating potential for tactical-grade performance.</p> ]]></content:encoded> <dc:title>Design, Fabrication and Characterization of Disk Resonator Gyroscope with Vibration and Shock Resistance</dc:title> <dc:creator>Zhaoyang Zhai</dc:creator> <dc:creator>Xiaorui Bie</dc:creator> <dc:creator>Bingchen Zhu</dc:creator> <dc:creator>Zhenxiang Qi</dc:creator> <dc:creator>Bowen Wang</dc:creator> <dc:creator>Kunfeng Wang</dc:creator> <dc:creator>Xudong Zou</dc:creator> <dc:identifier>doi: 10.3390/s24237553</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7553</prism:startingPage> <prism:doi>10.3390/s24237553</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7553</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7551"> <title>Sensors, Vol. 24, Pages 7551: A Fusion Localization System for Security Robots Based on Millimeter Wave Radar and Inertial Sensors</title> <link>https://www.mdpi.com/1424-8220/24/23/7551</link> <description>In smoggy and dusty environments, vision- and laser-based localization methods are not able to be used effectively for controlling the movement of a robot. Autonomous operation of a security robot can be achieved in such environments by using millimeter wave (MMW) radar for the localization system. In this study, an approximate center method under a sparse point cloud is proposed, and a security robot localization system based on millimeter wave radar is constructed. To improve the localization accuracy of the robot, inertial localization of the robot is integrated with MMW radar. Based on the concept of inertial localization, the state equation for the motion principle of the robot is deduced. According to principle of MMW localization, the measurement equation is derived, and a kinematics model of the robot is constructed. Further, by applying the Kalman filtering algorithm, a fusion localization system of the robot based on MMWs and inertial localization is proposed. The experimental results show that with iterations of the filtering algorithm, the gain matrix converges gradually, and the error of the fusion localization system decreases, leading to the stable operation of the robot. Compared to the localization system with only MMW radar, the average localization error is approximately reduced from 11 cm to 8 cm, indicating that the fusion localization system has better localization accuracy.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7551: A Fusion Localization System for Security Robots Based on Millimeter Wave Radar and Inertial Sensors</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7551">doi: 10.3390/s24237551</a></p> <p>Authors: Rui Zheng Geng Sun Fang Dong Li </p> <p>In smoggy and dusty environments, vision- and laser-based localization methods are not able to be used effectively for controlling the movement of a robot. Autonomous operation of a security robot can be achieved in such environments by using millimeter wave (MMW) radar for the localization system. In this study, an approximate center method under a sparse point cloud is proposed, and a security robot localization system based on millimeter wave radar is constructed. To improve the localization accuracy of the robot, inertial localization of the robot is integrated with MMW radar. Based on the concept of inertial localization, the state equation for the motion principle of the robot is deduced. According to principle of MMW localization, the measurement equation is derived, and a kinematics model of the robot is constructed. Further, by applying the Kalman filtering algorithm, a fusion localization system of the robot based on MMWs and inertial localization is proposed. The experimental results show that with iterations of the filtering algorithm, the gain matrix converges gradually, and the error of the fusion localization system decreases, leading to the stable operation of the robot. Compared to the localization system with only MMW radar, the average localization error is approximately reduced from 11 cm to 8 cm, indicating that the fusion localization system has better localization accuracy.</p> ]]></content:encoded> <dc:title>A Fusion Localization System for Security Robots Based on Millimeter Wave Radar and Inertial Sensors</dc:title> <dc:creator>Rui Zheng</dc:creator> <dc:creator>Geng Sun</dc:creator> <dc:creator>Fang Dong Li</dc:creator> <dc:identifier>doi: 10.3390/s24237551</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7551</prism:startingPage> <prism:doi>10.3390/s24237551</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7551</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7552"> <title>Sensors, Vol. 24, Pages 7552: Soil Sensor Use in Delimiting Management Zones for Sowing Maize in No-Till</title> <link>https://www.mdpi.com/1424-8220/24/23/7552</link> <description>This study aimed to analyze yield components and maize yield cultivated at different population densities in management zones (MZs) delimited based on mapping the spatial variability of the soil&amp;amp;rsquo;s apparent electrical conductivity (ECa). The soil ECa was measured, and two MZs were subsequently delimited, one with low ECa and the other with high ECa. In each MZ, four maize sowing densities were tested: 60,000 (D1); 80,000 (D2); 100,000 (D3); and 140,000 (D4) seeds ha&amp;amp;minus;1. Ear length, number of grains per ear, number of grains per row, number of rows per ear, thousand-grain weight, and yield were evaluated. The increase in sowing density in the high ECa MZ linearly reduced the values of ear diameter, number of rows per ear, number of grains per ear, and thousand-grain weight. Sowing density D3, when implemented in the low ECa MZ, showed higher values for the ear length, ear diameter, number of grains per row, number of grains per ear, and thousand-grain weight. Sowing density D2 was the one with the highest yield, regardless of the MZ where it was implemented (5628.48 kg ha&amp;amp;minus;1 in the high ECa management zone and 4463.63 kg ha&amp;amp;minus;1 in the low ECa).</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7552: Soil Sensor Use in Delimiting Management Zones for Sowing Maize in No-Till</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7552">doi: 10.3390/s24237552</a></p> <p>Authors: Eduardo Leonel Bottega Ederson Bitencourt Pinto Ezequiel Saretta Zanandra Boff de Oliveira Filipe Silveira Severo Johan Assmann </p> <p>This study aimed to analyze yield components and maize yield cultivated at different population densities in management zones (MZs) delimited based on mapping the spatial variability of the soil&amp;amp;rsquo;s apparent electrical conductivity (ECa). The soil ECa was measured, and two MZs were subsequently delimited, one with low ECa and the other with high ECa. In each MZ, four maize sowing densities were tested: 60,000 (D1); 80,000 (D2); 100,000 (D3); and 140,000 (D4) seeds ha&amp;amp;minus;1. Ear length, number of grains per ear, number of grains per row, number of rows per ear, thousand-grain weight, and yield were evaluated. The increase in sowing density in the high ECa MZ linearly reduced the values of ear diameter, number of rows per ear, number of grains per ear, and thousand-grain weight. Sowing density D3, when implemented in the low ECa MZ, showed higher values for the ear length, ear diameter, number of grains per row, number of grains per ear, and thousand-grain weight. Sowing density D2 was the one with the highest yield, regardless of the MZ where it was implemented (5628.48 kg ha&amp;amp;minus;1 in the high ECa management zone and 4463.63 kg ha&amp;amp;minus;1 in the low ECa).</p> ]]></content:encoded> <dc:title>Soil Sensor Use in Delimiting Management Zones for Sowing Maize in No-Till</dc:title> <dc:creator>Eduardo Leonel Bottega</dc:creator> <dc:creator>Ederson Bitencourt Pinto</dc:creator> <dc:creator>Ezequiel Saretta</dc:creator> <dc:creator>Zanandra Boff de Oliveira</dc:creator> <dc:creator>Filipe Silveira Severo</dc:creator> <dc:creator>Johan Assmann</dc:creator> <dc:identifier>doi: 10.3390/s24237552</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7552</prism:startingPage> <prism:doi>10.3390/s24237552</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7552</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7550"> <title>Sensors, Vol. 24, Pages 7550: A Composite Pulse Excitation Technique for Air-Coupled Ultrasonic Detection of Defects in Wood</title> <link>https://www.mdpi.com/1424-8220/24/23/7550</link> <description>To overcome the problems of the low signal-to-noise ratio and poor performance of wood ultrasonic images caused by ring-down vibrations during the ultrasonic quality detection of wood, a composite pulse excitation technique using a wood air-coupled ultrasonic detection system is proposed. Through a mathematical analysis of the output of the ultrasonic transducer, the conditions necessary for implementing composite pulse excitation were analyzed and established, and its feasibility was verified through COMSOL simulations. Firstly, wood samples with knot and pit defects were used as experimental samples. We refined the parameters for the composite pulse excitation technique by conducting A-scan measurements on both defective and non-defective areas of the samples. Moreover, two stepper motors were employed to control the path for C-scan imaging to detect wood defects. The experiment results showed that the composite pulse excitation technique significantly enhanced the precision of nondestructive ultrasonic testing for wood defects compared to the traditional single-pulse excitation method. This technique successfully achieved precise detection and location of pit defects, with a detection accuracy rate of 90% for knot defects.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7550: A Composite Pulse Excitation Technique for Air-Coupled Ultrasonic Detection of Defects in Wood</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7550">doi: 10.3390/s24237550</a></p> <p>Authors: Jun Wang Changsen Zhang Maocheng Zhao Hongyan Zou Liang Qi Zheng Wang </p> <p>To overcome the problems of the low signal-to-noise ratio and poor performance of wood ultrasonic images caused by ring-down vibrations during the ultrasonic quality detection of wood, a composite pulse excitation technique using a wood air-coupled ultrasonic detection system is proposed. Through a mathematical analysis of the output of the ultrasonic transducer, the conditions necessary for implementing composite pulse excitation were analyzed and established, and its feasibility was verified through COMSOL simulations. Firstly, wood samples with knot and pit defects were used as experimental samples. We refined the parameters for the composite pulse excitation technique by conducting A-scan measurements on both defective and non-defective areas of the samples. Moreover, two stepper motors were employed to control the path for C-scan imaging to detect wood defects. The experiment results showed that the composite pulse excitation technique significantly enhanced the precision of nondestructive ultrasonic testing for wood defects compared to the traditional single-pulse excitation method. This technique successfully achieved precise detection and location of pit defects, with a detection accuracy rate of 90% for knot defects.</p> ]]></content:encoded> <dc:title>A Composite Pulse Excitation Technique for Air-Coupled Ultrasonic Detection of Defects in Wood</dc:title> <dc:creator>Jun Wang</dc:creator> <dc:creator>Changsen Zhang</dc:creator> <dc:creator>Maocheng Zhao</dc:creator> <dc:creator>Hongyan Zou</dc:creator> <dc:creator>Liang Qi</dc:creator> <dc:creator>Zheng Wang</dc:creator> <dc:identifier>doi: 10.3390/s24237550</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7550</prism:startingPage> <prism:doi>10.3390/s24237550</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7550</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7549"> <title>Sensors, Vol. 24, Pages 7549: MCCA-VNet: A Vit-Based Deep Learning Approach for Micro-Expression Recognition Based on Facial Coding</title> <link>https://www.mdpi.com/1424-8220/24/23/7549</link> <description>In terms of facial expressions, micro-expressions are more realistic than macro-expressions and provide more valuable information, which can be widely used in psychological counseling and clinical diagnosis. In the past few years, deep learning methods based on optical flow and Transformer have achieved excellent results in this field, but most of the current algorithms are mainly concentrated on establishing a serialized token through the self-attention model, and they do not take into account the spatial relationship between facial landmarks. For the locality and changes in the micro-facial conditions themselves, we propose the deep learning model MCCA-VNET on the basis of Transformer. We effectively extract the changing features as the input of the model, fusing channel attention and spatial attention into Vision Transformer to capture correlations between features in different dimensions, which enhances the accuracy of the identification of micro-expressions. In order to verify the effectiveness of the algorithm mentioned, we conduct experimental testing in the SAMM, CAS (ME) II, and SMIC datasets and compared the results with other former best algorithms. Our algorithms can improve the UF1 score and UAR score to, respectively, 0.8676 and 0.8622 for the composite dataset, and they are better than other algorithms on multiple indicators, achieving the best comprehensive performance.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7549: MCCA-VNet: A Vit-Based Deep Learning Approach for Micro-Expression Recognition Based on Facial Coding</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7549">doi: 10.3390/s24237549</a></p> <p>Authors: Dehao Zhang Tao Zhang Haijiang Sun Yanhui Tang Qiaoyuan Liu </p> <p>In terms of facial expressions, micro-expressions are more realistic than macro-expressions and provide more valuable information, which can be widely used in psychological counseling and clinical diagnosis. In the past few years, deep learning methods based on optical flow and Transformer have achieved excellent results in this field, but most of the current algorithms are mainly concentrated on establishing a serialized token through the self-attention model, and they do not take into account the spatial relationship between facial landmarks. For the locality and changes in the micro-facial conditions themselves, we propose the deep learning model MCCA-VNET on the basis of Transformer. We effectively extract the changing features as the input of the model, fusing channel attention and spatial attention into Vision Transformer to capture correlations between features in different dimensions, which enhances the accuracy of the identification of micro-expressions. In order to verify the effectiveness of the algorithm mentioned, we conduct experimental testing in the SAMM, CAS (ME) II, and SMIC datasets and compared the results with other former best algorithms. Our algorithms can improve the UF1 score and UAR score to, respectively, 0.8676 and 0.8622 for the composite dataset, and they are better than other algorithms on multiple indicators, achieving the best comprehensive performance.</p> ]]></content:encoded> <dc:title>MCCA-VNet: A Vit-Based Deep Learning Approach for Micro-Expression Recognition Based on Facial Coding</dc:title> <dc:creator>Dehao Zhang</dc:creator> <dc:creator>Tao Zhang</dc:creator> <dc:creator>Haijiang Sun</dc:creator> <dc:creator>Yanhui Tang</dc:creator> <dc:creator>Qiaoyuan Liu</dc:creator> <dc:identifier>doi: 10.3390/s24237549</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7549</prism:startingPage> <prism:doi>10.3390/s24237549</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7549</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7548"> <title>Sensors, Vol. 24, Pages 7548: Adaptive Beamforming, Cell-Free Resource Allocation and NOMA in Large-Scale Wireless Networks</title> <link>https://www.mdpi.com/1424-8220/24/23/7548</link> <description>The goal of the study presented in this work is to evaluate the performance of a proposed adaptive beamforming approach when combined with non-orthogonal multiple access (NOMA) in cell-free massive multiple input multiple output (CF m-MIMO) orientations. In this context, cooperative beamforming is employed taking into consideration the geographically adjacent access points (APs) of a virtual cell, aiming to minimize co-channel interference (CCI) among mobile stations (MSs) participating in NOMA transmission. Performance is evaluated statistically via extensive Monte Carlo (MC) simulations in a two-tier wireless orientation. As the results indicate, for high data rate services, various key performance indicators (KPIs) can be improved compared to orthogonal multiple access, such as the minimum number of users in the topology as well as the available PRBs for downlink transmission. Although in NOMA transmission more directional beamforming configurations are required to compensate for the increased CCI levels, the increase in the number of hardware elements is reduced compared to the corresponding gain in the considered KPIs.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7548: Adaptive Beamforming, Cell-Free Resource Allocation and NOMA in Large-Scale Wireless Networks</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7548">doi: 10.3390/s24237548</a></p> <p>Authors: Gkonis Lavdas Vardoulias Trakadas Sarakis Papadopoulos </p> <p>The goal of the study presented in this work is to evaluate the performance of a proposed adaptive beamforming approach when combined with non-orthogonal multiple access (NOMA) in cell-free massive multiple input multiple output (CF m-MIMO) orientations. In this context, cooperative beamforming is employed taking into consideration the geographically adjacent access points (APs) of a virtual cell, aiming to minimize co-channel interference (CCI) among mobile stations (MSs) participating in NOMA transmission. Performance is evaluated statistically via extensive Monte Carlo (MC) simulations in a two-tier wireless orientation. As the results indicate, for high data rate services, various key performance indicators (KPIs) can be improved compared to orthogonal multiple access, such as the minimum number of users in the topology as well as the available PRBs for downlink transmission. Although in NOMA transmission more directional beamforming configurations are required to compensate for the increased CCI levels, the increase in the number of hardware elements is reduced compared to the corresponding gain in the considered KPIs.</p> ]]></content:encoded> <dc:title>Adaptive Beamforming, Cell-Free Resource Allocation and NOMA in Large-Scale Wireless Networks</dc:title> <dc:creator> Gkonis</dc:creator> <dc:creator> Lavdas</dc:creator> <dc:creator> Vardoulias</dc:creator> <dc:creator> Trakadas</dc:creator> <dc:creator> Sarakis</dc:creator> <dc:creator> Papadopoulos</dc:creator> <dc:identifier>doi: 10.3390/s24237548</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7548</prism:startingPage> <prism:doi>10.3390/s24237548</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7548</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7547"> <title>Sensors, Vol. 24, Pages 7547: Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy</title> <link>https://www.mdpi.com/1424-8220/24/23/7547</link> <description>The market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-infrared (vis/NIR) spectroscopy was tested in discriminating pesticide-free against pesticide-treated lettuce plants. Two commercial fungicides (mancozeb and fosetyl-al) and two insecticides (deltamethrin and imidacloprid) were applied as spray solutions at the recommended rates on baby leaf lettuce plants. Untreated-control plants were sprayed with water. Reflectance data in the wavelength range 400&amp;amp;ndash;2500 nm were captured on leaf samples until harvest on the 10th day upon pesticide application, as well as after 4 and 8 days during post-harvest storage at 5 &amp;amp;deg;C. In addition, biochemical components in leaf tissue were also determined during storage, such as antioxidant enzymes&amp;amp;rsquo; activities (peroxidase [POD], catalase [CAT], and ascorbate peroxidase [APX]), along with malondialdehyde [MDA] and hydrogen peroxide [H2O2] content. Partial least square discriminant analysis (PLSDA) combined with feature-selection techniques was implemented, in order to classify baby lettuce tissue into pesticide-free or pesticide-treated ones. The genetic algorithm (GA) and the variable importance in projection (VIP) scores identified eleven distinct regions and nine specific wavelengths that exhibited the most significant effect in the detection models, with most of them in the near-infrared region of the electromagnetic spectrum. According to the results, the classification accuracy of discriminating pesticide-treated against non-treated lettuce leaves ranged from 94% to 99% in both pre-harvest and post-harvest periods. Although there were no significant differences in enzyme activities or H2O2, the MDA content in pesticide-treated tissue was greater than in untreated ones, implying that the chemical spray application probably induced a stress response in the plant that was disclosed with the reflected energy. In conclusion, vis/NIR spectroscopy appears as a promising, reliable, rapid, and non-destructive tool in distinguishing pesticide-free from pesticide-treated lettuce products.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7547: Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7547">doi: 10.3390/s24237547</a></p> <p>Authors: Dimitrios S. Kasampalis Pavlos I. Tsouvaltzis Anastasios S. Siomos </p> <p>The market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-infrared (vis/NIR) spectroscopy was tested in discriminating pesticide-free against pesticide-treated lettuce plants. Two commercial fungicides (mancozeb and fosetyl-al) and two insecticides (deltamethrin and imidacloprid) were applied as spray solutions at the recommended rates on baby leaf lettuce plants. Untreated-control plants were sprayed with water. Reflectance data in the wavelength range 400&amp;amp;ndash;2500 nm were captured on leaf samples until harvest on the 10th day upon pesticide application, as well as after 4 and 8 days during post-harvest storage at 5 &amp;amp;deg;C. In addition, biochemical components in leaf tissue were also determined during storage, such as antioxidant enzymes&amp;amp;rsquo; activities (peroxidase [POD], catalase [CAT], and ascorbate peroxidase [APX]), along with malondialdehyde [MDA] and hydrogen peroxide [H2O2] content. Partial least square discriminant analysis (PLSDA) combined with feature-selection techniques was implemented, in order to classify baby lettuce tissue into pesticide-free or pesticide-treated ones. The genetic algorithm (GA) and the variable importance in projection (VIP) scores identified eleven distinct regions and nine specific wavelengths that exhibited the most significant effect in the detection models, with most of them in the near-infrared region of the electromagnetic spectrum. According to the results, the classification accuracy of discriminating pesticide-treated against non-treated lettuce leaves ranged from 94% to 99% in both pre-harvest and post-harvest periods. Although there were no significant differences in enzyme activities or H2O2, the MDA content in pesticide-treated tissue was greater than in untreated ones, implying that the chemical spray application probably induced a stress response in the plant that was disclosed with the reflected energy. In conclusion, vis/NIR spectroscopy appears as a promising, reliable, rapid, and non-destructive tool in distinguishing pesticide-free from pesticide-treated lettuce products.</p> ]]></content:encoded> <dc:title>Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy</dc:title> <dc:creator>Dimitrios S. Kasampalis</dc:creator> <dc:creator>Pavlos I. Tsouvaltzis</dc:creator> <dc:creator>Anastasios S. Siomos</dc:creator> <dc:identifier>doi: 10.3390/s24237547</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7547</prism:startingPage> <prism:doi>10.3390/s24237547</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7547</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7546"> <title>Sensors, Vol. 24, Pages 7546: LIO-SAM++: A Lidar-Inertial Semantic SLAM with Association Optimization and Keyframe Selection</title> <link>https://www.mdpi.com/1424-8220/24/23/7546</link> <description>Current lidar-inertial SLAM algorithms mainly rely on the geometric features of the lidar for point cloud alignment. The issue of incorrect feature association arises because the matching process is susceptible to influences such as dynamic objects, occlusion, and environmental changes. To address this issue, we present a lidar-inertial SLAM system based on the LIO-SAM framework, combining semantic and geometric constraints for association optimization and keyframe selection. Specifically, we mitigate the impact of erroneous matching points on pose estimation by comparing the consistency of normal vectors in the surrounding region. Additionally, we incorporate semantic information to establish semantic constraints, further enhancing matching accuracy. Furthermore, we propose an adaptive selection strategy based on semantic differences between frames to improve the reliability of keyframe generation. Experimental results on the KITTI dataset indicate that, compared to other systems, the accuracy of the pose estimation has significantly improved.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7546: LIO-SAM++: A Lidar-Inertial Semantic SLAM with Association Optimization and Keyframe Selection</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7546">doi: 10.3390/s24237546</a></p> <p>Authors: Bingke Shen Wenming Xie Xiaodong Peng Xiaoning Qiao Zhiyuan Guo </p> <p>Current lidar-inertial SLAM algorithms mainly rely on the geometric features of the lidar for point cloud alignment. The issue of incorrect feature association arises because the matching process is susceptible to influences such as dynamic objects, occlusion, and environmental changes. To address this issue, we present a lidar-inertial SLAM system based on the LIO-SAM framework, combining semantic and geometric constraints for association optimization and keyframe selection. Specifically, we mitigate the impact of erroneous matching points on pose estimation by comparing the consistency of normal vectors in the surrounding region. Additionally, we incorporate semantic information to establish semantic constraints, further enhancing matching accuracy. Furthermore, we propose an adaptive selection strategy based on semantic differences between frames to improve the reliability of keyframe generation. Experimental results on the KITTI dataset indicate that, compared to other systems, the accuracy of the pose estimation has significantly improved.</p> ]]></content:encoded> <dc:title>LIO-SAM++: A Lidar-Inertial Semantic SLAM with Association Optimization and Keyframe Selection</dc:title> <dc:creator>Bingke Shen</dc:creator> <dc:creator>Wenming Xie</dc:creator> <dc:creator>Xiaodong Peng</dc:creator> <dc:creator>Xiaoning Qiao</dc:creator> <dc:creator>Zhiyuan Guo</dc:creator> <dc:identifier>doi: 10.3390/s24237546</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7546</prism:startingPage> <prism:doi>10.3390/s24237546</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7546</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7545"> <title>Sensors, Vol. 24, Pages 7545: An Optimized SVR Algorithm for Pulse Pile-Up Correction in Pulse Shape Discrimination</title> <link>https://www.mdpi.com/1424-8220/24/23/7545</link> <description>Pulse pile-up presents a significant challenge in nuclear radiation measurements, particularly in neutron-gamma pulse shape discrimination, as it causes pulse distortion and diminishes identification accuracy. To address this, we propose an optimized Support Vector Regression (SVR) algorithm for correcting pulse pile-up. Initially, the Dung Beetle Optimizer (DBO) and Whale Optimization Algorithm (WOA) are integrated to refine the correction process, with performance evaluated using charge comparison methods (CCM) for pulse shape discrimination. Leveraging prior knowledge from simulated data, we further analyze the relationships between various types of pulse pile-ups, including their combinations, inter-peak distances, and the accuracy of corrections. Extensive experiments conducted in a mixed neutron-gamma radiation field using plastic scintillators demonstrate that the proposed method effectively corrects pulse pile-up and accurately discriminates between neutron and gamma. Moreover, our approach significantly improves the fidelity of pulse shape discrimination and enhances the overall reliability of radiation detection systems in high-interference environments.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7545: An Optimized SVR Algorithm for Pulse Pile-Up Correction in Pulse Shape Discrimination</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7545">doi: 10.3390/s24237545</a></p> <p>Authors: Xianghe Liu Bingqi Liu Mingzhe Liu Yufeng Tang Haonan Li Yao Huang </p> <p>Pulse pile-up presents a significant challenge in nuclear radiation measurements, particularly in neutron-gamma pulse shape discrimination, as it causes pulse distortion and diminishes identification accuracy. To address this, we propose an optimized Support Vector Regression (SVR) algorithm for correcting pulse pile-up. Initially, the Dung Beetle Optimizer (DBO) and Whale Optimization Algorithm (WOA) are integrated to refine the correction process, with performance evaluated using charge comparison methods (CCM) for pulse shape discrimination. Leveraging prior knowledge from simulated data, we further analyze the relationships between various types of pulse pile-ups, including their combinations, inter-peak distances, and the accuracy of corrections. Extensive experiments conducted in a mixed neutron-gamma radiation field using plastic scintillators demonstrate that the proposed method effectively corrects pulse pile-up and accurately discriminates between neutron and gamma. Moreover, our approach significantly improves the fidelity of pulse shape discrimination and enhances the overall reliability of radiation detection systems in high-interference environments.</p> ]]></content:encoded> <dc:title>An Optimized SVR Algorithm for Pulse Pile-Up Correction in Pulse Shape Discrimination</dc:title> <dc:creator>Xianghe Liu</dc:creator> <dc:creator>Bingqi Liu</dc:creator> <dc:creator>Mingzhe Liu</dc:creator> <dc:creator>Yufeng Tang</dc:creator> <dc:creator>Haonan Li</dc:creator> <dc:creator>Yao Huang</dc:creator> <dc:identifier>doi: 10.3390/s24237545</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7545</prism:startingPage> <prism:doi>10.3390/s24237545</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7545</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7544"> <title>Sensors, Vol. 24, Pages 7544: Development of an Integrating Sphere-Based Wide-Range Light Source System for the Linearity Evaluation of a Photodetector Used in Radiation Detection and Bioanalysis Instruments</title> <link>https://www.mdpi.com/1424-8220/24/23/7544</link> <description>We developed a compact wide-range light source system for evaluating the linearity of photomultiplier tube (PMT) output. This system utilizes two integrating spheres equipped with a continuously variable slit and output aperture to modulate a stabilized light-emitting diode light source, producing an output light range as wide as seven orders of magnitude. To verify the wide linearity range of the integrating sphere system, three silicon photodiodes coupled with electric current readers monitored the light intensity and simultaneously confirmed each other&amp;amp;rsquo;s linearity. Using this system, we evaluated the linearity of the PMT used in a neutron detector we are currently developing and found it to have a linear range of more than four orders of magnitude. Non-linearity characteristics were also successfully measured in detail at a higher output range. Neutron detector operation requires both calibration of the detection efficiency and evaluation of the linearity between the neutron dose and its output. These results indicate that this system is a simple and useful method to evaluate the linearity of photodetectors used in radiation detectors and other applications.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7544: Development of an Integrating Sphere-Based Wide-Range Light Source System for the Linearity Evaluation of a Photodetector Used in Radiation Detection and Bioanalysis Instruments</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7544">doi: 10.3390/s24237544</a></p> <p>Authors: Tetsuro Matsumoto Akihiko Masuda Minoru Tanabe Seiya Manabe Hideki Harano Kazuki Niwa </p> <p>We developed a compact wide-range light source system for evaluating the linearity of photomultiplier tube (PMT) output. This system utilizes two integrating spheres equipped with a continuously variable slit and output aperture to modulate a stabilized light-emitting diode light source, producing an output light range as wide as seven orders of magnitude. To verify the wide linearity range of the integrating sphere system, three silicon photodiodes coupled with electric current readers monitored the light intensity and simultaneously confirmed each other&amp;amp;rsquo;s linearity. Using this system, we evaluated the linearity of the PMT used in a neutron detector we are currently developing and found it to have a linear range of more than four orders of magnitude. Non-linearity characteristics were also successfully measured in detail at a higher output range. Neutron detector operation requires both calibration of the detection efficiency and evaluation of the linearity between the neutron dose and its output. These results indicate that this system is a simple and useful method to evaluate the linearity of photodetectors used in radiation detectors and other applications.</p> ]]></content:encoded> <dc:title>Development of an Integrating Sphere-Based Wide-Range Light Source System for the Linearity Evaluation of a Photodetector Used in Radiation Detection and Bioanalysis Instruments</dc:title> <dc:creator>Tetsuro Matsumoto</dc:creator> <dc:creator>Akihiko Masuda</dc:creator> <dc:creator>Minoru Tanabe</dc:creator> <dc:creator>Seiya Manabe</dc:creator> <dc:creator>Hideki Harano</dc:creator> <dc:creator>Kazuki Niwa</dc:creator> <dc:identifier>doi: 10.3390/s24237544</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7544</prism:startingPage> <prism:doi>10.3390/s24237544</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7544</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7543"> <title>Sensors, Vol. 24, Pages 7543: Optimizing Dielectric Rod Antenna Performance with Spoof Surface Plasmon Polariton-Based Feeding Method</title> <link>https://www.mdpi.com/1424-8220/24/23/7543</link> <description>This study investigates the use of spoof surface plasmon polaritons (SSPPs) as an effective feeding mechanism for antennas functioning within the extremely high-frequency (EHF) range. A novel method is proposed for feeding a dielectric rod antenna with SSPPs, featuring a simple design made from FR-4 material with a relative permittivity of 4.3. In contrast to traditional tapered dielectric rod antennas and their feeding configurations, this design shows promise for achieving a gain of up to 16.85 dBi with an antenna length of 7.6 &amp;amp;lambda;0. By carefully optimizing the design, impedance matching and directional radiation characteristics were obtained at 7.3 GHz. Simulations were conducted using CST Microwave Studio to validate and evaluate the design&amp;amp;rsquo;s performance. The enhanced gain, improved impedance bandwidth, and use of cost-effective materials such as FR-4 present a compelling case for adopting this design in future wireless communication technologies. Additionally, the remote sensing properties of the feeder can be utilized for concealed object detection, material characterization, and the analysis of the spectral properties of materials.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7543: Optimizing Dielectric Rod Antenna Performance with Spoof Surface Plasmon Polariton-Based Feeding Method</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7543">doi: 10.3390/s24237543</a></p> <p>Authors: Rishitej Chaparala Shaik Imamvali Sreenivasulu Tupakula Mohammad Aljaidi Shonak Bansal Krishna Prakash Ali Fayez Alkoradees </p> <p>This study investigates the use of spoof surface plasmon polaritons (SSPPs) as an effective feeding mechanism for antennas functioning within the extremely high-frequency (EHF) range. A novel method is proposed for feeding a dielectric rod antenna with SSPPs, featuring a simple design made from FR-4 material with a relative permittivity of 4.3. In contrast to traditional tapered dielectric rod antennas and their feeding configurations, this design shows promise for achieving a gain of up to 16.85 dBi with an antenna length of 7.6 &amp;amp;lambda;0. By carefully optimizing the design, impedance matching and directional radiation characteristics were obtained at 7.3 GHz. Simulations were conducted using CST Microwave Studio to validate and evaluate the design&amp;amp;rsquo;s performance. The enhanced gain, improved impedance bandwidth, and use of cost-effective materials such as FR-4 present a compelling case for adopting this design in future wireless communication technologies. Additionally, the remote sensing properties of the feeder can be utilized for concealed object detection, material characterization, and the analysis of the spectral properties of materials.</p> ]]></content:encoded> <dc:title>Optimizing Dielectric Rod Antenna Performance with Spoof Surface Plasmon Polariton-Based Feeding Method</dc:title> <dc:creator>Rishitej Chaparala</dc:creator> <dc:creator>Shaik Imamvali</dc:creator> <dc:creator>Sreenivasulu Tupakula</dc:creator> <dc:creator>Mohammad Aljaidi</dc:creator> <dc:creator>Shonak Bansal</dc:creator> <dc:creator>Krishna Prakash</dc:creator> <dc:creator>Ali Fayez Alkoradees</dc:creator> <dc:identifier>doi: 10.3390/s24237543</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7543</prism:startingPage> <prism:doi>10.3390/s24237543</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7543</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7537"> <title>Sensors, Vol. 24, Pages 7537: Integrating Remote Photoplethysmography and Machine Learning on Multimodal Dataset for Noninvasive Heart Rate Monitoring</title> <link>https://www.mdpi.com/1424-8220/24/23/7537</link> <description>Non-contact heart monitoring is crucial in advancing telemedicine, fitness tracking, and mass screening. Remote photoplethysmography (rPPG) is a non-contact technique to obtain information about heart pulse by analyzing the changes in the light intensity reflected or absorbed by the skin during the blood circulation cycle. However, this technique is sensitive to environmental lightning and different skin pigmentation, resulting in unreliable results. This research presents a multimodal approach to non-contact heart rate estimation by combining facial video and physical attributes, including age, gender, weight, height, and body mass index (BMI). For this purpose, we collected local datasets from 60 individuals containing a 1 min facial video and physical attributes such as age, gender, weight, and height, and we derived the BMI variable from the weight and height. We compare the performance of two machine learning models, support vector regression (SVR) and random forest regression on the multimodal dataset. The experimental results demonstrate that incorporating a multimodal approach enhances model performance, with the random forest model achieving superior results, yielding a mean absolute error (MAE) of 3.057 bpm, a root mean squared error (RMSE) of 10.532 bpm, and a mean absolute percentage error (MAPE) of 4.2% that outperforms the state-of-the-art rPPG methods. These findings highlight the potential for interpretable, non-contact, real-time heart rate measurement systems to contribute effectively to applications in telemedicine and mass screening.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7537: Integrating Remote Photoplethysmography and Machine Learning on Multimodal Dataset for Noninvasive Heart Rate Monitoring</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7537">doi: 10.3390/s24237537</a></p> <p>Authors: Rinaldi Anwar Buyung Alhadi Bustamam Muhammad Remzy Syah Ramazhan </p> <p>Non-contact heart monitoring is crucial in advancing telemedicine, fitness tracking, and mass screening. Remote photoplethysmography (rPPG) is a non-contact technique to obtain information about heart pulse by analyzing the changes in the light intensity reflected or absorbed by the skin during the blood circulation cycle. However, this technique is sensitive to environmental lightning and different skin pigmentation, resulting in unreliable results. This research presents a multimodal approach to non-contact heart rate estimation by combining facial video and physical attributes, including age, gender, weight, height, and body mass index (BMI). For this purpose, we collected local datasets from 60 individuals containing a 1 min facial video and physical attributes such as age, gender, weight, and height, and we derived the BMI variable from the weight and height. We compare the performance of two machine learning models, support vector regression (SVR) and random forest regression on the multimodal dataset. The experimental results demonstrate that incorporating a multimodal approach enhances model performance, with the random forest model achieving superior results, yielding a mean absolute error (MAE) of 3.057 bpm, a root mean squared error (RMSE) of 10.532 bpm, and a mean absolute percentage error (MAPE) of 4.2% that outperforms the state-of-the-art rPPG methods. These findings highlight the potential for interpretable, non-contact, real-time heart rate measurement systems to contribute effectively to applications in telemedicine and mass screening.</p> ]]></content:encoded> <dc:title>Integrating Remote Photoplethysmography and Machine Learning on Multimodal Dataset for Noninvasive Heart Rate Monitoring</dc:title> <dc:creator>Rinaldi Anwar Buyung</dc:creator> <dc:creator>Alhadi Bustamam</dc:creator> <dc:creator>Muhammad Remzy Syah Ramazhan</dc:creator> <dc:identifier>doi: 10.3390/s24237537</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7537</prism:startingPage> <prism:doi>10.3390/s24237537</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7537</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7542"> <title>Sensors, Vol. 24, Pages 7542: Metrology-Assisted Production in Agriculture and Forestry</title> <link>https://www.mdpi.com/1424-8220/24/23/7542</link> <description>According to the Food and Agriculture Organization of the United Nations, climate change will negatively affect food security and increase pressure on freshwater resources [...]</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7542: Metrology-Assisted Production in Agriculture and Forestry</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7542">doi: 10.3390/s24237542</a></p> <p>Authors: H. R. Bogena C. Brogi C. H眉bner A. Panagopoulos </p> <p>According to the Food and Agriculture Organization of the United Nations, climate change will negatively affect food security and increase pressure on freshwater resources [...]</p> ]]></content:encoded> <dc:title>Metrology-Assisted Production in Agriculture and Forestry</dc:title> <dc:creator>H. R. Bogena</dc:creator> <dc:creator>C. Brogi</dc:creator> <dc:creator>C. H眉bner</dc:creator> <dc:creator>A. Panagopoulos</dc:creator> <dc:identifier>doi: 10.3390/s24237542</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Editorial</prism:section> <prism:startingPage>7542</prism:startingPage> <prism:doi>10.3390/s24237542</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7542</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7541"> <title>Sensors, Vol. 24, Pages 7541: Exploring the Psychological and Physiological Effects of Operating a Telenoid: The Preliminary Assessment of a Minimal Humanoid Robot for Mediated Communication</title> <link>https://www.mdpi.com/1424-8220/24/23/7541</link> <description>Background: As the Internet of Things (IoT) expands, it enables new forms of communication, including interactions mediated by teleoperated robots like avatars. While extensive research exists on the effects of these devices on communication partners, there is limited research on the impact on the operators themselves. This study aimed to objectively assess the psychological and physiological effects of operating a teleoperated robot, specifically Telenoid, on its human operator. Methods: Twelve healthy participants (2 women and 10 men, aged 18&amp;amp;ndash;23 years) were recruited from Osaka University. Participants engaged in two communication sessions with a first-time partner: face-to-face and Telenoid-mediated. Telenoid is a minimalist humanoid robot teleoperated by a participant. Blood samples were collected before and after each session to measure hormonal and oxidative markers, including cortisol, diacron reactive oxygen metabolites (d-ROMs), and the biological antioxidat activity of plasma (BAP). Psychological stress was assessed using validated questionnaires (POMS-2, HADS, and SRS-18). Results: A trend of a decrease in cortisol levels was observed during Telenoid-mediated communication, whereas face-to-face interactions showed no significant changes. Oxidative stress, measured by d-ROMs, significantly increased after face-to-face interactions but not in Telenoid-mediated sessions. Significant correlations were found between oxytocin and d-ROMs and psychological stress scores, particularly in terms of helplessness and total stress measures. However, no significant changes were observed in other biomarkers or between the two conditions for most psychological measures. Conclusions: These findings suggest that cortisol and d-ROMs may serve as objective biomarkers for assessing psychophysiological stress during robot-mediated communication. Telenoid&amp;amp;rsquo;s minimalist design may help reduce social pressures and mitigate stress compared to face-to-face interactions. Further research with larger, more diverse samples and longitudinal designs is needed to validate these findings and explore the broader impacts of teleoperated robots.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7541: Exploring the Psychological and Physiological Effects of Operating a Telenoid: The Preliminary Assessment of a Minimal Humanoid Robot for Mediated Communication</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7541">doi: 10.3390/s24237541</a></p> <p>Authors: Aya Nakae Hani M. Bu-Omer Wei-Chuan Chang Chie Kishimoto Hidenobu Sumioka </p> <p>Background: As the Internet of Things (IoT) expands, it enables new forms of communication, including interactions mediated by teleoperated robots like avatars. While extensive research exists on the effects of these devices on communication partners, there is limited research on the impact on the operators themselves. This study aimed to objectively assess the psychological and physiological effects of operating a teleoperated robot, specifically Telenoid, on its human operator. Methods: Twelve healthy participants (2 women and 10 men, aged 18&amp;amp;ndash;23 years) were recruited from Osaka University. Participants engaged in two communication sessions with a first-time partner: face-to-face and Telenoid-mediated. Telenoid is a minimalist humanoid robot teleoperated by a participant. Blood samples were collected before and after each session to measure hormonal and oxidative markers, including cortisol, diacron reactive oxygen metabolites (d-ROMs), and the biological antioxidat activity of plasma (BAP). Psychological stress was assessed using validated questionnaires (POMS-2, HADS, and SRS-18). Results: A trend of a decrease in cortisol levels was observed during Telenoid-mediated communication, whereas face-to-face interactions showed no significant changes. Oxidative stress, measured by d-ROMs, significantly increased after face-to-face interactions but not in Telenoid-mediated sessions. Significant correlations were found between oxytocin and d-ROMs and psychological stress scores, particularly in terms of helplessness and total stress measures. However, no significant changes were observed in other biomarkers or between the two conditions for most psychological measures. Conclusions: These findings suggest that cortisol and d-ROMs may serve as objective biomarkers for assessing psychophysiological stress during robot-mediated communication. Telenoid&amp;amp;rsquo;s minimalist design may help reduce social pressures and mitigate stress compared to face-to-face interactions. Further research with larger, more diverse samples and longitudinal designs is needed to validate these findings and explore the broader impacts of teleoperated robots.</p> ]]></content:encoded> <dc:title>Exploring the Psychological and Physiological Effects of Operating a Telenoid: The Preliminary Assessment of a Minimal Humanoid Robot for Mediated Communication</dc:title> <dc:creator>Aya Nakae</dc:creator> <dc:creator>Hani M. Bu-Omer</dc:creator> <dc:creator>Wei-Chuan Chang</dc:creator> <dc:creator>Chie Kishimoto</dc:creator> <dc:creator>Hidenobu Sumioka</dc:creator> <dc:identifier>doi: 10.3390/s24237541</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7541</prism:startingPage> <prism:doi>10.3390/s24237541</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7541</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7540"> <title>Sensors, Vol. 24, Pages 7540: Planetary Gearboxes Fault Diagnosis Based on Markov Transition Fields and SE-ResNet</title> <link>https://www.mdpi.com/1424-8220/24/23/7540</link> <description>The working conditions of planetary gearboxes are complex, and their structural couplings are strong, leading to low reliability. Traditional deep neural networks often struggle with feature learning in noisy environments, and their reliance on one-dimensional signals as input fails to capture the interrelationships between data points. To address these challenges, we proposed a fault diagnosis method for planetary gearboxes that integrates Markov transition fields (MTFs) and a residual attention mechanism. The MTF was employed to encode one-dimensional signals into feature maps, which were then fed into a residual networks (ResNet) architecture. To enhance the network&amp;amp;rsquo;s ability to focus on important features, we embedded the squeeze-and-excitation (SE) channel attention mechanism into the ResNet34 network, creating a SE-ResNet model. This model was trained to effectively extract and classify features. The developed method was validated using a specific dataset and achieved an accuracy of about 98.1%. The results demonstrate the effectiveness and reliability of the developed method in diagnosing faults in planetary gearboxes under strong noise conditions.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7540: Planetary Gearboxes Fault Diagnosis Based on Markov Transition Fields and SE-ResNet</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7540">doi: 10.3390/s24237540</a></p> <p>Authors: Yanyan Liu Tongxin Gao Wenxu Wu Yongquan Sun </p> <p>The working conditions of planetary gearboxes are complex, and their structural couplings are strong, leading to low reliability. Traditional deep neural networks often struggle with feature learning in noisy environments, and their reliance on one-dimensional signals as input fails to capture the interrelationships between data points. To address these challenges, we proposed a fault diagnosis method for planetary gearboxes that integrates Markov transition fields (MTFs) and a residual attention mechanism. The MTF was employed to encode one-dimensional signals into feature maps, which were then fed into a residual networks (ResNet) architecture. To enhance the network&amp;amp;rsquo;s ability to focus on important features, we embedded the squeeze-and-excitation (SE) channel attention mechanism into the ResNet34 network, creating a SE-ResNet model. This model was trained to effectively extract and classify features. The developed method was validated using a specific dataset and achieved an accuracy of about 98.1%. The results demonstrate the effectiveness and reliability of the developed method in diagnosing faults in planetary gearboxes under strong noise conditions.</p> ]]></content:encoded> <dc:title>Planetary Gearboxes Fault Diagnosis Based on Markov Transition Fields and SE-ResNet</dc:title> <dc:creator>Yanyan Liu</dc:creator> <dc:creator>Tongxin Gao</dc:creator> <dc:creator>Wenxu Wu</dc:creator> <dc:creator>Yongquan Sun</dc:creator> <dc:identifier>doi: 10.3390/s24237540</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7540</prism:startingPage> <prism:doi>10.3390/s24237540</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7540</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7539"> <title>Sensors, Vol. 24, Pages 7539: Calibrated Adaptive Teacher for Domain-Adaptive Intelligent Fault Diagnosis</title> <link>https://www.mdpi.com/1424-8220/24/23/7539</link> <description>Intelligent fault diagnosis (IFD) based on deep learning can achieve high accuracy from raw condition monitoring signals. However, models usually perform well on the training distribution only, and experience severe performance drops when applied to a different distribution. This is also observed in fault diagnosis, where assets are often operated in working conditions different from the ones in which the labeled data have been collected. The scenario where labeled data are available in a source domain and only unlabeled data are available in a target domain has been addressed recently by unsupervised domain adaptation (UDA) approaches for IFD. Recent methods have relied on self-training with confident pseudo-labels for the unlabeled target samples. However, the confidence-based selection of pseudo-labels is hindered by poorly calibrated uncertainty estimates in the target domain, primarily due to over-confident predictions, which limits the quality of pseudo-labels and leads to error accumulation. In this paper, we propose a novel method called Calibrated Adaptive Teacher (CAT), where we propose to calibrate the predictions of the teacher network on target samples throughout the self-training process, leveraging post hoc calibration techniques. We evaluate CAT on domain-adaptive IFD and perform extensive experiments on the Paderborn University (PU) benchmark for fault diagnosis of rolling bearings under varying operating conditions, using both time- and frequency-domain inputs. We compare four different calibration techniques within our framework, where temperature scaling is both the most effective and lightweight one. The resulting method&amp;amp;mdash;CAT+TempScaling&amp;amp;mdash;achieves state-of-the-art performance on most transfer tasks, with on average 7.5% higher accuracy and 4 times lower calibration error compared to domain-adversarial neural networks (DANNs) across the twelve PU transfer tasks.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7539: Calibrated Adaptive Teacher for Domain-Adaptive Intelligent Fault Diagnosis</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7539">doi: 10.3390/s24237539</a></p> <p>Authors: Florent Forest Olga Fink </p> <p>Intelligent fault diagnosis (IFD) based on deep learning can achieve high accuracy from raw condition monitoring signals. However, models usually perform well on the training distribution only, and experience severe performance drops when applied to a different distribution. This is also observed in fault diagnosis, where assets are often operated in working conditions different from the ones in which the labeled data have been collected. The scenario where labeled data are available in a source domain and only unlabeled data are available in a target domain has been addressed recently by unsupervised domain adaptation (UDA) approaches for IFD. Recent methods have relied on self-training with confident pseudo-labels for the unlabeled target samples. However, the confidence-based selection of pseudo-labels is hindered by poorly calibrated uncertainty estimates in the target domain, primarily due to over-confident predictions, which limits the quality of pseudo-labels and leads to error accumulation. In this paper, we propose a novel method called Calibrated Adaptive Teacher (CAT), where we propose to calibrate the predictions of the teacher network on target samples throughout the self-training process, leveraging post hoc calibration techniques. We evaluate CAT on domain-adaptive IFD and perform extensive experiments on the Paderborn University (PU) benchmark for fault diagnosis of rolling bearings under varying operating conditions, using both time- and frequency-domain inputs. We compare four different calibration techniques within our framework, where temperature scaling is both the most effective and lightweight one. The resulting method&amp;amp;mdash;CAT+TempScaling&amp;amp;mdash;achieves state-of-the-art performance on most transfer tasks, with on average 7.5% higher accuracy and 4 times lower calibration error compared to domain-adversarial neural networks (DANNs) across the twelve PU transfer tasks.</p> ]]></content:encoded> <dc:title>Calibrated Adaptive Teacher for Domain-Adaptive Intelligent Fault Diagnosis</dc:title> <dc:creator>Florent Forest</dc:creator> <dc:creator>Olga Fink</dc:creator> <dc:identifier>doi: 10.3390/s24237539</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7539</prism:startingPage> <prism:doi>10.3390/s24237539</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7539</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7538"> <title>Sensors, Vol. 24, Pages 7538: Exploring rounD Dataset for Domain Generalization in Autonomous Vehicle Trajectory Prediction</title> <link>https://www.mdpi.com/1424-8220/24/23/7538</link> <description>This paper analyzes the rounD dataset to advance motion forecasting algorithms for autonomous vehicles navigating complex roundabout environments. We develop a trajectory prediction framework inspired by Gated Recurrent Unit (GRU) networks and graph-based modules to effectively model vehicle interactions. Our primary objective is to evaluate the generalizability of the proposed model across diverse training and testing datasets. Through extensive experiments, we investigate how varying data distributions&amp;amp;mdash;such as different road configurations and recording times&amp;amp;mdash;impact the model&amp;amp;rsquo;s prediction accuracy and robustness. This study provides key insights into the challenges of domain generalization in autonomous vehicle trajectory prediction.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7538: Exploring rounD Dataset for Domain Generalization in Autonomous Vehicle Trajectory Prediction</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7538">doi: 10.3390/s24237538</a></p> <p>Authors: Zikai Zhang </p> <p>This paper analyzes the rounD dataset to advance motion forecasting algorithms for autonomous vehicles navigating complex roundabout environments. We develop a trajectory prediction framework inspired by Gated Recurrent Unit (GRU) networks and graph-based modules to effectively model vehicle interactions. Our primary objective is to evaluate the generalizability of the proposed model across diverse training and testing datasets. Through extensive experiments, we investigate how varying data distributions&amp;amp;mdash;such as different road configurations and recording times&amp;amp;mdash;impact the model&amp;amp;rsquo;s prediction accuracy and robustness. This study provides key insights into the challenges of domain generalization in autonomous vehicle trajectory prediction.</p> ]]></content:encoded> <dc:title>Exploring rounD Dataset for Domain Generalization in Autonomous Vehicle Trajectory Prediction</dc:title> <dc:creator>Zikai Zhang</dc:creator> <dc:identifier>doi: 10.3390/s24237538</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7538</prism:startingPage> <prism:doi>10.3390/s24237538</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7538</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7536"> <title>Sensors, Vol. 24, Pages 7536: Pedestrian Re-Identification Based on Fine-Grained Feature Learning and Fusion</title> <link>https://www.mdpi.com/1424-8220/24/23/7536</link> <description>Video-based pedestrian re-identification (Re-ID) is used to re-identify the same person across different camera views. One of the key problems is to learn an effective representation for the pedestrian from video. However, it is difficult to learn an effective representation from one single modality of a feature due to complicated issues with video, such as background, occlusion, and blurred scenes. Therefore, there are some studies on fusing multimodal features for video-based pedestrian Re-ID. However, most of these works fuse features at the global level, which is not effective in reflecting fine-grained and complementary information. Therefore, the improvement in performance is limited. To obtain a more effective representation, we propose to learn fine-grained features from different modalities of the video, and then they are aligned and fused at the fine-grained level to capture rich semantic information. As a result, a multimodal token-learning and alignment model (MTLA) is proposed to re-identify pedestrians across camera videos. An MTLA consists of three modules, i.e., a multimodal feature encoder, token-based cross-modal alignment, and correlation-aware fusion. Firstly, the multimodal feature encoder is used to extract the multimodal features from the visual appearance and gait information views, and then fine-grained tokens are learned and denoised from these features. Then, the token-based cross-modal alignment module is used to align the multimodal features at the token level to capture fine-grained semantic information. Finally, the correlation-aware fusion module is used to fuse the multimodal token features by learning the inter- and intra-modal correlation, in which the features refine each other and a unified representation is obtained for pedestrian Re-ID. To evaluate the performance of fine-grained features alignment and fusion, we conduct extensive experiments on three benchmark datasets. Compared with the state-of-art approaches, all the evaluation metrices of mAP and Rank-K are improved by more than 0.4 percentage points.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7536: Pedestrian Re-Identification Based on Fine-Grained Feature Learning and Fusion</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7536">doi: 10.3390/s24237536</a></p> <p>Authors: Anming Chen Weiqiang Liu </p> <p>Video-based pedestrian re-identification (Re-ID) is used to re-identify the same person across different camera views. One of the key problems is to learn an effective representation for the pedestrian from video. However, it is difficult to learn an effective representation from one single modality of a feature due to complicated issues with video, such as background, occlusion, and blurred scenes. Therefore, there are some studies on fusing multimodal features for video-based pedestrian Re-ID. However, most of these works fuse features at the global level, which is not effective in reflecting fine-grained and complementary information. Therefore, the improvement in performance is limited. To obtain a more effective representation, we propose to learn fine-grained features from different modalities of the video, and then they are aligned and fused at the fine-grained level to capture rich semantic information. As a result, a multimodal token-learning and alignment model (MTLA) is proposed to re-identify pedestrians across camera videos. An MTLA consists of three modules, i.e., a multimodal feature encoder, token-based cross-modal alignment, and correlation-aware fusion. Firstly, the multimodal feature encoder is used to extract the multimodal features from the visual appearance and gait information views, and then fine-grained tokens are learned and denoised from these features. Then, the token-based cross-modal alignment module is used to align the multimodal features at the token level to capture fine-grained semantic information. Finally, the correlation-aware fusion module is used to fuse the multimodal token features by learning the inter- and intra-modal correlation, in which the features refine each other and a unified representation is obtained for pedestrian Re-ID. To evaluate the performance of fine-grained features alignment and fusion, we conduct extensive experiments on three benchmark datasets. Compared with the state-of-art approaches, all the evaluation metrices of mAP and Rank-K are improved by more than 0.4 percentage points.</p> ]]></content:encoded> <dc:title>Pedestrian Re-Identification Based on Fine-Grained Feature Learning and Fusion</dc:title> <dc:creator>Anming Chen</dc:creator> <dc:creator>Weiqiang Liu</dc:creator> <dc:identifier>doi: 10.3390/s24237536</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7536</prism:startingPage> <prism:doi>10.3390/s24237536</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7536</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7535"> <title>Sensors, Vol. 24, Pages 7535: A Ku-Band Compact Offset Cylindrical Reflector Antenna with High Gain for Low-Earth Orbit Sensing Applications</title> <link>https://www.mdpi.com/1424-8220/24/23/7535</link> <description>The rise of CubeSats has unlocked opportunities for cutting-edge space missions with reduced costs and accelerated development timelines. CubeSats necessitate a high-gain antenna that can fit within a tightly confined space. This paper is primarily concerned with designing a compact Ku-band offset cylindrical reflector antenna for a CubeSat-based Earth Observation mission, with the goal of monitoring Arctic snow and sea ice. The development of a Ku-band offset cylindrical reflector, with a compact aperture of 110 &amp;amp;times; 149 mm2 (6.3&amp;amp;lambda; &amp;amp;times; 8.5&amp;amp;lambda;), is described alongside a patch array feed consisting of 2 &amp;amp;times; 8 elements. The patch array feed is designed using a lightweight Rogers substrate and is utilized to test the reflector. Adopting an offset configuration helped prevent gain loss due to feed blockage. Analyzing the reflector antenna, including the feed, thorough simulations and measurements indicates that achieving a gain of 25 dBi and an aperture efficiency of 52% at 17.2 GHz is attainable. The reflector&amp;amp;rsquo;s cylindrical shape and compact size facilitate the design of a simple mechanism for reflector deployment, enabling the antenna to be stored within 1U. The array feed and reflector antenna have been fabricated and tested, demonstrating good consistency between the simulation and measurement outcomes.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7535: A Ku-Band Compact Offset Cylindrical Reflector Antenna with High Gain for Low-Earth Orbit Sensing Applications</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7535">doi: 10.3390/s24237535</a></p> <p>Authors: Bashar A. F. Esmail Dustin Isleifson Lotfollah Shafai </p> <p>The rise of CubeSats has unlocked opportunities for cutting-edge space missions with reduced costs and accelerated development timelines. CubeSats necessitate a high-gain antenna that can fit within a tightly confined space. This paper is primarily concerned with designing a compact Ku-band offset cylindrical reflector antenna for a CubeSat-based Earth Observation mission, with the goal of monitoring Arctic snow and sea ice. The development of a Ku-band offset cylindrical reflector, with a compact aperture of 110 &amp;amp;times; 149 mm2 (6.3&amp;amp;lambda; &amp;amp;times; 8.5&amp;amp;lambda;), is described alongside a patch array feed consisting of 2 &amp;amp;times; 8 elements. The patch array feed is designed using a lightweight Rogers substrate and is utilized to test the reflector. Adopting an offset configuration helped prevent gain loss due to feed blockage. Analyzing the reflector antenna, including the feed, thorough simulations and measurements indicates that achieving a gain of 25 dBi and an aperture efficiency of 52% at 17.2 GHz is attainable. The reflector&amp;amp;rsquo;s cylindrical shape and compact size facilitate the design of a simple mechanism for reflector deployment, enabling the antenna to be stored within 1U. The array feed and reflector antenna have been fabricated and tested, demonstrating good consistency between the simulation and measurement outcomes.</p> ]]></content:encoded> <dc:title>A Ku-Band Compact Offset Cylindrical Reflector Antenna with High Gain for Low-Earth Orbit Sensing Applications</dc:title> <dc:creator>Bashar A. F. Esmail</dc:creator> <dc:creator>Dustin Isleifson</dc:creator> <dc:creator>Lotfollah Shafai</dc:creator> <dc:identifier>doi: 10.3390/s24237535</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7535</prism:startingPage> <prism:doi>10.3390/s24237535</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7535</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7534"> <title>Sensors, Vol. 24, Pages 7534: Detecting Unusual Repetitive Patterns of Behavior Indicative of a Loop-Based Attack in IoT</title> <link>https://www.mdpi.com/1424-8220/24/23/7534</link> <description>Given the high risk of Internet of Things (IoT) device compromise, it is crucial to discuss the attack detection aspect. However, due to the physical limitations of IoT, such as battery life and sensing and processing power, the widely used detection techniques, such as signature-based or anomaly-based detection, are quite ineffective. This research extracted loop-based cases from the transmission session dataset of &amp;amp;ldquo;CTU-IoT-Malware-Capture-7-1&amp;amp;rdquo; (&amp;amp;ldquo;Linux, Mirai&amp;amp;rdquo;) and implemented a loop-based detection machine learning approach. The research employed nine machine learning models to illustrate how the loop patterns of the datasets can facilitate detection. The results of this study indicate that the XGBoost model achieves the best performance in terms of &amp;amp;ldquo;Accuracy: 8.85%&amp;amp;rdquo;, &amp;amp;ldquo;Precision: 96.57% (Class)&amp;amp;rdquo;, &amp;amp;ldquo;Recall: 96.72% (Class 1)&amp;amp;rdquo;, and &amp;amp;ldquo;F1-Score: 6.24%&amp;amp;rdquo;. The XGBoost model demonstrated exceptional performance across all metrics, indicating its capability in handling large IoT datasets effectively. It provides not only high accuracy but also strong generalization, which is crucial for detecting intricate and diverse patterns of malicious behavior in IoT networks. Its precision and recall performance further highlight its robustness in identifying both attack and normal activity, reducing the chances of false positives and negatives, making it a superior choice for real-time IoT threat detection.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7534: Detecting Unusual Repetitive Patterns of Behavior Indicative of a Loop-Based Attack in IoT</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7534">doi: 10.3390/s24237534</a></p> <p>Authors: Asmaa Munshi </p> <p>Given the high risk of Internet of Things (IoT) device compromise, it is crucial to discuss the attack detection aspect. However, due to the physical limitations of IoT, such as battery life and sensing and processing power, the widely used detection techniques, such as signature-based or anomaly-based detection, are quite ineffective. This research extracted loop-based cases from the transmission session dataset of &amp;amp;ldquo;CTU-IoT-Malware-Capture-7-1&amp;amp;rdquo; (&amp;amp;ldquo;Linux, Mirai&amp;amp;rdquo;) and implemented a loop-based detection machine learning approach. The research employed nine machine learning models to illustrate how the loop patterns of the datasets can facilitate detection. The results of this study indicate that the XGBoost model achieves the best performance in terms of &amp;amp;ldquo;Accuracy: 8.85%&amp;amp;rdquo;, &amp;amp;ldquo;Precision: 96.57% (Class)&amp;amp;rdquo;, &amp;amp;ldquo;Recall: 96.72% (Class 1)&amp;amp;rdquo;, and &amp;amp;ldquo;F1-Score: 6.24%&amp;amp;rdquo;. The XGBoost model demonstrated exceptional performance across all metrics, indicating its capability in handling large IoT datasets effectively. It provides not only high accuracy but also strong generalization, which is crucial for detecting intricate and diverse patterns of malicious behavior in IoT networks. Its precision and recall performance further highlight its robustness in identifying both attack and normal activity, reducing the chances of false positives and negatives, making it a superior choice for real-time IoT threat detection.</p> ]]></content:encoded> <dc:title>Detecting Unusual Repetitive Patterns of Behavior Indicative of a Loop-Based Attack in IoT</dc:title> <dc:creator>Asmaa Munshi</dc:creator> <dc:identifier>doi: 10.3390/s24237534</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7534</prism:startingPage> <prism:doi>10.3390/s24237534</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7534</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7533"> <title>Sensors, Vol. 24, Pages 7533: Low-Cost and Affordable Thermistor-Based Wideband Sub-THz Detector with Dielectric Waveguide Coupling</title> <link>https://www.mdpi.com/1424-8220/24/23/7533</link> <description>Bolometric detection of electromagnetic radiation is a well-established method in a wide frequency range, from millimeter waves through the terahertz region up to infrared. Fabrication of such a detector is often an expensive and demanding process. We propose a simple device based on a commercially available thermistor as a sensing element. To direct radiation to the sensor, we designed and fabricated a 3D-printed optical element integrated with the dielectric waveguide. An electronic setup was prepared to measure the sensor response. The described device is an affordable detector with acceptable detection parameters such as SNR or responsivity at a hundreds of volts per watt level.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7533: Low-Cost and Affordable Thermistor-Based Wideband Sub-THz Detector with Dielectric Waveguide Coupling</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7533">doi: 10.3390/s24237533</a></p> <p>Authors: Przemys艂aw Zagrajek Marcin Wojciechowski Pawe艂 Komorowski Kateryna Hovorova Marcin Maciejewski </p> <p>Bolometric detection of electromagnetic radiation is a well-established method in a wide frequency range, from millimeter waves through the terahertz region up to infrared. Fabrication of such a detector is often an expensive and demanding process. We propose a simple device based on a commercially available thermistor as a sensing element. To direct radiation to the sensor, we designed and fabricated a 3D-printed optical element integrated with the dielectric waveguide. An electronic setup was prepared to measure the sensor response. The described device is an affordable detector with acceptable detection parameters such as SNR or responsivity at a hundreds of volts per watt level.</p> ]]></content:encoded> <dc:title>Low-Cost and Affordable Thermistor-Based Wideband Sub-THz Detector with Dielectric Waveguide Coupling</dc:title> <dc:creator>Przemys艂aw Zagrajek</dc:creator> <dc:creator>Marcin Wojciechowski</dc:creator> <dc:creator>Pawe艂 Komorowski</dc:creator> <dc:creator>Kateryna Hovorova</dc:creator> <dc:creator>Marcin Maciejewski</dc:creator> <dc:identifier>doi: 10.3390/s24237533</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7533</prism:startingPage> <prism:doi>10.3390/s24237533</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7533</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7532"> <title>Sensors, Vol. 24, Pages 7532: Technologies and Sensors for Artificial Muscles in Rehabilitation</title> <link>https://www.mdpi.com/1424-8220/24/23/7532</link> <description>Muscles are very important parts of the human body. When there is an injury to a muscle that causes long-term dysfunctionality, sensors and artificial muscles can be used to help alleviate problems. Muscles have complex structures; thus, ultrasound and other types of scans may be needed to determine their parameters and model their shapes. Additionally, the measurement of chemicals in muscles plays a significant role in analyzing their performance and potential diseases in humans. All the above-mentioned components are needed for understanding the structure and function of muscles. The areas studied in this review include artificial muscles and exoskeletons, determining muscle parameters and modelling, assessing musculoskeletal functions, chemicals in muscles, and various applications, including those of wearable sensors. In future studies, we would like to understand the link between the brain and muscles and develop technologies that can assist in augmenting the motor skills of individuals affected by various debilitating conditions.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7532: Technologies and Sensors for Artificial Muscles in Rehabilitation</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7532">doi: 10.3390/s24237532</a></p> <p>Authors: Vina Basu Li Cheng Bin Zheng </p> <p>Muscles are very important parts of the human body. When there is an injury to a muscle that causes long-term dysfunctionality, sensors and artificial muscles can be used to help alleviate problems. Muscles have complex structures; thus, ultrasound and other types of scans may be needed to determine their parameters and model their shapes. Additionally, the measurement of chemicals in muscles plays a significant role in analyzing their performance and potential diseases in humans. All the above-mentioned components are needed for understanding the structure and function of muscles. The areas studied in this review include artificial muscles and exoskeletons, determining muscle parameters and modelling, assessing musculoskeletal functions, chemicals in muscles, and various applications, including those of wearable sensors. In future studies, we would like to understand the link between the brain and muscles and develop technologies that can assist in augmenting the motor skills of individuals affected by various debilitating conditions.</p> ]]></content:encoded> <dc:title>Technologies and Sensors for Artificial Muscles in Rehabilitation</dc:title> <dc:creator>Vina Basu</dc:creator> <dc:creator>Li Cheng</dc:creator> <dc:creator>Bin Zheng</dc:creator> <dc:identifier>doi: 10.3390/s24237532</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Review</prism:section> <prism:startingPage>7532</prism:startingPage> <prism:doi>10.3390/s24237532</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7532</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7531"> <title>Sensors, Vol. 24, Pages 7531: Excitation-Dependent pKa Extends the Sensing Range of Fluorescence Lifetime pH Sensors</title> <link>https://www.mdpi.com/1424-8220/24/23/7531</link> <description>Biological activity is strongly dependent on pH, which fluctuates within a variety of neutral, alkaline, and acidic local environments. The heterogeneity of tissue and subcellular pH has driven the development of sensors with different pKa values, and a huge assortment of fluorescent sensors have been created to measure and visualize pH in living cells and tissues. In particular, sensors that report based on fluorescence lifetime are advantageous for quantitation. Here, we apply a theoretical framework to derive how the apparent pKa of lifetime-based pH sensors depends on fluorescence excitation wavelength. We demonstrate that theory predicts the behavior of two different fluorescent protein-based pH sensors in solution as proofs-of-concept. Furthermore, we show that this behavior has great practical value in living cells because it extends the sensing range of a single sensor by simply choosing appropriate detection parameters to match the physiological pH range of interest. More broadly, our results show that the versatility of a single lifetime-based sensor has been significantly underappreciated, and our approach provides a means to use a single sensor across a range of pH environments.</description> <pubDate>2024-11-26</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7531: Excitation-Dependent pKa Extends the Sensing Range of Fluorescence Lifetime pH Sensors</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7531">doi: 10.3390/s24237531</a></p> <p>Authors: Emily P. Haynes Mary Canzano Mathew Tantama </p> <p>Biological activity is strongly dependent on pH, which fluctuates within a variety of neutral, alkaline, and acidic local environments. The heterogeneity of tissue and subcellular pH has driven the development of sensors with different pKa values, and a huge assortment of fluorescent sensors have been created to measure and visualize pH in living cells and tissues. In particular, sensors that report based on fluorescence lifetime are advantageous for quantitation. Here, we apply a theoretical framework to derive how the apparent pKa of lifetime-based pH sensors depends on fluorescence excitation wavelength. We demonstrate that theory predicts the behavior of two different fluorescent protein-based pH sensors in solution as proofs-of-concept. Furthermore, we show that this behavior has great practical value in living cells because it extends the sensing range of a single sensor by simply choosing appropriate detection parameters to match the physiological pH range of interest. More broadly, our results show that the versatility of a single lifetime-based sensor has been significantly underappreciated, and our approach provides a means to use a single sensor across a range of pH environments.</p> ]]></content:encoded> <dc:title>Excitation-Dependent pKa Extends the Sensing Range of Fluorescence Lifetime pH Sensors</dc:title> <dc:creator>Emily P. Haynes</dc:creator> <dc:creator>Mary Canzano</dc:creator> <dc:creator>Mathew Tantama</dc:creator> <dc:identifier>doi: 10.3390/s24237531</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-26</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-26</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7531</prism:startingPage> <prism:doi>10.3390/s24237531</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7531</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7530"> <title>Sensors, Vol. 24, Pages 7530: Movement Sensing Opportunities for Monitoring Dynamic Cognitive States</title> <link>https://www.mdpi.com/1424-8220/24/23/7530</link> <description>In occupational domains such as sports, healthcare, driving, and military, both individuals and small groups are expected to perform challenging tasks under adverse conditions that induce transient cognitive states such as stress, workload, and uncertainty. Wearable and standoff 6DOF sensing technologies are advancing rapidly, including increasingly miniaturized yet robust inertial measurement units (IMUs) and portable marker-less infrared optical motion tracking. These sensing technologies may offer opportunities to track overt physical behavior and classify cognitive states relevant to human performance in diverse human&amp;amp;ndash;machine domains. We describe progress in research attempting to distinguish cognitive states by tracking movement behavior in both individuals and small groups, examining potential applications in sports, healthcare, driving, and the military. In the context of military training and operations, there are no generally accepted methods for classifying transient mental states such as uncertainty from movement-related data, despite its importance for shaping decision-making and behavior. To fill this gap, an example data set is presented including optical motion capture of rifle trajectories during a dynamic marksmanship task that elicits variable uncertainty; using machine learning, we demonstrate that features of weapon trajectories capturing the complexity of motion are valuable for classifying low versus high uncertainty states. We argue that leveraging metrics of human movement behavior reveals opportunities to complement relatively costly and less portable neurophysiological sensing technologies and enables domain-specific human&amp;amp;ndash;machine interfaces to support a wide range of cognitive functions.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7530: Movement Sensing Opportunities for Monitoring Dynamic Cognitive States</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7530">doi: 10.3390/s24237530</a></p> <p>Authors: Tad T. Bruny茅 James McIntyre Gregory I. Hughes Eric L. Miller </p> <p>In occupational domains such as sports, healthcare, driving, and military, both individuals and small groups are expected to perform challenging tasks under adverse conditions that induce transient cognitive states such as stress, workload, and uncertainty. Wearable and standoff 6DOF sensing technologies are advancing rapidly, including increasingly miniaturized yet robust inertial measurement units (IMUs) and portable marker-less infrared optical motion tracking. These sensing technologies may offer opportunities to track overt physical behavior and classify cognitive states relevant to human performance in diverse human&amp;amp;ndash;machine domains. We describe progress in research attempting to distinguish cognitive states by tracking movement behavior in both individuals and small groups, examining potential applications in sports, healthcare, driving, and the military. In the context of military training and operations, there are no generally accepted methods for classifying transient mental states such as uncertainty from movement-related data, despite its importance for shaping decision-making and behavior. To fill this gap, an example data set is presented including optical motion capture of rifle trajectories during a dynamic marksmanship task that elicits variable uncertainty; using machine learning, we demonstrate that features of weapon trajectories capturing the complexity of motion are valuable for classifying low versus high uncertainty states. We argue that leveraging metrics of human movement behavior reveals opportunities to complement relatively costly and less portable neurophysiological sensing technologies and enables domain-specific human&amp;amp;ndash;machine interfaces to support a wide range of cognitive functions.</p> ]]></content:encoded> <dc:title>Movement Sensing Opportunities for Monitoring Dynamic Cognitive States</dc:title> <dc:creator>Tad T. Bruny茅</dc:creator> <dc:creator>James McIntyre</dc:creator> <dc:creator>Gregory I. Hughes</dc:creator> <dc:creator>Eric L. Miller</dc:creator> <dc:identifier>doi: 10.3390/s24237530</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Review</prism:section> <prism:startingPage>7530</prism:startingPage> <prism:doi>10.3390/s24237530</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7530</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7529"> <title>Sensors, Vol. 24, Pages 7529: An Identification Method for Road Hypnosis Based on the Fusion of Human Life Parameters</title> <link>https://www.mdpi.com/1424-8220/24/23/7529</link> <description>A driver in road hypnosis has two different types of characteristics. One is the external characteristics, which are distinct and can be directly observed. The other is internal characteristics, which are indistinctive and cannot be directly observed. The eye movement characteristic, as a distinct external characteristic, is one of the typical characteristics of road hypnosis identification. The electroencephalogram (EEG) characteristic, as an internal feature, is a golden parameter of drivers&amp;amp;rsquo; life identification. This paper proposes an identification method for road hypnosis based on the fusion of human life parameters. Eye movement data and EEG data are collected through vehicle driving experiments and virtual driving experiments. The collected data are preprocessed with principal component analysis (PCA) and independent component analysis (ICA), respectively. Eye movement data can be trained with a self-attention model (SAM), and the EEG data can be trained with the deep belief network (DBN). The road hypnosis identification model can be constructed by combining the two trained models with the stacking method. Repeated Random Subsampling Cross-Validation (RRSCV) is used to validate models. The results show that road hypnosis can be effectively recognized using the constructed model. This study is of great significance to reveal the essential characteristics and mechanisms of road hypnosis. The effectiveness and accuracy of road hypnosis identification can also be improved through this study.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7529: An Identification Method for Road Hypnosis Based on the Fusion of Human Life Parameters</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7529">doi: 10.3390/s24237529</a></p> <p>Authors: Bin Wang Jingheng Wang Xiaoyuan Wang Longfei Chen Chenyang Jiao Han Zhang Yi Liu </p> <p>A driver in road hypnosis has two different types of characteristics. One is the external characteristics, which are distinct and can be directly observed. The other is internal characteristics, which are indistinctive and cannot be directly observed. The eye movement characteristic, as a distinct external characteristic, is one of the typical characteristics of road hypnosis identification. The electroencephalogram (EEG) characteristic, as an internal feature, is a golden parameter of drivers&amp;amp;rsquo; life identification. This paper proposes an identification method for road hypnosis based on the fusion of human life parameters. Eye movement data and EEG data are collected through vehicle driving experiments and virtual driving experiments. The collected data are preprocessed with principal component analysis (PCA) and independent component analysis (ICA), respectively. Eye movement data can be trained with a self-attention model (SAM), and the EEG data can be trained with the deep belief network (DBN). The road hypnosis identification model can be constructed by combining the two trained models with the stacking method. Repeated Random Subsampling Cross-Validation (RRSCV) is used to validate models. The results show that road hypnosis can be effectively recognized using the constructed model. This study is of great significance to reveal the essential characteristics and mechanisms of road hypnosis. The effectiveness and accuracy of road hypnosis identification can also be improved through this study.</p> ]]></content:encoded> <dc:title>An Identification Method for Road Hypnosis Based on the Fusion of Human Life Parameters</dc:title> <dc:creator>Bin Wang</dc:creator> <dc:creator>Jingheng Wang</dc:creator> <dc:creator>Xiaoyuan Wang</dc:creator> <dc:creator>Longfei Chen</dc:creator> <dc:creator>Chenyang Jiao</dc:creator> <dc:creator>Han Zhang</dc:creator> <dc:creator>Yi Liu</dc:creator> <dc:identifier>doi: 10.3390/s24237529</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7529</prism:startingPage> <prism:doi>10.3390/s24237529</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7529</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7528"> <title>Sensors, Vol. 24, Pages 7528: Unidirectional Communications in Secure IoT Systems&amp;mdash;A Survey</title> <link>https://www.mdpi.com/1424-8220/24/23/7528</link> <description>The security of Internet of Things (IoT) systems has consistently been a challenge, particularly in the context of critical infrastructure. One particular approach not yet employed in this domain is the unidirectional communication paradigm. This survey presents an analysis of the most prevalent unidirectional communication solutions, namely, data diodes, network pumps, unidirectional gateways, and unidirectional protocols. The objective of the survey is to present an analysis of the unidirectional communication methods that meet the requirements of IoT security. These methods are classified according to their implementation and operational mode. The survey analyzes the unidirectional communication solutions based on their performance, the level of security offered, the cost-effectiveness, and their cost of implementation. Additionally, it includes an analysis of the existing off-the-shelf unidirectional communication implementations found in the industry. Furthermore, it identifies some of the most important current issues and development directions.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7528: Unidirectional Communications in Secure IoT Systems&amp;mdash;A Survey</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7528">doi: 10.3390/s24237528</a></p> <p>Authors: Lucian Gaina Cristina Sorina Stangaciu Daniela Stanescu Bianca Gusita Mihai Victor Micea </p> <p>The security of Internet of Things (IoT) systems has consistently been a challenge, particularly in the context of critical infrastructure. One particular approach not yet employed in this domain is the unidirectional communication paradigm. This survey presents an analysis of the most prevalent unidirectional communication solutions, namely, data diodes, network pumps, unidirectional gateways, and unidirectional protocols. The objective of the survey is to present an analysis of the unidirectional communication methods that meet the requirements of IoT security. These methods are classified according to their implementation and operational mode. The survey analyzes the unidirectional communication solutions based on their performance, the level of security offered, the cost-effectiveness, and their cost of implementation. Additionally, it includes an analysis of the existing off-the-shelf unidirectional communication implementations found in the industry. Furthermore, it identifies some of the most important current issues and development directions.</p> ]]></content:encoded> <dc:title>Unidirectional Communications in Secure IoT Systems&amp;amp;mdash;A Survey</dc:title> <dc:creator>Lucian Gaina</dc:creator> <dc:creator>Cristina Sorina Stangaciu</dc:creator> <dc:creator>Daniela Stanescu</dc:creator> <dc:creator>Bianca Gusita</dc:creator> <dc:creator>Mihai Victor Micea</dc:creator> <dc:identifier>doi: 10.3390/s24237528</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Review</prism:section> <prism:startingPage>7528</prism:startingPage> <prism:doi>10.3390/s24237528</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7528</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7527"> <title>Sensors, Vol. 24, Pages 7527: Developing a New Expected Goals Metric to Quantify Performance in a Virtual Reality Soccer Goalkeeping App called CleanSheet</title> <link>https://www.mdpi.com/1424-8220/24/23/7527</link> <description>As virtual reality (VR) sports training apps start to become more mainstream, it is important that human performance is measured from VR gameplay interaction data in a more meaningful way. CleanSheet is a VR training app that is played by over 100,000 users around the world. Many of those players are aspiring goalkeepers who want to use the app as a new way to train and improve their general goalkeeping performance. Whilst the leaderboards display how many shots players saved, these data do not take into account the difficulty of the shot faced. This study presents a regression model developed from a combination of existing expected goals (xG) models, goalkeeper performance metrics, and psychological research to produce a new shot difficulty metric called CSxG. Utilizing user save rate data as the target variable, a model was developed that incorporated three input variables relating to ball flight and in-goal positioning. Our analysis showed that the required rate of closure (RROC), adapted from Tau theory, was the most significant predictor of the proportion of goals conceded. A validation process evaluated the new xG model for CleanSheet by comparing its difficulty predictions against user performance data across players of varying skill levels. CSxG effectively predicted shot difficulty at the extremes but showed less accuracy for mid-range scores (0.4 to 0.8). Additional variables influencing shot difficulty, such as build-up play and goalpost size, were identified for future model enhancements. This research contributes to the advancement of predictive modeling in sports performance analysis, highlighting the potential for improved goalkeeper training and strategy development using VR technology.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7527: Developing a New Expected Goals Metric to Quantify Performance in a Virtual Reality Soccer Goalkeeping App called CleanSheet</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7527">doi: 10.3390/s24237527</a></p> <p>Authors: Matthew Simpson Cathy Craig </p> <p>As virtual reality (VR) sports training apps start to become more mainstream, it is important that human performance is measured from VR gameplay interaction data in a more meaningful way. CleanSheet is a VR training app that is played by over 100,000 users around the world. Many of those players are aspiring goalkeepers who want to use the app as a new way to train and improve their general goalkeeping performance. Whilst the leaderboards display how many shots players saved, these data do not take into account the difficulty of the shot faced. This study presents a regression model developed from a combination of existing expected goals (xG) models, goalkeeper performance metrics, and psychological research to produce a new shot difficulty metric called CSxG. Utilizing user save rate data as the target variable, a model was developed that incorporated three input variables relating to ball flight and in-goal positioning. Our analysis showed that the required rate of closure (RROC), adapted from Tau theory, was the most significant predictor of the proportion of goals conceded. A validation process evaluated the new xG model for CleanSheet by comparing its difficulty predictions against user performance data across players of varying skill levels. CSxG effectively predicted shot difficulty at the extremes but showed less accuracy for mid-range scores (0.4 to 0.8). Additional variables influencing shot difficulty, such as build-up play and goalpost size, were identified for future model enhancements. This research contributes to the advancement of predictive modeling in sports performance analysis, highlighting the potential for improved goalkeeper training and strategy development using VR technology.</p> ]]></content:encoded> <dc:title>Developing a New Expected Goals Metric to Quantify Performance in a Virtual Reality Soccer Goalkeeping App called CleanSheet</dc:title> <dc:creator>Matthew Simpson</dc:creator> <dc:creator>Cathy Craig</dc:creator> <dc:identifier>doi: 10.3390/s24237527</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7527</prism:startingPage> <prism:doi>10.3390/s24237527</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7527</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7526"> <title>Sensors, Vol. 24, Pages 7526: Kinematical and Physiological Responses of Overground Running Gait Pattern at Different Intensities</title> <link>https://www.mdpi.com/1424-8220/24/23/7526</link> <description>Runners achieve forward locomotion through diverse techniques. However, understanding the behavior of the involved kinematical variables remains incomplete, particularly when running overground and along an intensity spectrum. We aimed to characterize the biomechanical and physiological adaptations while running at low, moderate, heavy and severe intensities. Ten middle- and long-distance runners completed an incremental intermittent protocol of 800 m steps until exhaustion (1 km&amp;amp;middot;h&amp;amp;minus;1 velocity increments and 30 s intervals) on an outdoor track field. Biomechanical data were captured using two high-resolution video cameras, and linear and angular kinematic variables were analyzed. With the intensity rise, a decrease in stride, step and contact times ([0.70&amp;amp;ndash;0.65], [0.35&amp;amp;ndash;0.33] and [0.42&amp;amp;ndash;0.37] s) and an increase in stride length and frequency and flight time ([3.13&amp;amp;ndash;3.52] m, [1.43&amp;amp;ndash;1.52] Hz and [0.28&amp;amp;ndash;0.29] s; p &amp;amp;lt; 0.05) were observed, together with an increase in oxygen uptake and blood lactate concentrations ([54.7&amp;amp;ndash;67.6] mL&amp;amp;#8729;kg&amp;amp;minus;1&amp;amp;#8729;min&amp;amp;minus;1 and [3.1&amp;amp;ndash;10.2] mmol&amp;amp;#8729;L&amp;amp;minus;1). A more flexed hip at initial contact and toe-off (152.02&amp;amp;ndash;149.36] and [165.70&amp;amp;ndash;163.64]) and knee at initial contact ([162.64&amp;amp;ndash;159.57]; p &amp;amp;lt; 0.05) were also observed. A consistent gait pattern along each protocol step was exhibited, with minor changes without practical significance. Runners are constantly adapting their gait pattern, reflected in both biomechanical and physiological responses, both of which should be considered for better characterization.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7526: Kinematical and Physiological Responses of Overground Running Gait Pattern at Different Intensities</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7526">doi: 10.3390/s24237526</a></p> <p>Authors: Ana Sofia Monteiro Jo茫o Paulo Galano Filipa Cardoso Cosme F. Buzzachera Jo茫o Paulo Vilas-Boas Ricardo J. Fernandes </p> <p>Runners achieve forward locomotion through diverse techniques. However, understanding the behavior of the involved kinematical variables remains incomplete, particularly when running overground and along an intensity spectrum. We aimed to characterize the biomechanical and physiological adaptations while running at low, moderate, heavy and severe intensities. Ten middle- and long-distance runners completed an incremental intermittent protocol of 800 m steps until exhaustion (1 km&amp;amp;middot;h&amp;amp;minus;1 velocity increments and 30 s intervals) on an outdoor track field. Biomechanical data were captured using two high-resolution video cameras, and linear and angular kinematic variables were analyzed. With the intensity rise, a decrease in stride, step and contact times ([0.70&amp;amp;ndash;0.65], [0.35&amp;amp;ndash;0.33] and [0.42&amp;amp;ndash;0.37] s) and an increase in stride length and frequency and flight time ([3.13&amp;amp;ndash;3.52] m, [1.43&amp;amp;ndash;1.52] Hz and [0.28&amp;amp;ndash;0.29] s; p &amp;amp;lt; 0.05) were observed, together with an increase in oxygen uptake and blood lactate concentrations ([54.7&amp;amp;ndash;67.6] mL&amp;amp;#8729;kg&amp;amp;minus;1&amp;amp;#8729;min&amp;amp;minus;1 and [3.1&amp;amp;ndash;10.2] mmol&amp;amp;#8729;L&amp;amp;minus;1). A more flexed hip at initial contact and toe-off (152.02&amp;amp;ndash;149.36] and [165.70&amp;amp;ndash;163.64]) and knee at initial contact ([162.64&amp;amp;ndash;159.57]; p &amp;amp;lt; 0.05) were also observed. A consistent gait pattern along each protocol step was exhibited, with minor changes without practical significance. Runners are constantly adapting their gait pattern, reflected in both biomechanical and physiological responses, both of which should be considered for better characterization.</p> ]]></content:encoded> <dc:title>Kinematical and Physiological Responses of Overground Running Gait Pattern at Different Intensities</dc:title> <dc:creator>Ana Sofia Monteiro</dc:creator> <dc:creator>Jo茫o Paulo Galano</dc:creator> <dc:creator>Filipa Cardoso</dc:creator> <dc:creator>Cosme F. Buzzachera</dc:creator> <dc:creator>Jo茫o Paulo Vilas-Boas</dc:creator> <dc:creator>Ricardo J. Fernandes</dc:creator> <dc:identifier>doi: 10.3390/s24237526</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7526</prism:startingPage> <prism:doi>10.3390/s24237526</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7526</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7525"> <title>Sensors, Vol. 24, Pages 7525: Online Calibration of Inertial Sensors Based on Error Backpropagation</title> <link>https://www.mdpi.com/1424-8220/24/23/7525</link> <description>Global satellite navigation systems (GNSSs) are the most-used technology for the localization of vehicles in the outdoor environment, but in the case of a densely built-up area or during passage through a tunnel, the satellite signal is not available or has poor quality. Inertial navigation systems (INSs) allow localization dead reckoning, but they have an integration error that grows over time. Inexpensive inertial measurement units (IMUs) are subject to thermal-dependent error and must be calibrated almost continuously. This article proposes a novel method of online (continuous) calibration of inertial sensors with the aid of the data from the GNSS receiver during the vehicle&amp;amp;rsquo;s route. We performed data fusion using an extended Kalman filter (EKF) and calibrated the input sensors through error backpropagation. The algorithm thus calibrates the INS sensors while the GNSS receiver signal is good, and after a GNSS failure, for example in tunnels, the position is predicted only by low-cost inertial sensors. Such an approach significantly improved the localization precision in comparison with offline calibrated inertial localization with the same sensors.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7525: Online Calibration of Inertial Sensors Based on Error Backpropagation</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7525">doi: 10.3390/s24237525</a></p> <p>Authors: Vojtech Simak Jan Andel Dusan Nemec Juraj Kekelak </p> <p>Global satellite navigation systems (GNSSs) are the most-used technology for the localization of vehicles in the outdoor environment, but in the case of a densely built-up area or during passage through a tunnel, the satellite signal is not available or has poor quality. Inertial navigation systems (INSs) allow localization dead reckoning, but they have an integration error that grows over time. Inexpensive inertial measurement units (IMUs) are subject to thermal-dependent error and must be calibrated almost continuously. This article proposes a novel method of online (continuous) calibration of inertial sensors with the aid of the data from the GNSS receiver during the vehicle&amp;amp;rsquo;s route. We performed data fusion using an extended Kalman filter (EKF) and calibrated the input sensors through error backpropagation. The algorithm thus calibrates the INS sensors while the GNSS receiver signal is good, and after a GNSS failure, for example in tunnels, the position is predicted only by low-cost inertial sensors. Such an approach significantly improved the localization precision in comparison with offline calibrated inertial localization with the same sensors.</p> ]]></content:encoded> <dc:title>Online Calibration of Inertial Sensors Based on Error Backpropagation</dc:title> <dc:creator>Vojtech Simak</dc:creator> <dc:creator>Jan Andel</dc:creator> <dc:creator>Dusan Nemec</dc:creator> <dc:creator>Juraj Kekelak</dc:creator> <dc:identifier>doi: 10.3390/s24237525</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7525</prism:startingPage> <prism:doi>10.3390/s24237525</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7525</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7524"> <title>Sensors, Vol. 24, Pages 7524: Analysing Physical Performance Indicators Measured with Electronic Performance Tracking Systems in Men&amp;rsquo;s Beach Volleyball Formative Stages</title> <link>https://www.mdpi.com/1424-8220/24/23/7524</link> <description>Sports performance initiation is of significant interest in sports sciences, particularly in beach volleyball (BV), where players usually combine indoor and BV disciplines in the formative stages. This research aimed to apply an electronic performance tracking system to quantify the physical-conditional performance of young male BV players during competition, considering age group (U15 or U19), sport specialisation (indoor or beach) and the set outcome (winner or loser). Thirty-two young male players, categorised by age and sport specialisation, were analysed during 40 matches using electronic performance tracking systems (Wimu PROTM). Data collected were the set duration, total and relative distances covered, and number and maximum values in acceleration and deceleration actions. U19 players and BV specialists, compared to their younger and indoor counterparts, covered more distance (719.25 m/set vs. 597.85 m/set; 719.25 m/set vs. 613.15 m/set) and exhibited higher intensity in terms of maximum values in acceleration (4.09 m/s2 vs. 3.45 m/s2; 3.99 m/s2 vs. 3.65 m/s2) and deceleration (&amp;amp;minus;5.05 m/s2 vs. &amp;amp;minus;4.41 m/s2). More accelerations (557.50 n/set vs. 584.50 n/set) and decelerations (561.50 n/set vs. 589.00 n/set) were found in indoor players. Additionally, no significant differences were found in variables regarding the set outcome. These findings suggest that both age and specialisation play crucial roles in determining a great physical-conditional performance in young players, displaying a higher volume and intensity in external load metrics, whereas indoor players seem to need more accelerations and decelerations in a BV adaptation context. These insights highlight the age development and sport specialisation in young volleyball and BV athletes.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7524: Analysing Physical Performance Indicators Measured with Electronic Performance Tracking Systems in Men&amp;rsquo;s Beach Volleyball Formative Stages</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7524">doi: 10.3390/s24237524</a></p> <p>Authors: Joaqu铆n Mart铆n Marzano-Felisatti Rafael Mart铆nez-Gallego Jos茅 Pino-Ortega Antonio Garc铆a-de-Alcaraz Jose Ignacio Priego-Quesada Jos茅 Francisco Guzm谩n Luj谩n </p> <p>Sports performance initiation is of significant interest in sports sciences, particularly in beach volleyball (BV), where players usually combine indoor and BV disciplines in the formative stages. This research aimed to apply an electronic performance tracking system to quantify the physical-conditional performance of young male BV players during competition, considering age group (U15 or U19), sport specialisation (indoor or beach) and the set outcome (winner or loser). Thirty-two young male players, categorised by age and sport specialisation, were analysed during 40 matches using electronic performance tracking systems (Wimu PROTM). Data collected were the set duration, total and relative distances covered, and number and maximum values in acceleration and deceleration actions. U19 players and BV specialists, compared to their younger and indoor counterparts, covered more distance (719.25 m/set vs. 597.85 m/set; 719.25 m/set vs. 613.15 m/set) and exhibited higher intensity in terms of maximum values in acceleration (4.09 m/s2 vs. 3.45 m/s2; 3.99 m/s2 vs. 3.65 m/s2) and deceleration (&amp;amp;minus;5.05 m/s2 vs. &amp;amp;minus;4.41 m/s2). More accelerations (557.50 n/set vs. 584.50 n/set) and decelerations (561.50 n/set vs. 589.00 n/set) were found in indoor players. Additionally, no significant differences were found in variables regarding the set outcome. These findings suggest that both age and specialisation play crucial roles in determining a great physical-conditional performance in young players, displaying a higher volume and intensity in external load metrics, whereas indoor players seem to need more accelerations and decelerations in a BV adaptation context. These insights highlight the age development and sport specialisation in young volleyball and BV athletes.</p> ]]></content:encoded> <dc:title>Analysing Physical Performance Indicators Measured with Electronic Performance Tracking Systems in Men&amp;amp;rsquo;s Beach Volleyball Formative Stages</dc:title> <dc:creator>Joaqu铆n Mart铆n Marzano-Felisatti</dc:creator> <dc:creator>Rafael Mart铆nez-Gallego</dc:creator> <dc:creator>Jos茅 Pino-Ortega</dc:creator> <dc:creator>Antonio Garc铆a-de-Alcaraz</dc:creator> <dc:creator>Jose Ignacio Priego-Quesada</dc:creator> <dc:creator>Jos茅 Francisco Guzm谩n Luj谩n</dc:creator> <dc:identifier>doi: 10.3390/s24237524</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7524</prism:startingPage> <prism:doi>10.3390/s24237524</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7524</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7523"> <title>Sensors, Vol. 24, Pages 7523: High-Entropy Thermistor Ceramics (La1/3Nd1/3M1/3)2(Zr1/2Sn1/2)2O7 (M = Sm, Eu, Gd, or Dy) with High Sensitivity for High-Temperature Measurements</title> <link>https://www.mdpi.com/1424-8220/24/23/7523</link> <description>A series of high-entropy pyrochlore ceramics, specifically (La1/3Nd1/3M1/3)2(Zn1/2Sn1/2)2O7 (M = Sm, Eu, Gd, or Dy), have been synthesized using the solid-state reaction method. Their potential as high-temperature thermistors was investigated by analyzing electrical and aging properties at elevated temperatures. Characterization using X-ray diffraction, scanning electron microscopy, and Raman spectroscopy confirms that these ceramics are dense, single-phase solid solutions with a pyrochlore structure. Electrical analysis demonstrate that these ceramics maintain high resistivity and resistance stability, exhibiting typical negative temperature coefficient features and high B values across a wide temperature range. These characteristics make (La1/3Nd1/3M1/3)2(Zn1/2Sn1/2)2O7 promising candidates for the development of high-sensitivity, long-life high-temperature thermistors suitable for applications within the temperature range of 400&amp;amp;ndash;1200 &amp;amp;deg;C.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7523: High-Entropy Thermistor Ceramics (La1/3Nd1/3M1/3)2(Zr1/2Sn1/2)2O7 (M = Sm, Eu, Gd, or Dy) with High Sensitivity for High-Temperature Measurements</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7523">doi: 10.3390/s24237523</a></p> <p>Authors: Yian Chen Tingting Xuan Xiaohui Li Yuling Tuo Xiaoyi Chen Bo Gao </p> <p>A series of high-entropy pyrochlore ceramics, specifically (La1/3Nd1/3M1/3)2(Zn1/2Sn1/2)2O7 (M = Sm, Eu, Gd, or Dy), have been synthesized using the solid-state reaction method. Their potential as high-temperature thermistors was investigated by analyzing electrical and aging properties at elevated temperatures. Characterization using X-ray diffraction, scanning electron microscopy, and Raman spectroscopy confirms that these ceramics are dense, single-phase solid solutions with a pyrochlore structure. Electrical analysis demonstrate that these ceramics maintain high resistivity and resistance stability, exhibiting typical negative temperature coefficient features and high B values across a wide temperature range. These characteristics make (La1/3Nd1/3M1/3)2(Zn1/2Sn1/2)2O7 promising candidates for the development of high-sensitivity, long-life high-temperature thermistors suitable for applications within the temperature range of 400&amp;amp;ndash;1200 &amp;amp;deg;C.</p> ]]></content:encoded> <dc:title>High-Entropy Thermistor Ceramics (La1/3Nd1/3M1/3)2(Zr1/2Sn1/2)2O7 (M = Sm, Eu, Gd, or Dy) with High Sensitivity for High-Temperature Measurements</dc:title> <dc:creator>Yian Chen</dc:creator> <dc:creator>Tingting Xuan</dc:creator> <dc:creator>Xiaohui Li</dc:creator> <dc:creator>Yuling Tuo</dc:creator> <dc:creator>Xiaoyi Chen</dc:creator> <dc:creator>Bo Gao</dc:creator> <dc:identifier>doi: 10.3390/s24237523</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7523</prism:startingPage> <prism:doi>10.3390/s24237523</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7523</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7522"> <title>Sensors, Vol. 24, Pages 7522: Scalp-Implanted Ultra-Wideband Circularly Polarized MIMO Antenna for Biotelemetry Systems</title> <link>https://www.mdpi.com/1424-8220/24/23/7522</link> <description>This paper presents an innovative, compact, dual-element, implantable, ultra-wideband, circularly polarized multiple-input multiple-output (MIMO) antenna designed to operate within the 2.45 GHz industrial, scientific, and medical band, and both of its radiating units are circularly polarized antennas with polarization diversity. Specifically, antenna-1 exhibits left-handed circular polarization properties, while antenna-2 demonstrates right-handed circular polarization properties. The slots in the radiating patch and ground plane help the antenna achieve 690 MHz (2.14&amp;amp;ndash;2.83 GHz) ultra-wide bandwidth characteristics and circularly polarized characteristics. Additionally, a slit connecting two U-slots on the ground plane allows the antenna to achieve a wide effective circularly polarized axial ratio bandwidth of 400 MHz (2.23&amp;amp;ndash;2.63 GHz). The antenna is compact, with dimensions of 0.065 &amp;amp;times; 0.057 &amp;amp;times; 0.0042 &amp;amp;lambda;0&amp;amp;sup3; (&amp;amp;lambda;0 represents the free-space wavelength corresponding to the lowest operating frequency). The proposed antenna system&amp;amp;rsquo;s performance was evaluated with a seven-layer homogeneous human head model, a real human head model, and minced pork. This evaluation revealed that the antenna attained a peak gain of &amp;amp;minus;24.1 dBi and an isolation level of 27.5 dB. Furthermore, the assessment included the antenna&amp;amp;rsquo;s link margin (LM), key MIMO channel characteristics, and Specific Absorption Rate (SAR) metrics. The results indicate that the antenna performs exceptionally well.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7522: Scalp-Implanted Ultra-Wideband Circularly Polarized MIMO Antenna for Biotelemetry Systems</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7522">doi: 10.3390/s24237522</a></p> <p>Authors: Zhiwei Song Youwei Shi Xianren Zheng Yuchao Wang </p> <p>This paper presents an innovative, compact, dual-element, implantable, ultra-wideband, circularly polarized multiple-input multiple-output (MIMO) antenna designed to operate within the 2.45 GHz industrial, scientific, and medical band, and both of its radiating units are circularly polarized antennas with polarization diversity. Specifically, antenna-1 exhibits left-handed circular polarization properties, while antenna-2 demonstrates right-handed circular polarization properties. The slots in the radiating patch and ground plane help the antenna achieve 690 MHz (2.14&amp;amp;ndash;2.83 GHz) ultra-wide bandwidth characteristics and circularly polarized characteristics. Additionally, a slit connecting two U-slots on the ground plane allows the antenna to achieve a wide effective circularly polarized axial ratio bandwidth of 400 MHz (2.23&amp;amp;ndash;2.63 GHz). The antenna is compact, with dimensions of 0.065 &amp;amp;times; 0.057 &amp;amp;times; 0.0042 &amp;amp;lambda;0&amp;amp;sup3; (&amp;amp;lambda;0 represents the free-space wavelength corresponding to the lowest operating frequency). The proposed antenna system&amp;amp;rsquo;s performance was evaluated with a seven-layer homogeneous human head model, a real human head model, and minced pork. This evaluation revealed that the antenna attained a peak gain of &amp;amp;minus;24.1 dBi and an isolation level of 27.5 dB. Furthermore, the assessment included the antenna&amp;amp;rsquo;s link margin (LM), key MIMO channel characteristics, and Specific Absorption Rate (SAR) metrics. The results indicate that the antenna performs exceptionally well.</p> ]]></content:encoded> <dc:title>Scalp-Implanted Ultra-Wideband Circularly Polarized MIMO Antenna for Biotelemetry Systems</dc:title> <dc:creator>Zhiwei Song</dc:creator> <dc:creator>Youwei Shi</dc:creator> <dc:creator>Xianren Zheng</dc:creator> <dc:creator>Yuchao Wang</dc:creator> <dc:identifier>doi: 10.3390/s24237522</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7522</prism:startingPage> <prism:doi>10.3390/s24237522</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7522</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7521"> <title>Sensors, Vol. 24, Pages 7521: Research on Video Monitoring Technology for Galloping of OCS Additional Conductors of High-Speed Railway in Strong Wind Zone</title> <link>https://www.mdpi.com/1424-8220/24/23/7521</link> <description>The strong wind environment causes the additional conductor of the overhead contact system (OCS) of the Lanzhou&amp;amp;ndash;Xinjiang high-speed railway to gallop, significantly impacting the safe operation of the train. This paper presents the design of an online monitoring system for the galloping of additional conductors in the OCS, utilizing video monitoring for accurate and real-time assessment. Initially, the dynamics of the OCS additional conductor and its operational environment are examined, leading to the selection of suitable data transmission and power supply methods to finalize the camera configuration. Secondly, a preprocessing method for enhancing images of galloping in OCS additional conductors is developed, effectively reducing noise in edge detection through a region chain code clustering analysis. The video monitoring system effectively extracts wire edges, addressing the issues of splitting, breakage, and edge overlap in edge detection, while accurately identifying wire targets in video images. In conclusion, a galloping monitoring test platform is established to extract galloping data from additional conductors through video monitoring. The analysis of the galloping frequency and amplitude facilitates the comprehensive monitoring and assessment of the galloping status of OCS additional conductors. The video monitoring system effectively extracts and analyzes galloping data of the OCS additional conductor, fulfilling the fundamental requirements for the online monitoring of additional conductor galloping, and possesses significant engineering application value.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7521: Research on Video Monitoring Technology for Galloping of OCS Additional Conductors of High-Speed Railway in Strong Wind Zone</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7521">doi: 10.3390/s24237521</a></p> <p>Authors: Wentao Zhang Wenhao Wang Shanpeng Zhao Huayu Yuan Youpeng Zhang Xiaotong Yao Guangwu Chen </p> <p>The strong wind environment causes the additional conductor of the overhead contact system (OCS) of the Lanzhou&amp;amp;ndash;Xinjiang high-speed railway to gallop, significantly impacting the safe operation of the train. This paper presents the design of an online monitoring system for the galloping of additional conductors in the OCS, utilizing video monitoring for accurate and real-time assessment. Initially, the dynamics of the OCS additional conductor and its operational environment are examined, leading to the selection of suitable data transmission and power supply methods to finalize the camera configuration. Secondly, a preprocessing method for enhancing images of galloping in OCS additional conductors is developed, effectively reducing noise in edge detection through a region chain code clustering analysis. The video monitoring system effectively extracts wire edges, addressing the issues of splitting, breakage, and edge overlap in edge detection, while accurately identifying wire targets in video images. In conclusion, a galloping monitoring test platform is established to extract galloping data from additional conductors through video monitoring. The analysis of the galloping frequency and amplitude facilitates the comprehensive monitoring and assessment of the galloping status of OCS additional conductors. The video monitoring system effectively extracts and analyzes galloping data of the OCS additional conductor, fulfilling the fundamental requirements for the online monitoring of additional conductor galloping, and possesses significant engineering application value.</p> ]]></content:encoded> <dc:title>Research on Video Monitoring Technology for Galloping of OCS Additional Conductors of High-Speed Railway in Strong Wind Zone</dc:title> <dc:creator>Wentao Zhang</dc:creator> <dc:creator>Wenhao Wang</dc:creator> <dc:creator>Shanpeng Zhao</dc:creator> <dc:creator>Huayu Yuan</dc:creator> <dc:creator>Youpeng Zhang</dc:creator> <dc:creator>Xiaotong Yao</dc:creator> <dc:creator>Guangwu Chen</dc:creator> <dc:identifier>doi: 10.3390/s24237521</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7521</prism:startingPage> <prism:doi>10.3390/s24237521</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7521</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7519"> <title>Sensors, Vol. 24, Pages 7519: Quantitative Detection Method for Surface Angled Cracks Based on Laser Ultrasonic Full-Field Scanning Data</title> <link>https://www.mdpi.com/1424-8220/24/23/7519</link> <description>Surface angled cracks on critical components in high-speed machinery can lead to fractures under stress and pressure, posing a significant threat to the operational safety of equipment. To detect surface angled cracks on critical components, this paper proposes a &amp;amp;ldquo;Quantitative Detection Method for Surface Angled Cracks Based on Full-field Scanning Data.&amp;amp;rdquo; By analyzing different ultrasonic signals in the full-field scanning data from laser ultrasonics, the width, angle, and length of surface angled cracks can be determined. This study investigates the propagation behavior of ultrasonic waves and their interaction with surface angled cracks through theoretical calculations. The crack width is solved by analyzing the distribution of Rayleigh waves in the full-field scanning data. This paper also discusses the differences in ultrasonic wave propagation between near-field and far-field detection and identifies the critical point between these regions. Different computational methods are employed to calculate the inclination angle and the crack endpoint at various scan positions. Four sets of experiments were conducted to validate the proposed method, with results showing that the errors in determining the width, angle, and length of the surface angled cracks were all within 5%. This confirms the feasibility of the method for detecting surface angled cracks. The quantitative detection of surface angled cracks on critical components using this method allows for a comprehensive assessment of the component&amp;amp;rsquo;s condition, aiding in the prediction of service life and the mitigation of operational risks. This method shows promising application potential in areas such as aircraft engine blade inspection and gear inspection.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7519: Quantitative Detection Method for Surface Angled Cracks Based on Laser Ultrasonic Full-Field Scanning Data</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7519">doi: 10.3390/s24237519</a></p> <p>Authors: Wang Han Zhang Wang Zi Zhao </p> <p>Surface angled cracks on critical components in high-speed machinery can lead to fractures under stress and pressure, posing a significant threat to the operational safety of equipment. To detect surface angled cracks on critical components, this paper proposes a &amp;amp;ldquo;Quantitative Detection Method for Surface Angled Cracks Based on Full-field Scanning Data.&amp;amp;rdquo; By analyzing different ultrasonic signals in the full-field scanning data from laser ultrasonics, the width, angle, and length of surface angled cracks can be determined. This study investigates the propagation behavior of ultrasonic waves and their interaction with surface angled cracks through theoretical calculations. The crack width is solved by analyzing the distribution of Rayleigh waves in the full-field scanning data. This paper also discusses the differences in ultrasonic wave propagation between near-field and far-field detection and identifies the critical point between these regions. Different computational methods are employed to calculate the inclination angle and the crack endpoint at various scan positions. Four sets of experiments were conducted to validate the proposed method, with results showing that the errors in determining the width, angle, and length of the surface angled cracks were all within 5%. This confirms the feasibility of the method for detecting surface angled cracks. The quantitative detection of surface angled cracks on critical components using this method allows for a comprehensive assessment of the component&amp;amp;rsquo;s condition, aiding in the prediction of service life and the mitigation of operational risks. This method shows promising application potential in areas such as aircraft engine blade inspection and gear inspection.</p> ]]></content:encoded> <dc:title>Quantitative Detection Method for Surface Angled Cracks Based on Laser Ultrasonic Full-Field Scanning Data</dc:title> <dc:creator> Wang</dc:creator> <dc:creator> Han</dc:creator> <dc:creator> Zhang</dc:creator> <dc:creator> Wang</dc:creator> <dc:creator> Zi</dc:creator> <dc:creator> Zhao</dc:creator> <dc:identifier>doi: 10.3390/s24237519</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7519</prism:startingPage> <prism:doi>10.3390/s24237519</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7519</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7520"> <title>Sensors, Vol. 24, Pages 7520: Development of Advanced Positioning Techniques of UWB/Wi-Fi RTT Ranging for Personal Mobility Applications</title> <link>https://www.mdpi.com/1424-8220/24/23/7520</link> <description>&amp;amp;ldquo;Smart&amp;amp;rdquo; devices, such as contemporary smartphones and PDAs (Personal Digital Assistance), play a significant role in our daily live, be it for navigation or location-based services (LBSs). In this paper, the use of Ultra-Wide Band (UWB) and Wireless Fidelity (Wi-Fi) based on RTT (Round-Trip Time) measurements is investigated for pedestrian user localization. For this purpose, several scenarios are designed either using real observation or simulated data. In addition, the localization of user groups within a neighborhood based on collaborative navigation (CP) is investigated and analyzed. An analysis of the performance of these techniques for ranging the positioning estimation using different fusion algorithms is assessed. The methodology applied for CP leverages the hybrid nature of the range measurements obtained by UWB and Wi-Fi RTT systems. The proposed approach stands out due to its originality in two main aspects: (1) it focuses on developing and evaluating suitable models for correcting range errors in RF-based TWR (Two-Way Ranging) technologies, and (2) it emphasizes the development of a robust CP engine for groups of pedestrians. The results obtained demonstrate that a performance improvement with respect to position trueness for UWB and Wi-Fi RTT cases of the order of 74% and 54%, respectively, is achieved due to the integration of these techniques. The proposed localization algorithm based on a P2I/P2P (Peer-to-Infrastructure/Peer-to-Peer) configuration provides a potential improvement in position trueness up to 10% for continuous anchor availability, i.e., UWB known nodes or Wi-Fi access points (APs). Its full potential is evident for short-duration events of complete anchor loss (P2P-only), where an improvement of up to 53% in position trueness is achieved. Overall, the performance metrics estimated based on the extensive evaluation campaigns demonstrate the effectiveness of the proposed methodologies.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7520: Development of Advanced Positioning Techniques of UWB/Wi-Fi RTT Ranging for Personal Mobility Applications</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7520">doi: 10.3390/s24237520</a></p> <p>Authors: Harris Perakis Vassilis Gikas G眉nther Retscher </p> <p>&amp;amp;ldquo;Smart&amp;amp;rdquo; devices, such as contemporary smartphones and PDAs (Personal Digital Assistance), play a significant role in our daily live, be it for navigation or location-based services (LBSs). In this paper, the use of Ultra-Wide Band (UWB) and Wireless Fidelity (Wi-Fi) based on RTT (Round-Trip Time) measurements is investigated for pedestrian user localization. For this purpose, several scenarios are designed either using real observation or simulated data. In addition, the localization of user groups within a neighborhood based on collaborative navigation (CP) is investigated and analyzed. An analysis of the performance of these techniques for ranging the positioning estimation using different fusion algorithms is assessed. The methodology applied for CP leverages the hybrid nature of the range measurements obtained by UWB and Wi-Fi RTT systems. The proposed approach stands out due to its originality in two main aspects: (1) it focuses on developing and evaluating suitable models for correcting range errors in RF-based TWR (Two-Way Ranging) technologies, and (2) it emphasizes the development of a robust CP engine for groups of pedestrians. The results obtained demonstrate that a performance improvement with respect to position trueness for UWB and Wi-Fi RTT cases of the order of 74% and 54%, respectively, is achieved due to the integration of these techniques. The proposed localization algorithm based on a P2I/P2P (Peer-to-Infrastructure/Peer-to-Peer) configuration provides a potential improvement in position trueness up to 10% for continuous anchor availability, i.e., UWB known nodes or Wi-Fi access points (APs). Its full potential is evident for short-duration events of complete anchor loss (P2P-only), where an improvement of up to 53% in position trueness is achieved. Overall, the performance metrics estimated based on the extensive evaluation campaigns demonstrate the effectiveness of the proposed methodologies.</p> ]]></content:encoded> <dc:title>Development of Advanced Positioning Techniques of UWB/Wi-Fi RTT Ranging for Personal Mobility Applications</dc:title> <dc:creator>Harris Perakis</dc:creator> <dc:creator>Vassilis Gikas</dc:creator> <dc:creator>G眉nther Retscher</dc:creator> <dc:identifier>doi: 10.3390/s24237520</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7520</prism:startingPage> <prism:doi>10.3390/s24237520</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7520</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7518"> <title>Sensors, Vol. 24, Pages 7518: Temperature-Based Long-Term Stabilization of Photoacoustic Gas Sensors Using Machine Learning</title> <link>https://www.mdpi.com/1424-8220/24/23/7518</link> <description>In this study, we address the challenge of estimating the resonance frequency of a photoacoustic detector (PAD) gas cell under varying temperature conditions, which is crucial for improving the accuracy of gas concentration measurements. We introduce a novel approach that uses a long short-term memory network and a self-attention mechanism to model resonance frequency shifts based on temperature data. To investigate the impact of the gas mixture temperature on the resonance frequency, we modified the PAD to include an internal temperature sensor. Our experiments involved multiple heating and cooling cycles with varying methane concentrations, resulting in a comprehensive dataset of temperature and resonance frequency measurements. The proposed models were trained and validated on this dataset, and the results demonstrate real-time prediction capabilities with a mean absolute error of less than 1 Hz for frequency shifts exceeding 30 Hz over four-hour periods. This approach allows continuous, real-time tracking of the resonance frequency without interrupting the laser operation, significantly enhancing gas concentration measurements and contributing to the long-term stabilization of the sensor. The results suggest that the proposed approach is effective in managing temperature-induced frequency shifts, making it a valuable tool for improving the accuracy and stability of gas sensors in practical applications.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7518: Temperature-Based Long-Term Stabilization of Photoacoustic Gas Sensors Using Machine Learning</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7518">doi: 10.3390/s24237518</a></p> <p>Authors: Pavel Borozdin Evgenii Erushin Artem Kozmin Anastasia Bednyakova Ilya Miroshnichenko Nadezhda Kostyukova Andrey Boyko Alexey Redyuk </p> <p>In this study, we address the challenge of estimating the resonance frequency of a photoacoustic detector (PAD) gas cell under varying temperature conditions, which is crucial for improving the accuracy of gas concentration measurements. We introduce a novel approach that uses a long short-term memory network and a self-attention mechanism to model resonance frequency shifts based on temperature data. To investigate the impact of the gas mixture temperature on the resonance frequency, we modified the PAD to include an internal temperature sensor. Our experiments involved multiple heating and cooling cycles with varying methane concentrations, resulting in a comprehensive dataset of temperature and resonance frequency measurements. The proposed models were trained and validated on this dataset, and the results demonstrate real-time prediction capabilities with a mean absolute error of less than 1 Hz for frequency shifts exceeding 30 Hz over four-hour periods. This approach allows continuous, real-time tracking of the resonance frequency without interrupting the laser operation, significantly enhancing gas concentration measurements and contributing to the long-term stabilization of the sensor. The results suggest that the proposed approach is effective in managing temperature-induced frequency shifts, making it a valuable tool for improving the accuracy and stability of gas sensors in practical applications.</p> ]]></content:encoded> <dc:title>Temperature-Based Long-Term Stabilization of Photoacoustic Gas Sensors Using Machine Learning</dc:title> <dc:creator>Pavel Borozdin</dc:creator> <dc:creator>Evgenii Erushin</dc:creator> <dc:creator>Artem Kozmin</dc:creator> <dc:creator>Anastasia Bednyakova</dc:creator> <dc:creator>Ilya Miroshnichenko</dc:creator> <dc:creator>Nadezhda Kostyukova</dc:creator> <dc:creator>Andrey Boyko</dc:creator> <dc:creator>Alexey Redyuk</dc:creator> <dc:identifier>doi: 10.3390/s24237518</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7518</prism:startingPage> <prism:doi>10.3390/s24237518</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7518</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7517"> <title>Sensors, Vol. 24, Pages 7517: Fano Resonance-Associated Plasmonic Circular Dichroism in a Multiple-Dipole Interaction Born&amp;ndash;Kuhn Model</title> <link>https://www.mdpi.com/1424-8220/24/23/7517</link> <description>Plasmon chirality has garnered significant interest in sensing application due to its strong electromagnetic field localization and highly tunable optical properties. Understanding the effects of mode coupling in chiral structures on chiral optical activity is particularly important for advancing this field. In this work, we numerically investigate the circular dichroism (CD) of elliptical nanodisk dimers arranged in an up-and-down configuration with a specific rotation angle. By adjusting the inter-particle distance and geometric parameters, we introduce the coupling between dipole and electric hexapole modes, forming an extended Born&amp;amp;ndash;Kuhn model that achieves strong CD. Our findings show that the coupling of dipole modes with electric hexapole modes in elliptical nanodisks can also show obvious Fano resonance and a strong CD effect, and the structure with the largest Fano asymmetry factor shows the highest CD. In addition, CD spectroscopy is highly sensitive to changes in the refractive index of the surrounding medium, especially in the visible and near-infrared regions, highlighting its potential for application in high-sensitivity refractive index sensors.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7517: Fano Resonance-Associated Plasmonic Circular Dichroism in a Multiple-Dipole Interaction Born&amp;ndash;Kuhn Model</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7517">doi: 10.3390/s24237517</a></p> <p>Authors: Wanlu Bian Guodong Zhu Fengcai Ma Tongtong Zhu Yurui Fang </p> <p>Plasmon chirality has garnered significant interest in sensing application due to its strong electromagnetic field localization and highly tunable optical properties. Understanding the effects of mode coupling in chiral structures on chiral optical activity is particularly important for advancing this field. In this work, we numerically investigate the circular dichroism (CD) of elliptical nanodisk dimers arranged in an up-and-down configuration with a specific rotation angle. By adjusting the inter-particle distance and geometric parameters, we introduce the coupling between dipole and electric hexapole modes, forming an extended Born&amp;amp;ndash;Kuhn model that achieves strong CD. Our findings show that the coupling of dipole modes with electric hexapole modes in elliptical nanodisks can also show obvious Fano resonance and a strong CD effect, and the structure with the largest Fano asymmetry factor shows the highest CD. In addition, CD spectroscopy is highly sensitive to changes in the refractive index of the surrounding medium, especially in the visible and near-infrared regions, highlighting its potential for application in high-sensitivity refractive index sensors.</p> ]]></content:encoded> <dc:title>Fano Resonance-Associated Plasmonic Circular Dichroism in a Multiple-Dipole Interaction Born&amp;amp;ndash;Kuhn Model</dc:title> <dc:creator>Wanlu Bian</dc:creator> <dc:creator>Guodong Zhu</dc:creator> <dc:creator>Fengcai Ma</dc:creator> <dc:creator>Tongtong Zhu</dc:creator> <dc:creator>Yurui Fang</dc:creator> <dc:identifier>doi: 10.3390/s24237517</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Communication</prism:section> <prism:startingPage>7517</prism:startingPage> <prism:doi>10.3390/s24237517</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7517</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7514"> <title>Sensors, Vol. 24, Pages 7514: A Shortest Distance Priority UAV Path Planning Algorithm for Precision Agriculture</title> <link>https://www.mdpi.com/1424-8220/24/23/7514</link> <description>Unmanned aerial vehicles (UAVs) have made significant advances in autonomous sensing, particularly in the field of precision agriculture. Effective path planning is critical for autonomous navigation in large orchards to ensure that UAVs are able to recognize the optimal route between the start and end points. When UAVs perform tasks such as crop protection, monitoring, and data collection in orchard environments, they must be able to adapt to dynamic conditions. To address these challenges, this study proposes an enhanced Q-learning algorithm designed to optimize UAV path planning by combining static and dynamic obstacle avoidance features. A shortest distance priority (SDP) strategy is integrated into the learning process to minimize the distance the UAV must travel to reach the target. In addition, the root mean square propagation (RMSP) method is used to dynamically adjust the learning rate according to gradient changes, which accelerates the learning process and improves path planning efficiency. In this study, firstly, the proposed method was compared with state-of-the-art path planning techniques (including A-star, Dijkstra, and traditional Q-learning) in terms of learning time and path length through a grid-based 2D simulation environment. The results showed that the proposed method significantly improved performance compared to existing methods. In addition, 3D simulation experiments were conducted in the AirSim virtual environment. Due to the complexity of the 3D state, a deep neural network was used to calculate the Q-value based on the proposed algorithm. The results indicate that the proposed method can achieve the shortest path planning and obstacle avoidance operations in an orchard 3D simulation environment. Therefore, drones equipped with this algorithm are expected to make outstanding contributions to the development of precision agriculture through intelligent navigation and obstacle avoidance.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7514: A Shortest Distance Priority UAV Path Planning Algorithm for Precision Agriculture</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7514">doi: 10.3390/s24237514</a></p> <p>Authors: Guoqing Zhang Jiandong Liu Wei Luo Yongxiang Zhao Ruiyin Tang Keyu Mei Penggang Wang </p> <p>Unmanned aerial vehicles (UAVs) have made significant advances in autonomous sensing, particularly in the field of precision agriculture. Effective path planning is critical for autonomous navigation in large orchards to ensure that UAVs are able to recognize the optimal route between the start and end points. When UAVs perform tasks such as crop protection, monitoring, and data collection in orchard environments, they must be able to adapt to dynamic conditions. To address these challenges, this study proposes an enhanced Q-learning algorithm designed to optimize UAV path planning by combining static and dynamic obstacle avoidance features. A shortest distance priority (SDP) strategy is integrated into the learning process to minimize the distance the UAV must travel to reach the target. In addition, the root mean square propagation (RMSP) method is used to dynamically adjust the learning rate according to gradient changes, which accelerates the learning process and improves path planning efficiency. In this study, firstly, the proposed method was compared with state-of-the-art path planning techniques (including A-star, Dijkstra, and traditional Q-learning) in terms of learning time and path length through a grid-based 2D simulation environment. The results showed that the proposed method significantly improved performance compared to existing methods. In addition, 3D simulation experiments were conducted in the AirSim virtual environment. Due to the complexity of the 3D state, a deep neural network was used to calculate the Q-value based on the proposed algorithm. The results indicate that the proposed method can achieve the shortest path planning and obstacle avoidance operations in an orchard 3D simulation environment. Therefore, drones equipped with this algorithm are expected to make outstanding contributions to the development of precision agriculture through intelligent navigation and obstacle avoidance.</p> ]]></content:encoded> <dc:title>A Shortest Distance Priority UAV Path Planning Algorithm for Precision Agriculture</dc:title> <dc:creator>Guoqing Zhang</dc:creator> <dc:creator>Jiandong Liu</dc:creator> <dc:creator>Wei Luo</dc:creator> <dc:creator>Yongxiang Zhao</dc:creator> <dc:creator>Ruiyin Tang</dc:creator> <dc:creator>Keyu Mei</dc:creator> <dc:creator>Penggang Wang</dc:creator> <dc:identifier>doi: 10.3390/s24237514</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7514</prism:startingPage> <prism:doi>10.3390/s24237514</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7514</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7516"> <title>Sensors, Vol. 24, Pages 7516: A Deep Learning-Based Method for Bearing Fault Diagnosis with Few-Shot Learning</title> <link>https://www.mdpi.com/1424-8220/24/23/7516</link> <description>To tackle the issue of limited sample data in small sample fault diagnosis for rolling bearings using deep learning, we propose a fault diagnosis method that integrates a KANs-CNN network. Initially, the raw vibration signals are converted into two-dimensional time-frequency images via a continuous wavelet transform. Next, Using CNN combined with KANs for feature extraction, the nonlinear activation of KANs helps extract deep and complex features from the data. After the output of CNN-KANs, an FAN network module is added. The FAN module can employ various feature aggregation strategies, such as weighted averaging, max pooling, addition aggregation, etc., to combine information from multiple feature levels. To further tackle the small sample issue, data generation is performed on the original data through diffusion networks under conditions of fewer samples for bearings and tools, thereby increasing the sample size of the dataset and enhancing fault diagnosis accuracy. Experimental results demonstrate that, under small sample conditions, this method achieves higher accuracy compared to other approaches.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7516: A Deep Learning-Based Method for Bearing Fault Diagnosis with Few-Shot Learning</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7516">doi: 10.3390/s24237516</a></p> <p>Authors: Yang Li Xiaojiao Gu Yonghe Wei </p> <p>To tackle the issue of limited sample data in small sample fault diagnosis for rolling bearings using deep learning, we propose a fault diagnosis method that integrates a KANs-CNN network. Initially, the raw vibration signals are converted into two-dimensional time-frequency images via a continuous wavelet transform. Next, Using CNN combined with KANs for feature extraction, the nonlinear activation of KANs helps extract deep and complex features from the data. After the output of CNN-KANs, an FAN network module is added. The FAN module can employ various feature aggregation strategies, such as weighted averaging, max pooling, addition aggregation, etc., to combine information from multiple feature levels. To further tackle the small sample issue, data generation is performed on the original data through diffusion networks under conditions of fewer samples for bearings and tools, thereby increasing the sample size of the dataset and enhancing fault diagnosis accuracy. Experimental results demonstrate that, under small sample conditions, this method achieves higher accuracy compared to other approaches.</p> ]]></content:encoded> <dc:title>A Deep Learning-Based Method for Bearing Fault Diagnosis with Few-Shot Learning</dc:title> <dc:creator>Yang Li</dc:creator> <dc:creator>Xiaojiao Gu</dc:creator> <dc:creator>Yonghe Wei</dc:creator> <dc:identifier>doi: 10.3390/s24237516</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7516</prism:startingPage> <prism:doi>10.3390/s24237516</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7516</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7515"> <title>Sensors, Vol. 24, Pages 7515: Overview of Key Techniques for In Situ Tests of Electromagnetic Radiation Emission Characteristics</title> <link>https://www.mdpi.com/1424-8220/24/23/7515</link> <description>With the growing number of electronic devices loaded and increasing influence from electromagnetic interference, large-scale systems or platforms are confronted with increasingly severe electromagnetic compatibility challenges. Due to the vast size of these systems and the multitude of electronic devices they contain, standard laboratory environments are often inadequate for meeting test requirements. This paper reviews the state-of-art in the area of field measurement techniques related to the checking of electromagnetic compatibility, and the key technologies of electromagnetic interference filtering and wide-bandwidth, large-dynamic, and rapidly transient signal extraction in the measurement field are analyzed. The research status of electromagnetic interference suppression, transient and broadband measurement, and environmental interference suppression combined with time-domain fast measurement and other technologies are summarized and analyzed. Based on a comparative analysis of the aforementioned technologies, the future development trends of field measurement technology are also discussed.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7515: Overview of Key Techniques for In Situ Tests of Electromagnetic Radiation Emission Characteristics</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7515">doi: 10.3390/s24237515</a></p> <p>Authors: Zhonghao Lu Yan Chen Yunxiao Xue </p> <p>With the growing number of electronic devices loaded and increasing influence from electromagnetic interference, large-scale systems or platforms are confronted with increasingly severe electromagnetic compatibility challenges. Due to the vast size of these systems and the multitude of electronic devices they contain, standard laboratory environments are often inadequate for meeting test requirements. This paper reviews the state-of-art in the area of field measurement techniques related to the checking of electromagnetic compatibility, and the key technologies of electromagnetic interference filtering and wide-bandwidth, large-dynamic, and rapidly transient signal extraction in the measurement field are analyzed. The research status of electromagnetic interference suppression, transient and broadband measurement, and environmental interference suppression combined with time-domain fast measurement and other technologies are summarized and analyzed. Based on a comparative analysis of the aforementioned technologies, the future development trends of field measurement technology are also discussed.</p> ]]></content:encoded> <dc:title>Overview of Key Techniques for In Situ Tests of Electromagnetic Radiation Emission Characteristics</dc:title> <dc:creator>Zhonghao Lu</dc:creator> <dc:creator>Yan Chen</dc:creator> <dc:creator>Yunxiao Xue</dc:creator> <dc:identifier>doi: 10.3390/s24237515</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Review</prism:section> <prism:startingPage>7515</prism:startingPage> <prism:doi>10.3390/s24237515</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7515</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7511"> <title>Sensors, Vol. 24, Pages 7511: BSDA: Bayesian Random Semantic Data Augmentation for Medical Image Classification</title> <link>https://www.mdpi.com/1424-8220/24/23/7511</link> <description>Data augmentation is a crucial regularization technique for deep neural networks, particularly in medical imaging tasks with limited data. Deep learning models are highly effective at linearizing features, enabling the alteration of feature semantics through the shifting of latent space representations&amp;amp;mdash;an approach known as semantic data augmentation (SDA). The paradigm of SDA involves shifting features in a specified direction. Current SDA methods typically sample the amount of shifting from a Gaussian distribution or the sample variance. However, excessive shifting can lead to changes in data labels, which may negatively impact model performance. To address this issue, we propose a computationally efficient method called Bayesian Random Semantic Data Augmentation (BSDA). BSDA can be seamlessly integrated as a plug-and-play component into any neural network. Our experiments demonstrate that BSDA outperforms competitive methods and is suitable for both 2D and 3D medical image datasets, as well as most medical imaging modalities. Additionally, BSDA is compatible with mainstream neural network models and enhances baseline performance. The code is available online.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7511: BSDA: Bayesian Random Semantic Data Augmentation for Medical Image Classification</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7511">doi: 10.3390/s24237511</a></p> <p>Authors: Yaoyao Zhu Xiuding Cai Xueyao Wang Xiaoqing Chen Zhongliang Fu Yu Yao </p> <p>Data augmentation is a crucial regularization technique for deep neural networks, particularly in medical imaging tasks with limited data. Deep learning models are highly effective at linearizing features, enabling the alteration of feature semantics through the shifting of latent space representations&amp;amp;mdash;an approach known as semantic data augmentation (SDA). The paradigm of SDA involves shifting features in a specified direction. Current SDA methods typically sample the amount of shifting from a Gaussian distribution or the sample variance. However, excessive shifting can lead to changes in data labels, which may negatively impact model performance. To address this issue, we propose a computationally efficient method called Bayesian Random Semantic Data Augmentation (BSDA). BSDA can be seamlessly integrated as a plug-and-play component into any neural network. Our experiments demonstrate that BSDA outperforms competitive methods and is suitable for both 2D and 3D medical image datasets, as well as most medical imaging modalities. Additionally, BSDA is compatible with mainstream neural network models and enhances baseline performance. The code is available online.</p> ]]></content:encoded> <dc:title>BSDA: Bayesian Random Semantic Data Augmentation for Medical Image Classification</dc:title> <dc:creator>Yaoyao Zhu</dc:creator> <dc:creator>Xiuding Cai</dc:creator> <dc:creator>Xueyao Wang</dc:creator> <dc:creator>Xiaoqing Chen</dc:creator> <dc:creator>Zhongliang Fu</dc:creator> <dc:creator>Yu Yao</dc:creator> <dc:identifier>doi: 10.3390/s24237511</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7511</prism:startingPage> <prism:doi>10.3390/s24237511</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7511</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7510"> <title>Sensors, Vol. 24, Pages 7510: LPC-SonoNet: A Lightweight Network Based on SonoNet and Light Pyramid Convolution for Fetal Ultrasound Standard Plane Detection</title> <link>https://www.mdpi.com/1424-8220/24/23/7510</link> <description>The detection of fetal ultrasound standard planes (FUSPs) is important for the diagnosis of fetal malformation and the prevention of perinatal death. As a promising deep-learning technique in FUSP detection, SonoNet&amp;amp;rsquo;s network parameters have a large size. In this paper, we introduced a light pyramid convolution (LPC) block into SonoNet and proposed LPC-SonoNet with reduced network parameters for FUSP detection. The LPC block used pyramid convolution architecture inspired by SimSPPF from YOLOv6 and was able to extract features from various scales with a small parameter size. Using SonoNet64 as the backbone, the proposed network removed one of the convolutional blocks in SonoNet64 and replaced the others with LPC blocks. The proposed LPC-SonoNet model was trained and tested on a publicly available dataset with 12,400 ultrasound images. The dataset with six categories was further divided into nine categories. The images were randomly divided into a training set, a validation set, and a test set in a ratio of 8:1:1. Data augmentation was conducted on the training set to address the data imbalance issue. In the classification of six categories and nine categories, LPC-SonoNet obtained the accuracy of 97.0% and 91.9% on the test set, respectively, slightly higher than the accuracy of 96.60% and 91.70% by SonoNet64. Compared with SonoNet64 with 14.9 million parameters, LPC-SonoNet had a much smaller parameter size (4.3 million). This study pioneered the deep-learning classification of nine categories of FUSPs. The proposed LPC-SonoNet may be used as a lightweight network for FUSP detection.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7510: LPC-SonoNet: A Lightweight Network Based on SonoNet and Light Pyramid Convolution for Fetal Ultrasound Standard Plane Detection</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7510">doi: 10.3390/s24237510</a></p> <p>Authors: Tianxiang Yu Po-Hsiang Tsui Denis Leonov Shuicai Wu Guangyu Bin Zhuhuang Zhou </p> <p>The detection of fetal ultrasound standard planes (FUSPs) is important for the diagnosis of fetal malformation and the prevention of perinatal death. As a promising deep-learning technique in FUSP detection, SonoNet&amp;amp;rsquo;s network parameters have a large size. In this paper, we introduced a light pyramid convolution (LPC) block into SonoNet and proposed LPC-SonoNet with reduced network parameters for FUSP detection. The LPC block used pyramid convolution architecture inspired by SimSPPF from YOLOv6 and was able to extract features from various scales with a small parameter size. Using SonoNet64 as the backbone, the proposed network removed one of the convolutional blocks in SonoNet64 and replaced the others with LPC blocks. The proposed LPC-SonoNet model was trained and tested on a publicly available dataset with 12,400 ultrasound images. The dataset with six categories was further divided into nine categories. The images were randomly divided into a training set, a validation set, and a test set in a ratio of 8:1:1. Data augmentation was conducted on the training set to address the data imbalance issue. In the classification of six categories and nine categories, LPC-SonoNet obtained the accuracy of 97.0% and 91.9% on the test set, respectively, slightly higher than the accuracy of 96.60% and 91.70% by SonoNet64. Compared with SonoNet64 with 14.9 million parameters, LPC-SonoNet had a much smaller parameter size (4.3 million). This study pioneered the deep-learning classification of nine categories of FUSPs. The proposed LPC-SonoNet may be used as a lightweight network for FUSP detection.</p> ]]></content:encoded> <dc:title>LPC-SonoNet: A Lightweight Network Based on SonoNet and Light Pyramid Convolution for Fetal Ultrasound Standard Plane Detection</dc:title> <dc:creator>Tianxiang Yu</dc:creator> <dc:creator>Po-Hsiang Tsui</dc:creator> <dc:creator>Denis Leonov</dc:creator> <dc:creator>Shuicai Wu</dc:creator> <dc:creator>Guangyu Bin</dc:creator> <dc:creator>Zhuhuang Zhou</dc:creator> <dc:identifier>doi: 10.3390/s24237510</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7510</prism:startingPage> <prism:doi>10.3390/s24237510</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7510</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7513"> <title>Sensors, Vol. 24, Pages 7513: The Design and Application of an Assistive Hip Joint Exoskeleton for Tower Climbing</title> <link>https://www.mdpi.com/1424-8220/24/23/7513</link> <description>In order to ensure the safety of maintenance personnel during tower climbing and improve the efficiency of power maintenance work, this study designed an assistive hip joint exoskeleton robot and analyzed the kinematic data obtained from tower climbers during the climbing process. A neural-network-based assistive control algorithm for tower climbing was created, and a tower climbing experiment was conducted with volunteers. The surface electromyographic (sEMG) signals of four muscles, namely the biceps femoris (BF), gluteus maximus (GM), semimembranosus (SM), and semitendinosus (ST), were collected to evaluate the performance of the robot. The experimental results show that the exoskeleton robot could reduce the root mean square (RMS) values of the sEMG signals of the main force-generating muscles related to the hip joint. This suggests that the robot can effectively assist personnel in tower climbing operations.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7513: The Design and Application of an Assistive Hip Joint Exoskeleton for Tower Climbing</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7513">doi: 10.3390/s24237513</a></p> <p>Authors: Ming Li Hong Yin Zhan Yang Hongwei Hu Haoyuan Chen Zhijun Fu Xiao Yang Zhao Guo </p> <p>In order to ensure the safety of maintenance personnel during tower climbing and improve the efficiency of power maintenance work, this study designed an assistive hip joint exoskeleton robot and analyzed the kinematic data obtained from tower climbers during the climbing process. A neural-network-based assistive control algorithm for tower climbing was created, and a tower climbing experiment was conducted with volunteers. The surface electromyographic (sEMG) signals of four muscles, namely the biceps femoris (BF), gluteus maximus (GM), semimembranosus (SM), and semitendinosus (ST), were collected to evaluate the performance of the robot. The experimental results show that the exoskeleton robot could reduce the root mean square (RMS) values of the sEMG signals of the main force-generating muscles related to the hip joint. This suggests that the robot can effectively assist personnel in tower climbing operations.</p> ]]></content:encoded> <dc:title>The Design and Application of an Assistive Hip Joint Exoskeleton for Tower Climbing</dc:title> <dc:creator>Ming Li</dc:creator> <dc:creator>Hong Yin</dc:creator> <dc:creator>Zhan Yang</dc:creator> <dc:creator>Hongwei Hu</dc:creator> <dc:creator>Haoyuan Chen</dc:creator> <dc:creator>Zhijun Fu</dc:creator> <dc:creator>Xiao Yang</dc:creator> <dc:creator>Zhao Guo</dc:creator> <dc:identifier>doi: 10.3390/s24237513</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7513</prism:startingPage> <prism:doi>10.3390/s24237513</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7513</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7512"> <title>Sensors, Vol. 24, Pages 7512: A Novel Dataset and Detection Method for Unmanned Aerial Vehicles Using an Improved YOLOv9 Algorithm</title> <link>https://www.mdpi.com/1424-8220/24/23/7512</link> <description>With the growing popularity of unmanned aerial vehicles (UAVs), their improper use is significantly disrupting society. Individuals and organizations have been continuously researching methods for detecting UAVs. However, most existing detection methods fail to account for the impact of similar flying objects, leading to weak anti-interference capabilities. In other words, when such objects appear in the image, the detector may mistakenly identify them as UAVs. Therefore, this study aims to enhance the anti-interference ability of UAV detectors by constructing an anti-interference dataset comprising 5062 images. In addition to UAVs, this dataset also contains three other types of flying objects that are visually similar to the UAV targets: planes, helicopters, and birds. This dataset can be used in model training to help detectors distinguish UAVs from these nontarget objects and thereby improve their anti-interference capabilities. Furthermore, we propose an anti-interference UAV detection method based on YOLOv9-C in which the dot distance is used as an evaluation index to assign positive and negative samples. This results in an increased number of positive samples, improving detector performance in the case of small targets. The comparison of experimental results shows that the developed method has better anti-interference performance than other algorithms. The detection method and dataset used to test the anti-interference capabilities in this study are expected to assist in the development and validation of related research methods.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7512: A Novel Dataset and Detection Method for Unmanned Aerial Vehicles Using an Improved YOLOv9 Algorithm</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7512">doi: 10.3390/s24237512</a></p> <p>Authors: Depeng Gao Jianlin Tang Hongqi Li Bingshu Wang Jianlin Qiu Shuxi Chen Xiangxiang Mei </p> <p>With the growing popularity of unmanned aerial vehicles (UAVs), their improper use is significantly disrupting society. Individuals and organizations have been continuously researching methods for detecting UAVs. However, most existing detection methods fail to account for the impact of similar flying objects, leading to weak anti-interference capabilities. In other words, when such objects appear in the image, the detector may mistakenly identify them as UAVs. Therefore, this study aims to enhance the anti-interference ability of UAV detectors by constructing an anti-interference dataset comprising 5062 images. In addition to UAVs, this dataset also contains three other types of flying objects that are visually similar to the UAV targets: planes, helicopters, and birds. This dataset can be used in model training to help detectors distinguish UAVs from these nontarget objects and thereby improve their anti-interference capabilities. Furthermore, we propose an anti-interference UAV detection method based on YOLOv9-C in which the dot distance is used as an evaluation index to assign positive and negative samples. This results in an increased number of positive samples, improving detector performance in the case of small targets. The comparison of experimental results shows that the developed method has better anti-interference performance than other algorithms. The detection method and dataset used to test the anti-interference capabilities in this study are expected to assist in the development and validation of related research methods.</p> ]]></content:encoded> <dc:title>A Novel Dataset and Detection Method for Unmanned Aerial Vehicles Using an Improved YOLOv9 Algorithm</dc:title> <dc:creator>Depeng Gao</dc:creator> <dc:creator>Jianlin Tang</dc:creator> <dc:creator>Hongqi Li</dc:creator> <dc:creator>Bingshu Wang</dc:creator> <dc:creator>Jianlin Qiu</dc:creator> <dc:creator>Shuxi Chen</dc:creator> <dc:creator>Xiangxiang Mei</dc:creator> <dc:identifier>doi: 10.3390/s24237512</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7512</prism:startingPage> <prism:doi>10.3390/s24237512</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7512</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7509"> <title>Sensors, Vol. 24, Pages 7509: Modeling and Optimization of Energy Harvesters for Specific Applications Using COMSOL and Equivalent Spring Models</title> <link>https://www.mdpi.com/1424-8220/24/23/7509</link> <description>Energy harvesting from natural sources, including bodily movements, vehicle engine vibrations, and ocean waves, poses challenges due to the broad range of frequency bands involved. Piezoelectric materials are frequently used in energy harvesters, although their effectiveness depends on aligning the device&amp;amp;rsquo;s natural frequency with the frequency of the target energy source. This study models energy harvesters customized for specific applications by adjusting their natural frequencies to match the required bandwidth. We evaluate commercially available piezoelectric transducers and model them using COMSOL Multiphysics alongside an equivalent spring-mass schematic approach, enabling precise adjustments to optimize energy capture. The proposed system achieves a maximum power output of 160 &amp;amp;micro;W and a power density of 187.35 &amp;amp;micro;W/cm3 at a natural frequency of 65 Hz. Furthermore, the theoretical maximum power density is calculated as 692.97 W/m3, demonstrating the system&amp;amp;rsquo;s potential for high energy efficiency under optimal conditions. Simulations are validated against experimental data to ensure accuracy. Our findings provide a design framework for optimizing energy harvester performance across diverse energy sources, leading to more efficient and application-specific devices for varied environmental conditions.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7509: Modeling and Optimization of Energy Harvesters for Specific Applications Using COMSOL and Equivalent Spring Models</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7509">doi: 10.3390/s24237509</a></p> <p>Authors: Tharun Reddy Kandukuri Caizhi Liao Luigi G. Occhipinti </p> <p>Energy harvesting from natural sources, including bodily movements, vehicle engine vibrations, and ocean waves, poses challenges due to the broad range of frequency bands involved. Piezoelectric materials are frequently used in energy harvesters, although their effectiveness depends on aligning the device&amp;amp;rsquo;s natural frequency with the frequency of the target energy source. This study models energy harvesters customized for specific applications by adjusting their natural frequencies to match the required bandwidth. We evaluate commercially available piezoelectric transducers and model them using COMSOL Multiphysics alongside an equivalent spring-mass schematic approach, enabling precise adjustments to optimize energy capture. The proposed system achieves a maximum power output of 160 &amp;amp;micro;W and a power density of 187.35 &amp;amp;micro;W/cm3 at a natural frequency of 65 Hz. Furthermore, the theoretical maximum power density is calculated as 692.97 W/m3, demonstrating the system&amp;amp;rsquo;s potential for high energy efficiency under optimal conditions. Simulations are validated against experimental data to ensure accuracy. Our findings provide a design framework for optimizing energy harvester performance across diverse energy sources, leading to more efficient and application-specific devices for varied environmental conditions.</p> ]]></content:encoded> <dc:title>Modeling and Optimization of Energy Harvesters for Specific Applications Using COMSOL and Equivalent Spring Models</dc:title> <dc:creator>Tharun Reddy Kandukuri</dc:creator> <dc:creator>Caizhi Liao</dc:creator> <dc:creator>Luigi G. Occhipinti</dc:creator> <dc:identifier>doi: 10.3390/s24237509</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7509</prism:startingPage> <prism:doi>10.3390/s24237509</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7509</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7508"> <title>Sensors, Vol. 24, Pages 7508: A Multivariable Probability Density-Based Auto-Reconstruction Bi-LSTM Soft Sensor for Predicting Effluent BOD in Wastewater Treatment Plants</title> <link>https://www.mdpi.com/1424-8220/24/23/7508</link> <description>The precise detection of effluent biological oxygen demand (BOD) is crucial for the stable operation of wastewater treatment plants (WWTPs). However, existing detection methods struggle to meet the evolving drainage standards and management requirements. To address this issue, this paper proposed a multivariable probability density-based auto-reconstruction bidirectional long short-term memory (MPDAR-Bi-LSTM) soft sensor for predicting effluent BOD, enhancing the prediction accuracy and efficiency. Firstly, the selection of appropriate auxiliary variables for soft-sensor modeling is determined through the calculation of k-nearest-neighbor mutual information (KNN-MI) values between the global process variables and effluent BOD. Subsequently, considering the existence of strong interactions among different reaction tanks, a Bi-LSTM neural network prediction model is constructed with historical data. Then, a multivariate probability density-based auto-reconstruction (MPDAR) strategy is developed for adaptive updating of the prediction model, thereby enhancing its robustness. Finally, the effectiveness of the proposed soft sensor is demonstrated through experiments using the dataset from Benchmark Simulation Model No.1 (BSM1). The experimental results indicate that the proposed soft sensor not only outperforms some traditional models in terms of prediction performance but also excels in avoiding ineffective model reconstructions in scenarios involving complex dynamic wastewater treatment conditions.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7508: A Multivariable Probability Density-Based Auto-Reconstruction Bi-LSTM Soft Sensor for Predicting Effluent BOD in Wastewater Treatment Plants</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7508">doi: 10.3390/s24237508</a></p> <p>Authors: Wenting Li Yonggang Li Dong Li Jiayi Zhou </p> <p>The precise detection of effluent biological oxygen demand (BOD) is crucial for the stable operation of wastewater treatment plants (WWTPs). However, existing detection methods struggle to meet the evolving drainage standards and management requirements. To address this issue, this paper proposed a multivariable probability density-based auto-reconstruction bidirectional long short-term memory (MPDAR-Bi-LSTM) soft sensor for predicting effluent BOD, enhancing the prediction accuracy and efficiency. Firstly, the selection of appropriate auxiliary variables for soft-sensor modeling is determined through the calculation of k-nearest-neighbor mutual information (KNN-MI) values between the global process variables and effluent BOD. Subsequently, considering the existence of strong interactions among different reaction tanks, a Bi-LSTM neural network prediction model is constructed with historical data. Then, a multivariate probability density-based auto-reconstruction (MPDAR) strategy is developed for adaptive updating of the prediction model, thereby enhancing its robustness. Finally, the effectiveness of the proposed soft sensor is demonstrated through experiments using the dataset from Benchmark Simulation Model No.1 (BSM1). The experimental results indicate that the proposed soft sensor not only outperforms some traditional models in terms of prediction performance but also excels in avoiding ineffective model reconstructions in scenarios involving complex dynamic wastewater treatment conditions.</p> ]]></content:encoded> <dc:title>A Multivariable Probability Density-Based Auto-Reconstruction Bi-LSTM Soft Sensor for Predicting Effluent BOD in Wastewater Treatment Plants</dc:title> <dc:creator>Wenting Li</dc:creator> <dc:creator>Yonggang Li</dc:creator> <dc:creator>Dong Li</dc:creator> <dc:creator>Jiayi Zhou</dc:creator> <dc:identifier>doi: 10.3390/s24237508</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7508</prism:startingPage> <prism:doi>10.3390/s24237508</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7508</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7507"> <title>Sensors, Vol. 24, Pages 7507: Seasonal and Temporal Ensemble Models for Accurate Near-Surface Air Temperature Estimation</title> <link>https://www.mdpi.com/1424-8220/24/23/7507</link> <description>The near-surface air temperature (NSAT) is crucial for understanding thermal and urban environments. Traditional estimation methods using general remote sensing images often focus on the types of spatial data or machine learning models used, neglecting the importance of seasonal and temporal variations, limiting their accuracy. This study introduces a novel ensemble model that incorporates both seasonal and temporal information integrated with satellite-derived land surface temperature (LST) data to enhance NSAT estimation, along with a rigorous feature importance analysis to identify the most impactful parameters. Data from 2022, collected from 147 South Korean weather stations, were used to develop and evaluate the models. Thirteen initial variables, including the LST and other auxiliary data, were considered. Random forest regression was employed to build separate models for each season. This novel approach of separating data by season allowed optimized feature selection tailored to each season, improving the model efficiency and capturing finer seasonal and daily temperature variations. These seasonal models were then combined to form an ensemble model. The seasonal models demonstrated varying accuracy, with the R2 values indicating a strong correlation between the predicted and actual NSAT, particularly high in spring and fall and lower in summer and winter. The ensemble model showed improved performance, achieving an MAE of 0.534, an RMSE of 0.391, an R2 of 0.996, and a cross-validated R2 of 0.968. These findings highlight the effectiveness of incorporating seasonal and temporal information into NSAT estimation models, offering significant improvements over traditional approaches. The developed models support precise temperature monitoring and forecasting, aiding environmental and urban management.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7507: Seasonal and Temporal Ensemble Models for Accurate Near-Surface Air Temperature Estimation</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7507">doi: 10.3390/s24237507</a></p> <p>Authors: Rey Jalbuena Jurng-Jae Yee </p> <p>The near-surface air temperature (NSAT) is crucial for understanding thermal and urban environments. Traditional estimation methods using general remote sensing images often focus on the types of spatial data or machine learning models used, neglecting the importance of seasonal and temporal variations, limiting their accuracy. This study introduces a novel ensemble model that incorporates both seasonal and temporal information integrated with satellite-derived land surface temperature (LST) data to enhance NSAT estimation, along with a rigorous feature importance analysis to identify the most impactful parameters. Data from 2022, collected from 147 South Korean weather stations, were used to develop and evaluate the models. Thirteen initial variables, including the LST and other auxiliary data, were considered. Random forest regression was employed to build separate models for each season. This novel approach of separating data by season allowed optimized feature selection tailored to each season, improving the model efficiency and capturing finer seasonal and daily temperature variations. These seasonal models were then combined to form an ensemble model. The seasonal models demonstrated varying accuracy, with the R2 values indicating a strong correlation between the predicted and actual NSAT, particularly high in spring and fall and lower in summer and winter. The ensemble model showed improved performance, achieving an MAE of 0.534, an RMSE of 0.391, an R2 of 0.996, and a cross-validated R2 of 0.968. These findings highlight the effectiveness of incorporating seasonal and temporal information into NSAT estimation models, offering significant improvements over traditional approaches. The developed models support precise temperature monitoring and forecasting, aiding environmental and urban management.</p> ]]></content:encoded> <dc:title>Seasonal and Temporal Ensemble Models for Accurate Near-Surface Air Temperature Estimation</dc:title> <dc:creator>Rey Jalbuena</dc:creator> <dc:creator>Jurng-Jae Yee</dc:creator> <dc:identifier>doi: 10.3390/s24237507</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7507</prism:startingPage> <prism:doi>10.3390/s24237507</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7507</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7505"> <title>Sensors, Vol. 24, Pages 7505: Determining the Level of Threat in Maritime Navigation Based on the Detection of Small Floating Objects with Deep Neural Networks</title> <link>https://www.mdpi.com/1424-8220/24/23/7505</link> <description>The article describes the use of deep neural networks to detect small floating objects located in a vessel&amp;amp;rsquo;s path. The research aimed to evaluate the performance of deep neural networks by classifying sea surface images and assigning the level of threat resulting from the detection of objects floating on the water, such as fishing nets, plastic debris, or buoys. Such a solution could function as a decision support system capable of detecting and informing the watch officer or helmsman about possible threats and reducing the risk of overlooking them at a critical moment. Several neural network structures were compared to find the most efficient solution, taking into account the speed and efficiency of network training and its performance during testing. Additional time measurements have been made to test the real-time capabilities of the system. The research results confirm that it is possible to create a practical lightweight detection system with convolutional neural networks that calculates safety level in real time.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7505: Determining the Level of Threat in Maritime Navigation Based on the Detection of Small Floating Objects with Deep Neural Networks</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7505">doi: 10.3390/s24237505</a></p> <p>Authors: Miros艂aw 艁膮cki </p> <p>The article describes the use of deep neural networks to detect small floating objects located in a vessel&amp;amp;rsquo;s path. The research aimed to evaluate the performance of deep neural networks by classifying sea surface images and assigning the level of threat resulting from the detection of objects floating on the water, such as fishing nets, plastic debris, or buoys. Such a solution could function as a decision support system capable of detecting and informing the watch officer or helmsman about possible threats and reducing the risk of overlooking them at a critical moment. Several neural network structures were compared to find the most efficient solution, taking into account the speed and efficiency of network training and its performance during testing. Additional time measurements have been made to test the real-time capabilities of the system. The research results confirm that it is possible to create a practical lightweight detection system with convolutional neural networks that calculates safety level in real time.</p> ]]></content:encoded> <dc:title>Determining the Level of Threat in Maritime Navigation Based on the Detection of Small Floating Objects with Deep Neural Networks</dc:title> <dc:creator>Miros艂aw 艁膮cki</dc:creator> <dc:identifier>doi: 10.3390/s24237505</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Communication</prism:section> <prism:startingPage>7505</prism:startingPage> <prism:doi>10.3390/s24237505</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7505</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7506"> <title>Sensors, Vol. 24, Pages 7506: A Linear Rehabilitative Motion Planning Method with a Multi-Posture Lower-Limb Rehabilitation Robot</title> <link>https://www.mdpi.com/1424-8220/24/23/7506</link> <description>In rehabilitation, physicians plan lower-limb exercises via linear guidance. Ensuring efficacy and safety, they design patient-specific paths, carefully plotting smooth trajectories to minimize jerks. Replicating their precision in robotics is a major challenge. This study introduces a linear rehabilitation motion planning method designed for physicians to use a multi-posture lower-limb rehabilitation robot, encompassing both path and trajectory planning. By subdividing the lower limb&amp;amp;rsquo;s action space into four distinct training sections and classifying this space, we articulate the correlation between linear trajectories and key joint rehabilitation metrics. Building upon this foundation, a rehabilitative path generation system is developed, anchored in joint rehabilitation indicators. Subsequently, high-order polynomial curves are employed to mimic the smooth continuity of traditional rehabilitation trajectories and joint motions. Furthermore, trajectory planning is refined through the resolution of a constrained quadratic optimization problem, aiming to minimize the abrupt jerks in the trajectory. The optimized trajectories derived from our experiments are compared with randomly generated trajectories, demonstrating the suitability of trajectory optimization for real-time rehabilitation trajectory planning. Additionally, we compare trajectories generated based on the two groups of joint rehabilitation indicators, indicating that the proposed path generation system effectively assists clinicians in executing efficient and precise robot-assisted rehabilitation path planning.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7506: A Linear Rehabilitative Motion Planning Method with a Multi-Posture Lower-Limb Rehabilitation Robot</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7506">doi: 10.3390/s24237506</a></p> <p>Authors: Xincheng Wang Musong Lin Lingfeng Sang Hongbo Wang Yongfei Feng Jianye Niu Hongfei Yu Bo Cheng </p> <p>In rehabilitation, physicians plan lower-limb exercises via linear guidance. Ensuring efficacy and safety, they design patient-specific paths, carefully plotting smooth trajectories to minimize jerks. Replicating their precision in robotics is a major challenge. This study introduces a linear rehabilitation motion planning method designed for physicians to use a multi-posture lower-limb rehabilitation robot, encompassing both path and trajectory planning. By subdividing the lower limb&amp;amp;rsquo;s action space into four distinct training sections and classifying this space, we articulate the correlation between linear trajectories and key joint rehabilitation metrics. Building upon this foundation, a rehabilitative path generation system is developed, anchored in joint rehabilitation indicators. Subsequently, high-order polynomial curves are employed to mimic the smooth continuity of traditional rehabilitation trajectories and joint motions. Furthermore, trajectory planning is refined through the resolution of a constrained quadratic optimization problem, aiming to minimize the abrupt jerks in the trajectory. The optimized trajectories derived from our experiments are compared with randomly generated trajectories, demonstrating the suitability of trajectory optimization for real-time rehabilitation trajectory planning. Additionally, we compare trajectories generated based on the two groups of joint rehabilitation indicators, indicating that the proposed path generation system effectively assists clinicians in executing efficient and precise robot-assisted rehabilitation path planning.</p> ]]></content:encoded> <dc:title>A Linear Rehabilitative Motion Planning Method with a Multi-Posture Lower-Limb Rehabilitation Robot</dc:title> <dc:creator>Xincheng Wang</dc:creator> <dc:creator>Musong Lin</dc:creator> <dc:creator>Lingfeng Sang</dc:creator> <dc:creator>Hongbo Wang</dc:creator> <dc:creator>Yongfei Feng</dc:creator> <dc:creator>Jianye Niu</dc:creator> <dc:creator>Hongfei Yu</dc:creator> <dc:creator>Bo Cheng</dc:creator> <dc:identifier>doi: 10.3390/s24237506</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7506</prism:startingPage> <prism:doi>10.3390/s24237506</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7506</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7504"> <title>Sensors, Vol. 24, Pages 7504: Fractional-Order Identification of Gyroscope MEMS Noise Under Various Temperature Conditions</title> <link>https://www.mdpi.com/1424-8220/24/23/7504</link> <description>This paper deals with identifying the fractional-order noise parameters for MEMS gyroscopes under various temperature conditions. The significant contribution of the paper is to investigate the relation between the fractional noise model of MEMS devices and different ambient temperatures. In our paper, variance, correlation, and introduced estimation analysis methods have been meticulously applied to determine noise parameters with fractional-order dynamics. Experimental data were collected precisely under various ambient temperatures, while the MEMS device was located in a climate chamber. The origin of the paper is motivated by a project entitled &amp;amp;ldquo;Family of optoelectronic heads for guided missiles&amp;amp;mdash;SEEKER&amp;amp;rdquo;, where the IMU sensor is a crucial electronic device used to measure the angular velocity of the optoelectronic head. It is widely known that the IMU measurements built-in MEMS technology often come with a random walk, as well as biases and noises affecting the final results.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7504: Fractional-Order Identification of Gyroscope MEMS Noise Under Various Temperature Conditions</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7504">doi: 10.3390/s24237504</a></p> <p>Authors: Dominik Sierociuk Michal Macias Konrad Andrzej Markowski </p> <p>This paper deals with identifying the fractional-order noise parameters for MEMS gyroscopes under various temperature conditions. The significant contribution of the paper is to investigate the relation between the fractional noise model of MEMS devices and different ambient temperatures. In our paper, variance, correlation, and introduced estimation analysis methods have been meticulously applied to determine noise parameters with fractional-order dynamics. Experimental data were collected precisely under various ambient temperatures, while the MEMS device was located in a climate chamber. The origin of the paper is motivated by a project entitled &amp;amp;ldquo;Family of optoelectronic heads for guided missiles&amp;amp;mdash;SEEKER&amp;amp;rdquo;, where the IMU sensor is a crucial electronic device used to measure the angular velocity of the optoelectronic head. It is widely known that the IMU measurements built-in MEMS technology often come with a random walk, as well as biases and noises affecting the final results.</p> ]]></content:encoded> <dc:title>Fractional-Order Identification of Gyroscope MEMS Noise Under Various Temperature Conditions</dc:title> <dc:creator>Dominik Sierociuk</dc:creator> <dc:creator>Michal Macias</dc:creator> <dc:creator>Konrad Andrzej Markowski</dc:creator> <dc:identifier>doi: 10.3390/s24237504</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Communication</prism:section> <prism:startingPage>7504</prism:startingPage> <prism:doi>10.3390/s24237504</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7504</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7503"> <title>Sensors, Vol. 24, Pages 7503: A Large-Scale Building Unsupervised Extraction Method Leveraging Airborne LiDAR Point Clouds and Remote Sensing Images Based on a Dual P-Snake Model</title> <link>https://www.mdpi.com/1424-8220/24/23/7503</link> <description>Automatic large-scale building extraction from the LiDAR point clouds and remote sensing images is a growing focus in the fields of the sensor applications and remote sensing. However, this building extraction task remains highly challenging due to the complexity of building sizes, shapes, and surrounding environments. In addition, the discreteness, sparsity, and irregular distribution of point clouds, lighting, and shadows, as well as occlusions of the images, also seriously affect the accuracy of building extraction. To address the above issues, we propose a new unsupervised building extraction algorithm PBEA (Point and Pixel Building Extraction Algorithm) based on a new dual P-snake model (Dual Point and Pixel Snake Model). The proposed dual P-snake model is an enhanced active boundary model, which uses both point clouds and images simultaneously to obtain the inner and outer boundaries. The proposed dual P-snake model enables interaction and convergence between the inner and outer boundaries to improve the performance of building boundary detection, especially in complex scenes. Using the dual P-snake model and polygonization, this proposed PBEA can accurately extract large-scale buildings. We evaluated our PBEA and dual P-snake model on the ISPRS Vaihingen dataset and the Toronto dataset. The experimental results show that our PBEA achieves an area-based quality evaluation metric of 90.0% on the Vaihingen dataset and achieves the area-based quality evaluation metric of 92.4% on the Toronto dataset. Compared with other methods, our method demonstrates satisfactory performance.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7503: A Large-Scale Building Unsupervised Extraction Method Leveraging Airborne LiDAR Point Clouds and Remote Sensing Images Based on a Dual P-Snake Model</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7503">doi: 10.3390/s24237503</a></p> <p>Authors: Zeyu Tian Yong Fang Xiaohui Fang Yan Ma Han Li </p> <p>Automatic large-scale building extraction from the LiDAR point clouds and remote sensing images is a growing focus in the fields of the sensor applications and remote sensing. However, this building extraction task remains highly challenging due to the complexity of building sizes, shapes, and surrounding environments. In addition, the discreteness, sparsity, and irregular distribution of point clouds, lighting, and shadows, as well as occlusions of the images, also seriously affect the accuracy of building extraction. To address the above issues, we propose a new unsupervised building extraction algorithm PBEA (Point and Pixel Building Extraction Algorithm) based on a new dual P-snake model (Dual Point and Pixel Snake Model). The proposed dual P-snake model is an enhanced active boundary model, which uses both point clouds and images simultaneously to obtain the inner and outer boundaries. The proposed dual P-snake model enables interaction and convergence between the inner and outer boundaries to improve the performance of building boundary detection, especially in complex scenes. Using the dual P-snake model and polygonization, this proposed PBEA can accurately extract large-scale buildings. We evaluated our PBEA and dual P-snake model on the ISPRS Vaihingen dataset and the Toronto dataset. The experimental results show that our PBEA achieves an area-based quality evaluation metric of 90.0% on the Vaihingen dataset and achieves the area-based quality evaluation metric of 92.4% on the Toronto dataset. Compared with other methods, our method demonstrates satisfactory performance.</p> ]]></content:encoded> <dc:title>A Large-Scale Building Unsupervised Extraction Method Leveraging Airborne LiDAR Point Clouds and Remote Sensing Images Based on a Dual P-Snake Model</dc:title> <dc:creator>Zeyu Tian</dc:creator> <dc:creator>Yong Fang</dc:creator> <dc:creator>Xiaohui Fang</dc:creator> <dc:creator>Yan Ma</dc:creator> <dc:creator>Han Li</dc:creator> <dc:identifier>doi: 10.3390/s24237503</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7503</prism:startingPage> <prism:doi>10.3390/s24237503</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7503</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7500"> <title>Sensors, Vol. 24, Pages 7500: Flat-Knitted Double-Tube Structure Capacitive Pressure Sensors Integrated into Fingertips of Fully Fashioned Glove Intended for Therapeutic Use</title> <link>https://www.mdpi.com/1424-8220/24/23/7500</link> <description>A therapeutic glove, which enables medical non-professionals to perform physiotherapeutic gripping and holding movements on patients, would significantly improve the healthcare situation in physiotherapy. The glove aims to detect the orthogonal pressure load and provide feedback to the user. The use of textile materials for the glove assures comfort and a good fit for the user. This, in turn, implies a textile realization of the sensor system in order to manufacture both the glove and the sensor system in as few process steps as possible, using only one textile manufacturing technique. The flat knitting technology is an obvious choice here. The aim of the study is to develop a textile capacitive pressure sensor that can be integrated into the fingertips of a glove using flat knitting technology and to evaluate its sensor properties with regard to transmission behavior, hysteresis and drift. It was shown that the proposed method of a flat knitting sensor fabrication is suitable for producing both the sensors and the glove in one single process step. In addition, the implementation of an entire glove with integrated pressure sensors, including the necessary electrical connection of the sensor electrodes via knitted conductive paths in three fingers, was successfully demonstrated.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7500: Flat-Knitted Double-Tube Structure Capacitive Pressure Sensors Integrated into Fingertips of Fully Fashioned Glove Intended for Therapeutic Use</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7500">doi: 10.3390/s24237500</a></p> <p>Authors: Susanne Fischer Carola B枚hmer Shamima Nasrin Carmen Sachse Chokri Cherif </p> <p>A therapeutic glove, which enables medical non-professionals to perform physiotherapeutic gripping and holding movements on patients, would significantly improve the healthcare situation in physiotherapy. The glove aims to detect the orthogonal pressure load and provide feedback to the user. The use of textile materials for the glove assures comfort and a good fit for the user. This, in turn, implies a textile realization of the sensor system in order to manufacture both the glove and the sensor system in as few process steps as possible, using only one textile manufacturing technique. The flat knitting technology is an obvious choice here. The aim of the study is to develop a textile capacitive pressure sensor that can be integrated into the fingertips of a glove using flat knitting technology and to evaluate its sensor properties with regard to transmission behavior, hysteresis and drift. It was shown that the proposed method of a flat knitting sensor fabrication is suitable for producing both the sensors and the glove in one single process step. In addition, the implementation of an entire glove with integrated pressure sensors, including the necessary electrical connection of the sensor electrodes via knitted conductive paths in three fingers, was successfully demonstrated.</p> ]]></content:encoded> <dc:title>Flat-Knitted Double-Tube Structure Capacitive Pressure Sensors Integrated into Fingertips of Fully Fashioned Glove Intended for Therapeutic Use</dc:title> <dc:creator>Susanne Fischer</dc:creator> <dc:creator>Carola B枚hmer</dc:creator> <dc:creator>Shamima Nasrin</dc:creator> <dc:creator>Carmen Sachse</dc:creator> <dc:creator>Chokri Cherif</dc:creator> <dc:identifier>doi: 10.3390/s24237500</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7500</prism:startingPage> <prism:doi>10.3390/s24237500</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7500</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7502"> <title>Sensors, Vol. 24, Pages 7502: A Lightweight and High Yield Complementary Metal-Oxide Semiconductor True Random Number Generator with Lightweight Photon Post-Processing</title> <link>https://www.mdpi.com/1424-8220/24/23/7502</link> <description>This paper introduces a novel TRNG architecture that employs a wave converter to generate random outputs from the jitter noise in a customized ring oscillator (RO). Using a current-starved inverter, the proposed RO offers the option of operating three different oscillation frequencies from a single oscillator. To assess its performance, the core TRNG proposed in this work was designed with multiple samples, employing various transistor sizes for 28 nm CMOS processes. The measurements show that only a small number of measured TRNG samples passed the randomness NIST SP 800-22 tests, which is a common problem, not only with the proposed TRNG but also with other TRNG structures. To solve this issue, a lightweight post-processing algorithm using the Photon hash function was newly applied to the proposed TRNGs topology. The lightweight Photon hash function-based post-processing was implemented with the proposed TRNG topology in a 28 nm CMOS process. The design occupies 16,498 &amp;amp;micro;m2, with a throughput of 0.0142 Mbps and power consumption of 31.12 mW. Measurements showed significant improvement, with a 50% increase in chips passing the NIST SP 800-22 tests. Compared with the conventional DRBG post-processing method, the proposed lightweight Photon post-processing reduces area occupation by five times and power consumption by 65%.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7502: A Lightweight and High Yield Complementary Metal-Oxide Semiconductor True Random Number Generator with Lightweight Photon Post-Processing</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7502">doi: 10.3390/s24237502</a></p> <p>Authors: Chi Trung Ngo Hyun Woo Ko Ji Woo Choi Jae-Won Nam Jong-Phil Hong </p> <p>This paper introduces a novel TRNG architecture that employs a wave converter to generate random outputs from the jitter noise in a customized ring oscillator (RO). Using a current-starved inverter, the proposed RO offers the option of operating three different oscillation frequencies from a single oscillator. To assess its performance, the core TRNG proposed in this work was designed with multiple samples, employing various transistor sizes for 28 nm CMOS processes. The measurements show that only a small number of measured TRNG samples passed the randomness NIST SP 800-22 tests, which is a common problem, not only with the proposed TRNG but also with other TRNG structures. To solve this issue, a lightweight post-processing algorithm using the Photon hash function was newly applied to the proposed TRNGs topology. The lightweight Photon hash function-based post-processing was implemented with the proposed TRNG topology in a 28 nm CMOS process. The design occupies 16,498 &amp;amp;micro;m2, with a throughput of 0.0142 Mbps and power consumption of 31.12 mW. Measurements showed significant improvement, with a 50% increase in chips passing the NIST SP 800-22 tests. Compared with the conventional DRBG post-processing method, the proposed lightweight Photon post-processing reduces area occupation by five times and power consumption by 65%.</p> ]]></content:encoded> <dc:title>A Lightweight and High Yield Complementary Metal-Oxide Semiconductor True Random Number Generator with Lightweight Photon Post-Processing</dc:title> <dc:creator>Chi Trung Ngo</dc:creator> <dc:creator>Hyun Woo Ko</dc:creator> <dc:creator>Ji Woo Choi</dc:creator> <dc:creator>Jae-Won Nam</dc:creator> <dc:creator>Jong-Phil Hong</dc:creator> <dc:identifier>doi: 10.3390/s24237502</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7502</prism:startingPage> <prism:doi>10.3390/s24237502</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7502</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7501"> <title>Sensors, Vol. 24, Pages 7501: Online Monitoring of Catalytic Processes by Fiber-Enhanced Raman Spectroscopy</title> <link>https://www.mdpi.com/1424-8220/24/23/7501</link> <description>An innovative solution for real-time monitoring of reactions within confined spaces, optimized for Raman spectroscopy applications, is presented. This approach involves the utilization of a hollow-core waveguide configured as a compact flow cell, serving both as a conduit for Raman excitation and scattering and seamlessly integrating into the effluent stream of a cracking catalytic reactor. The analytical technique, encompassing device and optical design, ensures robustness, compactness, and cost-effectiveness for implementation into process facilities. Notably, the modularity of the approach empowers customization for diverse gas monitoring needs, as it readily adapts to the specific requirements of various sensing scenarios. As a proof of concept, the efficacy of a spectroscopic approach is shown by monitoring two catalytic processes: CO2 methanation (CO2 + 4H2 &amp;amp;rarr; CH4 + 2H2O) and ammonia cracking (2NH3 &amp;amp;rarr; N2 + 3H2). Leveraging chemometric data processing techniques, spectral signatures of the individual components involved in these reactions are effectively disentangled and the results are compared to mass spectrometry data. This robust methodology underscores the versatility and reliability of this monitoring system in complex chemical environments.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7501: Online Monitoring of Catalytic Processes by Fiber-Enhanced Raman Spectroscopy</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7501">doi: 10.3390/s24237501</a></p> <p>Authors: John T. Kelly Christopher J. Koch Robert Lascola Tyler Guin </p> <p>An innovative solution for real-time monitoring of reactions within confined spaces, optimized for Raman spectroscopy applications, is presented. This approach involves the utilization of a hollow-core waveguide configured as a compact flow cell, serving both as a conduit for Raman excitation and scattering and seamlessly integrating into the effluent stream of a cracking catalytic reactor. The analytical technique, encompassing device and optical design, ensures robustness, compactness, and cost-effectiveness for implementation into process facilities. Notably, the modularity of the approach empowers customization for diverse gas monitoring needs, as it readily adapts to the specific requirements of various sensing scenarios. As a proof of concept, the efficacy of a spectroscopic approach is shown by monitoring two catalytic processes: CO2 methanation (CO2 + 4H2 &amp;amp;rarr; CH4 + 2H2O) and ammonia cracking (2NH3 &amp;amp;rarr; N2 + 3H2). Leveraging chemometric data processing techniques, spectral signatures of the individual components involved in these reactions are effectively disentangled and the results are compared to mass spectrometry data. This robust methodology underscores the versatility and reliability of this monitoring system in complex chemical environments.</p> ]]></content:encoded> <dc:title>Online Monitoring of Catalytic Processes by Fiber-Enhanced Raman Spectroscopy</dc:title> <dc:creator>John T. Kelly</dc:creator> <dc:creator>Christopher J. Koch</dc:creator> <dc:creator>Robert Lascola</dc:creator> <dc:creator>Tyler Guin</dc:creator> <dc:identifier>doi: 10.3390/s24237501</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Communication</prism:section> <prism:startingPage>7501</prism:startingPage> <prism:doi>10.3390/s24237501</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7501</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7499"> <title>Sensors, Vol. 24, Pages 7499: A New Compressed Data Acquisition Method for Power System Based on Chaotic Compressive Measurement</title> <link>https://www.mdpi.com/1424-8220/24/23/7499</link> <description>The digitalization level of the new power system driven by &amp;amp;ldquo;dual carbon&amp;amp;rdquo; is increasing, leading to a growth in the amount of data that need to be acquired. This has intensified the contradiction between data volume and acquisition capacity. Therefore, it is urgent to study compressed data acquisition methods for power systems based on data compression. In this regard, a novel compressed data acquisition method based on chaotic compressive measurement with the compressed sensing principle is proposed. Firstly, the advantages of applying compressed sensing are analyzed for data acquisition in power systems, and the key issues that need to be addressed are identified. Subsequently, a chaotic map is sampled based on the basic requirements of the measurement matrix in compressed sensing, and the chaotic compressive measurement matrix is constructed and optimized based on the sampling results. Next, the sparse data difference of the power system is used as the compression target for the optimized chaotic measurement matrix, and an acquisition process is designed to recover the complete power data from a small amount of compressed data. Finally, the proposed method is validated in a case study, and the results demonstrate that the method is correct and effective.</description> <pubDate>2024-11-25</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7499: A New Compressed Data Acquisition Method for Power System Based on Chaotic Compressive Measurement</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7499">doi: 10.3390/s24237499</a></p> <p>Authors: Shan Yang Zhirong Gao Jingbo Guo </p> <p>The digitalization level of the new power system driven by &amp;amp;ldquo;dual carbon&amp;amp;rdquo; is increasing, leading to a growth in the amount of data that need to be acquired. This has intensified the contradiction between data volume and acquisition capacity. Therefore, it is urgent to study compressed data acquisition methods for power systems based on data compression. In this regard, a novel compressed data acquisition method based on chaotic compressive measurement with the compressed sensing principle is proposed. Firstly, the advantages of applying compressed sensing are analyzed for data acquisition in power systems, and the key issues that need to be addressed are identified. Subsequently, a chaotic map is sampled based on the basic requirements of the measurement matrix in compressed sensing, and the chaotic compressive measurement matrix is constructed and optimized based on the sampling results. Next, the sparse data difference of the power system is used as the compression target for the optimized chaotic measurement matrix, and an acquisition process is designed to recover the complete power data from a small amount of compressed data. Finally, the proposed method is validated in a case study, and the results demonstrate that the method is correct and effective.</p> ]]></content:encoded> <dc:title>A New Compressed Data Acquisition Method for Power System Based on Chaotic Compressive Measurement</dc:title> <dc:creator>Shan Yang</dc:creator> <dc:creator>Zhirong Gao</dc:creator> <dc:creator>Jingbo Guo</dc:creator> <dc:identifier>doi: 10.3390/s24237499</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-25</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-25</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7499</prism:startingPage> <prism:doi>10.3390/s24237499</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7499</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7498"> <title>Sensors, Vol. 24, Pages 7498: Assisting Standing Balance Recovery for Parkinson&amp;rsquo;s Patients with a Lower-Extremity Exoskeleton Robot</title> <link>https://www.mdpi.com/1424-8220/24/23/7498</link> <description>Parkinson&amp;amp;rsquo;s disease (PD) is a neurodegenerative disorder and always results in balance loss. Although studies in lower-extremity exoskeleton robots are ample, applications with a lower-extremity exoskeleton robot for PD patients are still challenging. This paper aims to develop an effective assistive control for PD patients with a lower-extremity exoskeleton robot to maintain standing balance while being subjected to external disturbances. When an external force is applied to participants to force them to lose balance, the hip strategy for balance recovery based on the zero moment point (ZMP) metrics is used to generate a reference trajectory of the hip joint, and then, a model-free linear extended state observer (LESO)-based fuzzy sliding mode control (FSMC) is synthesized to regulate the human body to recover balance. Balance recovery trials for healthy individuals and PD patients with and without exoskeleton assistance were conducted to evaluate the performance of the proposed exoskeleton robot and balance recovery strategy. Our experiments demonstrated the potential effectiveness of the proposed exoskeleton robot and controller for standing balance recovery control in PD patients.</description> <pubDate>2024-11-24</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7498: Assisting Standing Balance Recovery for Parkinson&amp;rsquo;s Patients with a Lower-Extremity Exoskeleton Robot</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7498">doi: 10.3390/s24237498</a></p> <p>Authors: Chi-Shiuan Lee Lo-Ping Yu Si-Huei Lee Yi-Chia Chen Chun-Ta Chen </p> <p>Parkinson&amp;amp;rsquo;s disease (PD) is a neurodegenerative disorder and always results in balance loss. Although studies in lower-extremity exoskeleton robots are ample, applications with a lower-extremity exoskeleton robot for PD patients are still challenging. This paper aims to develop an effective assistive control for PD patients with a lower-extremity exoskeleton robot to maintain standing balance while being subjected to external disturbances. When an external force is applied to participants to force them to lose balance, the hip strategy for balance recovery based on the zero moment point (ZMP) metrics is used to generate a reference trajectory of the hip joint, and then, a model-free linear extended state observer (LESO)-based fuzzy sliding mode control (FSMC) is synthesized to regulate the human body to recover balance. Balance recovery trials for healthy individuals and PD patients with and without exoskeleton assistance were conducted to evaluate the performance of the proposed exoskeleton robot and balance recovery strategy. Our experiments demonstrated the potential effectiveness of the proposed exoskeleton robot and controller for standing balance recovery control in PD patients.</p> ]]></content:encoded> <dc:title>Assisting Standing Balance Recovery for Parkinson&amp;amp;rsquo;s Patients with a Lower-Extremity Exoskeleton Robot</dc:title> <dc:creator>Chi-Shiuan Lee</dc:creator> <dc:creator>Lo-Ping Yu</dc:creator> <dc:creator>Si-Huei Lee</dc:creator> <dc:creator>Yi-Chia Chen</dc:creator> <dc:creator>Chun-Ta Chen</dc:creator> <dc:identifier>doi: 10.3390/s24237498</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-24</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-24</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7498</prism:startingPage> <prism:doi>10.3390/s24237498</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7498</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7497"> <title>Sensors, Vol. 24, Pages 7497: The Development of an Electron Pulse Dilation Photomultiplier Tube Diagnostic Instrument</title> <link>https://www.mdpi.com/1424-8220/24/23/7497</link> <description>A new pulse-dilated photomultiplier tube (PD-PMT) with sub-20 ps temporal resolution and associated drivers have been developed for use detection and signal amplification in the inertial confinement fusion (ICF) community. The PD-PMT is coupled to a transmission line output in order to provide a continuous time history of the input signal. Electron pulse dilation provides high-speed detection capabilities by converting incoming signals into a free-electron cloud and manipulating the electron signal with electric and magnetic fields. This velocity dispersion is translated into temporal separation after the electrons transit into a drift space. The free electrons are then detected by using conventional time-resolved methods and the effective temporal resolution is improved about 12 times. In order to accurately obtain the actual device input signal, we experimentally investigated the relationship between microchannel plate (MCP) gain and electron energy during the first collision. We report the measurements with the PD-PMT, and the error source of the amplitude of the compressed signal is analyzed, which provides a reference for subsequent accurate construction.</description> <pubDate>2024-11-24</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7497: The Development of an Electron Pulse Dilation Photomultiplier Tube Diagnostic Instrument</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7497">doi: 10.3390/s24237497</a></p> <p>Authors: Wenyong Fu Chenman Hu Ping Chen Rongyan Zhou Ling Li </p> <p>A new pulse-dilated photomultiplier tube (PD-PMT) with sub-20 ps temporal resolution and associated drivers have been developed for use detection and signal amplification in the inertial confinement fusion (ICF) community. The PD-PMT is coupled to a transmission line output in order to provide a continuous time history of the input signal. Electron pulse dilation provides high-speed detection capabilities by converting incoming signals into a free-electron cloud and manipulating the electron signal with electric and magnetic fields. This velocity dispersion is translated into temporal separation after the electrons transit into a drift space. The free electrons are then detected by using conventional time-resolved methods and the effective temporal resolution is improved about 12 times. In order to accurately obtain the actual device input signal, we experimentally investigated the relationship between microchannel plate (MCP) gain and electron energy during the first collision. We report the measurements with the PD-PMT, and the error source of the amplitude of the compressed signal is analyzed, which provides a reference for subsequent accurate construction.</p> ]]></content:encoded> <dc:title>The Development of an Electron Pulse Dilation Photomultiplier Tube Diagnostic Instrument</dc:title> <dc:creator>Wenyong Fu</dc:creator> <dc:creator>Chenman Hu</dc:creator> <dc:creator>Ping Chen</dc:creator> <dc:creator>Rongyan Zhou</dc:creator> <dc:creator>Ling Li</dc:creator> <dc:identifier>doi: 10.3390/s24237497</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-24</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-24</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7497</prism:startingPage> <prism:doi>10.3390/s24237497</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7497</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7496"> <title>Sensors, Vol. 24, Pages 7496: Phased Array Antenna Calibration Based on Autocorrelation Algorithm</title> <link>https://www.mdpi.com/1424-8220/24/23/7496</link> <description>The problem of calibrating phased array antennas in a noisy environment using an autocorrelation algorithm is investigated and a mathematical model of the autocorrelation calibration method is presented. The proposed calibration system is based on far-field scanning of the phased array antenna in an environment with internal noise and external interference. The proposed method is applied to a phased array antenna and compared with traditional rotating-element electric-field vector methods, which involve identifying the maximum and minimum vector&amp;amp;ndash;sum points (REVmax and REVmin, respectively). The proposed calibration system is verified for a phased array antenna at 3 GHz. Experimental verification of the mathematical model of the proposed method demonstrates that the autocorrelation method is more accurate than the rotating-element electric-field vector methods in determining the amplitude and phase shifts. The measured peak gain of the combined beam in the E-plane increased from 7.83 to 8.37 dB and 3.57 to 4.36 dB compared to the REVmax and REVmin methods, respectively, and the phase error improved from 47&amp;amp;deg; to 55.48&amp;amp;deg; and 19.43&amp;amp;deg; to 29.16&amp;amp;deg;, respectively. The proposed method can be considered an effective solution for large-scale phase calibration at both in-field and in-factory levels, even in the presence of external interference.</description> <pubDate>2024-11-24</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7496: Phased Array Antenna Calibration Based on Autocorrelation Algorithm</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7496">doi: 10.3390/s24237496</a></p> <p>Authors: Xuan Luong Nguyen Nguyen Trong Nhan Thanh Thuy Dang Thi Tran Van Thanh Phung Bao Nguyen Nguyen Duc Trien </p> <p>The problem of calibrating phased array antennas in a noisy environment using an autocorrelation algorithm is investigated and a mathematical model of the autocorrelation calibration method is presented. The proposed calibration system is based on far-field scanning of the phased array antenna in an environment with internal noise and external interference. The proposed method is applied to a phased array antenna and compared with traditional rotating-element electric-field vector methods, which involve identifying the maximum and minimum vector&amp;amp;ndash;sum points (REVmax and REVmin, respectively). The proposed calibration system is verified for a phased array antenna at 3 GHz. Experimental verification of the mathematical model of the proposed method demonstrates that the autocorrelation method is more accurate than the rotating-element electric-field vector methods in determining the amplitude and phase shifts. The measured peak gain of the combined beam in the E-plane increased from 7.83 to 8.37 dB and 3.57 to 4.36 dB compared to the REVmax and REVmin methods, respectively, and the phase error improved from 47&amp;amp;deg; to 55.48&amp;amp;deg; and 19.43&amp;amp;deg; to 29.16&amp;amp;deg;, respectively. The proposed method can be considered an effective solution for large-scale phase calibration at both in-field and in-factory levels, even in the presence of external interference.</p> ]]></content:encoded> <dc:title>Phased Array Antenna Calibration Based on Autocorrelation Algorithm</dc:title> <dc:creator>Xuan Luong Nguyen</dc:creator> <dc:creator>Nguyen Trong Nhan</dc:creator> <dc:creator>Thanh Thuy Dang Thi</dc:creator> <dc:creator>Tran Van Thanh</dc:creator> <dc:creator>Phung Bao Nguyen</dc:creator> <dc:creator>Nguyen Duc Trien</dc:creator> <dc:identifier>doi: 10.3390/s24237496</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-24</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-24</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7496</prism:startingPage> <prism:doi>10.3390/s24237496</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7496</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7492"> <title>Sensors, Vol. 24, Pages 7492: A Temporal Network Based on Characterizing and Extracting Time Series in Copper Smelting for Predicting Matte Grade</title> <link>https://www.mdpi.com/1424-8220/24/23/7492</link> <description>Addressing the issues of low prediction accuracy and poor interpretability in traditional matte grade prediction models, which rely on pre-smelting input and assay data for regression, we incorporate process sensors&amp;amp;rsquo; data and propose a temporal network based on Time to Vector (Time2Vec) and temporal convolutional network combined with temporal multi-head attention (TCN-TMHA) to tackle the weak temporal characteristics and uncertain periodic information in the copper smelting process. Firstly, we employed the maximum information coefficient (MIC) criterion to select temporal process sensors&amp;amp;rsquo; data strongly correlated with matte grade. Secondly, we used a Time2Vec module to extract periodic information from the copper smelting process variables, incorporates time series processing directly into the prediction model. Finally, we implemented the TCN-TMHA module and used specific weighting mechanisms to assign weights to the input features and prioritize relevant key time step features. Experimental results indicate that the proposed model yields more accurate predictions of copper content, and the coefficient of determination (R2) is improved by 2.13% to 11.95% and reduced compared to the existing matte grade prediction models.</description> <pubDate>2024-11-24</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7492: A Temporal Network Based on Characterizing and Extracting Time Series in Copper Smelting for Predicting Matte Grade</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7492">doi: 10.3390/s24237492</a></p> <p>Authors: Junjia Zhang Zhuorui Li Enzhi Wang Bin Yu Jiangping Li Jun Ma </p> <p>Addressing the issues of low prediction accuracy and poor interpretability in traditional matte grade prediction models, which rely on pre-smelting input and assay data for regression, we incorporate process sensors&amp;amp;rsquo; data and propose a temporal network based on Time to Vector (Time2Vec) and temporal convolutional network combined with temporal multi-head attention (TCN-TMHA) to tackle the weak temporal characteristics and uncertain periodic information in the copper smelting process. Firstly, we employed the maximum information coefficient (MIC) criterion to select temporal process sensors&amp;amp;rsquo; data strongly correlated with matte grade. Secondly, we used a Time2Vec module to extract periodic information from the copper smelting process variables, incorporates time series processing directly into the prediction model. Finally, we implemented the TCN-TMHA module and used specific weighting mechanisms to assign weights to the input features and prioritize relevant key time step features. Experimental results indicate that the proposed model yields more accurate predictions of copper content, and the coefficient of determination (R2) is improved by 2.13% to 11.95% and reduced compared to the existing matte grade prediction models.</p> ]]></content:encoded> <dc:title>A Temporal Network Based on Characterizing and Extracting Time Series in Copper Smelting for Predicting Matte Grade</dc:title> <dc:creator>Junjia Zhang</dc:creator> <dc:creator>Zhuorui Li</dc:creator> <dc:creator>Enzhi Wang</dc:creator> <dc:creator>Bin Yu</dc:creator> <dc:creator>Jiangping Li</dc:creator> <dc:creator>Jun Ma</dc:creator> <dc:identifier>doi: 10.3390/s24237492</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-24</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-24</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7492</prism:startingPage> <prism:doi>10.3390/s24237492</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7492</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7494"> <title>Sensors, Vol. 24, Pages 7494: Innovative Seatbelt-Integrated Metasurface Radar for Enhanced In-Car Healthcare Monitoring</title> <link>https://www.mdpi.com/1424-8220/24/23/7494</link> <description>This study introduces a novel seatbelt-integrated, non-invasive, beam-focusing metamaterial sensing system characterized by its thinness and flexibility. The system comprises a flexible transmitarray lens and an FMCW radar sensor, enabling the accurate detection and analysis of seatbelt usage and positioning through human tissue. The metasurface design remains effective even when subjected to different bending angles. Our system closely tracks heart rate and respiration, validated against standard reference methods, highlighting its potential for enhancing in-car healthcare monitoring. Experimental results demonstrate the system&amp;amp;rsquo;s reliability in monitoring physiological signals within dynamic vehicular environments.</description> <pubDate>2024-11-24</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7494: Innovative Seatbelt-Integrated Metasurface Radar for Enhanced In-Car Healthcare Monitoring</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7494">doi: 10.3390/s24237494</a></p> <p>Authors: Rifa Atul Izza Asyari Roy B. V. B. Simorangkir Daniel Teichmann </p> <p>This study introduces a novel seatbelt-integrated, non-invasive, beam-focusing metamaterial sensing system characterized by its thinness and flexibility. The system comprises a flexible transmitarray lens and an FMCW radar sensor, enabling the accurate detection and analysis of seatbelt usage and positioning through human tissue. The metasurface design remains effective even when subjected to different bending angles. Our system closely tracks heart rate and respiration, validated against standard reference methods, highlighting its potential for enhancing in-car healthcare monitoring. Experimental results demonstrate the system&amp;amp;rsquo;s reliability in monitoring physiological signals within dynamic vehicular environments.</p> ]]></content:encoded> <dc:title>Innovative Seatbelt-Integrated Metasurface Radar for Enhanced In-Car Healthcare Monitoring</dc:title> <dc:creator>Rifa Atul Izza Asyari</dc:creator> <dc:creator>Roy B. V. B. Simorangkir</dc:creator> <dc:creator>Daniel Teichmann</dc:creator> <dc:identifier>doi: 10.3390/s24237494</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-24</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-24</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7494</prism:startingPage> <prism:doi>10.3390/s24237494</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7494</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <item rdf:about="https://www.mdpi.com/1424-8220/24/23/7495"> <title>Sensors, Vol. 24, Pages 7495: Development of Textile-Based Strain Sensors for Compression Measurements in Sportswear (Sports Bra)</title> <link>https://www.mdpi.com/1424-8220/24/23/7495</link> <description>Women sports wearer&amp;amp;rsquo;s comfort and health are greatly impacted by the breast movements and resultant sports bra compression to prevent excessive movement. However, as sports bras are only made in universal sizes, they do not offer the right kind of support that is required for a certain activity. To prevent this issue, textile-based strain sensors may be utilized to track compression throughout various activities to create activity-specific designed sports bras. Textile-based strain sensors are prepared in this study using various conductive yarns, including steel, Ag-coated polyamide, and polypropylene/steel-blended threads. Various embroidery designs, including straight, zigzag, and square-wave embroidery patterns, etc., were created on knitted fabric and characterized for strain sensing efficiencies. The experiments concluded that strain sensors prepared from polypropylene/steel thread using a 2-thread square-wave design were best performed in terms of linear conductivity, sensitivity of mechanical impact, and wide working range. This best-performed sample was also tested by integrating it into the sportswear for proposed compression measurements in different body movements.</description> <pubDate>2024-11-24</pubDate> <content:encoded><![CDATA[ <p><b>Sensors, Vol. 24, Pages 7495: Development of Textile-Based Strain Sensors for Compression Measurements in Sportswear (Sports Bra)</b></p> <p>Sensors <a href="https://www.mdpi.com/1424-8220/24/23/7495">doi: 10.3390/s24237495</a></p> <p>Authors: Aqsa Imran Shahood uz Zaman Mozzan Razzaq Ayesha Ahmad Xuyuan Tao </p> <p>Women sports wearer&amp;amp;rsquo;s comfort and health are greatly impacted by the breast movements and resultant sports bra compression to prevent excessive movement. However, as sports bras are only made in universal sizes, they do not offer the right kind of support that is required for a certain activity. To prevent this issue, textile-based strain sensors may be utilized to track compression throughout various activities to create activity-specific designed sports bras. Textile-based strain sensors are prepared in this study using various conductive yarns, including steel, Ag-coated polyamide, and polypropylene/steel-blended threads. Various embroidery designs, including straight, zigzag, and square-wave embroidery patterns, etc., were created on knitted fabric and characterized for strain sensing efficiencies. The experiments concluded that strain sensors prepared from polypropylene/steel thread using a 2-thread square-wave design were best performed in terms of linear conductivity, sensitivity of mechanical impact, and wide working range. This best-performed sample was also tested by integrating it into the sportswear for proposed compression measurements in different body movements.</p> ]]></content:encoded> <dc:title>Development of Textile-Based Strain Sensors for Compression Measurements in Sportswear (Sports Bra)</dc:title> <dc:creator>Aqsa Imran</dc:creator> <dc:creator>Shahood uz Zaman</dc:creator> <dc:creator>Mozzan Razzaq</dc:creator> <dc:creator>Ayesha Ahmad</dc:creator> <dc:creator>Xuyuan Tao</dc:creator> <dc:identifier>doi: 10.3390/s24237495</dc:identifier> <dc:source>Sensors</dc:source> <dc:date>2024-11-24</dc:date> <prism:publicationName>Sensors</prism:publicationName> <prism:publicationDate>2024-11-24</prism:publicationDate> <prism:volume>24</prism:volume> <prism:number>23</prism:number> <prism:section>Article</prism:section> <prism:startingPage>7495</prism:startingPage> <prism:doi>10.3390/s24237495</prism:doi> <prism:url>https://www.mdpi.com/1424-8220/24/23/7495</prism:url> <cc:license rdf:resource="CC BY 4.0"/> </item> <cc:License rdf:about="https://creativecommons.org/licenses/by/4.0/"> <cc:permits rdf:resource="https://creativecommons.org/ns#Reproduction" /> <cc:permits rdf:resource="https://creativecommons.org/ns#Distribution" /> <cc:permits rdf:resource="https://creativecommons.org/ns#DerivativeWorks" /> </cc:License> </rdf:RDF>