Electronics | An Open Access Journal from MDPI

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access journal on the science of electronics and its applications published semimonthly online by MDPI. <a href="http://ptze.pl/">The Polish Society of Applied Electromagnetics (PTZE)</a> is affiliated with <em>Electronics</em> and their members receive a discount on article processing charges.<br /> <ul> <li><span class="label openaccess"><a title="Open Access" href="https://www.mdpi.com/openaccess">Open Access</a></span>— free for readers, with <a href="https://www.mdpi.com/journal/electronics/apc">article processing charges (APC)</a> paid by authors or their institutions.</li> <li><strong>High Visibility: </strong>indexed within <a href="https://www.scopus.com/sourceid/21100829272">Scopus</a>, <a href="https://mjl.clarivate.com/search-results?issn=2079-9292&hide_exact_match_fl=true&utm_source=mjl&utm_medium=share-by-link&utm_campaign=search-results-share-this-journal">SCIE (Web of Science)</a>, <a 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who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.</li> <li><strong>Companion journals for <em>Electronics</em> include:</strong> <em><a href="https://www.mdpi.com/journal/Magnetism">Magnetism</a></em>, <em><a href="https://www.mdpi.com/journal/microwave">Microwave</a></em><em>,</em> <em><a href="https://www.mdpi.com/journal/Network">Network</a></em>, <em><a href="https://www.mdpi.com/journal/Signals">Signals</a>,</em> <em><a href="https://www.mdpi.com/journal/software">Software</a> </em>and <a href="https://www.mdpi.com/journal/microelectronics"><em>Microelectronics</em></a>.</li> </ul> </div> <div style="margin-bottom: 15px;"> <strong>Impact Factor:</strong> 2.6 (2023); 5-Year Impact Factor: 2.6 (2023) </div> <div> <a href="/journal/electronics/imprint" class="UI_JournalImprintsInfoButton"> <i class="material-icons spaced-link">subject</i> Imprint Information </a>    <a href="/journal/electronics/electronics_flyer.pdf" class="UD_JournalFlyer"> <i class="material-icons spaced-link">get_app</i> Journal Flyer </a>     <a class="oa-link" href="https://www.mdpi.com/about/openaccess"> <i class="material icons spaced-link"></i> Open Access </a>     <strong> ISSN: 2079-9292 </strong> </div> <div style="clear: both;"></div> </div> </div> </div> <div class="content__container content__container--overflow-initial"> <div class="custom-accordion-for-small-screen-link active"> <h2 class="no-padding-left">Latest Articles</h2> </div> <div class="custom-accordion-for-small-screen-content"> <div class="expanding-div collapsed"> <div class="generic-item article-item no-border"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 22 pages, 13121 KiB   </span> <a href="/2079-9292/13/23/4629/pdf?version=1732357487" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Research on Irrigation Grade Discrimination Method Based on Semantic Segmentation" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4629">Research on Irrigation Grade Discrimination Method Based on Semantic Segmentation</a> <div class="authors"> by <span class="inlineblock "><strong>Xibao Wu</strong>, </span><span class="inlineblock "><strong>Wentao Chen</strong>, </span><span class="inlineblock "><strong>Kexin Yang</strong>, </span><span class="inlineblock "><strong>Xin Zhao</strong>, </span><span class="inlineblock "><strong>Yiqun Wang</strong> and </span><span class="inlineblock "><strong>Wenbai Chen</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4629; https://doi.org/10.3390/electronics13234629 (registering DOI) - 23 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> As one of China’s major grain crops, wheat has a high demand for water resources, making it susceptible to drought stress. Traditional irrigation evaluation methods are often based on experience and rule-based calculations, which struggle to cope with complex environmental factors and dynamic <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4629/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> As one of China’s major grain crops, wheat has a high demand for water resources, making it susceptible to drought stress. Traditional irrigation evaluation methods are often based on experience and rule-based calculations, which struggle to cope with complex environmental factors and dynamic changes in crop needs. With technological advancements, deep learning-based research methods, characterized by their strong data-driven analytical capabilities, are expected to improve the accuracy of evaluation results. This paper focuses on the irrigation demand assessment of winter wheat farmland, aiming to explore a new regional-scale irrigation demand assessment method based on deep learning. By establishing samples of different irrigation evaluation levels, this study seeks to better meet the requirements of irrigation demand assessment. For the problem of regional-scale irrigation-level discrimination, the Convolutional Network Attention(CONAT) module was proposed to optimize the backbone network structure of the Mask2Former model. To tackle issues related to data imbalance and underfitting across certain categories, a loss function tailored for imbalanced sample distributions was implemented, accompanied by enhancements to the training scheme. By contrasting this refined model with alternative methods for discriminating irrigation levels, the viability of this approach was showcased. <a href="/2079-9292/13/23/4629">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/MQ1E6L6DOB ">Machine Learning and Computational Intelligence in Remote Sensing</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4629/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1527888"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1527888"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1527888" data-cycle-prev="#prev1527888" data-cycle-progressive="#images1527888" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1527888-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g001-550.jpg?1732357596" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1527888" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1527888-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g002-550.jpg?1732357597'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1527888-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g003-550.jpg?1732357599'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1527888-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g004-550.jpg?1732357600'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1527888-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g005-550.jpg?1732357601'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1527888-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g006-550.jpg?1732357602'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1527888-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g007-550.jpg?1732357604'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1527888-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g008-550.jpg?1732357607'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1527888-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g009-550.jpg?1732357609'><p>Figure 9</p></div></script></div></div><div id="article-1527888-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g001-550.jpg?1732357596" title=" <strong>Figure 1</strong><br/> <p>Geographical location of the North China Plain and distribution map of different crops.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g002-550.jpg?1732357597" title=" <strong>Figure 2</strong><br/> <p>Irrigation assurance capability assessment technology roadmap.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g003-550.jpg?1732357599" title=" <strong>Figure 3</strong><br/> <p>Visualization of irrigation assurance capability indicators and data distribution information map. 2.43E-2 is expressed as <math display="inline"><semantics> <mrow> <mn>2.43</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math>, 9.52E-2 is expressed as <math display="inline"><semantics> <mrow> <mn>9.52</mn> <mo>×</mo> <msup> <mn>10</mn> <mrow> <mo>−</mo> <mn>2</mn> </mrow> </msup> </mrow> </semantics></math>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g004-550.jpg?1732357600" title=" <strong>Figure 4</strong><br/> <p>The scatter plot of <math display="inline"><semantics> <mrow> <mi>E</mi> <msub> <mi>T</mi> <mn>0</mn> </msub> </mrow> </semantics></math> calculated from meteorological stations and PET.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g005-550.jpg?1732357601" title=" <strong>Figure 5</strong><br/> <p>Mask2Former model structure.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g006-550.jpg?1732357602" title=" <strong>Figure 6</strong><br/> <p>(<b>a</b>) represents the Transformer module, (<b>b</b>) represents the ConvNeXt module, and (<b>c</b>) represents the CONAT module.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g007-550.jpg?1732357604" title=" <strong>Figure 7</strong><br/> <p>(<b>a</b>) Model accuracy for categorizing the level of farmland irrigation guarantee capacity; (<b>b</b>) Intersection over Union (IoU) results.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g008-550.jpg?1732357607" title=" <strong>Figure 8</strong><br/> <p>(<b>a</b>) Tagged image; (<b>b</b>) verification image of the Mask2former model with CONAT as the backbone network.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04629/article_deploy/html/images/electronics-13-04629-g009-550.jpg?1732357609" title=" <strong>Figure 9</strong><br/> <p>(<b>a</b>) Accuracy comparison of Mask2former models with different backbone networks; (<b>b</b>) Intersection over Union (IoU) comparison.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4629'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="extending-content content-ready"> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 39 pages, 16475 KiB   </span> <a href="/2079-9292/13/23/4627/pdf?version=1732359518" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Ring: A Lightweight and Versatile Cross-Platform Dynamic Programming Language Developed Using Visual Programming" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4627">Ring: A Lightweight and Versatile Cross-Platform Dynamic Programming Language Developed Using Visual Programming</a> <div class="authors"> by <span class="inlineblock "><strong>Mahmoud Samir Fayed</strong> and </span><span class="inlineblock "><strong>Yousef A. Alohali</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4627; https://doi.org/10.3390/electronics13234627 (registering DOI) - 23 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> New programming languages are often designed to keep up with technological advancements and project requirements while also learning from previous attempts and introducing more powerful expression mechanisms. However, most existing dynamic programming languages rely on English keywords and lack features that facilitate easy <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4627/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> New programming languages are often designed to keep up with technological advancements and project requirements while also learning from previous attempts and introducing more powerful expression mechanisms. However, most existing dynamic programming languages rely on English keywords and lack features that facilitate easy translation of language syntax. Additionally, maintaining multiple implementations of the same language for different platforms, such as desktops and microcontrollers, can lead to inconsistencies and fragmented features. Furthermore, they usually do not use visual programming to fully implement the compiler and virtual machine. In this research paper, we introduce Ring—a dynamically-typed language with a lightweight implementation. However, it boasts several advantages, including a rich and versatile standard library and direct support for classes and object-oriented programming. The Ring language offers customization features. For instance, it allows easy modification of the language syntax multiple times, enabling programming by writing code using Arabic, English, or other keywords. Additionally, the language permits the creation of domain-specific languages through new features that extend object-oriented programming, allowing for specialized languages resembling CSS or Supernova. In the era of the Internet of Things, instead of creating another language implementation to support microcontrollers, the same Ring implementation allows us to create projects and applications for desktops, the web, WebAssembly, Android, or Raspberry Pi Pico. The Ring Compiler and Virtual Machine are designed using the PWCT Visual Programming language based on ANSI C. The visual implementation is composed of 18,945 components that generate 24,743 lines of code, which increases the abstraction level by approximately 23.5% and hides unnecessary details. <a href="/2079-9292/13/23/4627">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/electronics/sections/computer_science_engineering">Computer Science & Engineering</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4627/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1527928"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1527928"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1527928" 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<div class='openpopupgallery' data-imgindex='6' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g007-550.jpg?1732359592'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g008-550.jpg?1732359594'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g009-550.jpg?1732359595'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g010-550.jpg?1732359596'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g011-550.jpg?1732359597'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g012-550.jpg?1732359598'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g013-550.jpg?1732359600'><p>Figure 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src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g017-550.jpg?1732359604'><p>Figure 17</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g018-550.jpg?1732359605'><p>Figure 18</p></div> --- <div class='openpopupgallery' data-imgindex='18' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g019-550.jpg?1732359607'><p>Figure 19</p></div> --- <div class='openpopupgallery' data-imgindex='19' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g020-550.jpg?1732359609'><p>Figure 20</p></div> --- <div class='openpopupgallery' data-imgindex='20' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g021-550.jpg?1732359611'><p>Figure 21</p></div> --- <div class='openpopupgallery' data-imgindex='21' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g022-550.jpg?1732359613'><p>Figure 22</p></div> --- <div class='openpopupgallery' data-imgindex='22' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g023-550.jpg?1732359615'><p>Figure 23</p></div> --- <div class='openpopupgallery' data-imgindex='23' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g024-550.jpg?1732359617'><p>Figure 24</p></div> --- <div class='openpopupgallery' data-imgindex='24' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g025-550.jpg?1732359618'><p>Figure 25</p></div> --- <div class='openpopupgallery' data-imgindex='25' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g026-550.jpg?1732359620'><p>Figure 26</p></div> --- <div class='openpopupgallery' data-imgindex='26' data-target='article-1527928-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g027-550.jpg?1732359622'><p>Figure 27</p></div></script></div></div><div id="article-1527928-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g001-550.jpg?1732359585" title=" <strong>Figure 1</strong><br/> <p>Some of the dynamic programming languages that were developed, starting in 1960.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g002-550.jpg?1732359586" title=" <strong>Figure 2</strong><br/> <p>Using commands in the Supernova language to describe the application user interface.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g003-550.jpg?1732359588" title=" <strong>Figure 3</strong><br/> <p>The key features of the proposed dynamic language and environment.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g004-550.jpg?1732359589" title=" <strong>Figure 4</strong><br/> <p>The proposed system architecture.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g005-550.jpg?1732359590" title=" <strong>Figure 5</strong><br/> <p>Arabic syntax within a WebAssembly application developed using Ring.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g006-550.jpg?1732359591" title=" <strong>Figure 6</strong><br/> <p>Ring code to implement a simple domain-specific language.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g007-550.jpg?1732359592" title=" <strong>Figure 7</strong><br/> <p>Extending our DSL using inheritance and the GUI library.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g008-550.jpg?1732359594" title=" <strong>Figure 8</strong><br/> <p>Using Declarative Style in Ring for Raspberry Pi Pico programming.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g009-550.jpg?1732359595" title=" <strong>Figure 9</strong><br/> <p>Ring IDE (Code Editor, Form Designer, etc.) is developed using Ring itself.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g010-550.jpg?1732359596" title=" <strong>Figure 10</strong><br/> <p>Using PWCT to define the List structure which uses a singleton cache.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g011-550.jpg?1732359597" title=" <strong>Figure 11</strong><br/> <p>Implementing the Ring language grammar using PWCT.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g012-550.jpg?1732359598" title=" <strong>Figure 12</strong><br/> <p>Using the VPL Compiler to get statistics about the visual representation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g013-550.jpg?1732359600" title=" <strong>Figure 13</strong><br/> <p>Ring Virtual Machine implementation using PWCT.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g014-550.jpg?1732359600" title=" <strong>Figure 14</strong><br/> <p>Early users and the language used prior to Ring.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g015-550.jpg?1732359601" title=" <strong>Figure 15</strong><br/> <p>Feedback from students about Ring language after a one-hour lecture.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g016-550.jpg?1732359603" title=" <strong>Figure 16</strong><br/> <p>Ring downloads statistics from Sourceforge (grouped by the Operating System).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g017-550.jpg?1732359604" title=" <strong>Figure 17</strong><br/> <p>Ring downloads statistics from Sourceforge (grouped by the Country).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g018-550.jpg?1732359605" title=" <strong>Figure 18</strong><br/> <p>A GUI application developed using the Ring language.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g019-550.jpg?1732359607" title=" <strong>Figure 19</strong><br/> <p>The GoldMagic800 game—A puzzle game developed using RingAllegro.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g020-550.jpg?1732359609" title=" <strong>Figure 20</strong><br/> <p>Visual implementation size for each module.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g021-550.jpg?1732359611" title=" <strong>Figure 21</strong><br/> <p>The loading time (LT) and code generation time (CGT) for each visual source file.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g022-550.jpg?1732359613" title=" <strong>Figure 22</strong><br/> <p>Code generation time (CGT) for large visual source files (measured in seconds).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g023-550.jpg?1732359615" title=" <strong>Figure 23</strong><br/> <p>Generated code size for Ring Compiler/VM from 2016 to 2024.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g024-550.jpg?1732359617" title=" <strong>Figure 24</strong><br/> <p>Code size for Lua Compiler/VM from 1993 to 2024.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g025-550.jpg?1732359618" title=" <strong>Figure 25</strong><br/> <p>Generated code size for Ring Compiler/VM from Ring 1.0.0 to Ring 1.21.2.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g026-550.jpg?1732359620" title=" <strong>Figure 26</strong><br/> <p>Function call (100 M) benchmark for Ring, VFP, and Python.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04627/article_deploy/html/images/electronics-13-04627-g027-550.jpg?1732359622" title=" <strong>Figure 27</strong><br/> <p>Different frames from the waving cubes animation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4627'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 6455 KiB   </span> <a href="/2079-9292/13/23/4626/pdf?version=1732356606" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Research on Deep Learning Model Enhancements for PCB Surface Defect Detection" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4626">Research on Deep Learning Model Enhancements for PCB Surface Defect Detection</a> <div class="authors"> by <span class="inlineblock "><strong>Hao Yan</strong>, </span><span class="inlineblock "><strong>Hong Zhang</strong>, </span><span class="inlineblock "><strong>Fengyu Gao</strong>, </span><span class="inlineblock "><strong>Huaqin Wu</strong> and </span><span class="inlineblock "><strong>Shun Tang</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4626; https://doi.org/10.3390/electronics13234626 (registering DOI) - 23 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> With the miniaturization and increasing complexity of electronic devices, the accuracy and efficiency of printed circuit board (PCB) defect detection are crucial to ensuring product quality. To address the issues of small defect sizes and high missed detection rates in PCB surface inspection, <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4626/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> With the miniaturization and increasing complexity of electronic devices, the accuracy and efficiency of printed circuit board (PCB) defect detection are crucial to ensuring product quality. To address the issues of small defect sizes and high missed detection rates in PCB surface inspection, this paper proposes an enhanced YOLOv8s model which not only improves detection performance but also achieves a lightweight design. Firstly, the Nexus Attention module is introduced, which organically integrates multiple attention mechanisms to further enhance feature extraction and fusion capabilities, improving the model’s learning and generalization performance. Secondly, an improved CGFPN network is designed to optimize multi-scale feature fusion, significantly boosting the detection of small objects. Additionally, the WaveletUnPool module is incorporated, leveraging wavelet transform technology to refine the upsampling process, accurately restoring detailed information and improving small-object detection in complex backgrounds. Lastly, the C2f-GDConv module replaces the traditional C2f module, reducing the number of model parameters and computational complexity while maintaining feature extraction efficiency. Comparative experiments on a public PCB dataset demonstrate that the enhanced model achieved a mean average precision (mAP) of 97.3% in PCB defect detection tasks, representing a 3.0% improvement over the original model, while reducing Giga Floating Point Operations (GFLOPs) by 26.8%. These enhancements make the model more practical and adaptable for industrial applications, providing a solid foundation for future research. <a href="/2079-9292/13/23/4626">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/_Object_Detection_Classification_ ">Deep Learning-Based Object Detection/Classification</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 21 pages, 753 KiB   </span> <a href="/2079-9292/13/23/4625/pdf?version=1732356021" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Deep Reinforcement Learning Recommendation System Algorithm Based on Multi-Level Attention Mechanisms" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4625">Deep Reinforcement Learning Recommendation System Algorithm Based on Multi-Level Attention Mechanisms</a> <div class="authors"> by <span class="inlineblock "><strong>Gaopeng Wang</strong>, </span><span class="inlineblock "><strong>Jingyi Ding</strong> and </span><span class="inlineblock "><strong>Fanlin Hu</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4625; https://doi.org/10.3390/electronics13234625 (registering DOI) - 23 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Traditional recommendation systems, which rely on static user profiles and historical interaction data, frequently face difficulties in adapting to the rapid changes in user preferences that are typical of dynamic environments. In contrast, recommendation algorithms based on deep reinforcement learning are capable of <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4625/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Traditional recommendation systems, which rely on static user profiles and historical interaction data, frequently face difficulties in adapting to the rapid changes in user preferences that are typical of dynamic environments. In contrast, recommendation algorithms based on deep reinforcement learning are capable of dynamically adjusting their strategies to accommodate real-time fluctuations in user preferences. However, current deep reinforcement learning recommendation algorithms encounter several challenges, including the oversight of item features associated with high long-term rewards that reflect users’ enduring interests, as well as a lack of significant relevance between user attributes and item characteristics. This leads to an inadequate extraction of personalized information. To address these issues, this study presents a novel recommendation system known as the Multi-Level Hierarchical Attention Mechanism Deep Reinforcement Recommendation (MHDRR), which is fundamentally grounded in a multi-layer attention mechanism. This mechanism consists of a local attention layer, a global attention layer, and a Transformer layer, allowing for a detailed analysis of individual attributes and interactions within short-term preferred items, while also exploring users’ long-term interests. This methodology promotes a comprehensive understanding of users’ immediate and enduring preferences, thereby improving the overall effectiveness of the system over time. Experimental results obtained from three publicly available datasets validate the effectiveness of the proposed model. <a href="/2079-9292/13/23/4625">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/Distributed_Parallel_Computing ">Emerging Distributed/Parallel Computing Systems</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 22 pages, 4744 KiB   </span> <a href="/2079-9292/13/23/4624/pdf?version=1732354355" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="The RedFish API and vSphere Hypervisor API: A Unified Framework for Policy-Based Server Monitoring" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4624">The RedFish API and vSphere Hypervisor API: A Unified Framework for Policy-Based Server Monitoring</a> <div class="authors"> by <span class="inlineblock "><strong>Vedran Dakić</strong>, </span><span class="inlineblock "><strong>Karlo Bertina</strong>, </span><span class="inlineblock "><strong>Jasmin Redžepagić</strong> and </span><span class="inlineblock "><strong>Damir Regvart</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4624; https://doi.org/10.3390/electronics13234624 (registering DOI) - 23 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Integrating remote monitoring systems is crucial in the ever-changing field of data center management to enhance performance and guarantee reliability. This paper outlines a comprehensive strategy for monitoring remote servers by utilizing agents that establish connections to the RedFish API (Application Programming Interface) <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4624/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Integrating remote monitoring systems is crucial in the ever-changing field of data center management to enhance performance and guarantee reliability. This paper outlines a comprehensive strategy for monitoring remote servers by utilizing agents that establish connections to the RedFish API (Application Programming Interface) and vSphere hypervisor API. Our solution uses the RedFish standard to provide secure and standardized management of hardware components in diverse server environments. This improves interoperability and scalability. Simultaneously, the vSphere agent enables monitoring and hardware administration in vSphere-based virtualized environments, offering crucial insights into the state of the underlying hardware. This system, which employs two agents, simplifies the management of servers and seamlessly integrates with current data center infrastructures, enhancing efficiency. The policy-based alerting system built on top of these agents offers many capabilities based on both agents leveraging their alerting systems. This, in turn, can improve the capabilities of next-generation data centers. <a href="/2079-9292/13/23/4624">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/electronics/sections/computer_science_engineering">Computer Science & Engineering</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 19 pages, 9437 KiB   </span> <a href="/2079-9292/13/23/4623/pdf?version=1732352481" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Enhanced 3D Outdoor Positioning Method Based on Adaptive Kalman Filter and Kernel Density Estimation for 6G Wireless System" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label feature" data-dropdown="drop-article-label-feature" aria-expanded="false">Feature Paper</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4623">Enhanced 3D Outdoor Positioning Method Based on Adaptive Kalman Filter and Kernel Density Estimation for 6G Wireless System</a> <div class="authors"> by <span class="inlineblock "><strong>Kyounghun Kim</strong>, </span><span class="inlineblock "><strong>Seongwoo Lee</strong>, </span><span class="inlineblock "><strong>Byungsun Hwang</strong>, </span><span class="inlineblock "><strong>Jinwook Kim</strong>, </span><span class="inlineblock "><strong>Joonho Seon</strong>, </span><span class="inlineblock "><strong>Soohyun Kim</strong>, </span><span class="inlineblock "><strong>Youngghyu Sun</strong> and </span><span class="inlineblock "><strong>Jinyoung Kim</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4623; https://doi.org/10.3390/electronics13234623 (registering DOI) - 23 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The implementation of accurate positioning methods in both line-of-sight (LOS) and non-line-of-sight (NLOS) environments has been emphasized for seamless 6G application services. In LOS environments with unobstructed paths between the transmitter and receiver, accurate tracking essential for seamless 6G services is achievable. However, <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4623/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The implementation of accurate positioning methods in both line-of-sight (LOS) and non-line-of-sight (NLOS) environments has been emphasized for seamless 6G application services. In LOS environments with unobstructed paths between the transmitter and receiver, accurate tracking essential for seamless 6G services is achievable. However, accurate three-dimensional (3D) outdoor positioning has been challenging to achieve in NLOS environments where positioning accuracy may be severely degraded. In this paper, a novel 3D outdoor positioning method considering both LOS and NLOS environments is proposed. Considering the practical positioning systems, the data received from satellites often contain null values and outliers. Thus, a kernel density estimation (KDE)-based outlier removal method is used for effectively detecting the null values and outliers through temporal correlation analysis. A dilution of precision-based adaptive Kalman filter (DOP-AKF) is proposed to mitigate the effects of an NLOS environment. In the proposed method, the DOP-AKF can optimize the performance of the 3D positioning system that dynamically adapts to complex environments. Experimental results show that the proposed method can improve 3D positioning accuracy by up to 18.84% compared to conventional methods. Therefore, the proposed approach can be suggested as a promising solution for 3D outdoor positioning in 6G wireless systems. <a href="/2079-9292/13/23/4623">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/18SVZVG15J ">5G and 6G Wireless Systems: Challenges, Insights, and Opportunities</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 3663 KiB   </span> <a href="/2079-9292/13/23/4622/pdf?version=1732341700" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="A Novel Multi-Task Self-Supervised Transfer Learning Framework for Cross-Machine Rolling Bearing Fault Diagnosis" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4622">A Novel Multi-Task Self-Supervised Transfer Learning Framework for Cross-Machine Rolling Bearing Fault Diagnosis</a> <div class="authors"> by <span class="inlineblock "><strong>Lujia Zhao</strong>, </span><span class="inlineblock "><strong>Yuling He</strong>, </span><span class="inlineblock "><strong>Derui Dai</strong>, </span><span class="inlineblock "><strong>Xiaolong Wang</strong>, </span><span class="inlineblock "><strong>Honghua Bai</strong> and </span><span class="inlineblock "><strong>Weiling Huang</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4622; https://doi.org/10.3390/electronics13234622 (registering DOI) - 23 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In recent years, intelligent methods based on transfer learning have achieved significant research results in the field of rolling bearing fault diagnosis. However, most studies focus on the transfer diagnosis scenario under different working conditions of the same machine. The transfer fault diagnosis <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4622/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In recent years, intelligent methods based on transfer learning have achieved significant research results in the field of rolling bearing fault diagnosis. However, most studies focus on the transfer diagnosis scenario under different working conditions of the same machine. The transfer fault diagnosis methods used for different machines have problems such as low recognition accuracy and unstable performance. Therefore, a novel multi-task self-supervised transfer learning framework (MTSTLF) is proposed for cross-machine rolling bearing fault diagnosis. The proposed method is trained using a multi-task learning paradigm, which includes three self-supervised learning tasks and one fault diagnosis task. First, three different scales of masking methods are designed to generate masked vibration data based on the periodicity and intrinsic information of the rolling bearing vibration signals. Through self-supervised learning, the attention to the intrinsic features of data in different health conditions is enhanced, thereby improving the model’s feature expression capability. Secondly, a multi-perspective feature transfer method is proposed for completing cross-machine fault diagnosis tasks. By integrating two types of metrics, probability distribution and geometric similarity, the method focuses on transferable fault diagnosis knowledge from different perspectives, thereby enhancing the transfer learning ability and accomplishing cross-machine fault diagnosis of rolling bearings. Two experimental cases are carried out to evaluate the effectiveness of the proposed method. Results suggest that the proposed method is effective for cross-machine rolling bearing fault diagnosis. <a href="/2079-9292/13/23/4622">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/74WBV55BOA ">Fault Detection Technology Based on Deep Learning</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4622/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1527582"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1527582"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1527582" data-cycle-prev="#prev1527582" data-cycle-progressive="#images1527582" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1527582-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g001-550.jpg?1732341794" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1527582" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g002-550.jpg?1732341795'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g003-550.jpg?1732341796'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g004-550.jpg?1732341797'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g005-550.jpg?1732341799'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g006-550.jpg?1732341801'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g007-550.jpg?1732341804'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g008-550.jpg?1732341807'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g009-550.jpg?1732341809'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1527582-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g010-550.jpg?1732341812'><p>Figure 10</p></div></script></div></div><div id="article-1527582-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g001-550.jpg?1732341794" title=" <strong>Figure 1</strong><br/> <p>MTSTLF structure.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g002-550.jpg?1732341795" title=" <strong>Figure 2</strong><br/> <p>The procedure of three masking methods.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g003-550.jpg?1732341796" title=" <strong>Figure 3</strong><br/> <p>Fault diagnosis process of the proposed method.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g004-550.jpg?1732341797" title=" <strong>Figure 4</strong><br/> <p>Experimental setup of CWRU.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g005-550.jpg?1732341799" title=" <strong>Figure 5</strong><br/> <p>The waveform of raw vibration signals: (<b>a</b>) Ottawa; (<b>b</b>) CWRU.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g006-550.jpg?1732341801" title=" <strong>Figure 6</strong><br/> <p>Experimental setup of Ottawa.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g007-550.jpg?1732341804" title=" <strong>Figure 7</strong><br/> <p>The confusion matrix of experimental results: (<b>a</b>) TCA; (<b>b</b>) DDC; (<b>c</b>) DAN; (<b>d</b>) DCC; (<b>e</b>) MTSTLF (ours).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g008-550.jpg?1732341807" title=" <strong>Figure 8</strong><br/> <p>The clustering visualization of experimental results: (<b>a</b>) TCA; (<b>b</b>) DDC; (<b>c</b>) DAN; (<b>d</b>) DCC; (<b>e</b>) MTSTLF (ours).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g009-550.jpg?1732341809" title=" <strong>Figure 9</strong><br/> <p>The results of different classification methods on T2 and T3.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04622/article_deploy/html/images/electronics-13-04622-g010-550.jpg?1732341812" title=" <strong>Figure 10</strong><br/> <p>Visualization results of clustering using different methods: (<b>a</b>) TCA; (<b>b</b>) DDC; (<b>c</b>) DAN; (<b>d</b>) DCC; (<b>e</b>) MTSTLF (ours).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4622'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 12 pages, 539 KiB   </span> <a href="/2079-9292/13/23/4621/pdf?version=1732291545" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Parameter-Efficient Tuning for Object Tracking by Migrating Pre-Trained Decoders" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4621">Parameter-Efficient Tuning for Object Tracking by Migrating Pre-Trained Decoders</a> <div class="authors"> by <span class="inlineblock "><strong>Ruijuan Zhang</strong>, </span><span class="inlineblock "><strong>Li Wang</strong> and </span><span class="inlineblock "><strong>Song Yang</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4621; <a href="https://doi.org/10.3390/electronics13234621">https://doi.org/10.3390/electronics13234621</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Video object tracking has taken advantage of pre-trained weights on large-scale datasets. However, most trackers fully fine-tune all the backbone’s parameters for adjusting to tracking-specific representations, where the utilization rate of parameter adjustment is inefficient. In this paper, we aim to explore whether <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4621/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Video object tracking has taken advantage of pre-trained weights on large-scale datasets. However, most trackers fully fine-tune all the backbone’s parameters for adjusting to tracking-specific representations, where the utilization rate of parameter adjustment is inefficient. In this paper, we aim to explore whether a better balance can be achieved between parameter efficiency and tracking performance, and fully utilize the weight advantage of training on large-scale datasets. There are two main differences from a normal tracking paradigm: (i) We freeze the pre-trained weights of the backbone and add a dynamic adapter structure for every transformer block for tuning. (ii) We migrate the pre-trained decoder blocks to the tracking head for better generalization and localization. Extensive experiments are conducted on both mainstream challenging datasets and datasets for special scenarios or targets such as night-time and transparent objects. With the full utilization of pre-training knowledge, we found through experiments that a few tuned parameters can compensate for the gap between the pre-trained representation and the tracking-specific representation, especially for large backbones. Even better performance and generalization can be achieved. For instance, our AdaDe-B256 tracker achieves 49.5 AUC on the LaSOT<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mo>⁢</mo><mi>ext</mi></msub></semantics></math></inline-formula> which contains 150 sequences. <a href="/2079-9292/13/23/4621">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/9K0E8X1B22 ">Selected Papers from the 7th Asian Conference on Artificial Intelligence Technology (ACAIT 2023)</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4621/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1527472"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1527472"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1527472" data-cycle-prev="#prev1527472" data-cycle-progressive="#images1527472" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1527472-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04621/article_deploy/html/images/electronics-13-04621-g001-550.jpg?1732291744" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1527472" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1527472-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04621/article_deploy/html/images/electronics-13-04621-g002-550.jpg?1732291745'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1527472-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04621/article_deploy/html/images/electronics-13-04621-g003-550.jpg?1732291747'><p>Figure 3</p></div></script></div></div><div id="article-1527472-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04621/article_deploy/html/images/electronics-13-04621-g001-550.jpg?1732291744" title=" <strong>Figure 1</strong><br/> <p>Details of our tracking framework with parameter-efficient transfer learning. “…” represents the several omitted transformer layers which are the same as others.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4621'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04621/article_deploy/html/images/electronics-13-04621-g002-550.jpg?1732291745" title=" <strong>Figure 2</strong><br/> <p>Three variants of trackers for performance effects of pre-trained decoder.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4621'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04621/article_deploy/html/images/electronics-13-04621-g003-550.jpg?1732291747" title=" <strong>Figure 3</strong><br/> <p>Visualization cases of our AdaDe-B256 tracker and other trackers.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4621'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 824 KiB   </span> <a href="/2079-9292/13/23/4620/pdf?version=1732283883" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Anti-Disturbance Target Tracking Control of Auxiliary Unmanned Ground Vehicles for Physical Education" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4620">Anti-Disturbance Target Tracking Control of Auxiliary Unmanned Ground Vehicles for Physical Education</a> <div class="authors"> by <span class="inlineblock "><strong>Lei Liu</strong> and </span><span class="inlineblock "><strong>Wei Yin</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4620; <a href="https://doi.org/10.3390/electronics13234620">https://doi.org/10.3390/electronics13234620</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The auxiliary unmanned ground vehicle (AUGV) for physical education can significantly enhance the continuity and safety of training and competitions. However, obstacles and area boundary constraints present substantial challenges to the efficiency of the AUGV. This paper proposes an anti-disturbance target tracking control <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4620/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The auxiliary unmanned ground vehicle (AUGV) for physical education can significantly enhance the continuity and safety of training and competitions. However, obstacles and area boundary constraints present substantial challenges to the efficiency of the AUGV. This paper proposes an anti-disturbance target tracking control strategy for AUGV, enabling rapid tracking of out-of-bounds balls. In the guidance layer, we design safety constraints based on the exponentially stabilizing control Lyapunov function (ES-CLF) position constraint and control barrier function (CBF), and solve the expected convergence velocity guidance law through quadratic programming. Additionally, the expected motion direction of AUGV is determined using the expected combined velocity. In the control layer, we employ a nonlinear tracking differentiators (NLTD) to achieve finite-time estimation of the derivative of the guidance velocity signal, and observed the model parameter uncertainty and external environmental disturbances through a fixed time disturbance observer. Finally, a fixed-time control strategy is developed to achieve precise target tracking. Stability analysis and simulation results confirm the effectiveness of the proposed AUGV target tracking control strategy and the safety collision avoidance method. <a href="/2079-9292/13/23/4620">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/electronics/sections/systems_control_engineering">Systems & Control Engineering</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 23 pages, 5281 KiB   </span> <a href="/2079-9292/13/23/4619/pdf?version=1732283432" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="A Multiscale Adaptive Fusion Network for Modular Multilevel Converter Fault Diagnosis" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4619">A Multiscale Adaptive Fusion Network for Modular Multilevel Converter Fault Diagnosis</a> <div class="authors"> by <span class="inlineblock "><strong>Longzhang Ke</strong>, </span><span class="inlineblock "><strong>Guozhen Hu</strong>, </span><span class="inlineblock "><strong>Zhi Liu</strong>, </span><span class="inlineblock "><strong>Yuqing Yang</strong>, </span><span class="inlineblock "><strong>Qianju Cheng</strong> and </span><span class="inlineblock "><strong>Peng Zhang</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4619; <a href="https://doi.org/10.3390/electronics13234619">https://doi.org/10.3390/electronics13234619</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Modular Multilevel Converters (MMCs) play a crucial role in new energy grid connection and renewable energy conversion systems due to the significant merits of good modularity, flexible scalability, and lower operating loss. However, reliability is a significant challenge for MMCs, which consist of <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4619/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Modular Multilevel Converters (MMCs) play a crucial role in new energy grid connection and renewable energy conversion systems due to the significant merits of good modularity, flexible scalability, and lower operating loss. However, reliability is a significant challenge for MMCs, which consist of a large number of Insulated Gate Bipolar Transistors (IGBTs). Failures of the IGBTs in submodules (SMs) are a critical issue that affect the performance and operation of MMCs. The insufficient ability of convolutional neural networks to learn key fault features affects the accuracy of MMC fault diagnosis. To resolve this issue, this paper proposes a novel deep fault diagnosis framework named the Multiscale Adaptive Fusion Network (MSAFN) for MMC fault diagnosis. In the proposed MSAFN, the fault features of the raw current in an MMC are extracted by employing multiscale convolutional neural networks (CNNs) firstly, and then a channel attention mechanism is added to adaptively select the channel containing key features, so as to improve the fault diagnosis ability of the MMC in a noisy environment. Finally, the adaptive size of a one-dimensional CNN is adopted to adjust the weight of the feature channels of different scales, which are adaptively fused for fault diagnosis. Experimental validation is performed on two different MMC datasets. Experimental results confirm that the introduction of an attention mechanism of the multiscale feature adaptive fusion channel improves the recognition accuracy of the model by an average of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>15</mn><mo>.</mo><mn>6</mn><mo>%</mo></mrow></semantics></math></inline-formula>. Moreover, comparative experiments under different signal-to-noise ratios (SNRs) demonstrate that the MSAFN maintains accuracy levels above <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>96</mn><mo>.</mo><mn>7</mn><mo>%</mo></mrow></semantics></math></inline-formula>, highlighting its excellent performance, particularly under noisy conditions. <a href="/2079-9292/13/23/4619">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/electronics/sections/power_electronics">Power Electronics</a>)<br/> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 5441 KiB   </span> <a href="/2079-9292/13/23/4618/pdf?version=1732280563" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Parallel Fusion of Graph and Text with Semantic Enhancement for Commonsense Question Answering" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4618">Parallel Fusion of Graph and Text with Semantic Enhancement for Commonsense Question Answering</a> <div class="authors"> by <span class="inlineblock "><strong>Jiachuang Zong</strong>, </span><span class="inlineblock "><strong>Zhao Li</strong>, </span><span class="inlineblock "><strong>Tong Chen</strong>, </span><span class="inlineblock "><strong>Liguo Zhang</strong> and </span><span class="inlineblock "><strong>Yiming Zhan</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4618; <a href="https://doi.org/10.3390/electronics13234618">https://doi.org/10.3390/electronics13234618</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Commonsense question answering (CSQA) is a challenging task in the field of knowledge graph question answering. It combines the context of the question with the relevant knowledge in the knowledge graph to reason and give an answer to the question. Existing CSQA models <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4618/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Commonsense question answering (CSQA) is a challenging task in the field of knowledge graph question answering. It combines the context of the question with the relevant knowledge in the knowledge graph to reason and give an answer to the question. Existing CSQA models combine pretrained language models and graph neural networks to process question context and knowledge graph information, respectively, and obtain each other’s information during the reasoning process to improve the accuracy of reasoning. However, the existing models do not fully utilize the textual representation and graph representation after reasoning to reason about the answer, and they do not give enough semantic representation to the edges during the reasoning process of the knowledge graph. Therefore, we propose a novel parallel fusion framework for text and knowledge graphs, using the fused global graph information to enhance the semantic information of reasoning answers. In addition, we enhance the relationship embedding by enriching the initial semantics and adjusting the initial weight distribution, thereby improving the reasoning ability of the graph neural network. We conducted experiments on two public datasets, CommonsenseQA and OpenBookQA, and found that our model is competitive when compared with other baseline models. Additionally, we validated the generalizability of our model on the MedQA-USMLE dataset. <a href="/2079-9292/13/23/4618">Full article</a> </div> </div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 24 pages, 4221 KiB   </span> <a href="/2079-9292/13/23/4617/pdf?version=1732276190" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Dynamic Resource Aggregation Method Based on Statistical Capacity Distribution" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4617">Dynamic Resource Aggregation Method Based on Statistical Capacity Distribution</a> <div class="authors"> by <span class="inlineblock "><strong>Yuexin Wang</strong>, </span><span class="inlineblock "><strong>Jiali You</strong> and </span><span class="inlineblock "><strong>Yang Li</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4617; <a href="https://doi.org/10.3390/electronics13234617">https://doi.org/10.3390/electronics13234617</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The computing network is a novel architecture that enables resource matching through the network. In distributed computing networks, computing resource management devices collect resource information and report it to network nodes. These nodes then broadcast the information to guide resource matching. One challenge <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4617/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The computing network is a novel architecture that enables resource matching through the network. In distributed computing networks, computing resource management devices collect resource information and report it to network nodes. These nodes then broadcast the information to guide resource matching. One challenge is efficiently aggregating and disseminating computing resource information, as directly reporting fully multi-dimensional data can cause excessive overhead, while overly simplified aggregation may reduce matching accuracy. Existing aggregation methods typically rely on static resource information, overlooking the heterogeneity and dynamics of computing resources that arise from variations in resource capabilities and fluctuations over time, leading to suboptimal matching decisions. In response, this study proposes a dynamic resource aggregation method based on statistical capacity distribution. By modeling the capacity distribution of computing nodes, this method captures dynamic resource information, enabling more precise resource matching. Additionally, constructing resource groups and calculating representative distributions effectively compress the volume of data announcements. Experiments and data analysis demonstrate that, compared to static resource matching methods, the proposed method improves matching accuracy by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>48</mn><mo>%</mo></mrow></semantics></math></inline-formula>. Furthermore, it reduces announcement overhead by approximately <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>77.1</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared to existing dynamic resource allocation methods. These findings provide an efficient solution for resource aggregation in distributed computing networks. <a href="/2079-9292/13/23/4617">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4617/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1527114"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1527114"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1527114" data-cycle-prev="#prev1527114" data-cycle-progressive="#images1527114" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1527114-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g001-550.jpg?1732276531" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1527114" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1527114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g002-550.jpg?1732276534'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1527114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g003-550.jpg?1732276535'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1527114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g004-550.jpg?1732276538'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1527114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g005-550.jpg?1732276539'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1527114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g006-550.jpg?1732276540'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1527114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g007-550.jpg?1732276541'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1527114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g008-550.jpg?1732276543'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1527114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g009-550.jpg?1732276544'><p>Figure 9</p></div></script></div></div><div id="article-1527114-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g001-550.jpg?1732276531" title=" <strong>Figure 1</strong><br/> <p>System architecture overview.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g002-550.jpg?1732276534" title=" <strong>Figure 2</strong><br/> <p>Computing resource aggregation diagram.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g003-550.jpg?1732276535" title=" <strong>Figure 3</strong><br/> <p>Topology in simulation experiment.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g004-550.jpg?1732276538" title=" <strong>Figure 4</strong><br/> <p>Matching accuracy.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g005-550.jpg?1732276539" title=" <strong>Figure 5</strong><br/> <p>Comparison of matched computing node counts.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g006-550.jpg?1732276540" title=" <strong>Figure 6</strong><br/> <p>Comparison of matched computing node counts.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g007-550.jpg?1732276541" title=" <strong>Figure 7</strong><br/> <p>Total data usage comparison at different node counts.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g008-550.jpg?1732276543" title=" <strong>Figure 8</strong><br/> <p>Data saving rate comparison at different node counts.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04617/article_deploy/html/images/electronics-13-04617-g009-550.jpg?1732276544" title=" <strong>Figure 9</strong><br/> <p>Information Loss Caused by Aggregation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4617'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 30 pages, 1831 KiB   </span> <a href="/2079-9292/13/23/4616/pdf?version=1732273711" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="MultiTagging: A Vulnerable Smart Contract Labeling and Evaluation Framework" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4616">MultiTagging: A Vulnerable Smart Contract Labeling and Evaluation Framework</a> <div class="authors"> by <span class="inlineblock "><strong>Shikah J. Alsunaidi</strong>, </span><span class="inlineblock "><strong>Hamoud Aljamaan</strong> and </span><span class="inlineblock "><strong>Mohammad Hammoudeh</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4616; <a href="https://doi.org/10.3390/electronics13234616">https://doi.org/10.3390/electronics13234616</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Identifying vulnerabilities in Smart Contracts (SCs) is crucial, as they can lead to significant financial losses if exploited. Although various SC vulnerability identification methods exist, selecting the most effective approach remains challenging. This article examines these challenges and introduces solutions to enhance SC <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4616/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Identifying vulnerabilities in Smart Contracts (SCs) is crucial, as they can lead to significant financial losses if exploited. Although various SC vulnerability identification methods exist, selecting the most effective approach remains challenging. This article examines these challenges and introduces solutions to enhance SC vulnerability identification. It introduces MultiTagging, a modular SC multi-labeling framework designed to overcome limitations in existing SC vulnerability identification approaches. MultiTagging automates SC vulnerability tagging by parsing analysis reports and mapping tool-specific tags to standardized labels, including SC Weakness Classification (SWC) codes and Decentralized Application Security Project (DASP) ranks. Its mapping strategy and the proposed vulnerability taxonomy resolve tool-level labeling inconsistencies, where different tools use distinct labels for identical vulnerabilities. The framework integrates an evaluation module to assess SC vulnerability identification methods. MultiTagging enables both tool-based and vote-based SC vulnerability labeling. To improve labeling accuracy, the article proposes Power-based voting, a method that systematically defines voter roles and voting thresholds for each vulnerability. MultiTagging is used to evaluate labeling across six tools: MAIAN, Mythril, Semgrep, Slither, Solhint, and VeriSmart. The results reveal high coverage for Mythril, Slither, and Solhint, which identified eight, seven, and six DASP classes, respectively. Tool performance varied, underscoring the impracticality of relying on a single tool to identify all vulnerability classes. A comparative evaluation of Power-based voting and two threshold-based methods—AtLeastOne and Majority voting—shows that while voting methods can increase vulnerability identification coverage, they may also reduce detection performance. Power-based voting proved more effective than pure threshold-based methods across all vulnerability classes. <a href="/2079-9292/13/23/4616">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4616/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1527091"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1527091"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1527091" data-cycle-prev="#prev1527091" data-cycle-progressive="#images1527091" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1527091-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g001-550.jpg?1732273801" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1527091" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1527091-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g002-550.jpg?1732273803'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1527091-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g003-550.jpg?1732273806'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1527091-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g004-550.jpg?1732273810'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1527091-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g005-550.jpg?1732273811'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1527091-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g006-550.jpg?1732273813'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1527091-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g007-550.jpg?1732273816'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1527091-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g008-550.jpg?1732273816'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1527091-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g009-550.jpg?1732273818'><p>Figure 9</p></div></script></div></div><div id="article-1527091-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g001-550.jpg?1732273801" title=" <strong>Figure 1</strong><br/> <p>Mapping SWC codes to CWE.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g002-550.jpg?1732273803" title=" <strong>Figure 2</strong><br/> <p>Mapping SWC codes to DASP Top 10.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g003-550.jpg?1732273806" title=" <strong>Figure 3</strong><br/> <p>Overview of MultiTagging framework.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g004-550.jpg?1732273810" title=" <strong>Figure 4</strong><br/> <p>Flowchart of the Power-based voting algorithm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g005-550.jpg?1732273811" title=" <strong>Figure 5</strong><br/> <p>Overview of used benchmarks.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g006-550.jpg?1732273813" title=" <strong>Figure 6</strong><br/> <p>Analysis tools efficiency metrics.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g007-550.jpg?1732273816" title=" <strong>Figure 7</strong><br/> <p>Performance overview of analysis tools and voting methods using a portion of the benchmark.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g008-550.jpg?1732273816" title=" <strong>Figure 8</strong><br/> <p>Overlap of analysis tool findings.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04616/article_deploy/html/images/electronics-13-04616-g009-550.jpg?1732273818" title=" <strong>Figure 9</strong><br/> <p>Overlap of analysis tool findings per vulnerability.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4616'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 14 pages, 2708 KiB   </span> <a href="/2079-9292/13/23/4615/pdf?version=1732270983" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="A Multi-Attack Adaptive Fake Face Detection Network Based on Global Feature Normalization" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4615">A Multi-Attack Adaptive Fake Face Detection Network Based on Global Feature Normalization</a> <div class="authors"> by <span class="inlineblock "><strong>Honggang Xie</strong>, </span><span class="inlineblock "><strong>Jia Liu</strong>, </span><span class="inlineblock "><strong>Zhiwei Chen</strong>, </span><span class="inlineblock "><strong>Kaiyuan Hou</strong> and </span><span class="inlineblock "><strong>Yuan Yao</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4615; <a href="https://doi.org/10.3390/electronics13234615">https://doi.org/10.3390/electronics13234615</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The advancement of deepfake technology has resulted in increasingly realistic forged faces, posing a challenge for existing fake face detection models, which often exhibit poor adaptability to complex and varied forgery techniques. To address this challenge, this paper proposes a fake face detection <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4615/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The advancement of deepfake technology has resulted in increasingly realistic forged faces, posing a challenge for existing fake face detection models, which often exhibit poor adaptability to complex and varied forgery techniques. To address this challenge, this paper proposes a fake face detection network that demonstrates high accuracy and generalization capabilities. A global normalization calibration module is designed to address the issue of ineffective feature extraction within the network, enhancing the model’s focus on key feature regions by establishing a mutual inhibition competition mechanism between different channels. This network maintains high accuracy even when facing various attack methods in both the objective and digital worlds. Experimental results indicate that the proposed method excels in both binary and multi-class classification tests on the CASIA-FASD dataset, the Celeb-DF dataset, and a self-constructed dataset. Specifically, for binary classification tasks, the accuracy reaches 98.19% on the CASIA-FASD dataset, 99.17% on the Celeb-DF dataset, and 98.03% on the self-constructed dataset. In comparison, other methods exhibit slightly inferior performance. For multi-class classification tasks, the proposed model achieves the best performance across all tested forgery types, demonstrating exceptional overall performance and adaptability. <a href="/2079-9292/13/23/4615">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/electronics/sections/Artificial_Intell">Artificial Intelligence</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4615/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1527011"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1527011"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1527011" data-cycle-prev="#prev1527011" data-cycle-progressive="#images1527011" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1527011-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g001-550.jpg?1732271049" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1527011" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1527011-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g002-550.jpg?1732271050'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1527011-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g003-550.jpg?1732271051'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1527011-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g004-550.jpg?1732271052'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1527011-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g005-550.jpg?1732271054'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1527011-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g006-550.jpg?1732271056'><p>Figure 6</p></div></script></div></div><div id="article-1527011-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g001-550.jpg?1732271049" title=" <strong>Figure 1</strong><br/> <p>Comparison of a fake face in the digital and objective worlds.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4615'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g002-550.jpg?1732271050" title=" <strong>Figure 2</strong><br/> <p>Overall network structure: It consists of four stages, each containing a set of FasterNet blocks. Each stage is preceded by a Conv4×4 embedding layer or a Conv2×2 merging layer. Each FasterNet block is composed of a PConv layer, a global normalization calibration module, and two convolutional layers. The final three layers of the network are global average pooling, a convolutional layer, and a fully connected layer, which are used for feature transformation and classification.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4615'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g003-550.jpg?1732271051" title=" <strong>Figure 3</strong><br/> <p>Global normalized calibration module diagram.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4615'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g004-550.jpg?1732271052" title=" <strong>Figure 4</strong><br/> <p>Examples of a multi-attack forged-face dataset.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4615'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g005-550.jpg?1732271054" title=" <strong>Figure 5</strong><br/> <p>Class activation maps of real faces before and after adding the global normalization calibration module at each layer.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4615'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04615/article_deploy/html/images/electronics-13-04615-g006-550.jpg?1732271056" title=" <strong>Figure 6</strong><br/> <p>Class activation maps of fake faces before and after adding the global normalization calibration module at each layer.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4615'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 21 pages, 3720 KiB   </span> <a href="/2079-9292/13/23/4614/pdf?version=1732270026" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Simple and Effective Control System for Active AC Ripple Filtering Circuits" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4614">Simple and Effective Control System for Active AC Ripple Filtering Circuits</a> <div class="authors"> by <span class="inlineblock "><strong>Roshan Sharma</strong>, </span><span class="inlineblock "><strong>Masoud Karimi-Ghartemani</strong> and </span><span class="inlineblock "><strong>Umar Iqbal</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4614; <a href="https://doi.org/10.3390/electronics13234614">https://doi.org/10.3390/electronics13234614</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In systems where dc and ac subsystems are interacting, dc capacitors are used to balance (filter or decouple) the ac power pulsations. The required capacitance often poses a limitation in terms of physical footprint, cost, and/or reliability. Active ripple filtering circuits are widely <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4614/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In systems where dc and ac subsystems are interacting, dc capacitors are used to balance (filter or decouple) the ac power pulsations. The required capacitance often poses a limitation in terms of physical footprint, cost, and/or reliability. Active ripple filtering circuits are widely studied in the literature for reducing the size of the capacitor needed by using power electronic switches, passive circuit components, and a control system. The passive circuit components include a substantially smaller dc capacitor at a reasonably higher or lower voltage, and an inductor for filtering the switching ripples. The control systems presented in the literature for such systems are complex and need multiple sensors and are hardly plug-and-play and universal. This paper proposes a simple yet effective control system which uses only one voltage sensor. The circuit accurately emulates a large capacitor within a wide frequency bandwidth in a plug-and-play manner. The paper explains the details of the proposed control system and presents simulation and experimental results to illustrate its properties. <a href="/2079-9292/13/23/4614">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/RFD1X186PM ">New Trends in Power Electronics for Microgrids</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4614/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1526982"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1526982"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1526982" data-cycle-prev="#prev1526982" data-cycle-progressive="#images1526982" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1526982-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g001-550.jpg?1732270327" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1526982" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g002-550.jpg?1732270327'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g003-550.jpg?1732270329'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g004-550.jpg?1732270330'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g005-550.jpg?1732270331'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g006-550.jpg?1732270331'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g007-550.jpg?1732270333'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g008-550.jpg?1732270335'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g009-550.jpg?1732270337'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g010-550.jpg?1732270339'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g011-550.jpg?1732270341'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g012-550.jpg?1732270343'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g013-550.jpg?1732270344'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g014-550.jpg?1732270347'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g015-550.jpg?1732270348'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g016-550.jpg?1732270349'><p>Figure 16</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g017-550.jpg?1732270350'><p>Figure 17</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g018-550.jpg?1732270351'><p>Figure 18</p></div> --- <div class='openpopupgallery' data-imgindex='18' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g019-550.jpg?1732270351'><p>Figure 19</p></div> --- <div class='openpopupgallery' data-imgindex='19' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g020-550.jpg?1732270352'><p>Figure 20</p></div> --- <div class='openpopupgallery' data-imgindex='20' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g021-550.jpg?1732270354'><p>Figure 21</p></div> --- <div class='openpopupgallery' data-imgindex='21' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g022-550.jpg?1732270355'><p>Figure 22</p></div> --- <div class='openpopupgallery' data-imgindex='22' data-target='article-1526982-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g023-550.jpg?1732270356'><p>Figure 23</p></div></script></div></div><div id="article-1526982-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g001-550.jpg?1732270327" title=" <strong>Figure 1</strong><br/> <p>Circuit structures of proposed SdcCap. (<b>a</b>) General structure; (<b>b</b>) Buck topology, <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>c</mi> </msub> <mo>&gt;</mo> <mi>v</mi> </mrow> </semantics></math>; (<b>c</b>) Boost topology, <math display="inline"><semantics> <mrow> <msub> <mi>v</mi> <mi>c</mi> </msub> <mo>&lt;</mo> <mi>v</mi> </mrow> </semantics></math>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g002-550.jpg?1732270327" title=" <strong>Figure 2</strong><br/> <p>Proposed control structures. (<b>a</b>) Buck topology control structure, <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>c</mi> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mo>&gt;</mo> <msub> <mi>V</mi> <mrow> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) Boost topology control structure, <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>c</mi> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mo>&lt;</mo> <msub> <mi>V</mi> <mrow> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g003-550.jpg?1732270329" title=" <strong>Figure 3</strong><br/> <p>Buck responses when bus voltage <math display="inline"><semantics> <mrow> <mi>v</mi> <mo stretchy="false">(</mo> <mi>t</mi> <mo stretchy="false">)</mo> <mo>=</mo> <mn>200</mn> <mo>+</mo> <mn>10</mn> <mo form="prefix">sin</mo> <mo stretchy="false">(</mo> <mn>240</mn> <mi>π</mi> <mi>t</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math> experiences <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>4</mn> </mrow> </semantics></math>% change in its offset value. (Control parameters: <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>n</mi> </mrow> </msub> <mo>=</mo> <mn>200</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>c</mi> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mo>=</mo> <mn>275</mn> </mrow> </semantics></math>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g004-550.jpg?1732270330" title=" <strong>Figure 4</strong><br/> <p>Boost responses when bus voltage <math display="inline"><semantics> <mrow> <mi>v</mi> <mo stretchy="false">(</mo> <mi>t</mi> <mo stretchy="false">)</mo> <mo>=</mo> <mn>200</mn> <mo>+</mo> <mn>10</mn> <mo form="prefix">sin</mo> <mo stretchy="false">(</mo> <mn>240</mn> <mi>π</mi> <mi>t</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math> experiences <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>4</mn> </mrow> </semantics></math>% change in its offset value. (Control parameters: <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>n</mi> </mrow> </msub> <mo>=</mo> <mn>200</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>c</mi> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mo>=</mo> <mn>125</mn> </mrow> </semantics></math>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g005-550.jpg?1732270331" title=" <strong>Figure 5</strong><br/> <p>Proposed modified controller for boost topology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g006-550.jpg?1732270331" title=" <strong>Figure 6</strong><br/> <p>Schematic diagram of a passive rectifier.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g007-550.jpg?1732270333" title=" <strong>Figure 7</strong><br/> <p>Proposed buck converter- based capacitor’s responses in a single-phase 1 kW passive rectifier: 500 W load-changes occur at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math> ms and <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> ms; grid voltage changes <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>10</mn> </mrow> </semantics></math>% at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>150</mn> </mrow> </semantics></math> ms and 200 ms.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g008-550.jpg?1732270335" title=" <strong>Figure 8</strong><br/> <p>Proposed boost converter-based capacitor’s responses in a single-phase 1 kW passive rectifier: 500 W load-changes occur at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math> ms and <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> ms; grid voltage changes <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>5</mn> </mrow> </semantics></math>% at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>150</mn> </mrow> </semantics></math> ms and 200 ms.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g009-550.jpg?1732270337" title=" <strong>Figure 9</strong><br/> <p>Proposed (modified) boost converter-based capacitor’s responses in a single-phase 1 kW passive rectifier: 500 W load-changes occur at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math> ms and <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> ms; grid voltage changes <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>5</mn> </mrow> </semantics></math>% at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>150</mn> </mrow> </semantics></math> ms and 200 ms.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g010-550.jpg?1732270339" title=" <strong>Figure 10</strong><br/> <p>Proposed (modified) boost converter-based capacitor’s responses in a single-phase 1 kW passive rectifier: 500 W load-changes occur at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math> ms and <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> ms; grid voltage changes <math display="inline"><semantics> <mrow> <mo>±</mo> <mn>10</mn> </mrow> </semantics></math>% at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>150</mn> </mrow> </semantics></math> ms and 200 ms.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g011-550.jpg?1732270341" title=" <strong>Figure 11</strong><br/> <p>Two-stage PV inverter topology and control.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g012-550.jpg?1732270343" title=" <strong>Figure 12</strong><br/> <p>Responses of the proposed SdcCap as a dc-link capacitor in a single-phase 3.5 kVA inverter with two-stage converter topology: the active power of the inverter changes at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>0.2</mn> </mrow> </semantics></math> s, while the reactive power changes at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <mn>0.4</mn> </mrow> </semantics></math> s. An SdcCap that uses a capacitor of 37.5 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>F is compared against a large capacitor of 750 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>F.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g013-550.jpg?1732270344" title=" <strong>Figure 13</strong><br/> <p>One-stage PV inverter topology and control.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g014-550.jpg?1732270347" title=" <strong>Figure 14</strong><br/> <p>Responses of the SdcCap as a dc-link capacitor in a single phase 8.5 kVA inverter with one-stage converter topology: the active power of the inverter changes at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>0.2</mn> </mrow> </semantics></math> s, while the reactive power changes at <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>0.4</mn> </mrow> </semantics></math> s. The proposed SdcCap that uses a capacitor of 75 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>F in the buck topology is compared against directly connected large capacitors of 1500 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>F.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g015-550.jpg?1732270348" title=" <strong>Figure 15</strong><br/> <p>Schematic diagram of the flyback converter.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g016-550.jpg?1732270349" title=" <strong>Figure 16</strong><br/> <p>Diagram of the approach of [<a href="#B8-electronics-13-04614" class="html-bibr">8</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g017-550.jpg?1732270350" title=" <strong>Figure 17</strong><br/> <p>Output voltages of flyback converter with large capacitor, with SdcCap, and with conventional method.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g018-550.jpg?1732270351" title=" <strong>Figure 18</strong><br/> <p>Capacitor voltage of SdcCap and conventional method.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g019-550.jpg?1732270351" title=" <strong>Figure 19</strong><br/> <p>Modulating index of SdcCap and conventional method.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g020-550.jpg?1732270352" title=" <strong>Figure 20</strong><br/> <p>Output voltages when the ac frequency is 50 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g021-550.jpg?1732270354" title=" <strong>Figure 21</strong><br/> <p>Experimental setup. (<b>a</b>) Photograph of laboratory experimental setup; (<b>b</b>) Experimental setup schematic.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g022-550.jpg?1732270355" title=" <strong>Figure 22</strong><br/> <p>Experimental results with large capacitor and proposed SdcCap. (<b>a</b>) Rectifier output voltage with large capacitor. (<b>b</b>) Rectifier output voltage with SdcCap. (<b>c</b>) Voltage across small capacitor in SdcCap.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04614/article_deploy/html/images/electronics-13-04614-g023-550.jpg?1732270356" title=" <strong>Figure 23</strong><br/> <p>Simulation results of load voltages of passive rectifier application described in experiment setup with a large capacitor and proposed SdcCap.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4614'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 28 pages, 3796 KiB   </span> <a href="/2079-9292/13/23/4613/pdf?version=1732269204" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Adaptive Dynamic Shuffle Convolutional Parallel Network for Image Super-Resolution" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4613">Adaptive Dynamic Shuffle Convolutional Parallel Network for Image Super-Resolution</a> <div class="authors"> by <span class="inlineblock "><strong>Yiting Long</strong>, </span><span class="inlineblock "><strong>Haoyu Ruan</strong>, </span><span class="inlineblock "><strong>Hui Zhao</strong>, </span><span class="inlineblock "><strong>Yi Liu</strong>, </span><span class="inlineblock "><strong>Lei Zhu</strong>, </span><span class="inlineblock "><strong>Chengyuan Zhang</strong> and </span><span class="inlineblock "><strong>Xinghui Zhu</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4613; <a href="https://doi.org/10.3390/electronics13234613">https://doi.org/10.3390/electronics13234613</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Image super-resolution has experienced significant advancements with the emergence of deep learning technology. However, deploying highly complex super-resolution networks on resource-constrained devices poses a challenge due to their substantial computational requirements. This paper presents the <b>A</b>daptive <b>D</b>ynamic <b>S</b>huffle <b>C</b>onvolutional <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4613/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Image super-resolution has experienced significant advancements with the emergence of deep learning technology. However, deploying highly complex super-resolution networks on resource-constrained devices poses a challenge due to their substantial computational requirements. This paper presents the <b>A</b>daptive <b>D</b>ynamic <b>S</b>huffle <b>C</b>onvolutional <b>P</b>arallel <b>N</b>etwork (<b>ADSCPN</b>), a novel lightweight super-resolution model designed to achieve an optimal balance between computational efficiency and image reconstruction quality. The ADSCPN framework employs large-kernel parallel depthwise separable convolutions, dynamic convolutions, and an enhanced attention mechanism to optimize feature extraction and improve detail preservation. Extensive evaluations on standard benchmark datasets demonstrate that ADSCPN achieves state-of-the-art performance while significantly reducing computational complexity, making it well-suited for practical applications on devices with limited computational resources. <a href="/2079-9292/13/23/4613">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/Big_Model_Image ">Big Model Techniques for Image Processing</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4613/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1526955"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1526955"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1526955" data-cycle-prev="#prev1526955" data-cycle-progressive="#images1526955" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1526955-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g001-550.jpg?1732269348" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1526955" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g002-550.jpg?1732269348'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g003-550.jpg?1732269349'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g004-550.jpg?1732269349'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g005-550.jpg?1732269350'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g006-550.jpg?1732269351'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g007-550.jpg?1732269352'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g008-550.jpg?1732269353'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g009-550.jpg?1732269355'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1526955-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g010-550.jpg?1732269358'><p>Figure 10</p></div></script></div></div><div id="article-1526955-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g001-550.jpg?1732269348" title=" <strong>Figure 1</strong><br/> <p>The architecture of ADSCPN.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g002-550.jpg?1732269348" title=" <strong>Figure 2</strong><br/> <p>The structure of the Feature Process Block (FPB).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g003-550.jpg?1732269349" title=" <strong>Figure 3</strong><br/> <p>The structure of the channel processing block (CPB).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g004-550.jpg?1732269349" title=" <strong>Figure 4</strong><br/> <p>The structure of point-wise multi-layer perceptron (PW-MLP).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g005-550.jpg?1732269350" title=" <strong>Figure 5</strong><br/> <p>The structure of the feature extraction block (FEB).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g006-550.jpg?1732269351" title=" <strong>Figure 6</strong><br/> <p>The structure of the point-attention convolution group (PACG).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g007-550.jpg?1732269352" title=" <strong>Figure 7</strong><br/> <p>ESA and EESA module structure comparison. (<b>a</b>) Original ESA block. (<b>b</b>) EESA block.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g008-550.jpg?1732269353" title=" <strong>Figure 8</strong><br/> <p>The impact of different settings on quantitative PSNR performance. (<b>a</b>) The number of Feature Process Blocks. (<b>b</b>) The number of model channels.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g009-550.jpg?1732269355" title=" <strong>Figure 9</strong><br/> <p>Visual comparison of the results for different methods.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04613/article_deploy/html/images/electronics-13-04613-g010-550.jpg?1732269358" title=" <strong>Figure 10</strong><br/> <p>Visual comparison of different super-resolution methods on the DRealSR, DIV2KRK, and RealSR datasets.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4613'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 2256 KiB   </span> <a href="/2079-9292/13/23/4612/pdf?version=1732268906" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Multitasking Feature Selection Using a Clonal Selection Algorithm for High-Dimensional Microarray Data" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4612">Multitasking Feature Selection Using a Clonal Selection Algorithm for High-Dimensional Microarray Data</a> <div class="authors"> by <span class="inlineblock "><strong>Yi Wang</strong>, </span><span class="inlineblock "><strong>Dan Luo</strong> and </span><span class="inlineblock "><strong>Jian Yao</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4612; <a href="https://doi.org/10.3390/electronics13234612">https://doi.org/10.3390/electronics13234612</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Effective gene feature selection is critical for enhancing the interpretability and accuracy of genetic data analysis, particularly in the realm of disease prediction and precision medicine. Most evolutionary feature selection algorithms tend to become stuck in local optima and incur high computational costs, <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4612/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Effective gene feature selection is critical for enhancing the interpretability and accuracy of genetic data analysis, particularly in the realm of disease prediction and precision medicine. Most evolutionary feature selection algorithms tend to become stuck in local optima and incur high computational costs, particularly when dealing with the complex and high-dimensional nature of genetic data. To address these issues, this study proposes a multitasking feature selection method based on clone selection for high-dimensional microarray data, which identifies optimal features by transferring useful knowledge across two related tasks derived from the same microarray dataset. First, a dual-task generation strategy is designed, where one task selects features based on the Relief-F method, and the other task is generated from the original features. Second, a new mutation operator is introduced to share useful information between the multiple tasks. Finally, an improved clonal selection algorithm is proposed to strengthen the global and local search abilities. The experimental results on six high-dimensional microarray datasets demonstrate that our method significantly outperforms four state-of-the-art feature selection methods, highlighting its effectiveness and efficiency in tackling complex feature selection problems. <a href="/2079-9292/13/23/4612">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/50EK4W3G1P ">Knowledge Information Extraction Research</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4612/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1526946"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1526946"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1526946" data-cycle-prev="#prev1526946" data-cycle-progressive="#images1526946" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1526946-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04612/article_deploy/html/images/electronics-13-04612-g001-550.jpg?1732269044" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1526946" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1526946-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04612/article_deploy/html/images/electronics-13-04612-g002-550.jpg?1732269045'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1526946-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04612/article_deploy/html/images/electronics-13-04612-g003-550.jpg?1732269046'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1526946-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04612/article_deploy/html/images/electronics-13-04612-g004-550.jpg?1732269047'><p>Figure 4</p></div></script></div></div><div id="article-1526946-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04612/article_deploy/html/images/electronics-13-04612-g001-550.jpg?1732269044" title=" <strong>Figure 1</strong><br/> <p>The general framework of CSA-EMT.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4612'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04612/article_deploy/html/images/electronics-13-04612-g002-550.jpg?1732269045" title=" <strong>Figure 2</strong><br/> <p>The flowchart of the improved clonal selection algorithm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4612'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04612/article_deploy/html/images/electronics-13-04612-g003-550.jpg?1732269046" title=" <strong>Figure 3</strong><br/> <p>The accuracy (%) of CSA-EMT vs. that of the 1NN classifier using all features.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4612'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04612/article_deploy/html/images/electronics-13-04612-g004-550.jpg?1732269047" title=" <strong>Figure 4</strong><br/> <p>The percentage of selected features relative to the total number of features (%).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4612'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 22 pages, 2169 KiB   </span> <a href="/2079-9292/13/23/4611/pdf?version=1732267569" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Leveraging AI for Network Threat Detection—A Conceptual Overview" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4611">Leveraging AI for Network Threat Detection—A Conceptual Overview</a> <div class="authors"> by <span class="inlineblock "><strong>Muhammad Ali Paracha</strong>, </span><span class="inlineblock "><strong>Syed Usman Jamil</strong>, </span><span class="inlineblock "><strong>Khurram Shahzad</strong>, </span><span class="inlineblock "><strong>Muhammad Arif Khan</strong> and </span><span class="inlineblock "><strong>Abdul Rasheed</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4611; <a href="https://doi.org/10.3390/electronics13234611">https://doi.org/10.3390/electronics13234611</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Network forensics is commonly used to identify and analyse evidence of any illegal or unauthorised activity in a given network. The collected information can be used for preventive measures against potential cyber attacks and serve as evidence acceptable in legal proceedings. Several conventional <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4611/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Network forensics is commonly used to identify and analyse evidence of any illegal or unauthorised activity in a given network. The collected information can be used for preventive measures against potential cyber attacks and serve as evidence acceptable in legal proceedings. Several conventional tools and techniques are available to identify and collect such pieces of evidence; however, most of them require expensive commercial resources, longer investigation times, and costly human expertise. Due to modern networks’ diverse and heterogeneous nature, forensic operations through conventional means become a cumbersome and challenging process. This calls for a new look at how network forensics is approached, considering contemporary approaches to network analysis. In this work, we explore artificial intelligence (AI) techniques based on contemporary machine learning (ML) algorithms such as deep learning (DL) to conduct network forensics. We also propose an investigation model based on AI/ML techniques that can analyse network traffic and behavioural patterns to identify any prior or potential cyber attacks. The proposed AI-based network forensics model speeds up the investigation process, boosting network monitoring without human intervention. This also aims to provide timely and accurate information to network administrators for quick and effective decisions, enabling them to avoid and circumvent future cyber attacks. <a href="/2079-9292/13/23/4611">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/R1265A6U3R ">Artificial Intelligence for IoT Systems</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4611/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1526884"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1526884"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1526884" data-cycle-prev="#prev1526884" data-cycle-progressive="#images1526884" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1526884-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g001-550.jpg?1732267709" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1526884" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1526884-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g002-550.jpg?1732267710'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1526884-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g003-550.jpg?1732267711'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1526884-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g004-550.jpg?1732267713'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1526884-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g005-550.jpg?1732267714'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1526884-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g006-550.jpg?1732267718'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1526884-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g007-550.jpg?1732267719'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1526884-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g008-550.jpg?1732267721'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1526884-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g009-550.jpg?1732267724'><p>Figure 9</p></div></script></div></div><div id="article-1526884-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g001-550.jpg?1732267709" title=" <strong>Figure 1</strong><br/> <p>A comparative analysis of annual DDoS attacks from 2018 to 2023 [<a href="#B12-electronics-13-04611" class="html-bibr">12</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g002-550.jpg?1732267710" title=" <strong>Figure 2</strong><br/> <p>Projected stages of our research work. The first stage focuses on conceptual development and forms the basis of this work.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g003-550.jpg?1732267711" title=" <strong>Figure 3</strong><br/> <p>The joint role of network forensics and AI in network security.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g004-550.jpg?1732267713" title=" <strong>Figure 4</strong><br/> <p>A common enterprise network security architecture model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g005-550.jpg?1732267714" title=" <strong>Figure 5</strong><br/> <p>An example of a malicious network log from ingested data [<a href="#B70-electronics-13-04611" class="html-bibr">70</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g006-550.jpg?1732267718" title=" <strong>Figure 6</strong><br/> <p>Cyber threat detection framework (CTDF).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g007-550.jpg?1732267719" title=" <strong>Figure 7</strong><br/> <p>Network dataflow timeline with normal and under attack traffic.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g008-550.jpg?1732267721" title=" <strong>Figure 8</strong><br/> <p>Preliminary performance outcomes of CTDF.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04611/article_deploy/html/images/electronics-13-04611-g009-550.jpg?1732267724" title=" <strong>Figure 9</strong><br/> <p>Proposed future research directions and challenges.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4611'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 19 pages, 4031 KiB   </span> <a href="/2079-9292/13/23/4610/pdf?version=1732267407" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="MSTrans: Multi-Scale Transformer for Building Extraction from HR Remote Sensing Images" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4610">MSTrans: Multi-Scale Transformer for Building Extraction from HR Remote Sensing Images</a> <div class="authors"> by <span class="inlineblock "><strong>Fei Yang</strong>, </span><span class="inlineblock "><strong>Fenlong Jiang</strong>, </span><span class="inlineblock "><strong>Jianzhao Li</strong> and </span><span class="inlineblock "><strong>Lei Lu</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4610; <a href="https://doi.org/10.3390/electronics13234610">https://doi.org/10.3390/electronics13234610</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Buildings are one of the most important goals of human transformation of the Earth’s surface. Therefore, building extraction (BE), such as in urban resource management and planning, is a task that is meaningful to actual production and life. Computational intelligence techniques based on <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4610/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Buildings are one of the most important goals of human transformation of the Earth’s surface. Therefore, building extraction (BE), such as in urban resource management and planning, is a task that is meaningful to actual production and life. Computational intelligence techniques based on convolutional neural networks (CNNs) and Transformers have begun to be of interest in BE, and have made some progress. However, the BE methods based on CNNs are limited by the difficulty in capturing global long-range relationships, while Transformer-based methods are often not detailed enough for pixel-level annotation tasks because they focus on global information. To conquer the limitations, a multi-scale Transformer (MSTrans) is proposed for BE from high-resolution remote sensing images. In the proposed MSTrans, we develop a plug-and-play multi-scale Transformer (MST) module based on atrous spatial pyramid pooling (ASPP). The MST module can effectively capture tokens of different scales through the Transformer encoder and Transformer decoder. This can enhance multi-scale feature extraction of buildings, thereby improving the BE performance. Experiments on three real and challenging BE datasets verify the effectiveness of the proposed MSTrans. While the proposed approach may not achieve the highest Precision and Recall accuracies compared with the seven benchmark methods, it improves the overall metrics F1 and mIoU by 0.4% and 1.67%, respectively. <a href="/2079-9292/13/23/4610">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/computational_intelligence_ele ">Emerging Technologies in Computational Intelligence</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4610/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1526878"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1526878"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1526878" data-cycle-prev="#prev1526878" data-cycle-progressive="#images1526878" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1526878-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g001-550.jpg?1732267566" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1526878" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1526878-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g002-550.jpg?1732267571'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1526878-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g003-550.jpg?1732267576'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1526878-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g004-550.jpg?1732267578'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1526878-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g005-550.jpg?1732267580'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1526878-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g006-550.jpg?1732267582'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1526878-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g007-550.jpg?1732267585'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1526878-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g008-550.jpg?1732267587'><p>Figure 8</p></div></script></div></div><div id="article-1526878-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g001-550.jpg?1732267566" title=" <strong>Figure 1</strong><br/> <p>Overview of the proposed MSTrans BE framework.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4610'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g002-550.jpg?1732267571" title=" <strong>Figure 2</strong><br/> <p>The architecture of the MST module.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4610'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g003-550.jpg?1732267576" title=" <strong>Figure 3</strong><br/> <p>Dataset presentations: (<b>a</b>) WHU-CD dataset; (<b>b</b>) LEVIR-CD dataset; (<b>c</b>) GZ-CD dataset.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4610'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g004-550.jpg?1732267578" title=" <strong>Figure 4</strong><br/> <p>The BE maps of different methods on the Massachusetts dataset: (<b>a</b>) image, (<b>b</b>) label, (<b>c</b>) U-Net [<a href="#B20-electronics-13-04610" class="html-bibr">20</a>], (<b>d</b>) SiU-Net [<a href="#B23-electronics-13-04610" class="html-bibr">23</a>], (<b>e</b>) Res2Unet [<a href="#B24-electronics-13-04610" class="html-bibr">24</a>], (<b>f</b>) CFENet [<a href="#B31-electronics-13-04610" class="html-bibr">31</a>], (<b>g</b>) CBRNet [<a href="#B32-electronics-13-04610" class="html-bibr">32</a>], (<b>h</b>) BBRNet [<a href="#B28-electronics-13-04610" class="html-bibr">28</a>], (<b>i</b>) AGPNet [<a href="#B29-electronics-13-04610" class="html-bibr">29</a>], and (<b>j</b>) proposed MSTrans.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4610'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g005-550.jpg?1732267580" title=" <strong>Figure 5</strong><br/> <p>The BE maps of different methods on the EastAsia dataset: (<b>a</b>) image, (<b>b</b>) label, (<b>c</b>) U-Net [<a href="#B20-electronics-13-04610" class="html-bibr">20</a>], (<b>d</b>) SiU-Net [<a href="#B23-electronics-13-04610" class="html-bibr">23</a>], (<b>e</b>) Res2Unet [<a href="#B24-electronics-13-04610" class="html-bibr">24</a>], (<b>f</b>) CFENet [<a href="#B31-electronics-13-04610" class="html-bibr">31</a>], (<b>g</b>) CBRNet [<a href="#B32-electronics-13-04610" class="html-bibr">32</a>], (<b>h</b>) BBRNet [<a href="#B28-electronics-13-04610" class="html-bibr">28</a>], (<b>i</b>) AGPNet [<a href="#B29-electronics-13-04610" class="html-bibr">29</a>], and (<b>j</b>) proposed MSTrans.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4610'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g006-550.jpg?1732267582" title=" <strong>Figure 6</strong><br/> <p>The BE maps of different methods on the Inria dataset: (<b>a</b>) image, (<b>b</b>) label, (<b>c</b>) U-Net [<a href="#B20-electronics-13-04610" class="html-bibr">20</a>], (<b>d</b>) SiU-Net [<a href="#B23-electronics-13-04610" class="html-bibr">23</a>], (<b>e</b>) Res2Unet [<a href="#B24-electronics-13-04610" class="html-bibr">24</a>], (<b>f</b>) CFENet [<a href="#B31-electronics-13-04610" class="html-bibr">31</a>], (<b>g</b>) CBRNet [<a href="#B32-electronics-13-04610" class="html-bibr">32</a>], (<b>h</b>) BBRNet [<a href="#B28-electronics-13-04610" class="html-bibr">28</a>], (<b>i</b>) AGPNet [<a href="#B29-electronics-13-04610" class="html-bibr">29</a>], and (<b>j</b>) proposed MSTrans.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4610'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g007-550.jpg?1732267585" title=" <strong>Figure 7</strong><br/> <p>The BE maps of different submodule combinations on the Massachusetts dataset for ablation studies.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4610'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04610/article_deploy/html/images/electronics-13-04610-g008-550.jpg?1732267587" title=" <strong>Figure 8</strong><br/> <p>The visual feature heatmaps of the proposed MSTrans on different submodules.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4610'>Full article</a></strong> "></a></div> </div> </div> </div> <div class="expanding-div collapsed"> <div class="generic-item article-item"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 16 pages, 1109 KiB   </span> <a href="/2079-9292/13/23/4609/pdf?version=1732269892" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="A Receiver-Driven Named Data Networking (NDN) Congestion Control Method Based on Reinforcement Learning" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/23/4609">A Receiver-Driven Named Data Networking (NDN) Congestion Control Method Based on Reinforcement Learning</a> <div class="authors"> by <span class="inlineblock "><strong>Ruijuan Zheng</strong>, </span><span class="inlineblock "><strong>Bohan Zhang</strong>, </span><span class="inlineblock "><strong>Xuhui Zhao</strong>, </span><span class="inlineblock "><strong>Lin Wang</strong> and </span><span class="inlineblock "><strong>Qingtao Wu</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(23), 4609; <a href="https://doi.org/10.3390/electronics13234609">https://doi.org/10.3390/electronics13234609</a> - 22 Nov 2024 </div> <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Named data networking (NDN) is a novel networking paradigm characterized by in-network caching, receiver-driven communication, and multi-source, multi-path data retrieval, which poses new challenges for congestion control. Existing work has largely focused on receiver-driven mechanisms. Due to delays in obtaining network control information <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4609/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Named data networking (NDN) is a novel networking paradigm characterized by in-network caching, receiver-driven communication, and multi-source, multi-path data retrieval, which poses new challenges for congestion control. Existing work has largely focused on receiver-driven mechanisms. Due to delays in obtaining network control information (timeouts, NACKs) within NDN, consumers are unable to access the network congestion status from this information in a timely manner. To address the issues above, this paper combines the Q-learning algorithm with the NDN architecture, proposing Q-NDN. In Q-NDN, consumers can dynamically adjust the congestion window (cwnd) through the real-time monitoring of network status, leveraging the Q-learning algorithm, achieving automatic congestion control for the NDN architecture. Additionally, this paper introduces content popularity-based traffic scheduling for multi-user scenarioswhich adjusts the transmission rates of content with different popularity levels to maintain a dynamic balance in the network. The experimental results show that Q-NDN can converge quickly, make full use of bandwidth resources, and keep the packet loss rate to 0 in the basic network topology. In competing network topologies, Q-NDN can rapidly address conflict issues, efficiently utilize bandwidth resources, and maintain a relatively low packet loss rate. <a href="/2079-9292/13/23/4609">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/23/4609/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1526976"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1526976"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1526976" data-cycle-prev="#prev1526976" data-cycle-progressive="#images1526976" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1526976-popup'><span class="helper"></span><img 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src='https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g004-550.jpg?1732270037'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1526976-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g005-550.jpg?1732270038'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1526976-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g006-550.jpg?1732270039'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1526976-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g007-550.jpg?1732270040'><p>Figure 7</p></div></script></div></div><div id="article-1526976-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g001-550.jpg?1732270033" title=" <strong>Figure 1</strong><br/> <p>Architecture of Q-NDN.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4609'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g002-550.jpg?1732270035" title=" <strong>Figure 2</strong><br/> <p>Basic functionality of the sliding window.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4609'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g003-550.jpg?1732270037" title=" <strong>Figure 3</strong><br/> <p>Q-NDN algorithm process.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4609'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g004-550.jpg?1732270037" title=" <strong>Figure 4</strong><br/> <p>Basic network topology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4609'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g005-550.jpg?1732270038" title=" <strong>Figure 5</strong><br/> <p>Competitive network topology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4609'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g006-550.jpg?1732270039" title=" <strong>Figure 6</strong><br/> <p>Experimental results for basic network topology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4609'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04609/article_deploy/html/images/electronics-13-04609-g007-550.jpg?1732270040" title=" <strong>Figure 7</strong><br/> <p>Experimental results for competitive network topology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/23/4609'>Full article</a></strong> "></a></div> </div> </div> </div> </div> <div class="generic-item last-item"> <a class="bold" 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Electronics | An Open Access Journal from MDPI