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detection</title> <meta name="description" content="Search results for: small target detection"> <meta name="keywords" content="small target detection"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="small target detection"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 10322</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: small target detection</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10322</span> Biologically Inspired Small Infrared Target Detection Using Local Contrast Mechanisms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tian%20Xia">Tian Xia</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuan%20Yan%20Tang"> Yuan Yan Tang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=small%20target%20detection" title="small target detection">small target detection</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20contrast" title=" local contrast"> local contrast</a>, <a href="https://publications.waset.org/abstracts/search?q=human%20vision%20system" title=" human vision system"> human vision system</a>, <a href="https://publications.waset.org/abstracts/search?q=Laplacian%20of%20Gaussian" title=" Laplacian of Gaussian"> Laplacian of Gaussian</a> </p> <a href="https://publications.waset.org/abstracts/19199/biologically-inspired-small-infrared-target-detection-using-local-contrast-mechanisms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19199.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">469</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10321</span> YOLO-IR: Infrared Small Object Detection in High Noise Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yufeng%20Li">Yufeng Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Yinan%20Ma"> Yinan Ma</a>, <a href="https://publications.waset.org/abstracts/search?q=Jing%20Wu"> Jing Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Chengnian%20Long"> Chengnian Long</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=infrared%20small%20target%20detection" title="infrared small target detection">infrared small target detection</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20noise" title=" high noise"> high noise</a>, <a href="https://publications.waset.org/abstracts/search?q=robustness" title=" robustness"> robustness</a>, <a href="https://publications.waset.org/abstracts/search?q=soft-threshold%20coordinate%20attention" title=" soft-threshold coordinate attention"> soft-threshold coordinate attention</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20fusion" title=" feature fusion"> feature fusion</a> </p> <a href="https://publications.waset.org/abstracts/180574/yolo-ir-infrared-small-object-detection-in-high-noise-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/180574.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10320</span> Small Target Recognition Based on Trajectory Information</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saad%20Alkentar">Saad Alkentar</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulkareem%20Assalem"> Abdulkareem Assalem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=small%20targets" title="small targets">small targets</a>, <a href="https://publications.waset.org/abstracts/search?q=drones" title=" drones"> drones</a>, <a href="https://publications.waset.org/abstracts/search?q=trajectory%20information" title=" trajectory information"> trajectory information</a>, <a href="https://publications.waset.org/abstracts/search?q=TBD" title=" TBD"> TBD</a>, <a href="https://publications.waset.org/abstracts/search?q=multivariate%20time%20series" title=" multivariate time series"> multivariate time series</a> </p> <a href="https://publications.waset.org/abstracts/184545/small-target-recognition-based-on-trajectory-information" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184545.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">47</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10319</span> Sensing Mechanism of Nano-Toxic Ions Using Quartz Crystal Microbalance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chanho%20Park">Chanho Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Juneseok%20You"> Juneseok You</a>, <a href="https://publications.waset.org/abstracts/search?q=Kuewhan%20Jang"> Kuewhan Jang</a>, <a href="https://publications.waset.org/abstracts/search?q=Sungsoo%20Na"> Sungsoo Na</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Detection technique of nanotoxic materials is strongly imperative, because nano-toxic materials can harmfully influence human health and environment as their engineering applications are growing rapidly in recent years. In present work, we report the DNA immobilized quartz crystal microbalance (QCM) based sensor for detection of nano-toxic materials such as silver ions, Hg2+ etc. by using functionalization of quartz crystal with a target-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz crystal is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated fast and in situ detection of nanotoxic materials using quartz crystal microbalance. We report the label-free and highly sensitive detection of silver ion for present case, which is a typical nano-toxic material by using QCM and silver-specific DNA. The detection is based on the measurement of frequency shift of Quartz crystal from constitution of the cytosine-Ag+-cytosine binding. It is shown that the silver-specific DNA measured frequency shift by QCM enables the capturing of silver ions below 100pM. The results suggest that DNA-based detection opens a new avenue for the development of a practical water-testing sensor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nano-toxic%20ions" title="nano-toxic ions">nano-toxic ions</a>, <a href="https://publications.waset.org/abstracts/search?q=quartz%20crystal%20microbalance" title=" quartz crystal microbalance"> quartz crystal microbalance</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20shift" title=" frequency shift"> frequency shift</a>, <a href="https://publications.waset.org/abstracts/search?q=target-specific%20DNA" title=" target-specific DNA"> target-specific DNA</a> </p> <a href="https://publications.waset.org/abstracts/69750/sensing-mechanism-of-nano-toxic-ions-using-quartz-crystal-microbalance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69750.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">321</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10318</span> Analysis Of Non-uniform Characteristics Of Small Underwater Targets Based On Clustering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tianyang%20Xu">Tianyang Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Small underwater targets generally have a non-centrosymmetric geometry, and the acoustic scattering field of the target has spatial inhomogeneity under active sonar detection conditions. In view of the above problems, this paper takes the hemispherical cylindrical shell as the research object, and considers the angle continuity implied in the echo characteristics, and proposes a cluster-driven research method for the non-uniform characteristics of target echo angle. First, the target echo features are extracted, and feature vectors are constructed. Secondly, the t-SNE algorithm is used to improve the internal connection of the feature vector in the low-dimensional feature space and to construct the visual feature space. Finally, the implicit angular relationship between echo features is extracted under unsupervised condition by cluster analysis. The reconstruction results of the local geometric structure of the target corresponding to different categories show that the method can effectively divide the angle interval of the local structure of the target according to the natural acoustic scattering characteristics of the target. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=underwater%20target%3B" title="underwater target;">underwater target;</a>, <a href="https://publications.waset.org/abstracts/search?q=non-uniform%20characteristics%3B" title=" non-uniform characteristics;"> non-uniform characteristics;</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster-driven%20method%3B" title=" cluster-driven method;"> cluster-driven method;</a>, <a href="https://publications.waset.org/abstracts/search?q=acoustic%20scattering%20characteristics" title=" acoustic scattering characteristics"> acoustic scattering characteristics</a> </p> <a href="https://publications.waset.org/abstracts/169602/analysis-of-non-uniform-characteristics-of-small-underwater-targets-based-on-clustering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169602.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">132</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10317</span> Automatic Vowel and Consonant's Target Formant Frequency Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Othmane%20Bouferroum">Othmane Bouferroum</a>, <a href="https://publications.waset.org/abstracts/search?q=Malika%20Boudraa"> Malika Boudraa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a dual exponential model for CV formant transition is derived from locus theory of speech perception. Then, an algorithm for automatic vowel and consonant’s target formant frequency detection is developed and tested on real speech. The results show that vowels and consonants are detected through transitions rather than their small stable portions. Also, vowel reduction is clearly observed in our data. These results are confirmed by the observations made in perceptual experiments in the literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acoustic%20invariance" title="acoustic invariance">acoustic invariance</a>, <a href="https://publications.waset.org/abstracts/search?q=coarticulation" title=" coarticulation"> coarticulation</a>, <a href="https://publications.waset.org/abstracts/search?q=formant%20transition" title=" formant transition"> formant transition</a>, <a href="https://publications.waset.org/abstracts/search?q=locus%20equation" title=" locus equation"> locus equation</a> </p> <a href="https://publications.waset.org/abstracts/58408/automatic-vowel-and-consonants-target-formant-frequency-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58408.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">271</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10316</span> Detection of Nanotoxic Material Using DNA Based QCM</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Juneseok%20You">Juneseok You</a>, <a href="https://publications.waset.org/abstracts/search?q=Chanho%20Park"> Chanho Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Kuehwan%20Jang"> Kuehwan Jang</a>, <a href="https://publications.waset.org/abstracts/search?q=Sungsoo%20Na"> Sungsoo Na</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sensing of nanotoxic materials is strongly important, as their engineering applications are growing recently and results in that nanotoxic material can harmfully influence human health and environment. In current study we report the quartz crystal microbalance (QCM)-based, in situ and real-time sensing of nanotoxic-material by frequency shift. We propose the in situ detection of nanotoxic material of zinc oxice by using QCM functionalized with a taget-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz electrode is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated the in-situ and fast detection of zinc oxide using the quartz crystal microbalance (QCM). The detection was derived from the DNA hybridization between the DNA on the quartz electrode. The results suggest that QCM-based detection opens a new avenue for the development of a practical water-testing sensor. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nanotoxic%20material" title="nanotoxic material">nanotoxic material</a>, <a href="https://publications.waset.org/abstracts/search?q=qcm" title=" qcm"> qcm</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency" title=" frequency"> frequency</a>, <a href="https://publications.waset.org/abstracts/search?q=in%20situ%20sensing" title=" in situ sensing"> in situ sensing</a> </p> <a href="https://publications.waset.org/abstracts/41494/detection-of-nanotoxic-material-using-dna-based-qcm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41494.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">422</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10315</span> An Optimal Matching Design Method of Space-Based Optical Payload for Typical Aerial Target Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yin%20Zhang">Yin Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Kai%20Qiao"> Kai Qiao</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiyang%20Zhi"> Xiyang Zhi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinnan%20Gong"> Jinnan Gong</a>, <a href="https://publications.waset.org/abstracts/search?q=Jianming%20Hu"> Jianming Hu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to effectively detect aerial targets over long distances, an optimal matching design method of space-based optical payload is proposed. Firstly, main factors affecting optical detectability of small targets under complex environment are analyzed based on the full link of a detection system, including band center, band width and spatial resolution. Then a performance characterization model representing the relationship between image signal-to-noise ratio (SCR) and the above influencing factors is established to describe a detection system. Finally, an optimal matching design example is demonstrated for a typical aerial target by simulating and analyzing its SCR under different scene clutter coupling with multi-scale characteristics, and the optimized detection band and spatial resolution are presented. The method can provide theoretical basis and scientific guidance for space-based detection system design, payload specification demonstration and information processing algorithm optimization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=space-based%20detection" title="space-based detection">space-based detection</a>, <a href="https://publications.waset.org/abstracts/search?q=aerial%20targets" title=" aerial targets"> aerial targets</a>, <a href="https://publications.waset.org/abstracts/search?q=optical%20system%20design" title=" optical system design"> optical system design</a>, <a href="https://publications.waset.org/abstracts/search?q=detectability%20characterization" title=" detectability characterization"> detectability characterization</a> </p> <a href="https://publications.waset.org/abstracts/107378/an-optimal-matching-design-method-of-space-based-optical-payload-for-typical-aerial-target-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/107378.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">168</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10314</span> Adaptive Target Detection of High-Range-Resolution Radar in Non-Gaussian Clutter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lina%20Pan">Lina Pan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In non-Gaussian clutter of a spherically invariant random vector, in the cases that a certain estimated covariance matrix could become singular, the adaptive target detection of high-range-resolution radar is addressed. Firstly, the restricted maximum likelihood (RML) estimates of unknown covariance matrix and scatterer amplitudes are derived for non-Gaussian clutter. And then the RML estimate of texture is obtained. Finally, a novel detector is devised. It is showed that, without secondary data, the proposed detector outperforms the existing Kelly binary integrator. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=non-Gaussian%20clutter" title="non-Gaussian clutter">non-Gaussian clutter</a>, <a href="https://publications.waset.org/abstracts/search?q=covariance%20matrix%20estimation" title=" covariance matrix estimation"> covariance matrix estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20detection" title=" target detection"> target detection</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood" title=" maximum likelihood"> maximum likelihood</a> </p> <a href="https://publications.waset.org/abstracts/24879/adaptive-target-detection-of-high-range-resolution-radar-in-non-gaussian-clutter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24879.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">464</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10313</span> Crater Detection Using PCA from Captured CMOS Camera Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tatsuya%20Takino">Tatsuya Takino</a>, <a href="https://publications.waset.org/abstracts/search?q=Izuru%20Nomura"> Izuru Nomura</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuji%20Kageyama"> Yuji Kageyama</a>, <a href="https://publications.waset.org/abstracts/search?q=Shin%20Nagata"> Shin Nagata</a>, <a href="https://publications.waset.org/abstracts/search?q=Hiroyuki%20Kamata"> Hiroyuki Kamata</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose a method of detecting the craters from the image of the lunar surface. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) working group aiming at the pinpoint landing on the lunar surface and investigating scientific research. It is difficult to equip and use high-performance computers for the small space probe. So, it is necessary to use a small computer with an exclusive hardware such as FPGA. We have studied the crater detection using principal component analysis (PCA), In this paper, We implement detection algorithm into the FPGA, and the detection is performed on the data that was captured from the CMOS camera. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=crater%20detection" title="crater detection">crater detection</a>, <a href="https://publications.waset.org/abstracts/search?q=PCA" title=" PCA"> PCA</a>, <a href="https://publications.waset.org/abstracts/search?q=FPGA" title=" FPGA"> FPGA</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20processing" title=" image processing"> image processing</a> </p> <a href="https://publications.waset.org/abstracts/19003/crater-detection-using-pca-from-captured-cmos-camera-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19003.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">550</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10312</span> Efficient Ground Targets Detection Using Compressive Sensing in Ground-Based Synthetic-Aperture Radar (SAR) Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gherbi%20Nabil">Gherbi Nabil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compressive%20sensing" title="compressive sensing">compressive sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=raw%20complex%20data" title=" raw complex data"> raw complex data</a>, <a href="https://publications.waset.org/abstracts/search?q=synthetic%20aperture%20radar" title=" synthetic aperture radar"> synthetic aperture radar</a>, <a href="https://publications.waset.org/abstracts/search?q=ADMM" title=" ADMM"> ADMM</a> </p> <a href="https://publications.waset.org/abstracts/191958/efficient-ground-targets-detection-using-compressive-sensing-in-ground-based-synthetic-aperture-radar-sar-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191958.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">19</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10311</span> mKDNAD: A Network Flow Anomaly Detection Method Based On Multi-teacher Knowledge Distillation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yang%20Yang">Yang Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Dan%20Liu"> Dan Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network%20flow%20anomaly%20detection%20%28NAD%29" title="network flow anomaly detection (NAD)">network flow anomaly detection (NAD)</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-teacher%20knowledge%20distillation" title=" multi-teacher knowledge distillation"> multi-teacher knowledge distillation</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a> </p> <a href="https://publications.waset.org/abstracts/156811/mkdnad-a-network-flow-anomaly-detection-method-based-on-multi-teacher-knowledge-distillation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/156811.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">122</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10310</span> An Improved Two-dimensional Ordered Statistical Constant False Alarm Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Weihao%20Wang">Weihao Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhulin%20Zong"> Zhulin Zong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Two-dimensional ordered statistical constant false alarm detection is a widely used method for detecting weak target signals in radar signal processing applications. The method is based on analyzing the statistical characteristics of the noise and clutter present in the radar signal and then using this information to set an appropriate detection threshold. In this approach, the reference cell of the unit to be detected is divided into several reference subunits. These subunits are used to estimate the noise level and adjust the detection threshold, with the aim of minimizing the false alarm rate. By using an ordered statistical approach, the method is able to effectively suppress the influence of clutter and noise, resulting in a low false alarm rate. The detection process involves a number of steps, including filtering the input radar signal to remove any noise or clutter, estimating the noise level based on the statistical characteristics of the reference subunits, and finally, setting the detection threshold based on the estimated noise level. One of the main advantages of two-dimensional ordered statistical constant false alarm detection is its ability to detect weak target signals in the presence of strong clutter and noise. This is achieved by carefully analyzing the statistical properties of the signal and using an ordered statistical approach to estimate the noise level and adjust the detection threshold. In conclusion, two-dimensional ordered statistical constant false alarm detection is a powerful technique for detecting weak target signals in radar signal processing applications. By dividing the reference cell into several subunits and using an ordered statistical approach to estimate the noise level and adjust the detection threshold, this method is able to effectively suppress the influence of clutter and noise and maintain a low false alarm rate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=two-dimensional" title="two-dimensional">two-dimensional</a>, <a href="https://publications.waset.org/abstracts/search?q=ordered%20statistical" title=" ordered statistical"> ordered statistical</a>, <a href="https://publications.waset.org/abstracts/search?q=constant%20false%20alarm" title=" constant false alarm"> constant false alarm</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a>, <a href="https://publications.waset.org/abstracts/search?q=weak%20target%20signals" title=" weak target signals"> weak target signals</a> </p> <a href="https://publications.waset.org/abstracts/163351/an-improved-two-dimensional-ordered-statistical-constant-false-alarm-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163351.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">78</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10309</span> OFDM Radar for High Accuracy Target Tracking</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahbube%20Eghtesad">Mahbube Eghtesad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For a number of years, the problem of simultaneous detection and tracking of a target has been one of the most relevant and challenging issues in a wide variety of military and civilian systems. We develop methods for detecting and tracking a target using an orthogonal frequency division multiplexing (OFDM) based radar. As a preliminary step we introduce the target trajectory and Gaussian noise model in discrete time form. Then resorting to match filter and Kalman filter we derive a detector and target tracker. After that we propose an OFDM radar in order to achieve further improvement in tracking performance. The motivation for employing multiple frequencies is that the different scattering centers of a target resonate differently at each frequency. Numerical examples illustrate our analytical results, demonstrating the achieved performance improvement due to the OFDM signaling method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=matched%20filter" title="matched filter">matched filter</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20trashing" title=" target trashing"> target trashing</a>, <a href="https://publications.waset.org/abstracts/search?q=OFDM%20radar" title=" OFDM radar"> OFDM radar</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a> </p> <a href="https://publications.waset.org/abstracts/8926/ofdm-radar-for-high-accuracy-target-tracking" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8926.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">398</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10308</span> Signal Amplification Using Graphene Oxide in Label Free Biosensor for Pathogen Detection </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Agampodi%20Promoda%20Perera">Agampodi Promoda Perera</a>, <a href="https://publications.waset.org/abstracts/search?q=Yong%20Shin"> Yong Shin</a>, <a href="https://publications.waset.org/abstracts/search?q=Mi%20Kyoung%20Park"> Mi Kyoung Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The successful detection of pathogenic bacteria in blood provides important information for early detection, diagnosis and the prevention and treatment of infectious diseases. Silicon microring resonators are refractive-index-based optical biosensors that provide highly sensitive, label-free, real-time multiplexed detection of biomolecules. We demonstrate the technique of using GO (graphene oxide) to enhance the signal output of the silicon microring optical sensor. The activated carboxylic groups in GO molecules bind directly to single stranded DNA with an amino modified 5’ end. This conjugation amplifies the shift in resonant wavelength in a real-time manner. We designed a capture probe for strain Staphylococcus aureus of 21 bp and a longer complementary target sequence of 70 bp. The mismatched target sequence we used was of Streptococcus agalactiae of 70 bp. GO is added after the complementary binding of the probe and target. GO conjugates to the unbound single stranded segment of the target and increase the wavelength shift on the silicon microring resonator. Furthermore, our results show that GO could successfully differentiate between the mismatched DNA sequences from the complementary DNA sequence. Therefore, the proposed concept could effectively enhance sensitivity of pathogen detection sensors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=label%20free%20biosensor" title="label free biosensor">label free biosensor</a>, <a href="https://publications.waset.org/abstracts/search?q=pathogenic%20bacteria" title=" pathogenic bacteria"> pathogenic bacteria</a>, <a href="https://publications.waset.org/abstracts/search?q=graphene%20oxide" title=" graphene oxide"> graphene oxide</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnosis" title=" diagnosis"> diagnosis</a> </p> <a href="https://publications.waset.org/abstracts/12619/signal-amplification-using-graphene-oxide-in-label-free-biosensor-for-pathogen-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12619.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">467</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10307</span> Anthraquinone Labelled DNA for Direct Detection and Discrimination of Closely Related DNA Targets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sarah%20A.%20Goodchild">Sarah A. Goodchild</a>, <a href="https://publications.waset.org/abstracts/search?q=Rachel%20Gao"> Rachel Gao</a>, <a href="https://publications.waset.org/abstracts/search?q=Philip%20N.%20Bartlett"> Philip N. Bartlett</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A novel detection approach using immobilized DNA probes labeled with Anthraquinone (AQ) as an electrochemically active reporter moiety has been successfully developed as a new, simple, reliable method for the detection of DNA. This method represents a step forward in DNA detection as it can discriminate between multiple nucleotide polymorphisms within target DNA strands without the need for any additional reagents, reporters or processes such as melting of DNA strands. The detection approach utilizes single-stranded DNA probes immobilized on gold surfaces labeled at the distal terminus with AQ. The effective immobilization has been monitored using techniques such as AC impedance and Raman spectroscopy. Simple voltammetry techniques (Differential Pulse Voltammetry, Cyclic Voltammetry) are then used to monitor the reduction potential of the AQ before and after the addition of complementary strand of target DNA. A reliable relationship between the shift in reduction potential and the number of base pair mismatch has been established and can be used to discriminate between DNA from highly related pathogenic organisms of clinical importance. This indicates that this approach may have great potential to be exploited within biosensor kits for detection and diagnosis of pathogenic organisms in Point of Care devices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anthraquinone" title="Anthraquinone">Anthraquinone</a>, <a href="https://publications.waset.org/abstracts/search?q=discrimination" title=" discrimination"> discrimination</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA%20detection" title=" DNA detection"> DNA detection</a>, <a href="https://publications.waset.org/abstracts/search?q=electrochemical%20biosensor" title=" electrochemical biosensor "> electrochemical biosensor </a> </p> <a href="https://publications.waset.org/abstracts/30840/anthraquinone-labelled-dna-for-direct-detection-and-discrimination-of-closely-related-dna-targets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30840.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">393</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10306</span> OFDM Radar for Detecting a Rayleigh Fluctuating Target in Gaussian Noise</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahboobeh%20Eghtesad">Mahboobeh Eghtesad</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20Mohseni"> Reza Mohseni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We develop methods for detecting a target for orthogonal frequency division multiplexing (OFDM) based radars. As a preliminary step we introduce the target and Gaussian noise models in discrete–time form. Then, resorting to match filter (MF) we derive a detector for two different scenarios: a non-fluctuating target and a Rayleigh fluctuating target. It will be shown that a MF is not suitable for Rayleigh fluctuating targets. In this paper we propose a reduced-complexity method based on fast Fourier transfrom (FFT) for such a situation. The proposed method has better detection performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=constant%20false%20alarm%20rate%20%28CFAR%29" title="constant false alarm rate (CFAR)">constant false alarm rate (CFAR)</a>, <a href="https://publications.waset.org/abstracts/search?q=match%20filter%20%28MF%29" title=" match filter (MF)"> match filter (MF)</a>, <a href="https://publications.waset.org/abstracts/search?q=fast%20Fourier%20transform%20%28FFT%29" title=" fast Fourier transform (FFT)"> fast Fourier transform (FFT)</a>, <a href="https://publications.waset.org/abstracts/search?q=OFDM%20radars" title=" OFDM radars"> OFDM radars</a>, <a href="https://publications.waset.org/abstracts/search?q=Rayleigh%20fluctuating%20target" title=" Rayleigh fluctuating target"> Rayleigh fluctuating target</a> </p> <a href="https://publications.waset.org/abstracts/5922/ofdm-radar-for-detecting-a-rayleigh-fluctuating-target-in-gaussian-noise" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5922.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">358</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10305</span> Detectability Analysis of Typical Aerial Targets from Space-Based Platforms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yin%20Zhang">Yin Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Kai%20Qiao"> Kai Qiao</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiyang%20Zhi"> Xiyang Zhi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinnan%20Gong"> Jinnan Gong</a>, <a href="https://publications.waset.org/abstracts/search?q=Jianming%20Hu"> Jianming Hu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to achieve effective detection of aerial targets over long distances from space-based platforms, the mechanism of interaction between the radiation characteristics of the aerial targets and the complex scene environment including the sunlight conditions, underlying surfaces and the atmosphere are analyzed. A large simulated database of space-based radiance images is constructed considering several typical aerial targets, target working modes (flight velocity and altitude), illumination and observation angles, background types (cloud, ocean, and urban areas) and sensor spectrums ranging from visible to thermal infrared. The target detectability is characterized by the signal-to-clutter ratio (SCR) extracted from the images. The influence laws of the target detectability are discussed under different detection bands and instantaneous fields of view (IFOV). Furthermore, the optimal center wavelengths and widths of the detection bands are suggested, and the minimum IFOV requirements are proposed. The research can provide theoretical support and scientific guidance for the design of space-based detection systems and on-board information processing algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=space-based%20detection" title="space-based detection">space-based detection</a>, <a href="https://publications.waset.org/abstracts/search?q=aerial%20targets" title=" aerial targets"> aerial targets</a>, <a href="https://publications.waset.org/abstracts/search?q=detectability%20analysis" title=" detectability analysis"> detectability analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=scene%20environment" title=" scene environment"> scene environment</a> </p> <a href="https://publications.waset.org/abstracts/97443/detectability-analysis-of-typical-aerial-targets-from-space-based-platforms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97443.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">144</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10304</span> Design and Fabrication of Optical Nanobiosensors for Detection of MicroRNAs Involved in Neurodegenerative Diseases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahdi%20Rahaie">Mahdi Rahaie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> MicroRNAs are a novel class of small RNAs which regulate gene expression by translational repression or degradation of messenger RNAs. To produce sensitive, simple and cost-effective assays for microRNAs, detection is in urgent demand due to important role of these biomolecules in progression of human disease such as Alzheimer’s, Multiple sclerosis, and some other neurodegenerative diseases. Herein, we report several novel, sensitive and specific microRNA nanobiosensors which were designed based on colorimetric and fluorescence detection of nanoparticles and hybridization chain reaction amplification as an enzyme-free amplification. These new strategies eliminate the need for enzymatic reactions, chemical changes, separation processes and sophisticated equipment whereas less limit of detection with most specify are acceptable. The important features of these methods are high sensitivity and specificity to differentiate between perfectly matched, mismatched and non-complementary target microRNAs and also decent response in the real sample analysis with blood plasma. These nanobiosensors can clinically be used not only for the early detection of neuro diseases but also for every sickness related to miRNAs by direct detection of the plasma microRNAs in real clinical samples, without a need for sample preparation, RNA extraction and/or amplification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hybridization%20chain%20reaction" title="hybridization chain reaction">hybridization chain reaction</a>, <a href="https://publications.waset.org/abstracts/search?q=microRNA" title=" microRNA"> microRNA</a>, <a href="https://publications.waset.org/abstracts/search?q=nanobiosensor" title=" nanobiosensor"> nanobiosensor</a>, <a href="https://publications.waset.org/abstracts/search?q=neurodegenerative%20diseases" title=" neurodegenerative diseases"> neurodegenerative diseases</a> </p> <a href="https://publications.waset.org/abstracts/96000/design-and-fabrication-of-optical-nanobiosensors-for-detection-of-micrornas-involved-in-neurodegenerative-diseases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/96000.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">151</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10303</span> Toward Subtle Change Detection and Quantification in Magnetic Resonance Neuroimaging</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Esmaeilpour">Mohammad Esmaeilpour</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the important open problems in the field of medical image processing is detection and quantification of small changes. In this poster, we try to investigate that, how the algebraic decomposition techniques can be used for semiautomatically detecting and quantifying subtle changes in Magnetic Resonance (MR) neuroimaging volumes. We mostly focus on the low-rank values of the matrices achieved from decomposing MR image pairs during a period of time. Besides, a skillful neuroradiologist will help the algorithm to distinguish between noises and small changes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=magnetic%20resonance%20neuroimaging" title="magnetic resonance neuroimaging">magnetic resonance neuroimaging</a>, <a href="https://publications.waset.org/abstracts/search?q=subtle%20change%20detection%20and%20quantification" title=" subtle change detection and quantification"> subtle change detection and quantification</a>, <a href="https://publications.waset.org/abstracts/search?q=algebraic%20decomposition" title=" algebraic decomposition"> algebraic decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=basis%20functions" title=" basis functions"> basis functions</a> </p> <a href="https://publications.waset.org/abstracts/32372/toward-subtle-change-detection-and-quantification-in-magnetic-resonance-neuroimaging" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32372.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">474</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10302</span> Suggestion for Malware Detection Agent Considering Network Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ji-Hoon%20Hong">Ji-Hoon Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Dong-Hee%20Kim"> Dong-Hee Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Nam-Uk%20Kim"> Nam-Uk Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Tai-Myoung%20Chung"> Tai-Myoung Chung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=android%20malware%20detection" title="android malware detection">android malware detection</a>, <a href="https://publications.waset.org/abstracts/search?q=software-defined%20network" title=" software-defined network"> software-defined network</a>, <a href="https://publications.waset.org/abstracts/search?q=interaction%20environment" title=" interaction environment"> interaction environment</a>, <a href="https://publications.waset.org/abstracts/search?q=android%20malware%20detection" title=" android malware detection"> android malware detection</a>, <a href="https://publications.waset.org/abstracts/search?q=software-defined%20network" title=" software-defined network"> software-defined network</a>, <a href="https://publications.waset.org/abstracts/search?q=interaction%20environment" title=" interaction environment"> interaction environment</a> </p> <a href="https://publications.waset.org/abstracts/39330/suggestion-for-malware-detection-agent-considering-network-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39330.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">433</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10301</span> An Electrochemical DNA Biosensor Based on Oracet Blue as a Label for Detection of Helicobacter pylori </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeedeh%20Hajihosseini">Saeedeh Hajihosseini</a>, <a href="https://publications.waset.org/abstracts/search?q=Zahra%20Aghili"> Zahra Aghili</a>, <a href="https://publications.waset.org/abstracts/search?q=Navid%20Nasirizadeh"> Navid Nasirizadeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An innovative method of a DNA electrochemical biosensor based on Oracet Blue (OB) as an electroactive label and gold electrode (AuE) for detection of Helicobacter pylori, was offered. A single–stranded DNA probe with a thiol modification was covalently immobilized on the surface of the AuE by forming an Au–S bond. Differential pulse voltammetry (DPV) was used to monitor DNA hybridization by measuring the electrochemical signals of reduction of the OB binding to double– stranded DNA (ds–DNA). Our results showed that OB–based DNA biosensor has a decent potential for detection of single–base mismatch in target DNA. Selectivity of the proposed DNA biosensor was further confirmed in the presence of non–complementary and complementary DNA strands. Under optimum conditions, the electrochemical signal had a linear relationship with the concentration of the target DNA ranging from 0.3 nmol L-1 to 240.0 nmol L-1, and the detection limit was 0.17 nmol L-1, whit a promising reproducibility and repeatability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DNA%20biosensor" title="DNA biosensor">DNA biosensor</a>, <a href="https://publications.waset.org/abstracts/search?q=oracet%20blue" title=" oracet blue"> oracet blue</a>, <a href="https://publications.waset.org/abstracts/search?q=Helicobacter%20pylori" title=" Helicobacter pylori"> Helicobacter pylori</a>, <a href="https://publications.waset.org/abstracts/search?q=electrode%20%28AuE%29" title=" electrode (AuE)"> electrode (AuE)</a> </p> <a href="https://publications.waset.org/abstracts/53867/an-electrochemical-dna-biosensor-based-on-oracet-blue-as-a-label-for-detection-of-helicobacter-pylori" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53867.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">266</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10300</span> Sensor Registration in Multi-Static Sonar Fusion Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Longxiang%20Guo">Longxiang Guo</a>, <a href="https://publications.waset.org/abstracts/search?q=Haoyan%20Hao"> Haoyan Hao</a>, <a href="https://publications.waset.org/abstracts/search?q=Xueli%20Sheng"> Xueli Sheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanjun%20Yu"> Hanjun Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jingwei%20Yin"> Jingwei Yin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20fusion" title="data fusion">data fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-static%20sonar%20detection" title=" multi-static sonar detection"> multi-static sonar detection</a>, <a href="https://publications.waset.org/abstracts/search?q=offline%20estimation" title=" offline estimation"> offline estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=sensor%20registration%20problem" title=" sensor registration problem"> sensor registration problem</a> </p> <a href="https://publications.waset.org/abstracts/103631/sensor-registration-in-multi-static-sonar-fusion-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/103631.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">169</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10299</span> A Microfluidic Biosensor for Detection of EGFR 19 Deletion Mutation Targeting Non-Small Cell Lung Cancer on Rolling Circle Amplification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ji%20Su%20Kim">Ji Su Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Bo%20Ram%20Choi"> Bo Ram Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ju%20Yeon%20Cho"> Ju Yeon Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Hyukjin%20Lee"> Hyukjin Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Epidermal growth factor receptor (EGFR) 19 deletion mutation gene is over-expressed in carcinoma patient. EGFR 19 deletion mutation is known as typical biomarker of non-small cell lung cancer (NSCLC), which one section in the coding exon 19 of EGFR is deleted. Therefore, there have been many attempts over the years to detect EGFR 19 deletion mutation for replacing conventional diagnostic method such as PCR and tissue biopsy. We developed a simple and facile detection platform based on Rolling Circle Amplification (RCA), which provides highly amplified products in isothermal amplification of the ligated DNA template. Limit of detection (~50 nM) and a faster detection time (~30 min) could be achieved by introducing RCA. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=EGFR19" title="EGFR19">EGFR19</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer" title=" cancer"> cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=diagnosis" title=" diagnosis"> diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=rolling%20circle%20amplification%20%28RCA%29" title=" rolling circle amplification (RCA)"> rolling circle amplification (RCA)</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrogel" title=" hydrogel"> hydrogel</a> </p> <a href="https://publications.waset.org/abstracts/72641/a-microfluidic-biosensor-for-detection-of-egfr-19-deletion-mutation-targeting-non-small-cell-lung-cancer-on-rolling-circle-amplification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72641.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">255</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10298</span> Cross Site Scripting (XSS) Attack and Automatic Detection Technology Research</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tao%20Feng">Tao Feng</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei-Wei%20Zhang"> Wei-Wei Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chang-Ming%20Ding"> Chang-Ming Ding</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cross-site scripting (XSS) is one of the most popular WEB Attacking methods at present, and also one of the most risky web attacks. Because of the population of JavaScript, the scene of the cross site scripting attack is also gradually expanded. However, since the web application developers tend to only focus on functional testing and lack the awareness of the XSS, which has made the on-line web projects exist many XSS vulnerabilities. In this paper, different various techniques of XSS attack are analyzed, and a method automatically to detect it is proposed. It is easy to check the results of vulnerability detection when running it as a plug-in. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=XSS" title="XSS">XSS</a>, <a href="https://publications.waset.org/abstracts/search?q=no%20target%20attack%20platform" title=" no target attack platform"> no target attack platform</a>, <a href="https://publications.waset.org/abstracts/search?q=automatic%20detection%EF%BC%8CXSS%20detection" title=" automatic detection，XSS detection"> automatic detection，XSS detection</a> </p> <a href="https://publications.waset.org/abstracts/41829/cross-site-scripting-xss-attack-and-automatic-detection-technology-research" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41829.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">403</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10297</span> Fast and Scale-Adaptive Target Tracking via PCA-SIFT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yawen%20Wang">Yawen Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Hongchang%20Chen"> Hongchang Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Shaomei%20Li"> Shaomei Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Chao%20Gao"> Chao Gao</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiangpeng%20Zhang"> Jiangpeng Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As the main challenge for target tracking is accounting for target scale change and real-time, we combine Mean-Shift and PCA-SIFT algorithm together to solve the problem. We introduce similarity comparison method to determine how the target scale changes, and taking different strategies according to different situation. For target scale getting larger will cause location error, we employ backward tracking to reduce the error. Mean-Shift algorithm has poor performance when tracking scale-changing target due to the fixed bandwidth of its kernel function. In order to overcome this problem, we introduce PCA-SIFT matching. Through key point matching between target and template, that adjusting the scale of tracking window adaptively can be achieved. Because this algorithm is sensitive to wrong match, we introduce RANSAC to reduce mismatch as far as possible. Furthermore target relocating will trigger when number of match is too small. In addition we take comprehensive consideration about target deformation and error accumulation to put forward a new template update method. Experiments on five image sequences and comparison with 6 kinds of other algorithm demonstrate favorable performance of the proposed tracking algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=target%20tracking" title="target tracking">target tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=PCA-SIFT" title=" PCA-SIFT"> PCA-SIFT</a>, <a href="https://publications.waset.org/abstracts/search?q=mean-shift" title=" mean-shift"> mean-shift</a>, <a href="https://publications.waset.org/abstracts/search?q=scale-adaptive" title=" scale-adaptive"> scale-adaptive</a> </p> <a href="https://publications.waset.org/abstracts/19009/fast-and-scale-adaptive-target-tracking-via-pca-sift" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19009.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">433</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10296</span> Bayesian Prospective Detection of Small Area Health Anomalies Using Kullback Leibler Divergence </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chawarat%20Rotejanaprasert">Chawarat Rotejanaprasert</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Lawson"> Andrew Lawson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Early detection of unusual health events depends on the ability to detect rapidly any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler (SKL) measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate (SCPO) within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian" title="Bayesian">Bayesian</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial" title=" spatial"> spatial</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal" title=" temporal"> temporal</a>, <a href="https://publications.waset.org/abstracts/search?q=surveillance" title=" surveillance"> surveillance</a>, <a href="https://publications.waset.org/abstracts/search?q=prospective" title=" prospective"> prospective</a> </p> <a href="https://publications.waset.org/abstracts/52142/bayesian-prospective-detection-of-small-area-health-anomalies-using-kullback-leibler-divergence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52142.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">311</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10295</span> Label Free Detection of Small Molecules Using Surface-Enhanced Raman Spectroscopy with Gold Nanoparticles Synthesized with Various Capping Agents</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zahra%20Khan">Zahra Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Surface-Enhanced Raman Spectroscopy (SERS) has received increased attention in recent years, focusing on biological and medical applications due to its great sensitivity as well as molecular specificity. In the context of biological samples, there are generally two methodologies for SERS based applications: label-free detection and the use of SERS tags. The necessity of tagging can make the process slower and limits the use for real life. Label-free detection offers the advantage that it reports direct spectroscopic evidence associated with the target molecule rather than the label. Reproducible, highly monodisperse gold nanoparticles (Au NPs) were synthesized using a relatively facile seed-mediated growth method. Different capping agents (TRIS, citrate, and CTAB) were used during synthesis, and characterization was performed. They were then mixed with different analyte solutions before drop-casting onto a glass slide prior to Raman measurements to see which NPs displayed the highest SERS activity as well as their stability. A host of different analytes were tested, both non-biomolecules and biomolecules, which were all successfully detected using this method at concentrations as low as 10-3M with salicylic acid reaching a detection limit in the nanomolar range. SERS was also performed on samples with a mixture of analytes present, whereby peaks from both target molecules were distinctly observed. This is a fast and effective rapid way of testing samples and offers potential applications in the biomedical field as a tool for diagnostic and treatment purposes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gold%20nanoparticles" title="gold nanoparticles">gold nanoparticles</a>, <a href="https://publications.waset.org/abstracts/search?q=label%20free" title=" label free"> label free</a>, <a href="https://publications.waset.org/abstracts/search?q=seed-mediated%20growth" title=" seed-mediated growth"> seed-mediated growth</a>, <a href="https://publications.waset.org/abstracts/search?q=SERS" title=" SERS"> SERS</a> </p> <a href="https://publications.waset.org/abstracts/134630/label-free-detection-of-small-molecules-using-surface-enhanced-raman-spectroscopy-with-gold-nanoparticles-synthesized-with-various-capping-agents" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/134630.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">125</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10294</span> A Plasmonic Mass Spectrometry Approach for Detection of Small Nutrients and Toxins</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Haiyang%20Su">Haiyang Su</a>, <a href="https://publications.waset.org/abstracts/search?q=Kun%20Qian"> Kun Qian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We developed a novel plasmonic matrix assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxin in complex biological emulsion samples. We used silver nanoshells (SiO₂@Ag) with optimized structures as matrices and achieved direct analysis of ~6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, superior to the conventional biochemical methods currently in use. Our approach contributed to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real case bio-analysis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=plasmonic%20materials" title="plasmonic materials">plasmonic materials</a>, <a href="https://publications.waset.org/abstracts/search?q=laser%20desorption%2Fionization" title=" laser desorption/ionization"> laser desorption/ionization</a>, <a href="https://publications.waset.org/abstracts/search?q=mass%20spectrometry" title=" mass spectrometry"> mass spectrometry</a>, <a href="https://publications.waset.org/abstracts/search?q=small%20nutrients" title=" small nutrients"> small nutrients</a>, <a href="https://publications.waset.org/abstracts/search?q=toxins" title=" toxins"> toxins</a> </p> <a href="https://publications.waset.org/abstracts/90310/a-plasmonic-mass-spectrometry-approach-for-detection-of-small-nutrients-and-toxins" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90310.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">211</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10293</span> An Embedded System for Early Detection of Gas Leakage in Hospitals and Industries</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sehreen%20Moorat">Sehreen Moorat</a>, <a href="https://publications.waset.org/abstracts/search?q=Hiba"> Hiba</a>, <a href="https://publications.waset.org/abstracts/search?q=Maham%20Mahnoor"> Maham Mahnoor</a>, <a href="https://publications.waset.org/abstracts/search?q=Faryal%20Soomro"> Faryal Soomro</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Leakage of gases in a system makes infrastructures and users vulnerable; it can occur due to its environmental conditions or old groundwork. In hospitals and industries, it is very important to detect any small level of gas leakage because of their sensitivity. In this research, a portable detection system for the small leakage of gases has been developed, gas sensor (MQ-2) is used to find leakage when it’s at its initial phase. The sensor and transmitting module senses the change in level of gas by using a sensing circuit. When a concentration of gas reach at a specified threshold level, it will activate an alarm and send the alarming situation notification to receiver through GSM module. The proposed system works well in hospitals, home, and industries. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gases" title="gases">gases</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a>, <a href="https://publications.waset.org/abstracts/search?q=Arduino" title=" Arduino"> Arduino</a>, <a href="https://publications.waset.org/abstracts/search?q=MQ-2" title=" MQ-2"> MQ-2</a>, <a href="https://publications.waset.org/abstracts/search?q=alarm" title=" alarm"> alarm</a> </p> <a href="https://publications.waset.org/abstracts/80477/an-embedded-system-for-early-detection-of-gas-leakage-in-hospitals-and-industries" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80477.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge 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