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trashing</title> <meta name="description" content="Search results for: target trashing"> <meta name="keywords" content="target trashing"> <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 d-lg-none 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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="target trashing"> <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> 2733</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: target trashing</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2733</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">2732</span> Trashing Customary International Law Comprehensive Evaluation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Vahidkia">Hamid Vahidkia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Central to the World Court’s mission is the assurance of universal custom “as prove of a common hone acknowledged as law.” Understudies of the Court’s law have long been mindful that the Court has been superior at applying standard law than characterizing it. However until Nicaragua v. Joined together States, small hurt was done. For within the strongly challenged cases earlier to Nicaragua, the Court overseen to inspire commonalities in factious structure that floated its decisions toward the standard standards certain in state hone. The Court’s need of hypothetical unequivocality basically implied that a career opportunity emerged for a few eyewitnesses like me to endeavor to supply the lost hypothesis of custom. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=law" title="law">law</a>, <a href="https://publications.waset.org/abstracts/search?q=international%20law" title=" international law"> international law</a>, <a href="https://publications.waset.org/abstracts/search?q=jurisdication" title=" jurisdication"> jurisdication</a>, <a href="https://publications.waset.org/abstracts/search?q=customary" title=" customary"> customary</a> </p> <a href="https://publications.waset.org/abstracts/181976/trashing-customary-international-law-comprehensive-evaluation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181976.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">61</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">2731</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">2730</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">2729</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">2728</span> CRISPR-DT: Designing gRNAs for the CRISPR-Cpf1 System with Improved Target Efficiency and Specificity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Houxiang%20Zhu">Houxiang Zhu</a>, <a href="https://publications.waset.org/abstracts/search?q=Chun%20Liang"> Chun Liang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. The published CRISPR-Cpf1 gRNA data was reanalyzed. Many sequences and structural features of gRNAs (e.g., the position-specific nucleotide composition, position-nonspecific nucleotide composition, GC content, minimum free energy, and melting temperature) correlated with target efficiency were found. Using machine learning technology, a support vector machine (SVM) model was created to predict target efficiency for any given gRNAs. The first web service application, CRISPR-DT (CRISPR DNA Targeting), has been developed to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT will empower researchers in genome editing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CRISPR-Cpf1" title="CRISPR-Cpf1">CRISPR-Cpf1</a>, <a href="https://publications.waset.org/abstracts/search?q=genome%20editing" title=" genome editing"> genome editing</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20efficiency" title=" target efficiency"> target efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20specificity" title=" target specificity"> target specificity</a> </p> <a href="https://publications.waset.org/abstracts/93235/crispr-dt-designing-grnas-for-the-crispr-cpf1-system-with-improved-target-efficiency-and-specificity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/93235.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">262</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">2727</span> Scheduling Nodes Activity and Data Communication for Target Tracking in Wireless Sensor Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=AmirHossein%20Mohajerzadeh">AmirHossein Mohajerzadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Alishahi"> Mohammad Alishahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Saeed%20Aslishahi"> Saeed Aslishahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohsen%20Zabihi"> Mohsen Zabihi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we consider sensor nodes with the capability of measuring the bearings (relative angle to the target). We use geometric methods to select a set of observer nodes which are responsible for collecting data from the target. Considering the characteristics of target tracking applications, it is clear that significant numbers of sensor nodes are usually inactive. Therefore, in order to minimize the total network energy consumption, a set of sensor nodes, called sentinel, is periodically selected for monitoring, controlling the environment and transmitting data through the network. The other nodes are inactive. Furthermore, the proposed algorithm provides a joint scheduling and routing algorithm to transmit data between network nodes and the fusion center (FC) in which not only provides an efficient way to estimate the target position but also provides an efficient target tracking. Performance evaluation confirms the superiority of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coverage" title="coverage">coverage</a>, <a href="https://publications.waset.org/abstracts/search?q=routing" title=" routing"> routing</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <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=wireless%20sensor%20networks" title=" wireless sensor networks"> wireless sensor networks</a> </p> <a href="https://publications.waset.org/abstracts/46939/scheduling-nodes-activity-and-data-communication-for-target-tracking-in-wireless-sensor-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46939.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">378</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">2726</span> Clutter Suppression Based on Singular Value Decomposition and Fast Wavelet Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ruomeng%20Xiao">Ruomeng Xiao</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhulin%20Zong"> Zhulin Zong</a>, <a href="https://publications.waset.org/abstracts/search?q=Longfa%20Yang"> Longfa Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clutter%20suppression" title="clutter suppression">clutter suppression</a>, <a href="https://publications.waset.org/abstracts/search?q=singular%20value%20decomposition" title=" singular value decomposition"> singular value decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20transform" title=" wavelet transform"> wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=Mallat%20algorithm" title=" Mallat algorithm"> Mallat algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=low%20SCR" title=" low SCR"> low SCR</a> </p> <a href="https://publications.waset.org/abstracts/181202/clutter-suppression-based-on-singular-value-decomposition-and-fast-wavelet-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/181202.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">118</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">2725</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">2724</span> Transfer Knowledge From Multiple Source Problems to a Target Problem in Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Terence%20Soule">Terence Soule</a>, <a href="https://publications.waset.org/abstracts/search?q=Tami%20Al%20Ghamdi"> Tami Al Ghamdi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=transfer%20learning" title="transfer learning">transfer learning</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20computation" title=" evolutionary computation"> evolutionary computation</a>, <a href="https://publications.waset.org/abstracts/search?q=source%20and%20target" title=" source and target"> source and target</a> </p> <a href="https://publications.waset.org/abstracts/147927/transfer-knowledge-from-multiple-source-problems-to-a-target-problem-in-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147927.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">140</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">2723</span> Identification and Selection of a Supply Chain Target Process for Re-Design</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jaime%20A.%20Palma-Mendoza">Jaime A. Palma-Mendoza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decision%20support%20systems" title="decision support systems">decision support systems</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20criteria%20analysis" title=" multiple criteria analysis"> multiple criteria analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=supply%20chain%20management" title=" supply chain management "> supply chain management </a> </p> <a href="https://publications.waset.org/abstracts/27912/identification-and-selection-of-a-supply-chain-target-process-for-re-design" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27912.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">492</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">2722</span> Particle Filter Supported with the Neural Network for Aircraft Tracking Based on Kernel and Active Contour</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Izadkhah">Mohammad Izadkhah</a>, <a href="https://publications.waset.org/abstracts/search?q=Mojtaba%20Hoseini"> Mojtaba Hoseini</a>, <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Khalili%20Tehrani"> Alireza Khalili Tehrani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we presented a new method for tracking flying targets in color video sequences based on contour and kernel. The aim of this work is to overcome the problem of losing target in changing light, large displacement, changing speed, and occlusion. The proposed method is made in three steps, estimate the target location by particle filter, segmentation target region using neural network and find the exact contours by greedy snake algorithm. In the proposed method we have used both region and contour information to create target candidate model and this model is dynamically updated during tracking. To avoid the accumulation of errors when updating, target region given to a perceptron neural network to separate the target from background. Then its output used for exact calculation of size and center of the target. Also it is used as the initial contour for the greedy snake algorithm to find the exact target's edge. The proposed algorithm has been tested on a database which contains a lot of challenges such as high speed and agility of aircrafts, background clutter, occlusions, camera movement, and so on. The experimental results show that the use of neural network increases the accuracy of tracking and segmentation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=video%20tracking" title="video tracking">video tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20filter" title=" particle filter"> particle filter</a>, <a href="https://publications.waset.org/abstracts/search?q=greedy%20snake" title=" greedy snake"> greedy snake</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a> </p> <a href="https://publications.waset.org/abstracts/11913/particle-filter-supported-with-the-neural-network-for-aircraft-tracking-based-on-kernel-and-active-contour" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11913.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">342</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">2721</span> Coral Reef Fishes in the Marine Protected Areas in Southern Cebu, Philippines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Christine%20M.%20Corrales">Christine M. Corrales</a>, <a href="https://publications.waset.org/abstracts/search?q=Gloria%20G.%20Delan"> Gloria G. Delan</a>, <a href="https://publications.waset.org/abstracts/search?q=Rachel%20Luz%20V.%20Rica"> Rachel Luz V. Rica</a>, <a href="https://publications.waset.org/abstracts/search?q=Alfonso%20S.%20Piquero"> Alfonso S. Piquero</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Marine protected areas (MPAs) in the study sites were established 8-13 years ago and are presently operational. This study was conducted to gather baseline information on the diversity, density and biomass of coral reef fishes inside and outside the four marine protected areas (MPAs) of Cawayan, Dalaguete; Daan-Lungsod Guiwang, Alcoy; North Granada, Boljoon and Sta. Cruz, Ronda. Coral reef fishes in the MPAs were identified using Fish Visual Census Method. Results of the t-test showed that the mean diversity (fish species/250m2) of target and non-target reef fish species found inside and outside the MPAs were significantly different. Density (ind./1,000m2) of target species inside and outside the MPAs showed no significant difference. Similarly, density of non-target species inside and outside the MPAs also showed no significant difference. This is an indication that fish density inside and outside the MPAs were more or less of the same condition. The mean biomass (kg/1,000m2) of target species inside and outside the MPAs showed a significant difference in contrast with non-target species inside and outside the MPAs which showed a no significant difference. Higher biomass of target fish species belonging to family Caesonidae (fusiliers) and Scaridae (parrotfishes) were commonly observed inside the MPAs. Results showed that fish species were more diverse with higher density and biomass inside the MPAs than the outside area. However, fish diversity and density were mostly contributed by non-target species. Hence, long term protection and management of MPAs is needed to effectively increase fish diversity, density and biomass specifically on target fish species. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biomass" title="biomass">biomass</a>, <a href="https://publications.waset.org/abstracts/search?q=density" title=" density"> density</a>, <a href="https://publications.waset.org/abstracts/search?q=diversity" title=" diversity"> diversity</a>, <a href="https://publications.waset.org/abstracts/search?q=marine%20protected%20area" title=" marine protected area"> marine protected area</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20fish%20species" title=" target fish species"> target fish species</a> </p> <a href="https://publications.waset.org/abstracts/39481/coral-reef-fishes-in-the-marine-protected-areas-in-southern-cebu-philippines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39481.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">397</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">2720</span> A Students' Ability Analysis Methods, Devices, Electronic Equipment and Storage Media Design</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dequn%20Teng">Dequn Teng</a>, <a href="https://publications.waset.org/abstracts/search?q=Tianshuo%20Yang"> Tianshuo Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Mingrui%20Wang"> Mingrui Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Qiuyu%20Chen"> Qiuyu Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiao%20Wang"> Xiao Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Katie%20Atkinson"> Katie Atkinson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Currently, many students are kind of at a loss in the university due to the complex environment within the campus, where every information within the campus is isolated with fewer interactions with each other. However, if the on-campus resources are gathered and combined with the artificial intelligence modelling techniques, there will be a bridge for not only students in understanding themselves, and the teachers will understand students in providing a much efficient approach in education. The objective of this paper is to provide a competency level analysis method, apparatus, electronic equipment, and storage medium. It uses a user’s target competency level analysis model from a plurality of predefined candidate competency level analysis models by obtaining a user’s promotion target parameters, promotion target parameters including at least one of the following parameters: target profession, target industry, and the target company, according to the promotion target parameters. According to the parameters, the model analyzes the user’s ability level, determines the user’s ability level, realizes the quantitative and personalized analysis of the user’s ability level, and helps the user to objectively position his ability level. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=model" title=" model"> model</a>, <a href="https://publications.waset.org/abstracts/search?q=university" title=" university"> university</a>, <a href="https://publications.waset.org/abstracts/search?q=education" title=" education"> education</a>, <a href="https://publications.waset.org/abstracts/search?q=recommendation%20system" title=" recommendation system"> recommendation system</a>, <a href="https://publications.waset.org/abstracts/search?q=evaluation" title=" evaluation"> evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=job%20hunting" title=" job hunting"> job hunting</a> </p> <a href="https://publications.waset.org/abstracts/131521/a-students-ability-analysis-methods-devices-electronic-equipment-and-storage-media-design" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131521.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">2719</span> Two-Sided Information Dissemination in Takeovers: Disclosure and Media</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eda%20Orhun">Eda Orhun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: This paper analyzes a target firm’s decision to voluntarily disclose information during a takeover event and the effect of such disclosures on the outcome of the takeover. Such voluntary disclosures especially in the form of earnings forecasts made around takeover events may affect shareholders’ decisions about the target firm’s value and in return takeover result. This study aims to shed light on this question. Design/methodology/approach: The paper tries to understand the role of voluntary disclosures by target firms during a takeover event in the likelihood of takeover success both theoretically and empirically. A game-theoretical model is set up to analyze the voluntary disclosure decision of a target firm to inform the shareholders about its real worth. The empirical implication of model is tested by employing binary outcome models where the disclosure variable is obtained by identifying the target firms in the sample that provide positive news by issuing increasing management earnings forecasts. Findings: The model predicts that a voluntary disclosure of positive information by the target decreases the likelihood that the takeover succeeds. The empirical analysis confirms this prediction by showing that positive earnings forecasts by target firms during takeover events increase the probability of takeover failure. Overall, it is shown that information dissemination through voluntary disclosures by target firms is an important factor affecting takeover outcomes. Originality/Value: This study is the first to the author's knowledge that studies the impact of voluntary disclosures by the target firm during a takeover event on the likelihood of takeover success. The results contribute to information economics, corporate finance and M&As literatures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=takeovers" title="takeovers">takeovers</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20firm" title=" target firm"> target firm</a>, <a href="https://publications.waset.org/abstracts/search?q=voluntary%20disclosures" title=" voluntary disclosures"> voluntary disclosures</a>, <a href="https://publications.waset.org/abstracts/search?q=earnings%20forecasts" title=" earnings forecasts"> earnings forecasts</a>, <a href="https://publications.waset.org/abstracts/search?q=takeover%20success" title=" takeover success"> takeover success</a> </p> <a href="https://publications.waset.org/abstracts/21649/two-sided-information-dissemination-in-takeovers-disclosure-and-media" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21649.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">318</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">2718</span> Classification of Random Doppler-Radar Targets during the Surveillance Operations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20C.%20Tikkiwal">G. C. Tikkiwal</a>, <a href="https://publications.waset.org/abstracts/search?q=Mukesh%20Upadhyay"> Mukesh Upadhyay</a> </p> <p class="card-text"><strong>Abstract:</strong></p> During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving the army, moving convoys etc. The radar operator selects one of the promising targets into single target tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper, we present a technique using mathematical and statistical methods like fast fourier transformation (FFT) and principal component analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=radar%20target" title="radar target">radar target</a>, <a href="https://publications.waset.org/abstracts/search?q=FFT" title=" FFT"> FFT</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20component%20analysis" title=" principal component analysis"> principal component analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=eigenvector" title=" eigenvector"> eigenvector</a>, <a href="https://publications.waset.org/abstracts/search?q=octave-notes" title=" octave-notes"> octave-notes</a>, <a href="https://publications.waset.org/abstracts/search?q=DSP" title=" DSP"> DSP</a> </p> <a href="https://publications.waset.org/abstracts/37430/classification-of-random-doppler-radar-targets-during-the-surveillance-operations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37430.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">394</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">2717</span> An Improved Sub-Nyquist Sampling Jamming Method for Deceiving Inverse Synthetic Aperture Radar</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yanli%20Qi">Yanli Qi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ning%20Lv"> Ning Lv</a>, <a href="https://publications.waset.org/abstracts/search?q=Jing%20Li"> Jing Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sub-Nyquist sampling jamming method (SNSJ) is a well known deception jamming method for inverse synthetic aperture radar (ISAR). However, the anti-decoy of the SNSJ method performs easier since the amplitude of the false-target images are weaker than the real-target image; the false-target images always lag behind the real-target image, and all targets are located in the same cross-range. In order to overcome the drawbacks mentioned above, a simple modulation based on SNSJ (M-SNSJ) is presented in this paper. The method first uses amplitude modulation factor to make the amplitude of the false-target images consistent with the real-target image, then uses the down-range modulation factor and cross-range modulation factor to make the false-target images move freely in down-range and cross-range, respectively, thus the capacity of deception is improved. Finally, the simulation results on the six available combinations of three modulation factors are given to illustrate our conclusion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=inverse%20synthetic%20aperture%20radar%20%28ISAR%29" title="inverse synthetic aperture radar (ISAR)">inverse synthetic aperture radar (ISAR)</a>, <a href="https://publications.waset.org/abstracts/search?q=deceptive%20jamming" title=" deceptive jamming"> deceptive jamming</a>, <a href="https://publications.waset.org/abstracts/search?q=Sub-Nyquist%20sampling%20jamming%20method%20%28SNSJ%29" title=" Sub-Nyquist sampling jamming method (SNSJ)"> Sub-Nyquist sampling jamming method (SNSJ)</a>, <a href="https://publications.waset.org/abstracts/search?q=modulation%20based%20on%20Sub-Nyquist%20sampling%20jamming%20method%20%28M-SNSJ%29" title=" modulation based on Sub-Nyquist sampling jamming method (M-SNSJ)"> modulation based on Sub-Nyquist sampling jamming method (M-SNSJ)</a> </p> <a href="https://publications.waset.org/abstracts/62644/an-improved-sub-nyquist-sampling-jamming-method-for-deceiving-inverse-synthetic-aperture-radar" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62644.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">218</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">2716</span> Multi-Sensor Target Tracking Using Ensemble Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bhekisipho%20Twala">Bhekisipho Twala</a>, <a href="https://publications.waset.org/abstracts/search?q=Mantepu%20Masetshaba"> Mantepu Masetshaba</a>, <a href="https://publications.waset.org/abstracts/search?q=Ramapulana%20Nkoana"> Ramapulana Nkoana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=single%20classifier" title="single classifier">single classifier</a>, <a href="https://publications.waset.org/abstracts/search?q=ensemble%20learning" title=" ensemble learning"> ensemble learning</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-target%20tracking" title=" multi-target tracking"> multi-target tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20classifiers" title=" multiple classifiers"> multiple classifiers</a> </p> <a href="https://publications.waset.org/abstracts/140816/multi-sensor-target-tracking-using-ensemble-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140816.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">268</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">2715</span> Prediction of MicroRNA-Target Gene by Machine Learning Algorithms in Lung Cancer Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nilubon%20Kurubanjerdjit">Nilubon Kurubanjerdjit</a>, <a href="https://publications.waset.org/abstracts/search?q=Nattakarn%20Iam-On"> Nattakarn Iam-On</a>, <a href="https://publications.waset.org/abstracts/search?q=Ka-Lok%20Ng"> Ka-Lok Ng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microRNA" title="microRNA">microRNA</a>, <a href="https://publications.waset.org/abstracts/search?q=miRNAs" title=" miRNAs"> miRNAs</a>, <a href="https://publications.waset.org/abstracts/search?q=lung%20cancer" title=" lung cancer"> lung cancer</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=Na%C3%AFve%20Bayes" title=" Naïve Bayes"> Naïve Bayes</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a> </p> <a href="https://publications.waset.org/abstracts/41904/prediction-of-microrna-target-gene-by-machine-learning-algorithms-in-lung-cancer-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41904.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">399</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">2714</span> Application of Principle Component Analysis for Classification of Random Doppler-Radar Targets during the Surveillance Operations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=G.%20C.%20Tikkiwal">G. C. Tikkiwal</a>, <a href="https://publications.waset.org/abstracts/search?q=Mukesh%20Upadhyay"> Mukesh Upadhyay</a> </p> <p class="card-text"><strong>Abstract:</strong></p> During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=radar%20target" title="radar target">radar target</a>, <a href="https://publications.waset.org/abstracts/search?q=fft" title=" fft"> fft</a>, <a href="https://publications.waset.org/abstracts/search?q=principal%20component%20analysis" title=" principal component analysis"> principal component analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=eigenvector" title=" eigenvector"> eigenvector</a>, <a href="https://publications.waset.org/abstracts/search?q=octave-notes" title=" octave-notes"> octave-notes</a>, <a href="https://publications.waset.org/abstracts/search?q=dsp" title=" dsp"> dsp</a> </p> <a href="https://publications.waset.org/abstracts/39492/application-of-principle-component-analysis-for-classification-of-random-doppler-radar-targets-during-the-surveillance-operations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39492.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">346</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">2713</span> Tracking Filtering Algorithm Based on ConvLSTM</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ailing%20Yang">Ailing Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Penghan%20Song"> Penghan Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Aihua%20Cai"> Aihua Cai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=maneuvering%20target" title="maneuvering target">maneuvering target</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimation" title=" state estimation"> state estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM" title=" LSTM"> LSTM</a>, <a href="https://publications.waset.org/abstracts/search?q=self-attention" title=" self-attention"> self-attention</a> </p> <a href="https://publications.waset.org/abstracts/164893/tracking-filtering-algorithm-based-on-convlstm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164893.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">177</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">2712</span> Design of Target Selection for Pedestrian Autonomous Emergency Braking System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tao%20Song">Tao Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Hao%20Cheng"> Hao Cheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Guangfeng%20Tian"> Guangfeng Tian</a>, <a href="https://publications.waset.org/abstracts/search?q=Chuang%20Xu"> Chuang Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An autonomous emergency braking system is an advanced driving assistance system that enables vehicle collision avoidance and pedestrian collision avoidance to improve vehicle safety. At present, because the pedestrian target is small, and the mobility is large, the pedestrian AEB system is faced with more technical difficulties and higher functional requirements. In this paper, a method of pedestrian target selection based on a variable width funnel is proposed. Based on the current position and predicted position of pedestrians, the relative position of vehicle and pedestrian at the time of collision is calculated, and different braking strategies are adopted according to the hazard level of pedestrian collisions. In the CNCAP standard operating conditions, comparing the method of considering only the current position of pedestrians and the method of considering pedestrian prediction position, as well as the method based on fixed width funnel and variable width funnel, the results show that, based on variable width funnel, the choice of pedestrian target will be more accurate and the opportunity of the intervention of AEB system will be more reasonable by considering the predicted position of the pedestrian target and vehicle's lateral motion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automatic%20emergency%20braking%20system" title="automatic emergency braking system">automatic emergency braking system</a>, <a href="https://publications.waset.org/abstracts/search?q=pedestrian%20target%20selection" title=" pedestrian target selection"> pedestrian target selection</a>, <a href="https://publications.waset.org/abstracts/search?q=TTC" title=" TTC"> TTC</a>, <a href="https://publications.waset.org/abstracts/search?q=variable%20width%20funnel" title=" variable width funnel"> variable width funnel</a> </p> <a href="https://publications.waset.org/abstracts/131807/design-of-target-selection-for-pedestrian-autonomous-emergency-braking-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131807.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">157</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">2711</span> The Enhancement of Target Localization Using Ship-Borne Electro-Optical Stabilized Platform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jaehoon%20Ha">Jaehoon Ha</a>, <a href="https://publications.waset.org/abstracts/search?q=Byungmo%20Kang"> Byungmo Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Kilho%20Hong"> Kilho Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Jungsoo%20Park"> Jungsoo Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Electro-optical (EO) stabilized platforms have been widely used for surveillance and reconnaissance on various types of vehicles, from surface ships to unmanned air vehicles (UAVs). EO stabilized platforms usually consist of an assembly of structure, bearings, and motors called gimbals in which a gyroscope is installed. EO elements such as a CCD camera and IR camera, are mounted to a gimbal, which has a range of motion in elevation and azimuth and can designate and track a target. In addition, a laser range finder (LRF) can be added to the gimbal in order to acquire the precise slant range from the platform to the target. Recently, a versatile functionality of target localization is needed in order to cooperate with the weapon systems that are mounted on the same platform. The target information, such as its location or velocity, needed to be more accurate. The accuracy of the target information depends on diverse component errors and alignment errors of each component. Specially, the type of moving platform can affect the accuracy of the target information. In the case of flying platforms, or UAVs, the target location error can be increased with altitude so it is important to measure altitude as precisely as possible. In the case of surface ships, target location error can be increased with obliqueness of the elevation angle of the gimbal since the altitude of the EO stabilized platform is supposed to be relatively low. The farther the slant ranges from the surface ship to the target, the more extreme the obliqueness of the elevation angle. This can hamper the precise acquisition of the target information. So far, there have been many studies on EO stabilized platforms of flying vehicles. However, few researchers have focused on ship-borne EO stabilized platforms of the surface ship. In this paper, we deal with a target localization method when an EO stabilized platform is located on the mast of a surface ship. Especially, we need to overcome the limitation caused by the obliqueness of the elevation angle of the gimbal. We introduce a well-known approach for target localization using Unscented Kalman Filter (UKF) and present the problem definition showing the above-mentioned limitation. Finally, we want to show the effectiveness of the approach that will be demonstrated through computer simulations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=target%20localization" title="target localization">target localization</a>, <a href="https://publications.waset.org/abstracts/search?q=ship-borne%20electro-optical%20stabilized%20platform" title=" ship-borne electro-optical stabilized platform"> ship-borne electro-optical stabilized platform</a>, <a href="https://publications.waset.org/abstracts/search?q=unscented%20kalman%20filter" title=" unscented kalman filter"> unscented kalman filter</a> </p> <a href="https://publications.waset.org/abstracts/52398/the-enhancement-of-target-localization-using-ship-borne-electro-optical-stabilized-platform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52398.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">520</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">2710</span> Role-Specific Target-Systems in Professional Bureaucracies: A Qualitative Analysis in the OR</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kirsten%20Hoeper">Kirsten Hoeper</a>, <a href="https://publications.waset.org/abstracts/search?q=Maike%20Kriependorf"> Maike Kriependorf</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper firstly discusses the initial situation and problems. Afterward, it defines professional bureaucracies and shows their impact for the OR-work. The OR-center and its actors are shown. Finally, the paper provides the empiric design for detecting the target systems of the different work groups within the OR, the quality criteria in qualitative research and empirical results. It is shown that different groups have different targets in their daily work and that helps for a better understanding. More precisely, by detecting the target systems of these experts, we can ‘bridge’ the different points of view to create a common basis for the work in the OR. One of the aims was to find bridges to overcome separating factors. This paper describes the situation in Germany focusing the Hannover Medical School. It can be assumed that the results can be transferred to other countries using the DRG-System (Diagnosis Related Groups). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hospital" title="hospital">hospital</a>, <a href="https://publications.waset.org/abstracts/search?q=OR" title=" OR"> OR</a>, <a href="https://publications.waset.org/abstracts/search?q=professional%20bureaucracies" title=" professional bureaucracies"> professional bureaucracies</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20systems" title=" target systems "> target systems </a> </p> <a href="https://publications.waset.org/abstracts/20136/role-specific-target-systems-in-professional-bureaucracies-a-qualitative-analysis-in-the-or" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20136.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">292</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">2709</span> Multi-Atlas Segmentation Based on Dynamic Energy Model: Application to Brain MR Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jie%20Huo">Jie Huo</a>, <a href="https://publications.waset.org/abstracts/search?q=Jonathan%20Wu"> Jonathan Wu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain%20MRI%20segmentation" title="brain MRI segmentation">brain MRI segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20energy%20model" title=" dynamic energy model"> dynamic energy model</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-atlas%20segmentation" title=" multi-atlas segmentation"> multi-atlas segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20minimization" title=" energy minimization"> energy minimization</a> </p> <a href="https://publications.waset.org/abstracts/68716/multi-atlas-segmentation-based-on-dynamic-energy-model-application-to-brain-mr-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68716.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">336</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">2708</span> Visual Servoing for Quadrotor UAV Target Tracking: Effects of Target Information Sharing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jason%20R.%20King">Jason R. King</a>, <a href="https://publications.waset.org/abstracts/search?q=Hugh%20H.%20T.%20Liu"> Hugh H. T. Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research presents simulation and experimental work in the visual servoing of a quadrotor Unmanned Aerial Vehicle (UAV) to stabilize overtop of a moving target. Most previous work in the field assumes static or slow-moving, unpredictable targets. In this experiment, the target is assumed to be a friendly ground robot moving freely on a horizontal plane, which shares information with the UAV. This information includes velocity and acceleration information of the ground target to aid the quadrotor in its tracking task. The quadrotor is assumed to have a downward-facing camera which is fixed to the frame of the quadrotor. Only onboard sensing for the quadrotor is utilized for the experiment, with a VICON motion capture system in place used only to measure ground truth and evaluate the performance of the controller. The experimental platform consists of an ArDrone 2.0 and a Create Roomba, communicating using Robot Operating System (ROS). The addition of the target’s information is demonstrated to help the quadrotor in its tracking task using simulations of the dynamic model of a quadrotor in Matlab Simulink. A nested PID control loop is utilized for inner-loop control the quadrotor, similar to previous works at the Flight Systems and Controls Laboratory (FSC) at the University of Toronto Institute for Aerospace Studies (UTIAS). Experiments are performed with ground truth provided by an indoor motion capture system, and the results are analyzed. It is demonstrated that a velocity controller which incorporates the additional information is able to perform better than the controllers which do not have access to the target’s information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quadrotor" title="quadrotor">quadrotor</a>, <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=unmanned%20aerial%20vehicle" title=" unmanned aerial vehicle"> unmanned aerial vehicle</a>, <a href="https://publications.waset.org/abstracts/search?q=UAV" title=" UAV"> UAV</a>, <a href="https://publications.waset.org/abstracts/search?q=UAS" title=" UAS"> UAS</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20servoing" title=" visual servoing"> visual servoing</a> </p> <a href="https://publications.waset.org/abstracts/56269/visual-servoing-for-quadrotor-uav-target-tracking-effects-of-target-information-sharing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56269.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">341</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">2707</span> Study on the Process of Detumbling Space Target by Laser</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Pinliang">Zhang Pinliang</a>, <a href="https://publications.waset.org/abstracts/search?q=Chen%20Chuan"> Chen Chuan</a>, <a href="https://publications.waset.org/abstracts/search?q=Song%20Guangming"> Song Guangming</a>, <a href="https://publications.waset.org/abstracts/search?q=Wu%20Qiang"> Wu Qiang</a>, <a href="https://publications.waset.org/abstracts/search?q=Gong%20Zizheng"> Gong Zizheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Ming"> Li Ming</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The active removal of space debris and asteroid defense are important issues in human space activities. Both of them need a detumbling process, for almost all space debris and asteroid are in a rotating state, and it`s hard and dangerous to capture or remove a target with a relatively high tumbling rate. So it`s necessary to find a method to reduce the angular rate first. The laser ablation method is an efficient way to tackle this detumbling problem, for it`s a contactless technique and can work at a safe distance. In existing research, a laser rotational control strategy based on the estimation of the instantaneous angular velocity of the target has been presented. But their calculation of control torque produced by a laser, which is very important in detumbling operation, is not accurate enough, for the method they used is only suitable for the plane or regularly shaped target, and they did not consider the influence of irregular shape and the size of the spot. In this paper, based on the triangulation reconstruction of the target surface, we propose a new method to calculate the impulse of the irregularly shaped target under both the covered irradiation and spot irradiation of the laser and verify its accuracy by theoretical formula calculation and impulse measurement experiment. Then we use it to study the process of detumbling cylinder and asteroid by laser. The result shows that the new method is universally practical and has high precision; it will take more than 13.9 hours to stop the rotation of Bennu with 1E+05kJ laser pulse energy; the speed of the detumbling process depends on the distance between the spot and the centroid of the target, which can be found an optimal value in every particular case. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=detumbling" title="detumbling">detumbling</a>, <a href="https://publications.waset.org/abstracts/search?q=laser%20ablation%20drive" title=" laser ablation drive"> laser ablation drive</a>, <a href="https://publications.waset.org/abstracts/search?q=space%20target" title=" space target"> space target</a>, <a href="https://publications.waset.org/abstracts/search?q=space%20debris%20remove" title=" space debris remove"> space debris remove</a> </p> <a href="https://publications.waset.org/abstracts/161293/study-on-the-process-of-detumbling-space-target-by-laser" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161293.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">84</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">2706</span> Synergism in the Inquiry Lab: An Analysis of Time Targets and Achievement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=John%20M.%20Basey">John M. Basey</a>, <a href="https://publications.waset.org/abstracts/search?q=Clinton%20D.%20Francis"> Clinton D. Francis</a>, <a href="https://publications.waset.org/abstracts/search?q=Maxwell%20B.%20Joseph"> Maxwell B. Joseph</a> </p> <p class="card-text"><strong>Abstract:</strong></p> After gathering data from experimental procedures, inquiry-oriented-science labs often allow students the freedom to stay and complete the write up in class or leave lab early and complete the write up later. Teachers must decide whether to allow students this freedom to self-regulate this time. Student interviews have indicated four time-target strategies that may influence how students utilize this time: grade-target-A, grade-target-C, time-limited, and proficiency. The hypothesis tested was that variability in class composition relative to the four grade-target strategies has an impact on when students leave class, which in turn may influence their overall learning as exemplified by grades. Students were divided into the four indicated groups with a survey. Class composition and the GTA teaching the class had significant impacts on how long students stayed in class with class composition having the greatest impact. A factor analysis identified two factors. Factor 1 included classes with percentages of grade-target students opposite time-limited/proficiency students and explained 43% of the variance. Factor 2 included classes with percentages of grade-target-A/proficiency students opposite grade-target-C students and explained 33% of the variance. Students who stayed longer received significantly higher grades (P = 0.008) with no significant relationships between grade and Factor 1 or Factor 2 (P > 0.05). The time students stayed in class was significantly positively related to Factor 1 (P = 0.006) and significantly negatively related to Factor 2 (P = 0.008). These results support the hypothesis and indicate that teachers may want to know the composition of student-target strategies before deciding on how to have students allocate study time at the end of inquiry-oriented labs. According to these results, ideal classes for self-regulation have a high proportion of proficiency and time-limited students and a low proportion of grade-target students, or a high proportion of grade-target-A and proficiency students and a low proportion of grade-target-C students. Non-ideal classes for self-regulation were comprised of the inverse proportions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=grades" title="grades">grades</a>, <a href="https://publications.waset.org/abstracts/search?q=inquiry%20lab%20design" title=" inquiry lab design"> inquiry lab design</a>, <a href="https://publications.waset.org/abstracts/search?q=synergism%20in%20student%20motivation" title=" synergism in student motivation"> synergism in student motivation</a>, <a href="https://publications.waset.org/abstracts/search?q=class%20composition" title=" class composition"> class composition</a> </p> <a href="https://publications.waset.org/abstracts/113351/synergism-in-the-inquiry-lab-an-analysis-of-time-targets-and-achievement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/113351.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">129</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">2705</span> Simulation for the Magnetized Plasma Compression Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Victor%20V.%20Kuzenov">Victor V. Kuzenov</a>, <a href="https://publications.waset.org/abstracts/search?q=Sergei%20V.%20Ryzhkov"> Sergei V. Ryzhkov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ongoing experimental and theoretical studies on magneto-inertial confinement fusion (Angara, C-2, CJS-100, General Fusion, MagLIF, MAGPIE, MC-1, YG-1, Omega) and new constructing facilities (Baikal, C-2W, Z300 and Z800) require adequate modeling and description of the physical processes occurring in high-temperature dense plasma in a strong magnetic field. This paper presents a mathematical model, numerical method, and results of the computer analysis of the compression process and the energy transfer in the target plasma, used in magneto-inertial fusion (MIF). The computer simulation of the compression process of the magnetized target by the high-power laser pulse and the high-speed plasma jets is presented. The characteristic patterns of the two methods of the target compression are being analysed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=magnetized%20target" title="magnetized target">magnetized target</a>, <a href="https://publications.waset.org/abstracts/search?q=magneto-inertial%20fusion" title=" magneto-inertial fusion"> magneto-inertial fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20model" title=" mathematical model"> mathematical model</a>, <a href="https://publications.waset.org/abstracts/search?q=plasma%20and%20laser%20beams" title=" plasma and laser beams"> plasma and laser beams</a> </p> <a href="https://publications.waset.org/abstracts/66035/simulation-for-the-magnetized-plasma-compression-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66035.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">296</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">2704</span> Highly Accurate Target Motion Compensation Using Entropy Function Minimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amin%20Aghatabar%20Roodbary">Amin Aghatabar Roodbary</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Hassan%20Bastani"> Mohammad Hassan Bastani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automatic%20target%20recognition%20%28ATR%29" title="automatic target recognition (ATR)">automatic target recognition (ATR)</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20resolution%20range%20profile%20%28HRRP%29" title=" high resolution range profile (HRRP)"> high resolution range profile (HRRP)</a>, <a href="https://publications.waset.org/abstracts/search?q=motion%20compensation" title=" motion compensation"> motion compensation</a>, <a href="https://publications.waset.org/abstracts/search?q=stepped%20frequency%20waveform%20technique%20%28SFW%29" title=" stepped frequency waveform technique (SFW)"> stepped frequency waveform technique (SFW)</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20motion%20parameters%20%28TMPs%29" title=" target motion parameters (TMPs)"> target motion parameters (TMPs)</a> </p> <a href="https://publications.waset.org/abstracts/97540/highly-accurate-target-motion-compensation-using-entropy-function-minimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97540.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">152</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=target%20trashing&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=target%20trashing&page=3">3</a></li> <li class="page-item"><a class="page-link" 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