Applied Sciences | September-2 2022

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return false;">Ok</a> </div> </div> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div> </div> <div> <div style="clear: both"></div> </div> </div> </div> <div class="jscroll"> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919310" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 14 pages, 7199 KiB   </span> <a href="/2076-3417/12/18/9397/pdf?version=1664518160" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Internet of Things Meets Computer Vision to Make an Intelligent Pest Monitoring Network" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9397">Internet of Things Meets Computer Vision to Make an Intelligent Pest Monitoring Network</a> <div class="authors"> by <span class="inlineblock "><strong>Bruno Cardoso</strong>, </span><span class="inlineblock "><strong>Catarina Silva</strong>, </span><span class="inlineblock "><strong>Joana Costa</strong> and </span><span class="inlineblock "><strong>Bernardete Ribeiro</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9397; <a href="https://doi.org/10.3390/app12189397">https://doi.org/10.3390/app12189397</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9397#metrics">Cited by 8</a> | Viewed by 4659 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> With the increase of smart farming in the agricultural sector, farmers have better control over the entire production cycle, notably in terms of pest monitoring. In fact, pest monitoring has gained significant importance, since the excessive use of pesticides can lead to great <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9397/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> With the increase of smart farming in the agricultural sector, farmers have better control over the entire production cycle, notably in terms of pest monitoring. In fact, pest monitoring has gained significant importance, since the excessive use of pesticides can lead to great damage to crops, substantial environmental impact, and unnecessary costs both in material and manpower. Despite the potential of new technologies, pest monitoring is still done in a traditional way, leading to excessive costs, lack of precision, and excessive use of human labour. In this paper, we present an Internet of Things (IoT) network combined with intelligent Computer Vision (CV) techniques to improve pest monitoring. First, we propose to use low-cost cameras at the edge that capture images of pest traps and send them to the cloud. Second, we use deep neural models, notably R-CNN and YOLO models, to detect the Whitefly (WF) pest in yellow sticky traps. Finally, the predicted number of WF is analysed over time and results are accessible to farmers through a mobile app that allows them to visualise the pest in each specific field. The contribution is to make pest monitoring autonomous, cheaper, data-driven, and precise. Results demonstrate that, by combining IoT, CV technology, and deep models, it is possible to enhance pest monitoring. <a href="/2076-3417/12/18/9397">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Advanced_IoT_Agriculture ">Advanced IoT Technologies in Agriculture</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9397/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919310"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919310"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919310" data-cycle-prev="#prev919310" data-cycle-progressive="#images919310" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919310-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g001-550.jpg?1664518266" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919310" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g002-550.jpg?1664518249'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g003-550.jpg?1664518265'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g004-550.jpg?1664518264'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g005-550.jpg?1664518268'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g006-550.jpg?1664518266'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g007-550.jpg?1664518255'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g008-550.jpg?1664518265'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g009-550.jpg?1664518263'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g010-550.jpg?1664518250'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g011-550.jpg?1664518253'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g0A1-550.jpg?1664518258'><p>Figure A1</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-919310-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g0A2-550.jpg?1664518268'><p>Figure A2</p></div></script></div></div><div id="article-919310-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g001-550.jpg?1664518266" title=" <strong>Figure 1</strong><br/> <p>Types of computation (adapted from [<a href="#B14-applsci-12-09397" class="html-bibr">14</a>]).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g002-550.jpg?1664518249" title=" <strong>Figure 2</strong><br/> <p>Network topology (adapted from [<a href="#B18-applsci-12-09397" class="html-bibr">18</a>]).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g003-550.jpg?1664518265" title=" <strong>Figure 3</strong><br/> <p>Faster R-CNN general architecture (adapted from [<a href="#B24-applsci-12-09397" class="html-bibr">24</a>]).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g004-550.jpg?1664518264" title=" <strong>Figure 4</strong><br/> <p>YOLOv5 general architecture (adapted from [<a href="#B26-applsci-12-09397" class="html-bibr">26</a>]).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g005-550.jpg?1664518268" title=" <strong>Figure 5</strong><br/> <p>Part of a dataset image with WFs.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g006-550.jpg?1664518266" title=" <strong>Figure 6</strong><br/> <p>Proposed IoT network.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g007-550.jpg?1664518255" title=" <strong>Figure 7</strong><br/> <p>YOLOv5 (XLarge) performance (number of whitefly detections) for different image dimensions and sizes.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g008-550.jpg?1664518265" title=" <strong>Figure 8</strong><br/> <p>Diagram of ESP32-CAM powered by solar panels.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g009-550.jpg?1664518263" title=" <strong>Figure 9</strong><br/> <p>Trap structures at the edge.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g010-550.jpg?1664518250" title=" <strong>Figure 10</strong><br/> <p>Example of a daily pest detection by the CV model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g011-550.jpg?1664518253" title=" <strong>Figure 11</strong><br/> <p>Part of the mobile app that allows users to monitor pests.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g0A1-550.jpg?1664518258" title=" <strong>Figure A1</strong><br/> <p>More examples of trap structures at the edge.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09397/article_deploy/html/images/applsci-12-09397-g0A2-550.jpg?1664518268" title=" <strong>Figure A2</strong><br/> <p>Another example of a daily pest detection by the CV model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9397'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919298" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 19543 KiB   </span> <a href="/2076-3417/12/18/9396/pdf?version=1663724372" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9396">Space Node Topology Optimization Design Considering Anisotropy of Additive Manufacturing</a> <div class="authors"> by <span class="inlineblock "><strong>Xianjie Wang</strong>, </span><span class="inlineblock "><strong>Fan Zhang</strong>, </span><span class="inlineblock "><strong>Zhenjiang Weng</strong>, </span><span class="inlineblock "><strong>Xinyu Jiang</strong>, </span><span class="inlineblock "><strong>Rushuang Wang</strong>, </span><span class="inlineblock "><strong>Hao Ren</strong> and </span><span class="inlineblock "><strong>Feiyun Zheng</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9396; <a href="https://doi.org/10.3390/app12189396">https://doi.org/10.3390/app12189396</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9396#metrics">Cited by 2</a> | Viewed by 2131 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9396/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> At present, a large number of scholars have conducted related research on topology optimization for additive manufacturing (AM). However, there are few relevant research reports on the impact of different directions of additive manufacturing on the optimal design and manufacturing results. In this paper, using the bidirectional evolutionary optimization (BESO) method, anisotropic optimization analysis was carried out on space nodes that are currently popular in the field of additive manufacturing and topology optimization. The elastic constants in different directions were used as anisotropic material properties for optimization research in this paper through tensile testing, which was carried out on 316L stainless-steel specimens fabricated using Selective Laser Melting (SLM) technology. In addition, SEM analyses were performed to explore the microscopic appearance of the material. The study found that additive manufacturing is affected by the printing direction in terms of both macroscopic mechanical properties and microscopic material structure; the deformation obtained by anisotropic optimization was about 1.1–2.3% smaller than that obtained by isotropic optimization. <a href="/2076-3417/12/18/9396">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Porous_Materials_Structures ">Porous Materials and Structures</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9396/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919298"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919298"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919298" data-cycle-prev="#prev919298" data-cycle-progressive="#images919298" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919298-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g001-550.jpg?1663749423" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919298" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g002-550.jpg?1663749404'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g003-550.jpg?1663749401'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g004-550.jpg?1663749407'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g005-550.jpg?1663749426'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g006-550.jpg?1663749403'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g007-550.jpg?1663749402'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g008-550.jpg?1663749428'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g009-550.jpg?1663749399'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g010-550.jpg?1663749424'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g011-550.jpg?1663749422'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g012-550.jpg?1663749415'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g013-550.jpg?1663749396'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g014-550.jpg?1663749411'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g015a-550.jpg?1663749425'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g015b-550.jpg?1663749400'><p>Figure 15 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-919298-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g016-550.jpg?1663749406'><p>Figure 16</p></div></script></div></div><div id="article-919298-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g001-550.jpg?1663749423" title=" <strong>Figure 1</strong><br/> <p>Schematic diagram of sensitivity filtering.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g002-550.jpg?1663749404" title=" <strong>Figure 2</strong><br/> <p>Flowchart of topology optimization.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g003-550.jpg?1663749401" title=" <strong>Figure 3</strong><br/> <p>Schematic diagram of SLM 316L stainless-steel metal specimen.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g004-550.jpg?1663749407" title=" <strong>Figure 4</strong><br/> <p>Schematic diagram of sample printing: (<b>a</b>) printing direction; (<b>b</b>) finished product.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g005-550.jpg?1663749426" title=" <strong>Figure 5</strong><br/> <p>Schematic diagram for adding properties of anisotropic materials.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g006-550.jpg?1663749403" title=" <strong>Figure 6</strong><br/> <p>Initial shape and load layout of nodes (the green part is the design domain, the gray part is the ear plate area, the yellow arrow is the combined load of axial force and pressure, and the blue area is the binding boundary).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g007-550.jpg?1663749402" title=" <strong>Figure 7</strong><br/> <p>Isotropic topology optimization results: (<b>a</b>) stress contour; (<b>b</b>) iterative curve.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g008-550.jpg?1663749428" title=" <strong>Figure 8</strong><br/> <p>Schematic diagram of tensile test: (<b>a</b>) Zwick electronic universal testing machine; (<b>b</b>) sample clamping state.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g009-550.jpg?1663749399" title=" <strong>Figure 9</strong><br/> <p>Stress–strain curve: (<b>a</b>) flat; (<b>b</b>) side; (<b>c</b>) vertical; (<b>d</b>) three directions.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g010-550.jpg?1663749424" title=" <strong>Figure 10</strong><br/> <p>Anisotropy of additively manufactured sample (including yield strength, elastic modulus, tensile strength, and elongation).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g011-550.jpg?1663749422" title=" <strong>Figure 11</strong><br/> <p>Surface topography before stretching: (<b>a</b>) flat-printed sample 200×; (<b>b</b>) vertical-printed sample 200×; (<b>c</b>) flat-printed sample 1000×; (<b>d</b>) vertical-printed sample 1000×.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g012-550.jpg?1663749415" title=" <strong>Figure 12</strong><br/> <p>Surface photo of the sample after tensile test: (<b>a</b>) overall appearance of the flat-printed sample after stretching; (<b>b</b>) overall appearance of the vertically printed sample after stretching; (<b>c</b>) particles in the crack of the flat-printed sample; (<b>d</b>) particles in the cracks of the vertically printed sample; (<b>e</b>) crack morphology of the flat-printed sample; (<b>f</b>) crack morphology of the vertical-printed sample.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g013-550.jpg?1663749396" title=" <strong>Figure 13</strong><br/> <p>Photo of the microscopic topography at the fracture: (<b>a</b>) flat-printed sample 200×; (<b>b</b>) vertical-printed sample 200×; (<b>c</b>) flat-printed sample 200×; (<b>d</b>) vertical-printed sample 200×.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g014-550.jpg?1663749411" title=" <strong>Figure 14</strong><br/> <p>Displacement nephogram under isotropic optimization: (<b>a</b>) X-direction print, Y-direction scan; (<b>b</b>) X-direction print, Z-direction scan; (<b>c</b>) Y-direction print, X-direction scan; (<b>d</b>) Y-direction print, Z-direction scan; (<b>e</b>) Z-direction print, X-direction scan; (<b>f</b>) Z-direction print, Y-direction scan.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g015a-550.jpg?1663749425" title=" <strong>Figure 15</strong><br/> <p>Shape and displacement nephogram under anisotropic optimization: (<b>a</b>) X-direction print, Y-direction scan; (<b>b</b>) X-direction print, Z-direction scan; (<b>c</b>) Y-direction print, X-direction scan; (<b>d</b>) Y-direction print, Z-direction scan; (<b>e</b>) Z-direction print, X-direction scan; (<b>f</b>) Z-direction print, Y-direction scan.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g015b-550.jpg?1663749400" title=" <strong>Figure 15 Cont.</strong><br/> <p>Shape and displacement nephogram under anisotropic optimization: (<b>a</b>) X-direction print, Y-direction scan; (<b>b</b>) X-direction print, Z-direction scan; (<b>c</b>) Y-direction print, X-direction scan; (<b>d</b>) Y-direction print, Z-direction scan; (<b>e</b>) Z-direction print, X-direction scan; (<b>f</b>) Z-direction print, Y-direction scan.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09396/article_deploy/html/images/applsci-12-09396-g016-550.jpg?1663749406" title=" <strong>Figure 16</strong><br/> <p>Deformation comparison between anisotropy and isotropy (yellow line is the deformation in six directions after isotropic optimization; red line is the deformation in six directions after anisotropic optimization).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9396'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919286" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 991 KiB   </span> <a href="/2076-3417/12/18/9395/pdf?version=1663729620" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Anonymous Identity Based Broadcast Encryption against Continual Side Channel Attacks in the State Partition Model" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9395">Anonymous Identity Based Broadcast Encryption against Continual Side Channel Attacks in the State Partition Model</a> <div class="authors"> by <span class="inlineblock "><strong>Qihong Yu</strong>, </span><span class="inlineblock "><strong>Jiguo Li</strong> and </span><span class="inlineblock "><strong>Sai Ji</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9395; <a href="https://doi.org/10.3390/app12189395">https://doi.org/10.3390/app12189395</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9395#metrics">Cited by 2</a> | Viewed by 1625 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In the past 10 years, many side-channel attacks have been discovered and exploited one after another by attackers, which have greatly damaged the security of cryptographic systems. Since no existing anonymous broadcast encryption scheme can resist the side-channel attack, the paper presents an <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9395/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In the past 10 years, many side-channel attacks have been discovered and exploited one after another by attackers, which have greatly damaged the security of cryptographic systems. Since no existing anonymous broadcast encryption scheme can resist the side-channel attack, the paper presents an anonymous identity-based broadcast encryption against continual side-channel attacks in the state partition model (CLR-SS-AIBBE). Based on split-state technology, the proposed scheme divides the private key into two states, and the decryption operations are correspondingly divided into two steps. Based on the three static hypotheses for a bilinear group with composite order, the proposed scheme can be proved to be fully secure by the dual system encryption technology in the standard model. The leakage ratio about the private key can reach 1/3. <a href="/2076-3417/12/18/9395">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9395/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919286"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919286"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919286" data-cycle-prev="#prev919286" data-cycle-progressive="#images919286" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919286-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09395/article_deploy/html/images/applsci-12-09395-g001-550.jpg?1663749379" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919286" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919286-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09395/article_deploy/html/images/applsci-12-09395-g002-550.jpg?1663749379'><p>Figure 2</p></div></script></div></div><div id="article-919286-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09395/article_deploy/html/images/applsci-12-09395-g001-550.jpg?1663749379" title=" <strong>Figure 1</strong><br/> <p>The relationship between the three leakage models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9395'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09395/article_deploy/html/images/applsci-12-09395-g002-550.jpg?1663749379" title=" <strong>Figure 2</strong><br/> <p>The system’s framework of anonymous leakage-resilient IBBE in cloud storage services.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9395'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919231" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 14 pages, 3590 KiB   </span> <a href="/2076-3417/12/18/9394/pdf?version=1663724599" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Earthquake Risk Probability Evaluation for Najin Lhasa in Southern Tibet" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9394">Earthquake Risk Probability Evaluation for Najin Lhasa in Southern Tibet</a> <div class="authors"> by <span class="inlineblock "><strong>Jianlong Zhang</strong>, </span><span class="inlineblock "><strong>Ye Zhu</strong>, </span><span class="inlineblock "><strong>Yingfeng Ji</strong>, </span><span class="inlineblock "><strong>Weiling Zhu</strong>, </span><span class="inlineblock "><strong>Rui Qu</strong>, </span><span class="inlineblock "><strong>Zhuoma Gongqiu</strong> and </span><span class="inlineblock "><strong>Chaodi Xie</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9394; <a href="https://doi.org/10.3390/app12189394">https://doi.org/10.3390/app12189394</a> - 19 Sep 2022 </div> Viewed by 1680 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The probabilistic seismic hazard analysis (PSHA) method is effectively used in an earthquake risk probability evaluation in seismogenic regions with active faults. In this study, by focusing on the potential seismic source area in Najin Lhasa, southern Tibet, and by incorporating the PSHA <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9394/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The probabilistic seismic hazard analysis (PSHA) method is effectively used in an earthquake risk probability evaluation in seismogenic regions with active faults. In this study, by focusing on the potential seismic source area in Najin Lhasa, southern Tibet, and by incorporating the PSHA method, we determined the seismic activity parameters and discussed the relationship of ground motion attenuation, the seismic hazard probability, and the horizontal bedrock ground motion acceleration peak value under different transcendence probabilities in this area. The calculation results show that the PSHA method divides the potential source area via specific tectonic scales and detailed tectonic markers, which reduces the scale of the potential source area and better reflects the uneven spatial distribution of seismic activity in the vicinity of Najin. The corrected attenuation relationship is also in line with the actual work requirements and is suitable for earthquake risk analysis. In addition, the major influences on the peak acceleration of ground motion in the study area are mainly in the potential source areas of Qushui (M7.5), Dangxiong (M8.5), and Kangma (M7.5). The peak horizontal ground motion acceleration (PGA) with a transcendence probability of 10% in 50 years is 185.9 cm/s<sup>2</sup>, and that with a transcendence probability of 2% in 50 years is 265.9 cm/s<sup>2</sup>. <a href="/2076-3417/12/18/9394">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/applsci/sections/earth_sciences_geography">Earth Sciences</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9394/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919231"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919231"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919231" data-cycle-prev="#prev919231" data-cycle-progressive="#images919231" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919231-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g001-550.jpg?1663724691" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919231" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919231-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g002-550.jpg?1663724699'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919231-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g003-550.jpg?1663724692'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919231-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g004-550.jpg?1663724693'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919231-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g005-550.jpg?1663724697'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919231-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g006-550.jpg?1663724696'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919231-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g007-550.jpg?1663724695'><p>Figure 7</p></div></script></div></div><div id="article-919231-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g001-550.jpg?1663724691" title=" <strong>Figure 1</strong><br/> <p>Tectonic map. The red rectangular indicates the study area. The background colored in pink indicates the Tibet autonomous region, and the green part indicates the Qinghai province, China. Black lines indicate the boundaries of the earthquake statistical area. The dashed red lines indicate the main faults and terrain boundaries. YZSZ: Yarlung–Zangpo suture zone; BNSZ: Bangong–Nujiang suture zone; JRSZ: Jinsha River suture zone; MBT: Main Boundary Thrust.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9394'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g002-550.jpg?1663724699" title=" <strong>Figure 2</strong><br/> <p>Division map of 18 potential seismogenic zones (red lines) according to this study. The numbers indicate the zone number. Black curves indicate the county boundaries.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9394'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g003-550.jpg?1663724692" title=" <strong>Figure 3</strong><br/> <p>Transcendence probability curve of the horizontal peak acceleration of bedrock at the engineering site of Najin Lhasa.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9394'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g004-550.jpg?1663724693" title=" <strong>Figure 4</strong><br/> <p>Response spectrum curve of the bedrock horizontal acceleration at the engineering site of Najin Lhasa.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9394'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g005-550.jpg?1663724697" title=" <strong>Figure 5</strong><br/> <p>Horizontal bedrock PGA decay curve with epicentral distance (R).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9394'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g006-550.jpg?1663724696" title=" <strong>Figure 6</strong><br/> <p>Attenuation curve of the response spectrum of horizontal bedrock acceleration (epicentral distance R = 50 km).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9394'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09394/article_deploy/html/images/applsci-12-09394-g007-550.jpg?1663724695" title=" <strong>Figure 7</strong><br/> <p>Attenuation curve of the response spectrum of horizontal bedrock acceleration (epicentral distance R = 100 km).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9394'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919219" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 12 pages, 3535 KiB   </span> <a href="/2076-3417/12/18/9393/pdf?version=1663724066" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Design and Implementation of an Additively Manufactured Reactor Concept for the Catalytic Methanation" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9393">Design and Implementation of an Additively Manufactured Reactor Concept for the Catalytic Methanation</a> <div class="authors"> by <span class="inlineblock "><strong>Alexander Hauser</strong>, </span><span class="inlineblock "><strong>Michael Neubert</strong>, </span><span class="inlineblock "><strong>Alexander Feldner</strong>, </span><span class="inlineblock "><strong>Alexander Horn</strong>, </span><span class="inlineblock "><strong>Fabian Grimm</strong> and </span><span class="inlineblock "><strong>Jürgen Karl</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9393; <a href="https://doi.org/10.3390/app12189393">https://doi.org/10.3390/app12189393</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9393#metrics">Cited by 6</a> | Viewed by 1689 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The methanation process is discussed as one way to chemically store renewable energy in a future energy system. An important criterion for its application is the availability of compact, low-cost reactor concepts with high conversion rates for decentralized use where the renewable energy <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9393/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The methanation process is discussed as one way to chemically store renewable energy in a future energy system. An important criterion for its application is the availability of compact, low-cost reactor concepts with high conversion rates for decentralized use where the renewable energy is produced. Current research focuses on the maximization of the methane yield through improved temperature control of the exothermic reaction, which attempts to avoid both kinetic and thermodynamic limitations. In this context, traditional manufacturing methods limit the design options of the reactor and thus the temperature control possibilities. The use of additive manufacturing methods removes this restriction and creates new freedom in the design process. This paper formulates the requirements for a novel methanation reactor and presents their implementation to a highly innovative reactor concept called ‘ADDmeth’. By using a conical reaction channel expanding from Ø 8 to 32 mm, three twisted, expanding heat pipes (Ø 8 mm in evaporation zone, Ø 12 mm in condenser zone) and a lattice structure for feed gas preheating and mechanical stabilization of the reactor, the design explicitly exploits the advantages of additive manufacturing. The reactor is very compact with a specific mass of 0.36 kg/kW and has a high share of functional volume of 52%. The reactor development was accompanied by tensile tests of additively manufactured samples with the used material 1.4404 (316 L), strength calculations for stability verification and feasibility studies on the printability of fine structures. Ultimate tensile strengths of up to 750 N/mm<sup>2</sup> (at room temperature) and sufficiently high safety factors of the pressure-loaded structures against yielding were determined. Finally, the paper presents the manufactured bench-scale reactor ADDmeth1 and its implementation. <a href="/2076-3417/12/18/9393">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Applications_of_3D_Printing_in_Different_Industries ">Applications of 3D Printing in Different Industries</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9393/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919219"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919219"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919219" data-cycle-prev="#prev919219" data-cycle-progressive="#images919219" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919219-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g001-550.jpg?1663724155" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919219" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919219-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g002-550.jpg?1663724157'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919219-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g003-550.jpg?1663724157'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919219-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g004-550.jpg?1663724153'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919219-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g005-550.jpg?1663724143'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919219-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g006-550.jpg?1663724149'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919219-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g007-550.jpg?1663724147'><p>Figure 7</p></div></script></div></div><div id="article-919219-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g001-550.jpg?1663724155" title=" <strong>Figure 1</strong><br/> <p>Schematic illustration of the main objectives of active temperature control for methanation reactors (adapted from [<a href="#B11-applsci-12-09393" class="html-bibr">11</a>] with permission of Elsevier).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9393'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g002-550.jpg?1663724157" title=" <strong>Figure 2</strong><br/> <p>Geometry of the tensile samples (dimensions in mm).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9393'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g003-550.jpg?1663724157" title=" <strong>Figure 3</strong><br/> <p>Mounted tensile sample incl. thermocouples.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9393'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g004-550.jpg?1663724153" title=" <strong>Figure 4</strong><br/> <p>CAD cutaway scheme of ADDmeth1 highlighting the innovations and an exemplary gas pathway.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9393'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g005-550.jpg?1663724143" title=" <strong>Figure 5</strong><br/> <p>Exemplary stress–strain curves (individual measurements) of tensile tests at room temperature for tensile samples additively manufactured in different spatial directions.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9393'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g006-550.jpg?1663724149" title=" <strong>Figure 6</strong><br/> <p>Metal print sample (1.4404) with fine structures.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9393'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09393/article_deploy/html/images/applsci-12-09393-g007-550.jpg?1663724147" title=" <strong>Figure 7</strong><br/> <p>ADDmeth1 with fittings and piping for reactants, product gas, cooling and instrumentation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9393'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919195" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 28 pages, 6720 KiB   </span> <a href="/2076-3417/12/18/9392/pdf?version=1663739431" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Understanding and Predicting the Usage of Shared Electric Scooter Services on University Campuses" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9392">Understanding and Predicting the Usage of Shared Electric Scooter Services on University Campuses</a> <div class="authors"> by <span class="inlineblock "><strong>Seyed Mohammad Hossein Moosavi</strong>, </span><span class="inlineblock "><strong>Zhenliang Ma</strong>, </span><span class="inlineblock "><strong>Danial Jahed Armaghani</strong>, </span><span class="inlineblock "><strong>Mahdi Aghaabbasi</strong>, </span><span class="inlineblock "><strong>Mogana Darshini Ganggayah</strong>, </span><span class="inlineblock "><strong>Yuen Choon Wah</strong> and </span><span class="inlineblock "><strong>Dmitrii Vladimirovich Ulrikh</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9392; <a href="https://doi.org/10.3390/app12189392">https://doi.org/10.3390/app12189392</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9392#metrics">Cited by 9</a> | Viewed by 4604 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Electric vehicles (EVs) have been progressing rapidly in urban transport systems given their potential in reducing emissions and energy consumptions. The Shared Free-Floating Electric Scooter (SFFES) is an emerging EV publicized to address the first-/last-mile problem in travel. It also offers alternatives for <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9392/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Electric vehicles (EVs) have been progressing rapidly in urban transport systems given their potential in reducing emissions and energy consumptions. The Shared Free-Floating Electric Scooter (SFFES) is an emerging EV publicized to address the first-/last-mile problem in travel. It also offers alternatives for short-distance journeys using cars or ride-hailing services. However, very few SFFES studies have been carried out in developing countries and for university populations. Currently, many universities are facing an increased number of short-distance private car travels on campus. The study is designed to explore the attitudes and perceptions of students and staff towards SFFES usage on campus and the corresponding influencing factors. Three machine learning models were used to predict SFFES usage. Eleven important factors for using SFFESs on campus were identified via the supervised and unsupervised feature selection techniques, with the top three factors being daily travel mode, road features (e.g., green spaces) and age. The random forest model showed the highest accuracy in predicting the usage frequency of SFFESs (93.5%) using the selected 11 variables. A simulation-based optimization analysis was further conducted to discover the characterization of SFFES users, barriers/benefits of using SFFESs and safety concerns. <a href="/2076-3417/12/18/9392">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Intelligence_Techniques_Engineering ">Novel Hybrid Intelligence Techniques in Engineering</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9392/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919195"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919195"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919195" data-cycle-prev="#prev919195" data-cycle-progressive="#images919195" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919195-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g001-550.jpg?1663739503" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919195" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g002-550.jpg?1663739506'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g003-550.jpg?1663739507'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g004-550.jpg?1663739524'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g005-550.jpg?1663739509'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g006-550.jpg?1663739502'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g007-550.jpg?1663739510'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g008-550.jpg?1663739515'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g009-550.jpg?1663739528'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g010-550.jpg?1663739523'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g011-550.jpg?1663739514'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g012-550.jpg?1663739512'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g013-550.jpg?1663739529'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g014-550.jpg?1663739513'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g015-550.jpg?1663739518'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g016-550.jpg?1663739527'><p>Figure 16</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g017-550.jpg?1663739531'><p>Figure 17</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-919195-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g018-550.jpg?1663739521'><p>Figure 18</p></div></script></div></div><div id="article-919195-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g001-550.jpg?1663739503" title=" <strong>Figure 1</strong><br/> <p>University of Malaya campus map.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g002-550.jpg?1663739506" title=" <strong>Figure 2</strong><br/> <p>Methodology workflow.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g003-550.jpg?1663739507" title=" <strong>Figure 3</strong><br/> <p>Random forest algorithm workflow.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g004-550.jpg?1663739524" title=" <strong>Figure 4</strong><br/> <p>Percentage of SFFES use frequency based on four categories.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g005-550.jpg?1663739509" title=" <strong>Figure 5</strong><br/> <p>Participants’ perceptions about the advantages/benefits of using SFFESs.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g006-550.jpg?1663739502" title=" <strong>Figure 6</strong><br/> <p>Participants’ opinions about what reasons would prevent them from using the SFFESs.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g007-550.jpg?1663739510" title=" <strong>Figure 7</strong><br/> <p>Safety concerns based on SFFES usage categories.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g008-550.jpg?1663739515" title=" <strong>Figure 8</strong><br/> <p>Impact of road features on the perceptions of respondents who believed safety was an extremely preventative factor for riding an e-scooter.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g009-550.jpg?1663739528" title=" <strong>Figure 9</strong><br/> <p>Cluster dendrogram of 22 variables.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g010-550.jpg?1663739523" title=" <strong>Figure 10</strong><br/> <p>Correlation between the 22 independent variables.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g011-550.jpg?1663739514" title=" <strong>Figure 11</strong><br/> <p>Importance score (weight) of variables based on three ML methods.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g012-550.jpg?1663739512" title=" <strong>Figure 12</strong><br/> <p>Accumulated weights of variables.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g013-550.jpg?1663739529" title=" <strong>Figure 13</strong><br/> <p>The error vs number of tree graphs for 11 important features.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g014-550.jpg?1663739513" title=" <strong>Figure 14</strong><br/> <p>Test error and out-of-bag (OOB) error rate of the predicted model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g015-550.jpg?1663739518" title=" <strong>Figure 15</strong><br/> <p>Optimization results and importance of variables based on the first scenario: Always use SFFESs.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g016-550.jpg?1663739527" title=" <strong>Figure 16</strong><br/> <p>Optimization results and importance of variables based on the second scenario: Frequently use SFFESs.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g017-550.jpg?1663739531" title=" <strong>Figure 17</strong><br/> <p>Optimization results and importance of variables based on the second scenario: Occasionally use SFFESs.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09392/article_deploy/html/images/applsci-12-09392-g018-550.jpg?1663739521" title=" <strong>Figure 18</strong><br/> <p>Optimization results and importance of variables based on the second scenario: Never use SFFESs.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9392'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919184" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-919184" aria-controls="drop-supplementary-919184" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-919184" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2076-3417/12/18/9391/s1?version=1663597116"> Supplementary File 1 (ZIP, 808 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 28 pages, 19023 KiB   </span> <a href="/2076-3417/12/18/9391/pdf?version=1663648418" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Geodetic Upper Crust Deformation Based on Primary GNSS and INSAR Data in the Strymon Basin, Northern Greece—Correlation with Active Faults" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9391">Geodetic Upper Crust Deformation Based on Primary GNSS and INSAR Data in the Strymon Basin, Northern Greece—Correlation with Active Faults</a> <div class="authors"> by <span class="inlineblock "><strong>Ilias Lazos</strong>, </span><span class="inlineblock "><strong>Ioannis Papanikolaou</strong>, </span><span class="inlineblock "><strong>Sotirios Sboras</strong>, </span><span class="inlineblock "><strong>Michael Foumelis</strong> and </span><span class="inlineblock "><strong>Christos Pikridas</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9391; <a href="https://doi.org/10.3390/app12189391">https://doi.org/10.3390/app12189391</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9391#metrics">Cited by 17</a> | Viewed by 3094 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The Strymon basin (Northern Greece) belongs to the geodynamically active regime of the Aegean and, as expected, it hosts active faults. Nevertheless, the study area exhibits a low instrumentally and historically recorded seismicity. In order to comprehend the crustal deformation, we implemented GNSS- <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9391/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The Strymon basin (Northern Greece) belongs to the geodynamically active regime of the Aegean and, as expected, it hosts active faults. Nevertheless, the study area exhibits a low instrumentally and historically recorded seismicity. In order to comprehend the crustal deformation, we implemented GNSS- and InSAR-based techniques. Global Navigation Satellite System (GNSS) primary geodetic data recorded by 32 permanent stations over 7 years were analyzed and input in the triangulation methodology so as to calculate a series of deformational parameters. Moreover, a geostatistical methodology indicated the spatial distribution of each parameter, showing strain delimited up to 2750 × 10<sup>−</sup><sup>9</sup>. These results are in broad agreement with palaeoseismological surveys and active fault mapping. Moreover, InSAR analysis, based on a 6-year data recording, concluded that no horizontal rates have been traced in the E–W direction; if they do exist, they would be below resolution (less than 2 mm/yr). Peak vertical subsidence values of a few mm/yr are traced towards the hanging wall of the Serres fault zone within the Quaternary sediments at the eastern margin of Strymon basin but are attributed mainly to groundwater extraction. However, it is noteworthy that geodetic strain analysis implies: (a) that a couple of areas need further study to trace potentially active faults by palaeoseismological means; (b) the fault trace of the Serres fault zone might be further prolonged 8–10 km eastwards, where Quaternary sediments cover the fault. <a href="/2076-3417/12/18/9391">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/geology_geomatics_seismic ">The Contribution of Geology and Geomatics to Seismic Hazard and Earthquake Engineering</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9391/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919184"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919184"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919184" data-cycle-prev="#prev919184" data-cycle-progressive="#images919184" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919184-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g001-550.jpg?1663661552" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919184" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g002-550.jpg?1663661543'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g003-550.jpg?1663661537'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g004-550.jpg?1663661540'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g005-550.jpg?1663661559'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g006-550.jpg?1663661547'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g007-550.jpg?1663661557'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g008-550.jpg?1663661549'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g009-550.jpg?1663661531'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g010-550.jpg?1663661560'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919184-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g011-550.jpg?1663661554'><p>Figure 11</p></div></script></div></div><div id="article-919184-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g001-550.jpg?1663661552" title=" <strong>Figure 1</strong><br/> <p>(<b>a</b>) Map showing the location of inset map (<b>b</b>). (<b>b</b>) Map of the principal tectonic structures in the broader Aegean region (after [<a href="#B20-applsci-12-09391" class="html-bibr">20</a>,<a href="#B25-applsci-12-09391" class="html-bibr">25</a>,<a href="#B26-applsci-12-09391" class="html-bibr">26</a>,<a href="#B59-applsci-12-09391" class="html-bibr">59</a>,<a href="#B60-applsci-12-09391" class="html-bibr">60</a>,<a href="#B61-applsci-12-09391" class="html-bibr">61</a>,<a href="#B62-applsci-12-09391" class="html-bibr">62</a>,<a href="#B63-applsci-12-09391" class="html-bibr">63</a>,<a href="#B64-applsci-12-09391" class="html-bibr">64</a>,<a href="#B65-applsci-12-09391" class="html-bibr">65</a>,<a href="#B66-applsci-12-09391" class="html-bibr">66</a>,<a href="#B67-applsci-12-09391" class="html-bibr">67</a>,<a href="#B68-applsci-12-09391" class="html-bibr">68</a>]). The North Aegean Basin (NAB) and the North Aegean Trough (NAT) comprise the northern strand of the North Anatolian Fault (NAF), while the Central Aegean Trough represents the corresponding southern strand. The Corinth Gulf (CG) is the most extensionally growing region in the Aegean. In the Ionian Sea, the Apulian–Aegean Collision Zone (AACZ) is shown to the north and the Hellenic Arc to the south, separated and displaced by the right-lateral Cephalonia Transfer Fault Zone (CTFZ) in the middle. Hatched areas represent extension. Moment tensor solutions since 1997 from the RCMT catalogue [<a href="#B69-applsci-12-09391" class="html-bibr">69</a>] are also shown. The white rectangle indicates the location of the inset map (<b>c</b>). (<b>c</b>) Hillshade map showing the active/Neotectonic faults of the study area (F = Fault, FZ = Fault Zone). Recent earthquake spatial distribution (M<sub>L</sub> ≥ 0.5) since 2008 by the Institute of Geodynamics, National Observatory of Athens (IG-NOA), is also shown.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g002-550.jpg?1663661543" title=" <strong>Figure 2</strong><br/> <p>Typical wine-glass valleys, related to the Tholos–Nea Zichni (TNFZ) fault zone, located at the eastern boundary of the Strymon Basin. The red solid line indicates the linear fault trace. White lines show the incised wine-glass valleys indicating footwall uplift. Overall, the fault trace separates uplift from subsidence, controlling the present-day sedimentation processes, and also demonstrating that the fault is active.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g003-550.jpg?1663661537" title=" <strong>Figure 3</strong><br/> <p>(<b>a</b>) Geological map of the broader Strymon region, showing the alpine and post-alpine formations and the alpine compressional tectonics [<a href="#B85-applsci-12-09391" class="html-bibr">85</a>], as well as the active-neotectonic faults as shown in <a href="#applsci-12-09391-f001" class="html-fig">Figure 1</a>; (<b>b</b>) 16 permanent GNSS stations (black triangles), monitoring the broader Strymon region.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g004-550.jpg?1663661540" title=" <strong>Figure 4</strong><br/> <p>Maximum (MaHE) and Minimum (MiHE) Horizontal Extension in the broader Strymon area: (<b>a</b>) MaHE (blue arrows) and MiHE (red arrows) parameters vectors; (<b>b</b>) MaHE values grid, based on the interpolation (kriging) geostatistical methodology; (<b>c</b>) MiHE values grid, based on the interpolation (kriging) geostatistical methodology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g005-550.jpg?1663661559" title=" <strong>Figure 5</strong><br/> <p>Velocity (V) parameter analysis, consisting of vectors and grid pattern, based on the interpolation (kriging) geostatistical methodology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g006-550.jpg?1663661547" title=" <strong>Figure 6</strong><br/> <p>Maximum Shear Strain (MaxSS) in the broader Strymon area: (<b>a</b>) MaxSS values (red circles) of the total examination points; (<b>b</b>) MaxSS values grid, based on the interpolation (kriging) geostatistical analysis.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g007-550.jpg?1663661557" title=" <strong>Figure 7</strong><br/> <p>Area Strain (AS) in the broader Strymon area: (<b>a</b>) calculated dilatation (blue circles) and compaction (red circles) values; (<b>b</b>) dilatation values grid, based on the interpolation (kriging) geostatistical methodology; (<b>c</b>) compaction values grid, based on the interpolation (kriging) geostatistical methodology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g008-550.jpg?1663661549" title=" <strong>Figure 8</strong><br/> <p>Average LoS displacement rates for the period 2015–2020, derived by SNAPPING service on GEP using Sentinel-1 data from ascending track 102. White lines (a–e and f–k) correspond to spatial profiles shown in <a href="#applsci-12-09391-f008" class="html-fig">Figure 8</a>. Please note that, for the selected color scale, rates higher than ±4 mm/yr appear saturated to allow for the proper visualization of spatial variability of motion.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g009-550.jpg?1663661531" title=" <strong>Figure 9</strong><br/> <p>Average LoS displacement rates for the period 2015–2020, derived by SNAPPING service on GEP using Sentinel-1 data from descending track 7. White lines (a–e and f–k) correspond to spatial profiles shown in <a href="#applsci-12-09391-f008" class="html-fig">Figure 8</a>. Please note that, for the selected color scale, rates higher than ±4 mm/yr appear saturated to allow for the proper visualization of spatial variability of motion.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g010-550.jpg?1663661560" title=" <strong>Figure 10</strong><br/> <p>PSI displacement time series for ascending track 102 at the location of high subsidence rates within the basin. The calculated trend (low pass filtering) has been subtracted from observed LoS displacements to obtain the seasonal component. The annual seasonality and linear trend are consistent to water table variations in underground aquifers. Time series has been arbitrarily shifted for visualization purposes.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09391/article_deploy/html/images/applsci-12-09391-g011-550.jpg?1663661554" title=" <strong>Figure 11</strong><br/> <p>Spatial profiles (<b>a</b>–<b>e</b> and <b>f</b>–<b>k</b>) showing LoS displacement rates across major fault zones from both ascending and descending satellite tracks (see <a href="#applsci-12-09391-f006" class="html-fig">Figure 6</a> and <a href="#applsci-12-09391-f007" class="html-fig">Figure 7</a>). For the calculations, average motion grids of 100 m spacing were used. Bars indicate the variability of motion within a buffer of 1–2 km, whereas dots the average calculated rates along the profiles.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9391'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919161" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 11 pages, 4607 KiB   </span> <a href="/2076-3417/12/18/9390/pdf?version=1663723272" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Design and Synthesis of 3D-Graphene@C/Co@N-C Composites with Broadband Microwave Absorption Performance" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9390">Design and Synthesis of 3D-Graphene@C/Co@N-C Composites with Broadband Microwave Absorption Performance</a> <div class="authors"> by <span class="inlineblock "><strong>Songyan Li</strong>, </span><span class="inlineblock "><strong>Xiaoxia Tian</strong>, </span><span class="inlineblock "><strong>Jiafu Wang</strong> and </span><span class="inlineblock "><strong>Shaobo Qu</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9390; <a href="https://doi.org/10.3390/app12189390">https://doi.org/10.3390/app12189390</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9390#metrics">Cited by 1</a> | Viewed by 1655 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Improving the microwave absorption performance of Co-MOF-derived Co@N-C composite by constructing the morphology and spatial structure is a known challenge. In this work, under the action of the binder polyvinylpyrrolidone, 3D-graphene particles can be well decorated on the surface of the Co@N-C composite <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9390/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Improving the microwave absorption performance of Co-MOF-derived Co@N-C composite by constructing the morphology and spatial structure is a known challenge. In this work, under the action of the binder polyvinylpyrrolidone, 3D-graphene particles can be well decorated on the surface of the Co@N-C composite after high-temperature pyrolysis. In addition, due to the structural characteristics of MOFs, Co particles can be well covered by a carbon layer, which effectively solves the problem that magnetic metal particles are prone to corrosion and oxidation. The microwave absorption performances of the composite can be well adjusted by changing the average dotted density of the 3D-graphene on the Co@N-C composite. It is worth noting that the maximum reflection loss can reach −58.72 dB at the thickness of 1.64 mm, and the maximum effective absorption bandwidth can achieve 5.74 GHz at the 1.79 mm thickness, which almost covers the whole Ku band. Importantly, these results demonstrate that 3D-graphene@C/Co@N-C composites have great potential as high-efficiency microwave absorption materials. <a href="/2076-3417/12/18/9390">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9390/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919161"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919161"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919161" data-cycle-prev="#prev919161" data-cycle-progressive="#images919161" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919161-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g001-550.jpg?1663723348" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919161" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g002-550.jpg?1663723351'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g003-550.jpg?1663723353'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g004-550.jpg?1663723353'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g005-550.jpg?1663723359'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g006-550.jpg?1663723358'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g007-550.jpg?1663723356'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g008-550.jpg?1663723352'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g009-550.jpg?1663723355'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919161-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g010-550.jpg?1663723354'><p>Figure 10</p></div></script></div></div><div id="article-919161-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g001-550.jpg?1663723348" title=" <strong>Figure 1</strong><br/> <p>The SEM images of all composites. (<b>a</b>) The SEM image of CNC; (<b>b</b>) The SEM image of CNCG-1; (<b>c</b>) The SEM image of CNCG-2; (<b>d</b>) The SEM image of CNCG-3.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g002-550.jpg?1663723351" title=" <strong>Figure 2</strong><br/> <p>The HR-TEM image of CNC.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g003-550.jpg?1663723353" title=" <strong>Figure 3</strong><br/> <p>The XRD patterns and Raman spectra of all composites. (<b>a</b>) The XRD patterns of all composites; (<b>b</b>) The Raman spectra of all composites.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g004-550.jpg?1663723353" title=" <strong>Figure 4</strong><br/> <p>The room-temperature hysteresis loops of all composites.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g005-550.jpg?1663723359" title=" <strong>Figure 5</strong><br/> <p>The Raman spectra of CNCG-2. (<b>a</b>) The XPS spectrum of CNCG-2; (<b>b</b>) The Co 2p spectrum of CNCG-2; (<b>c</b>) The C 1s spectrum of CNCG-2; (<b>d</b>) The N 1s spectrum of CNCG-2.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g006-550.jpg?1663723358" title=" <strong>Figure 6</strong><br/> <p>The electromagnetic parameters of all composites. (<b>a</b>) The <math display="inline"><semantics> <msup> <mi>ε</mi> <mo>′</mo> </msup> </semantics></math> of all composites; (<b>b</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>″</mo> </msup> </mrow> </semantics></math> of all composites; (<b>c</b>) The <math display="inline"><semantics> <msup> <mi>μ</mi> <mo>′</mo> </msup> </semantics></math> of all composites; (<b>d</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>μ</mi> <mo>″</mo> </msup> </mrow> </semantics></math> of all composites; (<b>e</b>) The <math display="inline"><semantics> <mrow> <mi>tan</mi> <mo> </mo> <msub> <mi>δ</mi> <mi>ε</mi> </msub> </mrow> </semantics></math> of all composites; (<b>f</b>) The <math display="inline"><semantics> <mrow> <mi>tan</mi> <mo> </mo> <msub> <mi>δ</mi> <mi>μ</mi> </msub> </mrow> </semantics></math> of all composites.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g007-550.jpg?1663723356" title=" <strong>Figure 7</strong><br/> <p>The reflection loss curves of all composites. (<b>a</b>) The reflection loss curve of CNC; (<b>b</b>) The reflection loss curve of CNCG-1; (<b>c</b>) The reflection loss curve of CNCG-2; (<b>d</b>) The reflection loss curve of CNCG-3.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g008-550.jpg?1663723352" title=" <strong>Figure 8</strong><br/> <p>The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curves of all composites. (<b>a</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curve of CNC; (<b>b</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curve of CNCG-1; (<b>c</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curve of CNCG-2; (<b>d</b>) The <math display="inline"><semantics> <mrow> <msup> <mi>ε</mi> <mo>′</mo> </msup> <mo>−</mo> <msup> <mi>ε</mi> <mrow> <mrow> <mo>″</mo> </mrow> </mrow> </msup> </mrow> </semantics></math> curve of CNCG-3.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g009-550.jpg?1663723355" title=" <strong>Figure 9</strong><br/> <p>The <math display="inline"><semantics> <mrow> <msub> <mi>C</mi> <mn>0</mn> </msub> </mrow> </semantics></math> curves of all composites.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09390/article_deploy/html/images/applsci-12-09390-g010-550.jpg?1663723354" title=" <strong>Figure 10</strong><br/> <p>The <math display="inline"><semantics> <mi>α</mi> </semantics></math> curve and <math display="inline"><semantics> <mrow> <mfenced close="|" open="|"> <mrow> <msub> <mi>Z</mi> <mrow> <mi>in</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>Z</mi> <mn>0</mn> </msub> </mrow> </mfenced> </mrow> </semantics></math> curve of CNCG. (<b>a</b>) The <math display="inline"><semantics> <mi>α</mi> </semantics></math> curve of CNCG; (<b>b</b>) The <math display="inline"><semantics> <mrow> <mfenced close="|" open="|"> <mrow> <msub> <mi>Z</mi> <mrow> <mi>in</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>Z</mi> <mn>0</mn> </msub> </mrow> </mfenced> </mrow> </semantics></math> curve of CNCG.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9390'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919149" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 16 pages, 2491 KiB   </span> <a href="/2076-3417/12/18/9389/pdf?version=1663653065" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="AdaCB: An Adaptive Gradient Method with Convergence Range Bound of Learning Rate" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9389">AdaCB: An Adaptive Gradient Method with Convergence Range Bound of Learning Rate</a> <div class="authors"> by <span class="inlineblock "><strong>Xuanzhi Liao</strong>, </span><span class="inlineblock "><strong>Shahnorbanun Sahran</strong>, </span><span class="inlineblock "><strong>Azizi Abdullah</strong> and </span><span class="inlineblock "><strong>Syaimak Abdul Shukor</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9389; <a href="https://doi.org/10.3390/app12189389">https://doi.org/10.3390/app12189389</a> - 19 Sep 2022 </div> Viewed by 2279 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their problems include extreme learning rates, non-convergence issues, <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9389/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their problems include extreme learning rates, non-convergence issues, as well as poor generalization. Some enhanced variants have been proposed, such as AMSGrad, and AdaBound. However, the performances of these alternatives are controversial and some drawbacks still occur. In this work, we proposed an optimizer called AdaCB, which limits the learning rates of Adam in a convergence range bound. The bound range is determined by the LR test, and then two bound functions are designed to constrain Adam, and two bound functions tend to a constant value. To evaluate our method, we carry out experiments on the image classification task, three models including Smallnet, Network IN Network, and Resnet are trained on CIFAR10 and CIFAR100 datasets. Experimental results show that our method outperforms other optimizers on CIFAR10 and CIFAR100 datasets with accuracies of (82.76%, 53.29%), (86.24%, 60.19%), and (83.24%, 55.04%) on Smallnet, Network IN Network and Resnet, respectively. The results also indicate that our method maintains a faster learning speed, like adaptive gradient methods, in the early stage and achieves considerable accuracy, like SGD (M), at the end. <a href="/2076-3417/12/18/9389">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/AI_Based_Image ">AI-Based Image Processing</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9389/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919149"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919149"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919149" data-cycle-prev="#prev919149" data-cycle-progressive="#images919149" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919149-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g001-550.jpg?1663653133" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919149" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919149-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g002-550.jpg?1663653130'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919149-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g003-550.jpg?1663653129'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919149-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g004-550.jpg?1663653132'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919149-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g005-550.jpg?1663653131'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919149-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g006-550.jpg?1663653128'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919149-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g007-550.jpg?1663653130'><p>Figure 7</p></div></script></div></div><div id="article-919149-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g001-550.jpg?1663653133" title=" <strong>Figure 1</strong><br/> <p>The curve of loss functions by learning rate range test on the CIFAR10 dataset (Smallnet). The <span class="html-italic">x</span>-axis is learning rate, and the <span class="html-italic">y</span>-axis is training loss.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9389'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g002-550.jpg?1663653130" title=" <strong>Figure 2</strong><br/> <p>The learning curve of testing accuracy on CIFAR10 under Smallnet.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9389'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g003-550.jpg?1663653129" title=" <strong>Figure 3</strong><br/> <p>The learning curve of testing accuracy on CIFAR100 under Smallnet.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9389'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g004-550.jpg?1663653132" title=" <strong>Figure 4</strong><br/> <p>The learning curve of testing accuracy on CIFAR10 under NIN.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9389'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g005-550.jpg?1663653131" title=" <strong>Figure 5</strong><br/> <p>The learning curve of testing accuracy on CIFAR100 under NIN.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9389'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g006-550.jpg?1663653128" title=" <strong>Figure 6</strong><br/> <p>The learning curve of testing accuracy on CIFAR10 under Resnet18.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9389'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09389/article_deploy/html/images/applsci-12-09389-g007-550.jpg?1663653130" title=" <strong>Figure 7</strong><br/> <p>The learning curve of testing accuracy on CIFAR100 under Resnet18.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9389'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919162" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 3224 KiB   </span> <a href="/2076-3417/12/18/9388/pdf?version=1663668418" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Evading Logits-Based Detections to Audio Adversarial Examples by Logits-Traction Attack" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9388">Evading Logits-Based Detections to Audio Adversarial Examples by Logits-Traction Attack</a> <div class="authors"> by <span class="inlineblock "><strong>Songshen Han</strong>, </span><span class="inlineblock "><strong>Kaiyong Xu</strong>, </span><span class="inlineblock "><strong>Songhui Guo</strong>, </span><span class="inlineblock "><strong>Miao Yu</strong> and </span><span class="inlineblock "><strong>Bo Yang</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9388; <a href="https://doi.org/10.3390/app12189388">https://doi.org/10.3390/app12189388</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9388#metrics">Cited by 2</a> | Viewed by 1561 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Automatic Speech Recognition (ASR) provides a new way of human-computer interaction. However, it is vulnerable to adversarial examples, which are obtained by deliberately adding perturbations to the original audios. Thorough studies on the universal feature of adversarial examples are essential to prevent potential <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9388/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Automatic Speech Recognition (ASR) provides a new way of human-computer interaction. However, it is vulnerable to adversarial examples, which are obtained by deliberately adding perturbations to the original audios. Thorough studies on the universal feature of adversarial examples are essential to prevent potential attacks. Previous research has shown classic adversarial examples have different logits distribution compared to normal speech. This paper proposes a logit-traction attack to eliminate this difference at the statistical level. Experiments on the LibriSpeech dataset show that the proposed attack reduces the accuracy of the LOGITS NOISE detection to 52.1%. To further verify the effectiveness of this approach in attacking detection based on logits, three different features quantifying the dispersion of logits are constructed in this paper. Furthermore, a richer target sentence is adopted for experiments. The results indicate that these features can detect baseline adversarial examples with an accuracy of about 90% but cannot effectively detect Logits-Traction adversarial examples, proving that Logits-Traction attack can evade the logits-based detection method. <a href="/2076-3417/12/18/9388">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/AI_Signal_Processing ">AI, Machine Learning and Deep Learning in Signal Processing</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9388/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919162"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919162"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919162" data-cycle-prev="#prev919162" data-cycle-progressive="#images919162" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919162-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g001-550.jpg?1663749210" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919162" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919162-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g002-550.jpg?1663749214'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919162-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g003-550.jpg?1663749217'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919162-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g004-550.jpg?1663749211'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919162-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g005-550.jpg?1663749218'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919162-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g006-550.jpg?1663749210'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919162-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g007-550.jpg?1663749219'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919162-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g008-550.jpg?1663749212'><p>Figure 8</p></div></script></div></div><div id="article-919162-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g001-550.jpg?1663749210" title=" <strong>Figure 1</strong><br/> <p>Logits-Traction attack.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9388'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g002-550.jpg?1663749214" title=" <strong>Figure 2</strong><br/> <p>The schematic diagram of sparse logits (<b>a</b>) and dense logits (<b>b</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9388'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g003-550.jpg?1663749217" title=" <strong>Figure 3</strong><br/> <p>Logits of the original speech (<b>a</b>), adversarial example (<b>b</b>) and raw speech signal (<b>c</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9388'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g004-550.jpg?1663749211" title=" <strong>Figure 4</strong><br/> <p>Deployment of the detection system.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9388'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g005-550.jpg?1663749218" title=" <strong>Figure 5</strong><br/> <p>Difference of each frame in Lingvo by five normal speech (<b>a</b>) and C&amp;W adversarial examples (<b>b</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9388'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g006-550.jpg?1663749210" title=" <strong>Figure 6</strong><br/> <p>Logits value statistics in Lingvo.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9388'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g007-550.jpg?1663749219" title=" <strong>Figure 7</strong><br/> <p>Detecting C&amp;W adversarial examples by <math display="inline"><semantics> <mrow> <msup> <mi>σ</mi> <mo>+</mo> </msup> <msup> <mrow/> <mn>2</mn> </msup> </mrow> </semantics></math> feature in Lingvo.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9388'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09388/article_deploy/html/images/applsci-12-09388-g008-550.jpg?1663749212" title=" <strong>Figure 8</strong><br/> <p>Detecting LT adversarial examples by <math display="inline"><semantics> <mrow> <msup> <mi>σ</mi> <mo>+</mo> </msup> <msup> <mrow/> <mn>2</mn> </msup> </mrow> </semantics></math> feature in Lingvo.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9388'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919124" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 5583 KiB   </span> <a href="/2076-3417/12/18/9387/pdf?version=1663738163" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Study on Spray Characteristics and Breakup Mechanism of an SCR Injector" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9387">Study on Spray Characteristics and Breakup Mechanism of an SCR Injector</a> <div class="authors"> by <span class="inlineblock "><strong>Chuanxin Bai</strong>, </span><span class="inlineblock "><strong>Kai Liu</strong>, </span><span class="inlineblock "><strong>Tong Zhao</strong> and </span><span class="inlineblock "><strong>Jinjin Liu</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9387; <a href="https://doi.org/10.3390/app12189387">https://doi.org/10.3390/app12189387</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9387#metrics">Cited by 5</a> | Viewed by 1839 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Selective catalytic reduction (SCR) is currently one of the most efficient denitration technologies to reduce nitrogen oxide (NO<sub>x</sub>) emissions of diesel engines. AdBlue (urea water solution, UWS) is the carrier of the reducing agent of SCR, and the spray process of <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9387/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Selective catalytic reduction (SCR) is currently one of the most efficient denitration technologies to reduce nitrogen oxide (NO<sub>x</sub>) emissions of diesel engines. AdBlue (urea water solution, UWS) is the carrier of the reducing agent of SCR, and the spray process of UWS is one of the critical factors affecting denitration efficiency. In this paper, a non-air-assisted pressure-driven full process spray (NPFPS) model is proposed to illustrate the breakup mechanism and the spray distribution properties of UWS through computational fluid dynamics (CFD). In the NPFPS model, the mechanism of the primary breakup is described by the volume of fluid (VOF) approach, which realizes the quantitative study of the critical parameters determining spray characteristics such as the breakup length, inclination angle, droplet size of the primary breakup, and primary velocity. The distribution of the spray after the primary breakup is depicted by the discrete phase model (DPM) coupled with the Taylor analogy breakup (TAB) model, through which the degree of secondary breakup can be obtained including quantitative studies of the droplet size distribution and velocity distribution in the different cross-sections. To verify the accuracy and feasibility of the NPFPS model, the experimental data are employed to compare with the simulation data. The results are in good agreement, which indicate the practical value of the model. <a href="/2076-3417/12/18/9387">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9387/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919124"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919124"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919124" data-cycle-prev="#prev919124" data-cycle-progressive="#images919124" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919124-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g001-550.jpg?1663738228" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919124" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g002-550.jpg?1663738231'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g003-550.jpg?1663738230'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g004a-550.jpg?1663738241'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g004b-550.jpg?1663738244'><p>Figure 4 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g005-550.jpg?1663738238'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g006-550.jpg?1663738236'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g007-550.jpg?1663738234'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g008-550.jpg?1663738233'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g009-550.jpg?1663738246'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g010-550.jpg?1663738235'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g011-550.jpg?1663738237'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g012-550.jpg?1663738242'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-919124-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g013-550.jpg?1663738229'><p>Figure 13</p></div></script></div></div><div id="article-919124-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g001-550.jpg?1663738228" title=" <strong>Figure 1</strong><br/> <p>(<b>a</b>) Diagram of non-air-assisted injector structure and flow field of primary breakup. (<b>b</b>) Computational mesh and boundary conditions of primary breakup.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g002-550.jpg?1663738231" title=" <strong>Figure 2</strong><br/> <p>(<b>a</b>) Cutaway view of the droplet development fluid domain. (<b>b</b>) Computational mesh and boundary conditions of droplet development process.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g003-550.jpg?1663738230" title=" <strong>Figure 3</strong><br/> <p>Displacement curve of the needle valve.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g004a-550.jpg?1663738241" title=" <strong>Figure 4</strong><br/> <p>Development of the primary breakup at different times: (<b>a</b>) 0.5 ms; (<b>b</b>) 1 ms; (<b>c</b>) 1.5 ms; (<b>d</b>) 2 ms; (<b>e</b>) 2.5 ms; (<b>f</b>) 3 ms.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g004b-550.jpg?1663738244" title=" <strong>Figure 4 Cont.</strong><br/> <p>Development of the primary breakup at different times: (<b>a</b>) 0.5 ms; (<b>b</b>) 1 ms; (<b>c</b>) 1.5 ms; (<b>d</b>) 2 ms; (<b>e</b>) 2.5 ms; (<b>f</b>) 3 ms.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g005-550.jpg?1663738238" title=" <strong>Figure 5</strong><br/> <p>Initial radial velocity of the jet versus time.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g006-550.jpg?1663738236" title=" <strong>Figure 6</strong><br/> <p>Jet breakup regimes.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g007-550.jpg?1663738234" title=" <strong>Figure 7</strong><br/> <p>Comparison of simulated mean breakup length with empirical curve.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g008-550.jpg?1663738233" title=" <strong>Figure 8</strong><br/> <p>Jet inclination angle: (<b>a</b>) simulation result; (<b>b</b>) experiment result [<a href="#B15-applsci-12-09387" class="html-bibr">15</a>]; (<b>c</b>) cause of jet inclination angle.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g009-550.jpg?1663738246" title=" <strong>Figure 9</strong><br/> <p>Droplet: (<b>a</b>) diameter distribution; (<b>b</b>) aerodynamic Weber number distribution; (<b>c</b>) velocity distribution.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g010-550.jpg?1663738235" title=" <strong>Figure 10</strong><br/> <p>Comparison of droplet size distributions between the simulation and experiment.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g011-550.jpg?1663738237" title=" <strong>Figure 11</strong><br/> <p>Comparison of droplet size distribution at different distances from nozzle exits.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g012-550.jpg?1663738242" title=" <strong>Figure 12</strong><br/> <p>Droplet radial velocity distribution at 30 mm from the nozzle exits.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09387/article_deploy/html/images/applsci-12-09387-g013-550.jpg?1663738229" title=" <strong>Figure 13</strong><br/> <p>Droplet axial velocity distribution at 30 mm from the nozzle exits.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9387'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919114" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 20 pages, 11008 KiB   </span> <a href="/2076-3417/12/18/9386/pdf?version=1663732176" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Investigating the Energy-Efficient Structures Using Building Energy Performance Simulations: A Case Study" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9386">Investigating the Energy-Efficient Structures Using Building Energy Performance Simulations: A Case Study</a> <div class="authors"> by <span class="inlineblock "><strong>Safeer Abbas</strong>, </span><span class="inlineblock "><strong>Omer Saleem</strong>, </span><span class="inlineblock "><strong>Mujasim Ali Rizvi</strong>, </span><span class="inlineblock "><strong>Syed Minhaj Saleem Kazmi</strong>, </span><span class="inlineblock "><strong>Muhammad Junaid Munir</strong> and </span><span class="inlineblock "><strong>Shahid Ali</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9386; <a href="https://doi.org/10.3390/app12189386">https://doi.org/10.3390/app12189386</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9386#metrics">Cited by 6</a> | Viewed by 3116 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The use of energy efficient structures in the local construction industry assists in promoting green building concepts, leading to economical and eco-friendly solutions for self-sustained structures. The main aim of this study was to examine and compare the energy performance of various local <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9386/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The use of energy efficient structures in the local construction industry assists in promoting green building concepts, leading to economical and eco-friendly solutions for self-sustained structures. The main aim of this study was to examine and compare the energy performance of various local buildings. Detailed 3D building models (house, office, and warehouse buildings) were constructed and investigated for their cost and energy savings using building energy simulation tools (green building studio and insight). Moreover, the effects of various building materials for walls, window panels, and roof construction were explored, and a life-cycle cost analysis was performed. It was observed that the effect of the window-to-wall ratio was less severe in term of energy use in office buildings compared to normal houses due to the larger amount of space available for air circulation. Furthermore, the most efficient location for windows was found to be at the middle of the wall in comparison with the top and bottom positions. The effect of the orientation mainly depended on the symmetry of the building. More symmetric buildings, i.e., tested warehouse buildings (rectangular structure), showed an energy use difference of around 7 MJ/m<sup>2</sup>/year for a 360° orientation change. Tested house buildings exhibited an energy use difference of up to 25 MJ/m<sup>2</sup>/year. Three-pane glass windows also showed major improvements, and the total energy consumption for houses was reduced to 14%. Furthermore, wood walls showed comparable energy performance with brick walls without the use of insulation. According to US-LEED guidelines, the tested house, office, and warehouse buildings achieved 79, 89, and 88 points, respectively. The cost recovery period for house, office, and warehouse buildings was estimated to 54, 13, and 14 years, respectively, including running and maintenance costs. It can be argued that the Insight and Green Building Studio packages can assist construction stakeholders to determine the energy efficiency of the modeled building as well as to help in the selection of materials for optimized and improved design. <a href="/2076-3417/12/18/9386">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/applsci/sections/civil_engineering">Civil Engineering</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9386/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919114"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919114"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" 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src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g003-550.jpg?1663749156'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g004-550.jpg?1663749178'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g005-550.jpg?1663749145'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g006-550.jpg?1663749164'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g007-550.jpg?1663749166'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g008-550.jpg?1663749144'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g009-550.jpg?1663749157'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g010-550.jpg?1663749167'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g011-550.jpg?1663749147'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g012-550.jpg?1663749161'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g013-550.jpg?1663749169'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g014-550.jpg?1663749176'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g015-550.jpg?1663749152'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g016-550.jpg?1663749180'><p>Figure 16</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g017-550.jpg?1663749148'><p>Figure 17</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g018-550.jpg?1663749162'><p>Figure 18</p></div> --- <div class='openpopupgallery' data-imgindex='18' data-target='article-919114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g019-550.jpg?1663749174'><p>Figure 19</p></div></script></div></div><div id="article-919114-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g001-550.jpg?1663749150" title=" <strong>Figure 1</strong><br/> <p>Model of the case study buildings: (<b>a</b>) House; (<b>b</b>) Office; (<b>c</b>) Warehouse.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g002-550.jpg?1663749159" title=" <strong>Figure 2</strong><br/> <p>Different types of walls for office and warehouse buildings. (<b>a</b>) WO2: Masonry wall with insulation; (<b>b</b>) WO3: Wood wall without insulation; (<b>c</b>) WO4: Wood wall with insulation; (<b>d</b>) WO5: Straw bale wall; (<b>e</b>) WO6: Structurally insulated panel; (<b>f</b>) WO8: Insulated concrete foam; (<b>g</b>) WH1: Metal frame wall without insulation; (<b>h</b>) WH2: Metal frame wall with insulation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g003-550.jpg?1663749156" title=" <strong>Figure 3</strong><br/> <p>Different types of roof materials for office and warehouse buildings. (<b>a</b>) RO1; (<b>b</b>) RO2; (<b>c</b>) RO4; (<b>d</b>) RO5; (<b>e</b>) RW5; (<b>f</b>) RW6.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g004-550.jpg?1663749178" title=" <strong>Figure 4</strong><br/> <p>Flowchart of adopted methodology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g005-550.jpg?1663749145" title=" <strong>Figure 5</strong><br/> <p>Insight energy analysis for house building. (<b>a</b>) Cooling load analysis; (<b>b</b>) Heating load analysis.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g006-550.jpg?1663749164" title=" <strong>Figure 6</strong><br/> <p>Insight energy analysis for office building. (<b>a</b>) Cooling load analysis; (<b>b</b>) Heating load analysis.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g007-550.jpg?1663749166" title=" <strong>Figure 7</strong><br/> <p>Effect of window material on energy use in tested house building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g008-550.jpg?1663749144" title=" <strong>Figure 8</strong><br/> <p>Effect of window material on energy use in tested office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g009-550.jpg?1663749157" title=" <strong>Figure 9</strong><br/> <p>Effect of wall materials on energy use in tested house building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g010-550.jpg?1663749167" title=" <strong>Figure 10</strong><br/> <p>Effect of wall materials on energy use in tested office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g011-550.jpg?1663749147" title=" <strong>Figure 11</strong><br/> <p>Effect of wall materials on energy use in tested warehouse building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g012-550.jpg?1663749161" title=" <strong>Figure 12</strong><br/> <p>Effect of roof materials on energy use in tested house building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g013-550.jpg?1663749169" title=" <strong>Figure 13</strong><br/> <p>Effect of roof materials on energy use in office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g014-550.jpg?1663749176" title=" <strong>Figure 14</strong><br/> <p>Effect of roof materials on energy use in tested warehouse building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g015-550.jpg?1663749152" title=" <strong>Figure 15</strong><br/> <p>Effect of window position on energy use in tested house building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g016-550.jpg?1663749180" title=" <strong>Figure 16</strong><br/> <p>Effect of window position on energy use in tested office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g017-550.jpg?1663749148" title=" <strong>Figure 17</strong><br/> <p>Effect of W/W ratio in energy use in tested house. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g018-550.jpg?1663749162" title=" <strong>Figure 18</strong><br/> <p>Effect of W/W ratio in energy use in tested office building. (<b>a</b>) Energy use; (<b>b</b>) Efficiency.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09386/article_deploy/html/images/applsci-12-09386-g019-550.jpg?1663749174" title=" <strong>Figure 19</strong><br/> <p>Effect of building orientation in energy use. (<b>a</b>) House; (<b>b</b>) Office; (<b>c</b>) Warehouse.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9386'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919054" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 13 pages, 2236 KiB   </span> <a href="/2076-3417/12/18/9385/pdf?version=1663646516" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Three-Dimensional Change of Lip after Two-Jaw Surgery in Facial Asymmetry Using Facial Scanner" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9385">Three-Dimensional Change of Lip after Two-Jaw Surgery in Facial Asymmetry Using Facial Scanner</a> <div class="authors"> by <span class="inlineblock "><strong>Young-Jae Kim</strong>, </span><span class="inlineblock "><strong>Sung-Hwan Choi</strong>, </span><span class="inlineblock "><strong>Yoon Jeong Choi</strong>, </span><span class="inlineblock "><strong>Kee-Joon Lee</strong>, </span><span class="inlineblock "><strong>Sang-Hwy Lee</strong> and </span><span class="inlineblock "><strong>Hyung-Seog Yu</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9385; <a href="https://doi.org/10.3390/app12189385">https://doi.org/10.3390/app12189385</a> - 19 Sep 2022 </div> Viewed by 2354 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> A facial scanner and three-dimensional computed tomography (CT) were used to evaluate the three-dimensional change in lip asymmetry before and after two-jaw surgery for 22 patients with facial asymmetry (menton deviation > 3 mm). We used the labrale superius (Ls), deviated/non-deviated-side cheilions (Ch-D/Ch-ND), <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9385/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> A facial scanner and three-dimensional computed tomography (CT) were used to evaluate the three-dimensional change in lip asymmetry before and after two-jaw surgery for 22 patients with facial asymmetry (menton deviation > 3 mm). We used the labrale superius (Ls), deviated/non-deviated-side cheilions (Ch-D/Ch-ND), and labrale inferius (Li) to construct the upper and lower lip planes to evaluate the lip asymmetry. A correlation analysis was performed to determine the factors related to the vertical change in the cheilions (ΔChZ-D/ND). In the transverse axis, Ch-D and Li moved to improve the asymmetry after surgery. All landmarks, except the Ls, moved backward in the anteroposterior axis. In the vertical axis, significant upward movement was observed in all hard tissue landmarks; however, there were no significant changes in the soft tissue. In the lip plane, the difference in the height of Ch-D and Ch-ND was significantly reduced (1.38 mm vs. 0.72 mm). In the anteroposterior axis, the ΔChZ-D/ND showed significant correlations with the mandibular setback. In the vertical axis, the ΔCh-ND showed significant correlations with the maxillary impaction of the non-deviated side. The improvement in lip asymmetry post-surgery was mainly achieved by the movement of the lower lip and Ch-D rather than the upper lip and Ch-ND. <a href="/2076-3417/12/18/9385">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Orthodontic_TSADs ">Clinical Applications of Orthodontic TSADs (Temporary Skeletal Anchorage Devices)</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9385/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919054"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919054"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919054" data-cycle-prev="#prev919054" data-cycle-progressive="#images919054" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919054-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g001-550.jpg?1663749096" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919054" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919054-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g002-550.jpg?1663749101'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919054-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g003-550.jpg?1663749107'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919054-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g004-550.jpg?1663749104'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919054-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g005-550.jpg?1663749094'><p>Figure 5</p></div></script></div></div><div id="article-919054-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g001-550.jpg?1663749096" title=" <strong>Figure 1</strong><br/> <p>Registration of preoperative (T1) CT and FS images. The references used for superimposition were the forehead and the dorsum of the nose area (blue color), exocanthions, endocanthions, and nasal alas: N’, soft tissue nasion; Ex, exocanthion; En, endocanthion; Al, nasal ala; CT, computed tomography; and FS, facial scanner.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9385'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g002-550.jpg?1663749101" title=" <strong>Figure 2</strong><br/> <p>Superimposition of preoperative (T1) and postoperative (T2) images of the facial scanner. The references used for superimposition were the forehead and nasal bridge area (blue color), exocanthions, endocanthions, and nasal alas. (<b>A</b>) Preoperative FS image, (<b>B</b>) postoperative FS image, and (<b>C</b>,<b>D</b>) superimposed images. N’, soft tissue nasion; Ex, exocanthion; En, endocanthion; and Al, nasal ala.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9385'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g003-550.jpg?1663749107" title=" <strong>Figure 3</strong><br/> <p>Hard tissue and soft tissue landmarks used in this study. MSP, midsagittal plane; U3-D/ND, maxillary canine cusp tip on the deviated side/non-deviated side; U6-D/ND, maxillary 1st molar mesiobuccal cusp tip on the deviated side/non-deviated side; Mf-D/ND, mental foramen on the deviated side/non-deviated side; Me, menton; Ls, labrale superius; Li, labrale inferius; and Ch-D/ND, cheilion on the deviated side/non-deviated side.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9385'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g004-550.jpg?1663749104" title=" <strong>Figure 4</strong><br/> <p>Changes in the upper and lower lip planes. The upper lip plane was established by connecting both sides of the Ch and Ls. The lower lip planes were also established by connecting both sides of the Ch and Li. (<b>A</b>–<b>C</b>) The lip planes on the FS images, (<b>D</b>) The coronal view of the lip planes, (<b>E</b>) The sagittal view of the lip planes, (<b>F</b>) The axial view of the upper lip plane, (<b>G</b>) The axial view of the lower lip plane. Green arrows indicate significant changes in the landmarks. MSP, midsagittal plane; FH, Frankfort horizontal plane; Ls, labrale superius; Ch-D/ND, cheilion on deviated side/non-deviated side; Li, labrale inferius; and Ls, labrale superius.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9385'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09385/article_deploy/html/images/applsci-12-09385-g005-550.jpg?1663749094" title=" <strong>Figure 5</strong><br/> <p>Schematic diagram of the upper and lower lip planes. (<b>A</b>) The coronal view of schematic diagram, (<b>B</b>) The axial view of schematic diagram. Abbreviations: MSP, midsagittal plane; FH, Frankfort horizontal plane; Ls, labrale superius; Ch-D/ND, cheilion on the deviated side/non-deviated side; Li, labrale inferius; b − a, transverse lip asymmetry; a + b, lip width; c, vertical lip asymmetry; and d, anteroposterior lip asymmetry.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9385'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919023" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 2054 KiB   </span> <a href="/2076-3417/12/18/9384/pdf?version=1663668173" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Applications of Metaheuristics Inspired by Nature in a Specific Optimisation Problem of a Postal Distribution Sector" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9384">Applications of Metaheuristics Inspired by Nature in a Specific Optimisation Problem of a Postal Distribution Sector</a> <div class="authors"> by <span class="inlineblock "><strong>Michał Berliński</strong>, </span><span class="inlineblock "><strong>Eryk Warchulski</strong> and </span><span class="inlineblock "><strong>Stanisław Kozdrowski</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9384; <a href="https://doi.org/10.3390/app12189384">https://doi.org/10.3390/app12189384</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9384#metrics">Cited by 3</a> | Viewed by 1495 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> This paper presents a logistics problem, related to the transport of goods, which can be applied in practice, for example, in postal or courier services. Two mathematical models are presented as problems occurring in a logistics network. The main objective of the optimisation <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9384/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> This paper presents a logistics problem, related to the transport of goods, which can be applied in practice, for example, in postal or courier services. Two mathematical models are presented as problems occurring in a logistics network. The main objective of the optimisation problem presented is to minimise capital resources (Capex), such as cars or containers. Three methods are proposed to solve this problem. The first is a method based on mixed integer programming (MIP) and available through the CPLEX solver. This method is the reference method for us because, as an exact method, it is guaranteed to find the optimal solution as long as the problem is not too large. However, the logistic problem under consideration belongs to the class of NP-complete problems and therefore, for larger problems, i.e., for networks of large size, the MIP method does not find any integer solution in a reasonable computational time. Therefore, two nature-inspired heuristic methods have been proposed. The first is the evolutionary algorithm and the second is the artificial bee colony algorithm. Results indicate that the heuristics methods solve instances of large size, giving suboptimal solutions and therefore, enabling their application to real-life scenarios. <a href="/2076-3417/12/18/9384">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/metaheuristic_algorithms_optimization ">Metaheuristics for Real-World Optimization Problems</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9384/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919023"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919023"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919023" data-cycle-prev="#prev919023" data-cycle-progressive="#images919023" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919023-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g001a-550.jpg?1663749072" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919023" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919023-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g001b-550.jpg?1663749075'><p>Figure 1 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919023-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g002a-550.jpg?1663749070'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919023-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g002b-550.jpg?1663749074'><p>Figure 2 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919023-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g003-550.jpg?1663749077'><p>Figure 3</p></div></script></div></div><div id="article-919023-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g001a-550.jpg?1663749072" title=" <strong>Figure 1</strong><br/> <p>Convergence curves plotted for the algorithms considered, for a logistic network of different sizes, for the BLP model. Each curve is an average of 20 independent runs. (<b>a</b>) 5-node. (<b>b</b>) 10-node. (<b>c</b>) 15-node. (<b>d</b>) 20-node. (<b>e</b>) 25-node. (<b>f</b>) 30-node.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9384'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g001b-550.jpg?1663749075" title=" <strong>Figure 1 Cont.</strong><br/> <p>Convergence curves plotted for the algorithms considered, for a logistic network of different sizes, for the BLP model. Each curve is an average of 20 independent runs. (<b>a</b>) 5-node. (<b>b</b>) 10-node. (<b>c</b>) 15-node. (<b>d</b>) 20-node. (<b>e</b>) 25-node. (<b>f</b>) 30-node.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9384'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g002a-550.jpg?1663749070" title=" <strong>Figure 2</strong><br/> <p>Convergence curves plotted for the algorithms considered, for a logistic network of different sizes, for the ELP model. Each curve is an average of 20 independent runs. (<b>a</b>) 5-node. (<b>b</b>) 10-node. (<b>c</b>) 15-node. (<b>d</b>) 20-node. (<b>e</b>) 25-node. (<b>f</b>) 30-node.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9384'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g002b-550.jpg?1663749074" title=" <strong>Figure 2 Cont.</strong><br/> <p>Convergence curves plotted for the algorithms considered, for a logistic network of different sizes, for the ELP model. Each curve is an average of 20 independent runs. (<b>a</b>) 5-node. (<b>b</b>) 10-node. (<b>c</b>) 15-node. (<b>d</b>) 20-node. (<b>e</b>) 25-node. (<b>f</b>) 30-node.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9384'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09384/article_deploy/html/images/applsci-12-09384-g003-550.jpg?1663749077" title=" <strong>Figure 3</strong><br/> <p>Box plot of calculation time for heuristic methods for the BLP—(<b>a</b>) and ELP models—(<b>b</b>) model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9384'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919016" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 2859 KiB   </span> <a href="/2076-3417/12/18/9383/pdf?version=1663638894" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="A Partial Multiplicative Dimensional Reduction-Based Reliability Estimation Method for Probabilistic and Non-Probabilistic Hybrid Structural Systems" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9383">A Partial Multiplicative Dimensional Reduction-Based Reliability Estimation Method for Probabilistic and Non-Probabilistic Hybrid Structural Systems</a> <div class="authors"> by <span class="inlineblock "><strong>Xuyong Chen</strong>, </span><span class="inlineblock "><strong>Yuanlin Peng</strong>, </span><span class="inlineblock "><strong>Zhifeng Xu</strong> and </span><span class="inlineblock "><strong>Qiaoyun Wu</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9383; <a href="https://doi.org/10.3390/app12189383">https://doi.org/10.3390/app12189383</a> - 19 Sep 2022 </div> Viewed by 1551 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> A new reliability estimation method based on partial multiplicative dimensional reduction is proposed for probabilistic and non-probabilistic hybrid structural systems. The proposed method is characterized by decorrelating interval input variables from random input variables using the partial multiplicative dimensional reduction method in conjunction <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9383/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> A new reliability estimation method based on partial multiplicative dimensional reduction is proposed for probabilistic and non-probabilistic hybrid structural systems. The proposed method is characterized by decorrelating interval input variables from random input variables using the partial multiplicative dimensional reduction method in conjunction with the weakest-link theory. In this method, the failure statistics of the original performance function are equivalent to a statical chain of two elements, in which one of the two elements represents the failures due to random input variables and the other represents the failures due to interval variables. Rather than yielding an estimated interval of failure probability, the proposed method produces a single value for failure probability, which is more meaningful for engineering. In addition, the accuracy, validity, and superiority of the proposed method are demonstrated, and the error-related properties of the proposed method are investigated. <a href="/2076-3417/12/18/9383">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Soft_Computing_Application ">Soft Computing Application to Engineering Design</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9383/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919016"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919016"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919016" data-cycle-prev="#prev919016" data-cycle-progressive="#images919016" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919016-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g001-550.jpg?1663661478" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919016" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919016-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g002-550.jpg?1663661465'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919016-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g003-550.jpg?1663661474'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919016-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g004-550.jpg?1663661466'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919016-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g005-550.jpg?1663661471'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919016-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g006-550.jpg?1663661476'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919016-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g007-550.jpg?1663661469'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919016-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g008-550.jpg?1663661481'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919016-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g009-550.jpg?1663661479'><p>Figure 9</p></div></script></div></div><div id="article-919016-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g001-550.jpg?1663661478" title=" <strong>Figure 1</strong><br/> <p>Conceptional illustration of the proposed method.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g002-550.jpg?1663661465" title=" <strong>Figure 2</strong><br/> <p>Flowchart of safety state determination.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g003-550.jpg?1663661474" title=" <strong>Figure 3</strong><br/> <p>The flow chart of reliability estimation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g004-550.jpg?1663661466" title=" <strong>Figure 4</strong><br/> <p>Configuration of the cantilever beam.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g005-550.jpg?1663661471" title=" <strong>Figure 5</strong><br/> <p>Comparison between the original function and the approximation obtained by the proposed method.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g006-550.jpg?1663661476" title=" <strong>Figure 6</strong><br/> <p>Error histogram of the proposed method.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g007-550.jpg?1663661469" title=" <strong>Figure 7</strong><br/> <p>Configuration of roof truss.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g008-550.jpg?1663661481" title=" <strong>Figure 8</strong><br/> <p>Absolute error vs. failure probability.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09383/article_deploy/html/images/applsci-12-09383-g009-550.jpg?1663661479" title=" <strong>Figure 9</strong><br/> <p>The finite element model of a plate arch bridge.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9383'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919003" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 19 pages, 6236 KiB   </span> <a href="/2076-3417/12/18/9382/pdf?version=1663763928" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Influence of FK209 Cobalt Doped Electron Transport Layer in Cesium Based Perovskite Solar Cells" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9382">Influence of FK209 Cobalt Doped Electron Transport Layer in Cesium Based Perovskite Solar Cells</a> <div class="authors"> by <span class="inlineblock "><strong>Ahmed Hayali</strong>, </span><span class="inlineblock "><strong>Roger J. Reeves</strong> and </span><span class="inlineblock "><strong>Maan M. Alkaisi</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9382; <a href="https://doi.org/10.3390/app12189382">https://doi.org/10.3390/app12189382</a> - 19 Sep 2022 </div> Viewed by 1975 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The efficiency and stability of perovskite solar cells (PSCs) depend not only on the perovskite film quality, but they are also influenced by the charge carriers of both the electron and hole transport layers (ETL and HTL). Doping of the carrier transport layers <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9382/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The efficiency and stability of perovskite solar cells (PSCs) depend not only on the perovskite film quality, but they are also influenced by the charge carriers of both the electron and hole transport layers (ETL and HTL). Doping of the carrier transport layers is considered one of effective technique applied to enhance the efficiency and performance of the PSCs. FK209 cobalt TFSI and lithium TFSI salt were investigated as dopants for mesoporous TiO<sub>2</sub> (M-TiO<sub>2</sub>) in the ETL. Herein, FK209 cobalt doping offers improved conductivity, reproducibility and stability compared to other doping or undoped M-TiO<sub>2</sub> control device. It has been found that an optimum concentration of 2.5 mg FK209 cobalt in the M-TiO<sub>2</sub> has resulted in an efficiency of 15.6% on 0.36 cm<sup>2</sup> active device area, whereas, the undoped M-TiO<sub>2</sub> yielded an average efficiency of 10.8%. The enhanced efficiency is due to the improved conductivity of the ETL while maintaining high transparency and low surface roughness with FK209 doping. The M-TiO<sub>2</sub> doped with FK209 has a transparency of the 90% over the visible range and its measured energy gap was 3.59 eV. Perovskite films deposited on the M-TiO<sub>2</sub> doped with FK209 has also a lower PL intensity indicating faster charge extraction. The measured lifetime of the perovskite films deposited on the optimised M-TiO<sub>2</sub> film was 115.8 ns. <a href="/2076-3417/12/18/9382">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/ICAET ">Selected Papers from ICAET 2022</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9382/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919003"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919003"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919003" data-cycle-prev="#prev919003" data-cycle-progressive="#images919003" data-cycle-slides=">div" 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src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g006-550.jpg?1663764017'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g007-550.jpg?1663764015'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g008-550.jpg?1663764027'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g009-550.jpg?1663763994'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g010-550.jpg?1663764022'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g011-550.jpg?1663764025'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g012-550.jpg?1663764013'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g013-550.jpg?1663763996'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g014-550.jpg?1663764034'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g015-550.jpg?1663764009'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g016-550.jpg?1663764028'><p>Figure 16</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-919003-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g017-550.jpg?1663764036'><p>Figure 17</p></div></script></div></div><div id="article-919003-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g001-550.jpg?1663764032" title=" <strong>Figure 1</strong><br/> <p>Left, AFM images of the surface morphology structure and roughness of the (<b>a</b>) undoped mesoporous TiO<sub>2</sub>, RMS = 34.5 nm; (<b>b</b>) M-TiO<sub>2</sub> doped with FK209, RMS = 16 nm; (<b>c</b>) FK209/Li<sup>+</sup>, RMS = 22.75 nm; (<b>d</b>) Li<sup>+</sup>, RMS = 25.46 nm. Right, contact angle measurement of (<b>a</b>) undoped M-TiO<sub>2</sub>, ɵ = 14°; (<b>b</b>) M-TiO<sub>2</sub> doped with FK209, ɵ = 4.2°; (<b>c</b>) FK209/Li<sup>+</sup>, ɵ = 9°; (<b>d</b>) Li<sup>+</sup>, ɵ = 13°.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g002a-550.jpg?1663764006" title=" <strong>Figure 2</strong><br/> <p>Left, SEM images of surface topography of the perovskite layer deposited on the (<b>a</b>) undoped M-TiO<sub>2</sub> and mesoporous TiO<sub>2</sub> doped with (<b>b</b>) FK209, (<b>c</b>) FK209/Li<sup>+</sup> and (<b>d</b>) Li<sup>+</sup>. Right, the histogram shows an average grains size for (<b>a</b>) undoped M-TiO<sub>2</sub>, 163.9 nm; (<b>b</b>) M-TiO<sub>2</sub> doped with FK209, 242 nm; (<b>c</b>) FK209/Li<sup>+</sup>, 210 nm; (<b>d</b>) Li<sup>+</sup>, 205 nm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g002b-550.jpg?1663764021" title=" <strong>Figure 2 Cont.</strong><br/> <p>Left, SEM images of surface topography of the perovskite layer deposited on the (<b>a</b>) undoped M-TiO<sub>2</sub> and mesoporous TiO<sub>2</sub> doped with (<b>b</b>) FK209, (<b>c</b>) FK209/Li<sup>+</sup> and (<b>d</b>) Li<sup>+</sup>. Right, the histogram shows an average grains size for (<b>a</b>) undoped M-TiO<sub>2</sub>, 163.9 nm; (<b>b</b>) M-TiO<sub>2</sub> doped with FK209, 242 nm; (<b>c</b>) FK209/Li<sup>+</sup>, 210 nm; (<b>d</b>) Li<sup>+</sup>, 205 nm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g003-550.jpg?1663764038" title=" <strong>Figure 3</strong><br/> <p>Optical transparency properties of mesoporous TiO<sub>2</sub> doped with FK209, FK209 /Li<sup>+</sup>, and Li<sup>+</sup>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g004-550.jpg?1663764011" title=" <strong>Figure 4</strong><br/> <p>Optical absorbance properties of mesoporous TiO<sub>2</sub> doped with FK209, FK209 /Li<sup>+</sup>, and Li<sup>+</sup>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g005-550.jpg?1663764007" title=" <strong>Figure 5</strong><br/> <p>Extrapolation of the energy gap of M-TiO<sub>2</sub> doped with FK209, FK209 /Li<sup>+</sup>, and Li<sup>+</sup>, using Tauc plot.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g006-550.jpg?1663764017" title=" <strong>Figure 6</strong><br/> <p>Absorption of perovskite film deposited on M-TiO<sub>2</sub> doped with FK209, FK209/Li<sup>+</sup> and lithium.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g007-550.jpg?1663764015" title=" <strong>Figure 7</strong><br/> <p>Energy gap of perovskite films deposited on M-TiO<sub>2</sub> doped with FK209, FK209/Li<sup>+</sup> and lithium, using Tauc plot.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g008-550.jpg?1663764027" title=" <strong>Figure 8</strong><br/> <p>Photoluminescence spectra of perovskite films deposited on M-TiO<sub>2</sub> doped with FK209, FK209/Li<sup>+</sup> and lithium.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g009-550.jpg?1663763994" title=" <strong>Figure 9</strong><br/> <p>Photoluminescence decay time of perovskite deposited on M-TiO<sub>2</sub> doped with FK209, FK209/lithium and lithium and measured using fluorescence PL decay lifetime.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g010-550.jpg?1663764022" title=" <strong>Figure 10</strong><br/> <p>Left, schematic structure of the perovskite solar cell. Right, photograph of 2.5 × 2.5 cm<sup>2</sup> PSC fabricated in this study.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g011-550.jpg?1663764025" title=" <strong>Figure 11</strong><br/> <p>An SEM image of the cross-section of the perovskite solar cell device fabricated in this study showing the different layers.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g012-550.jpg?1663764013" title=" <strong>Figure 12</strong><br/> <p>The illuminated J-V characteristic curves of perovskite solar cells deposited on ETL of M-TiO<sub>2</sub> doped with FK209, FK209/Li<sup>+</sup> and lithium.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g013-550.jpg?1663763996" title=" <strong>Figure 13</strong><br/> <p>Transparency of the M-TiO<sub>2</sub> doped with 1.5-mg, 2.5-mg and 5-mg concentrations of FK209 cobalt.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g014-550.jpg?1663764034" title=" <strong>Figure 14</strong><br/> <p>Absorbance spectrum of the M-TiO<sub>2</sub> doped with 1.5-mg, 2.5-mg and 5-mg concentrations of FK209 cobalt.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g015-550.jpg?1663764009" title=" <strong>Figure 15</strong><br/> <p>Energy gap of M-TiO<sub>2</sub> doped with various concentrations of FK209 (1.5 mg, 2.5 mg and 5 mg) using Tauc plot. Dotted lines represent the tangent to the slope for each plot.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g016-550.jpg?1663764028" title=" <strong>Figure 16</strong><br/> <p>Statistical histogram of the PCE measured over 30 fabricated solar cells. The ETL was fabricated using C-TiO<sub>2</sub> prepared using DC-sputtering and M-TiO<sub>2</sub> doped with various concentrations of FK209.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09382/article_deploy/html/images/applsci-12-09382-g017-550.jpg?1663764036" title=" <strong>Figure 17</strong><br/> <p>Device stability testing by measuring variations in the efficiency of the perovskite solar cells measured over 40 weeks period in weekly intervals. Devices were kept in ambient laboratory and tested under AM1.5, 100 mW/cm<sup>2</sup> illumination using ABET sunlight simulators with reference cell as a control.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9382'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918990" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 27 pages, 9180 KiB   </span> <a href="/2076-3417/12/18/9381/pdf?version=1663647685" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Design and Implementation of Cloud-Based Collaborative Manufacturing Execution System in the Korean Fashion Industry" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9381">Design and Implementation of Cloud-Based Collaborative Manufacturing Execution System in the Korean Fashion Industry</a> <div class="authors"> by <span class="inlineblock "><strong>Minjae Ko</strong>, </span><span class="inlineblock "><strong>Changho Lee</strong> and </span><span class="inlineblock "><strong>Yongju Cho</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9381; <a href="https://doi.org/10.3390/app12189381">https://doi.org/10.3390/app12189381</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9381#metrics">Cited by 6</a> | Viewed by 4181 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Recently, manufacturing companies have been improving quality and productivity, reducing costs, and producing customized products according to Industry 4.0. The global value chain (GVC) is also being reorganized and manufacturing companies are recovering the connectivity of value chains based on, e.g., the regional <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9381/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Recently, manufacturing companies have been improving quality and productivity, reducing costs, and producing customized products according to Industry 4.0. The global value chain (GVC) is also being reorganized and manufacturing companies are recovering the connectivity of value chains based on, e.g., the regional value chain (RVC) and reshoring. With the advent of Industry 4.0, many manufacturing companies are introducing smart factories. A new type of manufacturing execution system (MES), a core system of smart factories, is necessary, owing to the new technologies and the increase in collaboration between companies. Here, we present the framework, development, and application processes of a “cloud-based collaborative MES System” to support the value chain of “order-design-production-delivery” for the manufacture of personalized sportswear products in the fashion industry in Korea. To this end, first, nine future MES deployment directions and frameworks are presented. Second, we present the UML modeling, conceptual framework, and functional framework for MES system development, considering six future MES establishment directions such as cloud and collaboration. Third, the application and effect of the designed and developed cloud-based collaborative MES system are analyzed for design, fabric, printing, and sewing companies that play a role in each stage of the sportswear value chain. <a href="/2076-3417/12/18/9381">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/smart_manufacturing_systems ">Smart Manufacturing Systems in Industry 4.0</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9381/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918990"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918990"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918990" data-cycle-prev="#prev918990" data-cycle-progressive="#images918990" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918990-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g001-550.jpg?1663661459" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918990" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g002-550.jpg?1663661488'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g003-550.jpg?1663661484'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g004-550.jpg?1663661480'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g005-550.jpg?1663661493'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g006-550.jpg?1663661460'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' 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10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g011-550.jpg?1663661462'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g012-550.jpg?1663661492'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g013-550.jpg?1663661478'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g014-550.jpg?1663661475'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g015-550.jpg?1663661474'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g016-550.jpg?1663661485'><p>Figure 16</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g017-550.jpg?1663661494'><p>Figure 17</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g018-550.jpg?1663661467'><p>Figure 18</p></div> --- <div class='openpopupgallery' data-imgindex='18' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g019-550.jpg?1663661462'><p>Figure 19</p></div> --- <div class='openpopupgallery' data-imgindex='19' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g020-550.jpg?1663661472'><p>Figure 20</p></div> --- <div class='openpopupgallery' data-imgindex='20' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g021-550.jpg?1663661470'><p>Figure 21</p></div> --- <div class='openpopupgallery' data-imgindex='21' data-target='article-918990-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g022-550.jpg?1663661457'><p>Figure 22</p></div></script></div></div><div id="article-918990-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g001-550.jpg?1663661459" title=" <strong>Figure 1</strong><br/> <p>Changes in manufacturing methods and production systems.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g002-550.jpg?1663661488" title=" <strong>Figure 2</strong><br/> <p>Future Manufacturing Execution System (MES) development directions.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g003-550.jpg?1663661484" title=" <strong>Figure 3</strong><br/> <p>Framework for future MES system.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g004-550.jpg?1663661480" title=" <strong>Figure 4</strong><br/> <p>Value chain for sportswear manufacturing.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g005-550.jpg?1663661493" title=" <strong>Figure 5</strong><br/> <p>Hub and spoke collaboration model for sportswear manufacturing.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g006-550.jpg?1663661460" title=" <strong>Figure 6</strong><br/> <p>Analysis of the collaboration form for sportswear manufacturing.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g007-550.jpg?1663661465" title=" <strong>Figure 7</strong><br/> <p>Detailed manufacturing process of sportswear.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g008-550.jpg?1663661468" title=" <strong>Figure 8</strong><br/> <p>Component diagram for design of cloud-based collaborative MES.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g009-550.jpg?1663661479" title=" <strong>Figure 9</strong><br/> <p>Communication diagram for design of cloud-based collaborative MES.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g010-550.jpg?1663661482" title=" <strong>Figure 10</strong><br/> <p>Activity diagram for design of cloud-based collaborative MES.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g011-550.jpg?1663661462" title=" <strong>Figure 11</strong><br/> <p>Class diagram for design of cloud-based collaborative MES.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g012-550.jpg?1663661492" title=" <strong>Figure 12</strong><br/> <p>Conceptual framework for cloud-based collaborative MES.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g013-550.jpg?1663661478" title=" <strong>Figure 13</strong><br/> <p>Functional framework for cloud-based collaborative MES.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g014-550.jpg?1663661475" title=" <strong>Figure 14</strong><br/> <p>Status of work by process.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g015-550.jpg?1663661474" title=" <strong>Figure 15</strong><br/> <p>Online work order sheet.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g016-550.jpg?1663661485" title=" <strong>Figure 16</strong><br/> <p>Order information recognition using vision system in the cutting process.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g017-550.jpg?1663661494" title=" <strong>Figure 17</strong><br/> <p>IoT device for sewing machine data collection.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g018-550.jpg?1663661467" title=" <strong>Figure 18</strong><br/> <p>Management function of collaborative companies in the value chain.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g019-550.jpg?1663661462" title=" <strong>Figure 19</strong><br/> <p>Confirmation of work orders via mobile system.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g020-550.jpg?1663661472" title=" <strong>Figure 20</strong><br/> <p>Process work confirmation via mobile system.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g021-550.jpg?1663661470" title=" <strong>Figure 21</strong><br/> <p>I/F with MES and enterprise resource planning (ERP).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09381/article_deploy/html/images/applsci-12-09381-g022-550.jpg?1663661457" title=" <strong>Figure 22</strong><br/> <p>Analysis of process automation through application of MES system.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9381'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919191" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 3 pages, 185 KiB   </span> <a href="/2076-3417/12/18/9380/pdf?version=1663666538" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Special Issue on Development and Application of Particle Detectors" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Editorial</span></div> <a class="title-link" href="/2076-3417/12/18/9380">Special Issue on Development and Application of Particle Detectors</a> <div class="authors"> by <span class="inlineblock "><strong>Andrea Giachero</strong> and </span><span class="inlineblock "><strong>Luca Gironi</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9380; <a href="https://doi.org/10.3390/app12189380">https://doi.org/10.3390/app12189380</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9380#metrics">Cited by 1</a> | Viewed by 1247 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-full inline"> Particle detection has been increasingly applied over a wide range of disciplines, including high-energy physics, astroparticles, space science and astronomy, biological sciences, medical imaging, remote sensing, environmental monitoring, cultural heritage, and homeland security [...] <a href="/2076-3417/12/18/9380">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/particle_detector ">Development and Application of Particle Detectors</a>)<br/> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919179" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 16 pages, 6346 KiB   </span> <a href="/2076-3417/12/18/9379/pdf?version=1663660170" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Design and Kinematic Analysis of Cable-Driven Target Spray Robot for Citrus Orchards" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9379">Design and Kinematic Analysis of Cable-Driven Target Spray Robot for Citrus Orchards</a> <div class="authors"> by <span class="inlineblock "><strong>Xiulan Bao</strong>, </span><span class="inlineblock "><strong>Yuxin Niu</strong>, </span><span class="inlineblock "><strong>Yishu Li</strong>, </span><span class="inlineblock "><strong>Jincheng Mao</strong>, </span><span class="inlineblock "><strong>Shanjun Li</strong>, </span><span class="inlineblock "><strong>Xiaojie Ma</strong>, </span><span class="inlineblock "><strong>Qilin Yin</strong> and </span><span class="inlineblock "><strong>Biyu Chen</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9379; <a href="https://doi.org/10.3390/app12189379">https://doi.org/10.3390/app12189379</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9379#metrics">Cited by 6</a> | Viewed by 2013 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In Southeast Asia, many varieties of citrus are grown in hilly areas. Compared with plain orchards, it is difficult for large spraying equipment to move in hilly orchards. Small spraying equipment can enter hilly orchards, but their spraying power cannot make droplets penetrate <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9379/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In Southeast Asia, many varieties of citrus are grown in hilly areas. Compared with plain orchards, it is difficult for large spraying equipment to move in hilly orchards. Small spraying equipment can enter hilly orchards, but their spraying power cannot make droplets penetrate into the canopy, resulting in low deposition rates within the canopy. As a kind of unstructured narrow space, the branches within the canopy are interlaced, thus a flexible manipulator that can move within the canopy is required. In this paper, a novel remote-controlled, cable-driven target spray robot (CDTSR) was designed to achieve a precise spray within the canopy. It consisted of a small tracked vehicle, a cable-driven flexible manipulator (CDFM), and a spray system. The CDFM had six degrees of freedom driven by a cable tendon. The forward and inverse kinematics model of the CDFM were established and then the semispherical workspace was calculated. Furthermore, while considering precise control requirements, the dynamics equations were derived. The experimental results demonstrated that the CFDM could move dexterously within the canopy with interlacing branches to reach pests and diseases areas in the canopy. The entire operation took 3.5 s. This study solved the problem of a low spray deposition rate within a canopy and has potential applications in agricultural plant protection. <a href="/2076-3417/12/18/9379">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Advances_in_Robotics_and_Mechatronics_for_Agriculture ">Advances in Robotics and Mechatronics for Agriculture</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9379/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919179"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919179"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919179" data-cycle-prev="#prev919179" data-cycle-progressive="#images919179" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919179-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g001-550.jpg?1663661546" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919179" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g002-550.jpg?1663661528'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g003-550.jpg?1663661526'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g004-550.jpg?1663661550'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g005-550.jpg?1663661552'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g006-550.jpg?1663661551'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g007-550.jpg?1663661553'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g008-550.jpg?1663661551'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g009-550.jpg?1663661541'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g010-550.jpg?1663661535'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g011-550.jpg?1663661531'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g012-550.jpg?1663661543'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g013-550.jpg?1663661548'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g014-550.jpg?1663661524'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-919179-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g015-550.jpg?1663661539'><p>Figure 15</p></div></script></div></div><div id="article-919179-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g001-550.jpg?1663661546" title=" <strong>Figure 1</strong><br/> <p>Example of a single dwarf citrus tree.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g002-550.jpg?1663661528" title=" <strong>Figure 2</strong><br/> <p>(<b>a</b>) The overall model of the CDTSR: (1) nozzle; (2) cable-driven manipulator control box; (3) pesticide box; (4) diaphragm pump; (5) inlet pipe; (6) track vehicle control box; (7) track vehicle; (8) outlet pipe; (9) cable-driven manipulator. (<b>b</b>) CAD drawings with different viewing angles of the CDTSR (the unit is mm).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g003-550.jpg?1663661526" title=" <strong>Figure 3</strong><br/> <p>(<b>a</b>) The overall model of the CDFM: (1) tendon; (2) support; (3) graphite copper sleeve; (4) shaft; (5) reel; (6) pulley; (7) cooling fan; (8) coupling; (9) stepper motor; (10)flange base; (11) connecting rod; (12) proximal arm segment; (13) distal arm segment; (14) cable locking. (<b>b</b>) CAD drawings with different viewing angles of the CDFM (the unit is mm).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g004-550.jpg?1663661550" title=" <strong>Figure 4</strong><br/> <p>(<b>a</b>) The model of two adjacent joints and cable rope arrangement on a disc. (<b>b</b>) CAD drawings with different viewing angles of the connecting rod (the unit is mm).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g005-550.jpg?1663661552" title=" <strong>Figure 5</strong><br/> <p>Multilevel mapping relationship of CDFM.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g006-550.jpg?1663661551" title=" <strong>Figure 6</strong><br/> <p>The kinematic model of a single joint.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g007-550.jpg?1663661553" title=" <strong>Figure 7</strong><br/> <p>Static analysis of CDFM.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g008-550.jpg?1663661551" title=" <strong>Figure 8</strong><br/> <p>The coordinate transformation from base coordinate to end coordinate.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g009-550.jpg?1663661541" title=" <strong>Figure 9</strong><br/> <p>The prototype of the CDTSR.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g010-550.jpg?1663661535" title=" <strong>Figure 10</strong><br/> <p>The working space of the CDFM.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g011-550.jpg?1663661531" title=" <strong>Figure 11</strong><br/> <p>(<b>a</b>) The reachable space and position of the CDFM; (<b>b</b>) dimensions of the model tree.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g012-550.jpg?1663661543" title=" <strong>Figure 12</strong><br/> <p>The operations in the narrow space between branches: (<b>a</b>) initial state; (<b>b</b>) intermediate state one; (<b>c</b>) intermediate state two; (<b>d</b>) final state.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g013-550.jpg?1663661548" title=" <strong>Figure 13</strong><br/> <p>The three states of the spray manipulator in spraying operations: (<b>a</b>) initial state of the spray manipulator; (<b>b</b>) spraying state of the spray manipulator for target 1; (<b>c</b>) spraying state of the spray manipulator for target 2.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g014-550.jpg?1663661524" title=" <strong>Figure 14</strong><br/> <p>The measurement experiment to test the droplet diameter.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09379/article_deploy/html/images/applsci-12-09379-g015-550.jpg?1663661539" title=" <strong>Figure 15</strong><br/> <p>Samples of coverage rates: (<b>a</b>) the coverage rate of the spraying center was 98.4%; (<b>b</b>) the coverage rate of the spraying margin was 64.3%.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9379'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918840" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 12061 KiB   </span> <a href="/2076-3417/12/18/9378/pdf?version=1663758648" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Applying Evolutionary Multitasking for Process Parameter Optimization in Polymerization Process of Carbon Fiber Production" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9378">Applying Evolutionary Multitasking for Process Parameter Optimization in Polymerization Process of Carbon Fiber Production</a> <div class="authors"> by <span class="inlineblock "><strong>Liang Jin</strong>, </span><span class="inlineblock "><strong>Zude Zhou</strong>, </span><span class="inlineblock "><strong>Kunlun Li</strong>, </span><span class="inlineblock "><strong>Guoliang Zhang</strong>, </span><span class="inlineblock "><strong>Quan Liu</strong>, </span><span class="inlineblock "><strong>Bitao Yao</strong> and </span><span class="inlineblock "><strong>Yilin Fang</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9378; <a href="https://doi.org/10.3390/app12189378">https://doi.org/10.3390/app12189378</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9378#metrics">Cited by 4</a> | Viewed by 1846 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Carbon fiber is becoming a key material for engineering applications due to its excellent comprehensive properties. The process parameter optimization is an important step in the polymerization process of carbon fiber production. At present, most of the research on process parameter optimization is <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9378/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Carbon fiber is becoming a key material for engineering applications due to its excellent comprehensive properties. The process parameter optimization is an important step in the polymerization process of carbon fiber production. At present, most of the research on process parameter optimization is usually carried out on a single production line, without considering the correlation between optimization problems. In this paper, a multiobjective mechanism model for the co-optimization of the polymerization process of carbon fiber production is established. Each of these submodels is a multiobjective process parameter optimization task, corresponding to the polymerization process of a production line. In order to solve the model effectively, we also designed an evolutionary multitasking algorithm based on transfer learning, which reuses the past experiences of one task to generate a population pool for the next iteration of another task, enabling explicit genetic transfer between different tasks and accelerating the population convergence speed. The proposed multitasking framework for operation optimization has been conducted on 10 different production conditions of the polymerization process. Experimental results show that compared with other implicit and explicit genetic algorithms, this algorithm is very competitive in generating effective solutions. This research provides important support for process parameter optimization and manufacturing of carbon fiber production, which will help engineers and technicians to make informed decisions. <a href="/2076-3417/12/18/9378">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9378/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918840"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918840"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918840" data-cycle-prev="#prev918840" data-cycle-progressive="#images918840" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918840-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g001-550.jpg?1663833805" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918840" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918840-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g002-550.jpg?1663833800'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918840-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g003-550.jpg?1663833807'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918840-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g004-550.jpg?1663833809'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-918840-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g005-550.jpg?1663833802'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-918840-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g006-550.jpg?1663833804'><p>Figure 6</p></div></script></div></div><div id="article-918840-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g001-550.jpg?1663833805" title=" <strong>Figure 1</strong><br/> <p>Carbon fiber production flow chart.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9378'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g002-550.jpg?1663833800" title=" <strong>Figure 2</strong><br/> <p>Schematic diagram of polymerization unit.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9378'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g003-550.jpg?1663833807" title=" <strong>Figure 3</strong><br/> <p>Flow chart of the proposed Tr-EGT.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9378'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g004-550.jpg?1663833809" title=" <strong>Figure 4</strong><br/> <p>Average HV numerical curves of NSGA-II, MO-MFEA, EMT-EGT and Tr-EGT over 20 independent runs on task<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9378'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g005-550.jpg?1663833802" title=" <strong>Figure 5</strong><br/> <p>Average HV numerical curves of NSGA-II, MO-MFEA, EMT-EGT and Tr-EGT over 20 independent runs on task<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9378'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09378/article_deploy/html/images/applsci-12-09378-g006-550.jpg?1663833804" title=" <strong>Figure 6</strong><br/> <p>The average approximate PF was obtained by the multitask algorithms under Conditions 1, 7, and 8 over 20 runs in task<math display="inline"><semantics> <msub> <mrow/> <mn>1</mn> </msub> </semantics></math> and task<math display="inline"><semantics> <msub> <mrow/> <mn>2</mn> </msub> </semantics></math>.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9378'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="919074" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 4288 KiB   </span> <a href="/2076-3417/12/18/9377/pdf?version=1663652263" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Improving IoT Data Security and Integrity Using Lightweight Blockchain Dynamic Table" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9377">Improving IoT Data Security and Integrity Using Lightweight Blockchain Dynamic Table</a> <div class="authors"> by <span class="inlineblock "><strong>Saleem S. Hameedi</strong> and </span><span class="inlineblock "><strong>Oguz Bayat</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9377; <a href="https://doi.org/10.3390/app12189377">https://doi.org/10.3390/app12189377</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9377#metrics">Cited by 10</a> | Viewed by 2894 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Over the past few years, the Internet of Things (IoT) is one of the most significant technologies ever used, as everything is connected to the Internet. Integrating IoT technologies with the cloud improves the performance, activity, and innovation of such a system. However, <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9377/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Over the past few years, the Internet of Things (IoT) is one of the most significant technologies ever used, as everything is connected to the Internet. Integrating IoT technologies with the cloud improves the performance, activity, and innovation of such a system. However, one of the major problems which cannot be ignored in such integration is the security of the data that are transferred between the client (IoT) and the server (cloud). Solving that problem leads to the use the of IoT technologies in more critical applications and fields. This paper proposes a new security framework by combining blockchain technology with the AES algorithm. Blockchain technology is used and modified to protect data integrity and generate unique device identification within minimal power consumption and best performance. The AES algorithm is used to improve the data confidentiality when being transmitted to the server. The outcomes demonstrated that the proposed solution improves the security system of the IoT healthcare data and proved its efficiency and power consumption compared to other methods. <a href="/2076-3417/12/18/9377">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Internet_of_Things_Things ">Advances in Blockchain-enabled Internet of Things (IoT)</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9377/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev919074"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next919074"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next919074" data-cycle-prev="#prev919074" data-cycle-progressive="#images919074" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-919074-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g001-550.jpg?1663661506" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images919074" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g002-550.jpg?1663661503'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g003-550.jpg?1663661513'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g004-550.jpg?1663661509'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g005-550.jpg?1663661499'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g006-550.jpg?1663661502'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g007-550.jpg?1663661496'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g008-550.jpg?1663661504'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g009-550.jpg?1663661510'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g010-550.jpg?1663661500'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-919074-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g011-550.jpg?1663661514'><p>Figure 11</p></div></script></div></div><div id="article-919074-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g001-550.jpg?1663661506" title=" <strong>Figure 1</strong><br/> <p>Blockchain architecture.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g002-550.jpg?1663661503" title=" <strong>Figure 2</strong><br/> <p>Blockchain ledger.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g003-550.jpg?1663661513" title=" <strong>Figure 3</strong><br/> <p>Dynamic blockchain table architecture.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g004-550.jpg?1663661509" title=" <strong>Figure 4</strong><br/> <p>Multiple AES encryption architecture.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g005-550.jpg?1663661499" title=" <strong>Figure 5</strong><br/> <p>Key exchange mechanism.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g006-550.jpg?1663661502" title=" <strong>Figure 6</strong><br/> <p>Z1 IoT device.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g007-550.jpg?1663661496" title=" <strong>Figure 7</strong><br/> <p>Time Overhead evaluation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g008-550.jpg?1663661504" title=" <strong>Figure 8</strong><br/> <p>Energy consumption overhead (CPU and Tx).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g009-550.jpg?1663661510" title=" <strong>Figure 9</strong><br/> <p>Energy consumption overhead (Lx).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g010-550.jpg?1663661500" title=" <strong>Figure 10</strong><br/> <p>Energy consumption overhead (CPU and Tx) of healthcare application.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09377/article_deploy/html/images/applsci-12-09377-g011-550.jpg?1663661514" title=" <strong>Figure 11</strong><br/> <p>Energy consumption overhead (Lx) of healthcare application.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9377'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918795" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 470 KiB   </span> <a href="/2076-3417/12/18/9376/pdf?version=1663770068" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Target-Oriented Teaching Path Planning with Deep Reinforcement Learning for Cloud Computing-Assisted Instructions" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9376">Target-Oriented Teaching Path Planning with Deep Reinforcement Learning for Cloud Computing-Assisted Instructions</a> <div class="authors"> by <span class="inlineblock "><strong>Tengjie Yang</strong>, </span><span class="inlineblock "><strong>Lin Zuo</strong>, </span><span class="inlineblock "><strong>Xinduoji Yang</strong> and </span><span class="inlineblock "><strong>Nianbo Liu</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9376; <a href="https://doi.org/10.3390/app12189376">https://doi.org/10.3390/app12189376</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9376#metrics">Cited by 1</a> | Viewed by 1945 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In recent years, individual learning path planning has become prevalent in online learning systems, while few studies have focused on teaching path planning for traditional classroom teaching. This paper proposes a target-oriented teaching path optimization scheme for cloud computing-assisted instructions, in which a <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9376/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In recent years, individual learning path planning has become prevalent in online learning systems, while few studies have focused on teaching path planning for traditional classroom teaching. This paper proposes a target-oriented teaching path optimization scheme for cloud computing-assisted instructions, in which a sequence of learning contents is arranged to ensure the maximum benefit for a given group of students. First, to evaluate the teaching performance, we investigate various student models and define some teaching objectives, including the pass rate, the excellence rate, the average score, and related constraints. Second, a new Deep Reinforcement Learning (DRL)-based teaching path planning method is proposed to tackle the learning path by maximizing a multi-objective target while satisfying all teaching constraints. It adopts a Proximal Policy Optimization (PPO) framework to find a model-free solution for achieving fast convergence and better optimality. Finally, extensive simulations with a variety of commonly used teaching methods show that our scheme provides nice performance and versatility over commonly used student models. <a href="/2076-3417/12/18/9376">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/New_Engineering_in_Cloud_Computing_and_Cloud_Data ">New Engineering in Cloud Computing and Cloud Data</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9376/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918795"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918795"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918795" data-cycle-prev="#prev918795" data-cycle-progressive="#images918795" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918795-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09376/article_deploy/html/images/applsci-12-09376-g001-550.jpg?1663770137" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918795" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918795-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09376/article_deploy/html/images/applsci-12-09376-g002-550.jpg?1663770139'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918795-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09376/article_deploy/html/images/applsci-12-09376-g003-550.jpg?1663770140'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918795-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09376/article_deploy/html/images/applsci-12-09376-g004-550.jpg?1663770136'><p>Figure 4</p></div></script></div></div><div id="article-918795-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09376/article_deploy/html/images/applsci-12-09376-g001-550.jpg?1663770137" title=" <strong>Figure 1</strong><br/> <p>Partially observable Markov decision process [<a href="#B8-applsci-12-09376" class="html-bibr">8</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9376'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09376/article_deploy/html/images/applsci-12-09376-g002-550.jpg?1663770139" title=" <strong>Figure 2</strong><br/> <p>(I) The teacher teaches a knowledge point; (II) The students study it with the changes in their student states; (III) The results of in-class and off-class tests for students are observed. During the continuous teaching process, a knowledge point chain, a student state chain, and a student test result chain are formed.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9376'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09376/article_deploy/html/images/applsci-12-09376-g003-550.jpg?1663770140" title=" <strong>Figure 3</strong><br/> <p>Clip function.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9376'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09376/article_deploy/html/images/applsci-12-09376-g004-550.jpg?1663770136" title=" <strong>Figure 4</strong><br/> <p>PPO: (I) Sampling by actor; (II) the collected data are sampled again and passed to the actor and critic; and (III) updating through the two different loss functions.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9376'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918784" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-918784" aria-controls="drop-supplementary-918784" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-918784" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2076-3417/12/18/9375/s1?version=1663586945"> Supplementary File 1 (ZIP, 11 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 1977 KiB   </span> <a href="/2076-3417/12/18/9375/pdf?version=1663586944" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Particulate Matter Concentrations and Fungal Aerosol in Horse Stables as Potential Causal Agents in Recurrent Airway Disease in Horses and Human Asthma and Allergies" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9375">Particulate Matter Concentrations and Fungal Aerosol in Horse Stables as Potential Causal Agents in Recurrent Airway Disease in Horses and Human Asthma and Allergies</a> <div class="authors"> by <span class="inlineblock "><strong>Anna Lenart-Boroń</strong>, </span><span class="inlineblock "><strong>Anna Bajor</strong>, </span><span class="inlineblock "><strong>Marek Tischner</strong>, </span><span class="inlineblock "><strong>Klaudia Kulik</strong> and </span><span class="inlineblock "><strong>Julia Kabacińska</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9375; <a href="https://doi.org/10.3390/app12189375">https://doi.org/10.3390/app12189375</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9375#metrics">Cited by 3</a> | Viewed by 1933 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Exposure to bioaerosols associated with horse stable indoor environment and their health effects on people and horses has recently become of particular interest. Moreover, increasing frequency of recurrent airway disease (RAO) among horses made it necessary to search for the most probable causal <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9375/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Exposure to bioaerosols associated with horse stable indoor environment and their health effects on people and horses has recently become of particular interest. Moreover, increasing frequency of recurrent airway disease (RAO) among horses made it necessary to search for the most probable causal agents of this disease and methods of their eradication. The study was conducted in two horse stables in southern Poland (Kraków and Tarnów). Particulate matter (PM<sub>2.5</sub>, PM<sub>4</sub>, and PM<sub>10</sub>) concentrations were determined photometrically, the concentration of fungal aerosol was determined by a six-stage impactor, and next generation sequencing (NGS) was used to determine fungal community composition in one of these stables. The highest PM concentrations were observed in Tarnów, but fungal aerosol levels were higher in the Kraków stable. Based on the NGS results, the three most prevalent fungal species were <i>Wallemia sebi</i>, <i>Aspergillus penicillioides</i>, and <i>Epicoccum nigrum</i>, all highly allergenic and potentially involved in the occurrence of RAO in horses. Spores of the detected fungi can penetrate deeply into the respiratory system. Therefore, this study suggests that examinations of particulate matter and fungal aerosol concentrations, along with species composition assessment, should be regularly conducted in horse stables. <a href="/2076-3417/12/18/9375">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Fungi_Indoor_Environments_Materials ">Fungi Associated with Indoor Environments and Materials</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9375/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918784"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918784"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918784" data-cycle-prev="#prev918784" data-cycle-progressive="#images918784" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918784-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g001-550.jpg?1663587015" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918784" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918784-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g002-550.jpg?1663587021'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918784-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g003-550.jpg?1663587019'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918784-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g004-550.jpg?1663587017'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-918784-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g005-550.jpg?1663587012'><p>Figure 5</p></div></script></div></div><div id="article-918784-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g001-550.jpg?1663587015" title=" <strong>Figure 1</strong><br/> <p>(<b>A</b>). Location and schematic presentation of the Kraków stable. (<b>B</b>). Location and schematic presentation of the Tarnów stable.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9375'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g002-550.jpg?1663587021" title=" <strong>Figure 2</strong><br/> <p>Share (%) of different aerodynamic diameters of airborne fungi in the Kraków (<b>A</b>) and Tarnów (<b>B</b>) horse stables at different times of the day (M—early morning-no activity; F—feeding; I.B.—indoor background, mid-day; A—afternoon, animals return; O.B.—outdoor background).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9375'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g003-550.jpg?1663587019" title=" <strong>Figure 3</strong><br/> <p>Relative abundance (%) of fungal species, the share of which in the total number of reads exceeded 0.2% (<b>A</b>) and 10 most abundant fungal genera in the examined sample (<b>B</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9375'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g004-550.jpg?1663587017" title=" <strong>Figure 4</strong><br/> <p>Concentration of total fungal aerosol (CFU/m<sup>3</sup>) in different times of day compared with the inhalable particulate matter concentration (PM<sub>10</sub>; µg/m<sup>3</sup>). Kraków (<b>A</b>) and Tarnów (<b>B</b>) horse stables.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9375'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09375/article_deploy/html/images/applsci-12-09375-g005-550.jpg?1663587012" title=" <strong>Figure 5</strong><br/> <p>Concentration of respirable fungal aerosol (CFU/m<sup>3</sup>) at different times of the day compared with the concentration of respirable particulate matter (µg/m<sup>3</sup>). Kraków (<b>A</b>) and Tarnów (<b>B</b>) horse stables.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9375'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918768" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 12 pages, 5402 KiB   </span> <a href="/2076-3417/12/18/9374/pdf?version=1663586497" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Novel Method for Monitoring Mining Subsidence Featuring Co-Registration of UAV LiDAR Data and Photogrammetry" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9374">Novel Method for Monitoring Mining Subsidence Featuring Co-Registration of UAV LiDAR Data and Photogrammetry</a> <div class="authors"> by <span class="inlineblock "><strong>Jibo Liu</strong>, </span><span class="inlineblock "><strong>Xiaoyu Liu</strong>, </span><span class="inlineblock "><strong>Xieyu Lv</strong>, </span><span class="inlineblock "><strong>Bo Wang</strong> and </span><span class="inlineblock "><strong>Xugang Lian</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9374; <a href="https://doi.org/10.3390/app12189374">https://doi.org/10.3390/app12189374</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9374#metrics">Cited by 9</a> | Viewed by 2376 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combination with LiDAR. A dynamic subsidence basin based <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9374/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Addressing the problem that traditional methods cannot reliably monitor surface subsidence in coal mining, a novel method has been developed for monitoring subsidence in mining areas using time series unmanned aerial vehicle (UAV) photogrammetry in combination with LiDAR. A dynamic subsidence basin based on the differential digital elevation model (DEM) was constructed and accuracy of the proposed method was verified, with the uncertainty of the DEM of difference (DoD) being quantified via co-registration of a dense matching point cloud of the time series UAV data. The root mean square error calculated for the monitoring points on the subsidence DEM was typically between 0.2 m and 0.3 m with a minimum of 0.17 m. The relative error between the maximum subsidence value of the extracted profile line on the main section after fitting and the measured maximum subsidence value was not more than 20%, and the minimum value was 0.7%. The accuracy of the UAV based method was at the decimeter level, and high accuracy in monitoring the maximum subsidence value was attained, confirming that an innovative strategy for monitoring mining subsidence was realized. <a href="/2076-3417/12/18/9374">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/9FW0YF7JO7 ">Advances, Challenges and Applications in Unmanned Aerial Vehicle Remote Sensing Techniques</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9374/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918768"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918768"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918768" data-cycle-prev="#prev918768" data-cycle-progressive="#images918768" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918768-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g001-550.jpg?1663586569" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918768" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918768-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g002-550.jpg?1663586575'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918768-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g003-550.jpg?1663586573'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918768-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g004-550.jpg?1663586571'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-918768-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g005-550.jpg?1663586565'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-918768-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g006-550.jpg?1663586566'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-918768-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g007-550.jpg?1663586576'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-918768-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g008-550.jpg?1663586570'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-918768-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g009-550.jpg?1663586563'><p>Figure 9</p></div></script></div></div><div id="article-918768-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g001-550.jpg?1663586569" title=" <strong>Figure 1</strong><br/> <p>Schematic for relationship between the working face, observation stations, and study area.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g002-550.jpg?1663586575" title=" <strong>Figure 2</strong><br/> <p>The flow chart for subsidence monitoring via UAV.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g003-550.jpg?1663586573" title=" <strong>Figure 3</strong><br/> <p>Selection of the stable region: (<b>a</b>) stable zone for collaborative registration; and (<b>b</b>) number of overlapping images computed for each pixel of the DOM.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g004-550.jpg?1663586571" title=" <strong>Figure 4</strong><br/> <p>Histogram of the M3C2 distance: (<b>a</b>) LiDAR01.16−UAV06.14; (<b>b</b>) LiDAR01.16−UAV07.20; (<b>c</b>) LiDAR01.16−UAV09.07; (<b>d</b>) LiDAR01.16−UAV11.15; and (<b>e</b>) LiDAR01.16−UAV07.31.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g005-550.jpg?1663586565" title=" <strong>Figure 5</strong><br/> <p>Development process for the dynamic subsidence basin at the working face: (<b>a</b>) 1−06.14; (<b>b</b>) 2−07.20; (<b>c</b>) 3−09.07; (<b>d</b>) 4−11.15; (<b>e</b>) 5−07.31; (<b>f</b>) 1−2; (<b>g</b>) 2−3; (<b>h</b>) 3−4; (<b>i</b>) 4−5; (<b>j</b>) 1−2; (<b>k</b>) 1−3; (<b>l</b>) 1−4; and (<b>m</b>) 1−5.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g006-550.jpg?1663586566" title=" <strong>Figure 6</strong><br/> <p>Comparison of subsidence values about the monitoring points: (<b>a</b>) line A 07.20−06.14; (<b>b</b>) line A 09.07−06.14; (<b>c</b>) line A 11.15−06.14; (<b>d</b>) line A 07.31−06.14; (<b>e</b>) line B 07.20−06.14; (<b>f</b>) line B 09.07−06.14; (<b>g</b>) line B 11.15−06.14; and (<b>h</b>) line B 07.31−06.14.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g007-550.jpg?1663586576" title=" <strong>Figure 7</strong><br/> <p>Curve fitting of subsidence and scattered points on the profile line: (<b>a</b>) strike 07.20−06.14; (<b>b</b>) strike 09.07−06.14; (<b>c</b>) strike 11.15−06.14; (<b>d</b>) strike 07.31−06.14; (<b>e</b>) dip 07.20−06.14; (<b>f</b>) dip 09.07−06.14; (<b>g</b>) dip 11.15−06.14; and (<b>h</b>) dip 07.31−06.14.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g008-550.jpg?1663586570" title=" <strong>Figure 8</strong><br/> <p>Time series subsidence curve for the main section: (<b>a</b>) strike subsidence curve fitting; and (<b>b</b>) dip subsidence curve fitting.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09374/article_deploy/html/images/applsci-12-09374-g009-550.jpg?1663586563" title=" <strong>Figure 9</strong><br/> <p>MinLoD threshold assessment of the significance for the variability in the DoD elevation: (<b>a</b>) minlod = 0.00 m; (<b>b</b>) minlod = 0.10 m; and (<b>c</b>) minlod = 0.20 m.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9374'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918730" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 24 pages, 7443 KiB   </span> <a href="/2076-3417/12/18/9373/pdf?version=1663663806" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Proposed New Analytical Method of Tower Load in Large-Span Arch Bridge Cable Lifting Construction" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9373">Proposed New Analytical Method of Tower Load in Large-Span Arch Bridge Cable Lifting Construction</a> <div class="authors"> by <span class="inlineblock "><strong>Qian Huang</strong>, </span><span class="inlineblock "><strong>Xiaoguang Wu</strong>, </span><span class="inlineblock "><strong>Yunfei Zhang</strong> and </span><span class="inlineblock "><strong>Min Ma</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9373; <a href="https://doi.org/10.3390/app12189373">https://doi.org/10.3390/app12189373</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9373#metrics">Cited by 8</a> | Viewed by 2447 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The cable lifting construction method is the most widely used construction method for large-span arch bridges. The correct calculation and analysis of cable lifting construction is essential to ensure the safety and linearity in the construction of arch bridges. The existing research mainly <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9373/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The cable lifting construction method is the most widely used construction method for large-span arch bridges. The correct calculation and analysis of cable lifting construction is essential to ensure the safety and linearity in the construction of arch bridges. The existing research mainly focuses on the construction scheme and finite element analysis of cable lifting for large-span arch bridges. There is relatively little research on calculation theory, and there is no analytical method for cable lifting construction of arch bridges. To calculate and analyze cable lifting construction more quickly and accurately, based on the deformation coordination principle and suspension cable theory, a practical calculation method is proposed to calculate the load of the tower acting by a cable system in the cable lifting construction of arch bridges. A large-span arch bridge under construction was used as a case study, and the correctness of the calculation method was verified by measuring the displacements of the tower top. A brief description of the structure, verification method, and verification process is presented. The displacement results are calculated by the numerical calculation software SAP2000, the actual measured displacement data are discussed and comparatively analyzed, and the correctness and calculation accuracy of the proposed calculation method are also evaluated. The results show that the calculation method has sufficient accuracy. The tower load calculation is mainly undertaken to prepare for the analysis of the tower mechanical properties; therefore, the calculation method is applied to towers of the case engineering, and the stability, load carrying capacity, and deformation of the tower are analyzed to verify whether its mechanical properties meet the engineering requirements. The results show that steel pipe columns of the buckle tower are prone to twisting instability. The normal stress of the tower’s part of the pressurized rod or pressurized bending rod is larger. Wind cable load calculation models and tower design-related recommendations are presented in this tower analysis. The tower load calculation method and tower mechanics analysis method in this study can provide guidance for the calculation and analysis of the cable lifting construction of large-span arch bridges. <a href="/2076-3417/12/18/9373">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/bridge_design_construction ">Advanced Technologies for Bridge Design and Construction</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9373/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918730"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918730"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" 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src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g003-550.jpg?1663663900'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g004-550.jpg?1663663891'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g005a-550.jpg?1663663897'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g005b-550.jpg?1663663881'><p>Figure 5 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g006-550.jpg?1663663873'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g007-550.jpg?1663663880'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g008-550.jpg?1663663878'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g009-550.jpg?1663663886'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g010-550.jpg?1663663902'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g011-550.jpg?1663663874'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g012-550.jpg?1663663894'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g013-550.jpg?1663663895'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g014-550.jpg?1663663897'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g015-550.jpg?1663663890'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g016-550.jpg?1663663888'><p>Figure 16</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g017-550.jpg?1663663883'><p>Figure 17</p></div> --- <div class='openpopupgallery' data-imgindex='18' data-target='article-918730-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g018-550.jpg?1663663892'><p>Figure 18</p></div></script></div></div><div id="article-918730-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g001-550.jpg?1663663876" title=" <strong>Figure 1</strong><br/> <p>Cable lifting construction of large-span arch bridges: (<b>a</b>) Pingnan Third Bridge; (<b>b</b>) Jinghe Bridge.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g002-550.jpg?1663663901" title=" <strong>Figure 2</strong><br/> <p>Simplified model of cable lifting system.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g003-550.jpg?1663663900" title=" <strong>Figure 3</strong><br/> <p>Schematic diagram for calculating the forces acting on the towers from the main cable: (<b>a</b>) empty cable; (<b>b</b>) cable carrying load.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g004-550.jpg?1663663891" title=" <strong>Figure 4</strong><br/> <p>Calculation diagram of the acting force of lifting cable on tower.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g005a-550.jpg?1663663897" title=" <strong>Figure 5</strong><br/> <p>Schematic diagram of calculating the forces acting on a tower from a towing cable: (<b>a</b>) left bank; (<b>b</b>) right bank.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g005b-550.jpg?1663663881" title=" <strong>Figure 5 Cont.</strong><br/> <p>Schematic diagram of calculating the forces acting on a tower from a towing cable: (<b>a</b>) left bank; (<b>b</b>) right bank.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g006-550.jpg?1663663873" title=" <strong>Figure 6</strong><br/> <p>Overall layout of cable lifting system.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g007-550.jpg?1663663880" title=" <strong>Figure 7</strong><br/> <p>Overall numerical calculation model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g008-550.jpg?1663663878" title=" <strong>Figure 8</strong><br/> <p>Numerical calculation model of tower: (<b>a</b>) tower; (<b>b</b>) distribution beam at top of cable tower; (<b>c</b>) steel pipe column and universal rods; (<b>d</b>) universal rods; (<b>e</b>) distribution beam at top of buckle tower; (<b>f</b>) hinge seat distribution beam.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g009-550.jpg?1663663886" title=" <strong>Figure 9</strong><br/> <p>Tower and measurement point layouts for engineering case: (<b>a</b>) left bank; (<b>b</b>) right bank.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g010-550.jpg?1663663902" title=" <strong>Figure 10</strong><br/> <p>Deformation of tower at right bank (unit: mm): (<b>a</b>) Load 1; (<b>b</b>) Load 2; (<b>c</b>) Load 3.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g011-550.jpg?1663663874" title=" <strong>Figure 11</strong><br/> <p>Buckle cables acting on the tower.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g012-550.jpg?1663663894" title=" <strong>Figure 12</strong><br/> <p>First six orders of buckling mode characteristics of towers: (<b>a</b>) buckling mode 1; (<b>b</b>) buckling mode 2; (<b>c</b>) buckling mode 3; (<b>d</b>) buckling mode 4; (<b>e</b>) buckling mode 5; and (<b>f</b>) buckling mode 6.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g013-550.jpg?1663663895" title=" <strong>Figure 13</strong><br/> <p>Maximum axial force diagram of the universal rods of the tower located on the right bank: (<b>a</b>) cable tower; (<b>b</b>) buckle tower.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g014-550.jpg?1663663897" title=" <strong>Figure 14</strong><br/> <p>Location and number of steel pipe columns of the tower at the right bank.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g015-550.jpg?1663663890" title=" <strong>Figure 15</strong><br/> <p>Normal stress of steel pipe column under each load condition.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g016-550.jpg?1663663888" title=" <strong>Figure 16</strong><br/> <p>The changing tendency of normal stress with height for steel pipe columns: (<b>a</b>) No. 11 steel pipe column; (<b>b</b>) No. 7 steel pipe column.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g017-550.jpg?1663663883" title=" <strong>Figure 17</strong><br/> <p>Maximum displacement of the tower top under each load condition: (<b>a</b>) left bank; (<b>b</b>) right bank.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09373/article_deploy/html/images/applsci-12-09373-g018-550.jpg?1663663892" title=" <strong>Figure 18</strong><br/> <p>Deformation of the steel pipe columns along the longitudinal direction of the bridge.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9373'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918714" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <a data-dropdown="drop-supplementary-918714" aria-controls="drop-supplementary-918714" aria-expanded="false" title="Supplementary Material"> <i class="material-icons">attachment</i> </a> <div id="drop-supplementary-918714" class="f-dropdown label__btn__dropdown label__btn__dropdown--wide" data-dropdown-content aria-hidden="true" tabindex="-1"> Supplementary material: <br/> <a href="/2076-3417/12/18/9372/s1?version=1663585152"> Supplementary File 1 (ZIP, 178 KiB) </a><br/> </div> </div> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 1741 KiB   </span> <a href="/2076-3417/12/18/9372/pdf?version=1663750549" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Comparison of Methods to Identify and Monitor Mold Damages in Buildings" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9372">Comparison of Methods to Identify and Monitor Mold Damages in Buildings</a> <div class="authors"> by <span class="inlineblock "><strong>Pedro Maria Martin-Sanchez</strong>, </span><span class="inlineblock "><strong>Maria Nunez</strong>, </span><span class="inlineblock "><strong>Eva Lena Fjeld Estensmo</strong>, </span><span class="inlineblock "><strong>Inger Skrede</strong> and </span><span class="inlineblock "><strong>Håvard Kauserud</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9372; <a href="https://doi.org/10.3390/app12189372">https://doi.org/10.3390/app12189372</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9372#metrics">Cited by 4</a> | Viewed by 4753 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Molds thrive in indoor environments, challenging the stability of building materials and occupants’ health. Diverse sampling and analytical techniques can be applied in the microbiology of buildings, with specific benefits and drawbacks. We evaluated the use of two methods, the microscopy of visible <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9372/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Molds thrive in indoor environments, challenging the stability of building materials and occupants’ health. Diverse sampling and analytical techniques can be applied in the microbiology of buildings, with specific benefits and drawbacks. We evaluated the use of two methods, the microscopy of visible mold growth (hereinafter “mold” samples) (tape lifts) and the DNA metabarcoding of mold and dust samples (swabs), for mapping mold-damage indicator fungi in residential buildings in Oslo. Overall, both methods provided consistent results for the mold samples, where nearly 80% of the microscopy-identified taxa were confirmed by DNA analyses. <i>Aspergillus</i> was the most abundant genus colonizing all materials, while some taxa were associated with certain substrates: <i>Acremonium</i> with gypsum board, <i>Chaetomium</i> with chipboard, <i>Stachybotrys</i> with gypsum board and wood, and <i>Trichoderma</i> with wood. Based on the DNA data, the community composition was clearly different between the mold and the dust, with a much higher alpha diversity in the dust. Most genera identified in the mold were also detected with a low abundance in the dust from the same apartments. Their spatial distribution indicated some local spread from the mold growth to other areas, but there was no clear correlation between the relative abundances and the distance to the damages. To study mold damages, different microbiological analyses (microscopy, cultivation, DNA, and chemistry) should be combined with a thorough inspection of buildings. The interpretation of such datasets requires the collaboration of skilled mycologists and building consultants. <a href="/2076-3417/12/18/9372">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Fungi_Indoor_Environments_Materials ">Fungi Associated with Indoor Environments and Materials</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9372/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918714"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918714"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918714" data-cycle-prev="#prev918714" data-cycle-progressive="#images918714" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918714-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09372/article_deploy/html/images/applsci-12-09372-g001-550.jpg?1663750648" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918714" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918714-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09372/article_deploy/html/images/applsci-12-09372-g002-550.jpg?1663750650'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918714-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09372/article_deploy/html/images/applsci-12-09372-g003-550.jpg?1663750654'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918714-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09372/article_deploy/html/images/applsci-12-09372-g004-550.jpg?1663750653'><p>Figure 4</p></div></script></div></div><div id="article-918714-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09372/article_deploy/html/images/applsci-12-09372-g001-550.jpg?1663750648" title=" <strong>Figure 1</strong><br/> <p>Sampling of mold and dust in this study. (<b>a</b>) Mold-damaged gypsum board where M62-M64 samples were collected; (<b>b</b>) mold growing on wood, sample M65; (<b>c</b>) tape lifts taken directly on discoloration of building materials; (<b>d</b>) dust sample collected by swabbing the upper doorframe, picture extracted from Martin-Sanchez et al. [<a href="#B22-applsci-12-09372" class="html-bibr">22</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9372'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09372/article_deploy/html/images/applsci-12-09372-g002-550.jpg?1663750650" title=" <strong>Figure 2</strong><br/> <p>Comparison of dust and mold mycobiota, as revealed by DNA metabarcoding: (<b>a</b>) NMDS plot showing the differences in the fungal community composition of 42 dust samples and 48 mold samples; (<b>b</b>) variation of the alpha diversity indices; (<b>c</b>) the most abundant fungal genera (RA ≥ 2%) identified in each sample type. Note that the genus <span class="html-italic">Serpula</span> was initially misidentified as <span class="html-italic">Austropaxillus</span> in the first automatic taxonomic assignment (<b>*</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9372'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09372/article_deploy/html/images/applsci-12-09372-g003-550.jpg?1663750654" title=" <strong>Figure 3</strong><br/> <p>Mold mycobiota, as revealed by DNA metabarcoding: (<b>a</b>) NMDS plot comparing the fungal community composition in 48 mold samples collected from different materials; (<b>b</b>) the most abundant fungal genera (RA ≥ 5%) identified in the mold samples collected from different materials, excluding those materials represented by a single sample, i.e., concrete, paint, and plastic.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9372'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09372/article_deploy/html/images/applsci-12-09372-g004-550.jpg?1663750653" title=" <strong>Figure 4</strong><br/> <p>Venn diagrams showing the overlap in distribution of OTUs across sample types (dust and mold). (<b>a</b>) Mean percentage of overlapping and unique OTUs (with standard deviations), calculated on an apartment-by-apartment basis for the 11 apartments that included dust samples from both damaged and central rooms; (<b>b</b>) the same kind of data as “a” but calculated for the 25 apartments that only include dust from the damaged rooms; (<b>c</b>) overall percentages and number of OTUs (in parenthesis) for the same 25 apartments as “b”, without separated calculations by apartment.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9372'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918734" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 5304 KiB   </span> <a href="/2076-3417/12/18/9371/pdf?version=1663585783" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Supervised Learning-Based Image Classification for the Detection of Late Blight in Potato Crops" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9371">Supervised Learning-Based Image Classification for the Detection of Late Blight in Potato Crops</a> <div class="authors"> by <span class="inlineblock "><strong>Marco Javier Suarez Baron</strong>, </span><span class="inlineblock "><strong>Angie Lizeth Gomez</strong> and </span><span class="inlineblock "><strong>Jorge Enrique Espindola Diaz</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9371; <a href="https://doi.org/10.3390/app12189371">https://doi.org/10.3390/app12189371</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9371#metrics">Cited by 16</a> | Viewed by 2234 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> This article presents the application of supervised learning and image classification for the early detection of late blight disease in potato using convolutional neural network and support vector machine SVM. The study was realized in the Boyacá department, Colombia. An initial dataset is <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9371/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> This article presents the application of supervised learning and image classification for the early detection of late blight disease in potato using convolutional neural network and support vector machine SVM. The study was realized in the Boyacá department, Colombia. An initial dataset is created with the acquisition of a large number of images directly from the crops. These images are pre-processed in order to extract the main characteristics of the late blight disease. A classification model is developed to identify the potato plants as healthy or infected. Several performance, efficiency, and quality metrics were applied in the learning and classification tasks to determine the best machine learning algorithms. Then, an additional data set was used for validation, image classification, and detection of late blight disease in potato crops in the department of Boyacá, Colombia. The results obtained in the AUC curve show that the CNN trained with the data set obtained an AUC equal to 0.97; and the analysis through SVM obtained an AUC equal to 0.87. Future work requires the development of a mobile application with advanced features as a technological tool for precision agriculture that supports farmers with increased agricultural productivity. <a href="/2076-3417/12/18/9371">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/computer_vision_pattern_recognition ">Computer Vision and Pattern Recognition Based on Deep Learning</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9371/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918734"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918734"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918734" data-cycle-prev="#prev918734" data-cycle-progressive="#images918734" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918734-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g001-550.jpg?1663585862" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918734" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g002-550.jpg?1663585858'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g003-550.jpg?1663585864'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g004-550.jpg?1663585855'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g005-550.jpg?1663585864'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g006-550.jpg?1663585856'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g007-550.jpg?1663585852'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g008-550.jpg?1663585859'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g009-550.jpg?1663585860'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g010-550.jpg?1663585854'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g011-550.jpg?1663585863'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g012-550.jpg?1663585857'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g013-550.jpg?1663585861'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-918734-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g014-550.jpg?1663585851'><p>Figure 14</p></div></script></div></div><div id="article-918734-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g001-550.jpg?1663585862" title=" <strong>Figure 1</strong><br/> <p>The flowchart of the methodology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g002-550.jpg?1663585858" title=" <strong>Figure 2</strong><br/> <p>Functional architecture.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g003-550.jpg?1663585864" title=" <strong>Figure 3</strong><br/> <p>Samples of the data set used. (<b>A</b>) Healthy leaves, (<b>B</b>) leaves infected with late blight.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g004-550.jpg?1663585855" title=" <strong>Figure 4</strong><br/> <p>Input image and output images of the data augmentation algorithm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g005-550.jpg?1663585864" title=" <strong>Figure 5</strong><br/> <p>Transformation to HSV, LAB, and grayscale space.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g006-550.jpg?1663585856" title=" <strong>Figure 6</strong><br/> <p>Result obtained from the application of segmentation algorithm.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g007-550.jpg?1663585852" title=" <strong>Figure 7</strong><br/> <p>Result obtained from the application of Range Threshold Segmentation.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g008-550.jpg?1663585859" title=" <strong>Figure 8</strong><br/> <p>Proposed CNN Architecture.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g009-550.jpg?1663585860" title=" <strong>Figure 9</strong><br/> <p>Prototype design for diagnostic visualization of a leaf from an image.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g010-550.jpg?1663585854" title=" <strong>Figure 10</strong><br/> <p>Prototype designs of obtained data visualization for administrators.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g011-550.jpg?1663585863" title=" <strong>Figure 11</strong><br/> <p>Confusion Matrices of the CNN Models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g012-550.jpg?1663585857" title=" <strong>Figure 12</strong><br/> <p>Confusion Matrices of Support Vector Machine (SVM) Models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g013-550.jpg?1663585861" title=" <strong>Figure 13</strong><br/> <p>ROC curve of convolutional neural network (CNN) models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09371/article_deploy/html/images/applsci-12-09371-g014-550.jpg?1663585851" title=" <strong>Figure 14</strong><br/> <p>ROC curves of the Support Vector Machine (SVM) models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9371'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918641" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 14 pages, 4293 KiB   </span> <a href="/2076-3417/12/18/9370/pdf?version=1663583379" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Intelligent Timber Damage Monitoring Using PZT-Enabled Active Sensing and Intrinsic Multiscale Entropy Analysis" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9370">Intelligent Timber Damage Monitoring Using PZT-Enabled Active Sensing and Intrinsic Multiscale Entropy Analysis</a> <div class="authors"> by <span class="inlineblock "><strong>Shuai Guo</strong>, </span><span class="inlineblock "><strong>Tong Shen</strong>, </span><span class="inlineblock "><strong>Li Li</strong>, </span><span class="inlineblock "><strong>Huangxing Hu</strong>, </span><span class="inlineblock "><strong>Jicheng Zhang</strong> and </span><span class="inlineblock "><strong>Zhiwen Lu</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9370; <a href="https://doi.org/10.3390/app12189370">https://doi.org/10.3390/app12189370</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9370#metrics">Cited by 1</a> | Viewed by 1396 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Timber has been commonly used in the field of civil engineering, and the health condition of timber is of great significance for the whole structure in practical scenarios. However, due to mechanical load and environmental impact, timber-based constructions are vulnerable to termite attack, <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9370/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Timber has been commonly used in the field of civil engineering, and the health condition of timber is of great significance for the whole structure in practical scenarios. However, due to mechanical load and environmental impact, timber-based constructions are vulnerable to termite attack, microbial corrosion and fractures within their service lives. Thus, the damage monitoring of timber structures is very challenging under real situations. This paper presents an intelligent timber damage monitoring approach using Lead Zirconate Titanate (PZT)-enabled active sensing and intrinsic multiscale entropy analysis. The proposed approach adopts PZT-enabled active sensing to collect the signals depicting dynamic characteristics of the timber structure. The proposed intrinsic multiscale entropy analysis utilizes variational mode decomposition (VMD) to deal with the collected response signals. Decomposition of the response signals into a set of band-limited intrinsic mode functions (BLIMFs) denoting nonlinear and nonstationary characteristics. Then multiscale sample entropy (MSE) is employed to extract quantitative features, which are adopted as health condition indicators of timber structures. Finally, the convolutional neural network (CNN) fulfills the intelligent timber damage monitoring by using the quantitative features as the effective input. The research findings reveal the efficacy and superiority of the proposed method. <a href="/2076-3417/12/18/9370">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9370/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918641"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918641"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918641" data-cycle-prev="#prev918641" data-cycle-progressive="#images918641" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918641-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g001-550.jpg?1663583455" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918641" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918641-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g002-550.jpg?1663583458'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918641-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g003-550.jpg?1663583454'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918641-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g004-550.jpg?1663583457'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-918641-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g005-550.jpg?1663583459'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-918641-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g006a-550.jpg?1663583453'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-918641-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g006b-550.jpg?1663583464'><p>Figure 6 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-918641-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g007-550.jpg?1663583448'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-918641-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g008-550.jpg?1663583452'><p>Figure 8</p></div></script></div></div><div id="article-918641-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g001-550.jpg?1663583455" title=" <strong>Figure 1</strong><br/> <p>The illustration of conventional coarse-graining procedure: (<b>a</b>) <math display="inline"><semantics> <mi>τ</mi> </semantics></math> is 2; (<b>b</b>) <math display="inline"><semantics> <mi>τ</mi> </semantics></math> is 3.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g002-550.jpg?1663583458" title=" <strong>Figure 2</strong><br/> <p>The illustration of MSE procedures.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g003-550.jpg?1663583454" title=" <strong>Figure 3</strong><br/> <p>The structure of the CNN model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g004-550.jpg?1663583457" title=" <strong>Figure 4</strong><br/> <p>Timber specimens of three groups. (<b>a</b>) Specimen of Group A; (<b>b</b>) Specimen of Group B; (<b>c</b>) Specimen of Group C.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g005-550.jpg?1663583459" title=" <strong>Figure 5</strong><br/> <p>(<b>a</b>) A photo of the apparatus, (<b>b</b>) The schematic diagram of the apparatus.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g006a-550.jpg?1663583453" title=" <strong>Figure 6</strong><br/> <p>Sensor signal response of each type of timber damage mode. (<b>a</b>) Case 1, (<b>b</b>) Case 2, (<b>c</b>) Case 3, (<b>d</b>) Case 4, (<b>e</b>) Case 5, (<b>f</b>) Case 6.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g006b-550.jpg?1663583464" title=" <strong>Figure 6 Cont.</strong><br/> <p>Sensor signal response of each type of timber damage mode. (<b>a</b>) Case 1, (<b>b</b>) Case 2, (<b>c</b>) Case 3, (<b>d</b>) Case 4, (<b>e</b>) Case 5, (<b>f</b>) Case 6.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g007-550.jpg?1663583448" title=" <strong>Figure 7</strong><br/> <p>(<b>a</b>) The accuracy of training set and validation set; (<b>b</b>) The loss function of training set and validation set.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09370/article_deploy/html/images/applsci-12-09370-g008-550.jpg?1663583452" title=" <strong>Figure 8</strong><br/> <p>(<b>a</b>) VMD + MSE + CNN timber damage identification results; (<b>b</b>) ALIF + MSE + CNN timber damage identification results; (<b>c</b>) EEMD + MSE + CNN timber damage identification results; (<b>d</b>) EMD + MSE + CNN timber damage identification results. In all confusion matrices, the abscissa and ordinate of confusion matrix denote the true label and predicted label of timber damage conditions, respectively.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9370'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918705" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 2 pages, 156 KiB   </span> <a href="/2076-3417/12/18/9369/pdf?version=1663584936" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Special Issue “Spine and Spinal Cord Biomechanics and Rehabilitation”" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Editorial</span></div> <a class="title-link" href="/2076-3417/12/18/9369">Special Issue “Spine and Spinal Cord Biomechanics and Rehabilitation”</a> <div class="authors"> by <span class="inlineblock "><strong>Norihiro Nishida</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9369; <a href="https://doi.org/10.3390/app12189369">https://doi.org/10.3390/app12189369</a> - 19 Sep 2022 </div> Viewed by 1345 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-full inline"> Spinal cord injuries are directly related to quality of life [...] <a href="/2076-3417/12/18/9369">Full article</a> </div> </div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="918617" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 21 pages, 1429 KiB   </span> <a href="/2076-3417/12/18/9368/pdf?version=1663582694" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Application of Extension Engineering in Safety Evaluation of Chemical Enterprises" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2076-3417/12/18/9368">Application of Extension Engineering in Safety Evaluation of Chemical Enterprises</a> <div class="authors"> by <span class="inlineblock "><strong>Qilong Han</strong>, </span><span class="inlineblock "><strong>Peng Liu</strong> and </span><span class="inlineblock "><strong>Zhiqiang Ma</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2022</b>, <em>12</em>(18), 9368; <a href="https://doi.org/10.3390/app12189368">https://doi.org/10.3390/app12189368</a> - 19 Sep 2022 </div> <a href="/2076-3417/12/18/9368#metrics">Cited by 1</a> | Viewed by 1773 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> To effectively analyze the safety risk of chemical enterprises and ensure the safety of production and management of enterprises, the contradiction problems in the process of index selection and risk early warning model in practical application are addressed. In this paper, extension engineering <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9368/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> To effectively analyze the safety risk of chemical enterprises and ensure the safety of production and management of enterprises, the contradiction problems in the process of index selection and risk early warning model in practical application are addressed. In this paper, extension engineering is introduced into the safety-security field of chemical enterprises to extract hidden useful information from the production environment and outdoor environment data and provide decision support for the managers of chemical enterprises. First, based on data preprocessing and extension analysis, the safety-security data of chemical enterprises that meet the quality requirements and can be efficiently mined are searched. Then, the outdoor environment is combined in the paper to conduct the mining of these data in two aspects: (1) comprehensive analysis and evaluation of data quality; (2) key factors affecting factory safety mining, realizing the safety-security evaluation of intelligent factories in chemical enterprises. Based on the proposed chemical factory safety extension prerisk model, the risk assessment of the safety status of a chemical enterprise in Hebei Province is carried out. The research results of this paper provide a theoretical basis for the safety production analysis of such chemical enterprises and put forward practical suggestions for preventing possible accidents in the production process. <a href="/2076-3417/12/18/9368">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/Analysis_Applications_AI ">Recent Analysis and Applications of Algorithms, Programs and Data Based on Artificial Intelligence</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/12/18/9368/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev918617"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next918617"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next918617" data-cycle-prev="#prev918617" data-cycle-progressive="#images918617" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-918617-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-12-09368/article_deploy/html/images/applsci-12-09368-g001-550.jpg?1663582788" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images918617" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-918617-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09368/article_deploy/html/images/applsci-12-09368-g002-550.jpg?1663582787'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-918617-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09368/article_deploy/html/images/applsci-12-09368-g003-550.jpg?1663582791'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-918617-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-12-09368/article_deploy/html/images/applsci-12-09368-g004-550.jpg?1663582797'><p>Figure 4</p></div></script></div></div><div id="article-918617-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-12-09368/article_deploy/html/images/applsci-12-09368-g001-550.jpg?1663582788" title=" <strong>Figure 1</strong><br/> <p>SEDCI index screening and hierarchical division.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9368'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09368/article_deploy/html/images/applsci-12-09368-g002-550.jpg?1663582787" title=" <strong>Figure 2</strong><br/> <p>Workshop index data box diagram.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9368'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09368/article_deploy/html/images/applsci-12-09368-g003-550.jpg?1663582791" title=" <strong>Figure 3</strong><br/> <p>The production flow chart of a workshop in the chemical plant.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9368'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-12-09368/article_deploy/html/images/applsci-12-09368-g004-550.jpg?1663582797" title=" <strong>Figure 4</strong><br/> <p>The data collection scheme diagram of workshops in the chemical plant.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/12/18/9368'>Full article</a></strong> "></a></div> </div> </div> <span class="more" style="display: none;"></span> </div> <div class="row footer"> <div class="listing-select-options"> <div class="columns small-12"> <div class="select generic-item"> <a href="#" class="export-options-show export-element export-expanded"> Show export options <i class="material-icons">expand_more</i> </a> <a href="#" class="export-options-show export-element"> Show export options <i class="material-icons">expand_less</i> </a> </div> <div class="listing-export-options export-element"> <div class="export-element" style="margin-top: 10px; 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