Search results for: Aihua Cai

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Cai</title> <meta name="description" content="Search results for: Aihua Cai"> <meta name="keywords" content="Aihua Cai"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Aihua Cai"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 4</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Aihua Cai</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Hosoya Polynomials of Mycielskian Graphs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanju%20Vaidya">Sanju Vaidya</a>, <a href="https://publications.waset.org/abstracts/search?q=Aihua%20Li"> Aihua Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Vulnerability measures and topological indices are crucial in solving various problems such as the stability of the communication networks and development of mathematical models for chemical compounds. In 1947, Harry Wiener introduced a topological index related to molecular branching. Now there are more than 100 topological indices for graphs. For example, Hosoya polynomials (also called Wiener polynomials) were introduced to derive formulas for certain vulnerability measures and topological indices for various graphs. In this paper, we will find a relation between the Hosoya polynomials of any graph and its Mycielskian graph. Additionally, using this we will compute vulnerability measures, closeness and betweenness centrality, and extended Wiener indices. It is fascinating to see how Hosoya polynomials are useful in the two diverse fields, cybersecurity and chemistry. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hosoya%20polynomial" title="hosoya polynomial">hosoya polynomial</a>, <a href="https://publications.waset.org/abstracts/search?q=mycielskian%20graph" title=" mycielskian graph"> mycielskian graph</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20vulnerability%20measure" title=" graph vulnerability measure"> graph vulnerability measure</a>, <a href="https://publications.waset.org/abstracts/search?q=topological%20index" title=" topological index"> topological index</a> </p> <a href="https://publications.waset.org/abstracts/172528/hosoya-polynomials-of-mycielskian-graphs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172528.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">69</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Improvement on the Specific Activities of Immobilized Enzymes by Poly(Ethylene Oxide) Surface Modification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shaohua%20Li">Shaohua Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Aihua%20Zhang"> Aihua Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Kelly%20Zatopek"> Kelly Zatopek</a>, <a href="https://publications.waset.org/abstracts/search?q=Saba%20Parvez"> Saba Parvez</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20F.%20Gardner"> Andrew F. Gardner</a>, <a href="https://publications.waset.org/abstracts/search?q=Ivan%20R.%20Corr%C3%AAa%20Jr."> Ivan R. Corr锚a Jr.</a>, <a href="https://publications.waset.org/abstracts/search?q=Christopher%20J.%20Noren"> Christopher J. Noren</a>, <a href="https://publications.waset.org/abstracts/search?q=Ming-Qun%20Xu"> Ming-Qun Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Covalent immobilization of enzymes on solid supports is an alternative approach to biocatalysis with the added benefits of simple enzyme removal, improved stability, and adaptability to automation and high-throughput applications. Nevertheless, immobilized enzymes generally suffer from reduced activities compared to their soluble counterparts. One major factor leading to activity loss is the intrinsic hydrophobic property of the supporting material surface, which could result in the conformational change/confinement of enzymes. We report a strategy of utilizing flexible poly (ethylene oxide) (PEO) moieties as to improve the surface hydrophilicity of solid supports used for enzyme immobilization. DNA modifying enzymes were covalently conjugated to PEO-coated magnetic-beads. Kinetics studies proved that the activities of the covalently-immobilized DNA modifying enzymes were greatly enhanced by the PEO modification on the bead surface. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=immobilized%20enzymes" title="immobilized enzymes">immobilized enzymes</a>, <a href="https://publications.waset.org/abstracts/search?q=biocatalysis" title=" biocatalysis"> biocatalysis</a>, <a href="https://publications.waset.org/abstracts/search?q=poly%28ethylene%20oxide%29" title=" poly(ethylene oxide)"> poly(ethylene oxide)</a>, <a href="https://publications.waset.org/abstracts/search?q=surface%20modification" title=" surface modification"> surface modification</a> </p> <a href="https://publications.waset.org/abstracts/79716/improvement-on-the-specific-activities-of-immobilized-enzymes-by-polyethylene-oxide-surface-modification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79716.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">308</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Track Initiation Method Based on Multi-Algorithm Fusion Learning of 1DCNN And Bi-LSTM</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhe%20Li">Zhe Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Aihua%20Cai"> Aihua Cai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=track%20initiation" title="track initiation">track initiation</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-algorithm%20fusion" title=" multi-algorithm fusion"> multi-algorithm fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=1DCNN" title=" 1DCNN"> 1DCNN</a>, <a href="https://publications.waset.org/abstracts/search?q=Bi-LSTM" title=" Bi-LSTM"> Bi-LSTM</a> </p> <a href="https://publications.waset.org/abstracts/173764/track-initiation-method-based-on-multi-algorithm-fusion-learning-of-1dcnn-and-bi-lstm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173764.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">94</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Tracking Filtering Algorithm Based on ConvLSTM</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ailing%20Yang">Ailing Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Penghan%20Song"> Penghan Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Aihua%20Cai"> Aihua Cai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The nonlinear maneuvering target tracking problem is mainly a state estimation problem when the target motion model is uncertain. Traditional solutions include Kalman filtering based on Bayesian filtering framework and extended Kalman filtering. However, these methods need prior knowledge such as kinematics model and state system distribution, and their performance is poor in state estimation of nonprior complex dynamic systems. Therefore, in view of the problems existing in traditional algorithms, a convolution LSTM target state estimation (SAConvLSTM-SE) algorithm based on Self-Attention memory (SAM) is proposed to learn the historical motion state of the target and the error distribution information measured at the current time. The measured track point data of airborne radar are processed into data sets. After supervised training, the data-driven deep neural network based on SAConvLSTM can directly obtain the target state at the next moment. Through experiments on two different maneuvering targets, we find that the network has stronger robustness and better tracking accuracy than the existing tracking methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=maneuvering%20target" title="maneuvering target">maneuvering target</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimation" title=" state estimation"> state estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=LSTM" title=" LSTM"> LSTM</a>, <a href="https://publications.waset.org/abstracts/search?q=self-attention" title=" self-attention"> self-attention</a> </p> <a href="https://publications.waset.org/abstracts/164893/tracking-filtering-algorithm-based-on-convlstm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164893.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">176</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); 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Search results for: Aihua Cai