Search results for: Sohel Sikder

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Sikder</title> <meta name="description" content="Search results for: Sohel Sikder"> <meta name="keywords" content="Sohel Sikder"> <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 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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="Sohel Sikder"> <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: Sohel Sikder</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> Mining the Proteome of Fusobacterium nucleatum for Potential Therapeutics Discovery </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdul%20Musaweer%20Habib">Abdul Musaweer Habib</a>, <a href="https://publications.waset.org/abstracts/search?q=Habibul%20Hasan%20Mazumder"> Habibul Hasan Mazumder</a>, <a href="https://publications.waset.org/abstracts/search?q=Saiful%20Islam"> Saiful Islam</a>, <a href="https://publications.waset.org/abstracts/search?q=Sohel%20Sikder"> Sohel Sikder</a>, <a href="https://publications.waset.org/abstracts/search?q=Omar%20Faruk%20Sikder"> Omar Faruk Sikder </a> </p> <p class="card-text"><strong>Abstract:</strong></p> The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=colorectal%20cancer" title="colorectal cancer">colorectal cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=drug%20target" title=" drug target"> drug target</a>, <a href="https://publications.waset.org/abstracts/search?q=Fusobacterium%20nucleatum" title=" Fusobacterium nucleatum"> Fusobacterium nucleatum</a>, <a href="https://publications.waset.org/abstracts/search?q=homology%20modeling" title=" homology modeling"> homology modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=ligands" title=" ligands"> ligands</a> </p> <a href="https://publications.waset.org/abstracts/16273/mining-the-proteome-of-fusobacterium-nucleatum-for-potential-therapeutics-discovery" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16273.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">389</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> Application of Granular Computing Paradigm in Knowledge Induction </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Iftikhar%20U.%20Sikder">Iftikhar U. Sikder </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper illustrates an application of granular computing approach, namely rough set theory in data mining. The paper outlines the formalism of granular computing and elucidates the mathematical underpinning of rough set theory, which has been widely used by the data mining and the machine learning community. A real-world application is illustrated, and the classification performance is compared with other contending machine learning algorithms. The predictive performance of the rough set rule induction model shows comparative success with respect to other contending algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=concept%20approximation" title="concept approximation">concept approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=granular%20computing" title=" granular computing"> granular computing</a>, <a href="https://publications.waset.org/abstracts/search?q=reducts" title=" reducts"> reducts</a>, <a href="https://publications.waset.org/abstracts/search?q=rough%20set%20theory" title=" rough set theory"> rough set theory</a>, <a href="https://publications.waset.org/abstracts/search?q=rule%20induction" title=" rule induction"> rule induction</a> </p> <a href="https://publications.waset.org/abstracts/78370/application-of-granular-computing-paradigm-in-knowledge-induction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78370.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">531</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> On the Performance of Improvised Generalized M-Estimator in the Presence of High Leverage Collinearity Enhancing Observations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Habshah%20Midi">Habshah Midi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20A.%20Mohammed"> Mohammed A. Mohammed</a>, <a href="https://publications.waset.org/abstracts/search?q=Sohel%20Rana"> Sohel Rana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Multicollinearity occurs when two or more independent variables in a multiple linear regression model are highly correlated. The ridge regression is the commonly used method to rectify this problem. However, the ridge regression cannot handle the problem of multicollinearity which is caused by high leverage collinearity enhancing observation (HLCEO). Since high leverage points (HLPs) are responsible for inducing multicollinearity, the effect of HLPs needs to be reduced by using Generalized M estimator. The existing GM6 estimator is based on the Minimum Volume Ellipsoid (MVE) which tends to swamp some low leverage points. Hence an improvised GM (MGM) estimator is presented to improve the precision of the GM6 estimator. Numerical example and simulation study are presented to show how HLPs can cause multicollinearity. The numerical results show that our MGM estimator is the most efficient method compared to some existing methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=identification" title="identification">identification</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20leverage%20points" title=" high leverage points"> high leverage points</a>, <a href="https://publications.waset.org/abstracts/search?q=multicollinearity" title=" multicollinearity"> multicollinearity</a>, <a href="https://publications.waset.org/abstracts/search?q=GM-estimator" title=" GM-estimator"> GM-estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=DRGP" title=" DRGP"> DRGP</a>, <a href="https://publications.waset.org/abstracts/search?q=DFFITS" title=" DFFITS"> DFFITS</a> </p> <a href="https://publications.waset.org/abstracts/55345/on-the-performance-of-improvised-generalized-m-estimator-in-the-presence-of-high-leverage-collinearity-enhancing-observations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55345.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">263</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> Development and Characterization of Re-Entrant Auxetic Fibrous Structures for Application in Ballistic Composites </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rui%20Magalh%C3%A3es">Rui Magalh茫es</a>, <a href="https://publications.waset.org/abstracts/search?q=Sohel%20Rana"> Sohel Rana</a>, <a href="https://publications.waset.org/abstracts/search?q=Raul%20Fangueiro"> Raul Fangueiro</a>, <a href="https://publications.waset.org/abstracts/search?q=Clara%20Gon%C3%A7alves"> Clara Gon莽alves</a>, <a href="https://publications.waset.org/abstracts/search?q=Pedro%20Nunes"> Pedro Nunes</a>, <a href="https://publications.waset.org/abstracts/search?q=Gustavo%20Dias"> Gustavo Dias</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Auxetic fibrous structures and composites with negative Poisson’s ratio (NPR) have huge potential for application in ballistic protection due to their high energy absorption and excellent impact resistance. In the present research, re-entrant lozenge auxetic fibrous structures were produced through weft knitting technology using high performance polyamide and para-aramid fibres. Fabric structural parameters (e.g. loop length) and machine parameters (e.g. take down load) were varied in order to investigate their influence on the auxetic behaviours of the produced structures. These auxetic structures were then impregnated with two types of polymeric resins (epoxy and polyester) to produce composite materials, which were subsequently characterized for the auxetic behaviour. It was observed that the knitted fabrics produced using the polyamide yarns exhibited NPR over a wide deformation range, which was strongly dependant on the loop length and take down load. The polymeric composites produced from the auxetic fabrics also showed good auxetic property, which was superior in case of the polyester matrix. The experimental results suggested that these composites made from the auxetic fibrous structures can be properly designed to find potential use in the body amours for personal protection applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=auxetic%20fabrics" title="auxetic fabrics">auxetic fabrics</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20performance" title=" high performance"> high performance</a>, <a href="https://publications.waset.org/abstracts/search?q=composites" title=" composites"> composites</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20absorption" title=" energy absorption"> energy absorption</a>, <a href="https://publications.waset.org/abstracts/search?q=impact%20resistance" title=" impact resistance"> impact resistance</a> </p> <a href="https://publications.waset.org/abstracts/89742/development-and-characterization-of-re-entrant-auxetic-fibrous-structures-for-application-in-ballistic-composites" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89742.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">255</span> </span> </div> </div> </div> </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 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Search results for: Sohel Sikder