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features.</title> <meta name="description" content="Search results for: stylometric features."> <meta name="keywords" content="stylometric features."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="stylometric features."> <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> 1554</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: stylometric features.</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1554</span> A Comparison of Fuzzy Clustering Algorithms to Cluster Web Messages</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Sara%20El%20Manar%20El%20Bouanani">Sara El Manar El Bouanani</a>, <a href="https://publications.waset.org/search?q=Ismail%20Kassou"> Ismail Kassou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Our objective in this paper is to propose an approach capable of clustering web messages. The clustering is carried out by assigning, with a certain probability, texts written by the same web user to the same cluster based on Stylometric features and using fuzzy clustering algorithms. Focus in the present work is on comparing the most popular algorithms in fuzzy clustering theory namely, Fuzzy C-means, Possibilistic C-means and Fuzzy Possibilistic C-Means.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Authorship%20detection" title="Authorship detection">Authorship detection</a>, <a href="https://publications.waset.org/search?q=fuzzy%20clustering" title=" fuzzy clustering"> fuzzy clustering</a>, <a href="https://publications.waset.org/search?q=profiling" title=" profiling"> profiling</a>, <a href="https://publications.waset.org/search?q=stylometric%20features." title=" stylometric features."> stylometric features.</a> </p> <a href="https://publications.waset.org/16551/a-comparison-of-fuzzy-clustering-algorithms-to-cluster-web-messages" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/16551/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/16551/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/16551/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/16551/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/16551/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/16551/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/16551/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/16551/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/16551/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/16551/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/16551.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">2052</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1553</span> Exploring Performance-Based Music Attributes for Stylometric Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Abdellghani%20Bellaachia">Abdellghani Bellaachia</a>, <a href="https://publications.waset.org/search?q=Edward%20Jimenez"> Edward Jimenez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Music Information Retrieval (MIR) and modern data mining techniques are applied to identify style markers in midi music for stylometric analysis and author attribution. Over 100 attributes are extracted from a library of 2830 songs then mined using supervised learning data mining techniques. Two attributes are identified that provide high informational gain. These attributes are then used as style markers to predict authorship. Using these style markers the authors are able to correctly distinguish songs written by the Beatles from those that were not with a precision and accuracy of over 98 per cent. The identification of these style markers as well as the architecture for this research provides a foundation for future research in musical stylometry.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Music%20Information%20Retrieval" title="Music Information Retrieval">Music Information Retrieval</a>, <a href="https://publications.waset.org/search?q=Music%20Data%20Mining" title=" Music Data Mining"> Music Data Mining</a>, <a href="https://publications.waset.org/search?q=Stylometry." title=" Stylometry."> Stylometry.</a> </p> <a href="https://publications.waset.org/14200/exploring-performance-based-music-attributes-for-stylometric-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14200/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14200/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14200/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14200/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14200/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14200/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14200/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14200/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14200/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14200/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14200.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">1680</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1552</span> Relevant LMA Features for Human Motion Recognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Insaf%20Ajili">Insaf Ajili</a>, <a href="https://publications.waset.org/search?q=Malik%20Mallem"> Malik Mallem</a>, <a href="https://publications.waset.org/search?q=Jean-Yves%20Didier"> Jean-Yves Didier</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Motion recognition from videos is actually a very complex task due to the high variability of motions. This paper describes the challenges of human motion recognition, especially motion representation step with relevant features. Our descriptor vector is inspired from Laban Movement Analysis method. We propose discriminative features using the Random Forest algorithm in order to remove redundant features and make learning algorithms operate faster and more effectively. We validate our method on MSRC-12 and UTKinect datasets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Human%20motion%20recognition" title="Human motion recognition">Human motion recognition</a>, <a href="https://publications.waset.org/search?q=Discriminative%20LMA%0D%0Afeatures" title=" Discriminative LMA features"> Discriminative LMA features</a>, <a href="https://publications.waset.org/search?q=random%20forest" title=" random forest"> random forest</a>, <a href="https://publications.waset.org/search?q=features%20reduction." title=" features reduction."> features reduction.</a> </p> <a href="https://publications.waset.org/10009574/relevant-lma-features-for-human-motion-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10009574/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10009574/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10009574/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10009574/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10009574/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10009574/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10009574/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10009574/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10009574/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10009574/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10009574.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">773</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1551</span> Reducing the False Rejection Rate of Iris Recognition Using Textural and Topological Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20Vatsa">M. Vatsa</a>, <a href="https://publications.waset.org/search?q=R.%20Singh"> R. Singh</a>, <a href="https://publications.waset.org/search?q=A.%20Noore"> A. Noore</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a novel iris recognition system using 1D log polar Gabor wavelet and Euler numbers. 1D log polar Gabor wavelet is used to extract the textural features, and Euler numbers are used to extract topological features of the iris. The proposed decision strategy uses these features to authenticate an individual-s identity while maintaining a low false rejection rate. The algorithm was tested on CASIA iris image database and found to perform better than existing approaches with an overall accuracy of 99.93%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Iris%20recognition" title="Iris recognition">Iris recognition</a>, <a href="https://publications.waset.org/search?q=textural%20features" title=" textural features"> textural features</a>, <a href="https://publications.waset.org/search?q=topological%0Afeatures." title=" topological features."> topological features.</a> </p> <a href="https://publications.waset.org/5639/reducing-the-false-rejection-rate-of-iris-recognition-using-textural-and-topological-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/5639/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/5639/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/5639/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/5639/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/5639/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/5639/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/5639/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/5639/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/5639/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/5639/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/5639.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">1944</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1550</span> One Dimensional Object Segmentation and Statistical Features of an Image for Texture Image Recognition System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Nang%20Thwe%20Thwe%20Oo">Nang Thwe Thwe Oo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Traditional object segmentation methods are time consuming and computationally difficult. In this paper, onedimensional object detection along the secant lines is applied. Statistical features of texture images are computed for the recognition process. Example matrices of these features and formulae for calculation of similarities between two feature patterns are expressed. And experiments are also carried out using these features.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=1-D%20object%20segmentation" title="1-D object segmentation">1-D object segmentation</a>, <a href="https://publications.waset.org/search?q=secant%20lines" title=" secant lines"> secant lines</a>, <a href="https://publications.waset.org/search?q=objectoccurrence%28frequency%29%20matrix" title=" objectoccurrence(frequency) matrix"> objectoccurrence(frequency) matrix</a>, <a href="https://publications.waset.org/search?q=contiguity%20matrix" title=" contiguity matrix"> contiguity matrix</a>, <a href="https://publications.waset.org/search?q=statistical%20features." title=" statistical features."> statistical features.</a> </p> <a href="https://publications.waset.org/1501/one-dimensional-object-segmentation-and-statistical-features-of-an-image-for-texture-image-recognition-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1501/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1501/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/1501/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/1501/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/1501/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/1501/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/1501/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/1501/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/1501/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/1501/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/1501.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">1501</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1549</span> Optimizing Feature Selection for Recognizing Handwritten Arabic Characters </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohammed%20Z.%20Khedher">Mohammed Z. Khedher</a>, <a href="https://publications.waset.org/search?q=Gheith%20A.%20Abandah"> Gheith A. Abandah</a>, <a href="https://publications.waset.org/search?q=Ahmed%20M.%20Al-Khawaldeh"> Ahmed M. Al-Khawaldeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recognition based on the selected features give average accuracies of 88% and 70% for the numbers and letters, respectively. Further improvements are achieved by using feature weights based on insights gained from the accuracies of individual features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Arabic%20handwritten%20characters" title="Arabic handwritten characters">Arabic handwritten characters</a>, <a href="https://publications.waset.org/search?q=Feature%20extraction" title=" Feature extraction"> Feature extraction</a>, <a href="https://publications.waset.org/search?q=Off-line%20recognition" title=" Off-line recognition"> Off-line recognition</a>, <a href="https://publications.waset.org/search?q=Optical%20character%20recognition." title=" Optical character recognition."> Optical character recognition.</a> </p> <a href="https://publications.waset.org/12621/optimizing-feature-selection-for-recognizing-handwritten-arabic-characters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/12621/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/12621/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/12621/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/12621/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/12621/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/12621/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/12621/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/12621/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/12621/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/12621/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/12621.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">1691</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1548</span> Finding Sparse Features in Face Detection Using Genetic Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=H.%20Sagha">H. Sagha</a>, <a href="https://publications.waset.org/search?q=S.%20Kasaei"> S. Kasaei</a>, <a href="https://publications.waset.org/search?q=E.%20Enayati"> E. Enayati</a>, <a href="https://publications.waset.org/search?q=M.%20Dehghani"> M. Dehghani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and its recent analogous is Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and gets more effective features in learning process for face detection that causes more accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Face%20Detection" title="Face Detection">Face Detection</a>, <a href="https://publications.waset.org/search?q=Genetic%20Algorithms" title=" Genetic Algorithms"> Genetic Algorithms</a>, <a href="https://publications.waset.org/search?q=Sparse%0AFeature." title=" Sparse Feature."> Sparse Feature.</a> </p> <a href="https://publications.waset.org/3993/finding-sparse-features-in-face-detection-using-genetic-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/3993/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/3993/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/3993/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/3993/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/3993/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/3993/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/3993/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/3993/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/3993/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/3993/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/3993.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">1581</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1547</span> Face Recognition using Features Combination and a New Non-linear Kernel</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Essam%20Al%20Daoud">Essam Al Daoud</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To improve the classification rate of the face recognition, features combination and a novel non-linear kernel are proposed. The feature vector concatenates three different radius of local binary patterns and Gabor wavelet features. Gabor features are the mean, standard deviation and the skew of each scaling and orientation parameter. The aim of the new kernel is to incorporate the power of the kernel methods with the optimal balance between the features. To verify the effectiveness of the proposed method, numerous methods are tested by using four datasets, which are consisting of various emotions, orientations, configuration, expressions and lighting conditions. Empirical results show the superiority of the proposed technique when compared to other methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Face%20recognition" title="Face recognition">Face recognition</a>, <a href="https://publications.waset.org/search?q=Gabor%20wavelet" title=" Gabor wavelet"> Gabor wavelet</a>, <a href="https://publications.waset.org/search?q=LBP" title=" LBP"> LBP</a>, <a href="https://publications.waset.org/search?q=Non-linearkerner" title=" Non-linearkerner"> Non-linearkerner</a> </p> <a href="https://publications.waset.org/4963/face-recognition-using-features-combination-and-a-new-non-linear-kernel" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/4963/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/4963/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/4963/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/4963/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/4963/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/4963/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/4963/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/4963/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/4963/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/4963/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/4963.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">1540</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1546</span> Video Data Mining based on Information Fusion for Tamper Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Girija%20Chetty">Girija Chetty</a>, <a href="https://publications.waset.org/search?q=Renuka%20Biswas"> Renuka Biswas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose novel algorithmic models based on information fusion and feature transformation in crossmodal subspace for different types of residue features extracted from several intra-frame and inter-frame pixel sub-blocks in video sequences for detecting digital video tampering or forgery. An evaluation of proposed residue features – the noise residue features and the quantization features, their transformation in cross-modal subspace, and their multimodal fusion, for emulated copy-move tamper scenario shows a significant improvement in tamper detection accuracy as compared to single mode features without transformation in cross-modal subspace. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=image%20tamper%20detection" title="image tamper detection">image tamper detection</a>, <a href="https://publications.waset.org/search?q=digital%20forensics" title=" digital forensics"> digital forensics</a>, <a href="https://publications.waset.org/search?q=correlation%0Afeatures%20image%20fusion" title=" correlation features image fusion"> correlation features image fusion</a> </p> <a href="https://publications.waset.org/7183/video-data-mining-based-on-information-fusion-for-tamper-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/7183/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/7183/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/7183/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/7183/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/7183/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/7183/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/7183/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/7183/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/7183/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/7183/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/7183.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">1899</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1545</span> Exploiting Global Self Similarity for Head-Shoulder Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Lae-Jeong%20Park">Lae-Jeong Park</a>, <a href="https://publications.waset.org/search?q=Jung-Ho%20Moon"> Jung-Ho Moon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>People detection from images has a variety of applications such as video surveillance and driver assistance system, but is still a challenging task and more difficult in crowded environments such as shopping malls in which occlusion of lower parts of human body often occurs. Lack of the full-body information requires more effective features than common features such as HOG. In this paper, new features are introduced that exploits global self-symmetry (GSS) characteristic in head-shoulder patterns. The features encode the similarity or difference of color histograms and oriented gradient histograms between two vertically symmetric blocks. The domain-specific features are rapid to compute from the integral images in Viola-Jones cascade-of-rejecters framework. The proposed features are evaluated with our own head-shoulder dataset that, in part, consists of a well-known INRIA pedestrian dataset. Experimental results show that the GSS features are effective in reduction of false alarmsmarginally and the gradient GSS features are preferred more often than the color GSS ones in the feature selection.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Pedestrian%20detection" title="Pedestrian detection">Pedestrian detection</a>, <a href="https://publications.waset.org/search?q=cascade%20of%20rejecters" title=" cascade of rejecters"> cascade of rejecters</a>, <a href="https://publications.waset.org/search?q=feature%0D%0Aextraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=self-symmetry" title="self-symmetry">self-symmetry</a>, <a href="https://publications.waset.org/search?q=HOG." title=" HOG."> HOG.</a> </p> <a href="https://publications.waset.org/14935/exploiting-global-self-similarity-for-head-shoulder-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14935/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14935/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14935/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14935/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14935/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14935/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14935/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14935/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14935/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14935/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14935.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">2400</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1544</span> Improving Classification Accuracy with Discretization on Datasets Including Continuous Valued Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mehmet%20Hacibeyoglu">Mehmet Hacibeyoglu</a>, <a href="https://publications.waset.org/search?q=Ahmet%20Arslan"> Ahmet Arslan</a>, <a href="https://publications.waset.org/search?q=Sirzat%20Kahramanli"> Sirzat Kahramanli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study analyzes the effect of discretization on classification of datasets including continuous valued features. Six datasets from UCI which containing continuous valued features are discretized with entropy-based discretization method. The performance improvement between the dataset with original features and the dataset with discretized features is compared with k-nearest neighbors, Naive Bayes, C4.5 and CN2 data mining classification algorithms. As the result the classification accuracies of the six datasets are improved averagely by 1.71% to 12.31%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Data%20mining%20classification%20algorithms" title="Data mining classification algorithms">Data mining classification algorithms</a>, <a href="https://publications.waset.org/search?q=entropy-baseddiscretization%20method" title=" entropy-baseddiscretization method"> entropy-baseddiscretization method</a> </p> <a href="https://publications.waset.org/1314/improving-classification-accuracy-with-discretization-on-datasets-including-continuous-valued-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1314/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1314/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/1314/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/1314/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/1314/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/1314/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/1314/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/1314/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/1314/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/1314/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/1314.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">2461</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1543</span> Using Reservoir Models for Monitoring Geothermal Surface Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=John%20P.%20O%E2%80%99Sullivan">John P. O’Sullivan</a>, <a href="https://publications.waset.org/search?q=Thomas%20M.%20P.%20Ratouis"> Thomas M. P. Ratouis</a>, <a href="https://publications.waset.org/search?q=Michael%20J.%20O%E2%80%99Sullivan"> Michael J. O’Sullivan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>As the use of geothermal energy grows internationally more effort is required to monitor and protect areas with rare and important geothermal surface features. A number of approaches are presented for developing and calibrating numerical geothermal reservoir models that are capable of accurately representing geothermal surface features. The approaches are discussed in the context of cases studies of the Rotorua geothermal system and the Orakei-korako geothermal system, both of which contain important surface features. The results show that models are able to match the available field data accurately and hence can be used as valuable tools for predicting the future response of the systems to changes in use.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Geothermal%20reservoir%20models" title="Geothermal reservoir models">Geothermal reservoir models</a>, <a href="https://publications.waset.org/search?q=surface%20features" title=" surface features"> surface features</a>, <a href="https://publications.waset.org/search?q=monitoring" title=" monitoring"> monitoring</a>, <a href="https://publications.waset.org/search?q=TOUGH2." title=" TOUGH2."> TOUGH2.</a> </p> <a href="https://publications.waset.org/10000647/using-reservoir-models-for-monitoring-geothermal-surface-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10000647/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10000647/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10000647/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10000647/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10000647/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10000647/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10000647/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10000647/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10000647/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10000647/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10000647.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">2072</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1542</span> Investigating Relationship between Product Features and Supply Chain Integration</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Saied%20Rasul%20Hosseini%20Baharanchi">Saied Rasul Hosseini Baharanchi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses integration issues in supply chain, and tries to investigate how different aspects of integration are linked with some product features. Integration in this study is interpreted as "internal", "upstream" (supply), and "downstream" (demand). Two features of product innovative and quality are considered. To examine the relationships between supply chain integrations – as mentioned above, and product features, this research follows the survey method in automotive industry.The results imply that supply chain upstream integration has a higher impact on product quality, comparing to internal and supply chain downstream integrations. It is also found that the influence of supply chain downstream integration on product innovation is greater than other variables. In brief, this study mainly tackles the importance of specific level of supply chain integrations and its effects on two product features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Supply%20chain%20upstream%20integration" title="Supply chain upstream integration">Supply chain upstream integration</a>, <a href="https://publications.waset.org/search?q=supply%20chaindownstream%20integration" title=" supply chaindownstream integration"> supply chaindownstream integration</a>, <a href="https://publications.waset.org/search?q=internal%20integration" title=" internal integration"> internal integration</a>, <a href="https://publications.waset.org/search?q=product%20features" title=" product features"> product features</a> </p> <a href="https://publications.waset.org/6752/investigating-relationship-between-product-features-and-supply-chain-integration" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6752/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6752/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6752/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6752/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6752/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6752/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6752/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6752/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6752/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6752/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6752.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">1830</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1541</span> Myanmar Character Recognition Using Eight Direction Chain Code Frequency Features </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Kyi%20Pyar%20Zaw">Kyi Pyar Zaw</a>, <a href="https://publications.waset.org/search?q=Zin%20Mar%20Kyu"> Zin Mar Kyu </a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Chain%20code%20frequency" title="Chain code frequency">Chain code frequency</a>, <a href="https://publications.waset.org/search?q=character%20recognition" title=" character recognition"> character recognition</a>, <a href="https://publications.waset.org/search?q=feature%20extraction" title=" feature extraction"> feature extraction</a>, <a href="https://publications.waset.org/search?q=features%20matching" title=" features matching"> features matching</a>, <a href="https://publications.waset.org/search?q=segmentation." title=" segmentation."> segmentation.</a> </p> <a href="https://publications.waset.org/10009080/myanmar-character-recognition-using-eight-direction-chain-code-frequency-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10009080/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10009080/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10009080/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10009080/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10009080/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10009080/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10009080/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10009080/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10009080/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10009080/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10009080.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">753</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1540</span> Image Search by Features of Sorted Gray level Histogram Polynomial Curve </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Awais%20Adnan">Awais Adnan</a>, <a href="https://publications.waset.org/search?q=Muhammad%20Ali"> Muhammad Ali</a>, <a href="https://publications.waset.org/search?q=Amir%20Hanif%20Dar"> Amir Hanif Dar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Image Searching was always a problem specially when these images are not properly managed or these are distributed over different locations. Currently different techniques are used for image search. On one end, more features of the image are captured and stored to get better results. Storing and management of such features is itself a time consuming job. While on the other extreme if fewer features are stored the accuracy rate is not satisfactory. Same image stored with different visual properties can further reduce the rate of accuracy. In this paper we present a new concept of using polynomials of sorted histogram of the image. This approach need less overhead and can cope with the difference in visual features of image.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Sorted%20Histogram" title="Sorted Histogram">Sorted Histogram</a>, <a href="https://publications.waset.org/search?q=Polynomial%20Curves" title=" Polynomial Curves"> Polynomial Curves</a>, <a href="https://publications.waset.org/search?q=feature%20pointsof%20images" title=" feature pointsof images"> feature pointsof images</a>, <a href="https://publications.waset.org/search?q=Grayscale" title=" Grayscale"> Grayscale</a>, <a href="https://publications.waset.org/search?q=visual%20properties%20of%20image." title=" visual properties of image."> visual properties of image.</a> </p> <a href="https://publications.waset.org/770/image-search-by-features-of-sorted-gray-level-histogram-polynomial-curve" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/770/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/770/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/770/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/770/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/770/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/770/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/770/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/770/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/770/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/770/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/770.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">1428</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1539</span> Effective Features for Disambiguation of Turkish Verbs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Zeynep%20Orhan">Zeynep Orhan</a>, <a href="https://publications.waset.org/search?q=Zeynep%20Altan"> Zeynep Altan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This paper summarizes the results of some experiments for finding the effective features for disambiguation of Turkish verbs. Word sense disambiguation is a current area of investigation in which verbs have the dominant role. Generally verbs have more senses than the other types of words in the average and detecting these features for verbs may lead to some improvements for other word types. In this paper we have considered only the syntactical features that can be obtained from the corpus and tested by using some famous machine learning algorithms.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Word%20sense%20disambiguation" title="Word sense disambiguation">Word sense disambiguation</a>, <a href="https://publications.waset.org/search?q=feature%20selection." title=" feature selection."> feature selection.</a> </p> <a href="https://publications.waset.org/13001/effective-features-for-disambiguation-of-turkish-verbs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/13001/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/13001/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/13001/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/13001/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/13001/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/13001/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/13001/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/13001/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/13001/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/13001/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/13001.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">1747</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1538</span> A Web-Based System for Mapping Features into ISO 14649-Compliant Machining Workingsteps</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=J.%20C.%20T.%20Benavente">J. C. T. Benavente</a>, <a href="https://publications.waset.org/search?q=J.%20C.%20E.%20Ferreira"> J. C. E. Ferreira</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>The rapid development of manufacturing and information systems has caused significant changes in manufacturing environments in recent decades. Mass production has given way to flexible manufacturing systems, in which an important characteristic is customized or "on demand" production. In this scenario, the seamless and without gaps information flow becomes a key factor for success of enterprises. In this paper we present a framework to support the mapping of features into machining workingsteps compliant with the ISO 14649 standard (known as STEP-NC). The system determines how the features can be made with the available manufacturing resources. Examples of the mapping method are presented for features such as a pocket with a general surface.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Features" title="Features">Features</a>, <a href="https://publications.waset.org/search?q=ISO%2014649%20standard" title=" ISO 14649 standard"> ISO 14649 standard</a>, <a href="https://publications.waset.org/search?q=STEP-NC" title=" STEP-NC"> STEP-NC</a>, <a href="https://publications.waset.org/search?q=mapping" title=" mapping"> mapping</a>, <a href="https://publications.waset.org/search?q=machining%20workingsteps." title=" machining workingsteps."> machining workingsteps.</a> </p> <a href="https://publications.waset.org/17327/a-web-based-system-for-mapping-features-into-iso-14649-compliant-machining-workingsteps" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/17327/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/17327/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/17327/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/17327/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/17327/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/17327/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/17327/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/17327/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/17327/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/17327/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/17327.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">1895</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1537</span> Image Segmentation Using the K-means Algorithm for Texture Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Wan-Ting%20Lin">Wan-Ting Lin</a>, <a href="https://publications.waset.org/search?q=Chuen-Horng%20Lin"> Chuen-Horng Lin</a>, <a href="https://publications.waset.org/search?q=Tsung-Ho%20Wu"> Tsung-Ho Wu</a>, <a href="https://publications.waset.org/search?q=Yung-Kuan%20Chan"> Yung-Kuan Chan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to segment objects using the K-means algorithm for texture features. Firstly, the algorithm transforms color images into gray images. This paper describes a novel technique for the extraction of texture features in an image. Then, in a group of similar features, objects and backgrounds are differentiated by using the K-means algorithm. Finally, this paper proposes a new object segmentation algorithm using the morphological technique. The experiments described include the segmentation of single and multiple objects featured in this paper. The region of an object can be accurately segmented out. The results can help to perform image retrieval and analyze features of an object, as are shown in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=k-mean" title="k-mean">k-mean</a>, <a href="https://publications.waset.org/search?q=multiple%20objects" title=" multiple objects"> multiple objects</a>, <a href="https://publications.waset.org/search?q=segmentation" title=" segmentation"> segmentation</a>, <a href="https://publications.waset.org/search?q=texturefeatures." title=" texturefeatures."> texturefeatures.</a> </p> <a href="https://publications.waset.org/8719/image-segmentation-using-the-k-means-algorithm-for-texture-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8719/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8719/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8719/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8719/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8719/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8719/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8719/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8719/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8719/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8719/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8719.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">2821</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1536</span> Identification of Arousal and Relaxation by using SVM-Based Fusion of PPG Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Chi%20Jung%20Kim">Chi Jung Kim</a>, <a href="https://publications.waset.org/search?q=Mincheol%20Whang"> Mincheol Whang</a>, <a href="https://publications.waset.org/search?q=Eui%20Chul%20Lee"> Eui Chul Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose a new method to distinguish between arousal and relaxation states by using multiple features acquired from a photoplethysmogram (PPG) and support vector machine (SVM). To induce arousal and relaxation states in subjects, 2 kinds of sound stimuli are used, and their corresponding biosignals are obtained using the PPG sensor. Two features–pulse to pulse interval (PPI) and pulse amplitude (PA)–are extracted from acquired PPG data, and a nonlinear classification between arousal and relaxation is performed using SVM. This methodology has several advantages when compared with previous similar studies. Firstly, we extracted 2 separate features from PPG, i.e., PPI and PA. Secondly, in order to improve the classification accuracy, SVM-based nonlinear classification was performed. Thirdly, to solve classification problems caused by generalized features of whole subjects, we defined each threshold according to individual features. Experimental results showed that the average classification accuracy was 74.67%. Also, the proposed method showed the better identification performance than the single feature based methods. From this result, we confirmed that arousal and relaxation can be classified using SVM and PPG features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Support%20Vector%20Machine" title="Support Vector Machine">Support Vector Machine</a>, <a href="https://publications.waset.org/search?q=PPG" title=" PPG"> PPG</a>, <a href="https://publications.waset.org/search?q=Emotion%20Recognition" title=" Emotion Recognition"> Emotion Recognition</a>, <a href="https://publications.waset.org/search?q=Arousal" title=" Arousal"> Arousal</a>, <a href="https://publications.waset.org/search?q=Relaxation" title=" Relaxation"> Relaxation</a> </p> <a href="https://publications.waset.org/10837/identification-of-arousal-and-relaxation-by-using-svm-based-fusion-of-ppg-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10837/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10837/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10837/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10837/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10837/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10837/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10837/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10837/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10837/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10837/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10837.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">2484</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1535</span> Comparison between XGBoost, LightGBM and CatBoost Using a Home Credit Dataset</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Essam%20Al%20Daoud">Essam Al Daoud</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Gradient%20boosting" title="Gradient boosting">Gradient boosting</a>, <a href="https://publications.waset.org/search?q=XGBoost" title=" XGBoost"> XGBoost</a>, <a href="https://publications.waset.org/search?q=LightGBM" title=" LightGBM"> LightGBM</a>, <a href="https://publications.waset.org/search?q=CatBoost" title=" CatBoost"> CatBoost</a>, <a href="https://publications.waset.org/search?q=home%20credit." title=" home credit."> home credit.</a> </p> <a href="https://publications.waset.org/10009954/comparison-between-xgboost-lightgbm-and-catboost-using-a-home-credit-dataset" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10009954/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10009954/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10009954/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10009954/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10009954/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10009954/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10009954/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10009954/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10009954/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10009954/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10009954.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">9458</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1534</span> Automatic Extraction of Features and Opinion-Oriented Sentences from Customer Reviews</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Khairullah%20Khan">Khairullah Khan</a>, <a href="https://publications.waset.org/search?q=Baharum%20B.%20Baharudin"> Baharum B. Baharudin</a>, <a href="https://publications.waset.org/search?q=Aurangzeb%20Khan"> Aurangzeb Khan</a>, <a href="https://publications.waset.org/search?q=Fazal_e_Malik"> Fazal_e_Malik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Opinion extraction about products from customer reviews is becoming an interesting area of research. Customer reviews about products are nowadays available from blogs and review sites. Also tools are being developed for extraction of opinion from these reviews to help the user as well merchants to track the most suitable choice of product. Therefore efficient method and techniques are needed to extract opinions from review and blogs. As reviews of products mostly contains discussion about the features, functions and services, therefore, efficient techniques are required to extract user comments about the desired features, functions and services. In this paper we have proposed a novel idea to find features of product from user review in an efficient way. Our focus in this paper is to get the features and opinion-oriented words about products from text through auxiliary verbs (AV) {is, was, are, were, has, have, had}. From the results of our experiments we found that 82% of features and 85% of opinion-oriented sentences include AVs. Thus these AVs are good indicators of features and opinion orientation in customer reviews. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Classification" title="Classification">Classification</a>, <a href="https://publications.waset.org/search?q=Customer%20Reviews" title=" Customer Reviews"> Customer Reviews</a>, <a href="https://publications.waset.org/search?q=Helping%20Verbs" title=" Helping Verbs"> Helping Verbs</a>, <a href="https://publications.waset.org/search?q=Opinion%20Mining." title="Opinion Mining.">Opinion Mining.</a> </p> <a href="https://publications.waset.org/10183/automatic-extraction-of-features-and-opinion-oriented-sentences-from-customer-reviews" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10183/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10183/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10183/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10183/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10183/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10183/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10183/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10183/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10183/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10183/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10183.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">2096</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1533</span> Deployment of Service Quality Characteristics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Shuki%20Dror">Shuki Dror</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work discusses an innovative methodology for deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational relationships. A House of Service Quality (HOSQ) matrix is built to extract the desired improvement in the service quality characteristics and to translate them into a hierarchy of important organizational features. The Mean Square Error (MSE) criterion enables the pinpointing of the few essential service quality characteristics to be improved as well as selection of the vital organizational features. The method was implemented in an engineering supply enterprise and provides useful information on its vital service dimensions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=HOQ" title="HOQ">HOQ</a>, <a href="https://publications.waset.org/search?q=organizational%20features" title=" organizational features"> organizational features</a>, <a href="https://publications.waset.org/search?q=service%20quality." title=" service quality."> service quality.</a> </p> <a href="https://publications.waset.org/6154/deployment-of-service-quality-characteristics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6154/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6154/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6154/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6154/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6154/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6154/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6154/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6154/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6154/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6154/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6154.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">1866</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1532</span> Genetic Algorithm for Feature Subset Selection with Exploitation of Feature Correlations from Continuous Wavelet Transform: a real-case Application</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=G.%20Van%20Dijck">G. Van Dijck</a>, <a href="https://publications.waset.org/search?q=M.%20M.%20Van%20Hulle"> M. M. Van Hulle</a>, <a href="https://publications.waset.org/search?q=M.%20Wevers"> M. Wevers</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated according to the classification performance. Features derived from the continuous wavelet transform are potentially strongly correlated. GA-s that do not take the correlation structure of features into account are inefficient. The proposed algorithm forms clusters of correlated features and searches for a good candidate set of clusters. Secondly a search within the clusters is performed. Different simulations of the algorithm on a real-case data set with strong correlations between features show the increased classification performance. Comparison is performed with a standard GA without use of the correlation structure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Classification" title="Classification">Classification</a>, <a href="https://publications.waset.org/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/search?q=hierarchicalagglomerative%20clustering" title=" hierarchicalagglomerative clustering"> hierarchicalagglomerative clustering</a>, <a href="https://publications.waset.org/search?q=wavelet%20transform." title=" wavelet transform."> wavelet transform.</a> </p> <a href="https://publications.waset.org/3763/genetic-algorithm-for-feature-subset-selection-with-exploitation-of-feature-correlations-from-continuous-wavelet-transform-a-real-case-application" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/3763/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/3763/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/3763/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/3763/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/3763/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/3763/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/3763/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/3763/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/3763/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/3763/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/3763.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">1224</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1531</span> Native Language Identification with Cross-Corpus Evaluation Using Social Media Data: 'Reddit'</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Yasmeen%20Bassas">Yasmeen Bassas</a>, <a href="https://publications.waset.org/search?q=Sandra%20Kuebler"> Sandra Kuebler</a>, <a href="https://publications.waset.org/search?q=Allen%20Riddell"> Allen Riddell</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Native Language Identification is one of the growing subfields in Natural Language Processing (NLP). The task of Native Language Identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL) and then the trained models are evaluated on a different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and Logistic Regression. Results show that content-based features are more accurate and robust than content independent ones when tested within corpus and across corpus.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=NLI" title="NLI">NLI</a>, <a href="https://publications.waset.org/search?q=NLP" title=" NLP"> NLP</a>, <a href="https://publications.waset.org/search?q=content-based%20features" title=" content-based features"> content-based features</a>, <a href="https://publications.waset.org/search?q=content%20independent%0D%0Afeatures" title=" content independent features"> content independent features</a>, <a href="https://publications.waset.org/search?q=social%20media%20corpus" title=" social media corpus"> social media corpus</a>, <a href="https://publications.waset.org/search?q=ML." title=" ML."> ML.</a> </p> <a href="https://publications.waset.org/10012918/native-language-identification-with-cross-corpus-evaluation-using-social-media-data-reddit" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10012918/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10012918/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10012918/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10012918/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10012918/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10012918/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10012918/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10012918/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10012918/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10012918/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10012918.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">414</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1530</span> Image Retrieval: Techniques, Challenge, and Trend</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hui%20Hui%20Wang">Hui Hui Wang</a>, <a href="https://publications.waset.org/search?q=Dzulkifli%20Mohamad"> Dzulkifli Mohamad</a>, <a href="https://publications.waset.org/search?q=N.A%20Ismail"> N.A Ismail</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper attempts to discuss the evolution of the retrieval techniques focusing on development, challenges and trends of the image retrieval. It highlights both the already addressed and outstanding issues. The explosive growth of image data leads to the need of research and development of Image Retrieval. However, Image retrieval researches are moving from keyword, to low level features and to semantic features. Drive towards semantic features is due to the problem of the keywords which can be very subjective and time consuming while low level features cannot always describe high level concepts in the users- mind. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=content%20based%20image%20retrieval" title="content based image retrieval">content based image retrieval</a>, <a href="https://publications.waset.org/search?q=keyword%20based%20imageretrieval" title=" keyword based imageretrieval"> keyword based imageretrieval</a>, <a href="https://publications.waset.org/search?q=semantic%20gap" title=" semantic gap"> semantic gap</a>, <a href="https://publications.waset.org/search?q=semantic%20image%20retrieval." title=" semantic image retrieval."> semantic image retrieval.</a> </p> <a href="https://publications.waset.org/6291/image-retrieval-techniques-challenge-and-trend" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6291/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6291/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6291/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6291/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6291/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6291/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6291/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6291/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6291/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6291/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6291.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">2524</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1529</span> Hybrid Anomaly Detection Using Decision Tree and Support Vector Machine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Elham%20Serkani">Elham Serkani</a>, <a href="https://publications.waset.org/search?q=Hossein%20Gharaee%20Garakani"> Hossein Gharaee Garakani</a>, <a href="https://publications.waset.org/search?q=Naser%20Mohammadzadeh"> Naser Mohammadzadeh</a>, <a href="https://publications.waset.org/search?q=Elaheh%20Vaezpour"> Elaheh Vaezpour</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Intrusion%20detection%20system" title="Intrusion detection system">Intrusion detection system</a>, <a href="https://publications.waset.org/search?q=decision%20tree" title=" decision tree"> decision tree</a>, <a href="https://publications.waset.org/search?q=support%20vector%20machine" title=" support vector machine"> support vector machine</a>, <a href="https://publications.waset.org/search?q=feature%20selection." title=" feature selection."> feature selection.</a> </p> <a href="https://publications.waset.org/10009167/hybrid-anomaly-detection-using-decision-tree-and-support-vector-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10009167/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10009167/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10009167/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10009167/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10009167/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10009167/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10009167/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10009167/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10009167/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10009167/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10009167.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">1239</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1528</span> Improving Classification in Bayesian Networks using Structural Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hong%20Choon%20Ong">Hong Choon Ong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Naïve Bayes classifiers are simple probabilistic classifiers. Classification extracts patterns by using data file with a set of labeled training examples and is currently one of the most significant areas in data mining. However, Naïve Bayes assumes the independence among the features. Structural learning among the features thus helps in the classification problem. In this study, the use of structural learning in Bayesian Network is proposed to be applied where there are relationships between the features when using the Naïve Bayes. The improvement in the classification using structural learning is shown if there exist relationship between the features or when they are not independent. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Bayesian%20Network" title="Bayesian Network">Bayesian Network</a>, <a href="https://publications.waset.org/search?q=Classification" title=" Classification"> Classification</a>, <a href="https://publications.waset.org/search?q=Na%C3%AFve%20Bayes" title=" Naïve Bayes"> Naïve Bayes</a>, <a href="https://publications.waset.org/search?q=Structural%20Learning." title="Structural Learning.">Structural Learning.</a> </p> <a href="https://publications.waset.org/15047/improving-classification-in-bayesian-networks-using-structural-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/15047/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/15047/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/15047/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/15047/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/15047/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/15047/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/15047/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/15047/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/15047/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/15047/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/15047.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">2599</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1527</span> Using the Keystrokes Dynamic for Systems of Personal Security</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Gl%C3%A1ucya%20C.%20Boechat">Gláucya C. Boechat</a>, <a href="https://publications.waset.org/search?q=Jeneffer%20C.%20Ferreira"> Jeneffer C. Ferreira</a>, <a href="https://publications.waset.org/search?q=Edson%20C.%20B.%20Carvalho"> Edson C. B. Carvalho</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a boarding on biometric authentication through the Keystrokes Dynamics that it intends to identify a person from its habitual rhythm to type in conventional keyboard. Seven done experiments: verifying amount of prototypes, threshold, features and the variation of the choice of the times of the features vector. The results show that the use of the Keystroke Dynamics is simple and efficient for personal authentication, getting optimum resulted using 90% of the features with 4.44% FRR and 0% FAR. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Biometrics%20techniques" title="Biometrics techniques">Biometrics techniques</a>, <a href="https://publications.waset.org/search?q=Keystroke%20Dynamics" title=" Keystroke Dynamics"> Keystroke Dynamics</a>, <a href="https://publications.waset.org/search?q=patternrecognition." title=" patternrecognition."> patternrecognition.</a> </p> <a href="https://publications.waset.org/4018/using-the-keystrokes-dynamic-for-systems-of-personal-security" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/4018/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/4018/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/4018/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/4018/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/4018/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/4018/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/4018/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/4018/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/4018/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/4018/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/4018.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">1741</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1526</span> Investigation on Feature Extraction and Classification of Medical Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=P.%20Gnanasekar">P. Gnanasekar</a>, <a href="https://publications.waset.org/search?q=A.%20Nagappan"> A. Nagappan</a>, <a href="https://publications.waset.org/search?q=S.%20Sharavanan"> S. Sharavanan</a>, <a href="https://publications.waset.org/search?q=O.%20Saravanan"> O. Saravanan</a>, <a href="https://publications.waset.org/search?q=D.%20Vinodkumar"> D. Vinodkumar</a>, <a href="https://publications.waset.org/search?q=T.%20Elayabharathi"> T. Elayabharathi</a>, <a href="https://publications.waset.org/search?q=G.%20Karthik"> G. Karthik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc.. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=ACO%20Ant%20Colony%20Optimization" title="ACO Ant Colony Optimization">ACO Ant Colony Optimization</a>, <a href="https://publications.waset.org/search?q=Correlogram" title=" Correlogram"> Correlogram</a>, <a href="https://publications.waset.org/search?q=CCM%0ACo-Occurrence%20Matrix" title=" CCM Co-Occurrence Matrix"> CCM Co-Occurrence Matrix</a>, <a href="https://publications.waset.org/search?q=RTS%20Rough-Set%20theory" title=" RTS Rough-Set theory"> RTS Rough-Set theory</a> </p> <a href="https://publications.waset.org/11279/investigation-on-feature-extraction-and-classification-of-medical-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/11279/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/11279/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/11279/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/11279/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/11279/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/11279/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/11279/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/11279/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/11279/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/11279/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/11279.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">3012</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1525</span> Realization of Design Features for Linear Flow Splitting in NX 6</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Anselm%20L.%20Sch%C3%BCle">Anselm L. Schüle</a>, <a href="https://publications.waset.org/search?q=Thomas%20Rollmann"> Thomas Rollmann</a>, <a href="https://publications.waset.org/search?q=Reiner%20Anderl"> Reiner Anderl</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Within the collaborative research center 666 a new product development approach and the innovative manufacturing method of linear flow splitting are being developed. So far the design process is supported by 3D-CAD models utilizing User Defined Features in standard CAD-Systems. This paper now presents new functions for generating 3D-models of integral sheet metal products with bifurcations using Siemens PLM NX 6. The emphasis is placed on design and semi-automated insertion of User Defined Features. Therefore User Defined Features for both, linear flow splitting and its derivative linear bend splitting, were developed. In order to facilitate the modeling process, an application was developed that guides through the insertion process. Its usability and dialog layout adapt known standard features. The work presented here has significant implications on the quality, accurateness and efficiency of the product generation process of sheet metal products with higher order bifurcations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Linear%20Flow%20Splitting" title="Linear Flow Splitting">Linear Flow Splitting</a>, <a href="https://publications.waset.org/search?q=CRC%20666" title=" CRC 666"> CRC 666</a>, <a href="https://publications.waset.org/search?q=User%20Defined%20Features." title=" User Defined Features."> User Defined Features.</a> </p> <a href="https://publications.waset.org/8438/realization-of-design-features-for-linear-flow-splitting-in-nx-6" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8438/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8438/bibtex" target="_blank" rel="nofollow" class="btn btn-primary 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