Search results for: Ruel A. Welch

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Welch</title> <meta name="description" content="Search results for: Ruel A. Welch"> <meta name="keywords" content="Ruel A. Welch"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="Ruel A. 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Welch"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 4</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Ruel A. Welch</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> The Use of Knowledge Management Systems and ICT Service Desk Management to Minimize the Digital Divide Experienced in the Museum Sector</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Ruel%20A.%20Welch">Ruel A. Welch</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Since the introduction of ServiceNow, the UK鈥檚 Science Museum Group鈥檚 (SMG) ICT service desk portal, there has not been an analysis of the tools available to SMG staff for Just-in-time knowledge acquisition (Knowledge Management Systems) and reporting ICT incidents with a focus on an aspect of professional identity namely, gender. Therefore, it is important for SMG to investigate the apparent disparities so that solutions can be derived to minimize this digital divide if one exists. This study is conducted in the milieu of UK museums, galleries, arts, academic, charitable, and cultural heritage sector. It is acknowledged at SMG that there are challenges with keeping up with an ever-changing digital landscape. Subsequently, this entails the rapid upskilling of staff and developing an infrastructure that supports just-in-time technological knowledge acquisition and reporting technology related issues. This problem was addressed by analysing ServiceNow ICT incident reports and reports from knowledge articles from a six-month period from February to July. This study found a statistically significant relationship between gender and reporting an ICT incident. There is also a significant relationship between gender and the priority level of ICT incident. Interestingly, there is no statistically significant relationship between gender and reading knowledge articles. Additionally, there is no statistically significant relationship between gender and reporting an ICT incident related to the knowledge article that was read by staff. The knowledge acquired from this study is useful to service desk management practice as it will help to inform the creation of future knowledge articles and ICT incident reporting processes.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=digital%20divide" title="digital divide">digital divide</a>, <a href="https://publications.waset.org/search?q=ICT%20service%20desk%20practice" title=" ICT service desk practice"> ICT service desk practice</a>, <a href="https://publications.waset.org/search?q=knowledge%20management%20systems" title=" knowledge management systems"> knowledge management systems</a>, <a href="https://publications.waset.org/search?q=workplace%20learning" title=" workplace learning"> workplace learning</a> </p> <a href="https://publications.waset.org/10012291/the-use-of-knowledge-management-systems-and-ict-service-desk-management-to-minimize-the-digital-divide-experienced-in-the-museum-sector" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10012291/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10012291/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10012291/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10012291/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10012291/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10012291/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10012291/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10012291/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10012291/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10012291/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10012291.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">640</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">3</span> A Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mahmoud%20Elmezain">Mahmoud Elmezain</a>, <a href="https://publications.waset.org/search?q=Ayoub%20Al-Hamadi"> Ayoub Al-Hamadi</a>, <a href="https://publications.waset.org/search?q=J%C3%B6rg%20Appenrodt"> J枚rg Appenrodt</a>, <a href="https://publications.waset.org/search?q=Bernd%20Michaelis"> Bernd Michaelis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Computer%20Vision%20%26%20Image%20Processing" title="Computer Vision & Image Processing">Computer Vision & Image Processing</a>, <a href="https://publications.waset.org/search?q=Gesture%20Recognition" title=" Gesture Recognition"> Gesture Recognition</a>, <a href="https://publications.waset.org/search?q=Pattern%20Recognition" title=" Pattern Recognition"> Pattern Recognition</a>, <a href="https://publications.waset.org/search?q=Application" title=" Application"> Application</a> </p> <a href="https://publications.waset.org/1497/a-hidden-markov-model-based-isolated-and-meaningful-hand-gesture-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1497/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1497/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/1497/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/1497/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/1497/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/1497/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/1497/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/1497/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/1497/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/1497/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/1497.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">2250</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">2</span> On Developing an Automatic Speech Recognition System for Standard Arabic Language</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=R.%20Walha">R. Walha</a>, <a href="https://publications.waset.org/search?q=F.%20Drira"> F. Drira</a>, <a href="https://publications.waset.org/search?q=H.%20El-Abed"> H. El-Abed</a>, <a href="https://publications.waset.org/search?q=A.%20M.%20Alimi"> A. M. Alimi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Automatic Speech Recognition (ASR) applied to Arabic language is a challenging task. This is mainly related to the language specificities which make the researchers facing multiple difficulties such as the insufficient linguistic resources and the very limited number of available transcribed Arabic speech corpora. In this paper, we are interested in the development of a HMM-based ASR system for Standard Arabic (SA) language. Our fundamental research goal is to select the most appropriate acoustic parameters describing each audio frame, acoustic models and speech recognition unit. To achieve this purpose, we analyze the effect of varying frame windowing (size and period), acoustic parameter number resulting from features extraction methods traditionally used in ASR, speech recognition unit, Gaussian number per HMM state and number of embedded re-estimations of the Baum-Welch Algorithm. To evaluate the proposed ASR system, a multi-speaker SA connected-digits corpus is collected, transcribed and used throughout all experiments. A further evaluation is conducted on a speaker-independent continue SA speech corpus. The phonemes recognition rate is 94.02% which is relatively high when comparing it with another ASR system evaluated on the same corpus. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=ASR" title="ASR">ASR</a>, <a href="https://publications.waset.org/search?q=HMM" title=" HMM"> HMM</a>, <a href="https://publications.waset.org/search?q=acoustical%20analysis" title=" acoustical analysis"> acoustical analysis</a>, <a href="https://publications.waset.org/search?q=acoustic%20modeling" title=" acoustic modeling"> acoustic modeling</a>, <a href="https://publications.waset.org/search?q=Standard%20Arabic%20language" title=" Standard Arabic language"> Standard Arabic language</a> </p> <a href="https://publications.waset.org/6086/on-developing-an-automatic-speech-recognition-system-for-standard-arabic-language" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6086/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6086/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6086/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6086/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6086/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6086/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6086/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6086/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6086/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6086/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6086.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">1779</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">1</span> Hand Gesture Recognition Based on Combined Features Extraction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mahmoud%20Elmezain">Mahmoud Elmezain</a>, <a href="https://publications.waset.org/search?q=Ayoub%20Al-Hamadi"> Ayoub Al-Hamadi</a>, <a href="https://publications.waset.org/search?q=Bernd%20Michaelis"> Bernd Michaelis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hand gesture is an active area of research in the vision community, mainly for the purpose of sign language recognition and Human Computer Interaction. In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences using Hidden Markov Models (HMMs). Our system is based on three main stages; automatic segmentation and preprocessing of the hand regions, feature extraction and classification. In automatic segmentation and preprocessing stage, color and 3D depth map are used to detect hands where the hand trajectory will take place in further step using Mean-shift algorithm and Kalman filter. In the feature extraction stage, 3D combined features of location, orientation and velocity with respected to Cartesian systems are used. And then, k-means clustering is employed for HMMs codeword. The final stage so-called classification, Baum- Welch algorithm is used to do a full train for HMMs parameters. The gesture of alphabets and numbers is recognized using Left-Right Banded model in conjunction with Viterbi algorithm. Experimental results demonstrate that, our system can successfully recognize hand gestures with 98.33% recognition rate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Gesture%20Recognition" title="Gesture Recognition">Gesture Recognition</a>, <a href="https://publications.waset.org/search?q=Computer%20Vision%20%26%20Image%20Processing" title=" Computer Vision & Image Processing"> Computer Vision & Image Processing</a>, <a href="https://publications.waset.org/search?q=Pattern%20Recognition." title=" Pattern Recognition."> Pattern Recognition.</a> </p> <a href="https://publications.waset.org/1761/hand-gesture-recognition-based-on-combined-features-extraction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/1761/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/1761/bibtex" target="_blank" rel="nofollow" class="btn btn-primary 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Search results for: Ruel A. Welch