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model</title> <meta name="description" content="Search results for: hierarchical model"> <meta name="keywords" content="hierarchical model"> <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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publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7574</span> Applying Gibbs Sampler for Multivariate Hierarchical Linear Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Satoshi%20Usami">Satoshi Usami</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Among various HLM techniques, the Multivariate Hierarchical Linear Model (MHLM) is desirable to use, particularly when multivariate criterion variables are collected and the covariance structure has information valuable for data analysis. In order to reflect prior information or to obtain stable results when the sample size and the number of groups are not sufficiently large, the Bayes method has often been employed in hierarchical data analysis. In these cases, although the Markov Chain Monte Carlo (MCMC) method is a rather powerful tool for parameter estimation, Procedures regarding MCMC have not been formulated for MHLM. For this reason, this research presents concrete procedures for parameter estimation through the use of the Gibbs samplers. Lastly, several future topics for the use of MCMC approach for HLM is discussed.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Gibbs%20sampler" title="Gibbs sampler">Gibbs sampler</a>, <a href="https://publications.waset.org/search?q=Hierarchical%20Linear%20Model" title=" Hierarchical Linear Model"> Hierarchical Linear Model</a>, <a href="https://publications.waset.org/search?q=Markov%20Chain%20Monte%20Carlo" title=" Markov Chain Monte Carlo"> Markov Chain Monte Carlo</a>, <a href="https://publications.waset.org/search?q=Multivariate%20Hierarchical%20Linear%20Model" title=" Multivariate Hierarchical Linear Model"> Multivariate Hierarchical Linear Model</a> </p> <a href="https://publications.waset.org/11498/applying-gibbs-sampler-for-multivariate-hierarchical-linear-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/11498/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/11498/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/11498/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/11498/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/11498/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/11498/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/11498/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/11498/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/11498/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/11498/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/11498.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">1867</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">7573</span> Knowledge Discovery from Production Databases for Hierarchical Process Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Pavol%20Tanuska">Pavol Tanuska</a>, <a href="https://publications.waset.org/search?q=Pavel%20Vazan"> Pavel Vazan</a>, <a href="https://publications.waset.org/search?q=Michal%20Kebisek"> Michal Kebisek</a>, <a href="https://publications.waset.org/search?q=Dominika%20Jurovata"> Dominika Jurovata</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system thus the proposed solution has been verified. The paper documents how is possible to apply the new discovery knowledge to use in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Hierarchical%20process%20control" title="Hierarchical process control">Hierarchical process control</a>, <a href="https://publications.waset.org/search?q=knowledge%20discovery%20from%20databases" title=" knowledge discovery from databases"> knowledge discovery from databases</a>, <a href="https://publications.waset.org/search?q=neural%20network." title=" neural network."> neural network.</a> </p> <a href="https://publications.waset.org/17390/knowledge-discovery-from-production-databases-for-hierarchical-process-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/17390/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/17390/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/17390/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/17390/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/17390/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/17390/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/17390/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/17390/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/17390/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/17390/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/17390.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">1775</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">7572</span> Markov Chain Monte Carlo Model Composition Search Strategy for Quantitative Trait Loci in a Bayesian Hierarchical Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Susan%20J.%20Simmons">Susan J. Simmons</a>, <a href="https://publications.waset.org/search?q=Fang%20Fang"> Fang Fang</a>, <a href="https://publications.waset.org/search?q=Qijun%20Fang"> Qijun Fang</a>, <a href="https://publications.waset.org/search?q=Karl%20Ricanek"> Karl Ricanek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quantitative trait loci (QTL) experiments have yielded important biological and biochemical information necessary for understanding the relationship between genetic markers and quantitative traits. For many years, most QTL algorithms only allowed one observation per genotype. Recently, there has been an increasing demand for QTL algorithms that can accommodate more than one observation per genotypic distribution. The Bayesian hierarchical model is very flexible and can easily incorporate this information into the model. Herein a methodology is presented that uses a Bayesian hierarchical model to capture the complexity of the data. Furthermore, the Markov chain Monte Carlo model composition (MC3) algorithm is used to search and identify important markers. An extensive simulation study illustrates that the method captures the true QTL, even under nonnormal noise and up to 6 QTL. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Bayesian%20hierarchical%20model" title="Bayesian hierarchical model">Bayesian hierarchical model</a>, <a href="https://publications.waset.org/search?q=Markov%20chain%20MonteCarlo%20model%20composition" title=" Markov chain MonteCarlo model composition"> Markov chain MonteCarlo model composition</a>, <a href="https://publications.waset.org/search?q=quantitative%20trait%20loci." title=" quantitative trait loci."> quantitative trait loci.</a> </p> <a href="https://publications.waset.org/10121/markov-chain-monte-carlo-model-composition-search-strategy-for-quantitative-trait-loci-in-a-bayesian-hierarchical-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10121/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10121/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10121/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10121/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10121/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10121/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10121/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10121/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10121/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10121/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10121.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">1962</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">7571</span> The Sizes of Large Hierarchical Long-Range Percolation Clusters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Yilun%20Shang">Yilun Shang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We study a long-range percolation model in the hierarchical lattice ΩN of order N where probability of connection between two nodes separated by distance k is of the form min{αβ−k, 1}, α ≥ 0 and β > 0. The parameter α is the percolation parameter, while β describes the long-range nature of the model. The ΩN is an example of so called ultrametric space, which has remarkable qualitative difference between Euclidean-type lattices. In this paper, we characterize the sizes of large clusters for this model along the line of some prior work. The proof involves a stationary embedding of ΩN into Z. The phase diagram of this long-range percolation is well understood. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=percolation" title="percolation">percolation</a>, <a href="https://publications.waset.org/search?q=component" title=" component"> component</a>, <a href="https://publications.waset.org/search?q=hierarchical%20lattice" title=" hierarchical lattice"> hierarchical lattice</a>, <a href="https://publications.waset.org/search?q=phase%20transition." title=" phase transition."> phase transition.</a> </p> <a href="https://publications.waset.org/3332/the-sizes-of-large-hierarchical-long-range-percolation-clusters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/3332/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/3332/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/3332/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/3332/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/3332/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/3332/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/3332/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/3332/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/3332/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/3332/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/3332.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">1271</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">7570</span> Multi-Label Hierarchical Classification for Protein Function Prediction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Helyane%20B.%20Borges"> Helyane B. Borges</a>, <a href="https://publications.waset.org/search?q=Julio%20Cesar%20Nievola"> Julio Cesar Nievola</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Hierarchical classification is a problem with applications in many areas as protein function prediction where the dates are hierarchically structured. Therefore, it is necessary the development of algorithms able to induce hierarchical classification models. This paper presents experimenters using the algorithm for hierarchical classification called Multi-label Hierarchical Classification using a Competitive Neural Network (MHC-CNN). It was tested in ten datasets the Gene Ontology (GO) Cellular Component Domain. The results are compared with the Clus-HMC and Clus-HSC using the hF-Measure.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Hierarchical%20Classification" title=" Hierarchical Classification"> Hierarchical Classification</a>, <a href="https://publications.waset.org/search?q=Competitive%20Neural%20Network" title=" Competitive Neural Network"> Competitive Neural Network</a>, <a href="https://publications.waset.org/search?q=Global%20Classifier." title=" Global Classifier."> Global Classifier.</a> </p> <a href="https://publications.waset.org/16089/multi-label-hierarchical-classification-for-protein-function-prediction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/16089/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/16089/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/16089/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/16089/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/16089/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/16089/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/16089/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/16089/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/16089/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/16089/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/16089.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">2380</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">7569</span> Hierarchical Clustering Analysis with SOM Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Diego%20Ordonez">Diego Ordonez</a>, <a href="https://publications.waset.org/search?q=Carlos%20Dafonte"> Carlos Dafonte</a>, <a href="https://publications.waset.org/search?q=Minia%20Manteiga"> Minia Manteiga</a>, <a href="https://publications.waset.org/search?q=Bernardino%20Arcayy"> Bernardino Arcayy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work presents a neural network model for the clustering analysis of data based on Self Organizing Maps (SOM). The model evolves during the training stage towards a hierarchical structure according to the input requirements. The hierarchical structure symbolizes a specialization tool that provides refinements of the classification process. The structure behaves like a single map with different resolutions depending on the region to analyze. The benefits and performance of the algorithm are discussed in application to the Iris dataset, a classical example for pattern recognition. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Neural%20networks" title="Neural networks">Neural networks</a>, <a href="https://publications.waset.org/search?q=Self-organizing%20feature%20maps" title=" Self-organizing feature maps"> Self-organizing feature maps</a>, <a href="https://publications.waset.org/search?q=Hierarchicalsystems" title=" Hierarchicalsystems"> Hierarchicalsystems</a>, <a href="https://publications.waset.org/search?q=Pattern%20clustering%20methods." title=" Pattern clustering methods."> Pattern clustering methods.</a> </p> <a href="https://publications.waset.org/6849/hierarchical-clustering-analysis-with-som-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6849/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6849/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6849/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6849/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6849/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6849/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6849/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6849/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6849/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6849/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6849.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">1947</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">7568</span> Meta-Learning for Hierarchical Classification and Applications in Bioinformatics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Fabio%20Fabris">Fabio Fabris</a>, <a href="https://publications.waset.org/search?q=Alex%20A.%20Freitas"> Alex A. Freitas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Algorithm%20recommendation" title="Algorithm recommendation">Algorithm recommendation</a>, <a href="https://publications.waset.org/search?q=meta-learning" title=" meta-learning"> meta-learning</a>, <a href="https://publications.waset.org/search?q=bioinformatics" title=" bioinformatics"> bioinformatics</a>, <a href="https://publications.waset.org/search?q=hierarchical%20classification." title=" hierarchical classification."> hierarchical classification.</a> </p> <a href="https://publications.waset.org/10009269/meta-learning-for-hierarchical-classification-and-applications-in-bioinformatics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10009269/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10009269/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10009269/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10009269/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10009269/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10009269/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10009269/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10009269/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10009269/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10009269/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10009269.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">1370</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">7567</span> Enhancement Throughput of Unplanned Wireless Mesh Networks Deployment Using Partitioning Hierarchical Cluster (PHC)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Ahmed%20K.%20Hasan">Ahmed K. Hasan</a>, <a href="https://publications.waset.org/search?q=A.%20A.%20Zaidan"> A. A. Zaidan</a>, <a href="https://publications.waset.org/search?q=Anas%20Majeed"> Anas Majeed</a>, <a href="https://publications.waset.org/search?q=B.%20B.%20Zaidan"> B. B. Zaidan</a>, <a href="https://publications.waset.org/search?q=Rosli%20Salleh"> Rosli Salleh</a>, <a href="https://publications.waset.org/search?q=Omar%20Zakaria"> Omar Zakaria</a>, <a href="https://publications.waset.org/search?q=Ali%20Zuheir"> Ali Zuheir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless mesh networks based on IEEE 802.11 technology are a scalable and efficient solution for next generation wireless networking to provide wide-area wideband internet access to a significant number of users. The deployment of these wireless mesh networks may be within different authorities and without any planning, they are potentially overlapped partially or completely in the same service area. The aim of the proposed model is design a new model to Enhancement Throughput of Unplanned Wireless Mesh Networks Deployment Using Partitioning Hierarchical Cluster (PHC), the unplanned deployment of WMNs are determinates there performance. We use throughput optimization approach to model the unplanned WMNs deployment problem based on partitioning hierarchical cluster (PHC) based architecture, in this paper the researcher used bridge node by allowing interworking traffic between these WMNs as solution for performance degradation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Wireless%20Mesh%20Networks" title="Wireless Mesh Networks">Wireless Mesh Networks</a>, <a href="https://publications.waset.org/search?q=802.11s%20Internetworking" title=" 802.11s Internetworking"> 802.11s Internetworking</a>, <a href="https://publications.waset.org/search?q=partitioning%20Hierarchical%20Cluste." title=" partitioning Hierarchical Cluste."> partitioning Hierarchical Cluste.</a> </p> <a href="https://publications.waset.org/15102/enhancement-throughput-of-unplanned-wireless-mesh-networks-deployment-using-partitioning-hierarchical-cluster-phc" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/15102/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/15102/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/15102/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/15102/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/15102/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/15102/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/15102/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/15102/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/15102/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/15102/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/15102.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">1533</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">7566</span> Spatial Econometric Approaches for Count Data: An Overview and New Directions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Paula%20Sim%C3%B5es">Paula Simões</a>, <a href="https://publications.waset.org/search?q=Isabel%20Nat%C3%A1rio"> Isabel Natário</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Spatial%20data%20analysis" title="Spatial data analysis">Spatial data analysis</a>, <a href="https://publications.waset.org/search?q=spatial%20econometrics" title=" spatial econometrics"> spatial econometrics</a>, <a href="https://publications.waset.org/search?q=Bayesian%0D%0Ahierarchical%20models" title=" Bayesian hierarchical models"> Bayesian hierarchical models</a>, <a href="https://publications.waset.org/search?q=count%20data." title=" count data."> count data.</a> </p> <a href="https://publications.waset.org/10003743/spatial-econometric-approaches-for-count-data-an-overview-and-new-directions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10003743/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10003743/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10003743/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10003743/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10003743/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10003743/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10003743/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10003743/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10003743/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10003743/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10003743.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">2704</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">7565</span> Exploring the Activity Fabric of an Intelligent Environment with Hierarchical Hidden Markov Theory</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Chiung-Hui%20Chen">Chiung-Hui Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Behavior" title="Behavior">Behavior</a>, <a href="https://publications.waset.org/search?q=big%20data" title=" big data"> big data</a>, <a href="https://publications.waset.org/search?q=hierarchical%20Hidden%20Markov%20Model" title=" hierarchical Hidden Markov Model"> hierarchical Hidden Markov Model</a>, <a href="https://publications.waset.org/search?q=intelligent%20object." title=" intelligent object."> intelligent object.</a> </p> <a href="https://publications.waset.org/10007896/exploring-the-activity-fabric-of-an-intelligent-environment-with-hierarchical-hidden-markov-theory" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10007896/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10007896/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10007896/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10007896/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10007896/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10007896/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10007896/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10007896/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10007896/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10007896/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10007896.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">764</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">7564</span> A Bayesian Hierarchical 13COBT to Correct Estimates Associated with a Delayed Gastric Emptying</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Leslie%20J.C.Bluck">Leslie J.C.Bluck</a>, <a href="https://publications.waset.org/search?q=Sarah%20J.Jackson"> Sarah J.Jackson</a>, <a href="https://publications.waset.org/search?q=Georgios%20Vlasakakis"> Georgios Vlasakakis</a>, <a href="https://publications.waset.org/search?q=Adrian%20Mander"> Adrian Mander</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Bayesian%20hierarchical%20analysis" title="Bayesian hierarchical analysis">Bayesian hierarchical analysis</a>, <a href="https://publications.waset.org/search?q=13COBT" title=" 13COBT"> 13COBT</a>, <a href="https://publications.waset.org/search?q=Gastricemptying" title=" Gastricemptying"> Gastricemptying</a>, <a href="https://publications.waset.org/search?q=WinBUGS." title=" WinBUGS."> WinBUGS.</a> </p> <a href="https://publications.waset.org/3809/a-bayesian-hierarchical-13cobt-to-correct-estimates-associated-with-a-delayed-gastric-emptying" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/3809/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/3809/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/3809/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/3809/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/3809/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/3809/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/3809/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/3809/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/3809/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/3809/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/3809.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">1455</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">7563</span> Bottom Up Text Mining through Hierarchical Document Representation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Y.%20Djouadi.">Y. Djouadi.</a>, <a href="https://publications.waset.org/search?q=F.%20Souam."> F. Souam.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Most of the existing text mining approaches are proposed, keeping in mind, transaction databases model. Thus, the mined dataset is structured using just one concept: the “transaction", whereas the whole dataset is modeled using the “set" abstract type. In such cases, the structure of the whole dataset and the relationships among the transactions themselves are not modeled and consequently, not considered in the mining process. We believe that taking into account structure properties of hierarchically structured information (e.g. textual document, etc ...) in the mining process, can leads to best results. For this purpose, an hierarchical associations rule mining approach for textual documents is proposed in this paper and the classical set-oriented mining approach is reconsidered profits to a Direct Acyclic Graph (DAG) oriented approach. Natural languages processing techniques are used in order to obtain the DAG structure. Based on this graph model, an hierarchical bottom up algorithm is proposed. The main idea is that each node is mined with its parent node. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Graph%20based%20association%20rules%20mining" title="Graph based association rules mining">Graph based association rules mining</a>, <a href="https://publications.waset.org/search?q=Hierarchical%0Adocument%20structure" title=" Hierarchical document structure"> Hierarchical document structure</a>, <a href="https://publications.waset.org/search?q=Text%20mining." title=" Text mining."> Text mining.</a> </p> <a href="https://publications.waset.org/6348/bottom-up-text-mining-through-hierarchical-document-representation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6348/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6348/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6348/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6348/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6348/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6348/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6348/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6348/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6348/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6348/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6348.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">2057</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">7562</span> Hierarchical Clustering Algorithms in Data Mining</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Z.%20Abdullah">Z. Abdullah</a>, <a href="https://publications.waset.org/search?q=A.%20R.%20Hamdan"> A. R. Hamdan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the area in data mining and it can be classified into partition, hierarchical, density based and grid based. Therefore, in this paper we do survey and review four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems as well as deriving more robust and scalable algorithms for clustering. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Clustering" title="Clustering">Clustering</a>, <a href="https://publications.waset.org/search?q=method" title=" method"> method</a>, <a href="https://publications.waset.org/search?q=algorithm" title=" algorithm"> algorithm</a>, <a href="https://publications.waset.org/search?q=hierarchical" title=" hierarchical"> hierarchical</a>, <a href="https://publications.waset.org/search?q=survey." title=" survey."> survey.</a> </p> <a href="https://publications.waset.org/10002625/hierarchical-clustering-algorithms-in-data-mining" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10002625/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10002625/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10002625/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10002625/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10002625/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10002625/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10002625/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10002625/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10002625/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10002625/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10002625.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">3376</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">7561</span> A Review: Comparative Study of Enhanced Hierarchical Clustering Protocols in WSN</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20Sangeetha">M. Sangeetha</a>, <a href="https://publications.waset.org/search?q=A.%20Sabari"> A. Sabari</a>, <a href="https://publications.waset.org/search?q=T.%20Shanthi%20Priya"> T. Shanthi Priya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Recent advances in wireless networking technologies introduce several energy aware routing protocols in sensor networks. Such protocols aim to extend the lifetime of network by reducing the energy consumption of nodes. Many researchers are looking for certain challenges that are predominant in the grounds of energy consumption. One such protocol that addresses this energy consumption issue is ‘Cluster based hierarchical routing protocol’. In this paper, we intend to discuss some of the major hierarchical routing protocols adhering towards sensor networks. Furthermore, we examine and compare several aspects and characteristics of few widely explored hierarchical clustering protocols, and its operations in wireless sensor networks (WSN). This paper also presents a discussion on the future research topics and the challenges of hierarchical clustering in WSNs.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Clustering" title="Clustering">Clustering</a>, <a href="https://publications.waset.org/search?q=Energy%20Efficiency" title=" Energy Efficiency"> Energy Efficiency</a>, <a href="https://publications.waset.org/search?q=Hierarchical%20routing" title=" Hierarchical routing"> Hierarchical routing</a>, <a href="https://publications.waset.org/search?q=Wireless%20sensor%20networks." title=" Wireless sensor networks."> Wireless sensor networks.</a> </p> <a href="https://publications.waset.org/9999736/a-review-comparative-study-of-enhanced-hierarchical-clustering-protocols-in-wsn" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9999736/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9999736/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9999736/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9999736/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9999736/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9999736/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9999736/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9999736/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9999736/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9999736/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9999736.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">2653</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">7560</span> Robust Image Transmission Over Time-varying Channels using Hierarchical Joint Source Channel Coding </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hatem.%20Elmeddeb">Hatem. Elmeddeb</a>, <a href="https://publications.waset.org/search?q=Noureddine"> Noureddine</a>, <a href="https://publications.waset.org/search?q=Hamdi"> Hamdi</a>, <a href="https://publications.waset.org/search?q=Ammar.%20Bouall%C3%A8gue"> Ammar. Bouallègue</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a joint source-channel coding (JSCC) scheme for time-varying channels is presented. The proposed scheme uses hierarchical framework for both source encoder and transmission via QAM modulation. Hierarchical joint source channel codes with hierarchical QAM constellations are designed to track the channel variations which yields to a higher throughput by adapting certain parameters of the receiver to the channel variation. We consider the problem of still image transmission over time-varying channels with channel state information (CSI) available at 1) receiver only and 2) both transmitter and receiver being informed about the state of the channel. We describe an algorithm that optimizes hierarchical source codebooks by minimizing the distortion due to source quantizer and channel impairments. Simulation results, based on image representation, show that, the proposed hierarchical system outperforms the conventional schemes based on a single-modulator and channel optimized source coding. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Channel-optimized%20VQ%20%28COVQ%29" title="Channel-optimized VQ (COVQ)">Channel-optimized VQ (COVQ)</a>, <a href="https://publications.waset.org/search?q=joint%20optimization" title=" joint optimization"> joint optimization</a>, <a href="https://publications.waset.org/search?q=QAM" title="QAM">QAM</a>, <a href="https://publications.waset.org/search?q=hierarchical%20systems." title=" hierarchical systems."> hierarchical systems.</a> </p> <a href="https://publications.waset.org/14283/robust-image-transmission-over-time-varying-channels-using-hierarchical-joint-source-channel-coding" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14283/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14283/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14283/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14283/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14283/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14283/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14283/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14283/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14283/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14283/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14283.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">1425</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">7559</span> Genetic Programming Approach to Hierarchical Production Rule Discovery</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Basheer%20M.%20Al-Maqaleh">Basheer M. Al-Maqaleh</a>, <a href="https://publications.waset.org/search?q=Kamal%20K.%20Bharadwaj"> Kamal K. Bharadwaj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Automated discovery of hierarchical structures in large data sets has been an active research area in the recent past. This paper focuses on the issue of mining generalized rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses flat rules as initial individuals of GP and discovers hierarchical structure. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy. Experimental results are presented to demonstrate the performance of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Genetic%20Programming" title="Genetic Programming">Genetic Programming</a>, <a href="https://publications.waset.org/search?q=Hierarchy" title=" Hierarchy"> Hierarchy</a>, <a href="https://publications.waset.org/search?q=Knowledge%0ADiscovery%20in%20Database" title=" Knowledge Discovery in Database"> Knowledge Discovery in Database</a>, <a href="https://publications.waset.org/search?q=Subsumption%20Matrix." title=" Subsumption Matrix."> Subsumption Matrix.</a> </p> <a href="https://publications.waset.org/10022/genetic-programming-approach-to-hierarchical-production-rule-discovery" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10022/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10022/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10022/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10022/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10022/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10022/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10022/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10022/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10022/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10022/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10022.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">1451</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">7558</span> Forecasting Models for Steel Demand Uncertainty Using Bayesian Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Watcharin%20Sangma">Watcharin Sangma</a>, <a href="https://publications.waset.org/search?q=Onsiri%20Chanmuang"> Onsiri Chanmuang</a>, <a href="https://publications.waset.org/search?q=Pitsanu%20Tongkhow"> Pitsanu Tongkhow</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p> A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Forecasting%20model" title="Forecasting model">Forecasting model</a>, <a href="https://publications.waset.org/search?q=Steel%20demand%20uncertainty" title=" Steel demand uncertainty"> Steel demand uncertainty</a>, <a href="https://publications.waset.org/search?q=Hierarchical%20Bayesian%20framework" title=" Hierarchical Bayesian framework"> Hierarchical Bayesian framework</a>, <a href="https://publications.waset.org/search?q=Exponential%20smoothing%20method." title=" Exponential smoothing method. "> Exponential smoothing method. </a> </p> <a href="https://publications.waset.org/9998918/forecasting-models-for-steel-demand-uncertainty-using-bayesian-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9998918/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9998918/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9998918/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9998918/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9998918/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9998918/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9998918/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9998918/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9998918/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9998918/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9998918.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">2535</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">7557</span> Agglomerative Hierarchical Clustering Using the Tθ Family of Similarity Measures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Salima%20Kouici">Salima Kouici</a>, <a href="https://publications.waset.org/search?q=Abdelkader%20Khelladi"> Abdelkader Khelladi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this work, we begin with the presentation of the Tθ family of usual similarity measures concerning multidimensional binary data. Subsequently, some properties of these measures are proposed. Finally the impact of the use of different inter-elements measures on the results of the Agglomerative Hierarchical Clustering Methods is studied.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Binary%20data" title="Binary data">Binary data</a>, <a href="https://publications.waset.org/search?q=similarity%20measure" title=" similarity measure"> similarity measure</a>, <a href="https://publications.waset.org/search?q=T%CE%B8%20measures" title=" Tθ measures"> Tθ measures</a>, <a href="https://publications.waset.org/search?q=Agglomerative%20Hierarchical%20Clustering." title=" Agglomerative Hierarchical Clustering."> Agglomerative Hierarchical Clustering.</a> </p> <a href="https://publications.waset.org/10000997/agglomerative-hierarchical-clustering-using-the-tth-family-of-similarity-measures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10000997/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10000997/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10000997/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10000997/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10000997/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10000997/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10000997/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10000997/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10000997/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10000997/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10000997.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">3445</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">7556</span> An E-Assessment Website to Implement Hierarchical Aggregate Assessment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=M.%20Lesage">M. Lesage</a>, <a href="https://publications.waset.org/search?q=G.%20Ra%C3%AEche"> G. Raîche</a>, <a href="https://publications.waset.org/search?q=M.%20Riopel"> M. Riopel</a>, <a href="https://publications.waset.org/search?q=F.%20Fortin"> F. Fortin</a>, <a href="https://publications.waset.org/search?q=D.%20Sebkhi"> D. Sebkhi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This paper describes a Web server implementation of the hierarchical aggregate assessment process in the field of education. This process describes itself as a field of teamwork assessment where teams can have multiple levels of hierarchy and supervision. This process is applied everywhere and is part of the management, education, assessment and computer science fields. The E-Assessment website named “Cluster” records in its database the students, the course material, the teams and the hierarchical relationships between the students. For the present research, the hierarchical relationships are team member, team leader and group administrator appointments. The group administrators have the responsibility to supervise team leaders. The experimentation of the application has been performed by high school students in geology courses and Canadian army cadets for navigation patrols in teams. This research extends the work of Nance that uses a hierarchical aggregation process similar as the one implemented in the “Cluster” application. </p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=E-Learning" title="E-Learning">E-Learning</a>, <a href="https://publications.waset.org/search?q=E-Assessment" title=" E-Assessment"> E-Assessment</a>, <a href="https://publications.waset.org/search?q=Teamwork%20Assessment" title=" Teamwork Assessment"> Teamwork Assessment</a>, <a href="https://publications.waset.org/search?q=Hierarchical%20Aggregate%20Assessment." title=" Hierarchical Aggregate Assessment. "> Hierarchical Aggregate Assessment. </a> </p> <a href="https://publications.waset.org/9997566/an-e-assessment-website-to-implement-hierarchical-aggregate-assessment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9997566/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9997566/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9997566/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9997566/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9997566/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9997566/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9997566/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9997566/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9997566/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9997566/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9997566.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">1836</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">7555</span> Power System Damping Using Hierarchical Fuzzy Multi- Input PSS and Communication Lines Active Power Deviations Input and SVC </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohammad%20Hasan%20Raouf">Mohammad Hasan Raouf</a>, <a href="https://publications.waset.org/search?q=Ahmad%20Rouhani"> Ahmad Rouhani</a>, <a href="https://publications.waset.org/search?q=Mohammad%20Abedini"> Mohammad Abedini</a>, <a href="https://publications.waset.org/search?q=Ebrahim%20Rasooli%20Anarmarzi"> Ebrahim Rasooli Anarmarzi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this paper the application of a hierarchical fuzzy system (HFS) based on MPSS and SVC in multi-machine environment is studied. Also the effect of communication lines active power variance signal between two ΔP<sub>Tie</sub><sub>-</sub><sub>line</sub> regions, as one of the inputs of hierarchical fuzzy multi-input PSS and SVC (HFMPSS & SVC), on the increase of low frequency oscillation damping is examined. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type PSS. The number of rules grows exponentially with the number of variables in a classic fuzzy system. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. Phasor model of SVC is described and used in this paper. The performances of MPSS and ΔP<sub>Tie</sub><sub>-</sub><sub>line</sub> based HFMPSS and also the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. The efficiency of the proposed model is examined by simulating a four-machine power system. Results show that the proposed method is performing satisfactorily within the whole range of disturbances and reduces the cost of system.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Communication%20lines%20active%20power%20variance%20signal" title="Communication lines active power variance signal">Communication lines active power variance signal</a>, <a href="https://publications.waset.org/search?q=Hierarchical%20fuzzy%20system%20%28HFS%29" title=" Hierarchical fuzzy system (HFS)"> Hierarchical fuzzy system (HFS)</a>, <a href="https://publications.waset.org/search?q=Multi-input%20power%20system%20stabilizer%20%28MPSS%29" title=" Multi-input power system stabilizer (MPSS)"> Multi-input power system stabilizer (MPSS)</a>, <a href="https://publications.waset.org/search?q=Static%20VAR%20compensator%20%28SVC%29." title=" Static VAR compensator (SVC)."> Static VAR compensator (SVC).</a> </p> <a href="https://publications.waset.org/9997269/power-system-damping-using-hierarchical-fuzzy-multi-input-pss-and-communication-lines-active-power-deviations-input-and-svc" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9997269/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9997269/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9997269/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9997269/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9997269/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9997269/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9997269/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9997269/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9997269/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9997269/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9997269.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">1670</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">7554</span> Fuzzy Hierarchical Clustering Applied for Quality Estimation in Manufacturing System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Y.%20Q.%20Lv">Y. Q. Lv</a>, <a href="https://publications.waset.org/search?q=C.K.M.%20Lee"> C.K.M. Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper develops a quality estimation method with the application of fuzzy hierarchical clustering. Quality estimation is essential to quality control and quality improvement as a precise estimation can promote a right decision-making in order to help better quality control. Normally the quality of finished products in manufacturing system can be differentiated by quality standards. In the real life situation, the collected data may be vague which is not easy to be classified and they are usually represented in term of fuzzy number. To estimate the quality of product presented by fuzzy number is not easy. In this research, the trapezoidal fuzzy numbers are collected in manufacturing process and classify the collected data into different clusters so as to get the estimation. Since normal hierarchical clustering methods can only be applied for real numbers, fuzzy hierarchical clustering is selected to handle this problem based on quality standards. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Quality%20Estimation" title="Quality Estimation">Quality Estimation</a>, <a href="https://publications.waset.org/search?q=Fuzzy%20Quality%20Mean" title=" Fuzzy Quality Mean"> Fuzzy Quality Mean</a>, <a href="https://publications.waset.org/search?q=Fuzzy%0AHierarchical%20Clustering" title=" Fuzzy Hierarchical Clustering"> Fuzzy Hierarchical Clustering</a>, <a href="https://publications.waset.org/search?q=Fuzzy%20Number" title=" Fuzzy Number"> Fuzzy Number</a>, <a href="https://publications.waset.org/search?q=Manufacturing%20system" title=" Manufacturing system"> Manufacturing system</a> </p> <a href="https://publications.waset.org/5558/fuzzy-hierarchical-clustering-applied-for-quality-estimation-in-manufacturing-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/5558/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/5558/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/5558/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/5558/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/5558/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/5558/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/5558/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/5558/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/5558/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/5558/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/5558.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">1667</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">7553</span> Power System Damping Using Hierarchical Fuzzy Multi- Input Power System Stabilizer and Static VAR Compensator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohammad%20Hasan%20Raouf">Mohammad Hasan Raouf</a>, <a href="https://publications.waset.org/search?q=Ebrahim%20Rasooli%20Anarmarzi"> Ebrahim Rasooli Anarmarzi</a>, <a href="https://publications.waset.org/search?q=Hamid%20Lesani"> Hamid Lesani</a>, <a href="https://publications.waset.org/search?q=Javad%20Olamaei"> Javad Olamaei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This paper proposes the application of a hierarchical fuzzy system (HFS) based on multi-input power system stabilizer (MPSS) and also Static Var Compensator (SVC) in multi-machine environment.The number of rules grows exponentially with the number of variables in a conventional fuzzy logic system. The proposed HFS method is developed to solve this problem. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. In fact, by using HFS the total number of involved rules increases only linearly with the number of input variables. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type Power system stabilizer (PSS). Phasor model of SVC is described and used in this paper. The performances of MPSS, Conventional power system stabilizer (CPSS), hierarchical Fuzzy Multi-input Power System Stabilizer (HFMPSS) and the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. By using digital simulations the comparative study is illustrated. It can be seen that the proposed PSS is performing satisfactorily within the whole range of disturbances.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Power%20system%20stabilizer%20%28PSS%29" title="Power system stabilizer (PSS)">Power system stabilizer (PSS)</a>, <a href="https://publications.waset.org/search?q=hierarchical%20fuzzysystem%20%28HFS%29" title=" hierarchical fuzzysystem (HFS)"> hierarchical fuzzysystem (HFS)</a>, <a href="https://publications.waset.org/search?q=Static%20VAR%20compensator%20%28SVC%29" title=" Static VAR compensator (SVC)"> Static VAR compensator (SVC)</a> </p> <a href="https://publications.waset.org/7203/power-system-damping-using-hierarchical-fuzzy-multi-input-power-system-stabilizer-and-static-var-compensator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/7203/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/7203/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/7203/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/7203/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/7203/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/7203/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/7203/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/7203/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/7203/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/7203/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/7203.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">1526</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">7552</span> Using Suffix Tree Document Representation in Hierarchical Agglomerative Clustering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Daniel%20I.%20Morariu">Daniel I. Morariu</a>, <a href="https://publications.waset.org/search?q=Radu%20G.%20Cretulescu"> Radu G. Cretulescu</a>, <a href="https://publications.waset.org/search?q=Lucian%20N.%20Vintan"> Lucian N. Vintan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In text categorization problem the most used method for documents representation is based on words frequency vectors called VSM (Vector Space Model). This representation is based only on words from documents and in this case loses any “word context" information found in the document. In this article we make a comparison between the classical method of document representation and a method called Suffix Tree Document Model (STDM) that is based on representing documents in the Suffix Tree format. For the STDM model we proposed a new approach for documents representation and a new formula for computing the similarity between two documents. Thus we propose to build the suffix tree only for any two documents at a time. This approach is faster, it has lower memory consumption and use entire document representation without using methods for disposing nodes. Also for this method is proposed a formula for computing the similarity between documents, which improves substantially the clustering quality. This representation method was validated using HAC - Hierarchical Agglomerative Clustering. In this context we experiment also the stemming influence in the document preprocessing step and highlight the difference between similarity or dissimilarity measures to find “closer" documents. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Text%20Clustering" title="Text Clustering">Text Clustering</a>, <a href="https://publications.waset.org/search?q=Suffix%20tree%20documentrepresentation" title=" Suffix tree documentrepresentation"> Suffix tree documentrepresentation</a>, <a href="https://publications.waset.org/search?q=Hierarchical%20Agglomerative%20Clustering" title=" Hierarchical Agglomerative Clustering"> Hierarchical Agglomerative Clustering</a> </p> <a href="https://publications.waset.org/7768/using-suffix-tree-document-representation-in-hierarchical-agglomerative-clustering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/7768/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/7768/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/7768/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/7768/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/7768/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/7768/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/7768/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/7768/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/7768/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/7768/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/7768.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">1910</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">7551</span> Journey on Image Clustering Based on Color Composition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Achmad%20Nizar%20Hidayanto">Achmad Nizar Hidayanto</a>, <a href="https://publications.waset.org/search?q=Elisabeth%20Martha%20Koeanan"> Elisabeth Martha Koeanan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc. This research aims to explore image clustering using color composition. In order to complete this image clustering, three main components should be considered, which are color space, image representation (feature extraction), and clustering method itself. We aim to explore which composition of these factors will produce the best clustering results by combining various techniques from the three components. The color spaces use RGB, HSV, and L*a*b* method. The image representations use Histogram and Gaussian Mixture Model (GMM), whereas the clustering methods use KMeans and Agglomerative Hierarchical Clustering algorithm. The results of the experiment show that GMM representation is better combined with RGB and L*a*b* color space, whereas Histogram is better combined with HSV. The experiments also show that K-Means is better than Agglomerative Hierarchical for images clustering. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Image%20clustering" title="Image clustering">Image clustering</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=RGB" title=" RGB"> RGB</a>, <a href="https://publications.waset.org/search?q=HSV" title=" HSV"> HSV</a>, <a href="https://publications.waset.org/search?q=L%2Aa%2Ab%2A" title="L*a*b*">L*a*b*</a>, <a href="https://publications.waset.org/search?q=Gaussian%20Mixture%20Model%20%28GMM%29" title=" Gaussian Mixture Model (GMM)"> Gaussian Mixture Model (GMM)</a>, <a href="https://publications.waset.org/search?q=histogram" title=" histogram"> histogram</a>, <a href="https://publications.waset.org/search?q=Agglomerative%20Hierarchical%20Clustering%20%28AHC%29" title="Agglomerative Hierarchical Clustering (AHC)">Agglomerative Hierarchical Clustering (AHC)</a>, <a href="https://publications.waset.org/search?q=K-Means" title=" K-Means"> K-Means</a>, <a href="https://publications.waset.org/search?q=Expectation-Maximization%20%28EM%29." title="Expectation-Maximization (EM).">Expectation-Maximization (EM).</a> </p> <a href="https://publications.waset.org/11825/journey-on-image-clustering-based-on-color-composition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/11825/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/11825/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/11825/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/11825/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/11825/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/11825/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/11825/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/11825/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/11825/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/11825/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/11825.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">2206</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">7550</span> Interactive Concept-based Search using MOEA:The Hierarchical Preferences Case</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Gideon%20Avigad">Gideon Avigad</a>, <a href="https://publications.waset.org/search?q=Amiram%20Moshaiov"> Amiram Moshaiov</a>, <a href="https://publications.waset.org/search?q=Neima%20Brauner"> Neima Brauner</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An IEC technique is described for a multi-objective search of conceptual solutions. The survivability of solutions is influenced by both model-based fitness and subjective human preferences. The concepts- preferences are articulated via a hierarchy of sub-concepts. The suggested method produces an objectivesubjective front. Academic example is employed to demonstrate the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Conceptual%20solution" title="Conceptual solution">Conceptual solution</a>, <a href="https://publications.waset.org/search?q=engineering%20design" title=" engineering design"> engineering design</a>, <a href="https://publications.waset.org/search?q=hierarchical%20planning" title="hierarchical planning">hierarchical planning</a>, <a href="https://publications.waset.org/search?q=multi-objective%20search" title=" multi-objective search"> multi-objective search</a>, <a href="https://publications.waset.org/search?q=problem%20reduction." title=" problem reduction."> problem reduction.</a> </p> <a href="https://publications.waset.org/8910/interactive-concept-based-search-using-moeathe-hierarchical-preferences-case" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/8910/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/8910/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/8910/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/8910/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/8910/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/8910/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/8910/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/8910/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/8910/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/8910/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/8910.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">1008</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">7549</span> Survival of Neutrino Mass Models in Nonthermal Leptogenesis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Amal%20Kr%20Sarma">Amal Kr Sarma</a>, <a href="https://publications.waset.org/search?q=H%20Zeen%20Devi"> H Zeen Devi</a>, <a href="https://publications.waset.org/search?q=N%20Nimai%20Singh"> N Nimai Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Constraints imposed by non-thermal leptogenesis on the survival of the neutrino mass models describing the presently available neutrino mass patterns, are studied numerically. We consider the Majorana CP violating phases coming from right-handed Majorana mass matrices to estimate the baryon asymmetry of the universe, for different neutrino mass models namely quasi-degenerate, inverted hierarchical and normal hierarchical models, with tribimaximal mixings. Considering two possible diagonal forms of Dirac neutrino mass matrix as either charged lepton or up-quark mass matrix, the heavy right-handed mass matrices are constructed from the light neutrino mass matrix. Only the normal hierarchical model leads to the best predictions of baryon asymmetry of the universe, consistent with observations in non-thermal leptogenesis scenario. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Thermal%20leptogenesis" title="Thermal leptogenesis">Thermal leptogenesis</a>, <a href="https://publications.waset.org/search?q=Non-thermal%20leptogenesis." title=" Non-thermal leptogenesis."> Non-thermal leptogenesis.</a> </p> <a href="https://publications.waset.org/14566/survival-of-neutrino-mass-models-in-nonthermal-leptogenesis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14566/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14566/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14566/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14566/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14566/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14566/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14566/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14566/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14566/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14566/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14566.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">1286</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">7548</span> A Serial Hierarchical Support Vector Machine and 2D Feature Sets Act for Brain DTI Segmentation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Mohammad%20Javadi">Mohammad Javadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>Serial hierarchical support vector machine (SHSVM) is proposed to discriminate three brain tissues which are white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). SHSVM has novel classification approach by repeating the hierarchical classification on data set iteratively. It used Radial Basis Function (rbf) Kernel with different tuning to obtain accurate results. Also as the second approach, segmentation performed with DAGSVM method. In this article eight univariate features from the raw DTI data are extracted and all the possible 2D feature sets are examined within the segmentation process. SHSVM succeed to obtain DSI values higher than 0.95 accuracy for all the three tissues, which are higher than DAGSVM results.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Brain%20segmentation" title="Brain segmentation">Brain segmentation</a>, <a href="https://publications.waset.org/search?q=DTI" title=" DTI"> DTI</a>, <a href="https://publications.waset.org/search?q=hierarchical" title=" hierarchical"> hierarchical</a>, <a href="https://publications.waset.org/search?q=SVM." title=" SVM."> SVM.</a> </p> <a href="https://publications.waset.org/16401/a-serial-hierarchical-support-vector-machine-and-2d-feature-sets-act-for-brain-dti-segmentation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/16401/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/16401/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/16401/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/16401/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/16401/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/16401/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/16401/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/16401/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/16401/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/16401/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/16401.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">1856</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">7547</span> On the Hierarchical Ergodicity Coefficient</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Yilun%20Shang">Yilun Shang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this paper, we deal with the fundamental concepts and properties of ergodicity coefficients in a hierarchical sense by making use of partition. Moreover, we establish a hierarchial Hajnal’s inequality improving some previous results.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Stochastic%20matrix" title="Stochastic matrix">Stochastic matrix</a>, <a href="https://publications.waset.org/search?q=ergodicity%20coefficient" title=" ergodicity coefficient"> ergodicity coefficient</a>, <a href="https://publications.waset.org/search?q=partition." title=" partition."> partition.</a> </p> <a href="https://publications.waset.org/9996769/on-the-hierarchical-ergodicity-coefficient" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9996769/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/9996769/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/9996769/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/9996769/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/9996769/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/9996769/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/9996769/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/9996769/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/9996769/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/9996769/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/9996769.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">1347</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">7546</span> Applying Clustering of Hierarchical K-means-like Algorithm on Arabic Language</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Sameh%20H.%20Ghwanmeh">Sameh H. Ghwanmeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>In this study a clustering technique has been implemented which is K-Means like with hierarchical initial set (HKM). The goal of this study is to prove that clustering document sets do enhancement precision on information retrieval systems, since it was proved by Bellot & El-Beze on French language. A comparison is made between the traditional information retrieval system and the clustered one. Also the effect of increasing number of clusters on precision is studied. The indexing technique is Term Frequency * Inverse Document Frequency (TF * IDF). It has been found that the effect of Hierarchical K-Means Like clustering (HKM) with 3 clusters over 242 Arabic abstract documents from the Saudi Arabian National Computer Conference has significant results compared with traditional information retrieval system without clustering. Additionally it has been found that it is not necessary to increase the number of clusters to improve precision more.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Hierarchical%20K-mean%20like%20clustering%20%28HKM%29" title="Hierarchical K-mean like clustering (HKM)">Hierarchical K-mean like clustering (HKM)</a>, <a href="https://publications.waset.org/search?q=Kmeans" title=" Kmeans"> Kmeans</a>, <a href="https://publications.waset.org/search?q=cluster%20centroids" title="cluster centroids">cluster centroids</a>, <a href="https://publications.waset.org/search?q=initial%20partition" title=" initial partition"> initial partition</a>, <a href="https://publications.waset.org/search?q=and%20document%20distances" title=" and document distances"> and document distances</a> </p> <a href="https://publications.waset.org/3/applying-clustering-of-hierarchical-k-means-like-algorithm-on-arabic-language" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/3/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/3/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/3/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/3/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/3/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/3/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/3/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/3/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/3/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/3/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/3.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">2572</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">7545</span> TOSOM: A Topic-Oriented Self-Organizing Map for Text Organization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Hsin-Chang%20Yang">Hsin-Chang Yang</a>, <a href="https://publications.waset.org/search?q=Chung-Hong%20Lee"> Chung-Hong Lee</a>, <a href="https://publications.waset.org/search?q=Kuo-Lung%20Ke"> Kuo-Lung Ke</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM was usually applied on data clustering and visualization tasks. However, the SOM has main disadvantage of the need to know the number and structure of neurons prior to training, which are difficult to be determined. Several schemes have been proposed to tackle such deficiency. Examples are growing/expandable SOM, hierarchical SOM, and growing hierarchical SOM. These schemes could dynamically expand the map, even generate hierarchical maps, during training. Encouraging results were reported. Basically, these schemes adapt the size and structure of the map according to the distribution of training data. That is, they are data-driven or dataoriented SOM schemes. In this work, a topic-oriented SOM scheme which is suitable for document clustering and organization will be developed. The proposed SOM will automatically adapt the number as well as the structure of the map according to identified topics. Unlike other data-oriented SOMs, our approach expands the map and generates the hierarchies both according to the topics and their characteristics of the neurons. The preliminary experiments give promising result and demonstrate the plausibility of the method.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Self-organizing%20map" title="Self-organizing map">Self-organizing map</a>, <a href="https://publications.waset.org/search?q=topic%20identification" title=" topic identification"> topic identification</a>, <a href="https://publications.waset.org/search?q=learning%20algorithm" title=" learning algorithm"> learning algorithm</a>, <a href="https://publications.waset.org/search?q=text%20clustering." title=" text clustering."> text clustering.</a> </p> <a href="https://publications.waset.org/7708/tosom-a-topic-oriented-self-organizing-map-for-text-organization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/7708/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/7708/bibtex" target="_blank" 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