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IEEE/ACS International Conference on Computer systems and Applications

作者： Nouha Dammak Yassine BenAyed Multimedia InfoRmation system and Advanced Computing Laboratory MIRACL Sfax Tunisia

ISBN: (纸本)9781509004799

In this paper, classifying and indexing hierarchical video genres using Support Vector Machines (SVMs) are based on only audio features. In fact, segmentation parameters are extracted at block levels, which have a major benefit by capturing local temporal information. The main contribution of our study is to present a powerful combination between the two employed audio descriptors;Mel Frequency Cepstral Coefficients (MFCC) and signal energy in order to classify a big YouTube dataset that includes multi-Arabic dialects video genres and even sub-genres: several sports analysis and various matches categories (foot-ball, basket-ball, hand-ball and volley-ball), both studio and fields news scenes over and above various multi-singer and multi-instruments music clips. Validation of this approach was carried out on over 18 hours of video span yielding a classification accuracy of 98,5% for genres, 97% for sports subgenres and 76% for music sub-genres. Finally we discuss SVM kernels performance on our proposed dataset.

关键词： audio feature classification hierarchical segmentation support vector machine video genre

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Graphical Models for Multi-dialect Arabic Isolated Words Recognition

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Procedia Computer Science 2015年 60卷 508-516页

作者： Elyes Zarrouk Yassine BenAyed Faiez Gargouri MIRACL Multimedia InfoRmation system and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia ISIMS University of Sfax Tunisia.

This paper presents the use of multiple hybrid systems for the recognition of isolated words from a large multi-dialect Arabic vocabulary. Such as the Hidden Markov models (HMM), Dynamic Bayesian networks (DBN) lack a discriminatory ability especially on speech recognition even if their progress is huge. Multi-Layer perceptrons (MLP) was applied in literature as an estimator of emission probabilities in HMM and proves it effectiveness. In order to ameliorate the results of recognition systems, we apply Support Vectors Machine (SVM) as an estimator of posterior probabilities since they are characterized by a high predictive power and discrimination. Moreover, they are based on a structural risk minimization (SRM) where the aim is to set up a classifier that minimizes a bound on the expected risk, rather than the empirical risk. In this work we have done a comparative study between three hybrid systems MLP/HMM, SVM/HMM and SVM/DBN and the standards models of HMM and DBN. In this paper, we describe the use of the hybrid model SVM/DBN for multi-dialect Arabic isolated words recognition. So, by using 67,132 speech files of Arabic isolated words, this work arises a comparative study of our acknowledgment system of it as the following: the use of especially the HMM standards leads to a recognition rate of 74.18%.as the average rate of 8 domains for everyone of the 4 dialects. Also, with the hybrid systems MLP/HMM and SVM/HMM we succeed in achieving the value of 77.74%.and 7806% respectively. Moreover, our proposed system SVM/DBN realizes the best performances, whereby, we achieve 87.67% as a recognition rate more than 83.01% obtained by GMM/DBN.

关键词： graphical models hidden markov models dynamic bayesian networks supports vecotrs machine multi-layer perceptrons isoalted words recognition.

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Decision tree transformation for knowledge warehousing 17

Decision tree transformation for knowledge warehousing

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17th International Conference on Enterprise information systems, ICEIS 2015

作者： Ayadi, Rim Hachaichi, Yasser Alshomrani, Saleh Feki, Jamel Multimedia InfoRmation Systems and Advanced Computing Laboratory Sakiet Ezzit Tunisia University of Sfax Sfax Tunisia Faculty of Computing and IT University of Jeddah Jeddah Saudi Arabia

ISBN: (纸本)9789897580970

Explicit knowledge extracted from data, formalized tacit knowledge from experts or even knowledge existing in business sources may be in several heterogeneous formal representations and structures: as rules, models, functions, etc. However, a knowledge warehouse should solve this structural heterogeneity before storing knowledge. This requires specific tasks of harmonizing. This paper first presents our proposed definition and architecture of a knowledge warehouse, and then presents some languages for knowledge representations as particular the MOT (Modeling with Object Types) language. In addition, we suggest a metamodel for the MOT, and a metamodel for the explicit knowledge obtained using decision trees technique. As we aim to represent knowledge having different modeling formalisms into MOT, as a unified model, then we suggest a set of transformation rules that assure the move from the decision tree source model into the MOT target model. This work is still in progress, it is currently completed with tranformations for additional.

关键词： Data mining

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Arabic named entity recognition process using transducer cascade and Arabic wikipedia 10

Arabic named entity recognition process using transducer cas...

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10th International Conference on Recent Advances in Natural Language Processing, RANLP 2015

作者： Mesmia, Fatma Ben Friburger, Nathalie Haddar, Kais Maurel, Denis University of Sfax Laboratory MIRACL Multimedia InfoRmation Systems and Advanced Computing Laboratory Tunisia University François Rabelais of Tours LI Computer laboratory France

Transducers namely transducer cascades are used in several NLP-applications such as Arabic named entity recognition (ANER). To experiment and evaluate an ANER process, a weight coverage corpus is necessary. In this paper, we propose an ANER method based on transducer cascade. The proposed transducer cascade is generated with the CasSys tool integrated in Unitex linguistic platform. The experimentation of our method is done on a Wikipedia corpus. The Wikipedia text format is obtained with Kiwix tool. The experiment results are satisfactory based on calculated measures.

关键词： Transducers

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A system for composition and adaptation of educational resources based on learner profile

A system for composition and adaptation of educational resou...

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International Conference on information and Communication Technology and Accessibility (ICTA)

作者： Fedia Hlioui Nadia Alioui Faiez Gargouri Multimedia InfoRmation system and Advanced Computing Laboratory University of Sfax Sfax Tunisia

computing Environment for Human Learning (CEHL) systems are based on the use of new technologies to improve the quality of learning. However, their training suffers from a crucial problem mainly in the construction of the adapted learning process according to the needs of the learner. In fact thousands of educational resources are available through the web today. Therefore, the learner gets lost and hesitated to choose the most adequate educational resources according to their preferences and state of knowledge. This paper aims to define reusable, accessible and adapted educational resources. For reusing phase, we propose to define a composed educational resource by assembling existing resources through an appropriate schema called also a narrative structure. For the adaptation, we propose a new general learner model. We treat not only the pedagogic aspect, but also the psychological aspect of the learner by including models from cognitive theories such as the MBTI model (Myers-Briggs Type Indicator).

关键词： Adaptation models Object oriented modeling Psychology Electronic learning Metadata Semantics Engines

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Transducers cascades for an automatic recognition of Arabic named entities in order to establish links to free resources 1

Transducers cascades for an automatic recognition of Arabic ...

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1st International Conference on Arabic Computational Linguistics, ACLing 2015

作者： Mesmia, Fatma Ben Friburger, Nathalie Haddar, Kais Maurel, Denis University of Sfax Laboratory MIRACL Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax Tunisia University of François Rabelais of Tours LI Computer Laboratory Tours France

ISBN: (纸本)9781467391559

Arabic named entities (ANE) are often sources of information. That is why they are used by several applications of natural language processing (NLP) mainly in information retrieval. In order to improve the relevance of the information obtained, links to free resources can be established. Indeed, the recognition of these entities requires the use of adequate formalisms. In this paper, we propose an approach based on transducer cascades which allows the recognition of ANE more precisely the dates. This categorycan be an integral part in the events and the names of places. The implementation of the developed transducers cascades elaborated by using the CasSys tool is available under the Unitex platform. The results are motivating. © 2015 IEEE.

关键词： Transducers

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A formal modeling method to enrich the Arabic treebank ATB with syntactic properties 7

A formal modeling method to enrich the Arabic treebank ATB w...

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7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015

作者： Bahloul, Raja Bensalem Haddar, Kais Blache, Philippe Multimedia InfoRmation Systems and Advanced Computing Laboratory Higher Institute of Computer Science and Multimedia Sfax Tunisia Laboratoire Parole et Langage CNRS Université de Provence Aix-en-Provence France

ISBN: (纸本)9789897581588

The enrichment of an Arabic treebank with syntactic properties can facilitate many types of parsing processes. This enrichment allows also the increase of its use in different NLP applications, the acquirement of new linguistic resources and the ease of the probabilistic parsing process by using statistics to limit the properties to the satisfied ones or to the most frequent ones. In this context, our proposed enrichment method is based on a formalization phase, a Property Grammar induction phase from a source treebank and a treebank regeneration phase with a new syntactic property-based representation. Starting with a formalization phase in our enrichment problem may succeed its resolution procedure. In fact, it limits the specification of the data sets and the interactions between them to the used ones, which avoids any duplication. The formalization allows also the anticipation of the constraints to respect in the problem. The implementation of this enrichment method is experimented essentially on the Arabic treebank ATB. This experiment provides us with good and encouraging results and various properties of different types. Copyright © 2015 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Modeling languages

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Fuzzy H∞ Filtering for Nonlinear Networked systems with Multiple Stochastic Time-Varying Delays, Packet Dropouts and Sensor Saturation 34

Fuzzy H∞ Filtering for Nonlinear Networked Systems with Mul...

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第三十四届中国控制会议

作者： XU Xiaoli YAN Huaicheng ZHANG Hao SHI Hongbo Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education School of information Science and Engineering East China University of Science and Technology Key Laboratory of Embedded System and Service Computing Ministry of Education

ISBN: (纸本)9781467374439

This paper investigates the problem of H∞ filter design for a class of nonlinear networked system based on T-S fuzzy model. Multiple stochastic time-varying delays and some incomplete information are considered simultaneously. Incomplete information includes randomly occurring sensor saturation and packet dropouts. Stochastic time-varying delays are depicted as a sequence of stochastic and independent variables, which take values on 0 and 1. Two sets of Bernoulli distributed white noises are introduced to describe randomly occurring sensor saturation and packet dropouts. system conservatism is reduced due to introduce an approach of piecewise quadratic Lyapunov function. By solving a set of linear matrix inequalities(LMIs), the filter parameters are obtained. Finally, a simulation example is provided to illustrate the effectiveness of the proposed filter design approach.

关键词： H ∞ filtering,multiple time-varying delays,randomly occurring sensor saturation,packet dropouts,piecewise quadratic Lyapunov function

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3D Ear Shape Matching Using Joint -Entropy

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Journal of Computer Science & Technology 2015年第3期30卷 565-577页

作者：孙晓鹏李思慧韩枫魏小鹏 Institute of Computer Systems School of Computer and Information Technology Liaoning Normal University Dalian 116029 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China School of Mechanical and Engineering Dalian University of Technology Dalian 116024 China Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian 116622 China

In this article, we investigate the use of joint a-entropy for 3D ear matching by incorporating the local shape feature of 3D ears into the joint a-entropy. First, we extract a sut^cient number of key points from the 3D ear point cloud, and fit the neighborhood of each key point to a single-value quadric surface on product parameter regions. Second, we define the local shape feature vector of each key point as the sampling depth set on the parametric node of the quadric surface. Third, for every pair of gallery ear and probe ear, we construct the minimum spanning tree （MST） on their matched key points. Finally, we minimize the total edge weight of MST to estimate its joint a-entropy the smaller the entropy is, the more similar the ear pair is. We present several examples to demonstrate the advantages of our algorithm, including low time complexity, high recognition rate, and high robustness. To the best of our knowledge, it is the first time that, in computer graphics, the classical information theory of joint a-entropy is used to deal with 3D ear shape recognition.

关键词： joint a-entropy minimum spanning tree local shape feature ear matching ear recognition

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Author Correction: Federated learning enables big data for rare cancer boundary detection

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Nature communications 2023年第1期14卷 436页

作者： Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI

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