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15th International Conference on Information Technology Based Higher Education and Training, ITHET 2016

作者： Elghibari, Fatiha Elouahbi, Rachid El Khoukhi, Fatima Ezzahri, Layla Macs, Labo Amali, Said Department of Mathematics and Computer Science Moulay Ismail University Faculty of Sciences Meknes Morocco Team Modeling Applied Informatics in Humanities MIASH Moulay Ismail University Faculty of Humanities Meknes Morocco Team Théorie des Systèmes et Informatique TSI Moulay Ismail University Faculty of Sciences Meknes Morocco Team Outils Mathématiques en Economie Gestion et Actuariat OMEGA Moulay Ismail University Faculty of Juridical Economic and Social Sciences Meknes Morocco

ISBN: (纸本)9781509007783

Learner satisfaction is an important factor for a successful e-Learning. It allows learners to continue learning and provide their conveniences to facilitate the knowledge. That is why, the main purpose of this study is to enhance learning services in online environments, in order to keep learners' motivation and track their cognition' evolution. Namely, identify their satisfaction toward new inserted contents. In this paper, we present a learning model that detects satisfaction' degree of learners at two levels;during and after completing the course. During learning by using satisfaction agent (SA) that collects data and calculates satisfaction level towards each content' unit. This process allows to integrate improvement if we have a low levels of satisfaction. And after completing course in order to evaluate the evolution of learners' knowledge, and test the effectiveness of the methods and tools used in. © 2016 IEEE.

关键词： Motivation

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Intelligent model for measuring learners' satisfaction towards new contents

Intelligent model for measuring learners' satisfaction towar...

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International Conference on Information Technology Based Higher Education and Training, ITHET

作者： Fatiha Elghibari Rachid Elouahbi Fatima El Khoukhi Layla Ezzahri Said Amali Department of mathematics and computer Science Moulay Ismail University Meknes Morocco Team Modeling Applied Informatics in Humanities MIASH Moulay Ismail University Meknes Morocco Faculty of Sciences Moulay Ismail University Meknes Morocco Team Outils Mathématiques en Economie Moulay Ismail University Meknes Morocco

ISBN: (纸本)9781509007790

Learner satisfaction is an important factor for a successful e-Learning. It allows learners to continue learning and provide their conveniences to facilitate the knowledge. That is why, the main purpose of this study is to enhance learning services in online environments, in order to keep learners' motivation and track their cognition' evolution. Namely, identify their satisfaction toward new inserted contents. In this paper, we present a learning model that detects satisfaction' degree of learners at two levels; during and after completing the course. During learning by using satisfaction agent (SA) that collects data and calculates satisfaction level towards each content' unit. This process allows to integrate improvement if we have a low levels of satisfaction. And after completing course in order to evaluate the evolution of learners' knowledge, and test the effectiveness of the methods and tools used in.

关键词： Electronic learning Training Computational modeling Mathematical model computer science

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Author Correction: A human immune dysregulation syndrome characterized by severe hyperinflammation with a homozygous nonsense Roquin-1 mutation

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Nature communications 2019年第1期10卷 5337页

作者： S J Tavernier V Athanasopoulos P Verloo G Behrens J Staal D J Bogaert L Naesens M De Bruyne S Van Gassen E Parthoens J Ellyard J Cappello L X Morris H Van Gorp G Van Isterdael Y Saeys M Lamkanfi P Schelstraete J Dehoorne V Bordon R Van Coster B N Lambrecht B Menten R Beyaert C G Vinuesa V Heissmeyer M Dullaers F Haerynck Primary Immune Deficiency Research Lab Department of Internal Medicine and Pediatrics Centre for Primary Immunodeficiency Ghent Jeffrey Modell Diagnosis and Research Centre Ghent University Hospital Ghent Belgium. VIB Center for Inflammation Research Unit of Molecular Signal Transduction in Inflammation Ghent Belgium. Department of Biomedical Molecular Biology Ghent University Ghent Belgium. Department of Immunology and Infectious Disease and Center for Personalised Immunology (NHMRC Centre for Research Excellence) John Curtin School of Medical Research Australian National University Canberra Australia. Centre for Personalised Immunology (CACPI) Shanghai Renji Hospital Shanghai Jiao Tong University Shanghai China. Department of Internal Medicine and Pediatrics Division of Pediatric Neurology and Metabolism Ghent University Hospital Ghent Belgium. Institute for Immunology Biomedical Center Ludwig-Maximilians-Universität München Planegg-Martinsried Germany. Research Unit Molecular Immune Regulation Helmholtz Zentrum München Munich Germany. Department of Internal Medicine and Pediatrics Division of Pediatric Immunology and Pulmonology Ghent University Hospital Ghent Belgium. Department of Internal Medicine and Pediatrics Ghent University Hospital Ghent Belgium. Center for Medical Genetics Ghent University Hospital Ghent Belgium. VIB Center for Inflammation Research Unit of Data Mining and Modeling for Biomedicine Ghent Belgium. Department of Applied Mathematics Computer Science and Statistics Ghent University Gent Belgium. VIB Bioimaging Core VIB Center for Inflammation Research Ghent Belgium. The Australian Phenomics Facility John Curtin School of Medical Research Australian National University Canberra Australia. VIB Center for Inflammation Research Ghent Belgium. VIB Flow Core VIB Center for Inflammation Research Ghent Belgium. Department of Internal Medicine and Pediatrics Division of Pediatric Rheumatology Ghent University Hospital Ghent Belgium. D

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Intelligent e-learning system model for maintenance of updates courses

Intelligent e-learning system model for maintenance of updat...

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International Conference on Information Technology Based Higher Education and Training, ITHET

作者： Fatiha Elghibari Rachid Elouahbi Fatima Elkhoukhi Sanae Chehbi Imane Kamsa Department of mathematics and computer Science Moulay Ismail University Meknes Morocco Team Modeling Applied Informatics in Humanities Moulay Ismail University Meknes Morocco

E-learning is becoming the most popular educational system used in the world, the learners can easily access to the information at anywhere in anytime. The teaching methods used in this context are effective because they can combine practice and feedback, to combine collaborative activities with individualized learning, customized learning paths based on the needs of learners and to offer educational games and simulations. However, the lack of courses updates can bring some educational problems to the learner and the process of updating becomes very difficult and tiring to the tutor. This study aims to improve the learning quality by providing a good content, courses materials updated and well-structured to the learners in the one hand, and minimize the time and labor spent in the process of updating, changing the learning and looking for the content to the tutor in the other hand. The proposed system provides an automatic maintenance of updates courses by using intelligent agents.

关键词： Electronic learning Intelligent agents Adaptive systems Computational modeling Maintenance engineering computer science

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Erratum to: A novel revenue optimization model to address the operation and maintenance cost of a data center

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Journal of Cloud Computing 2016年第1期5卷 1-1页

作者： Snehanshu Saha Jyotirmoy Sarkar Avantika Dwivedi Nandita Dwivedi Anand M. Narasimhamurthy Ranjan Roy Shrisha Rao Center for Applied Mathematical Modeling and Simulation (CAMMS) & Department of Computer Science and Engineering PESIT-BSC Bangalore India GE Healthcare Bangalore India BITS Pilani Hyderabad India State Resource Centre Chattisgarh India IIIT Bangalore Bangalore India

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The ACE1 thoracic Electrical Impedance Tomography system for ventilation and perfusion 37

The ACE1 thoracic Electrical Impedance Tomography system for...

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37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015

作者： Mellenthin, Michelle M. Mueller, Jennifer L. De Camargo, Erick Dario Leon Bueno De Moura, Fernando Silva Hamilton, Sarah J. Lima, Raul Gonzalez School of Biomedical Engineering Colorado State University Fort CollinsCO United States Department of Mathematics and School of Biomedical Engineering Colorado State University Fort CollinsCO United States Center for Engineering Modeling and Applied Social Sciences Federal University of ABC São Paulo Brazil Department of Mathematics Statistics and Computer Science Marquette University MilwaukeeWI United States Mechanical Engineering Department University of São Paulo Brazil

ISBN: (纸本)9781424492718

Electrical Impedance Tomography (EIT) is a technique which can image the varying electrical properties of biological tissues. For clinical use of EIT, it can be advantageous to know both tissue conductivity and permittivity. Presented is the hardware design for the pairwise current injection active complex electrode (ACE1) EIT system which measures phasic voltages for conductivity and permittivity image reconstruction. In this system, alternating current is injected on electrodes on the boundary of a domain and single-ended voltage measurements are used in image reconstructions of the domain's interior and in calculating the current applied at the electrodes. © 2015 IEEE.

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Application of regression trees in optimization of metal forming process 15

Application of regression trees in optimization of metal for...

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15th International Conference on Metal Forming 2014

作者： Regulski, Krzysztof Szeliga, Danuta Kusiak, Jan Department of Applied Computer Science and Modeling AGH University of Science and Technology Al. Mickiewicza 30 Kraków30-059 Poland

ISBN: (纸本)9783038351931

Application of sensitivity analysis in optimization of process parameters of production processes for innovative materials, e.g. dual phase steel, requires deterministic model of thermomechanical processes and large datasets that covers whole surface of results. Difficulties in optimization of process parameters correspond with large number of control variables, which should be considered in the technology design. Furthermore, conduction of such analysis takes the great computational cost. Presented work concerns possibility of application of regression trees, especially CART model, in preliminary analysis for sensitivity analysis. Use of data mining algorithms enables acquiring of preliminary, rough results: relationships among parameters of the hot rolling process of dual phase steel strips and rules of optimization of this process, it also does not require any apriori knowledge about thermomechanical processes. © (2014) Trans Tech Publications, Switzerland.

关键词： Sensitivity analysis

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The ACE1 Thoracic Electrical Impedance Tomography System for Ventilation and Perfusion

The ACE1 Thoracic Electrical Impedance Tomography System for...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Michelle M. Mellenthin Jennifer L. Mueller Erick Dario León Bueno de Camargo Fernando Silva de Moura Sarah J. Hamilton Raul Gonzalez Lima School of Biomedical Engineering Colorado State University Fort Collins CO USA Department of Mathematics and School of Biomedical Engineering Colorado State University Fort Collins CO USA Center for Engineering Modeling and Applied Social Sciences Federal University of ABC S?o Paulo Brazil Department of Mathematics Statistics and Computer Science Marquette University Milwaukee WI USA Mechanical Engineering Department University of S?o Paulo S?o Paulo Brazil

ISBN: (纸本)9781424492695

Electrical Impedance Tomography (EIT) is a technique which can image the varying electrical properties of biological tissues. For clinical use of EIT, it can be advantageous to know both tissue conductivity and permittivity. Presented is the hardware design for the pair wise current injection active complex electrode (ACE1) EIT system which measures phasic voltages for conductivity and permittivity image reconstruction. In this system, alternating current is injected on electrodes on the boundary of a domain and single-ended voltage measurements are used in image reconstructions of the domain's interior and in calculating the current applied at the electrodes.

关键词： ACE1 Ventilation and Perfusion EIT

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