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Convolution gradient method based on fitness-driven design considering global information

ICIC Express Letters 2014年第3期8卷 651-659页

作者： Domoto, Eri Okuhara, Koji Koide, Noriaki Ueno, Nobuyuki Department of Media Business Hiroshima University of Economics 5-37-1 Gion Asaminami-Ku Hiroshima 731-0192 Japan Department of Information and Physical Sciences Graduate School of Information Science and Technology Osaka University 1-5 Yamadaoka Suita Osaka 565-0871 Japan Graduate School of Comprehensive Scientific Research Program in Management and Information Systems Prefectural University of Hiroshima 1-1-71 Ujina-Higashi Minami-ku Hiroshima City Hiroshima 734-8558 Japan

In many industries, a usual business model has a problem to realize mass customization, because it is difficult to satisfy the diversified customer needs. Total supply chain optimization is formulated as a stochastic programming problem, and then it is difficult to obtain a better solution for it. In this paper, we have proposed a new hybrid dynamical system of convolution gradient dynamics and swarm intelligence for finding a better optimal solution. Dynamics of convolution gradient has been derived in neural network framework. Swarm intelligence is the optimization technique based on the action of groups, such as birds, fish, and a colony of ants. From a theoretical point of view, we show how to combine them. The proposed hybrid algorithm can realize the interpolation search which is the mechanism of the dynamics of local search and global search. In numerical examples, we show that the proposed model can behave better dynamics for test functions and application of total supply chain optimization. © 2014 ICIC International.

关键词： Convolution

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An image mining based approach to detect pressure ulcer stage

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Pattern Recognition and Image Analysis 2014年第2期24卷 292-296页

作者： Guadagnin, R. Neves, R.de S. Santana, L.A. Guilhem, D.B. MS Program on Information Technology and Knowledge Management SGAN 916 Modulo B Catholic University of Brasilia 70790-160 Brasilia DF Brazil 72.300-175 Samambaia DF Brazil Bachelor Degree on Physiotherapy Catholic University of Brasilia Campus I QS 07 Lote 01 EPCT 71966-700 Aguas Claras Taguatinga DF Brazil

Treatment of pressure ulcers (PU) is essentially image dependent, because its surface provides relevant visual information for medical procedures. There is an increasing interest to adapt information technology advances for a more effective medical image processing. Artificial Intelligence concerned techniques, say Image Mining, can be very helpful to manage large amount of PU images in order to increase productivity of health professionals and patients life quality. This paper proposes an Image Mining based system for automatic interpretation of tissue and color to support the treatment of patients with PU. © 2014 Pleiades Publishing, Ltd.

关键词： Patient treatment

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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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An approach to provide visual information to support skin wounds therapy

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Pattern Recognition and Image Analysis 2014年第1期24卷 81-85页

作者： Guadagnin, R. Santana, L.A. Brasil', L.M. Neves, R.S. MS Program in Information Technology and Knowledge Management Catholic University of Brasília Campus II SGAN 916 Norte 70. 790-160 Brasília DF Brazil BS Course in Physiotherapy Catholic University of Brasília Campus I QS 07 Lote 01 EPCT 71. 966-700 Águas Claras Taguatinga DF Brazil Faculdade Gama Setor Central University of Brasilia 72405-610 Gama DF Brazil 300-573 Samambaia DF Brazil

Availability of visual information means an effective way to improve specialized work in quite different areas. They enable reality modeling, a faster context analysis, a more successful search for problem solutions, an objective oriented decision making, as well as important elements for instructional processes. Avisual model is a simulation form that stimulate insights, say, creative answers to yet open questions and derivation of yet not imagined possible facts concerning a studied reality. Visual features of human body are highly relevant as basic information for a variety of decisions on activities in health domain. Through mechanisms of user-friendly interface one can promptly access and eventually perform adjustments. One can achieve better life quality and greater efficiency in health service from state as well. This paper describes an approach towards a visualization process of skin lesions, including features recognition for therapeutic processes and relevant decisions, with experimental validation. © 2014 Pleiades Publishing, Ltd.

关键词： Visualization

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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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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

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Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

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A lightweight method for wireless sensor network intrusion detections

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ICIC Express Letters 2013年第6期7卷 1793-1798页

作者： Chen, Rung-Ching Hsieh, Chia-Fen Huang, Yung-Fa Department of Information Management College of Informatics Chaoyang University of Technology No. 168 Jifeng E. Rd Wufeng District Taichung 41349 Taiwan Graduate Institute of Informatics Doctoral Program College of Informatics Chaoyang University of Technology No. 168 Jifeng E. Rd Wufeng District Taichung 41349 Taiwan Department of Information and Communication Engineering College of Informatics Chaoyang University of Technology No. 168 Jifeng E. Rd Wufeng District Taichung 41349 Taiwan

Wireless sensor networks can be applied to health care and disaster response, etc. The importance and accuracy of the information requirements of wireless sensors are more stringent. It corresponding to the use of information security should be taken seriously. The detection technology of intrusion detection system (IDS) will affect the lifetime of entire wireless sensor network (WSN). This study combines ontology with intrusion detection system to propose a lightweight ontology intrusion detection system (OWIDS). The system builds the relationship of sensor node in the ontology to detect Sybil attack firstly. The patrol node loads a part of the ontology to detect Sybil attack. Finally, the system uses the isolation table to continue isolation abnormal nodes to avoid duplicate detection energy-consuming. The preliminary experimental result shows that our proposed method can reduce the energy consumption for wireless sensor network intrusion detection, and improve the availability of intrusion detection systems. © 2013 ISSN 1881-803X.

关键词： Ontology

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Ontologies for support preventive maintenance processes of critical IT assets 22

Ontologies for support preventive maintenance processes of c...

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22nd International Conference on Production Research, ICPR 2013

作者： Czelusniak, D.J. De Abreu, A.F. Souza, J.A. Dergint, D.E.A. Federal University of Santa Catarina Engineering Production Post Graduate Program Technological Center P.O. Box 476 Trindade Florianópolis SCCEP 88010-970 Brazil Federal University of Santa Catarina Knowledge Management Engineering Post Graduate Program Technological Center P.O.Box 476 Trindade Florianópolis SC.CEP 88010-970 Brazil Federal Technological University of Paraná Technology Post Graduate Program 3165 Sete de Setembro Avenue Rebouças Curitiba PR.CEP 80230-901 Brazil

The goal of this paper is to show a study to evaluate the possibility of using ontologies to support maintenance procedures in IT equipment in a small power company. The aim is to improve the degree of reliability in detection of potential failures and defects in maintenance processes of information technology critical assets, trying to obtain less downtime of services that they provide. The methodological procedures used in this study were literature review, to present the modeling concepts of knowledge focused on ontologies creation and state of the art in building of field procedures describing the steps from initial drafting of ontology finishing with their tests. The results demonstrate that it is viable to utilize this technique, where the network equipment that keeps critical services require high level of availability on meeting the needs of the corporation.

关键词： Ontology

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A thionic for service visualization

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Journal of the Institute of Electronics, information and Communication Engineers 2013年第8期96卷 610-615页

作者： Yoshimoto, Kazuho Saito, Aya Mihara, Kozi Tango, Shigetaka Okubo, Hiroki Suzuki, Hiroto Yamaguchi, Masatomo School of Creative Science and Engineering Waseda University Tokyo 169-8555 Japan School of Information-Oriented Management SANNO University Isehara-shi-259-1197 Japan Faculty of Comprehensive informatics Shizuoka Institute of Science and Technology Fukuroi-shi 437-8555 Japan Fuji Xerox Global Services Fuji Xerox Co. Ltd. Tokyo 106-0032 Japan School of Knowledge Engineering Tokyo City University Tokyo 158-8557 Japan Faculty of Science and Engineering Waseda University Tokyo 169-8555 Japan Graduate School of Creative Science and Engineering Waseda University Tokyo 169-8555 Japan

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Pressure ulcers attributes image mining to support therapeutic process: A research proposal

Pressure ulcers attributes image mining to support therapeut...

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4th International Workshop on Image Mining. Theory and Applications, IMTA 2013, In Conjunction with VISIGRAPP 2013

作者： De Souza Neves, Rinaldo Guadagnin, Renato Gulhem, Dirce B. Santana, Levy Aniceto University of Brasília Faculty of Health Sciences Asa Norte Campus Universitário 70910-900 Brasília DF Brazil Catholic University of Brasília MS Program on Information Technology and Knowledge Management SGAN 916 Módulo B 70790-160 Brasília DF Brazil Catholic University of Brasília Campus I QS 07 Lote 01 EPCT 71966-700 Águas Claras Taguatinga DF Brazil

ISBN: (纸本)9789898565501

The high number of clients suffering from pressure ulcers (PU) overloads hospital services, which are not equipped with the necessary human and technological resources. One needs to increase the productivity of this work, since health professionals, especially nurses use subjective and inaccurate assessments for PU diagnosis. This paper proposes a system for automatic interpretation of tissue and color to support the treatment of patients with PU.

关键词： Diagnosis

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