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Titlebook: Intelligence and Security Informatics; Pacific Asia Worksho Michael Chau,G. Alan Wang,Wenji Mao Conference proceedings 2011 Springer-Verlag

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书目名称Intelligence and Security Informatics
副标题Pacific Asia Worksho
编辑Michael Chau,G. Alan Wang,Wenji Mao
视频video
概述Up-to-date results.Fast-track conference proceedings.State-of-the-art research
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Intelligence and Security Informatics; Pacific Asia Worksho Michael Chau,G. Alan Wang,Wenji Mao Conference proceedings 2011 Springer-Verlag
描述This book constitutes the refereed proceedings of the Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2011, held in Beijing, China, in July 2011. The 8 revised full papers and the 5 short papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on terrorism informatics and crime analysis; intelligence analysis and knowledge discovery; information access and security; and infectious disease informatics.
出版日期Conference proceedings 2011
关键词Web usage mining; crime ontology; geospatial analysis; modeling and simulation; public health security
版次1
doihttps://doi.org/10.1007/978-3-642-22039-5
isbn_softcover978-3-642-22038-8
isbn_ebook978-3-642-22039-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag GmbH Berlin Heidelberg 2011
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Modeling and Simulation for the Spread of H1N1 Influenza in School Using Artificial Societiesree roles, which were susceptible, infectious and recovered student. Finally, it conducted simulation experiments to compare the emergency measures of segregating non-classmates and segregating non-roommates.
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A Geospatial Analysis on the Potential Value of News Comments in Infectious Disease Surveillancer data volume(a correlation of 0.902 p<0.01). It suggests that extracting geospatial distribution from comments data for estimation could be an important supplementary method when the surveillance data are incomplete and unreliable.
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Using Spatial Prediction Model to Analyze Driving Forces of the Beijing 2008 HFMD Epidemicution attained 88%. However, CLRM showed low prediction accuracy and bias estimation. It was demonstrated that including spatial effect item into CLRM could greatly improve the performance of HFMD morbidity prediciton model.
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