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Author Xiao LongDeng; Hui Zhang; Ya Qi Tang; Le Yi Ren pdf  isbn
openurl 
  Title Risk Analysis of International Spreading in 2014 Ebola Outbreak to China Compared to Social Media Type Conference Article
  Year 2015 Publication ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2015  
  Volume Issue Pages  
  Keywords Airline Data; Ebola; Online Opinion Analysis; Risk analysis; social media  
  Abstract The 2014 West African EbolaOutbreak raisedfrom Sierra Leone, Guinea, and Liberia at December in 2013 has been reported to cause 21296 cases and 8429 deaths until now which became the deadliest recorded in history. In this paper, we proposed the riskanalysis to assess the international spread risk from mentioned three African countries to China by GEM(Global Epidemic Mobility) Model. As another part of analysis, we crawled related online social media data of Ebola from the most four favorite online social networks (including SINA, TENCENT) in China from June to November in 2014.By analyzing these attained social media data and airline data of GEM, we found some interesting results. For example, Beijing has the most importing risk of Ebola while it has the hottest discussion on social network.. Furthermore, we showed analysis of combining social network data with geographicaldemonstration and Chinese citizen sentiment towards this disaster.  
  Address  
  Corporate Author Thesis  
  Publisher University of Agder (UiA) Place of Publication Kristiansand, Norway Editor L. Palen; M. Buscher; T. Comes; A. Hughes  
  Language English Summary Language English Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9788271177881 Medium  
  Track Planning, Foresight and Risk Analysis Expedition Conference ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved yes  
  Call Number Serial 1304  
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Author Yaping Ma; Hui Zhang; Tao Chen; Rui Yang pdf  isbn
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  Title Decentralized Evacuation System Based on Occupants Distribution and Building Information Type Conference Article
  Year 2015 Publication ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2015  
  Volume Issue Pages  
  Keywords decentralized system; decision making support system; Evacuation guidance; sensor and network  
  Abstract Effective evacuation is critical for safety of occupants. The exiting evacuation systems lack flexibility and don?t consider the distribution of occupants. It is possible to direct occupants to danger areas or cause congestion in certain areas. In this paper, a decentralized evacuation system is proposed to compute the safest path in real time. The system is composed of fire detection sensors, zone controllers, elevator sensors, human tracking and monitoring systems and dynamic egress signs. All devices are placed at the predetermined locations based on integrated design of the building. The entire building is divided into many basic zones which are operating quite independently, and global information is communicated to neighboring zones and consequently to entire network by zone controllers. The system acts in decentralized fashion. The elevator and dynamic factors are considered in guidance system. Simulations are performed to determine the advantage of the system.  
  Address  
  Corporate Author Thesis  
  Publisher University of Agder (UiA) Place of Publication Kristiansand, Norway Editor L. Palen; M. Buscher; T. Comes; A. Hughes  
  Language English Summary Language English Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9788271177881 Medium  
  Track Decision Support Systems Expedition Conference ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved yes  
  Call Number Serial 1294  
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Author Xiaojing Guo; Xinzhi Wang; Luyao Kou; Hui Zhang pdf  openurl
  Title A Question Answering System Applied to Disasters Type Conference Article
  Year 2021 Publication ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2021  
  Volume Issue Pages 2-16  
  Keywords Emergency Management, Disaster, Natural Language Processing, Deep Learning  
  Abstract In emergency management, identifying disaster information accurately and promptly out of numerous documents like news articles, announcements, and reports is important for decision makers to accomplish their mission efficiently. This paper studies the application of the question answering system which can automatically locate answers in the documents by natural language processing to improve the efficiency and accuracy of disaster knowledge extraction. Firstly, an improved question answering model was constructed based on the advantages of the existing neural network models. Secondly, the English question answering dataset pertinent to disasters and the Chinese question answering dataset were constructed. Finally, the improved neural network model was trained on the datasets and tested by calculating the F1 and EM scores which indicated that a higher question answering accuracy was achieved. The improved system has a deeper understanding of the semantic information and can be used to construct the disaster knowledge graph.  
  Address Institute of Public Safety Research, Tsinghua University; School of Computer Engineering and Science, Shanghai University; Institute of Public Safety Research, Tsinghua University; Institute of Public Safety Research, Tsinghua University  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title (up) Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-61-5 ISBN Medium  
  Track AI and Intelligent Systems for Crises and Risks Expedition Conference 18th International Conference on Information Systems for Crisis Response and Management  
  Notes gxj19@mails.tsinghua.edu.cn Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2308  
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