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Author Lida Huang; Guoray Cai; Hongyong Yuan; Jianguo Chen; Yan Wang; Feng Sun
Title Modeling Threats of Mass Incidents Using Scenario-based Bayesian Network Reasoning Type Conference Article
Year 2018 Publication ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2018
Volume Issue Pages 121-134
Keywords Bayesian network, mass incidents, threat assessment, scenario analysis, interpretive structural modeling.
Abstract Mass incidents represent a global problem, putting potential threats to public safety. Due to the complexity and uncertainties of mass incidents, law enforcement agencies lack analytical models and structured processes for anticipating potential threats. To address such challenge, this paper presents a threat analysis framework combining the scenario analysis method and Bayesian network (BN) reasoning. Based on a case library
Address
Corporate Author Thesis
Publisher Rochester Institute of Technology Place of Publication Rochester, NY (USA) Editor Kees Boersma; Brian Tomaszeski
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-0-692-12760-5 Medium
Track (up) Analytical Modeling and Simulation Expedition Conference ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 2094
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Author Bo Yu; Guoray Cai
Title Coordination of emergency response operations via the event-based awareness mechanism Type Conference Article
Year 2012 Publication ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2012
Volume Issue Pages
Keywords Information systems; Awareness; Coordination; Dependency; Emergency response; Event Processing; Emergency services
Abstract Emergency response involves collaboration among search and rescue workers, medical staff, transportation coordinators, and others to save human lives and minimize damages. While carrying out local activities, members of the teams must also attend to new events happening elsewhere that may affect their work, and be prepared to adjust their activities accordingly. This paper describes a computer supported coordination system, DACE (Dependency-based Awareness and Coordination Environment), which offers a scalable solution to coordination in emergency response. The system serves as a cognitive aid to human actors in both maintaining a group mental model of the overall collaborative activities and their dependencies, and determining the effects of events as they propagate through the web of dependencies. We demonstrate the principles and utility of the DACE system through a hypothetical scenario of search and rescue exercise. This work contributes to the goal of scaling up awareness-based coordination in emergency response. © 2012 ISCRAM.
Address College of Information Sciences and Technology, Pennsylvania State University, University Park, PA 16802, United States
Corporate Author Thesis
Publisher Simon Fraser University Place of Publication Vancouver, BC Editor L. Rothkrantz, J. Ristvej, Z.Franco
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780864913326 Medium
Track (up) Event-Driven Techniques and Methods for Crisis Management Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 243
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Author Yongzhong Sha; Jinsong Yan; Guoray Cai
Title Detecting public sentiment over PM2.5 pollution hazards through analysis of Chinese microblog Type Conference Article
Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014
Volume Issue Pages 722-726
Keywords Air pollution; Information systems; Time series analysis; Crisis; Pm2.5; Public opinions; Sentiment analysis; Social media analysis; Social aspects
Abstract Decision-making in crisis management can benefit from routine monitoring of the (social) media to discover the mass opinion on highly sensitive crisis events. We present an experiment that analyzes Chinese microblog data (extracted from Weibo.cn) to measure sentiment strength and its change in relation to the recent PM 2.5 air pollution events. The data were analyzed using SentiStrength algorithm together with a special sentiment words dictionary tailored and refined for Chinese language. The results of time series analysis on detected sentiment strength showed that less than one percent of the posts are strong-positive or strong negative. Weekly sentiment strength measures show symmetric changes in positive and negative strength, but overall trend moved towards more positive opinions. Special attention was given to sharp bursts of sentiment strength that coincide temporally with the occurrence of extreme social events. These findings suggest that sentiment strength analysis may generate useful alert and awareness of pending extreme social events.
Address Lanzhou University, Gansu, China; Penn State University, University Park, PA, United States
Corporate Author Thesis
Publisher The Pennsylvania State University Place of Publication University Park, PA Editor S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780692211946 Medium
Track (up) Social Media in Crisis Response and Management Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 939
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