|   | 
Details
   web
Records
Author Gaoussou Camara; Rim Djedidi; Sylvie Despres; Moussa Lo
Title Towards an ontology for an epidemiological monitoring system 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 Disease control; Information systems; Disease spreading; Early prediction; Monitoring system; Ontological modeling; Qualitative approach; Quantitative approach; Risk predictions; Simulation; Monitoring
Abstract Epidemiological monitoring systems are used to control the evolution of disease spreading and to suggest action plans to prevent identified risks. In this domain, risk prediction is based on quantitative approaches that are hardly usable when data collection is not possible. In this paper, a qualitative approach based on an epidemiological monitoring ontology is proposed. We describe the design of this ontology and show how it fits into classical monitoring systems and helps overcoming limits related to quantitative approaches. © 2012 ISCRAM.
Address LANI, Université Gaston Berger, B.P. 234, Saint-Louis, Senegal; LIM and BIO, Université Paris 13, 74 rue Marcel Cachin, 93017 Bobigny, France
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 (up) Edition
ISSN 2411-3387 ISBN 9780864913326 Medium
Track Analytical Modelling and Simulation Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 86
Share this record to Facebook
 

 
Author Mauro Falasca; Christopher W. Zobel; Deborah Cook
Title A decision support framework to assess supply chain resilience Type Conference Article
Year 2008 Publication Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2008
Volume Issue Pages 596-605
Keywords Artificial intelligence; Decision support systems; Disasters; Information systems; Inventory control; Decision framework; Decision support framework; Quantitative approach; Resilience; Simulation; Supply chain design; Supply chain resiliences; Supply chain systems; Supply chains
Abstract Our research is aimed at developing a quantitative approach for assessing supply chain resilience to disasters, a topic that has been discussed primarily in a qualitative manner in the literature. For this purpose, we propose a simulation-based framework that incorporates concepts of resilience into the process of supply chain design. In this context, resilience is defined as the ability of a supply chain system to reduce the probabilities of disruptions, to reduce the consequences of those disruptions, and to reduce the time to recover normal performance. The decision framework incorporates three determinants of supply chain resilience (density, complexity, and node criticality) and discusses their relationship to the occurrence of disruptions, to the impacts of those disruptions on the performance of a supply chain system and to the time needed for recovery. Different preliminary strategies for evaluating supply chain resilience to disasters are identified, and directions for future research are discussed.
Address Dept. of Business Information Technology, R.B. Pamplin College of Business, Virginia Polytechnic Institute and State University, Blacksburg VA, 24061, United States
Corporate Author Thesis
Publisher Information Systems for Crisis Response and Management, ISCRAM Place of Publication Washington, DC Editor F. Fiedrich, B. Van de Walle
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue (up) Edition
ISSN 2411-3387 ISBN 9780615206974 Medium
Track Impact of Disasters on Industry and Economic Effects Expedition Conference 5th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 481
Share this record to Facebook
 

 
Author Jose Vargas Florez; Anthony Charles; Matthieu Lauras; Lionel Dupont
Title Designing realistic scenarios for disaster management quantitative models 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 180-189
Keywords Disaster prevention; Information systems; Disaster management; Disaster scenario; Quantitative approach; Quantitative modeling; Quantitative models; Real situation; Realism; Realistic scenario; Disasters
Abstract Disaster Management has received a lot of attention over the last twenty years, and can now be considered a full research area. But a gap exists between research work proposals and their applications on the field. This is particularly true regarding quantitative approaches. One of the main issues is that the scenarios used to design and validate the proposals are often not accurate and/or too simple compared to the complexity of real situations. Designing realistic scenarios is of prime importance to be able to propose relevant quantitative models which could be implemented by practitioners. This paper tackles this problem by proposing a structured methodology which aims at defining realistic disaster scenarios. The case of earthquakes management in Peru is used to illustrate the consistency of our proposal.
Address Pontificia Universidad Católica Del Peru, Peru; Université Lyon 2 Lumière, DISP, France; Université de Toulouse, Mines Albi, Toulouse Business School, France
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 (up) Edition
ISSN 2411-3387 ISBN 9780692211946 Medium
Track Disaster Relief Supply Chain Management Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 500
Share this record to Facebook