Model-Based Decision Support System for Improving Emergency Response

References

• Adams, E. H., Scanlon, E., Callahan, J. J., 3rd, & Carney, M. T. (2010). Utilization of an incident command system for a public health threat: West nile virus in Nassau County, New York, 2008. Journal of Public Health Management and Practice: JPHMP, 16(4), 309–315. https://doi.org/10.1097/PHH.0b013e3181bb8392
   PubMed Web of Science ®Google Scholar
• Andrew, S. A., & Kendra, J. M. (2012). An adaptive governance approach to disaster-related behavioural health services. Disasters, 36(3), 514–532. https://doi.org/10.1111/j.1467-7717.2011.01262.x
   PubMed Web of Science ®Google Scholar
• Arnold, J., O’Brien, D., Walsh, D., Ersoy, G., & Rodoplu, U. (2001). The perceived usefulness of the hospital emergency incident command system and an assessment tool for hospital disaster response capabilities and needs in hospital disaster planning in turkey. Prehospital and Disaster Medicine, 16(S1), S12–S12. https://doi.org/10.1017/S1049023X00035044
   Google Scholar
• Bangor, A., Kortum, P., & Miller, J. (2008). An empirical evaluation of the system usability scale. International Journal of Human-Computer Interaction, 24(6), 574–594. https://doi.org/10.1080/10447310802205776
   Google Scholar
• Carver, L., & Turoff, M. (2007). Human Computer Interaction: The human and computer as a team in emergency management information systems. Communications of the ACM, 50(3), 33–38. https://doi.org/10.1145/1226736.1226761
   Web of Science ®Google Scholar
• FEMA, U. S. (1969). Private sector fact sheet: Situational awareness viewer for emergency response and recovery. FEMA.
   Google Scholar
• Fischer, G. (2012). Context-aware systems: The ‘right’ information, at the ‘right’ time, in the ‘right’ place, in the ‘right’ way, to the ‘right’ person. In Proceedings of the international working conference on advanced visual interfaces (pp. 287–294). ACM.
   Google Scholar
• Gangemi, A., & Presutti, V. (2009). Ontology design patterns. In S. Staab & R. Studer (eds.), Handbook on Ontologies (2nd ed., pp. 221–243). Springer.
   Google Scholar
• Gartner, D., Zhang, Y., & Padman, R. (2018). Cognitive workload reduction in hospital information systems: Decision support for order set optimization. Health Care Management Science, 21(2), 224–243. https://doi.org/10.1007/s10729-017-9406-6
   PubMed Web of Science ®Google Scholar
• Gasaway, R. B. (2013). Situational awareness for emergency response. Fire Engineering Books.
   Google Scholar
• Gyorfi, J., Buhrke, E., Tarlton, M., Lopez, J., & Valliath, G. (2008). Applying telepresence to incident management: The virtual incident command center. Presence: Teleoperators and Virtual Environments, 17(3), 231–241. https://doi.org/10.1162/pres.17.3.231
   Web of Science ®Google Scholar
• Hansen, R. R. (2006). Letter to the editor regarding incident command system (ICS). Journal of Homeland Security and Emergency Management, 3(4), 1–3. https://doi.org/10.2202/1547-7355.1289
   Google Scholar
• Homeland Security. (2013). Homeland Security Exercise and Evaluation Program (HSEEP). ICS. https://training.fema.gov/EMIWeb/IS/ICSResource/assets/reviewMaterials.pdf
   Google Scholar
• Keim, D. A., Mansmann, F., Schneidewind, J., Thomas, J., & Zeigler, H. (2008). Visual analytics: Scope and challenges. Visual Data Mining, 4404, 76–90. https://doi.org/10.1007/978-3-540-71080-6_6
   Google Scholar
• Kohlhammer, J., & Zeltzer, D. (2003). DCV: A decision-centered visualization system for time-critical applications. In SMC’03 Conference Proceedings 2003 IEEE International Conference on Systems, Man & Cybernetics. Conference Theme -- System Security & Assurance (Cat. No.03CH37483), 3905. IEEE. https://doi.org/10.1109/ICSMC.2003.1244498
   Google Scholar
• Kohlhammer, J., & Zeltzer, D. (2004). Towards a visualization architecture for time-critical applications. In Proceedings of the 9th International Conference: Intelligent User Interfaces (pp. 271–273). Association for Computing Machinery. https://doi.org/10.1145/964442.964502
   Google Scholar
• Lindell, M. K. (2000). An Overview of protective action decision-making for a nuclear power plant emergency. Journal of Hazardous Materials, 75(2–3), 113–129. https://doi.org/10.1016/S0304-3894(00)00175-8
   PubMed Web of Science ®Google Scholar
• Mailliez, M., Hosseini, S., Battaïa, O., & Roy, R. N. (2020). Decision support system-like task to investigate operators’ performance in manufacturing environments. IFAC-PapersOnLine, 53(5), 324–329. https://doi.org/10.1016/j.ifacol.2021.04.110
   Google Scholar
• Moynihan, D. P. (2009). The network governance of crisis response: Case studies of incident command systems. Journal of Public Administration Research and Theory, 19(4), 895–915. NIMS, https://doi.org/10.1093/jopart/mun033
   Web of Science ®Google Scholar
• MSDS (Material Safety Data Sheets) requirements and regulations (2021). Retrieved November 24, 2021, from https://www.ehso.com/msds_regulations.php.
   Google Scholar
• Ongenae, F., Hristoskova, A., Tsiporkova, E., Tourwe, T., & De Turck, F. (2013). Semantic reasoning for intelligent emergency response applications. In 2013 11th IEEE International Conference on Industrial Informatics (INDIN) (p. 547). IEEE.
   Google Scholar
• Röttger, S., Bali, K., & Manzey, D. (2009). Impact of automated decision aids on performance, operator behaviour and workload in a simulated supervisory control task. Ergonomics, 52(5), 512–523. https://doi.org/10.1080/00140130802379129
   PubMed Web of Science ®Google Scholar
• Wenger, D., Quarantelli, E. L., & Dynes, R. R. (1990). Is the incident command system a plan for all seasons and emergency situations? Hazard Monthly, 10(12), 8–9.
   Google Scholar
• Yoon, S., Velasquez, J., Partridge, B., & Nof, S. (2008). Transportation security decision support system for emergency response: A training prototype. Decision Support Systems, 46(1), 139–148. https://doi.org/10.1016/j.dss.2008.06.002
   Web of Science ®Google Scholar
• Zografos, K., & Androutsopoulos, K. (2008). A decision support system for integrated hazardous materials routing and emergency response decisions. Transportation Research Part C: Emerging Technologies, 16(6), 684–703. https://doi.org/10.1016/j.trc.2008.01.004
   Web of Science ®Google Scholar