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Aygul Gabdulkhakova, Birgitta König-Ries, & Dmitry Rizvanov. (2012). Rational resource allocation in mass casualty incidents – Adaptivity and efficiency. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Mass casualty incidents (MCI) are highly dynamic situations in which limited available resources need to be quickly and efficiently allocated. In this paper, we suggest considerable extensions to an allocation method that we presented in earlier work. The extensions address two major challenges: First, the need to balance real-world resource usage and second, the need to adapt to changing situations. Additionally, a theoretical evaluation of the efficiency of the suggested approach is described. © 2012 ISCRAM.
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Hussain Aziz Saleh. (2005). Dynamic optimisation of the use of space technology for rapid disaster response and management. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 139–141). Brussels: Royal Flemish Academy of Belgium.
Abstract: Modern space and information technologies provide valuable tools for the solution of many real-world problems in fields of managing effects of natural and man-made disasters, geomatic engineering, etc. Therefore, the need to develop and optimise the use of these technologies in an efficient manner is necessary for providing reliable solutions. This paper aims to develop powerful optimisation algorithms extending current highly successful ideas of artificial intelligence for developing of the disaster warning network which is a system of satellites and ground stations for providing real time early warning of the impact of the disaster and minimise its effects (e.g., earthquakes, landslides, floods, volcanoes, etc). Such intelligent algorithms can provide a degree of functionality and flexibility suitable both for constructing high-accuracy models and in monitoring their behaviour in real time.
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Muhammad Imran, Carlos Castillo, Jesse Lucas, Patrick Meier, & Jakob Rogstadius. (2014). Coordinating human and machine intelligence to classify microblog communications in crises. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 712–721). University Park, PA: The Pennsylvania State University.
Abstract: An emerging paradigm for the processing of data streams involves human and machine computation working together, allowing human intelligence to process large-scale data. We apply this approach to the classification of crisis-related messages in microblog streams. We begin by describing the platform AIDR (Artificial Intelligence for Disaster Response), which collects human annotations over time to create and maintain automatic supervised classifiers for social media messages. Next, we study two significant challenges in its design: (1) identifying which elements must be labeled by humans, and (2) determining when to ask for such annotations to be done. The first challenge is selecting the items to be labeled by crowd sourcing workers to maximize the productivity of their work. The second challenge is to schedule the work in order to reliably maintain high classification accuracy over time. We provide and validate answers to these challenges by extensive experimentation on real world datasets.
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Rahele B. Dilmaghani, & Ramesh R. Rao. (2008). A wireless mesh infrastructure deployment with application for emergency scenarios. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 484–494). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: When a disaster or emergency occurs, one of the most pressing needs is to establish a communication network for the first responders at the scene. Establishing and accessing a reliable communication infrastructure at a crisis site is crucial in order to have accurate and real-time exchange of information. Failure in the exchange of timely and crucial information or delay in allocating resources impedes early response efforts, potentially resulting in loss of life and additional economic impact. At a disaster site, the existing communication infrastructure may be damaged and therefore partially or totally unavailable; or, there may not have been previously existing infrastructure (as in the case of remote areas). A communication infrastructure within the context of emergency applications should be reliable, easily configurable, robust, interoperable in a heterogeneous environment with minimum interdependencies, and quickly deployable at low cost. A disaster scene is a chaotic environment which requires a systematic approach to abstract the system, study the flow of information and collaboration among different disciplines and jurisdictions to facilitate response and recovery efforts. We have deployed the wireless mesh infrastructure in several drills at the university campus and in the city as part of the California Institute for Telecommunications and Information Technology (Calit2) NSF-funded RESCUE project (Responding to Crises and Unexpected Events). To evaluate network performance and identify the source(s) of bottleneck, we have captured the network traffic. The lessons learned from test bed evaluations of the network based on real-world scenarios can be applied to future applications to enhance the network design and performance.
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Therese Friberg, Benedikt Birkhäuser, Jens Pottebaum, & Rainer Koch. (2010). Using scenarios for the identification of real-world events in an event-based system. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This work focuses on the requirements engineering process of an event-based system in the domain of emergency management. The goal is to identify events which occur and have an effect on the actions and decision making during an operation. We outline a case study to apply scenario-based requirements engineering processes to describe and identify events. Under the special circumstances of the case study one important result is the need of integrating multiple sources into the scenario generation activities due to the singular characteristics of many operations.
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Tina Comes, Michael Hiete, Niek Wijngaards, & Masja Kempen. (2009). Integrating scenario-based reasoning into multi-criteria decision analysis. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Multi-criteria decision analysis (MCDA) is a technique for decision support which aims at providing transparent and coherent support for complex decision situations taking into account subjective preferences of the decision makers. However, MCDA does not foresee an analysis of multiple plausible future developments of a given situation. In contrast, scenario-based reasoning (SBR) is frequently used to assess future developments on the longer term. The ability to discuss multiple plausible future developments provides a rationale for strategic plans and actions. Nevertheless, SBR lacks an in-depth performance evaluation of the considered actions. This paper explores the integration of both techniques that combines their respective strengths as well as their application in environmental crisis management. The proposed methodology is illustrated by an environmental incident example. Future work is to conduct validations on the basis of real-world scenarios by public Dutch and Danish chemical incident crisis management authorities.
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