Abbas Ganji, Negin Alimohammadi, & Scott Miles. (2019). Challenges in Community Resilience Planning and Opportunities with Simulation Modeling. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: The importance of community resilience has become increasingly recognized in emergency management and
post-disaster community well-being. To this end, three seismic resilience planning initiatives have been
conducted in the U.S. in the last decade to envision the current state of community resilience. Experts who
participated in these initiatives confronted challenges that must be addressed for future planning initiatives.
We interviewed eighteen participants to learn about the community resilience planning process, its
characteristics, and challenges. Conducting qualitative content analysis, we identify six main challenges to
community resilience planning: complex network systems; interdependencies among built environment systems;
inter-organizational collaboration; connections between the built environment and social systems;
communications between built environment and social institutions? experts; and communication among
decision-makers, social stakeholders, and community members. To overcome the identified challenges, we
discuss the capability of human-centered simulation modeling as a combination of simulation modeling and
human-centered design to facilitate community resilience planning.
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Kpotissan Adjetey-Bahun, Babiga Birregah, Eric Châtelet, Jean-Luc Planchet, & Edgar Laurens-Fonseca. (2014). A simulation-based approach to quantifying resilience indicators in a mass transportation system. 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. 75–79). University Park, PA: The Pennsylvania State University.
Abstract: A simulation-based model used to measure resilience indicators of the railway transportation system is presented. This model is tested through a perturbation scenario: the inoperability of a track which links two stations in the system. The performance of the system is modelled through two indicators: (a) the number of passengers that reach their destination and (b) the total delay of passengers after a serious perturbation. The number of passengers within a given station at a given time is considered as early warning in the model. Furthermore, a crisis management plan has been simulated for this perturbation scenario in order to help the system to recover quickly from this perturbation. This crisis management plan emphasizes the role and the importance of the proposed indicators when managing crises.
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Ahmed Abdeltawab Abdelgawad. (2019). Reliability of expert estimates of cascading failures in Critical Infrastructure. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Owing to the complexity of Critical Infrastructures and the richness of issues to analyze, numerous approaches are used to model the behavior of CIs. Organizations having homeland security as mission often conduct desktop-based simulations using judgmental assessment of CI interdependencies and cascading failures. Expert estimates concern direct effects between the originally disrupted CI sector and other sectors. To better understand the magnitude of aggregate cascading effects, we developed a system dynamics model that uses expert estimates of cascading failures to compare the aggregate effect of cascading failures with the primary direct cascading failures. We find that the aggregate effect of compounded cascading failures becomes significantly greater than the primary cascading failures the longer the duration of the original disruption becomes. Our conceptually simple system dynamics model could be used to improve desktop-based exercises, since it illustrates consequences that go beyond judgmental assessment.
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Ahmed Laatabi, Benoit Gaudou, Chihab Hanachi, Patricia Stolf, & Sébastien Truptil. (2022). Coupling Agent-based Simulation with Optimization to Enhance Population Sheltering. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 116–132). Tarbes, France.
Abstract: Population sheltering is a recurrent problem in crisis management that requires addressing two aspects: evacuating vulnerable people using emergency vehicles and regulating movements of pedestrians and individual vehicles towards shelters. While these aspects have received considerable attention in modeling and simulation literature, very few approaches consider them simultaneously. In this paper, we argue that Agent-Based Modeling and Simulation (ABMS) and Optimization are two complementary approaches that can address the problem of sheltering globally and efficiently and be the basis of coherent frameworks for decision- and policy-making. Optimization can build efficient sheltering plans, and ABMS can explore what-if scenarios and use geospatial data to display results within a realistic environment. To illustrate the benefits of a framework based on this coupling approach, we simulate actual flash flood scenarios using real-world data from the city of Trèbes in South France. Local authorities may use the developed tools to plan and decide on sheltering strategies, notably, when and how to evacuate depending on available time and resources.
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Alexander Gabriel, Babette Tecklenburg, Yann Guillouet, & Frank Sill Torres. (2021). Threat analysis of offshore wind farms by Bayesian networks – a new modeling approach. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 174–185). Blacksburg, VA (USA): Virginia Tech.
Abstract: As a result of the ongoing commitment to climate protection in more and more countries and the corresponding expansion of renewable energies, the importance of renewables for the security of electricity supply is also increasing. Wind energy generated in offshore wind farms already accounts for a significant share of the energy mix and will continue to grow in the future. Therefore, approaches and models for security assessment and protection against threats are also needed for these infrastructures. Due to the special characteristics and geographical location of offshore wind farms, they are confronted with particular challenges. In this context, this contribution outlines how an approach for threat analysis of offshore wind farms is to be developed within the framework of the new research project “ARROWS” of the German Aerospace Center. The authors first explain the structure of offshore wind farms and then present a possible modeling approach using Qualitative function models and Bayesian networks.
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Michael Ammann, Tuomas Peltonen, Juhani Lahtinen, Kaj Vesterbacka, Tuula Summanen, Markku Seppänen, et al. (2010). KETALE Web application to improve collaborative emergency management. 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: KETALE is a database and web application intended to improve the collaborative decision support of the Finnish Radiation and Nuclear Safety Authority (STUK) and of the Finnish Meteorological Institute (FMI). It integrates distributed modeling (weather forecasts and dispersion predictions by FMI, source term and dose assessments by STUK) and facilitates collaboration and sharing of information. It does so by providing functionalities for data acquisition, data management, data visualization, and data analysis. The report outlines the software development from requirement analysis to system design and implementation. Operational aspects and user experiences are presented in a separate report.
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Victor A. Bañuls, Murray Turoff, & Joaquin Lopez. (2010). Clustering scenarios using cross-impact analysis. 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: Scenarios are frequently used in Emergency Planning and Preparedness. These scenarios are developed based on the hypothesis of occurrence or not of significant events. This is a complex process because of the interrelations between events. This fact, along with the uncertainty about the occurrence or non-occurrence of the events, makes the scenario generation process a challenging issue for emergency managers. In this work a new step-by-step model for clustering scenarios via cross-impact is proposed. The authors. proposal adds tools for detecting critical events and graphical representation to the previous scenario-generation methods based on Cross-Impact Analysis. Moreover, it allows working with large sets of events without using great computational infrastructures. These contributions are expected to be useful for supporting the analysis of critical events and risk assessment tasks in Emergency Planning and Preparedness. Operational issues and practical implications of the model are discussed by means of an example.
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Michael R. Bartolacci, Christoph Aubrecht, & Dilek Ozceylan Aubrecht. (2014). A portable base station optimization model for wireless infrastructure deployment in disaster planning and management. 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. 50–54). University Park, PA: The Pennsylvania State University.
Abstract: Disaster response requires communications among all affected parties including emergency responders and the affected populace. Wireless telecommunications, if available through a fixed structure cellular mobile network, satellites, portable station mobile networks and ad hoc mobile networks, can provide this means for such communications. While the deployment of temporary mobile networks and other wireless equipment following disasters has been successfully accomplished by governmental agencies and mobile network providers following previous disasters, there appears to be little optimization effort involved with respect to maximizing key performance measures of the deployment or minimizing overall 'cost' (including time aspects) to deploy. This work-in-progress does not focus on the question of what entity will operate the portable base during a disaster, but on optimizing the placement of mobile base stations or similar network nodes for planning and real time management purposes. An optimization model is proposed for the staging and placement of portable base stations to support disaster relief efforts.
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Ben Ortiz, Laura Kahn, Marc Bosch, Philip Bogden, Viveca Pavon-Harr, Onur Savas, et al. (2020). Improving Community Resiliency and Emergency Response With Artificial Intelligence. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 35–41). Blacksburg, VA (USA): Virginia Tech.
Abstract: New crisis response and management approaches that incorporate the latest information technologies are essential in all phases of emergency preparedness and response, including the planning, response, recovery, and assessment phases. Accurate and timely information is as crucial as is rapid and coherent coordination among the responding organizations. We are working towards a multi-pronged emergency response tool that provide stakeholders timely access to comprehensive, relevant, and reliable information. The faster emergency personnel are able to analyze, disseminate and act on key information, the more effective and timelier their response will be and the greater the benefit to affected populations. Our tool consists of encoding multiple layers of open source geospatial data including flood risk location, road network strength, inundation maps that proxy inland flooding and computer vision semantic segmentation for estimating flooded areas and damaged infrastructure. These data layers are combined and used as input data for machine learning algorithms such as finding the best evacuation routes before, during and after an emergency or providing a list of available lodging for first responders in an impacted area for first. Even though our system could be used in a number of use cases where people are forced from one location to another, we demonstrate the feasibility of our system for the use case of Hurricane Florence in Lumberton, a town of 21,000 inhabitants that is 79 miles northwest of Wilmington, North Carolina.
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Frédérick Bénaben, Chihab Hanachi, Matthieu Lauras, Pierre Couget, & Vincent Chapurlat. (2008). A metamodel and its ontology to guide crisis characterization and its collaborative management. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 189–196). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents a research in progress about the French ISyCri project that aims at providing partners involved in crisis management with an agile Mediation Information System (MIS). Not only this MIS shoul support the interoperability of the partners' information systems but it is also dedicated to coordinate their activities through a collaborative process. One of the first and main steps towards such a MIS, is to elaborate a common and sharable reference model built to characterize crisis situations. Such a model is also an input for automated reasoning to elaborate and adapt a crisis solving collaborative process. This article presents the objective of the project, our approach and our first results: a UML metamodel of crisis situation and its corresponding OWL ontology on top of which deductions are possible.
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Thomas Bernard, Mathias Braun, Olivier Piller, Denis Gilbert, Jochen Deuerlein, Andreas Korth, et al. (2013). SMaRT-OnlineWDN: Online security management and reliability toolkit for water distribution networks. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 171–176). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Water distribution Networks (WDNs) are critical infrastructures that are exposed to deliberate or accidental contamination. Until now, no monitoring system is capable of protecting a WDN in real time. In the immediate future water service utilities that are installing water quantity and quality sensors in their networks will be producing a continuous and huge data stream for treating. The main objective of the project SMaRT-OnlineWDN is the development of an online security management toolkit for water distribution networks that is based on sensor measurements of water quality as well as water quantity and online simulation. Its field of application ranges from detection of deliberate contamination, including source identification and decision support for effective countermeasures, to improved operation and control of a WDN under normal and abnormal conditions.
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Gaoussou Camara, Rim Djedidi, Sylvie Despres, & Moussa Lo. (2012). Towards an ontology for an epidemiological monitoring system. 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: 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.
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Hüseyin Can Ünen, Muhammed Sahin, & Amr S. Elnashai. (2011). Assessment of interdependent lifeline networks performance in earthquake disaster management. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Several studies and observations regarding past earthquakes such as 1989 Loma Prieta, 1994 Northridge, or 1999 Marmara earthquakes have shown the importance of lifeline systems functionality on response and recovery efforts. The general direction of studies on simulating lifelines seismic performance is towards achieving more accurate models to represent the system behavior. The methodology presented in this paper is a product of research conducted in the Mid-America Earthquake Center. Electric power, potable water, and natural gas networks are modeled as interacting systems where the state of one network is influenced by the state of another network. Interdependent network analysis methodology provides information on operational aspects of lifeline networks in post-seismic conditions in addition to structural damage assessment. These results are achieved by different components of the tool which are classified as structural and topological. The topological component analyzes the post seismic operability of the lifeline networks based on the damage assessment outcome of the structural model. Following an overview of the models, potential utilizations in different phases of disaster management are briefly discussed.
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Alayne Da Costa Duarte, Marcos R. S. Borges, Jose Orlando Gomes, & De Paulo V. R. Carvalho. (2013). ASC model: A process model for the evaluation of simulated field exercises in the emergency domain. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 551–555). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The undefined flow of execution of activities in an evaluation process hampers its implementation. A consistent evaluation process defines interrelated methodological steps that make it easier for the evaluator to lead the process. This article presents a process model for the evaluation of simulated field exercises in the emergency domain, including their sub processes and activities. The proposed model was derived from observations made during real situations of a simulated evacuation exercise of communities in high-risk areas in Rio de Janeiro (Brazil). The motivation came from the finding that the assessment of simulated field exercises is conducted by completing an activity report that does not follow a structural model, an evaluation program or a formal standard. The results of this research show the experts' satisfaction with the application of the model proposed for the development of an evaluation process. The same occurs when comparing to reports currently used by them for this purpose.
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Denis Barcaroli, Alex Coletti, Antonio De Nicola, Antonio Di Pietro, Luigi La Porta, Maurizio Pollino, et al. (2019). An Automatic Approach to Qualitative Risk Assessment in Metropolitan Areas. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Risk assessment aims at improving prevention and preparedness phases of the crisis management lifecycle.
Qualitative risk assessment of a system is important for risks identification and analysis by the various stakeholders and often requires multi-disciplinary knowledge. We present an automatic approach to qualitative
risk assessment in metropolitan areas using semantic techniques. In particular, users are provided with a computational support to identify and prioritize by relevance risks of city services, through generation of
semantic descriptions of risk situations. This approach is enabled by a software system consisting of: TERMINUS, a domain ontology representing city knowledge; WS-CREAM, a web service implementing risk identification and ranking functions; and CIPCast, a GIS-based Decision Support System with functions of risk
forecast due to natural hazards. Finally we present the results of a preliminary validation of the generated risks concerning some points of interest in two different areas of the city of Rome.
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Diana Fischer, Carsten Schwemmer, & Kai Fischbach. (2018). Terror Management and Twitter: The Case of the 2016 Berlin Terrorist Attack. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 459–468). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: There is evidence that people increasingly use social networking sites like Twitter in the aftermath of terrorist attacks to make sense of the events at the collective level. This work-in-progress paper focuses on the content of Twitter messages related to the 2016 terrorist attack on the Berlin Christmas market. We chose topic modeling to investigate the Twitter data and the terror management theory perspective to understand why people used Twitter in the aftermath of the attack. In particular, by connecting people and providing a real-time communication channel, Twitter helps its users collectively negotiate their worldviews and re-establish self-esteem. We provide first results and discuss next steps.
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Dick Ooms, Willem-Jan van den Heuvel, & Bartel Van de Walle. (2018). A Conceptual Framework for Civil-Military Interaction in Peace Support Operations. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1003–1015). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In complex emergencies, civil and military organizations often find themselves being partners in an international effort aimed at peace keeping, humanitarian relief, and development support. Civil and military partners need to exchange information and to cooperate as required. This assumes effective and efficient Civil-Military Interaction (CMI). However, CMI research literature shows that, in practice, this is far from a reality. In particular, our research indicates that deficiencies in knowledge processes and knowledge management within international civil and military organizations contribute to the causes of ineffective and inefficient CMI. Our research aims to investigate the feasibility of developing technical solutions exploiting knowledge engineering, to support fieldworkers in overcoming these CMI problems. As a first step, this paper introduces a Conceptual Framework (CF) that captures reference models of the CMI domain. The CF has been developed to analyze CMI problems and underlying KM deficiencies. It is being illustrated, explored and validated using real-world case studies.
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Elisa Canzani. (2016). Modeling Dynamics of Disruptive Events for Impact Analysis in Networked Critical Infrastructures. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Governments have strongly recognized that the proper functioning of critical infrastructures (CIs) highly determines the societal welfare. If a failed infrastructure is unable to deliver services and products to the others, disruptive effects can cascade into the larger system of CIs. In turn, decision-makers need to understand causal interdependencies and nonlinear feedback behaviors underlying the entire CIs network toward more effective crisis response plans. This paper proposes a novel block building modeling approach based on System Dynamics (SD) to capture complex dynamics of CIs disruptions. We develop a SD model and apply it to hypothetical scenarios for simulation-based impact analysis of single and multiple disruptive events. With a special focus on temporal aspects of system resilience, we also demonstrate how the model can be used for dynamic resilience assessment. The model supports crisis managers in understanding scenarios of disruptions and forecasting their impacts to improve strategic planning in Critical Infrastructure Protection (CIP).
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Elisa Canzani, & Ulrike Lechner. (2015). Insights from Modeling Epidemics of Infectious Diseases ? A Literature Review. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: The relevance of modeling epidemics? spread goes beyond the academic. The mathematical understanding of infectious diseases has become an important tool in policy making. Our research interest is modeling of dynamics in crisis situations. This paper explores the extant body of literature of mathematical models in epidemiology, with particular emphasis on theories and methodologies used beyond them. Our goal is to identify core building blocks of models and research patterns to model the dynamics of crisis situations such as epidemics. The wide range of applications of epidemic models to many other disciplines that show biological analogies, makes this paper helpful for many modelers and mathematicians within the broader field of Crisis Management.
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Mauro Falasca, Christopher W. Zobel, & Gary M. Fetter. (2009). An optimization model for humanitarian relief volunteer management. 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: One of the challenges of humanitarian organizations is that there exist limited decision technologies that fit their needs. It has also been pointed out that those organizations experience coordination difficulties with volunteers willing to help. The purpose of this paper is to help address those challenges through the development of a decision model to assist in the management of volunteers. While employee workforce management models have been the topic of extensive research over the past decades, no work has focused on the problem of managing humanitarian relief volunteers. In this paper, we discuss a series of principles from the field of volunteer management and develop a multi criteria optimization model to assist in the assignment of volunteers to tasks. We present an illustrative example and analyze a solution methodology where the decision maker exercises his/her preferences by trading-off conflicting objectives. Conclusions, limitations, and directions for future research are also discussed.
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Gary M. Fetter, Mauro Falasca, Christopher W. Zobel, & Terry R. Rakes. (2010). A multi-stage decision model for debris disposal operations. 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: As shown by Hurricane Katrina, disposing of disaster-generated debris can be quite challenging. Extraordinary amounts of debris far exceeding typical annual amounts of solid waste are almost instantaneously deposited across a widespread area. Although the locations and amounts of debris can be easily summarized looking back after recovery activities have been completed, they are uncertain and difficult at best to estimate as debris operations begin to unfold. Further complicating matters is that the capacity of cleanup resources, which is dependent upon available equipment, labor, and subcontractors, can fluctuate during on-going cleanup operations. As a result, debris coordinators often modify initial resource assignments as more accurate debris estimates and more stable resource capacities become known. In this research, we develop a computer-based decision support system that incorporates a multi-stage programming model to assist decision makers with allocating debris cleanup resources immediately following a crisis event and during ongoing operations as debris volumes and resource capacities become known with increasing certainty.
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Flávio Horita, João Porto de Albuquerque, Victor Marchezini, & Eduardo M. Mendiondo,. (2016). A qualitative analysis of the early warning decision-making process in disaster management. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Early warning systems are an important means of improving the efficiency of disaster response and preparedness. However, in its analysis of the technological aspects of the infrastructure, the literature has failed to carry out an investigation of early warning process. This paper has sought to take a step toward understanding this issue by carrying out a qualitative analysis of the early warning process in disaster management. This has involved participatory observations and conducting interviews with practitioners from the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN). The results have shown that this research area is a promising way of increasing efficiency and reducing the response time to warnings. This might be achieved by conducting a process analysis, which could provide evidence and information about bottlenecks or investigate the misuse of information systems or tasks by the players involved.
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Jose Vargas Florez, Anthony Charles, Matthieu Lauras, & Lionel Dupont. (2014). Designing realistic scenarios for disaster management quantitative models. 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. 180–189). University Park, PA: The Pennsylvania State University.
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.
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Stephen C. Fortier, & Ioannis M. Dokas. (2008). Setting the specification framework of an Early Warning System using IDEF0 and information modeling. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 441–450). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Our goal is to develop an Early Warning System for an engineering system with a special interest in applying this to a material recovery facility. This on-going research points out that there is no clear definition of what Early Warning Systems are. A literature search for Early Warning Systems identifies hundred of thousands hits (Buchanan-Smith, 1999; Davies, Buchanan-Smith, Lambert, 1991). Almost all of the references had to do with financial systems for third world countries, tracking the destructive nature of violent conflicts that led to human suffering, or systems for syndromic surveillance. The goal of our research, and of this paper, is to define a framework for creating a specification that can be considered as the basis for the development of any Early Warning System-specifically for engineering systems. Therefore, we will describe Early Warning Systems and its requirements and specifications. Based on specification patterns, we have developed an abstract model of an Early Warning System; and developed an IDEF0 model of a material recovery facility that provides the framework for specifying an Early Warning System. The Early Warning System is then specified using information modeling.
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Sérgio Freire, Christoph Aubrecht, & Stephanie Wegscheider. (2012). When the tsunami comes to town – Improving evacuation modeling by integrating high-resolution population exposure. 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: Tsunamis are a major risk for Lisbon (Portugal) coastal areas whose impacts can be extremely high, as confirmed by the past occurrence of major events. For correct risk assessment and awareness and for implementing mitigation measures, detailed simulation of exposure and evacuation is essential. This work uses a spatial modeling approach for estimating residential population distribution and exposure to tsunami flooding by individual building, and for simulating their evacuation travel time considering horizontal and vertical displacement. Results include finer evaluation of exposure to, and evacuation from, a potential tsunami, considering the specific inundation depth and building's height. This more detailed and accurate modeling of exposure to and evacuation from a potential tsunami can benefit risk assessment and contribute to more efficient Crisis Response and Management. © 2012 ISCRAM.
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