André Simões, Armanda Rodrigues, Patricia Pires, & Luis Sá. (2011). Evaluating emergency scenarios using historic data: Flood 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: The evaluation of an emergency scenario is often based on the use of simulation models. The specificity of these models involves the need for a complex evaluation of the problem domain, including the physical conditions behind the considered threat. Based on emergency occurrences data, provided by the Portuguese National Civil Protection Authority, we are currently developing a methodology for evaluating a real situation, based on past occurrences. The aim is to develop a platform that will enable the evaluation of a risk scenario based on existing civil protection data. The methodology under development should enable the evaluation of different scenarios based on the collected available data. This will be achieved thanks to the facilitated configuration of several aspects, such as the geographical region and relevant properties of the considered threat. In this paper, we describe the methodology development process and the current state of the platform for risk evaluation.
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Anna Kruspe, Jens Kersten, & Friederike Klan. (2019). Detecting event-related tweets by example using few-shot models. 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: Social media sources can be helpful in crisis situations, but discovering relevant messages is not trivial. Methods
have so far focused on universal detection models for all kinds of crises or for certain crisis types (e.g. floods).
Event-specific models could implement a more focused search area, but collecting data and training new models for
a crisis that is already in progress is costly and may take too much time for a prompt response. As a compromise,
manually collecting a small amount of example messages is feasible. Few-shot models can generalize to unseen
classes with such a small handful of examples, and do not need be trained anew for each event. We show how
these models can be used to detect crisis-relevant tweets during new events with just 10 to 100 examples and
counterexamples. We also propose a new type of few-shot model that does not require counterexamples.
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Arif Cagdas Aydinoglu, Elif Demir, & Serpil Ates. (2011). Designing a harmonized geo-data model for 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: There are problems for managing and sharing geo-data effectively in Turkey. The key to resolving these problems is to develop a harmonized geo-data model. General features of this model are based on ISO/TC211 standards, INSPIRE Data Specifications, and expectations of Turkey National GIS actions. The generic conceptual model components were defined to harmonize geo-data and to produce data specifications. In order to enable semantic interoperability, application schemas were designed for data themes such as administrative unit, address, cadastre/building, hydrographic, topography, geodesy, transportation, and land cover/use. The model, as base and the domain geo-data model, is a starting point to create sector models in different thematic areas. Disaster Management Geo-data Model model was developed as an extension of base geo-data model to manage geo-data collaborate on disaster management activities. This model includes existing geo-data special for disaster management activities and dynamic data collecting during disaster.
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Arthur H. Hendela, Murray Turoff, & Starr Roxanne Hiltz. (2010). Cross impact security analysis using the HACKING Game. 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: Security of network assets is a high priority with little traditional return on investment. Increasingly, cyber attacks are being used by both terrorist and unfriendly government organizations. The HACKING Game, a Cross Impact Analysis planning tool, can be used to plan security resource allocation in computer networks. Cross Impact Analysis provides a mathematical basis to determine the interrelationships of one event with a set of other events. Output from the HACKING Game's Cross Impact Analysis model can be used to help justify security expenditures, with an added benefit of being a training tool for employees learning to protect networks. This paper presents details of the Hacking Game's design and its capabilities. Cross impact modeling can be used to develop games for any situation characterized by a set of offense and defense events to produce an individual or collaborative model for such things as natural and man-made disasters.
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Babajide Osatuyi, & David Mendonça. (2010). Requirements for modeling collaborative information foraging behavior: An application to emergency response organizations. 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: Collaborative information foraging refers to the collective activities of seeking and handling information in order to meet information needs. This paper delineates requirements for modeling salient factors that shape collaborative information foraging behavior of groups. Existing modeling approaches are assessed based on their adequacy for measuring identified salient factors that shape collaborative information foraging behavior. A view of information foraging behavior as a dynamic process is presented. Consequently, this paper purports that modeling methods employed to aid understanding of foraging behavior must allow for plausible explanation of the inherent dynamism in foraging activities. This work therefore provides an initial roadmap to defining salient factors that need to be addressed in order to adequately model collaborative information foraging behavior within teams that operate in extreme environments. Implications of this work in practice and research are discussed.
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Beate Rottkemper, & Kathrin Fischer. (2013). Decision making in humanitarian logistics – A multi-objective optimization model for relocating relief goods during disaster recovery operations. 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. 647–657). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Disaster recovery operations rarely proceed smoothly and disruptions often require the redistribution of relief items. Such a redistribution has to be carried out taking into account both the current disruption and the uncertainty regarding possible future incidents in the respective area. As decisions have to be made fast in humanitarian operations, extensive optimization runs cannot be conducted in such a situation. Nevertheless, sensible decisions should be made to ensure an efficient redistribution, considering not only satisfaction of needs but also operational costs, as the budget is usually scarce in the recovery phase of a disaster. In this work, different scenarios are generated and then solved with a multiobjective optimization model to explore possible developments. By evaluating the results of these scenarios, decision rules are identified which can support the decision maker in the actual disaster situation in making fast, but nevertheless well-founded, decisions.
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Catherine Lowry Campbell, Fadi Deek, Murray Turoff, & Bartel A. Van De Walle. (2004). Measuring consensus and conflict among stakeholders in emergency response information system requirements negotiations. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 121–126). Brussels: Royal Flemish Academy of Belgium.
Abstract: This paper introduces the experimental design we developed for the analysis of asynchronous negotiations among five different stakeholders as they work towards consensus on the functional system requirements that are needed for a common emergency response information system. We present three analytical preference models to measure the evolving consensus and conflict among the stakeholders as they modify their preferences during the negotiation. We illustrate the use of these techniques for obtaining a detailed understanding of the negotiation dynamics among the stakeholders. © Proceedings ISCRAM 2004.
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Christoph Aubrecht, Klaus Steinnocher, & Hermann Huber. (2014). DynaPop – Population distribution dynamics as basis for social impact evaluation in crisis 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. 314–318). University Park, PA: The Pennsylvania State University.
Abstract: In this paper ongoing developments regarding the conceptual setup and subsequent implementation logic of a seamless spatio-temporal population dynamics model are presented. The DynaPop model aims at serving as basic input for social impact evaluation in crisis management. In addition to providing the starting point for assessing population exposure dynamics, i.e. the location and number of affected people at different stages during an event, knowledge of spatio-temporal population distribution patterns is also considered crucial for a set of other related aspects in disaster risk and crisis management including evacuation planning and casualty assessment. DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation.
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Cindy Hui, Mark Goldberg, Malik Magdon-Ismail, & William A. Wallace. (2008). Micro-simulation of diffusion of warnings. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 424–430). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents a unique view of modeling the diffusion of warnings in social networks where the network structure may change over time. Since the characteristics and actions of people in a community have significant influence on the flow of information through a network, we present an axiomatic framework for modeling the diffusion process through the concept of trust. This ongoing work provides a micro level view of the behavior of individuals and groups in a community. Preliminary experiments were made to explore how model parameters such as trust and the social network structure affect warning message belief and evacuation.
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Daniel E. Lane, Tracey L. O'Sullivan, Craig E. Kuziemsky, Fikret Berkes, & Anthony Charles. (2013). A structured equation model of collaborative community response. 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. 906–911). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper analyses the collaborative dynamic of community in response to urgent situations. Community emergencies arising from natural or man-induced threats are considered as exogenous events that stimulate community resources to be unified around the response, action, and recovery activities related to the emergency. A structured equation model is derived to depict the actions of the community system. The system is described in terms of its resources including the propensity to trigger community action and collaboration among diverse groups. The community is profiled with respect to its ability to respond. The system defines the trigger mechanisms that are considered to be the drivers of collaborative action. A simulation model is presented to enact the system emergencies, community profiles, and collaborative response. The results develop an improved understanding of conditions that engage community collaborative actions as illustrated by examples from community research in the EnRiCH and the C-Change community research projects.
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Dragos Datcu, & Leon J.M. Rothkrantz. (2007). The use of active appearance model for facial expression recognition in crisis environments. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 515–524). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In the past a crisis event was notified by local witnesses that use to make phone calls to the special services. They reported by speech according to their observation on the crisis site. The recent improvements in the area of human computer interfaces make possible the development of context-aware systems for crisis management that support people in escaping a crisis even before external help is available at site. Apart from collecting the people's reports on the crisis, these systems are assumed to automatically extract useful clues during typical human computer interaction sessions. The novelty of the current research resides in the attempt to involve computer vision techniques for performing an automatic evaluation of facial expressions during human-computer interaction sessions with a crisis management system. The current paper details an approach for an automatic facial expression recognition module that may be included in crisis-oriented applications. The algorithm uses Active Appearance Model for facial shape extraction and SVM classifier for Action Units detection and facial expression recognition.
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Erkki Kurkinen. (2013). The effect of age on technology acceptance among field police officers. 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. 468–477). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper studies the differences on technology acceptance between two age groups among uniform police forces. The goal was to seek more understanding on the effects of age on technology adaption in the context of mandatory technology use. Data was collected from police officers in field operations. User intentions were measured after subjects had seen a presentation of a pre-prototype of a mobile information system on the video. The results of this study suggest that there is no difference between the old and young age groups. Similarly, the results suggest that the effect of age is similar between the age groups on the effects of the factors in the research model. This suggests that the old police officers are similar to young police officers regarding the acceptance of new technology for their use. The most prominent result was that regression of behavioral intention on perceived usefulness was not statistically important.
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Felix Wex, Guido Schryen, & Dirk Neumann. (2012). Operational emergency response under informational uncertainty: A fuzzy optimization model for scheduling and allocating rescue units. 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: Coordination deficiencies have been identified after the March 2011 earthquakes in Japan in terms of scheduling and allocation of resources, with time pressure, resource shortages, and especially informational uncertainty being main challenges. We suggest a decision support model that accounts for these challenges by drawing on fuzzy set theory and fuzzy optimization. Based on requirements from practice and the findings of our literature review, the decision model considers the following premises: incidents and rescue units are spatially distributed, rescue units possess specific capabilities, processing is non-preemptive, and informational uncertainty through linguistic assessments is predominant when on-site units vaguely report about incidents and their attributes, or system reports are not exact. We also suggest a Monte Carlo-based heuristic solution procedure and conduct a computational evaluation of different scenarios. We benchmark the results of our heuristic with results yielded through applying a greedy approach. The results indicate that using our Monte Carlo simulation to solve the decision support model inspired by fuzzy set theory can substantially reduce the overall harm. © 2012 ISCRAM.
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Franclin Foping, & Ioannis M. Dokas. (2013). A saas-based early warning information fusion system for critical infrastructure safety. 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. 156–165). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Maintaining the critical infrastructures, such as Drinking Water Treatment Plants (DWTP), transportation, power generation and communications systems, in a safe state is a complex problem. The effective collaboration, as well as the collection aggregation and dissemination of early warning information among the stakeholders of the Safety Management System (SMS) responsible for the safety of these critical infrastructures are some of the challenges that need to be addressed. This paper argues that the Software as a Service (SaaS) deployment model can offer new ways of enhancing the fusion of early warning information during the operation phase of critical infrastructures. It presents the requirements, the architecture and a number of features of a working prototype SaaS-based early warning information fusion system for DWTP safety issues in the Republic of Ireland. It is the first time that a SaaSbased working prototype system is reported of providing early warning information fusion services in the literature.
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Gabriel Jakobson, Nandan Parameswaran, John Buford, Lundy Lewis, & Pradeep Ray. (2006). Situation-Aware multi-Agent system for disaster relief operations management. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 313–324). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Natural and human-made disasters create unparalleled challenges to Disaster Situation Management (DSM). One of the major weaknesses of the current DSM solutions is the lack of comprehensive understanding of the overall disaster operational situation, and very often making decisions based on a single event. Such weakness is clearly exhibited by the solutions based on the widely used Belief-Desire-Intention (BDI) models for building the Muiti-Agent Systems (MAS). In this work we present the adaptation of the AESOP situation management architecture to address the requirements of disaster relief operations. In particular, we extend the existing BDI model with the capability of situation awareness. We describe how the key functions of event collection, situation identification, and situation assessment are implemented in MAS architecture suitable to the characteristics of large-scale disaster recovery. We present the details of a BDI agent in this architecture including a skeleton ontology, and the distributed service architecture of the AESOP platform.
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Gary Eifried. (2005). A model describing a response to a terrorism incident. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 125–127). Brussels: Royal Flemish Academy of Belgium.
Abstract: Understanding how the response to an incident of terrorism involving a Weapons of Mass Destruction (WMD) transpires is essential to understanding the necessary flow of information within that response. A model describing incident response functions overlaid on a realistic timeline is presented.
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Hans Christian Augustijn Wienen, Faiza Allah Bukhsh, Eelco Vriezekolk, & Roel J. Wieringa. (2018). Accident Analysis Methods and Models – a Systematic Review. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 398–408). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: After a risk has manifested itself and has led to an accident, valuable lessons can be learned that can be taken into account to reduce the risk of a similar accident occurring again. This calls for accident analysis methods. In the past 20 years a large number of accident analysis methods have been proposed and it is difficult to find the right method to apply in a specific circumstance. We conducted a review of the state of the art of accident analysis methods and models across domains. We classify the models using the well-known categorization into sequential, epidemiological and systemic methods. We find that these classes have their own characteristics in terms of speed of application versus pay-off. For optimum risk reduction, methods that take organizational issues into account can add valuable information to the risk management process in an organization.
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Huizhang Shen, & Jidi Zhao. (2010). Decision-making support based on the combination of CBR and logic reasoning. 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: In recent years, various crises arise frequently and cause tremendous economic and life losses. Meanwhile, current emergency decision models and decision support systems still need further improvement. This paper first proposes a new emergency decision model based on the combination of a new case retrieval algorithm for Case-Based Reasoning (CBR) and logic reasoning, and then address a sample flood disaster emergency decision process to explain the application of the model in practice.
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Jean-François Gagnon, Martin Rivest, François Couderc, & Sébastien Tremblay. (2012). Capturing the task model of experts in emergency response using SYnRGY. 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: The need for better team measurement in realistic environments has been recognized as one of the key challenges that characterize the field of team work studies (Salas, Cooke, & Rosen, 2008). This challenge is particularly hard to address in the context of emergency response, due to the inherent complexity and dynamism of the domain. Emergency response is part of the emergency management cycle, and refers to the mobilization of the adequate actors and resources to mitigate the impact of an incident on the public and on the environment (Abrahamsson, Hassel, and Tehler, 2010). Emergency response often requires the cooperation of multiple agencies such as police, medical, and fire services, consequently increasing the complexity of such operations. We report of how SYnRGY – a human-centered emergency response technological tool – is embedded with extensive measurement and simulation capabilities to allow tracing of experts' task models in a silent and reliable way. We describe how these capabilities; combined with an innovative modeling technique – dynamic cognitive task modeling – can be used to extract experts' representations of the task. We discuss the importance of such a model for training, improvement of emergency response procedures and development of emergency response tools. © 2012 ISCRAM.
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Jennifer Mathieu, Mark Pfaff, Gary L. Klein, Jill L. Drury, Michael Geodecke, John James, et al. (2010). Tactical robust decision-making methodology: Effect of disease spread model fidelity on option awareness. 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: We demonstrate a method of validating the utility of simpler, more agile models for supporting tactical robust decision making. The key is a focus on the decision space rather than the situation space in decision making under deep uncertainty. Whereas the situation space is characterized by facts about the operational environment, the decision space is characterized by a comparison of the options for action. To visualize the range of options available, we can use computer models to generate the distribution of plausible consequences for each decision option. If we can avoid needless detail in these models, we can save computational time and enable more tactical decision-making, which will in turn contribute to more efficient Information Technology systems. We show how simpler low fidelity, low precision models can be proved to be sufficient to support the decision maker. This is a pioneering application of exploratory modeling to address the human-computer integration requirements of tactical robust decision making.
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Jian Wang, Daniela Rosca, Williams Tepfenhart, & Allen Milewski. (2006). Incident command system workflow modeling and analysis: A case study. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 127–136). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: The dynamics and volunteer-based workforce characteristics of incident command systems have raised significant challenges to workflow management systems. Incident command systems must be able to adapt to ever changing surroundings and tasks during an incident. These changes need to be known by all responsible parties, since people work in shifts, get tired or sick during the management of an incident. In order to create this awareness, job action sheets and forms have been created. We propose a paperless system that can dynamically take care of these aspects, and formally verify the correctness of the workflows. Furthermore, during an incident, the majority of workers are volunteers that vary in their knowledge of computers, or workflows. To address these challenges, we developed an intuitive, yet formal approach to workflow modeling, modification, enactment and validation. In this paper, we show how to apply this approach to address the needs of a typical incident command system workflow.
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Johan Jenvald, Michael Morin, Toomas Timpka, & Henrik Eriksson. (2007). Simulation as decision support in pandemic influenza preparedness and response. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 295–304). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Outbreak of a destructive pandemic influenza threatens to disrupt societies worldwide. International agencies and national governments have prepared plans and recommendations, but it is often decision-makers with the local authorities that are responsible for implementing the response. A central issue for these decision makers is what interventions are available and effective for the specific local community. The paper presents a simulator architecture and its relation to a workflow for decision support in influenza preparedness and response. The simulator can simulate pandemic scenarios, using localized community models, in the presence of various interventions to support an evaluation of potential response strategies. The architecture includes a customized modeling tool, separated from the simulation engine, which facilitates swift scenario modification and recalculation. This flexibility is essential both to explore alternative solutions in planning, and to adapt to changing requirements, information, and resources in outbreak response. An example simulation, based on actual population data from a reference city, illustrates the approach.
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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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Julian Zobel, Patrick Lieser, Tobias Meuser, Lars Baumgärtner, Mira Mezini, & Ralf Steinmetz. (2021). Modeling Civilian Mobility in Large-Scale Disasters. 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. 119–132). Blacksburg, VA (USA): Virginia Tech.
Abstract: When disasters destroy critical communication infrastructure, smartphone-based Delay-Tolerant Networks (DTNs) can provide basic communication for civilians. Although field tests have shown the practicability of such systems, real-world experiments are expensive and hardly repeatable. Simulations are therefore required for the design and extensive evaluation of novel DTN protocols, but meaningful assertions require realistic mobility models for civilians. In this paper, trace files from a large-scale disaster field test are analyzed to identify typical human behavior patterns in a disaster area. Based on this, we derive a novel civilian disaster mobility model that incorporates identified behaviors such as group-based movement and clustering around points-of-interests such as hospitals and shelters. We evaluate the impact of mobility on DTN communication performance by comparing our model with other established mobility models as well as the trace file dataset in a simulative evaluation based on the field test scenario. In general, our mobility model leads to a more realistic assessment of DTN communication performance compared to other mobility models.
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Kelli de Faria Cordeiro, Maria Luiza M Campos, & Marcos R. S. Borges. (2014). Adaptive integration of information supporting decision making: A case on humanitarian logistic. 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. 225–229). University Park, PA: The Pennsylvania State University.
Abstract: There is an urgent demand for information systems to gather heterogeneous information about needs, donations and warehouse stocks to provide an integrated view for decision making in humanitarian logistics. The dynamic flow of information, due to the unpredicted events, requires adaptive features. The traditional relational data model is not suitable due to its schema rigidity. As an alternative, Graph Data models complemented by semantic representations, like Linked Open Data on the Web, can be used. Based on both, this research proposes an approach for the adaptive integration of information and an associated architecture. An application example is discussed in a real scenario where relief goods are managed through a dynamic and multi-perspective view.
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