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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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Anying Chen, Guofeng Su, & Manchun Liang. (2019). Simulation of Crowd Response During Emergency Considering People's Rational and Irrational Thinking. 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: Human beings have been facing numerous emergencies which could threaten their property or even their lives in all ages. In order to learn how people respond to the emergencies like earthquakes and fire disasters, a two-stage simulation considering people?s rational thinking and irrational thinking was conducted. Results show that people?s irrational thinking, like the herd effect, could exaggerate people?s behavior of conformity, and it changes the spatial features that stronger herd effect leads to higher cohesion level. It is also worth mentioning that crowd response of condition of smaller population is harder to predict because of its instability, and the response of the very first part of people who make decisions could make great changes to the whole crowd?s response. These results could give some enlightenment on the evacuation instruction during emergencies and future research works.
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Duygu Pamukçu, Christopher William Zobel, & Andrew Arnette. (2019). A New Data-Driven Approach to Measuring Hurricane Risk. 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: Improving disaster operations requires understanding and managing risk. This paper proposes a new data-driven approach for measuring the risk associated with a natural hazard, in support of developing more effective approaches for managing disaster operations. The paper focuses, in particular, on the issue of defining the inherent severity of a hazard event, independent of its impacts on human society, and concentrates on hurricanes as a specific type of natural hazard. After proposing a preliminary severity measure in the context of a hurricane, the paper discusses the issues associated with collecting empirical data to support its implementation. The approach is then illustrated by comparing the relative risk associated with two different locations in the state of North Carolina subject to the impacts of Hurricane Florence in 2018.
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Eric Daudé, Kevin Chapuis, Clément Caron, Alexis Drogoul, Benoit Gaudou, Sebastien Rey-Coyrehourq, et al. (2019). ESCAPE: Exploring by Simulation Cities Awareness on Population Evacuation. 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: Partial or total horizontal evacuation of populations in urban areas is an important protection measure against a natural or technological risk. However, casualties during massive displacement in a context of stress and in a potentially degraded environment may be high due to non-compliance with instructions, accidents, traffic jams, incivilities, lack of preparation of civil security or increased exposure to hazards. Working in evacuation plans is therefore fundamental in avoiding casualties caused by improvisation and in promoting self-evacuation whenever possible. Since it is impossible to re-create the conditions of a crisis on the ground to assess such evacuation plans, there is a need for realistic models in order to evaluate them using simulations. In this paper, we present the ESCAPE software framework that helps in the development of such plans and testing them. In particular, ESCAPE, which uses the GAMA open-source platform as a core component, provides an agent-based simulation tool that supports simulation of the evacuation of a city's population at fine temporal and Geographical scales. The framework was developed such that it works for a wide range of scenarios, both in terms of hazards, geographical configurations, individual behaviors and crisis management. In order to show its adaptability, two applications are presented, one concerning the evacuation of the city of Rouen (France) in the context of a technological hazard and the other pertaining to the evacuation of the district of Hanoi (Vietnam) in the event of floods.
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Flavio Dusse, Renato Novais, & Manoel Mendonça. (2019). Understanding the Main Themes Towards a Visual Analytics Based Model for Crisis Management Decision-Making. 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: Crisis Management (CM) refers to the ability to deal with crisis tasks in different phases and iterations. People working in a crisis are generally under stress to make the right decision at the right time. They have to process large amounts of data and to assimilate the received information in an intuitive and visual way. Visual Analytics (VA) is potentially useful to analyze and understand the huge amount of data in several areas including in a crisis. We designed a survey protocol to understand which themes influence visualizations to support CM. In previous work, we carried out systematic mapping studies, analysis of official documents, ethnographic studies, questionnaires during the large events held in Brazil in recent years. In this work, we interviewed eight CM specialists. We analyzed this data qualitatively with the coding technique. Then we evaluated the coding results with the focus group technique. With the results, we identified the relationships between the visual needs and other main themes of influence for CM. This thematic synthesis enabled us to build a draft model based on VA.
We hope that, after future cycles of validations and improvements, the agencies that manage crises might use this model as a reference in their activities of knowledge production and decision-making.
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Haya Aldossary, & Graham Coates. (2019). A Preliminary Optimisation-based Approach to Coordinate the Response of Ambulances in Mass Casualty Incidents. 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: Mass Casualty Incidents (MCIs) may occur with no notice and require a rapid response to manage the casualties and arrange their transportation to hospitals. MCIs may result in different numbers of casualties and fatalities. Further, response time can play a crucial role in reducing fatalities and protecting lives. This paper reports on a preliminary optimisation-based approach, termed MCIER, which has been developed to co-ordinate the response of ambulances to multiple MCIs. In this approach, a realistic representation of the road network is modelled for the geographical area of interest. Also, a Neighbourhood Search Algorithm (NSA) has been developed in order to find the optimum solution to the problem under consideration. A hypothetical case study of a MCI in Newcastle-upon-Tyne has been considered to investigate the effect on response time of the time of day, and day of week, on which the incident occurs.
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Juan Francisco Carías, Leire Labaka, Jose Maria Sarriegi, Andrea Tapia, & Josune Hernantes. (2019). The Dynamics of Cyber Resilience Management. 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: With the latent problem of security breaches, denial of service attacks, other types of cybercrime, and cyber incidents in general, the correct management of cyber resilience in critical infrastructures has become a high priority. However, the very nature of cyber resilience, requires managing variables whose effects are hard to predict, and that could potentially be expensive. This makes the management of cyber resilience in critical infrastructures a substantially hard task.
To address the unpredictability of the variables involved in managing cyber resilience, we have developed a system dynamics model that represents the theoretical behaviors of variables involved in the management of cyber resilience. With this model, we have simulated different scenarios that show how the dynamics of different variables act, and to show how the system would react to different inputs.
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Marco Polo Ruiz Herrera, & Juan Sánchez Díaz. (2019). Improving Emergency Response through Business Process, Case Management, and Decision 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: The emergency procedures contain a set of actions responsible for providing the necessary corrective measures to address an emergency. The relevance of contextual knowledge during emergency responses is of utmost importance since many decisions are made from the information gathered in real time that sometimes conflicts with the formal knowledge specified in the emergency plan. Consequently, tools that support the emergency plan mentioned must be sensitive to context and allow decision making at the time an emergency takes place. We demonstrate how Case Management Modeling Notation (CMMN) along with Decision Model and Notation (DMN) are very suitable approaches to obtain a flexible model adapted to the context-driven response processes.
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Meshal Alharbi, & Graham Coates. (2019). Assessing Flood Recovery of Small Businesses using Agent-Based Modelling and Simulation. 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: In developed countries, small and medium-sized enterprises (SMEs) represent the majority of all businesses, e.g. 99.9% in the UK. Given this significant proportion, any disruption to the operation of SMEs will have a negative impact on a nation?s economy. In the context of flooding, this paper reports on the use of agent-based modelling and simulation (ABMS) to assess SMEs immediate response and short-term recovery. In particular, it focuses on the interactions between manufacturing SMEs and mutual aid partners, and retail SMEs and companies specializing in refurbishing premises. Results show that a manufacturing SME with a mutual aid partner can reduce loss in production by approximately 6% over a 7 working day period. In relation to retail
SMEs, those with employees able to be allocated to refurbish its premises recovered faster than SMEs employing a refurbishment company, potentially one day earlier.
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Patrick Lieser, Julian Zobel, Björn Richerzhagen, & Ralf Steinmetz. (2019). Simulation Platform for Unmanned Aerial Systems in Emergency Ad Hoc Networks. 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.
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Toshihiro Osaragi, & Noriaki Hirokawa. (2019). Simulation Analysis of Fire Hydrant Usability Levels after Large Earthquake. 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: Since large earthquakes can disrupt water supply networks, it is essential to gain an understanding of the expected
usability of fire hydrants in post-quake firefighting activities. In this study, data about water supply networks was
collected and a water outage simulation model was constructed in order to predict the likelihood that individual
fire hydrants would become unusable in the wake of a large earthquake. The water outage simulation model was
integrated with a previously developed urban zone damage simulation and a fire department activity simulation
in order to carry out a simulation-based analysis of the 23 wards of Tokyo, after which a quantitative analysis of
the relation-ship between use of fire hydrants and the number of buildings lost to fire was performed. This analysis
revealed the benefits of hardening water lines against earthquakes, fire hydrant usage variations depending on
locality, and the benefits of using water pressure sensors to identify usable fire hydrants.
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Xiujuan Zhao, Jianguo Chen, Peng Du, Wei Xu, Ran Liu, & Hongyong Yuan. (2019). Location-allocation model for earthquake shelter solved using MPSO algorithm. 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: Constructing shelters in suitable quantities, with adequate capacities and at the right locations is essential for evacuees under earthquake disasters. As one of the disaster management methods, constructing shelters can help to significantly reduce disruption and devastation to affected population. Mathematical models have been used to solve this problem allied with a heuristic optimization algorithm. The optimization of evacuation efficiency, as one of the most important objectives, has many expressive forms, such as minimizing evacuation distance and evacuation time. This paper proposes a new model that aims to minimize evacuation time with a new calculation method and to maximize total evacuees? comfort level. The modified particle swarm optimization (MPSO) algorithm is employed to solve the model and the result is compared with a model that calculated evacuation time differently and a model without distance constraint, respectively.
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