Track 2: Analytical Modelling and Simulation


Long Papers


 

Crowd Security Detection based on Entropy Model

Ying Zhao, Mengqi Yuan, Guofeng Su, Tao Chen

Abstract

Identifying the terror attack, illegal public gathering or other mass events risks by utilizing cameras is an important concern both in crowd security area and in pattern recognition research area. This paper provides a physical entropy model to measure the crowd security level.The entropy model was created by identifying individuals’moving velocity and the related probability. The individuals are represented by Harris Corners in videos, thus to avoid the time-consuming human recognition task. Simulation experiment and video detection experiments were conducted, verified that in the disordered state, the entropy is higher; while in ordered state, the entropy is much lower; when the crowd security has a sudden change, the entropy will change. It was verified that the entropy is the applicable indicator of crowd security. By recognizing the entropy mutation, it is possible to automatically detect the abnormal crowd behavior and to set the warning alarm.

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Short Papers


 

Influence of Information-Hearsay on Wide-Area Evacuation at a Large Earthquake

Takuya Tsuchiya, Toshihiro Osaragi, Takuya Oki

Abstract

In order to evacuate smoothly and safely at a large earthquake, it is important to obtain the information on property damages (such as street-blockage and fire) and on evacuation areas by hearsay, guidance and bulletin boards. In this paper, we construct a model, which describes wide-area evacuation, information-hearsay among evacuees and guidance behavior. Using this model, we evaluate the influence of information-hearsay on wide-area evacuation in terms of the evacuation time and the risk on evacuation routes. Simulation results demonstrate that the locational information of evacuation areas and damages is the most helpful for people who are unfamiliar with an area. In addition, we discuss the effective and efficient methods of evacuation guidance. The results show that the guides contribute to reducing the evacuation time and the risk on evacuation routes of evacuees, and sharing information among guides enables more efficient and safer evacuation / guidance.

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Agent-based modelling to identify possible measures in case of Critical Infrastructure disruption

Wolfgang Raskob, Stefan Wandler, Evgenia Deines

Abstract

Understanding critical infrastructures and in particular protecting them in case of natural or man-made threats or disasters is the objective of our research. As use case, the security of the power supply in the year 2030 for the city of Karlsruhe was selected. This scenario contains interdependencies between the electrical power grid and IT components as well as critical infrastructures such as water supply and health care. To simulate the critical infrastructure, their dependencies and potential measures to mitigate effects, agent based simulation models have been developed and applied. The ultimate objective of the research activity is to develop a holistic analysis framework to quantify and evaluate requirements and design decisions of the many players in such complex infrastructures.

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EDXL-RESCUER ontology: Conceptual Model for Semantic Integration

Rebeca Barros, Pedro Kislansky, Laís Salvador, Reinaldo Almeida, Matthias Breyer, Laia Gasparin

Abstract

This paper describes an ontology created for the RESCUER[1] (Reliable and Smart Crowdsourcing Solution for Emergency and Crisis Management), a project funded by the European Union and the Brazilian Ministry of Science, Technology and Innovation, it uses crowdsourcing information for supporting Industrial Parks (InPa) and Security Forces during an emergency situation. The proposal, EDXL-RESCUER ontology, is based on EDXL (Emergency Data Exchange Language), and it aims to be the RESCUER conceptual model related to the coordinating and exchanging of information with legacy systems. The ontology was evaluated with end users during a workshop and the results show that EDXL-RESCUER is adequate for Emergency and Crisis domain in InPa and Security forces contexts.

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OntoEmergePlan: variability of emergency plans supported by a domain ontology

Maria I. G. B. Ferreira, João L. R. Moreira, Maria Luiza M. Campos, Bernardo F. B. Braga, Tiago P. Sales, Kelli de F. Cordeiro, Marcos R. S. Borges

Abstract

The preparation of high quality emergency plans to guide operational decisions is an approach to mitigate the emergency management complexity. In such multidisciplinary scenario, teams with different perspectives need to collaborate towards a common goal and interact within a common understanding. In this scenario, the characterization of the variability of the elements involved in these plans is an important issue, which is addressed by the emergency plans generation methodology Document Product Line for Emergency Plans (DPL(EP)). To increase common understanding of plans, we propose an adaptation of this methodology by applying a well-founded emergency ontology, termed OntoEmergePlan, which supports the domain engineering phase. It is grounded in a foundational ontology, which ensures a higher consistency degree to the process of plans generation.

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Applying Best Supply Chain Practices to Humanitarian Relief

Roberta S. Russell, Janine S. Hiller

Abstract

With the growth in length and breadth of extended supply chains, more companies are employing risk management techniques and resilience planning to deal with burgeoning and costly supply chain disruptions. As companies can learn from humanitarian groups, so can humanitarian groups learn from industry how to respond, recover, and prepare for these disruptive events. This paper looks at industry leaders in supply chain risk management and explores how humanitarian supply chains can learn from industry best practices.

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Insights from two-stage stochastic programming in emergency logistics

Douglas Alem, Alistair Clark

Abstract

This paper discusses the practical aspects and resulting insights of the results of a two-stage mathematical network flow model to help make the decisions required to get humanitarian aid quickly to needy recipients as part of a disaster relief operation.  The aim of model is to plan where to best place aid inventory in preparation for possible disasters, and to make fast decisions about how best to channel aid to recipients as fast as possible.  Humanitarian supply chains differ from commercial supply chains in their greater urgency of response and in the poor quality of data and increased uncertainty about important inputs such as transportation resources, aid availability, and the suddenness and degree of "demand".  The context is usually more chaotic with poor information feedback and a multiplicity of decision-makers in different aid organizations.  The model attempts to handle this complexity by incorporating practical decisions, such as pre-allocation of emergency goods, transportation policy, fleet management and procurement, in an uncertainty environment featured by a scenario-based approach. Preliminary results based on the floods and landslides disaster of the Mountain Region of Rio de Janeiro state, Brazil, point to how to cope with these challenges by using the mathematical model.

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Scenario Based Approach for Risks Analysis in Critical Infrastructures

Joaquín López-Silva, Victor A. Bañuls, Murray Turoff

Abstract

This paper proposes a Cross Impact Analysis for supporting critical infrastructures risk analysis. This methodology contributes to decision-makers and planners with analytical tools for modeling complex situations. These features are generally useful in emergency management and particularly within the critical infrastructures scope, where complex scenarios for risk analysis and emergency plans design have to be analyzed. This paper will show by an example how CIA methodology can be applied for risks and identification analysis with an application to a Data Centre of a Critical Infrastructure.

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A multi-agency perspective to disaster preparedness

Oscar Rodríguez-Espíndola, Pavel Albores, Christopher Bewster

Abstract

The increasing number of victims from disasters in recent years results in several challenges for authorities aiming to protect and provide support to affected people. Humanitarian logistics represents one of the most important fields during preparedness and response in cases of disaster, seeking to provide relief, information and services to disaster victims. However, on top of the challenges of logistical activities, the successful completion of operations depends to a large extent on coordination. This is particularly important for developing countries, where disasters occur very often and resources are even scarcer.

This paper assumes a multi-agency approach to disaster preparedness that combines geographical information systems (GIS) and multi-objective optimization. The purpose of the tool is to determine the location of emergency facilities, stock prepositioning and distribution allocation for floods. We illustrate the application and the results using a case study centred on Acapulco, México.

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Expression and Deduction of emergency scenario based on scenario element model

Chao Sun, Fushen Zhang, Shaobo Zhong, Quanyi Huang

Abstract

In the context of an era filled with frequent occurrence of emergencies, it is urgent to carry out effective treatment. The existing studies focus their research on general rule of emergency evolution, ignoring the consideration of concrete composition of scenario, whilethe formulation of contingency plan based on the real evolution process of the emergency is rare. In this paper, the basic model of scenario elements is proposed firstly. Next, from the perspective of evolution and disposal of emergency, the framework of scenario for emergencies and emergency disposal is put forward, which paves the way for depiction and scenario analysis of emergency. Finally, this paper takes the stampede as an example, dividing the scenario of emergency and its components, namely scenario elements, and representing the evolution scenario of stampede by scenario elements model. Our method takes advantage of scenario elements model to provide support for the formulation and evaluation of emergency exercise.

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Collaborative Evolution of a Dynamic Scenario Model for the Interaction of Critical Infrastructures

Murray Turoff, Victor A. Bañuls, Linda Plotnick, Starr Roxanne Hiltz, Miguel Ramirez de la Huerga

Abstract

This paper reviews current work on a model of the cascading effects of Critical Infrastructure (CI) failures during disasters.  Based upon the contributions of 26 professionals, we have created a reliable model for the interaction among sixteen CIs.  An internal CI model can be used as a core part of a number of larger models, each of which are tailored to a specific disaster in a specific location.

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Critical Infrastructure Resilience: A Framework for Considering Micro and Macro Observation Levels

Florian Brauner, Thomas Münzberg, Marcus Wiens, Frank Fiedrich, Alex Lechleuthner, Frank Schultmann

Abstract

The resilience mechanisms of Critical Infrastructures (CIs) are often hard to understand due to system complexity. With rising research interest, models are developed to reduce this complexity. However, these models imply reductions and limitations. According to the level of observation, models either focus on effects in a CI system or on effects in a single CI. In cases of limited resources, such limitations exclude some considerations of crisis interventions, which could be identified in combining both observation levels. To overcome these restrictions, we propose a two-step framework which enables to analyze the vulnerability of a CI and as well in comparison to other CIs. This enhances the understanding of temporal crisis impacts on the overall performance of the supply, and the crisis preparations in each CI can be assessed. The framework is applied to the demonstrating example of the functionalities of hospitals that are potentially suffering from a power outage.

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Enhanced forest fire risk assessment through the use of fire simulation models

Joaquin Ramirez, Miguel Mendes, Santiago Monedero

Abstract

Forest fire risk assessment is an important task for forest fire management and planning. This paper presents current work on the definition and implementation of forest fire risk assessment models in the Wildfire AnalystTM software with the purpose of providing support and increased value in risk assessment. Three models are presented based on the concept of forest fire risk: forest fire structural hazard model that provides the assessment of the expected easiness that a fire has to spread in a certain area, a stochastic model that assesses the fire growth potential considering as potential ignition points critical elements of electric supply networks and a stochastic model that assesses the potential impact of forest fires on these infrastructures.

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Enhancing the quality of contingency planning by simulation

Hanna Honkavuo, Markus Jähi, Ari Kosonen, Kalevi Piira, Kalev Rannat, Jari Soininen, Merik Meriste, Kuldar Taveter

Abstract

Contingency planning is a significant challenge when dealing with rarely occurring cases. First of all, the situation related threats can be difficult to identify. Moreover, it is difficult to conclude what happens when multiple threats occur simultaneously. In this paper we introduce the idea of an application which allows seamless cooperation between many experts.

In this paper we describe a computer based simulation application which is designed to support contingency planning – having resources available – in extreme winter condition. First we introduce the background of the simulation - sparsely populated areas in Northern Finland where long distances and extremely cold weather can make disturbance situations even more difficult to be normalized by authorities. Secondly we present the tools that are used to build up the application. Finally, we discuss what benefits the application offers for the authorities, preparedness planning and society.

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Stochastic source term estimation of HAZMAT releases: algorithms and uncertainty

Yan Wang, Hong Huang, Wei Zhu

Abstract

Source term estimation (STE) of hazardous material (HAZMAT) releases is critical for emergency response. Such problem is usually solved with the aid of atmospheric dispersion modelling and inversion algorithms accompanied with a variety of uncertainty, including uncertainty in atmospheric dispersion models, uncertainty in meteorological data, uncertainty in measurement process and uncertainty in inversion algorithms. Bayesian inference methods provide a unified framework for solving STE problem and quantifying the uncertainty at the same time. In this paper, three stochastic methods for STE, namely Markov chain Monte Carlo (MCMC), sequential Monte Carlo (SMC) and ensemble Kalman filter (EnKF), are compared in accuracy, time consumption as well as the quantification of uncertainty, based on which a kind of flip ambiguity phenomenon caused by various uncertainty in STE problems is pointed out. The advantage of non-Gaussian estimation methods like SMC is emphasized.

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Fast Marching Method Applied For Emergency Evacuation in High-rise Building Fire

Quanlai Zhao, Guofeng Su, Hongyong Yuan

Abstract

In this paper, we use the fast marching method to solve the emergency evacuation in high-rise building fire. This method is a numerical method which is used to solve the Eikonal equation in rectangular grids. As we know, building fires are very common in the world. They have caused a great deal of personnel casualty and property losses. How to reduce the casualty and ensure the life safety of trapped persons and rescuers have become the most important problem of the fire department. We carry out fire experiment and FDS simulation to research the structure fire firstly. Second, we divide the construction into 0.4m*0.4m grid. This size is a person who occupied when he is standing. After that, we use interpolation method to analyze the experiment and FDS simulation data so that we can get the risk value of each grid. At last, we calculate the global potential energy field of the scene based on the fast marching method and obtain a safest path for the trapped persons. The safest path represents the fastest-risk-decline path. In the cause of fire rescue we can provide the safest path to the trapped persons through evacuation signals of the building in order to guide them to evacuate and self-rescue.

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Assessment of the radiation doses to the public from the cesium in oceans after Fukushima Nuclear Accident

Yue Guan, Shifei Shen, Hong Huang

Abstract

A great number of radioactive cesium were released into sea water after Fukushima Accident. We modified the Regional Oceanic Modelling System (ROMS) to reproduce the dispersion process of the cesium in oceans. The simulated water concentration was in good agreement with observation. In order to explore the nuclear impact of these contaminant in ocean, we established a food web model to calculate the concentration in marine organisms and assess the internal dose rate to the public. The estimated internal dose rate is small compared with the recommended limit by International Atomic Energy Agency (IAEA). Then, we employed the Monte Carlo N Particle Transport Code (MCNP) to calculate the transfer coefficient. The external dose rate could be estimated by this coefficient and simulated water concentration.

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