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.

Abstract: In summer of 2014 the city of Münster experienced an urban flash flood not seen before with such intensity in Germany. This paper investigates the subsequent governmental and ad-hoc community response actions with a focus on the chronologies of Facebook and Twitter usage. Interviews identified drawbacks of coordinating volunteers in social media ecosystems. Possible solutions to overcome issues related to the interaction of community and official relief activities are identified.

Abstract: Crisis management training software is gaining researchers? as well as practitioners? interest. In order to truly support organizations it is important that such software responds to actual user needs. The aim of this study is to compare existing initiative described in research with the needs of the users and to identify possible research directions for forthcoming studies. The literature review shows that discussions on users? needs are superficial at best. The software described in research mainly focus on co-located execution of exercises, often in the form of simulations. Furthermore, a ?right or wrong? behavior is usually built-in. Empirical data from a web survey indicate that flexibility in time and space during training is a fundamental user need. This is not particularly acknowledged in earlier research. Neither is the users? wish for better support in designing exercises. We propose that system flexibility, modularity and pedagogy for computer based crisis training are urgent issues for future research.

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.

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.

Abstract: In this paper, we motivate the need for collaborative research and design for IT innovation in crisis response and management. We describe the value of such methodology and demonstrate how working alongside users enables creative anticipation of emergent future practices that can inform both more ?appropriate? and more ambitious innovation. We demonstrate how co-design methods are particularly valuable for eliciting ethical, legal, and social issues that would otherwise go unconsidered.

Abstract: Given the importance of geographic information for riverine flood evacuations, a geographic information system (GIS) is a vital tool for supporting successful flood evacuation operations. This paper discusses the development of a GIS-based riverine flood evacuation model which used to model trip distributions between flooded areas and relocation shelters. As the ultimate goal of this research is to simulate, model, and optimise a planned evacuation, all components of evacuation time have been considered (e.g., travel time between flooded areas and relocation shelters, warning time for each flooded area, and the time needed for evacuation before these areas get inundated). As well, variation in population (static and dynamic population) within the flooded areas has been considered.

Abstract: In a large earthquake, rescue operations and fire-fighting are obstructed by fire-spreading and street-blockages. Therefore, it is important to quickly collect and utilize disaster information for disaster mitigation. In this paper, firstly, we develop a Web application for posting and viewing information collected by users in real time. Using this system, it is possible not only to easily share disaster information among users but also to apply to damage forecast such as fire-spreading. Next, we demonstrate the usefulness of the Web application by the following evaluation view points: (1) relationship between the access time of emergency vehicles from fire stations to the locations of fires and the ratio of collected information on street-blockage which is assumed to be collected with this system; (2) reciprocating time between a server and a client which is dependent on the number of users and band limitation after the occurrence of a disaster.

Abstract: Warning systems are technically, socially, and organizationally shaped and rest on specific assumptions concerning human behavior during disasters. The common notions about people?s behavior in disaster situations are often not based on empirical data, but rather on so-called ?myths? which overemphasize rare and situation-dependent extreme behaviors such as panic, disaster shock, looting or helplessness. Due to the fact that these expectations are shaped within social environments, different stakeholders such as a heterogeneous population and professionals exhibit different assumptions. These assumptions may not only be misplaced, they additionally interfere with warning systems. The paper compares empirical results of three connected surveys: a comprehensive document analysis on disaster behavior, qualitative interviews with disaster relief workers and a quantitative representative poll. By contrasting the status of research with professional narrations as well as with the people?s expectations, different expectations and their variations are explored.

Abstract: Innovations in mobile technology allow the use of Internet and smartphones for communicating disasters and coordinating evacuations. However, given the turbulent nature of disaster situations, the people and systems at crisis center are subjected to information overload, which can obstruct timely and accurate information sharing. A dynamic and automated evacuation plan that is able to predict future disaster outcome can be used to coordinate the affected people to safety in times of crisis. In this paper, we present a dynamic version of the shortest path algorithm of Dijkstra. The algorithm is able to compute the shortest path from the user?s location (sent by the smartphone) to the safety area by taking into account possible affected areas in future. We aim at employing the computed routes on our mobile communication system for navigating affected people during emergency and disaster evacuations. Two simulation studies have validated the performance of the developed algorithm.

Abstract: This paper provides insight into crisis management of infectious disease outbreaks by comparing the current 2014 Ebola outbreak with a well-documented 1793 Yellow Fever outbreak. These reflections on crisis approaches and management from a human factors and cognitive engineering perspective may help encourage the application of historical epidemiology to better prepare for the next global infectious disease outbreak.

Abstract: We present the first release of EMTerms (Emergency Management Terms), the largest crisis-related terminological resource to date, containing over 7,000 terms used in Twitter to describe various crises. This resource can be used by practitioners to search for relevant messages in Twitter during crises, and by computer scientists to develop new automatic methods for crises in Twitter.
The terms have been collected from a seed set of terms manually annotated by a linguist and an emergency manager from tweets broadcast during 4 crisis events. A Conditional Random Fields (CRF) method was then applied to tweets from 35 crisis events, in order to expand the set of terms while overcoming the difficulty of getting more emergency managers? annotations.
The terms are classified into 23 information-specific categories, by using a combination of expert annotations and crowdsourcing. This article presents the detailed terminology extraction methodology, as well as final results.