Abstract: This paper describes an approach to training emergency responders for mass casualty incidents. The approach is derived from a methodology and supporting software system called Summit. The Summit approach uses an integration of scenarios, hierarchical task analysis, interaction modeling, and expected utility theory to represent how actors engage in complex tasks; here we model mass casualty incident (MCI) activities supported by interactive technologies. Our goal is to ground MCI training in realistic scenarios and to demonstrate required response capabilities through associated hierarchical task analyses (HTA). The terminal nodes in an HTA are interactions, that provide a fine-grained model of the actors, technologies, data, and methods involved in realizing the required capability. The components of an interaction may have associated utility factors (benefits, costs, and risks) that provide learners with a rationale-based resource for understanding how different technologies are used to support MCI response efforts. Assessment of the approach is underway within a local EMS organization.

Abstract: Networking in the event of disasters requires new hybrid wireless architectures such as Wireless Mesh Networks (WMNs). Provisioning Quality of Service (QoS) in such networks which are quickly deployed during emergencies demand radical solutions. In this paper, we provide a new QoS approach for voice calls over a wireless mesh networks during emergency situations. According to our scheme, the contention and back-off parameters are modified based on the emotion content in the voice streams. This paper also looks at methods for detecting emotion from an incoming voice call using the speech signal. The issues of interest in such situations are whether the caller is in a state of extreme panic, moderate panic, or in a normal state of behavior. The communication network behavior should be modified to provide differentiated QoS for calls based on the degree of emotion. We use several features extracted from the speech signal like the range of pitch variation, energy in the critical bark band, range of the first three formant variations, and speaking rate among others to discriminate between the three emotional states. At the back end the Gaussian mixture modeling techniques is used to model the three emotional states of the speaker. Since a large number of features increase the computational complexity and time, a feature selection technique is employed based on the Bhattacharya distance, to select the set of features that give maximum discrimination between the classes. These set of features are employed to simulate an emotion recognition system. The results indicate a promising emotion detection rate for the three emotions. We also present the early results on detecting the emotion content in the speech and using this in the MAC layer differentiated QoS provisioning scheme. Our scheme provides an end-to-end delay performance improvement for panicked calls as high as 60% compared to normal calls.

Abstract: In this work we present the results of a survey on major challenges in humanitarian logistics. The survey was conducted among logistics managers of relief organizations, logistic service providers, and universities investigating in humanitarian logistics. The following issue areas were consulted: (1) Information and Technology, (2) Processes, Organization, Coordination, (3) Infrastructure, (4) Politics, Government. The results in the first issue area focus mainly on needs for action in the context of the transparency, compatibility, and functionality of IT-systems for humanitarian logistics. The transferability of classical and the establishment of specific concepts of logistics and supply chain management were identified as an important challenge in the second issue area. The need for an improved information situation was noticed within the areas “Infrastructure” and “Politics, Government”. Additionally, it can be highlighted that the assessments of the three questioned groups differ in important points, although a common ground for further research was identified.

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.

Abstract: The Chernobyl nuclear accident made Europe and even the whole world clearly aware of the threats posed by nuclear accidents. When the Fukushima nuclear accident happened in Japan, the “Rush for Salt Affair” took place in some Chinese cities. Meanwhile, large numbers of anti-nuclear parades were held in many Western countries, such as Germany and the United States. Nuclear accidents have a much more serious impact on society than does an ordinary disaster, due both to the nature and characteristics of nuclear accidents, as well as asymmetric in the general public's access to reliable information. By analyzing the mechanisms and characteristics of the impacts on social stability of a nuclear accident, this paper develops a multi-attributes decision making method based on index system of social stability factors in nuclear accident scenarios.

Abstract: The creation of action statistics of fire extinction services is a common activity in the management of forest-fires emergencies. The compilation of action data and the elaboration of statistics based upon those data allow drawing relevant information about forest fires emergencies and fire extinction services. The creation of action statistics requires the exchange of heterogeneous data, with different granularity and detail, among scattered sources. This paper introduces a Forest Fire Report Data Model devoted to be a data reference model for sharing and exchanging forest fire reports in order to achieve syntactic interoperability among independent systems. The definition of the model has been based on the review of forest fire statistics made by different agencies as well as the experience gained in developing an information system, called SIU6, for the creation of action reports of.

Abstract: Mitigating, detecting, evaluating, responding and recovering from crises are highly complex tasks that involve many decision makers (agents). As a consequence using collaborative methods that allow the cooperation among these agents during the crisis management strategy and procedures design is of significant importance. Group Model Building (GMB) is a robust collaborative methodology that has been successfully used for modelling several complex socio-technical problems, where different agents may have diverse perspectives or interests in the problem under analysis. Through the development of a series of exercises, GMB allows the integration of these initially fragmented perspectives. Modellers translate the knowledge elicited from experts during GMB workshops into simulation models that reproduce the behaviour of the problem. This paper presents the use and adaptation of the GMB methodology in a research project about large pan European crises due to outages in the electricity sector.

Abstract: In this contribution we present an analysis of passenger trajectories in an urban transportation hub. We collected an extensive amount of empirical data consisting of both gate and individual stalking observation in the central station of Cologne. Three different data mining algorithms are used to analyze this data, producing both data that may be used as input for simulation frameworks, and, as an aside, visualizations of passenger movements that could be of high interest to transport and emergency managers. © 2012 ISCRAM.

Abstract: Based on a state of the art analysis of exercise classifications and empirical findings from an Action Research approach this paper presents a classification for command post exercises, that addresses identified shortcomings concerning practical support for goal-achievement and evaluation in exercise design. The authors' classification distinguishes between Training, Test and Experimentation Exercises, which are characterized by the following aspects: Goal and purpose of exercise, participants, evaluation content and output, evaluation methodology, role of observers, scenario complexity, potential for organizational innovation and results. The classification was developed in an Action Research approach with an empirical basis of four command post exercises. Results indicate high benefit for exercises and the approach is perceived rather simple, easy to understand and to apply.

Abstract: Natural and man-made hazards may affect industrial production sites by both direct losses (due to physical damage to assets and buildings) and indirect losses (production losses). Indirect losses, e.g. from production downtimes, can exceed direct losses multiple times. Thus, the vulnerability of industrial sectors to indirect losses is an important component of risk and its determination is an important part within risk analysis. In this paper a conceptual indicator framework is presented which allows to assess the indirect vulnerability of industrial sectors to different types of disasters in a quantitative manner. The results are useful for information sharing and decision making in crisis management and emergency planning (mitigation measures, business continuity planning), since the developed indicator system helps to take the complex phenomenon of industrial vulnerability and the underlying interdependencies into account. Besides the identification and conceptual motivation of the indicators, methodical aspects such as standardization, weighting and aggregation are addressed.

Abstract: Many crisis response and recovery efforts require choosing locations in order to deliver needed materials and services. Automated methods can help choose optimal locations for relief camps, field hospitals, command centers, and other critical relief infrastructure. However, current information technology tools for siting relief infrastructure suffer from exposing too much complexity to the user. We are developing a tool, CR-Site, which we hope will serve as an exemplar of an emergency siting tool that eliminates unnecessary complexity, while exposing necessary parameters. In this paper, we describe the technical design and user workflow for CR-Site and provide a case study for the functionality provided by CR-Site. © 2012 ISCRAM.

Abstract: A high level conceptual model is presented of factors hypothesized to be key determinants of the effectiveness of decision making in large scale disasters, grounded in the literature on disaster management. ICT robustness (including the use of social media) sensemaking, and the effectiveness of decision making processes by the multi-organizational Partially Distributed Teams that must cooperate are accorded key roles in the process model. The outcomes of the decision making processes modeled are decisions, in terms of timeliness and quality.

Abstract: Developing key state-wide indicators of Florida's health care system's public health capacity during the H1N1 Pandemic has been challenging. This demonstration outlines work to develop a key indicator of patient surge caused by the H1N1 outbreak. Further work to calibrate this measure and relate it to surge in other health care organizations is outlined.