| Records |
Author  |
Zvonko Grzetic; Nenad Mladineo; Snjezana Knezic |
| Title |
Emergency management systems to accommodate ships in distress |
Type |
Conference Article |
| Year |
2008 |
Publication |
Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2008 |
| Volume |
|
Issue |
|
Pages |
669-678 |
| Keywords |
Artificial intelligence; Civil defense; Decision support systems; Disasters; Geographic information systems; Information systems; Risk management; Decision support system (dss); Dss; Emergency management; Emergency management systems; European Parliament; Model-based OPC; Multi Criteria Analysis; Operational research; Ships |
| Abstract |
As a future member of the European Union (EU), Croatia has decided to implement EU Directive 2002/59/EC of the European Parliament and of the Council binding all EU member states to define places of refuge for ships in need of assistance off their coasts, or to develop techniques for providing assistance to such ships. Consequently, the Ministry of the Sea, Tourism, Transport and Development of the Republic of Croatia has initiated a project for developing an effective Decision Support System (DSS) for defining the places of refuge for ships in distress at sea. Such a system would include a model based upon GIS and different operational research models, which would eventually result in establishing an integral DSS. Starting points for analysis are shipping corridors, and 380 potential locations for places of refuge designated in the official navigational pilot book. Multicriteria analysis, with GIS-generated input data, would be used to establish worthiness of a place of refuge for each ship category, taking into account kinds of accident. Tables of available intervention resources would be made, as well as analysis of their availability in respect of response time, and quantitative and qualitative sufficiency. |
| Address |
Hydrographic Institute of the Republic of Croatia, Zrinsko-Frankopanska 161, 21000 Split, Croatia; University of Split, Faculty of Civil Engineering and Architecture, Matice hrvatske 15, 21000 Split, Croatia |
| Corporate Author |
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Thesis |
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| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Washington, DC |
Editor |
F. Fiedrich, B. Van de Walle |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9780615206974 |
Medium |
|
| Track |
Visualization and Smart Room Technology for Decision Making, Information Sharing, and Collaboration |
Expedition |
|
Conference |
5th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
551 |
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| Author |
Yasir Javed; Tony Norris; David Johnston |
| Title |
Design approach to an emergency decision support system for mass evacuation |
Type |
Conference Article |
| Year |
2010 |
Publication |
ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings |
Abbreviated Journal |
ISCRAM 2010 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Decision support systems; Design; Information science; Information systems; Ontology; Volcanoes; Edss; Emergency; Emergency decision makings; Emergency decision support; Evacuation; Human system interface; Information needs; Volcanic eruptions; Artificial intelligence |
| Abstract |
This paper is directed primarily to investigating the information needs of emergency managers following recognition of a risk of volcanic eruption. These needs include type of information required during the collection, integration, synthesis, presentation, and sharing of information. This will identify and model the processes underpinning the design of an emergency decision support system (EDSS). Exploration of the information needs, flows, and processes involved in emergency decision making can improve the design of EDSS both in terms of their content and the all-important human-system interfaces that determine their usability.The information attributes and flows then lead to the development of a prototype system that can be evaluated to test and refine the concepts. |
| Address |
Institute of Information and Mathematical Sciences, Massey University, Auckland, New Zealand; Joint Centre of Disaster Research, Massey University, Wellington, New Zealand |
| Corporate Author |
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Thesis |
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| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Seattle, WA |
Editor |
S. French, B. Tomaszewski, C. Zobel |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
|
Series Title |
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Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
|
Medium |
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| Track |
Poster Session |
Expedition |
|
Conference |
7th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
622 |
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| Author |
Xiang Yao; Murray Turoff |
| Title |
Using task structure to improve Collaborative Scenario Creation |
Type |
Conference Article |
| Year |
2007 |
Publication |
Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers |
Abbreviated Journal |
ISCRAM 2007 |
| Volume |
|
Issue |
|
Pages |
591-594 |
| Keywords |
Artificial intelligence; Decision support systems; Collaborative Scenario Creation; Creation process; Design tasks; Entity-relationship; Modeling methodology; Task structure; Design |
| Abstract |
This paper provides a task structure design for collaborative scenario elicitation. Task structure design is part of this effort to design a new Collaborative Scenario Creation (CSC) system. The complexity of the scenario creation process hinders participants, especially novice participants, from prudently designing scenarios. Research in Group Decision Support Systems (GDSS) shows that task structure helps to improve processes and collaborations. To design task structure for collaborative scenario elicitation, this paper invokes the Entity-Relationship data modeling methodology. |
| Address |
New Jersey Institute of Technology, United States |
| Corporate Author |
|
Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Delft |
Editor |
B. Van de Walle, P. Burghardt, K. Nieuwenhuis |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9789054874171; 9789090218717 |
Medium |
|
| Track |
CSE |
Expedition |
|
Conference |
4th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
1125 |
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| Author |
Wolfgang Raskob; Valentin Bertsch; Jutta Geldermann.; Sandra Baig; Florian Gering |
| Title |
Demands to and experience with the decision support system rodos for off-site emergency management in the decision making process in Germany |
Type |
Conference Article |
| Year |
2005 |
Publication |
Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2005 |
| Volume |
|
Issue |
|
Pages |
269-278 |
| Keywords |
Accidents; Civil defense; Decision making; Decision support systems; Disasters; Information systems; Risk management; Sensitivity analysis; Decision making process; Emergency management; Emergency situation; Integrated evaluation; Multi-criteria decision analysis; Multi-criteria evaluation; Radiological accidents; Stakeholder involvement; Artificial intelligence |
| Abstract |
Emergency situations, man-made as well as natural, can differ considerably. However, they share the characteristic of sudden onset, involve complex decisions and necessitate a coherent and effective emergency management. In the event of a nuclear or radiological accident in Europe, the real-time on-line decision support system RODOS provides support from the early phase through to the medium and long-term phases. This paper describes the demands to a Decision Support System from a user-centred view as well as experiences gained from conducting moderated decision making workshops based on a hypothetical accident scenario focusing on the evaluation of long-term countermeasures using the simulation capabilities of the RODOS system and its recently integrated evaluation component Web-HIPRE, a tool for multi-criteria decision analysis (MCDA). |
| Address |
Forschungszentrum Karlsruhe (FZK), IKET, Karlsruhe, Germany; University of Karlsruhe (TH), DFIU, Karlsruhe, Germany; Federal Office for Radiation Protection (BfS), Germany |
| Corporate Author |
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Thesis |
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| Publisher |
Royal Flemish Academy of Belgium |
Place of Publication |
Brussels |
Editor |
B. Van de Walle, B. Carle |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9076971099 |
Medium |
|
| Track |
NUCLEAR EMERGENCY MANAGEMENT |
Expedition |
|
Conference |
2nd International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
869 |
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| Author |
Wolfgang Raskob; Florian Gering; Valentin Bertsch |
| Title |
Approaches to visualisation of uncertainties to decision makers in an operational decision support system |
Type |
Conference Article |
| Year |
2009 |
Publication |
ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives |
Abbreviated Journal |
ISCRAM 2009 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Artificial intelligence; Decision support systems; Information systems; Risk management; Visualization; Agricultural management; Decision making process; Operational decision support; Radiological emergency; Rodos; Uncertain informations; Uncertainties; Uncertainty handling; Decision making |
| Abstract |
Decision making in case of any emergency is associated with uncertainty of input data, model data and changing preferences in the decision making process. Uncertainty handling was from the beginning an integral part of the decision support system RODOS for the off-site emergency management following nuclear or radiological emergencies. What is missing so far is the visualisation of the uncertainties in the results of the model calculations. In this paper we present the first attempt to visualise uncertain information in the early and late phase of the decision making process. For the early phase, the area of sheltering was selected as example. For the later phase, the results of the evaluation subsystem of RODOS were selected being used for the analysis of remediation measures such as agricultural management options. Both attempts are still under discussion but the presentation of the early phase uncertainty will be realised in the next version. |
| Address |
Forschungszentrum Karlsruhe (FZK), Karlsruhe, Germany; Federal Office for Radiation Protection, Neuherberg, Germany; Karlsruhe Institute of Technology, Karlsruhe, Germany |
| Corporate Author |
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Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Gothenburg |
Editor |
J. Landgren, S. Jul |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9789163347153 |
Medium |
|
| Track |
Open Track |
Expedition |
|
Conference |
6th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
870 |
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| Author |
Tsai, C.-H.; Rayi, P.; Kadire, S.; Wang, Y.-F.; Krafka, S.; Zendejas, E.; Chen, Y.-C. |
| Title |
Co-Design Disaster Management Chatbot with Indigenous Communities |
Type |
Conference Article |
| Year |
2023 |
Publication |
Proceedings of the 20th International ISCRAM Conference |
Abbreviated Journal |
Iscram 2023 |
| Volume |
|
Issue |
|
Pages |
1-12 |
| Keywords |
Native American; Emergency Management; Artificial intelligence; Conversational Agent; Human-Centered Computing |
| Abstract |
Indigenous communities are disproportionately impacted by rising disaster risk, climate change, and environmental degradation due to their close relationship with the environment and its resources. Unfortunately, gathering the necessary information or evidence to request or co-share sufficient funds can be challenging for indigenous people and their lands. This paper aims to co-design an AI-based chatbot with two tribes and investigate their perception and experience of using it in disaster reporting practices. The study was conducted in two stages. Firstly, we interviewed experienced first-line emergency managers and invited tribal members to an in-person design workshop. Secondly, based on qualitative analysis, we identified three themes of emergency communication, documentation, and user experience. Our findings support that indigenous communities favored the proposed Emergency Reporter chatbot solution. We further discussed how the proposed chatbot could empower the tribes in disaster management, preserve sovereignty, and seek support from other agencies. |
| Address |
Technical University of Darmstadt |
| Corporate Author |
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Thesis |
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| Publisher |
University of Nebraska at Omaha |
Place of Publication |
Omaha, USA |
Editor |
Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi |
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
Hosssein Baharmand |
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
1 |
| ISSN |
|
ISBN |
|
Medium |
|
| Track |
Usability and Universal Design of ICT for Emergency Management |
Expedition |
|
Conference |
|
| Notes |
http://dx.doi.org/10.59297/RZLJ7481 |
Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2501 |
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| Author |
Tim A. Majchrzak; Oliver Noack; Herbert Kuchen; Philipp Neuhaus; Frank Ückert |
| Title |
Towards a decision support system for the allocation of traumatized patients |
Type |
Conference Article |
| Year |
2010 |
Publication |
ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings |
Abbreviated Journal |
ISCRAM 2010 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Artificial intelligence; Information systems; Business rules; Crisis management; Development project; IT system; Patient dispatching; Related works; Traumatized patients; Decision support systems |
| Abstract |
We present a decision support system for the allocation of traumatized patients. The assignment of patients to vehicles and hospitals is a task that requires detailed up-to-date information but has to be carried out quickly. We pro-pose to support medical staff with an IT system. We especially encourage such a system to be used in cases of mass incidents as it is very problematic – yet essential – To provide all injured with adequate healthcare as fast as possible. Our proposal is a system based on business rules. In this paper we describe the development project's background as well as the system's requirements and some details of its implementation. Moreover, we explain an exemplary scenario to show strengths of our approach. Besides discussing related work, we draw an overview of future tasks. |
| Address |
Department of Information Systems, University of Muenster, Germany; Department of Medical Informatics, University Hospital Muenster, Germany |
| Corporate Author |
|
Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Seattle, WA |
Editor |
S. French, B. Tomaszewski, C. Zobel |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
|
Medium |
|
| Track |
Geo-Information Support |
Expedition |
|
Conference |
7th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
738 |
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| Author |
Stephen Potter; Yannis Kalfoglou; Harith Alani; Michelle Bachler; Simon Buckingham Shum; Rodrigo Carvalho; Ajay Chakravarthy; Stuart Chalmers; Sam Chapman; Beibei Hu; Alun Preece; Nigel Shadbolt; Austin Tate; Mischa Tuffield |
| Title |
The application of advanced knowledge technologies for emergency response |
Type |
Conference Article |
| Year |
2007 |
Publication |
Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers |
Abbreviated Journal |
ISCRAM 2007 |
| Volume |
|
Issue |
|
Pages |
361-368 |
| Keywords |
Artificial intelligence; Decision support systems; Decision supports; Emergency response; Intelligent messaging; Semantic technologies; Sensemaking; Emergency services |
| Abstract |
Making sense of the current state of an emergency and of the response to it is vital if appropriate decisions are to be made. This task involves the acquisition, interpretation and management of information. In this paper we present an integrated system that applies recent ideas and technologies from the fields of Artificial Intelligence and semantic web research to support sense-and decision-making at the tactical response level, and demonstrate it with reference to a hypothetical large-scale emergency scenario. We offer no end-user evaluation of this system; rather, we intend that it should serve as a visionary demonstration of the potential of these technologies for emergency response. |
| Address |
University of Edinburgh, United Kingdom; University of Southampton, United Kingdom; Open University, United Kingdom; University of Sheffield, United Kingdom; University of Aberdeen, United Kingdom |
| Corporate Author |
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Thesis |
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| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Delft |
Editor |
B. Van de Walle, P. Burghardt, K. Nieuwenhuis |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
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Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9789054874171; 9789090218717 |
Medium |
|
| Track |
ASCM |
Expedition |
|
Conference |
4th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
852 |
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| Author |
Stephen Potter; Gerhard Wickler |
| Title |
Model-based query systems for emergency response |
Type |
Conference Article |
| Year |
2008 |
Publication |
Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2008 |
| Volume |
|
Issue |
|
Pages |
495-503 |
| Keywords |
Artificial intelligence; Information systems; Models; Advanced sensors; Command-and-control; Emergency responders; Emergency response; Fire emergencies; General architectures; Grid technologies; Query systems; Emergency services |
| Abstract |
In this paper we describe the approach adopted and experiences gained during a project to develop a general architecture that aims to harness advanced sensor, modelling and Grid technologies to assist emergency responders in tackling emergencies (specifically fire emergencies). Here we focus on the command and control aspects of this architecture, and in particular, on a query-based approach that has been adopted to allow end users to interact with available models of physical and other phenomena. The development of this has provided a number of insights about the use of such models, which along with the approach itself, should be of interest to any considering similar applications. |
| Address |
AIAI, School of Informatics, University of Edinburgh, United Kingdom |
| Corporate Author |
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Thesis |
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| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Washington, DC |
Editor |
F. Fiedrich, B. Van de Walle |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
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Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9780615206974 |
Medium |
|
| Track |
Intelligent Systems for Crisis and Disaster Management |
Expedition |
|
Conference |
5th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
851 |
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| Author |
Stella Moehrle |
| Title |
Generic self-learning decision support system for large-scale disasters |
Type |
Conference Article |
| Year |
2012 |
Publication |
ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2012 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Artificial intelligence; Decision making; Decision support systems; Disaster prevention; Disasters; Information systems; Complex structure; Decision makers; Decision making process; Decision process; Disaster management; Emergency response; Large-scale disasters; Work in progress; Emergency services |
| Abstract |
Large-scale disasters, particularly failures of critical infrastructures, are exceptional situations which cannot be solved with standard countermeasures. The crises are complex and the decision makers face acute time pressure to respond to the disaster. IT based decision support systems provide potential solutions and assist the decision making process. Many decision support systems in emergency response and management concentrate on one kind of disaster. Moreover, complex structures are modeled and recommendations are made rule-based. This work in progress paper describes the first steps towards the development of a generic and self-learning decision support system. The methodology used is case-based reasoning. The paper concludes with a sample emergency decision process. © 2012 ISCRAM. |
| Address |
Institute for Nuclear and Energy Technologies, Karlsruhe Institute of Technology, Germany |
| Corporate Author |
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Thesis |
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| Publisher |
Simon Fraser University |
Place of Publication |
Vancouver, BC |
Editor |
L. Rothkrantz, J. Ristvej, Z.Franco |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9780864913326 |
Medium |
|
| Track |
Track Decision Support Methods for Complex Crises |
Expedition |
|
Conference |
9th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
171 |
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| Author |
Stella Moehrle |
| Title |
On the assessment of disaster management strategies |
Type |
Conference Article |
| Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
| Volume |
|
Issue |
|
Pages |
215-219 |
| Keywords |
Artificial intelligence; Decision support systems; Disaster prevention; Information systems; Case based reasoning systems; Decision makers; Disaster management; Disasters |
| Abstract |
Decision support systems can recommend strategies for disaster management, which can be further discussed by decision-makers. To provide rationales for the recommendations, the strategies need to be assessed according to relevant criteria. If several strategies are available, the criteria can be used for ranking the strategies. This paper addresses the issue concerning the choice of suitable criteria from several perspectives. The assessment integrates concepts on robustness, experience with regard to the implementation of a strategy, quantifiable ratios which can be deduced from simulations, and system-specific parameters. Objectives are to facilitate transparency with respect to the assessments, to provide a basis for discussions concerning the strategies, and to preserve adaptability and flexibility to account for the variability of disasters and users' preferences. The assessment should be used for ranking solutions gained from a case-based reasoning system and to reveal contributions of criteria values to the overall assessment. |
| Address |
Institute for Nuclear and Energy Technologies, Karlsruhe Institute of Technology, Germany |
| Corporate Author |
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Thesis |
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| Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
|
Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9780692211946 |
Medium |
|
| Track |
Decision Support Systems |
Expedition |
|
Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
776 |
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| Author |
Stella Moehrle |
| Title |
Modeling of countermeasures for large-scale disasters using high-level petri nets |
Type |
Conference Article |
| Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
| Volume |
|
Issue |
|
Pages |
284-289 |
| Keywords |
Artificial intelligence; Decision support systems; Disaster prevention; Information systems; Petri nets; Automatic processing; Disaster management; Generic approach; Generic decisions; High-level Petri nets; Large-scale disasters; Disasters |
| Abstract |
In order to support decision-making in large-scale disasters, IT-based decision support systems provide appropriate countermeasures to respond to the event. For the implementation of measures, logical and temporal dependencies have to be considered. Furthermore, factors influencing the choice of measures should be taken into account. This paper presents a generic approach to modeling sequences of countermeasures using Highlevel Petri Nets including information about the influencing factors and endangered objects. Moreover, an approach to combining several nets is proposed, which establish new sequences for recommendation. The research is part of the development of a generic decision support system for large-scale disasters. Consequently, the focus is on modeling in a generic manner and on automatic processing. |
| Address |
Institute for Nuclear and Energy Technologies, Germany |
| Corporate Author |
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Thesis |
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| Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
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Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
|
| Track |
Decision Support Systems |
Expedition |
|
Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
777 |
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| Author |
Soudip Roy Chowdhury; Muhammad Imran; Muhammad Rizwan Asghar; Amer-Yahia, S.; Carlos Castillo |
| Title |
Tweet4act: Using incident-specific profiles for classifying crisis-related messages |
Type |
Conference Article |
| Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
| Volume |
|
Issue |
|
Pages |
834-839 |
| Keywords |
Artificial intelligence; Disaster prevention; Classification methods; Crisis informatics; Disaster management; Micro-blogging platforms; Microblogging; Precision and recall; Standard machines; Twitter data-analytics; Information systems |
| Abstract |
We present Tweet4act, a system to detect and classify crisis-related messages communicated over a microblogging platform. Our system relies on extracting content features from each message. These features and the use of an incident-specific dictionary allow us to determine the period type of an incident that each message belongs to. The period types are: Pre-incident (messages talking about prevention, mitigation, and preparedness), during-incident (messages sent while the incident is taking place), and post-incident (messages related to the response, recovery, and reconstruction). We show that our detection method can effectively identify incident-related messages with high precision and recall, and that our incident-period classification method outperforms standard machine learning classification methods. |
| Address |
University of Trento, Italy; Fehler Textmarke Nicht Definiert, University of Trento, Italy; CNRS, LIG, France; QCRI, Doha, Qatar |
| Corporate Author |
|
Thesis |
|
| Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
|
| Track |
Social Media |
Expedition |
|
Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
396 |
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| |
| Author |
Simone De Kleermaeker; Jan Verkade |
| Title |
A decision support system for effective use of probability forecasts |
Type |
Conference Article |
| Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
| Volume |
|
Issue |
|
Pages |
290-295 |
| Keywords |
Artificial intelligence; Decision support systems; Forecasting; Hydrology; Information systems; Uncertainty analysis; Water management; Decision support system (dss); Hydrological forecast; Management decisions; Multidimensional problems; Predictive uncertainty; Probabilistic forecasts; Probability forecasts; Risk-based decisions; Decision making |
| Abstract |
Often, water management decisions are based on hydrological forecasts, which are affected by inherent uncertainties. It is increasingly common for forecasters to make explicit estimates of these uncertainties. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a more strict separation of responsibilities between forecasters and decision maker can be made. A recent study identified some issues related to the effective use of probability forecasts. These add a dimension to an already multi-dimensional problem, making it increasingly difficult for decision makers to extract relevant information from a forecast. Secondly, while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be fully known, including estimates of flood damage and costs and effect of damage reducing measures. Here, we present suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development is outlined. |
| Address |
Deltares, Delft, Netherlands; Water Management Centre of Netherlands, Ministry of Infrastructure and the Environment, Storm Surge Forecasting Service, Lelystad, Netherlands; Delft University of Technology, Delft, Netherlands |
| Corporate Author |
|
Thesis |
|
| Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9783923704804 |
Medium |
|
| Track |
Decision Support Systems |
Expedition |
|
Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
432 |
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| |
| Author |
Simon French; Carmen Niculae |
| Title |
Believe in the model: Mishandle the emergency |
Type |
Conference Article |
| Year |
2004 |
Publication |
Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2004 |
| Volume |
|
Issue |
|
Pages |
9-14 |
| Keywords |
Artificial intelligence; Civil aviation; Civil defense; Decision making; Decision support systems; Disasters; Forecasting; Information systems; Risk management; Crisis management; Cynefin; Decision support system (dss); Emergency management; Model prediction; Uncertainty; Economic and social effects |
| Abstract |
During the past quarter century there have been many developments in scientific models and computer codes to help predict the ongoing consequences in the aftermath of many types of emergency: e.g. storms and flooding, chemical and nuclear accident, epidemics such as SARS and terrorist attack. Some of these models relate to the immediate events and can help in managing the emergency; others predict longer term impacts and thus can help shape the strategy for the return to normality. But there are many pitfalls in the way of using these models effectively. Firstly, non-scientists and, sadly, many scientists believe in the models' predictions too much. The inherent uncertainties in the models are underestimated; sometimes almost unacknowledged. This means that initial strategies may need to be revised in ways that unsettle the public, losing their trust in the emergency management process. Secondly, the output from these models form an extremely valuable input to the decision making process; but only one such input. Most emergencies are events that have huge social and economic impacts alongside the health and environmental consequences. While we can model the latter passably well, we are not so good at modelling economic impacts and very poor at modelling social impacts. Too often our political masters promise the best 'science-based' decision making and too late realise that the social and economic impacts need addressing. In this paper, we explore how model predictions should be drawn into emergency management processes in more balanced ways than often has occurred in the past. © Proceedings ISCRAM 2004. |
| Address |
Manchester Business School, University of Manchester, Booth Street West, Manchester M15 6PB, United Kingdom |
| Corporate Author |
|
Thesis |
|
| Publisher |
Royal Flemish Academy of Belgium |
Place of Publication |
Brussels |
Editor |
B. Van de Walle, B. Carle |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9076971080 |
Medium |
|
| Track |
Conference Keynote |
Expedition |
|
Conference |
1st International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
111 |
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| Author |
Rianne Gouman; Masja Kempen; Niek Wijngaards |
| Title |
Actor-agent team experimentation in the context of incident management |
Type |
Conference Article |
| Year |
2010 |
Publication |
ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings |
Abbreviated Journal |
ISCRAM 2010 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Artificial intelligence; Human resource management; Information systems; Intelligent agents; Actor-agent teaming; Artificial intelligent; Comparative experiments; Empirical research method; Experimentation; Performance indicators; Simulation; Simulation toolkits; Experiments |
| Abstract |
The collaboration between humans (actors) and artificial entities (agents) can be a potential performance boost. Agents, as complementary artificial intelligent entities, can alleviate actors from certain activities, while enlarging the collective effectiveness. This paper describes our approach for experimentation with actors, agents and their interaction. This approach is based on a principled combination of existing empirical research methods and is illustrated by a small experiment which assesses the performance of a specific actor-agent team in comparison with an actor-only team in an incident management context. The REsearch and Simulation toolKit (RESK) is instrumental for controlled and repeatable experimentation. The indicative findings show that the approach is viable and forms a basis for further data collection and comparative experiments. The approach supports applied actor-agent research to show its (dis)advantages as compared to actor-only solutions. |
| Address |
D-CIS Lab, Thales Research and Technology NL, Netherlands |
| Corporate Author |
|
Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Seattle, WA |
Editor |
S. French, B. Tomaszewski, C. Zobel |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
|
Medium |
|
| Track |
Research Methods |
Expedition |
|
Conference |
7th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
539 |
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| |
| Author |
Rene Windhouwer; Gerdien A. Klunder; F.M. Sanders |
| Title |
Decision support system emergency planning, creating evacuation strategies in the event of flooding |
Type |
Conference Article |
| Year |
2005 |
Publication |
Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2005 |
| Volume |
|
Issue |
|
Pages |
171-180 |
| Keywords |
Artificial intelligence; Behavioral research; Decision support systems; Disaster prevention; Disasters; Information systems; Oil well flooding; Risk perception; Traffic control; Decision support system (dss); Decision supports; Emergency planning; Evacuation; Evacuation strategy; Extreme weather; River flooding; Traffic flow; Floods |
| Abstract |
The Decision Support System (DSS) Emergency Planning is designed for use in the event of sea or river flooding. It makes accessible all the information related to the decision whether to evacuate an area. An important factor in this decision is the time required for the evacuation. The model used by the DSS Emergency Planning system to estimate the time required employs a strategy that prevents congestion on the road network in the area at risk. The use of the DSS Emergency Planning system during the proactive and prevention phases enables disaster containment organisations to prepare better for a flood situation. Moreover, all relevant information is saved and is therefore available for the post-disaster evaluation. The DSS Emergency Planning system can play a significant role in ensuring that the evacuation of an area at risk goes according to plan. In the future the DSS Emergency Planning system can also be used to evacuate people in the event of a nuclear, natural fire or extreme weather disaster. |
| Address |
Ingenieursbureau Oranjewoud, Netherlands; TNO Inro, Netherlands |
| Corporate Author |
|
Thesis |
|
| Publisher |
Royal Flemish Academy of Belgium |
Place of Publication |
Brussels |
Editor |
B. Van de Walle, B. Carle |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9076971099 |
Medium |
|
| Track |
DECISION SUPPORT SYSTEMS |
Expedition |
|
Conference |
2nd International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
1094 |
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| Author |
Rego Granlund; Helena Granlund |
| Title |
GPS impact on performance, response time and communication – A review of three studies |
Type |
Conference Article |
| Year |
2011 |
Publication |
8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 |
Abbreviated Journal |
ISCRAM 2011 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Artificial intelligence; Decision making; Decision support systems; Global positioning system; Information systems; Tracking (position); Command posts; Controlled experiment; Crisis management; Decision makers; Decision supports; Service personnel; University students; Work performance; Human resource management |
| Abstract |
This paper describes the basic work performance analysis from three research projects with a goal to investigate the impact of a decision support system that presents global positioning system (GPS) information to the decision makers in crisis management organizations. The goal was to compare the performance between teams that had access to GPS information in the command post with teams that had access only to paper maps. The method used was controlled experiments with the C3Fire micro-world. A total of 304 participants, forming 48 teams, participated in the three studies. The participants came from three different groups, university students, municipal crisis management organizations and rescue service personnel. The result shows that the performance and communication change depending on if the teams used GPS support or paper maps. The result also shows that the participants' background and perceived complexity of the task have an impact on the results. |
| Address |
Santa Anna IT Research Institute, Swedish Defence Research Agency, Linköping, Sweden |
| Corporate Author |
|
Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Lisbon |
Editor |
M.A. Santos, L. Sousa, E. Portela |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9789724922478 |
Medium |
|
| Track |
Advanced Research Methods and Unconventional Results |
Expedition |
|
Conference |
8th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
543 |
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| Author |
Qing Gu; David Mendonça |
| Title |
Patterns of group information-seeking in a simulated emergency response environment |
Type |
Conference Article |
| Year |
2005 |
Publication |
Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2005 |
| Volume |
|
Issue |
|
Pages |
109-116 |
| Keywords |
Artificial intelligence; Decision support systems; Information retrieval; Information systems; Information use; Emergency response; Emergency situation; Expertise; Information seeking; Information seeking behaviors; Emergency services |
| Abstract |
Groups in emergency response environment may be confronted with problems that cannot be solved by following predefined procedures. They must therefore engage in a collective search for relevant information, cooperating and collaborating as they move towards the deadline. Information technologies and expertise may help shape group information seeking and determine its effectiveness. By understanding how response personnel search for information in emergencies and extending the findings to determine demands on information systems, we may begin to understand how to support and train for skillful information seeking in emergency situations. Accordingly, this research evaluates the impact of decision support systems and member expertise on group information-seeking behavior in a simulated emergency response environment. The results of the evaluation are then used to identify how information technologies may further support information seeking in emergency response. |
| Address |
Information Systems Department, New Jersey Institute of Technology, Newark, NJ, United States |
| Corporate Author |
|
Thesis |
|
| Publisher |
Royal Flemish Academy of Belgium |
Place of Publication |
Brussels |
Editor |
B. Van de Walle, B. Carle |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9076971099 |
Medium |
|
| Track |
RESEARCH METHODS |
Expedition |
|
Conference |
2nd International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
552 |
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| Author |
Peter Serwylo; Paul Arbon; Grace Rumantir |
| Title |
Predicting patient presentation rates at mass gatherings using machine learning |
Type |
Conference Article |
| Year |
2011 |
Publication |
8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 |
Abbreviated Journal |
ISCRAM 2011 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Artificial intelligence; Data mining; Forecasting; Information systems; Event Types; Heat indices; Machine learning techniques; Mass gathering; Optimization techniques; Predictive models; Predictive variables; Time of day; Learning systems |
| Abstract |
Mass gatherings have been defined as events where more than 1,000 people are present for a defined period of time. Such an event presents specific challenges with respect to medical care. First aid is provisioned on-site at most events in order to prevent undue strain on the local emergency services. In order to allocate enough resources to deal with the expected injuries, it is important to be able to accurately predict patient volumes. This study used machine learning techniques to identify which variables are the most important in predicting patient volumes at mass gatherings. Data from 201 mass gatherings across Australia was analysed, finding that event type is the most predictive variable, followed by the state or territory, heat index, humidity, whether it is bounded, and the time of day. Variables with little bearing on the outcome included the presence of alcohol, whether the event was indoors or outdoors, and whether it had one point of focus. The best predictive models produced acceptable predictions of the patient presentations 80% of the time, and this could be further improved using optimization techniques. |
| Address |
Monash University, Australia; Flinders University, Australia |
| Corporate Author |
|
Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Lisbon |
Editor |
M.A. Santos, L. Sousa, E. Portela |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9789724922478 |
Medium |
|
| Track |
Planning and Foresight |
Expedition |
|
Conference |
8th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
938 |
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| Author |
Peng Xia; Ji Ruan; Dave Parry; Jian Yu; Sally Britnell |
| Title |
Enhancing Triage Training for Mass Casualty Incidents with Virtual Reality and Artificial Intelligence |
Type |
Conference Article |
| Year |
2023 |
Publication |
Proceedings of the ISCRAM Asia Pacific Conference 2022 |
Abbreviated Journal |
Proc. ISCRAM AP 2022 |
| Volume |
|
Issue |
|
Pages |
68-76 |
| Keywords |
Mass Casualty Incidents; Triage Training; Virtual Reality; Artificial Intelligence |
| Abstract |
Mass casualty incidents (MCIs) occur with natural or man-made disasters. Training emergency staff for combating MCIs is essential, but the cost can be high as such incidents rarely occur, and a physical simulation is resource-intensive. Triage is a critical task in dealing with MCIs. In this paper, we propose to use Virtual Reality (VR) and Artificial Intelligence (AI) technologies to build a low-cost, high-efficient system for MCI triage training. Our system captures more comprehensive training data and utilizes state-of-the-art AI evaluation methods. |
| Address |
Auckland University of Technology; Auckland University of Technology; Murdoch University; Auckland Unviversity of Technology; Auckland University of Technology |
| Corporate Author |
|
Thesis |
|
| Publisher |
Massey Unversity |
Place of Publication |
Palmerston North, New Zealand |
Editor |
Thomas J. Huggins, V.L. |
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Track |
Practitioners Track |
Expedition |
|
Conference |
|
| Notes |
|
Approved |
no |
| Call Number |
ISCRAM @ idladmin @ |
Serial |
2481 |
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| Author |
Oduor Erick Nelson Otieno; Anna Gryszkiewicz; Nihal Siriwardanegea; Fang Chen |
| Title |
Concept for intelligent integrated system for crisis management |
Type |
Conference Article |
| Year |
2010 |
Publication |
ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings |
Abbreviated Journal |
ISCRAM 2010 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Artificial intelligence; Decision support systems; Information systems; Cell phone; Crisis management; Integrated systems; Intelligent decision support; Significant points; Standalone applications; Support systems; User friendly interface; Decision making |
| Abstract |
In this document, we describe the need for providing a uniform common picture that is missing in several crisis management decision support tools. Through research, we have reviewed some existing crisis management support systems in use and noted key user requirements that these tools are missing. A significant point of this research is to stress the importance of developing a decision support system that would improve the way an ideal support system would collect, analyze and disseminate necessary information to a crisis management decision maker. We also note the importance of ensuring that such a tool presents information to its user over a user friendly interface. The structure thus developed should be a standalone application that could be incorporated into existing platforms (Rinkineva, 2004) such as cell phones, PDAs and laptops. |
| Address |
Chalmers Institute of Technology, Sweden; Chalmers Institute of Technology, Computer Science and Engineering, Sweden |
| Corporate Author |
|
Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Seattle, WA |
Editor |
S. French, B. Tomaszewski, C. Zobel |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
|
Medium |
|
| Track |
Intelligent Systems |
Expedition |
|
Conference |
7th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
820 |
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| Author |
Niels Netten; Maarten Van Someren |
| Title |
Automated support for dynamic information distribution in incident management |
Type |
Conference Article |
| Year |
2006 |
Publication |
Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2006 |
| Volume |
|
Issue |
|
Pages |
230-237 |
| Keywords |
Artificial intelligence; Information systems; Adaptive information; Automated support; Dynamic information; Emergency response personnels; Group communications; Incident Management; Machine learning methods; Simulated experiments; Learning systems |
| Abstract |
For all emergency response personnel involved in crisis situations it is essential to timely acquire all information critical to their task performance. However, in practice errors occur in the distribution of information between these collaborating actors leading to mistakes and subsequently more damage to the situation. In this paper we present a prototype system for dynamic information distribution able to support the information flow between collaborating crisis actors. The system has been evaluated by means of simulated experiments that use data from a real incident scenario. The results indicate that automated support by means of Machine Learning method works well. Especially, when actor work context features are included, then the performance on selecting and distributing relevant information is high. Furthermore, actors acquire relevant information much faster making group communication much more efficient. |
| Address |
Human-Computer Studies Laboratory, Informatics Institute, University of Amsterdam (UvA), Netherlands |
| Corporate Author |
|
Thesis |
|
| Publisher |
Royal Flemish Academy of Belgium |
Place of Publication |
Newark, NJ |
Editor |
B. Van de Walle, M. Turoff |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9090206019; 9789090206011 |
Medium |
|
| Track |
COMMAND AND CONTROL |
Expedition |
|
Conference |
3rd International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
807 |
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| Author |
Nan Zhang; Clare Bayley; Simon French |
| Title |
Use of web-based group decision support for crisis management |
Type |
Conference Article |
| Year |
2008 |
Publication |
Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2008 |
| Volume |
|
Issue |
|
Pages |
55-58 |
| Keywords |
Artificial intelligence; Information systems; Websites; Collaboration; Crisis management; Crisis situations; Distributed decision making; Group decision supports; Small-scale experiment; Web-based group decision support system (wGDSS); Decision support systems |
| Abstract |
Web-based group decision support systems (wGDSS) are becoming more common in organizations. In this paper, we provide a review and critique of the literature on wGDSS, raising a number of issues that need addressing. Then we report on a small scale experiment using Groupsystems ThinkTank to manage an issue to do with food safety. We also describe how we propose to use ThinkTank in a crisis situation. |
| Address |
Manchester Business School, United Kingdom |
| Corporate Author |
|
Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Washington, DC |
Editor |
F. Fiedrich, B. Van de Walle |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9780615206974 |
Medium |
|
| Track |
Social Networking, Web Collaboration and e Participation in Crisis and Risk Managements |
Expedition |
|
Conference |
5th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
1146 |
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| Author |
Muhammad Imran; Shady Elbassuoni; Carlos Castillo; Fernando Díaz; Patrick Meier |
| Title |
Extracting information nuggets from disaster- Related messages in social media |
Type |
Conference Article |
| Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
| Volume |
|
Issue |
|
Pages |
791-801 |
| Keywords |
Artificial intelligence; Data visualization; Disasters; Information retrieval; Information systems; Learning systems; Social networking (online); Emergency responders; Extracting information; Machine learning methods; Situational awareness; Social media; Supervised classification; Twitter; Visualization system; Emergency services |
| Abstract |
Microblogging sites such as Twitter can play a vital role in spreading information during “natural” or man-made disasters. But the volume and velocity of tweets posted during crises today tend to be extremely high, making it hard for disaster-affected communities and professional emergency responders to process the information in a timely manner. Furthermore, posts tend to vary highly in terms of their subjects and usefulness; from messages that are entirely off-topic or personal in nature, to messages containing critical information that augments situational awareness. Finding actionable information can accelerate disaster response and alleviate both property and human losses. In this paper, we describe automatic methods for extracting information from microblog posts. Specifically, we focus on extracting valuable “information nuggets”, brief, self-contained information items relevant to disaster response. Our methods leverage machine learning methods for classifying posts and information extraction. Our results, validated over one large disaster-related dataset, reveal that a careful design can yield an effective system, paving the way for more sophisticated data analysis and visualization systems. |
| Address |
University of Trento, Italy; American Univ. of Beirut, Lebanon; QCRI, Qatar; Microsoft Research, Qatar |
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| Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language |
English |
Summary Language |
English |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
9783923704804 |
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| Track |
Social Media |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
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Serial |
613 |
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