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Author (up) Abhish Khanal; Deepak Chand; Prakash Chaudhary; Subash Timilsina; Sanjeeb Prasad Panday; Aman Shakya; Rom Kant Pandey pdf  isbn
openurl 
  Title Search Disaster Victims using Sound Source Localization Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 1022-1030  
  Keywords Sound Source Localization (SSL); Omni-Directional Drive; Disaster Victim; Generalized Cross Correlation Phase Transform (GCC-PHAT)  
  Abstract Sound Source Localization (SSL) are used to estimate the position of sound sources. Various methods have been used for detecting sound and its localization. This paper presents a system for stationary sound source localization by cubical microphone array consisting of eight microphones placed on four vertical adjacent faces which is mounted on three wheel omni-directional drive for the inspection and monitoring of the disaster victims in disaster areas. The proposed method localizes sound source on a 3D space by grid search method using Generalized Cross Correlation Phase Transform (GCC-PHAT) which is robust when operating in real life scenario where there is lack of visibility. The computed azimuth and elevation angle of victimized human voice are fed to embedded omni-directional drive system which navigates the vehicle automatically towards the stationary sound source.  
  Address Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Institute of Engineering, Pulchowk Campus; Sanothimi Campus, Tribhuvan University  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-92 ISBN 2411-3478 Medium  
  Track Usability and Universal Design of ICT for Emergency Management Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes 072bex402@ioe.edu.np Approved no  
  Call Number Serial 2293  
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Author (up) Aditya Irfansyah; Adam Widera; Mark Haselkorn; Bernd Hellingrath pdf  isbn
openurl 
  Title Current Trends and Future Challenges in Congestion Management Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 622-636  
  Keywords Congestion Management, Traffic Incident Management, Intelligent Transportation System, Traffic Management System, Future Mobility, Social Evolution, Future Challenges.  
  Abstract Traffic congestion creates multidimensional impacts that require stakeholders' integration and coordination. This paper tries to close the research gaps in congestion management by examining a case study of integrated solutions of congestion measures and analyzing future challenges in congestion management based on two selected factors. The authors develop the result from the literature study and an expert interview that provides a better perspective on the case study. The study generates a new perspective on reviewing the organizational aspect of integrated congestion management measures. Secondly, it starts a discussion on future challenges in congestion management and connects the domain of future mobility with congestion theories as an independent discussion.  
  Address University of Münster; University of Münster; University of Washington; University of Münster  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-58 ISBN 2411-3444 Medium  
  Track Practitioner-centered Logistics and Supply Chain Management in Crisis Response Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes irfansyah@uni-muenster.de Approved no  
  Call Number Serial 2259  
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Author (up) Alessandro Farasin; Luca Colomba; Giulio Palomba; Giovanni Nini pdf  isbn
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  Title Supervised Burned Areas Delineation by Means of Sentinel-2 Imagery and Convolutional Neural Networks Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 1060-1071  
  Keywords Burned Area Delineation, Sentinel-2, U-Net, CuMedVision1, Convolutional Neural Network, Deep Learning, Supervised Learning, Pixel-wise Segmentation.  
  Abstract Wildfire events are increasingly threatening our lands, cities, and lives. To contrast this phenomenon and to limit its damages, governments around the globe are trying to find proper counter-measures, identifying prevention and monitoring as two key factors to reduce wildfires impact worldwide. In this work, we propose two deep convolutional neural networks to automatically detect and delineate burned areas from satellite acquisitions, assessing their performances at scale using validated maps of burned areas of historical wildfires. We demonstrate that the proposed networks substantially improve the burned area delineation accuracy over conventional methods.  
  Address Politecnico di Torino – DAUIN dept., and LINKS Foundation – DSISA dept.; Politecnico di Torino – DAUIN dept.; LINKS Foundation – DSISA dept.; LINKS Foundation – DSISA dept.  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-96 ISBN 2411-3482 Medium  
  Track Using Artificial Intelligence to exploit Satellite Data in Risk and Crisis Management Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes alessandro.farasin@polito.it Approved no  
  Call Number Serial 2297  
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Author (up) Alexander Gabriel; Florian Klein; Frank Fiedrich pdf  isbn
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  Title Modelling of Passenger Handling Processes in Railway Stations – A Mixed-Methods Approach Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 580-592  
  Keywords Crowd-Management; Mixed-Methods; Process Modelling; Critical Infrastructure; Railway Transportation  
  Abstract The constantly increasing number of passengers using public transportation leads to an expansion of the ser-vices offered by public transportation companies. The existing transportation infrastructures, especially rail-way stations, can only partly cope with this rapid growth. There is already overcrowding on platforms and access routes, especially during disruptions caused by natural disasters or major public events. This crowding may result in personal injury or shutdown of operations for safety reasons. The research project CroMa aims at improving robustness, safety, security and performance of railway stations at peak loads. The paper contributes thereto by developing an approach to assess railway infrastructure in terms of the risk of overcrowding. The core of this research is to combine qualitative workshop results with quantitative database analysis. Furthermore, the paper gives an outlook on the ongoing process model development as a basis for a semi-quantitative evaluation tool for railway stations applicable by end users.  
  Address University of Wuppertal, Germany; University of Wuppertal, Germany; University of Wuppertal, Germany  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-54 ISBN 2411-3440 Medium  
  Track Planning, Foresight and Risk Analysis Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes gabriel@uni-wuppertal.de Approved no  
  Call Number Serial 2255  
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Author (up) Alexander Staves; Harry Balderstone; Benjamin Green; Antonios Gouglidis; David Hutchison pdf  isbn
openurl 
  Title A Framework to Support ICS Cyber Incident Response and Recovery Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 638-651  
  Keywords ICS; CNI; Cyber Incident; Guidance; Response and Recovery  
  Abstract During the past decade there has been a steady increase in cyber attacks targeting Critical National Infrastructure. In order to better protect against an ever-expanding threat landscape, governments, standards bodies, and a plethora of industry experts have produced relevant guidance for operators in response to incidents. However, in a context where safety, reliability, and availability are key, combined with the industrial nature of operational systems, advice on the right practice remains a challenge. This is further compounded by the volume of available guidance, raising questions on where operators should start, which guidance set should be followed, and how confidence in the adopted approach can be established. In this paper, an analysis of existing guidance with a focus on cyber incident response and recovery is provided. From this, a work in progress framework is posited, to better support operators in the development of response and recovery operations.  
  Address Lancaster University, UK; Lancaster University, UK; Lancaster University, UK; Lancaster University, UK; Lancaster University, UK  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-59 ISBN 2411-3445 Medium  
  Track Resilience in Critical Infrastructures Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes a.staves@lancaster.ac.uk Approved no  
  Call Number Serial 2260  
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Author (up) Amanda Hughes; Fiona McNeill; Christopher W. Zobel pdf  isbn
openurl 
  Title 17th ISCRAM Conference Proceedings Type Conference Volume
  Year 2020 Publication ISCRAM 2020 Conference Proceedings � 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 1-1193  
  Keywords  
  Abstract The 17th annual conference on Information Systems for Crisis Response and Management (ISCRAM 2020) was scheduled to be held in Blacksburg, Virginia from May 24th-27th, 2020. Unfortunately, due to the widespread impacts of the COVID-19 pandemic, the conference organizers and the ISCRAM Board decided to postpone the conference until May 2021. Even though we could not hold the conference as originally planned, all papers accepted for presentation at ISCRAM 2020 are published in the conference proceedings presented here, and the authors of these papers will have the opportunity to present their papers at the 2021 conference. The 2021 conference will once again be hosted at Virginia Tech in Blacksburg, Virginia, and it will take place during the week of May 23rd, 2021.

The theme of ISCRAM 2020 is �Bringing Disaster Resilience into Focus.� These proceedings seek to highlight resilience in Crisis and Emergency Management and to stimulate discussions that enable the design of crisis and emergency management systems that contribute to more resilient organizations and communities. We are pleased to present the accepted papers for ISCRAM 2020, which consist of excellent contributions on a wide range of topics.
 
  Address  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-92 ISBN 2411-3478 Medium  
  Track Proceedings Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved yes  
  Call Number Serial 2307  
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Author (up) Ana-Gabriela Núñez; Sebastián Cedillo; Andrés Alvarado Martínez; Ma Carmen Penadés pdf  isbn
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  Title Towards the Building of a Resilient City able to Face Flood Risk Scenarios Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 593-601  
  Keywords Risk Management; Floods; River Morphology; Resilience; IT  
  Abstract Despite the efforts that have been made to inform the community about the possible environmental risks, there is still a general lack of information. Currently, we are working on a flood risk scenario focused on a proposal towards a resilient culture together with the support of Information Technologies (IT) as a way to manage information. The goal is twofold: (i) on the one hand, to manage data in a small scenario to analyze and process the data collected from sensors in different sites in a micro-basin. Data get from data processing such as flow and velocity will then be the input data for hydraulic models to predict floods downstream; (ii) on the other hand, to publicize the predictions and the data already processed means people can benefit from information on flood risks, and the different participants may change their perception and consider cooperating in improving resilience.  
  Address Universidad de Cuenca, Ecuador, Universitat Politècnica de València, Spain; Universidad de Cuenca, Ecuador; Universidad de Cuenca, Ecuador; Universitat Polit\`{e}cnica de Val\`{e}ncia, Spain  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-55 ISBN 2411-3441 Medium  
  Track Planning, Foresight and Risk Analysis Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes anag.nunez@ucuenca.edu.ec Approved no  
  Call Number Serial 2256  
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Author (up) Anastasia Moumtzidou; Marios Bakratsas; Stelios Andreadis; Anastasios Karakostas; Ilias Gialampoukidis; Stefanos Vrochidis; Ioannis Kompatsiaris pdf  isbn
openurl 
  Title Flood detection with Sentinel-2 satellite images in crisis management systems Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 1049-1059  
  Keywords Floods, Change Detection, Bi-temporal Analysis, Sentinel-2, Deep Neural Networks.  
  Abstract The increasing amount of falling rain may cause several problems especially in urban areas, which drainage system can often not handle this large amount in a short time. Confirming a flooded scene in a timely manner can help the authorities to take further actions to counter the crisis event or to get prepared for future relevant incidents. This paper studies the detection of flood events comparing two successive in time Sentinel-2 images, a method that can be extended for detecting floods in a time-series. For the flood detection, fine-tuned pre-trained Deep Convolutional Neural Networks are used, testing as input different sets of three water sensitive satellite bands. The proposed approach is evaluated against different change detection baseline methods, based on remote sensing. Experiments showed that the proposed method with the augmentation technique applied, improved significantly the performance of the neural network, resulting to an F-Score of 62% compared to 22% of the traditional remote sensing techniques. The proposed method supports the crisis management authority to better estimate and evaluate the flood impact.  
  Address Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece; Centre for Research & Technology Hellas, Information Technologies Institute, Thessaloniki, Greece;  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-95 ISBN 2411-3481 Medium  
  Track Using Artificial Intelligence to exploit Satellite Data in Risk and Crisis Management Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes moumtzid@iti.gr Approved no  
  Call Number Serial 2296  
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Author (up) Andreas Lotter; Philipp John; Patricia Schütte; Florian Brauner; Frank Fiedrich pdf  isbn
openurl 
  Title Field Observation of Parallel Working Coordination Groups and Command and Control Centres to Understand and Improve Inter-organizational Information Management – A Methodical Approach Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 303-314  
  Keywords Information Management, Field Observation, Coordination Groups, Command and Control Centres, Risk and Crisis Management.  
  Abstract In emergency response, parallel working coordination groups and command and control centres are responsible to deal with complex events. A well-functioning exchange of information between organizations, officials and these coordination groups is the basis for an efficient risk management. This paper describes a methodical ap-proach for field observation to understand and improve the inter-organizational information management be-tween the involved partners. The method was tested within a practical approach and possible occurring problems during the observation were identified and solutions for these problems are provided.  
  Address University of Wuppertal, Germany; University of Wuppertal, Germany; University of Wuppertal, Germany; Kölner Verkehrs-Betriebe AG; University of Wuppertal, Germany  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-30 ISBN 2411-3416 Medium  
  Track Command & Control Studies Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes lotter@uni-wuppertal.de Approved no  
  Call Number Serial 2231  
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Author (up) Andrew Arnette; Christopher W. Zobel; Duygu Pamukcu pdf  isbn
openurl 
  Title Post-Impact Analysis of Disaster Relief Resource Pre-Positioning After the 2013 Colorado Floods Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 237-243  
  Keywords Disaster Operations Management; Facility Location; Humanitarian Operations  
  Abstract Pre-positioning of supplies is important to facilitate disaster relief operations, however it is only after a disaster event occurs that the effectiveness of the pre-positioning strategy can be properly assessed. With this in mind, this paper analyzes a risk-based pre-positioning algorithm, developed for the American Red Cross, in the context of its actual performance in the 2013 Colorado Front Range floods. The paper assesses the relative effectiveness of the pre-positioning approach with respect to historical asset placements, and it discusses changes to the model that are necessary to support such comparisons and allow for further model extensions.  
  Address University of Wyoming; Virginia Tech; Virginia Tech  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-23 ISBN 2411-3409 Medium  
  Track Analytical Modeling and Simulation Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes aarnette@uwyo.edu Approved no  
  Call Number Serial 2224  
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Author (up) Andrew Marinik; Ludwig Gantner; Scott Fritz; Sean Smith pdf  isbn
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  Title Developing Performance Metrics of an Emergency Notification System Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 663-668  
  Keywords Emergency Notification System, Early Warning System, Socio-Technical Systems Theory.  
  Abstract The use of emergency notification systems (ENS), or early warning systems, are not only common practice among Institutes of Higher Education (IHEs), but are required by law in the United States. The dramatic increase in use is matched by the increase in community expectation. This community expectation corresponding with societal shifts challenges Public Safety leaders to implement and maintain a broad and highly reliable ENS. Most Public Safety programs lack the internal resources to consistently assess system risk, reliability, and messaging validity of their ENS sufficient to match the required system performance. Virginia Tech Emergency Management is proposing an ENS evaluation system capable of supporting assessment of reliability and risk across the entire system through the lens of Socio-Technical Systems (STS) theory at a practitioner level. By organizing emergency notification/early warning systems through Human Subsystems, Technical Subsystems, and Task Design the practitioner can assess their system by performance and risk.  
  Address Virginia Tech Emergency Management; Virginia Tech Network Infrastructure & Services; Virginia Tech Division of Operations IT; Virginia Tech Police Department  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-61 ISBN 2411-3447 Medium  
  Track Resilience in Critical Infrastructures Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes amarinik@vt.edu Approved no  
  Call Number Serial 2262  
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Author (up) Anna Kruspe pdf  isbn
openurl 
  Title Detecting Novelty in Social Media Messages During Emerging Crisis Events Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 860-871  
  Keywords Social media; Clustering; Novelty; Embeddings  
  Abstract Social media can be a highly valuable source of information during disasters. A crisis' development over time is of particular interest here, as social media messages can convey unfolding events in near-real time. Previous approaches for the automatic detection of information in such messages have focused on a static analysis, not taking temporal changes and already-known information into account. In this paper, we present a novel method for detecting new topics in incoming Twitter messages (tweets) conditional upon previously found related tweets. We do this by first extracting latent representations of each tweet using pre-trained sentence embedding models. Then, Infinite Mixture modeling is used to dynamically cluster these embeddings anew with each incoming tweet. Once a cluster reaches a minimum number of members, it is considered to be a new topic. We validate our approach on the TREC Incident Streams 2019A data set.  
  Address German Aerospace Center (DLR), Jena, Germany  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-76 ISBN 2411-3462 Medium  
  Track Social Media for Disaster Response and Resilie Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes anna.kruspe@dlr.de Approved no  
  Call Number Serial 2277  
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Author (up) Anne-Marie Barthe-Delanoë; Wenxin Mu pdf  isbn
openurl 
  Title Towards a Context-Aware Systemic Risk Management Framework for the Crisis Response Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 1122-1129  
  Keywords Context-Awareness; Risk Analysis; Risk Evaluation; Knowledge Base; Systemic Risk  
  Abstract Crisis response is, as any other collaborative networked organization, challenged by changes and vulnerabilities. Moreover, as a complex system with distributed activities and numerous interdependencies, considering the risk of such an organization at a systemic level, including time and space dimensions, is necessary. Systemic risk management is a topic traditionally studied in the finance area. Even if a few researches now focus on the supply chain management area (a more relatable domain regarding crisis response), there is even fewer literature regarding systemic risk management for the crisis response. Thus, this paper proposes first to define systemic risk related to the case of the crisis response. Then, a framework for context-aware systemic risk management is presented, to support the design as well as the follow-up of the crisis response, meeting one of the challenges of the Sendai Framework for Disaster Risk Reduction.  
  Address Laboratoire de Génie Chimique, Université de Toulouse, CNRS, INPT, UPS, Toulouse, France; Department of Information Management, Jiao Tong University, Beijing, China  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-101 ISBN 2411-3487 Medium  
  Track Visions for Future Crisis Management Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes annemarie.barthe@ensiacet.fr Approved no  
  Call Number Serial 2302  
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Author (up) Anying Chen; Zhongliang Huang; Manchun Liang; Guofeng Su pdf  isbn
openurl 
  Title Empirical Study of Individual Evacuation Decision-making in Fire Accidents: Evacuate Intention and Herding Effect Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 200-209  
  Keywords Fire Accidents, Evacuation Experiment, Evacuate Intention, Herding Behaviors.  
  Abstract People's decision of evacuating or not could greatly influence the final losses in fire accidents. In order to study people's response under emergent occasions, a fire accident evacuation drill experiment was conducted in an office building without advance notice. 113 Participants' response and their decision-making process were collected by questionnaire survey right after the experiment. In this study, we mainly focused on two aspects of people's response, including participants' evacuate intention and their herding tendency during evacuate decision-making. It is found that the classical Expected Utility Theory (EUT) has certain limitation in explaining individual's evacuation intention, but the relationship between the expected utility and the evacuation intention could be represented with a modified model based on EUT. Furthermore, the herding tendency is found to be different for the two groups of people who intend to evacuate and not to evacuate. People who firstly intend not to evacuate are more easily to form herding behavior and change their minds to evacuate. Based on these findings, models of individual evacuation intention and herding tendency for two groups of people are put forward. Simulation is conducted to investigate the effect of these two changes in people's evacuation decision-making process, and results show that they both increase the final evacuation rate, reflecting the majority's risk aversion characteristics.  
  Address Tsinghua University;Tsinghua University; Tsinghua University; Tsinghua University  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-19 ISBN 2411-3405 Medium  
  Track Analytical Modeling and Simulation Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes chenay15@mails.tsinghua.edu.cn Approved no  
  Call Number Serial 2220  
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Author (up) Arnis Parsovs pdf  isbn
openurl 
  Title Solving the Estonian ID Card Crisis: the Legal Issues Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 459-471  
  Keywords Cyber Resilience, Electronic Identity, Cyber Legislation, eIDAS.  
  Abstract In 2017, Estonia experienced a cyber crisis caused by a vulnerability found in the smart card chips produced by Infineon Technologies AG. Since the affected chip was used in the electronic identity card (ID card) issued by the State to more than half of the Estonian population, the vulnerability posed a risk to the resilience of Estonian e-state and thus quickly escalated into a manageable crisis. This work studies to what extent, in such a national emergency, the involved parties were able to precisely follow the applicable laws and regulations in the field. We enlist the cases where the requirements were not fully followed, either due to the lack of technical preparedness, suboptimal decisions made under heavy time pressure, or the critical nature of the situation.  
  Address STACC OU, Estonia University of Tartu, Estonia  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-44 ISBN 2411-3430 Medium  
  Track Ethical, Legal, and Social Issues Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes arnis.parsovs@ut.ee Approved no  
  Call Number Serial 2245  
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Author (up) Artur Ricardo Bizon; Luciana P. de Araújo Kohler; Adilson Luiz Nicoletti; Fernanda Dal Bosco; Murilo Schramm da Silva; Thales Bohn Pessatti pdf  isbn
openurl 
  Title Integration statistical systems for land cover mapping in Southern Brazil Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 498-505  
  Keywords Random Forest, Logistic Regression, Classifier, Google Earth Engine, Remote Sensing.  
  Abstract The remote sensing is a way to optimize the process of land cover classification allowing that this process will be by high definition images of satellite. For the research it was used the Google Earth Engine with JavaScript programming language to classify the images, identifying the areas with forest or reforest. It was identified that classifiers Random Forest and Logistic Regression have a high performance in classify the images. From them it was developed functions to process automatically of new images with purpose of classify them in relation to land cover.  
  Address Departamento de Engenharia Florestal -- Universidade Regional de Blumenau; Departamento de Engenharia Florestal -- Universidade Regional de Blumenau; Departamento de Engenharia Florestal -- Universidade Regional de Blumenau;Departamento de Engenharia Florestal -- Universidade Regional de Blumenau; Departamento de Engenharia Florestal -- Universidade Regional de Blumenau; Departamento de Engenharia Florestal -- Universidade Regional de Blumenau  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-47 ISBN 2411-3433 Medium  
  Track Geospatial Technologies and Geographic Information Science for Crisis Management (GIS) Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes abizon@furb.br Approved no  
  Call Number Serial 2248  
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Author (up) Aurélie Congès; Alexis Evain; Olivier Chabiron; Col. Jacob Graham(USMC, R.); Frédérick Benaben pdf  isbn
openurl 
  Title Virtual Reality to Train for Crisis Management Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 1100-1112  
  Keywords Virtual reality; Crisis Management; Exercises; Decision-Support System  
  Abstract The EGCERSIS project aims at using virtual reality to improve the efficiency of the crisis management preparation phase. The idea is to tackle the drawbacks of regular crisis management exercises thanks to fully configurable scenarios taking place in digital twins of real critical sites. Virtual exercises will improve, among other things, the frequency, efficiency, and modularity of crisis management preparation, while reducing its costs. In this article, we demonstrate the idea of the project through a simple use-case taking place in a metro station and involving three crisis responders. By linking virtual exercises to our crisis management platform, we also want to demonstrate the usefulness of decision-support systems during a crisis.  
  Address IMT Mines Albi; IMT Mines Albi; Immersive Factory; The Pennsylvania State University; IMT Mines Albi  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-99 ISBN 2411-3485 Medium  
  Track Visions for Future Crisis Management Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes aurelie.conges@mines-albi.fr Approved no  
  Call Number Serial 2300  
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Author (up) Ben Ortiz; Laura Kahn; Marc Bosch; Philip Bogden; Viveca Pavon-Harr; Onur Savas; Ian McCulloh pdf  isbn
openurl 
  Title Improving Community Resiliency and Emergency Response With Artificial Intelligence Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 35-41  
  Keywords Emergency Management, Semantic Segmentation, Inland Flood Modeling, Route Optimization.  
  Abstract New crisis response and management approaches that incorporate the latest information technologies are essential in all phases of emergency preparedness and response, including the planning, response, recovery, and assessment phases. Accurate and timely information is as crucial as is rapid and coherent coordination among the responding organizations. We are working towards a multi-pronged emergency response tool that provide stakeholders timely access to comprehensive, relevant, and reliable information. The faster emergency personnel are able to analyze, disseminate and act on key information, the more effective and timelier their response will be and the greater the benefit to affected populations. Our tool consists of encoding multiple layers of open source geospatial data including flood risk location, road network strength, inundation maps that proxy inland flooding and computer vision semantic segmentation for estimating flooded areas and damaged infrastructure. These data layers are combined and used as input data for machine learning algorithms such as finding the best evacuation routes before, during and after an emergency or providing a list of available lodging for first responders in an impacted area for first. Even though our system could be used in a number of use cases where people are forced from one location to another, we demonstrate the feasibility of our system for the use case of Hurricane Florence in Lumberton, a town of 21,000 inhabitants that is 79 miles northwest of Wilmington, North Carolina.  
  Address Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services; Accenture Federal Services  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-4 ISBN 2411-3390 Medium  
  Track AI Systems for Crisis and Risks Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes Laura.kahn@accenturefederal.com Approved no  
  Call Number Serial 2205  
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Author (up) Benjamin Barth; Govinda Chaithanya Kabbinahithilu; Alexandros Bartzas; Spyros Pantazis; Tomaso deCola pdf  isbn
openurl 
  Title A Content Oriented Information Sharing System for Disaster Management Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 922-927  
  Keywords Information Sharing, Preparation, Response, Content Oriented.  
  Abstract In response to natural and man-made hazards multiple organisations usually are involved in a very complex situation. On the other hand, extreme weather situations due to the climate change create hazards in areas which were considered safe before. In order to improve the capabilities of involved organisations in responding and preparing for disaster events, the availability of an efficient information sharing approach is a key enabler. To this end, we propose a communication system based on a content oriented architecture tailored to disaster management. It includes a catalogue that is offering web services for publishing and subscribing of disaster information and for further collaboration amongst agencies and first responders. Moreover, the considered approach also allows for full content access control and enables a flexible system. The paper shows the current status of the system design. Next steps will include the implementation and evaluation of the approach.  
  Address German Aerospace Center (DLR); German Aerospace Center (DLR); Space Hellas S.A.; Space Hellas S.A.; German Aerospace Center (DLR)  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-82 ISBN 2411-3468 Medium  
  Track Technologies for First Responders Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes Benjamin.Barth@dlr.de Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2283  
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Author (up) Björn J E Johansson pdf  isbn
openurl 
  Title Boundary Stories – A Systems Perspective on Inter-organizational Learning from Crisis Response Exercises Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 427-434  
  Keywords Inter-organizational Learning, Boundary-crossing Competence, Boundary Discourse, Systems Science, Complex Adaptive Systems.  
  Abstract Inter-organizational exercises are commonly conducted with the aim to improve overall crisis response system performance. However, there are challenges associated with establishing learning goals for, designing and evaluating inter-organizational exercises. This work-in-progress paper applies a systems science perspective on the Swedish crisis response system with the aim to understand (1) what kind of a system it is (2) what properties or mechanisms enable good system performance?, and, (3) what are desirable training goals for improving the crisis response capability of the Swedish crisis response system? The author suggests that (1) the Swedish crisis response system can be seen as a Complex Adaptive System, and (2) that the focus must shift from exercising organizations' intra-organizational capabilities to adaptive capabilities. The latter can be achieved by designing exercises comprising boundary-crossing activities with the purpose to support the buildup of boundary-crossing competence. Cross-organizational learning can be achieved by identifying, documenting and disseminating boundary stories.  
  Address Swedish Defence Research Agency  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-41 ISBN 2411-3427 Medium  
  Track Enhancing resilient response in inter-organizational contexts: Learning from experience Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes bjorn.j.e.johansson@foi.se Approved no  
  Call Number Serial 2242  
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Author (up) Björn JE Johansson; Amanda Jaber; Joeri van Laere; Peter Berggren pdf  isbn
openurl 
  Title Crisis Response During Payment Disruptions – The Themes of TRAMS Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 264-275  
  Keywords Crisis Management, Payment Disruptions, Resilience, Thematic Analysis.  
  Abstract A qualitative analysis of observation protocols and audio recordings from 14 crisis response exercises has been conducted revealing eight themes reoccurring in multi-disciplinary team discussions about crisis response to large disruptions to the card payment system. The themes were: Coordinate and collaborate, Payment options, Cash circulation, Fuel and transportation, Security, Inform, communicate and the media, Hoarding and rationing, and Vulnerable groups. The analysis suggest that Swedish society is vulnerable to disruptions in the card payment services, largely due to a low diversity in payment options, the lack of prepared back up solutions for payment, and insufficient cash flows to support a cash only scenario. A longer (several days) disruption in the card payment system will demand coordinating mechanisms for information management, available payment options, and preparedness for rapid establishment of cash flows. Today, these mechanisms do not exist. Simulation exercises with stake-holders are an important mean for increasing awareness about these vulnerabilities and the challenges associated with coping with them.  
  Address Linköping University; Linköping University; Skövde University; Linköping University  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-26 ISBN 2411-3412 Medium  
  Track Command & Control Studies Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes bjorn.j.johansson@liu.se Approved no  
  Call Number Serial 2227  
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Author (up) Briony Gray pdf  isbn
openurl 
  Title Turning Words into Wisdom: A Framework for Using Post-Disaster Data for Community Resilience Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 356-365  
  Keywords Resilience, Recovery, Framework, Small Island Developing States, Social Capital.  
  Abstract Small island developing states (SIDs) face a range of underlying issues that increase their vulnerability and risk to disaster. This commonly results in a lack of available, reliable and actionable data for both island nations as well as their insular communities. Simultaneously, issues such as climate change make their riskscapes unique and challenging to mitigate, forcing the need to find methods of improving community resiliency. This paper uses qualitative interviews conducted in the post-disaster phase of the 2017 Atlantic hurricane season to highlight the main issues experienced by communities. It then uses these, as well as literature guidance, to create a Lessons Learnt Framework (LLF) designed to challenge underlying assumptions, assess management efforts, discuss and record community experiences, and to feedback social capital into vulnerable communities to support future community resilience.  
  Address University of Southampton  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-34 ISBN 2411-3420 Medium  
  Track Data and Resilience: Opportunities and Challenges Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes Bjg1g11@soton.ac.uk Approved no  
  Call Number Serial 2235  
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Author (up) Cecilia Hammar Wijkmark; Ilona Heldal pdf  isbn
openurl 
  Title Virtual and Live Simulation-Based Training for Incident Commanders Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 1154-1162  
  Keywords Virtual Simulation; Simulation; Serious Games; Training; Live Training; Cost and Benefit; Use; Usability; Incident Command  
  Abstract Computer and virtual simulation-based training (CST) offer several benefits for emergency response and management preparedness. However, organizations responsible for training are often hesitant to use CST, based on cost and perceived lack of benefit when compared to live simulation training (LST). This paper investigates how CST can complement LST, and how it contributes to achieving the necessary learning objectives for level one fire and rescue service incident commanders (ICs). Data and examples come from an experimental study with students from different fire and rescue services trained in the role of the IC in LST and CST, in a similar scenario. Results show the cost and benefits of the CST implementation based on evaluations from learners, instructors and responsible managers. Participants had a positive attitude towards using virtual simulations, but the results also point to barriers regarding the suitable design of learning scenarios and implementation.  
  Address Western Norway University of Applied Sciences; Western Norway University of Applied Sciences  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-105 ISBN 2411-3491 Medium  
  Track Open Track Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes Cecilia.hammar.wijkmark@hvl.no Approved no  
  Call Number Serial 2306  
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Author (up) Cheng Wang; Benjamin Bowes; Arash Tavakoli; Stephen Adams; Jonathan Goodall; Peter Beling pdf  isbn
openurl 
  Title Smart Stormwater Control Systems: A Reinforcement Learning Approach Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 2-13  
  Keywords Reinforcement Learning, Stormwater, Flooding Control.  
  Abstract Flooding poses a significant and growing risk for many urban areas. Stormwater systems are typically used to control flooding, but are traditionally passive (i.e. have no controllable components). However, if stormwater systems are retrofitted with valves and pumps, policies for controlling them in real-time could be implemented to enhance system performance over a wider range of conditions than originally designed for. In this paper, we propose an autonomous, reinforcement learning (RL) based, stormwater control system that aims to minimize flooding during storms. With this approach, an optimal control policy can be learned by letting an RL agent interact with the system in response to received reward signals. In comparison with a set of static control rules, RL shows superior performance on a wide range of artificial storm events. This demonstrates RL's ability to learn control actions based on observation and interaction, a key benefit for dynamic and ever-changing urban areas.  
  Address Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia; Department of Engineering Systems and Environment, University of Virginia  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication