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Author | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel (eds) | ||||
Title | 18th ISCRAM Conference Proceedings | Type | Conference Volume | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
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Abstract | The theme of ISCRAM 2021 is ?Embracing the Interdisciplinary Nature of Crisis Management.? These proceedings highlight the range of interdisciplinary research required to understand the design, behavior, and performance of crisis and emergency management systems. We are pleased to present the included papers, which offer excellent contributions on a wide range of topics related to the use of information systems in crisis response and management. |
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Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2411-3387 | ISBN | 978-1-949373-61-5 | Medium | |
Track | Proceedings | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | Approved | no | |||
Call Number | ISCRAM @ idladmin @ | Serial | 2396 | ||
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Author | Therese Habig; Richard Lüke; Simon Gehlhar; Torben Sauerland; Daniel Tappe | ||||
Title | A Consolidated Understanding of Disaster Community Technologies | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 778-791 | ||
Keywords | Disaster Community Technologies, social media and crowdsourcing, categorization and classification schema, knowledge base | ||||
Abstract | Since the beginning of this millennium, there has been an increasing use of social media and crowdsourcing (SMCS) technologies in disaster situations (Reuter & Kaufhold, 2018). Disaster management organizations and corresponding research are increasingly working on ways of integrating SMCS into the processes of crisis management. In a changing technological landscape to address disasters, and with increasing diversity of stakeholders in disasters, the purpose of this research is to provide an overview of technologies for SMCS within disasters to improve community resilience. The identified and analyzed technologies are summarized under the term “Disaster Community Technologies” (DCT). The paper presents a classification schema (the “DCT-schema”) for those technologies. The goal is to generate an overview of DCT in a rapidly evolving environment and to provide the practical benefit for different stakeholders to identify the right one from the overview. | ||||
Address | safety innovation center; safety innovation center; safety innovation center; safety innovation center; safety innovation center | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | habig@safetyinnovation.center | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2373 | ||
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Author | Lucas Dorigueto; Carlos Brumatti; Erick Figueiredo; Jugurta Lisboa-Filho | ||||
Title | A Framework for Landslide Information Management Systems Development | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 515-526 | ||
Keywords | Disaster Information Management Systems, Landslide, Interoperability, Volunteered Geographic Information | ||||
Abstract | Volunteered Geographic Information (VGI) integrated with Disaster Information Management Systems (DIMS) has great potential to assist managers and the community in times of emergency. However, there is little research focusing on integrating VGI with DIMS, in addition, there are a lack of use of standards of interoperability and emergency, which can impair interoperability and the quality of the information contained in these systems. This work presents a fully interoperable framework aimed at the construction of DIMS, which integrates official data and VGI through ISO and OGC standards, allowing managers and the community to work with official data and VGI in order to assist managers in decision making. To show the viability of the framework, a case study using data from the risk situation of dams located in the municipality of Barão de Cocais in Brazil was carried out. | ||||
Address | Universidade Federal de Viçosa (UFV); Universidade Federal de Viçosa (UFV); Universidade Federal de Viçosa (UFV); Universidade Federal de Viçosa (UFV) | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Geospatial Technologies and Geographic Information Science for Crisis Management (GIS) | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | lucas.dorigueto@ufv.br | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2352 | ||
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Author | Sindisiwe Magutshwa; Jaziar Radianti | ||||
Title | A Qualitative Risk Identification Framework for Cyber-Physical-Social Systems | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 377-390 | ||
Keywords | Cyber physical systems, Cyber physical Social Systems, risk, vulnerability, mission critical | ||||
Abstract | As information and communication technologies, real-world physical systems, and people become interconnected in critical infrastructure, attention has shifted to the operations of Cyber-Physical-Social Systems (CPSS). CPSS are progressively integrated in core critical infrastructure organisational processes to achieve a combination of benefits. However, the high degree of integration of technology into human society and mission-critical processes leads to an increase in complexity and introduces novel risks and vulnerabilities. These novel constraints extend beyond what is known from previous cyber-physical and critical infrastructure systems studies and prompt the need for revised risk perception and identification methodologies. This paper aims to develop a novel qualitative risk identification framework that is used in the identification of risk and vulnerability in CPSS ecosystems deployed in critical infrastructure or mission-critical organisational processes. The framework emphasizes interactions between humans and the system making it possible to identify and under-stand how non-technical risk impacts the CPSS ecosystem. | ||||
Address | University of Agder; University of Agder | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Enhancing Protection of Critical Infrastructures | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | sindisiwe.magutshwa@uia.no | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2340 | ||
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Author | Xiaojing Guo; Xinzhi Wang; Luyao Kou; Hui Zhang | ||||
Title | A Question Answering System Applied to Disasters | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 2-16 | ||
Keywords | Emergency Management, Disaster, Natural Language Processing, Deep Learning | ||||
Abstract | In emergency management, identifying disaster information accurately and promptly out of numerous documents like news articles, announcements, and reports is important for decision makers to accomplish their mission efficiently. This paper studies the application of the question answering system which can automatically locate answers in the documents by natural language processing to improve the efficiency and accuracy of disaster knowledge extraction. Firstly, an improved question answering model was constructed based on the advantages of the existing neural network models. Secondly, the English question answering dataset pertinent to disasters and the Chinese question answering dataset were constructed. Finally, the improved neural network model was trained on the datasets and tested by calculating the F1 and EM scores which indicated that a higher question answering accuracy was achieved. The improved system has a deeper understanding of the semantic information and can be used to construct the disaster knowledge graph. | ||||
Address | Institute of Public Safety Research, Tsinghua University; School of Computer Engineering and Science, Shanghai University; Institute of Public Safety Research, Tsinghua University; Institute of Public Safety Research, Tsinghua University | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | AI and Intelligent Systems for Crises and Risks | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | gxj19@mails.tsinghua.edu.cn | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2308 | ||
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Author | Sofia Kostakonti; Ramona Velea; Vassilis Papataxiarhis; Daniele Del Bianco; Uberto Delprato; Stathes Hadjiefthymiades | ||||
Title | A semantic approach for modeling vulnerability of communities | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 305-318 | ||
Keywords | Community vulnerability, semantic modeling, community resilience, knowledge representation and reasoning | ||||
Abstract | In this paper, we propose the use of semantic technologies for the representation of concepts and relationships required for the modeling of vulnerability data for local communities. First, we discuss the concepts of vulnerability and resilience and we try to identify the relationship between the two. We provide some background knowledge and we present basic characteristics of the two concepts. Next, we discuss the motivation behind the use of semantic technologies, and we show how the proposed framework can address existing challenges in terms of vulnerability assessment. The core part of this paper focuses on the semantic representation of community vulnerability aspects. We give an overview of the layered semantic framework consisting of interconnected ontological models and we provide a set of use-cases where the use of semantic-based modeling and query answering can prove beneficial in terms of assessing vulnerability. | ||||
Address | National and Kapodistrian University of Athens; Institute of International Sociology of Gorizia; National and Kapodistrian University of Athens; Institute of International Sociology of Gorizia; Intelligence for Environment and Security; National and Kapod | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Data and Resilience: Opportunities and Challenges | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | sofkost@di.uoa.gr | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2335 | ||
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Author | Ivar Svare Holand; Peter Mozelius; Trond Olav Skevik | ||||
Title | A structured and dynamic model for emergency management exercises | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 186-197 | ||
Keywords | Emergency exercises, Vulnerability assessment, Non-linear emergency exercise model, Norwegian-Swedish cross-border collaboration, Gaining Security Symbiosis (GSS) projects | ||||
Abstract | Emergencies are management challenges, and emergency exercises that involve multiple collaborating parties is a means towards mastering them. Such exercises are often conducted in a virtual training environment based on complex disaster scenarios. The reported study was carried out using a requirement-focused design approach. The aim was to describe and discuss a relevant design for lean, dynamic, and cost-efficient emergency management exercise systems. Data were gathered from a literature study and analyses of earlier emergency management projects in which the authors had participated. Despite the complexity of many current emergency management exercises, the scenarios usually involve only the response phases and have a linear structure that hinders both didactic aspects and the software structure. The conclusion drawn from the study is that an emergency management exercise model should focus on managing the activities that correspond to alternatives that unfold from a dynamic scenario. Finally, the authors recommend the principles of alternate reality games as a way towards more dynamic and cost-efficient emergency exercise systems. | ||||
Address | Nord University; Mid Sweden University; Nord University | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Analytical Modeling and Simulation | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | ivar.s.holand@nord.no | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2324 | ||
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Author | Maki Tagashira; Toshihiro Osaragi | ||||
Title | Accessibility Assessment of Vulnerable Roadside Areas after a Major Earthquake | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 553-566 | ||
Keywords | Large earthquake, accessibility assessment, emergency activity, building collapse, road blockage | ||||
Abstract | In order to reduce human casualty after a large earthquake, it is vital to secure the traffic function of main roads. Local governments promote the seismic reinforcement of roadside buildings, however, the project is not going well as planned. There is a high demand for appropriate information of its effect. In this paper, we proposed a method to identify the roadside areas with vulnerable accessibility to disaster bases after a large earthquake. First, we defined the accessibility indices; Link Isolation ratio (LI ratio) and Network Isolation ratio (NI ratio). Then, using the simulation model, we evaluated the accessibility to disaster base hospitals using emergency transportation roads in the Tokyo Metropolitan Area. LI ratio tended to be low in areas with a sparse road network. Furthermore, some hospitals indicated a severely high NI ratio. In secondary medical areas with these hospitals, it is necessary to consider the measures to improve accessibility. | ||||
Address | Tokyo Institute of Technology; Tokyo Institute of Technology | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Planning, Foresight and Risk Analysis | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | tagashira@arch.titech.ac.jp | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2355 | ||
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Author | Julien Coche; Jess Kropczynski; Aurélie Montarnal; Andrea Tapia; Frédérick Bénaben | ||||
Title | Actionability in a Situation Awareness world: Implications for social media processing system design | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 994-1001 | ||
Keywords | Actionable Information, Situation Awareness, Social Media, Crisis Management | ||||
Abstract | The field of crisis informatics now has a decade-long history of designing tools that leverage social media to support decision-makers situation awareness. Despite this history, there remains few examples of these tools adopted by practitioners. Recent fieldwork with public safety answering points and first responders has led to an awareness of the need for tools that gather actionable information, rather than situational awareness alone. This paper contributes to an ongoing discussion about these concepts by proposing a model that embeds the concept of actionable information into Endsley's model of situation awareness. We also extend the insights of this model to the design implications of future information processing systems. | ||||
Address | IMT Mines Albi; University of Cincinnati; Ecole des Mines d'Albi Carmaux; The Pennsylvania State University; Ecole des Mines d'Albi-Carmaux | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Visions for Future Crisis Management | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | coche.emac@gmail.com | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2391 | ||
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Author | Tina Mioch; Reinier Sterkenburg; Tatjana Beuker; Mark A. Neerincx | ||||
Title | Actionable Situation Awareness: Supporting Team Decisions in Hazardous Situations | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 62-70 | ||
Keywords | Situation Awareness, Actionability, Decision support, Chemical hazard | ||||
Abstract | Situation Awareness (SA) has been recognized and studied as an important requirement for an effective task performance of first responders. The integration of increasingly advanced sensor, network and artificial intelligence technology into the work processes affects the building, maintenance and sharing of SA. Connecting SA to decision support models provides new possibilities for the development of actionable SA (aSA), entailing information that guides the momentary decision-making processes of the concerning actors. In the European ASSISTANCE project, we are developing an aSA module that displays information about gas distributions, its current and predicted future states (e.g., entailing risks of breathing-in of toxic gases), with references to effective decision-making patterns for this situation. The aSA model is continuously updated based on sensor data. This paper gives an overview of this aSA module for chemical hazard prediction and corresponding display, and presents initial team design patterns that will be integrated into this display to support its actionability. | ||||
Address | Tno; Tno; Tno; Tno | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | AI and Intelligent Systems for Crises and Risks | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | tina.mioch@tno.nl | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2313 | ||
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Author | Ke Wang; Yongsheng Yang; Genserik Reniers; Jian Li; Quanyi Huang | ||||
Title | An Attribute-based Model to Retrieve Storm Surge Disaster Cases | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 567-580 | ||
Keywords | Storm surge disaster, multiple attributes, retrieval model, affected region prediction | ||||
Abstract | In China, storm surge disasters cause severe damages in coastal regions. One of the most important tasks is to predict affected regions and their relative damage levels to support decision-making. This study develops a two-stage retrieval model to search the most similar past disaster case to complete prediction. Based on spatial attributes of cases, the top-ranking past cases with a similar location to the target case are selected. Among these past cases, the most similar past case is selected by disaster attribute similarities. Three typical storm surge case studies have been used and implemented into this proposed model and the results show that all the most affected regions can be predicted. The proposed model simplifies the prediction process and updates results quickly. This study provides useful information for the government to make real-time response plans. | ||||
Address | Tsinghua University; Tsinghua University; KU Leuven; Tsinghua University; Tsinghua University | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Planning, Foresight and Risk Analysis | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | wangke16@mails.tsinghua.edu.cn | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2356 | ||
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Author | Enrique Caballero; Angel Madridano; Dimitrios Sainidis; Konstantinos Konstantoudakis; Petros Daras; Pablo Flores | ||||
Title | An automated UAV-assisted 2D mapping system for First Responders | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 890-902 | ||
Keywords | UAV, drone, 2D Mapping, Swarm, First Responders, Emergency Operations | ||||
Abstract | Recent advances in the Unmanned Aerial Vehicles (UAVs) sector have allowed such systems to carry a range of sensors, thus increasing their versatility and adaptability to a wider range of tasks and services. Furthermore, the agility of these vehicles allows them to adapt to rapidly changing environments making them an effective tool for emergency situations. A single UAV, or a swarm working in collaboration, can be a handy and helpful tool for First Responders (FRs) during mission planning, mission monitoring, and the tracking of evolving risks. UAVs, with their on-board sensors, can, among other things, capture visual information of the disaster scene in a safe and quick manner, and generate an up-to-date map of the area. This work presents a system for UAV-assisted mapping optimized for FRs, including the generation of routes for the UAVs to follow, data collection and processing, and map generation. | ||||
Address | Drone Hopper; Drone Hopper; Centre for Research & Technology, CERTH; Centre for Research & Technology, CERTH; Centre for Research & Technology, CERTH; Drone Hopper | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Technologies for First Responders | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | e.caballero@drone-hopper.com | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2381 | ||
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Author | Shivam Sharma; Cody Buntain | ||||
Title | An Evaluation of Twitter Datasets from Non-Pandemic Crises Applied to Regional COVID-19 Contexts | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 808-815 | ||
Keywords | covid19, twitter, trecis, cross-validation, machine learning, transfer learning | ||||
Abstract | In 2020, we have witnessed an unprecedented crisis event, the COVID-19 pandemic. Various questions arise regarding the nature of this crisis data and the impacts it would have on the existing tools. In this paper, we aim to study whether we can include pandemic-type crisis events with general non-pandemic events and hypothesize that including labeled crisis data from a variety of non-pandemic events will improve classification performance over models trained solely on pandemic events. To test our hypothesis we study the model performance for different models by performing a cross validation test on pandemic only held-out sets for two different types of training sets, one containing only pandemic data and the other a combination of pandemic and non-pandemic crisis data, and comparing the results of the two. Our results approve our hypothesis and give evidence of some crucial information propagation upon inclusion of non-pandemic crisis data to pandemic data. | ||||
Address | New Jersey Institute of Technology; New Jersey Institute of Technology | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | cbuntain@njit.edu | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2375 | ||
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Author | Nathan Elrod; Pranav Mahajan; Monica Katragadda; Shane Halse; Jess Kropczynski | ||||
Title | An Exploration of Methods Using Social Media to Examine Local Attitudes Towards Mask-Wearing During a Pandemic | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 345-358 | ||
Keywords | Social media analytics, situational awareness, sentiment analysis, n-grams, social network analysis | ||||
Abstract | During the COVID-19 health crisis, local public offcials expend considerable energy encouraging citizens to comply with prevention measures in order to reduce the spread of infection. During the pandemic, mask-wearing has been accepted among health offcials as a simple preventative measure; however, some local areas have been more likely to comply than others. This paper explores methods to better understand local attitudes towards mask-wearing as a tool for public health offcials' situational awareness when preparing public messaging campaigns. This exploration compares three methods to explore local attitudes: sentiment analysis, n-grams, and hashtags. We also explore hashtag co-occurrence networks as a starting point to begin the filtering process. The results show that while sentiment analysis is quick and easy to employ, the results oer little insight into specific local attitudes towards mask-wearing, while examining hashtags and hashtag co-occurrence networks may be used a tool for a more robust understanding of local areas when attempting to gain situational awareness. | ||||
Address | University of Cincinnati; University of Cincinnati; University of Cincinnati; University of Cincinnati; University of Cincinnati | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
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ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Disaster Public Health & Healthcare Informatics in the Pandemic | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | elrodnj@ucmail.uc.edu | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2338 | ||
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Author | Duygu Pamukcu; Christopher Zobel; Yue Ge | ||||
Title | Analysis of Orange County, Florida 311 System Service Requests During the COVID-19 Pandemic | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 208-217 | ||
Keywords | Disaster management, COVID-19, 311 system, Orlando | ||||
Abstract | The Orlando metropolitan area in Florida, where Walt Disney World is located, is intimately familiar with impacts of natural disasters because of the yearly threat of hurricanes in the southeastern United States. One of the tools that has aided them in their efforts to monitor and manage such disasters is their 311 non-emergency call system, through which local residents can issue requests to the municipality for disaster-related information or other services. This paper provides a preliminary examination of the potential for the Orange County 311 system to provide actionable information to them in support of their efforts to manage a different type of disaster: the COVID-19 pandemic. The potential of the system to support the County in this context is illustrated through several preliminary analyses of the complete set of service requests that were registered in the first ten months of 2020. | ||||
Address | Virginia Tech; Virginia Tech; University of Central Florida | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Analytical Modeling and Simulation | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | duygu@vt.edu | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2326 | ||
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Author | Nada Matta; Thomas Godard; Guillaume Delatour; Ludovic Blay; Franck Pouzet; Audrey Senator | ||||
Title | Analyzing Social Media in Crisis Management Using Expertise Feedback Modelling | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 17-27 | ||
Keywords | Social Media analysis, TextMining, sentiment analysis, crisis management, decision making | ||||
Abstract | Currently social media are largely used in interactions, especially in crisis situations. We note a big volume of interactions around events. Observing these interactions give information even to alert the existence of an incident, event, or to understand the expansion of a problem. Crisis management actors observe social media to be aware about this type of information in order to consider them in their decisions. Specific organizations are founded in order to observe social media interactions and send their analysis to rescue and crisis management actors. In our work, an experience feedback of this type of organizations (VISOV, a crisis social media analysis association) is capitalized in order to emphasize from one side, main dimensions of this analysis and from another side, to simulate some aspects using TextMining that help to explore big volume of data. | ||||
Address | University of Technology of Troyes; University of Technology of Troyes; University of Technology of Troyes; VISOV; CS Group; ENSOSP | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | AI and Intelligent Systems for Crises and Risks | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | nada.matta@utt.fr | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2309 | ||
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Author | Zeno Franco; Chris Davis; Adina Kalet; Michelle Horng; Johnathan Horng; Christian Hernandez; Karen Dotson; Andrew Yaspan; Ajay Kumar; Bas Lijnse | ||||
Title | Augmenting Google Sheets to Improvise Community COVID-19 Mask Distribution | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 359-375 | ||
Keywords | Logistics, face masks, Google Sheets, modular software, community engagement | ||||
Abstract | Face mask scarcity in the United States hindered early infection control efforts during the COVID-19 pandemic. Areas with a history of racial segregation and poverty experienced differential COVID-19 death and morbidity rates. Supplying masks equitably and rapidly became an urgent public health priority. A partnership between a local manufacturer with available polypropylene fabric and the Medical College of Wisconsin, which had the capability to assemble and distribute masks, was formed in April, 2020. An improvised logistics framework allowed for rapid distribution more than 250,000 masks, and later facilitated hand-off to other organizations to distribute over 3 million masks. Using an action research framework three phases of the effort are considered, 1) initial deliveries to community clinics, 2) equitable distribution to community agencies while under “safer at home” orders, and 3) depot deliveries and transfer of logistics management as larger agencies recovered. A multi-actor view was used to interrogate the information needs of faculty and staff remotely directing distribution, medical student volunteers delivering masks, and the manufacturer monitorng overall inventory. Logistics information was managed using Google Sheets augmented with a small SQLite component. A phenomenological view, toggling back and forth from the “socio” to the “technical” provides detailed insight into the strengths and limitations of digital solutions for humanitarian logistics, highlighting where paper-based processes remain more efficient. This case study suggests that rather than building bespoke logistics software, supporting relief efforts with non-traditional responders may benefit from extensible components that augment widely used digital tools. | ||||
Address | Medical College of Wisconsin; Medical College of Wisconsin; Medical College of Wisconsin; Marquette University; Medical College of Wisconsin; Medical College of Wisconsin; Medical College of Wisconsin; Code for Milwaukee; University of Muenster; Netherlan | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Disaster Public Health & Healthcare Informatics in the Pandemic | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | zfranco@mcw.edu | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2339 | ||
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Author | Zijun Long; Richard Mccreadie | ||||
Title | Automated Crisis Content Categorization for COVID-19 Tweet Streams | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 667-678 | ||
Keywords | COVID-19, Tweet Classification, Crisis Management, Deep Learning | ||||
Abstract | Social media platforms, like Twitter, are increasingly used by billions of people internationally to share information. As such, these platforms contain vast volumes of real-time multimedia content about the world, which could be invaluable for a range of tasks such as incident tracking, damage estimation during disasters, insurance risk estimation, and more. By mining this real-time data, there are substantial economic benefits, as well as opportunities to save lives. Currently, the COVID-19 pandemic is attacking societies at an unprecedented speed and scale, forming an important use-case for social media analysis. However, the amount of information during such crisis events is vast and information normally exists in unstructured and multiple formats, making manual analysis very time consuming. Hence, in this paper, we examine how to extract valuable information from tweets related to COVID-19 automatically. For 12 geographical locations, we experiment with supervised approaches for labelling tweets into 7 crisis categories, as well as investigated automatic priority estimation, using both classical and deep learned approaches. Through evaluation using the TREC-IS 2020 COVID-19 datasets, we demonstrated that effective automatic labelling for this task is possible with an average of 61% F1 performance across crisis categories, while also analysing key factors that affect model performance and model generalizability across locations. | ||||
Address | University of Glasgow; University of Glasgow | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | 2452593L@student.gla.ac.uk | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2363 | ||
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Author | Yitong Li; Duoduo Liao; Jundong Li; Wenying Ji | ||||
Title | Automated Generation of Disaster Response Networks through Information Extraction | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 431-438 | ||
Keywords | Disaster response, Stakeholder collaboration, Natural language processing, Network generation | ||||
Abstract | Following a disaster, maintaining and restoring community lifelines require collective efforts from various stakeholders. Aiming at reducing the efforts associated with generating stakeholder collaboration networks (SCNs), this research proposes a systematic approach for reliably extracting stakeholder collaboration information from texts and automatically generating SCNs. In the proposed approach, stakeholders and their interactions are automatically extracted from texts through a natural language processing technique--Named Entity Recognition. Once extracted, the collaboration information is stored into structured datasets to automate the generation of SCNs. A case study on stakeholder collaboration in response to Hurricane Harvey is used to demonstrate the feasibility and applicability of the proposed approach. Overall, the proposed approach achieves the reliable and automated generation of SCNs from texts, which largely reduces practitioners' interpretation loads and eases the data collection process. | ||||
Address | George Mason University; George Mason University; University of Virginia; George Mason University | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Enhancing Resilient Response in Inter-organizational Contexts | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | wji2@gmu.edu | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2344 | ||
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Author | Yohann Chasseray; Anne-Marie Barthe-Delanoë; Stéphane Négny; Jean-Marc Le Lann | ||||
Title | Automated unsupervised ontology population system applied to crisis management domain | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 968-981 | ||
Keywords | Automated knowledge extraction, Crisis management systems, Ontologies, Experience feedback exploitation, Background knowledge acquisition | ||||
Abstract | As crisis are complex systems, providing an accurate response to an ongoing crisis is not possible without ensuring situational awareness. The ongoing works around knowledge management and ontologies provide relevant and machine readable structures towards situational awareness and context understanding. Many metamodels, that can be derived into ontologies, supporting the collect and organization of crucial information for Decision Support Systems have been designed and are now used on specific cases. The next challenge into crisis management is to provide tools that can process an automated population of these metamodels/ontologies. The aim of this paper is to present a strategy to extract concept-instance relations in order to feed crisis management ontologies. The presented system is based on a previously proposed generic metamodel for information extraction and is applied in this paper to three different case studies representing three different crisis namely Ebola sanitarian crisis, Fukushima nuclear crisis and Hurricane Katrina natural disaster. | ||||
Address | Laboratoire de Génie Chimique, Universitéde Toulouse, CNRS, INPT, UPS, Toulouse,France; Centre Génie Industriel, Université deToulouse, IMT Mines Albi, France; Laboratoire de Génie Chimique, Universitéde Toulouse, CNRS, INPT, UPS, Toulouse,France; Laborat | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Visions for Future Crisis Management | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | yohann.chasseray@inp-toulouse.fr | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2389 | ||
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Author | Boris Petrenj; Paolo Trucco | ||||
Title | Blockchain-based Solutions to support inter-organisational Critical Infrastructure Resilience | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 982-993 | ||
Keywords | Critical Infrastructure, Blockchain, Research agenda, Resilience, Capability, Inter-organizational | ||||
Abstract | This conceptual paper critically discusses opportunities for and challenges to the development and exploitation of blockchain-based solutions for resilience management at inter-organizational level of interdependent Critical Infrastructure (CI) systems. The main premise behind this idea is that trustful information-sharing and inter-institutional collaboration are the key elements of government and private sector efforts to build CI resilience (CIR). The discussion presents a vision that the adoption and adaptation of Blockchain Technology (BCT) could significantly improve the way a network of stakeholders prepares for and performs in face of inevitable CI disruptions. Even though BCT is regarded as technological innovation, the impacts go far beyond information systems. BCT application in this domain would entail significant benefits to organizational, managerial, legal and social issues, but would require adequate operational and organizational changes. We discuss how interdisciplinary approach (BCT and CIR) could address existing challenges, how it could introduce new challenges and how it could support other approaches and paradigms currently being regarded as the future of risk and resilience management. Even though the discussion in this paper is focused on Critical Infrastructure resilience, each point also applies to Crisis/Disaster management domain in general. This is a preliminary overview with the aim to stimulate further discussions and point to possible new, disruptive and interdisciplinary research avenues. To this end, a possible research agenda is eventually proposed. | ||||
Address | Politecnico di Milano; Politecnico di Milano | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Visions for Future Crisis Management | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | boris.petrenj@polimi.it | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2390 | ||
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Author | Anmol Haque; Duygu Pamukcu; Ruixiang Xie; Mohsen Zaker Esteghamati; Margaret Cowell; Jennifer L. Irish | ||||
Title | Cascading Effects of Mass Gatherings on COVID-19 Infections from a Multi-hazard Perspective: A Case Study of New York City | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 218-227 | ||
Keywords | COVID-19 pandemic, Mass gatherings, Multi-hazard, Vulnerability | ||||
Abstract | The devastating economic and societal impacts of COVID-19 can be substantially compounded by other secondary events that increase individuals' exposure through mass gatherings such as protests or sheltering due to a natural disaster. Based on the Crichton's Risk Triangle model, this paper proposes a Markov Chain Monte Carlo (MCMC) simulation framework to estimate the impact of mass gatherings on COVID-19 infections by adjusting levels of exposure and vulnerability. To this end, a case study of New York City is considered, at which the impact of mass gathering at public shelters due to a hypothetical hurricane will be studied. The simulation results will be discussed in the context of determining effective policies for reducing the impact of multi-hazard generalizability of our approach to other secondary events that can cause mass gatherings during a pandemic will also be discussed. | ||||
Address | Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech; Virginia Tech | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Analytical Modeling and Simulation | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | anmol91@vt.edu | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2327 | ||
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Author | Stella Polikarpus; Tobias Ley; Katrin Poom-Valickis | ||||
Title | Collaborative Authoring of Virtual Simulation Scenarios for Assessing Situational Awareness | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 229-237 | ||
Keywords | situational awareness (SA), virtual simulation, virtual simulation scenario, process model, Effective Command Behavioral Marker Framework | ||||
Abstract | Situational awareness (SA), the ability to perceive, comprehend and predict situation around you and it is a key in attending any incident as critical foundation for successful decision-making. Because incidents are solitary events, development and assessment of SA presents a significant challenge. In this article we analyze the authoring process of twenty-two scenarios implemented in the XVR on-scene virtual simulation software used to assess rescue incident commanders' (ICs) SA. To allow the scenarios to be used by different assessors, the Collaborative Authoring Process Model for Virtual Simulation Scenarios (CAPM) was developed. In Estonia, 473 assessments were recorded in Effective Command database and analysed by all three levels of SA as recommended by Endsley (2000). Introduction of CAPM resulted in scenarios being re-used by different assessors for authentic SA measuring. In the last sections of this article, we introduce our suggestions to improve virtual scenario design and SA research. | ||||
Address | Tallinn University; Tallinn University; Tallinn University | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Command & Control Studies | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | stella.polikarpus@gmail.com | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2328 | ||
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Author | Aikaterini Christodoulou; John Lioumbas; Kostantinos Zambetoglou; Nikoletta Xanthopoulou | ||||
Title | Combined innovative technologies for ensuring water safety in utilities: The city of Thessaloniki case study | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 929-934 | ||
Keywords | Water safety, satellite images, drones, risk assessment | ||||
Abstract | Innovative technologies such as monitoring the quality of surface water aquifers with satellite images, applying UAV (Unmanned Aerial Vehicle) and drone technology for a variety of operations, water quality measurements with improved techniques along with IoT (Internet of Things) and ICT (Information and Communication Technologies), can provide sufficient data for enhancing water safety in urban water utilities. Specifically, these data could be an effective tool for improving risk assessment process and management of water supply systems. Nevertheless, till now, there is a relative lack of published works that validate the efficiency of combing these technologies on water safety processes by incorporating most of them with a systematic way and during real working conditions in water utilities. This work aims to present the preliminary design concept of a platform that embraces innovating water safety technologies planned to be applied to Thessaloniki's Water Supply and Sewerage Co. S.A Standard Operating Procedures (SOP). | ||||
Address | Thessaloniki Water Supply and Sewerage Co. S.A (EYATH SA); Thessaloniki Water Supply and Sewerage Co. S.A (EYATH SA); Thessaloniki Water Supply and Sewerage Co. S.A (EYATH SA); Thessaloniki Water Supply and Sewerage Co. S.A (EYATH SA) | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Technologies for First Responders | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | catchristo@eyath.gr | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2385 | ||
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Author | Hongmin Li; Doina Caragea; Cornelia Caragea | ||||
Title | Combining Self-training with Deep Learning for Disaster Tweet Classification | Type | Conference Article | ||
Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
Volume | Issue | Pages | 719-730 | ||
Keywords | Domain Adaptation, Self-training, Crisis Tweets Classification, BERT, CNN | ||||
Abstract | Significant progress has been made towards automated classification of disaster or crisis related tweets using machine learning approaches. Deep learning models, such as Convolutional Neural Networks (CNN), domain adaptation approaches based on self-training, and approaches based on pre-trained language models, such as BERT, have been proposed and used independently for disaster tweet classification. In this paper, we propose to combine self-training with CNN and BERT models, respectively, to improve the performance on the task of identifying crisis related tweets in a target disaster where labeled data is assumed to be unavailable, while unlabeled data is available. We evaluate the resulting self-training models on three crisis tweet collections and find that: 1) the pre-trained language model BERTweet is better than the standard BERT model, when fine-tuned for downstream crisis tweets classification; 2) self-training can help improve the performance of the CNN and BERTweet models for larger unlabeled target datasets, but not for smaller datasets. | ||||
Address | Department of Computer Science, Kansas State University; Department of Computer Science, Kansas State University; Department of Computer Science, University of Illinois at Chicago | ||||
Corporate Author | Thesis | ||||
Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
Language | English | Summary Language | English | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | hongminli@ksu.edu | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2367 | ||
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