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Author |
Gonzalez, J.J.; Eden, C. |
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Title |
Devising Mitigation Strategies With Stakeholders Against Systemic Risks in a Pandemic |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the 20th International ISCRAM Conference |
Abbreviated Journal |
Iscram 2023 |
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Volume |
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Pages |
1000-1013 |
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Keywords |
Systemic Risk, Cascading Effects; Participatory Modelling; Strategy Mapping; Vicious Cycles; Risk System Analysis; Risk Mitigation. |
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Abstract |
Understanding and managing systemic risk has huge importance for disaster risk reduction in our globally connected world. The COVID-19 pandemic is a prominent case for the global impact of systemic risk. Did so the added urgency of the pandemic systemic risk trigger such paradigm shift? The use of qualitative modelling of systemic risk has progressed the field, particularly when policy makers need support urgently and want to utilize a range of interdisciplinary expertise. We have extended to disaster risk reduction a method for causal mapping for problem solving and strategy development targeting complex project management. Our approach delivers useful, useable, and used mitigation to systemic risk in a pandemic using participatory modelling with practitioners, domain experts and power-brokers. |
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Department of ICT, Faculty of Engineering and Science, Centre for Integrated Emergency Management (CIEM), University of Agder; Strathclyde Business School |
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Publisher |
University of Nebraska at Omaha |
Place of Publication |
Omaha, USA |
Editor |
Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi |
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Language |
English |
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Series Editor |
Hosssein Baharmand |
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Edition |
1 |
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Track |
Open Track |
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http://dx.doi.org/10.59297/ALXR6340 |
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no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2583 |
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Author |
Edjossan-Sossou, A.; Selouane, K.; Sayah, M.A.; Ouabou, M.; Vignote, C.; Capitaine, M.; Soto, D.; Edelblutte, E. |
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Title |
An innovative scenario-based modeling tool for the management of resilient water resources |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the 20th International ISCRAM Conference |
Abbreviated Journal |
Iscram 2023 |
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Volume |
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Issue |
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Pages |
808-821 |
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Keywords |
Climate Change; Resilience Performance Assessment; Water Resources Management; Scenario-Based Analysis; Predictive Modelling |
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Abstract |
As freshwater availability for domestic and agro-industrial uses is highly sensitive to climate change, there is an urgent need for the management of this critical resource to be resilient, i.e., to cope with and rapidly recover from climate risks. To achieve this resilient goal, decision-makers need to have a comprehensive understanding of (i) the current and future local water resources, (ii) the ways these resources are and will be impacted by climate change, and (iii) the effects their management decisions can have. In this paper, we present an innovative scenario based modeling tool that help decision-makers make the most appropriate decision towards managing water resources: the Resilience Performance Assessment (RPA). This GIS-based decision support tool illustrates the current and future effects of climate change on local water resources and simulates the outcomes of different water resources management strategies. The RPA helps guide decision-makers towards the implementation of context specific adaptation strategies. |
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Publisher |
University of Nebraska at Omaha |
Place of Publication |
Omaha, USA |
Editor |
Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
Hosssein Baharmand |
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Series Issue |
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Edition |
1 |
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Track |
Geospatial Technologies, Location Analytics, and Geographic Information Science |
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Notes |
http://dx.doi.org/10.59297/AHXP6903 |
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no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2568 |
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Author |
Pettersson, M.N.; Axelsson, J.; Svenson, P.; Johansson, A. |
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Title |
Towards a Risk Analysis Method for Systems of Systems: A Case Study on Wildfire Rescue Operations |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the 20th International ISCRAM Conference |
Abbreviated Journal |
Iscram 2023 |
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Volume |
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Issue |
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Pages |
530-545 |
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Keywords |
Systems of Systems; Risk Analysis Methods, Case Study, Wildfire, STAMP. Crisis Management |
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Abstract |
Crisis management (CM) is facing new challenges due to the increasing complexity of contemporary society. To mitigate a crisis, it is often necessary for a collection of independent systems, people, and organizations to cooperate. These collaborating entities constitute an interconnected socio-technical system of systems (SoS). An important question is how a CM SoS should be constructed to minimize the risk of failure and accurately handle a crisis. SoS pose new challenges in analysing risk during interactions. This paper investigates whether the risk analysis method STAMP (System-Theoretic Accident Model and Processes) is suitable for SoS, using a forest fire rescue operation case study. Results show characteristics of various risk sources and identify some SoS characteristics, such as dynamic structure and latent risks, that are not sufficiently handled in STAMP. The study further contributes to the body of knowledge by presenting potential directions for research on SoS risk assessment methods. |
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Address |
Mälardalen University; Research Institutes of Sweden |
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Publisher |
University of Nebraska at Omaha |
Place of Publication |
Omaha, USA |
Editor |
Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
Hosssein Baharmand |
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Series Issue |
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Edition |
1 |
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Track |
Analytical Modeling and Simulation |
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Conference |
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Notes |
http://dx.doi.org/10.59297/SFUF2569 |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2545 |
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Author |
Lamsal, R.; Read, M.R.; Karunasekera, S. |
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Title |
A Twitter narrative of the COVID-19 pandemic in Australia |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the 20th International ISCRAM Conference |
Abbreviated Journal |
Iscram 2023 |
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Volume |
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Issue |
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Pages |
353-370 |
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Keywords |
Crisis Informatics; Situational Awareness; Topic Modeling; Granger Causality; Network Analysis |
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Abstract |
Social media platforms contain abundant data that can provide comprehensive knowledge of historical and real-time events. During crisis events, the use of social media peaks, as people discuss what they have seen, heard, or felt. Previous studies confirm the usefulness of such socially generated discussions for the public, first responders, and decision-makers to gain a better understanding of events as they unfold at the ground level. This study performs an extensive analysis of COVID-19-related Twitter discussions generated in Australia between January 2020, and October 2022. We explore the Australian Twitterverse by employing state-of-the-art approaches from both supervised and unsupervised domains to perform network analysis, topic modeling, sentiment analysis, and causality analysis. As the presented results provide a comprehensive understanding of the Australian Twitterverse during the COVID-19 pandemic, this study aims to explore the discussion dynamics to aid the development of future automated information systems for epidemic/pandemic management. |
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Address |
The University of Melbourne |
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Publisher |
University of Nebraska at Omaha |
Place of Publication |
Omaha, USA |
Editor |
Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
Hosssein Baharmand |
Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
1 |
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Track |
Social Media for Crisis Management |
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Conference |
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Notes |
http://dx.doi.org/10.59297/GQED8281 |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2531 |
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Author |
Guillermo Romera Rodriguez |
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Title |
Parler, Capitol Riots, Alt-Right and Radicalization in Social Media |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the ISCRAM Asia Pacific Conference 2022 |
Abbreviated Journal |
Proc. ISCRAM AP 2022 |
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Issue |
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Pages |
268-277 |
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Keywords |
Social Media; Parler; Sentiment Analysis; Alt-Right |
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Abstract |
Social media platforms have risen in popularity since their inception. These platforms have since then come to be at the forefront of controversies, from being accused of election interference to, more recently, disseminating fake news and campaigns to sway political behavior. One such episode took place on January 6 when a group of individuals stormed the United States Capitol, and the social media platform Parler came under scrutiny. The platform was accused of being a place for right-wing extremists and Trump supporters who claimed the 2020 election was fraudulent. Initial reports suggested these individuals used Parler to organize and call others to action. This paper explores the feasibility of using social media to detect alt-right radicalization and examines its possible relation to the Capitol Insurrection and Parler. Moreover, we examine if those events could have been detected and averted through the investigation of the platform. |
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Pennsylvania State University; Pennsylvania State University; Pennsylvania State University |
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Publisher |
Massey Unversity |
Place of Publication |
Palmerston North, New Zealand |
Editor |
Thomas J. Huggins, V.L. |
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Language |
English |
Summary Language |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-0-473-66845-7 |
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Track |
Social Media for Disaster Response |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2500 |
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Author |
Marion Lara Tan; Oshada Senaweera; Asanka Gunawardana; Mohamed Rasith; Mohamed Suaib; Theepika Shanthakumar; Miznath Hisham |
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Title |
New Zealand COVID Tracer App: Understanding Usage and User Sentiments |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the ISCRAM Asia Pacific Conference 2022 |
Abbreviated Journal |
Proc. ISCRAM AP 2022 |
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Issue |
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Pages |
89-102 |
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Keywords |
Mobile Apps; COVID-19 Response; Sentiment Analysis; User Reviews; App Store Data |
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Abstract |
The NZ COVID Tracer app is a part of Aotearoa New Zealand (NZ) Government’s strategy to manage the COVID-19 pandemic. This paper investigates people’s usage and sentiment on the app from its release in May 2020 to the end of 2021. Descriptive analysis of app data and sentiment analysis on user review data were used. The results show that before March 2021, the overall sentiment on the app was negative but gradually improved over time. The passive Bluetooth-tracing feature is utilised more consistently than the anual features. However, the increased proportion of positive sentiments is seen to increase with active app use. Results highlight the consistency of the Bluetooth-tracing feature but do not discredit the importance of manual interaction, as active use can improve the perception of the app. Insights from this study will be helpful as apps adapt to the changing context of the ongoing COVID-19 pandemic. |
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Address |
Massey University; University of Colombo; University of Moratuwa; University of Moratuwa; University of Moratuwa; University of Moratuwa; University of Moratuwa |
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Publisher |
Massey Unversity |
Place of Publication |
Palmerston North, New Zealand |
Editor |
Thomas J. Huggins, V.L. |
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Language |
English |
Summary Language |
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Series Volume |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-0-473-66845-7 |
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Track |
Healthcare During Emergencies and COVID-19 |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2483 |
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Author |
Carolyn Huston; Jennifer Davis; Petra Kuhnert; Andrew Bolt |
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Title |
Creating Trusted Extensions to Existing Software Tools in Bushfire Consequence Estimation |
Type |
Conference Article |
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Year |
2023 |
Publication |
Proceedings of the ISCRAM Asia Pacific Conference 2022 |
Abbreviated Journal |
Proc. ISCRAM AP 2022 |
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Pages |
25-34 |
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Keywords |
Wildfires; Trustworthiness; Optimal Decisions; Affordance Analysis; Emulation |
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Abstract |
Bushfire modelling has advanced with wildfire simulators such as Spark and Phoenix Rapidfire that can generate plausible fire dynamics and simulations that decision-makers can easily explore. With extreme weather impacting the Australian landscapes through the onset of droughts and heatwaves, it is becoming more important to make decisions rapidly from fire simulations. An element of this decision-making process is trust, in which the decision-maker feels empowered to make decisions from models of complex systems like fire. We propose a framework for decision-making that makes use of a fire emulator, a surrogate version of Spark, to facilitate faster exploration of wildfire predictions and their uncertainties under a changing climate. We discuss the advantages and next steps of an emulator model using the mechanisms and conditions framework, a powerful vocabulary and design framework that builds in trust to allow users of a technology to understand and accept the features of a system. |
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Address |
CSIRO Data61; Australia National University; CSIRO Data61; CSIRO Data61 |
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Publisher |
Massey Unversity |
Place of Publication |
Palmerston North, New Zealand |
Editor |
Thomas J. Huggins, V.L. |
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Language |
English |
Summary Language |
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ISSN |
2411-3387 |
ISBN |
978-0-473-66845-7 |
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Track |
Analytical Modelling and Simulation |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2477 |
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Author |
Savannah Thais; Shaine Leibowitz; Allie Saizan; Ashay Singh |
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Title |
Understanding Historical, Socio-Economic, and Policy Contributions to COVID-19 Health Inequities |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Issue |
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Pages |
481-494 |
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Keywords |
Public Health; COVID-19; Economic Impact; Mobile Health; Unsupervised Learning; Longitudinal Analysis; Community Vulnerability Index; Proxy Outcomes; Health Policy; Social Determinants of Health; Equity |
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Abstract |
The COVID-19 pandemic has generated unprecedented, devastating impacts across the United States. However, some communities have disproportionately endured adverse health outcomes and socioeconomic injuries. Ascertaining the factors driving these inequities is crucial to determining how policy could mitigate the impacts of future public health crises. We have established research-driven metrics, aggregated as the Community Vulnerability Index (CVI), that quantify vulnerability to public health and economic impacts of COVID-19. We performed two analyses to better understand similarities between communities in terms of the vulnerabilities represented by the metrics. We performed an unsupervised k-means clustering analysis to understand whether communities can be grouped together based on their levels of negative social and health indicators. Our goal for this analysis is to determine whether attributes of the constructed clusters reveal areas of opportunity for potential policy impacts and future disaster response efforts. We also analyzed similarities between communities across time using time-sensitive clustering analysis to discover whether historical community vulnerabilities were persistent in the years preceding the pandemic and to better understand the historical factors associated with disparate COVID-19 impacts. In particular, we highlight where communities should invest based on their historical health and socioeconomic patterns and related COVID impacts. Through extensive interpretation of our findings, we uncover how health policy can advance equity and improve community resilience. |
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Princeton University; Community Insight and Impact; Community Insight and Impact; Community Insight and Impact |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
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Track |
Data and Resilience: Opportunities and Challenges |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2434 |
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Author |
Eulalia Gomez Martin; Josune Hernantes; Leire Labaka; Marcos Borges |
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Title |
Building upon the Existing Knowledge: Updating and Improving the Smart Mature Resilience Model |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Pages |
437-459 |
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Keywords |
Resilience dimensions; bibliometric analysis; urban resilience; framework |
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Abstract |
In recent years the concept of urban resilience has acquired great relevance within urban planning. The complexity of urban systems and the wide scope of the resilience concept require tools to facilitate the integration of the concept in urban development. Numerous studies, tools, and theoretical frameworks have been developed to support the resilient transformation of cities. However, these initiatives are usually not holistically integrated and limit incorporating the changes and advances in the resilience concept. This article highlights the importance of shifting from a continuously-building-new approach to building on an existing knowledge approach. This study has updated and improved the maturity model developed within the Horizon 2020 project Smart Mature Resilience. A bibliometric analysis was carried out to study the developments in resilience over the past four years and to integrate the relevant advances in the area into a new version of the Smart Mature Resilience Maturity Model (SMR MM). |
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Address |
University of Navarra; University of Navarra; University of Navarra; University of Navarra |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
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Track |
Data and Resilience: Opportunities and Challenges |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2431 |
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Author |
Viktor Sköld Gustafsson; Tobias Andersson Granberg; Sofie Pilemalm; Martin Waldemarsson |
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Title |
Managing Natural Hazards in Sweden – Needs for Improved Information and Decision Support Systems |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Pages |
376-384 |
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Keywords |
Emergency response; extreme weather events; command and control; needs analysis |
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Abstract |
This paper explores opportunities for information systems to support emergency response to multiple natural hazards. Interviews were conducted with 12 representatives from actors of the Swedish emergency response system about response to multiple natural hazards. Challenges and needs connected to five themes influencing the response effort were identified: Cooperation, Resource management, Command and control, Common operational picture, and Risk management. The results illuminate a lack of technology to support decisions and analyses during emergency response to both single and multiple natural hazards. Based on this, the paper suggests and discusses information systems and decision support tools to assist in satisfying the identified needs. The findings can inform policy makers in emergency response of where to concentrate the development of collaborative preparedness and response work, and the scientific community of future research directions. |
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Address |
Linköping University; University of Agder |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
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Track |
Command and Control Studies |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2425 |
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Author |
Cendrella Chahine; François Peres; Thierry Vidal; Mohamad El Falou |
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Title |
Functional and Dysfunctional Modelling and Assessment of an Emergency Response Plan |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Volume |
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Issue |
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Pages |
363-375 |
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Keywords |
Crisis management; risk analysis; FMECA; BPMN; emergency response plan |
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Abstract |
The objective of crisis management is to limit the impact of a feared event that has occurred and to restore the conditions corresponding to a nominal situation. In this context, we will focus on emergency response plans for mass casualty crises. In this paper, we propose a functional modelling of the French generic emergency plan, ORSEC plan, using the Business Process Model and Notation (BPMN). On the basis of this representation, a dysfunctional analysis is performed from a new approach identifying Failure mode, effects and criticality analysis (FMECA), in order to better anticipate, the events likely to interrupt the intervention plan. This work will then be used in a multi-agent dynamic planning and scheduling model to allow an actor to choose among the dynamic planning approaches the one that allows him/her to reach his/her goal. |
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Address |
ULF Liban/LGP-ENIT |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
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Track |
Command and Control Studies |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2424 |
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Author |
Ayda Kianmehr; Duygu Pamukcu |
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Title |
Analyzing Citizens’ Needs during an Extreme Heat Event, based on 311 Service Requests: A Case Study of the 2021 Heatwave in Vancouver, British Columbia |
Type |
Conference Article |
|
Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Volume |
|
Issue |
|
Pages |
174-182 |
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Keywords |
Extreme heat; 311 calls; weather-related variables; time-series analysis; hazard preparedness |
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Abstract |
Heat waves are becoming more common and intense with global climate change, which requires deploying resilience strategies of governments to prepare for long-term trends of higher temperatures and carefully plan emergency responses for such extreme heat events. The British Columbia province of Canada is one of the regions severely affected by extreme climatic events in 2021, which resulted in several deaths and put hundreds of thousands of people scrambling for relief. This study examines the public reactions to one of these extreme climatic events, the 2021 Pacific Northwest heatwave, in a non-emergency service request platform to uncover the types of municipal service needs during severe climatic disasters. City of Vancouver 311 system data is used to identify the impact of the heatwave on the frequency and types of service needs and examine the significance of the relationship between climatic conditions and the non-emergency service volumes. |
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Address |
Virginia Tech; Virginia Tech |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
Medium |
|
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Track |
Analytical Modeling and Simulation |
Expedition |
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Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2408 |
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Author |
Duygu Pamukcu; Christopher Zobel; Yue Ge |
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Title |
A Data Envelopment Analysis-based Approach for Managing Performance of Public Service Systems During a Disaster |
Type |
Conference Article |
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Year |
2022 |
Publication |
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2022 |
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Volume |
|
Issue |
|
Pages |
144-153 |
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Keywords |
Performance measurement; Efficiency; Data Envelopment Analysis; 311; Public Service |
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Abstract |
In addition to their normal task of supporting community participation, engagement, and improved information access, information technology-based public service systems are also essential for maintaining critical services and providing effective communication with citizens before, during, and after emergencies. This study focuses on the impacts of disaster events on the operational performance of such service systems and discusses opportunities for managing service efficiency by rearranging and reallocating resources during emergencies. To the best of our knowledge, this is the first attempt to provide a practical method for improving the relative efficiency of public service systems in such a context. We suggest a Data Envelopment Analysis (DEA) approach for quantifying the relative efficiencies associated with service requests from an input-output-based standpoint, and discuss the Orange County (Florida) 311 non-emergency service system, in the context of the COVID-19 pandemic, as an example of how such operational efficiency can be managed during a disruption. |
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Address |
Virginia Tech; Virginia Tech; University of Central Florida |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
Tarbes, France |
Editor |
Rob Grace; Hossein Baharmand |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-82-8427-099-9 |
Medium |
|
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Track |
Analytical Modeling and Simulation |
Expedition |
|
Conference |
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Notes |
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Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2405 |
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Author |
Jaziar Radianti; Terje Gjøsæter; Weiqin Chen |
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Title |
Slaying the SA Demons – Humans vs. Technology – A Content Analysis |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
946-958 |
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Keywords |
situation awareness, SA Demons, crisis management, human error, universal design, content analysis |
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Abstract |
In this paper, we examine Situation Awareness (SA) and the application of Endsley's Demons of SA in different contexts and research areas and perform content analysis to examine how they are used, and to what degree they are perceived as stemming from human error or weaknesses in technology and if any suggestions for mitigation are primarily focused on the human or the technology side. Based on our findings, we propose universal design as a tool that can counter the effects of the demons of SA by improving the usability and accessibility of SA-supporting technology and thereby removing barriers to SA, rather than challenging the users to overcome not only barriers that are a result of the complexity of the situation itself, but also additional barriers that are caused by inferior and suboptimal design of the technology in use. |
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Address |
University of Agder; University of Agder; Oslo Metropolitan University |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Usability and Universal Design of ICT for Emergency Management |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
jaziar.radianti@uia.no |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2387 |
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Author |
Lennart Landsberg; Alexandra Braun; Ompe Aimé Mudimu; Klaus-Dieter Büttgen |
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Title |
Considering end user needs when developing new technologies – a new plug and play sensor technology for locating trapped victims |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
922-928 |
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Keywords |
Search and Rescue, UAV, Multi Sensors, Requirement Analysis, Building Collapse |
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Abstract |
Building collapses often happen unexpectedly and suddenly. Consequently, people are often buried under the debris. What follows is a complicated search by first responders, which is characterized by time pressure and danger. In the research project SORTIE, a modular and UAV-based technical system is being developed to support the first responders in their search efforts. During the first phase of this project, an extensive requirements analysis was conducted with the involvement of end users. This ensures that the developed technology meets the requirements for later use under realistic circumstance. The project consortium has good experience with this operational approach and is in close cooperation with end users who are part of the consortium. In addition to a comprehensive understanding of building collapses and prevailing conditions, the technical partners were also able to identify requirements that they might not have discovered without the involvement of end users and the appropriate methods. |
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Address |
TH Köln – University of Applied Sciences; Federal Agency for Technical Relief; TH Köln – University of Applied Sciences; Federal Agency for Technical Relief |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Technologies for First Responders |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
lennart_walter.landsberg@th-koeln.de |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2384 |
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Author |
Antone Evans Jr.; Yingyuan Yang; Sunshin Lee |
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Title |
Towards Predicting COVID-19 Trends: Feature Engineering on Social Media Responses |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
792-807 |
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Keywords |
Big Data Analysis, Machine Learning, COVID-19, Twitter |
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Abstract |
During the course of this pandemic, the use of social media and virtual networks has been at an all-time high. Individuals have used social media to express their thoughts on matters related to this pandemic. It is difficult to predict current trends based on historic case data because trends are more connected to social activities which can lead to the spread of coronavirus. So, it's important for us to derive meaningful information from social media as it is widely used. Therefore, we grouped tweets by common keywords, found correlations between keywords and daily COVID-19 statistics and built predictive modeling. The features correlation analysis was very effective, so trends were predicted very well. A RMSE score of 0.0425504, MAE of 0.03295105 and RSQ of 0.5237014 in relation to daily deaths. In addition, we found a RMSE score of 0.07346836, MAE of 0.0491152 and RSQ 0.374529 in relation to daily cases. |
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Address |
University of Illinois Springfield; University of Illinois Springfield; University of Illinois Springfield |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Social Media for Disaster Response and Resilience |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
aevan7@uis.edu |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2374 |
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Author |
Valentin Barriere; Guillaume Jacquet |
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Title |
How does a Pre-Trained Transformer Integrate Contextual Keywords? Application to Humanitarian Computing |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
766-771 |
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Keywords |
Transformers, Contextual keywords, Humanitarian Computing, Tweets analysis |
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Abstract |
In a classification task, dealing with text snippets and metadata usually requires to deal with multimodal approaches. When those metadata are textual, it is tempting to use them intrinsically with a pre-trained transformer, in order to leverage the semantic information encoded inside the model. This paper describes how to improve a humanitarian classification task by adding the crisis event type to each tweet to be classified. Based on additional experiments of the model weights and behavior, it identifies how the proposed neural network approach is partially over-fitting the particularities of the Crisis Benchmark, to better highlight how the model is still undoubtedly learning to use and take advantage of the metadata's textual semantics. |
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Address |
European Commission's Joint Research Center; European Commission's Joint Research Center |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Social Media for Disaster Response and Resilience |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
valbarrierepro@gmail.com |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2371 |
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Author |
Congcong Wang; Paul Nulty; David Lillis |
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Title |
Transformer-based Multi-task Learning for Disaster Tweet Categorisation |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
705-718 |
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Keywords |
Disaster Response, Tweet Analysis, Transformers, Natural Language Processing |
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Abstract |
Social media has enabled people to circulate information in a timely fashion, thus motivating people to post messages seeking help during crisis situations. These messages can contribute to the situational awareness of emergency responders, who have a need for them to be categorised according to information types (i.e. the type of aid services the messages are requesting). We introduce a transformer-based multi-task learning (MTL) technique for classifying information types and estimating the priority of these messages. We evaluate the effectiveness of our approach with a variety of metrics by submitting runs to the TREC Incident Streams (IS) track: a research initiative specifically designed for disaster tweet classification and prioritisation. The results demonstrate that our approach achieves competitive performance in most metrics as compared to other participating runs. Subsequently, we find that an ensemble approach combining disparate transformer encoders within our approach helps to improve the overall effectiveness to a significant extent, achieving state-of-the-art performance in almost every metric. We make the code publicly available so that our work can be reproduced and used as a baseline for the community for future work in this domain. |
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Address |
University College Dublin; University College Dublin; University College Dublin |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Social Media for Disaster Response and Resilience |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
wangcongcongcc@gmail.com |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2366 |
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Author |
Jose J. Gonzalez; Colin Eden; Eirik Abildsnes; Martin Hauge; Monica Trentin; Luca Ragazzoni; Peter Berggren; Carl-Oscar Jonson; Ahmed A. Abdelgawad |
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Title |
Elicitation, analysis and mitigation of systemic pandemic risks |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
581-596 |
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Keywords |
Systemic risk, Cascading effects, Vicious cycles, Risk system analysis, Risk mitigation |
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Abstract |
The Covid-19 pandemic has disrupted the health care system and affected all sectors of society, including critical infrastructures. In turn, the impact on society's infrastructures has impacted back on the health care sector. These interactions have created a system of associated risks and outcomes, where the outcomes of risks are risks themselves and where the resulting consequences are complex vicious cycles. Traditional risks assessment methods cannot cope with interdependent risks. This paper describes a novel risk systemicity approach to elicit and mitigate the systemic risks of a major pandemic. The approach employed the internet-based software strategyfinder[TM] in workshops to elicit relevant risk information from sixteen appropriately selected experts from the health care sector and major sectors impacted by and impacting back on the health care sector. The risk information was processed with powerful analytical tools of strategyfinder to allow the experts to prioritise portfolios of strategies attacking the vicious cycles. |
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Address |
Centre for Integrated Emergency Management (CIEM), University of Agder; Strathclyde Business School, Glasgow; University of Agder, Dep. of psychosocial health and Kristiansand municipality, Dep. of research and innovation; Sørlandet Sykehus HF; Center for |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Planning, Foresight and Risk Analysis |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
jose.j.gonzalez@uia.no |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2357 |
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Author |
Nathan Elrod; Pranav Mahajan; Monica Katragadda; Shane Halse; Jess Kropczynski |
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Title |
An Exploration of Methods Using Social Media to Examine Local Attitudes Towards Mask-Wearing During a Pandemic |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
345-358 |
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Keywords |
Social media analytics, situational awareness, sentiment analysis, n-grams, social network analysis |
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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. |
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Address |
University of Cincinnati; University of Cincinnati; University of Cincinnati; University of Cincinnati; University of Cincinnati |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Disaster Public Health & Healthcare Informatics in the Pandemic |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
elrodnj@ucmail.uc.edu |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2338 |
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Author |
Alexander Gabriel; Babette Tecklenburg; Yann Guillouet; Frank Sill Torres |
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Title |
Threat analysis of offshore wind farms by Bayesian networks – a new modeling approach |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
174-185 |
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Keywords |
Threat analysis, Bayesian networks, process modeling, Critical infrastructurs |
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Abstract |
As a result of the ongoing commitment to climate protection in more and more countries and the corresponding expansion of renewable energies, the importance of renewables for the security of electricity supply is also increasing. Wind energy generated in offshore wind farms already accounts for a significant share of the energy mix and will continue to grow in the future. Therefore, approaches and models for security assessment and protection against threats are also needed for these infrastructures. Due to the special characteristics and geographical location of offshore wind farms, they are confronted with particular challenges. In this context, this contribution outlines how an approach for threat analysis of offshore wind farms is to be developed within the framework of the new research project “ARROWS” of the German Aerospace Center. The authors first explain the structure of offshore wind farms and then present a possible modeling approach using Qualitative function models and Bayesian networks. |
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Address |
German Aerospace Center – Institute for the Protection of Maritime Infrastructures; German Aerospace Center – Institute for the Protection of Maritime Infrastructures; German Aerospace Center – Institute for the Protection of Maritime Infrastructures; Ger |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
Analytical Modeling and Simulation |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
Alexander.Gabriel@dlr.de |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2323 |
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Author |
Nada Matta; Thomas Godard; Guillaume Delatour; Ludovic Blay; Franck Pouzet; Audrey Senator |
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Title |
Analyzing Social Media in Crisis Management Using Expertise Feedback Modelling |
Type |
Conference Article |
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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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Volume |
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Issue |
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Pages |
17-27 |
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Keywords |
Social Media analysis, TextMining, sentiment analysis, crisis management, decision making |
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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. |
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Address |
University of Technology of Troyes; University of Technology of Troyes; University of Technology of Troyes; VISOV; CS Group; ENSOSP |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-61-5 |
ISBN |
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Medium |
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Track |
AI and Intelligent Systems for Crises and Risks |
Expedition |
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Conference |
18th International Conference on Information Systems for Crisis Response and Management |
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Notes |
nada.matta@utt.fr |
Approved |
no |
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Call Number |
ISCRAM @ idladmin @ |
Serial |
2309 |
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Author |
Daniel Lichte; Dustin Witte; Kai-Dietrich Wolf |
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Title |
Comprehensive Security Hazard Analysis for Transmission Systems |
Type |
Conference Article |
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Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Volume |
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Issue |
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Pages |
1145-1153 |
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Keywords |
Physical Security; Energy Transmission Systems; Scenario Analysis; Threat Analysis; Risk Assessment |
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Abstract |
Critical energy infrastructures are more and more focused upon by politics and society. Modern society depends on these structures, since they enable the steady support of electricity and other types of energy. Deliberately precipitated hazards of certain critical parts of electrical transmission systems (ETS) can lead to catastrophic consequences. Therefore, the analysis of feasible security hazards and resulting consequences for the operation of transmission systems are a concern to transmission system operators (TSO). Alas, there is no common method available that comprehensively identifies these feasible security related scenarios and classifies them according to their overall criticality for the safe operation of the ETS. To tackle this challenge, we propose a comprehensive, yet easy-to-apply method to systematically identify and assess the criticality of security threat scenarios. It is conducted in four steps and consists of a matrix based consistency check of threat scenarios in a defined solution space and a convenient semi-quantitative assessment of a risk factor for the ETS. The approach is illustrated by the simplified generic example of an EETS. |
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Address |
German Aerospace Center; University of Wuppertal; University of Wuppertal |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-27-104 |
ISBN |
2411-3490 |
Medium |
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Track |
Open Track |
Expedition |
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Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
daniel.lichte@dlr.de |
Approved |
no |
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Call Number |
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Serial |
2305 |
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Author |
Anne-Marie Barthe-Delanoë; Wenxin Mu |
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Title |
Towards a Context-Aware Systemic Risk Management Framework for the Crisis Response |
Type |
Conference Article |
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Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Volume |
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Issue |
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Pages |
1122-1129 |
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Keywords |
Context-Awareness; Risk Analysis; Risk Evaluation; Knowledge Base; Systemic Risk |
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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. |
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Address |
Laboratoire de Génie Chimique, Université de Toulouse, CNRS, INPT, UPS, Toulouse, France; Department of Information Management, Jiao Tong University, Beijing, China |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-27-101 |
ISBN |
2411-3487 |
Medium |
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Track |
Visions for Future Crisis Management |
Expedition |
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Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
annemarie.barthe@ensiacet.fr |
Approved |
no |
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Call Number |
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Serial |
2302 |
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Author |
Anastasia Moumtzidou; Marios Bakratsas; Stelios Andreadis; Anastasios Karakostas; Ilias Gialampoukidis; Stefanos Vrochidis; Ioannis Kompatsiaris |
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Title |
Flood detection with Sentinel-2 satellite images in crisis management systems |
Type |
Conference Article |
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Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Volume |
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Issue |
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Pages |
1049-1059 |
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Keywords |
Floods, Change Detection, Bi-temporal Analysis, Sentinel-2, Deep Neural Networks. |
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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. |
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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; |
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Corporate Author |
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Thesis |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
978-1-949373-27-95 |
ISBN |
2411-3481 |
Medium |
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Track |
Using Artificial Intelligence to exploit Satellite Data in Risk and Crisis Management |
Expedition |
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Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
moumtzid@iti.gr |
Approved |
no |
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Call Number |
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Serial |
2296 |
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