| Home | << 1 >> |
|
| Records | |||||
|---|---|---|---|---|---|
Author  |
Anne Marie Barthe; Sabine Carbonnel; Frédérick Bénaben; Hervé Pingaud | ||||
| Title | Event-driven agility of crisis management collaborative processes | Type | Conference Article | ||
| Year | 2012 | Publication | ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2012 |
| Volume | Issue | Pages | |||
| Keywords | Error detection; Information services; Service oriented architecture (SOA); Web services; Adaptation; Agility; Collaborative process; Complex event processing (CEP); Event-driven architectures; Eventdriven architecture (EDA); Information systems interoperability; Model driven architectures; Information systems | ||||
| Abstract | This article aims at presenting a whole approach of Information Systems interoperability management in a crisis management cell. We propose a Mediation Information System (MIS) to help the crisis cell partners to design, run and manage the workflows of the response to a crisis situation. The architecture of the MIS meets the need of low coupling between the partners' Information System components and the need of agility for a such platform. Based on the Service Oriented Architecture (SOA) and the Event Driven Architecture (EDA) principles which, combined to the Complex Event Processing (CEP) principles, it will leads to an easier orchestration, choreography and real-time monitoring of the workflows' activities, and even allows the automated agility of the crisis response on-the-fly-we consider agility as the ability of the processes to remain consistent with the response to the crisis-. © 2012 ISCRAM. | ||||
| Address | Université de Toulouse, Mines Albi, France | ||||
| Corporate Author | Thesis | ||||
| Publisher | Simon Fraser University | Place of Publication | Vancouver, BC | Editor | L. Rothkrantz, J. Ristvej, Z.Franco |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9780864913326 | Medium | |
| Track | Event-Driven Techniques and Methods for Crisis Management | Expedition | Conference | 9th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 79 | |||
| Share this record to Facebook | |||||
| Author |
Bruna Diirr; Marcos Borges; David Mendonça | ||||
| Title | Putting plans on track in unforeseen situations | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Disruption diagnosis; emergency response; On-the-fly adaptation; Plan revision | ||||
| Abstract | The dynamically evolving environment of the post-disaster scene?where unpredictable scenarios and uncertain data are commonplace?can bring about considerable complexity into response tasks. The multiplicity and interdependence of approaches to undertaking these tasks may yield many decision alternatives, further complicating the response effort. Additionally, because emergencies are evolving, expectations regarding the post-disaster scene may not match those that are actually encountered. Plans compiled before the disaster may therefore be judged as inadequate, requiring personnel to adjust or even redefine them during the response activities. This paper outlines and illustrates one approach?drawing upon the paradigm of improvisation?for providing management-level response personnel with information and tools to support on-the-fly adaptation of emergency response plans. A case study illustrates the approach application. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Decision Support Systems | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1293 | |||
| Share this record to Facebook | |||||
| Author |
Congcong Wang; Paul Nulty; David Lillis | ||||
| Title | Crisis Domain Adaptation Using Sequence-to-Sequence Transformers | 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 | 655-666 | ||
| Keywords | Domain Adaptation, Emergency Response, Social media, Transformers | ||||
| Abstract | User-generated content (UGC) on social media can act as a key source of information for emergency responders incrisis situations. However, due to the volume concerned, computational techniques are needed to effectively filter and prioritise this content as it arises during emerging events. In the literature, these techniques are trained using annotated content from previous crises. In this paper, we investigate how this prior knowledge can be best leveraged for new crises by examining the extent to which crisis events of a similar type are more suitable for adaptation tonew events (cross-domain adaptation). Given the recent successes of transformers in various language processing tasks, we propose CAST: an approach for Crisis domain Adaptation leveraging Sequence-to-sequence Transformers. We evaluate CAST using two major crisis-related message classification datasets. Our experiments show that ourCAST-based best run without using any target data achieves the state of the art performance in both in-domain and cross-domain contexts. Moreover, CAST is particularly effective in one-to-one cross-domain adaptation when trained with a larger language model. In many-to-one adaptation where multiple crises are jointly used as the source domain, CAST further improves its performance. In addition, we find that more similar events are more likely to bring better adaptation performance whereas fine-tuning using dissimilar events does not help for adaptation. To aid reproducibility, we open source our code to the community. | ||||
| Address | University College Dublin; University College Dublin; University College Dublin | ||||
| 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 | wangcongcongcc@gmail.com | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2362 | ||
| Share this record to Facebook | |||||
| Author |
Daniel E. Lane; Tracey L. O'Sullivan; Craig E. Kuziemsky; Fikret Berkes; Anthony Charles | ||||
| Title | A structured equation model of collaborative community response | Type | Conference Article | ||
| Year | 2013 | Publication | ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2013 |
| Volume | Issue | Pages | 906-911 | ||
| Keywords | Computer simulation; Decision theory; Information systems; Mathematical models; Risk analysis; Adaptation; C-change; Community collaboration; Community engagement; Emergency response; EnRiCH; Preparedness; Simulation; Structured equation modeling; Emergency services | ||||
| Abstract | This paper analyses the collaborative dynamic of community in response to urgent situations. Community emergencies arising from natural or man-induced threats are considered as exogenous events that stimulate community resources to be unified around the response, action, and recovery activities related to the emergency. A structured equation model is derived to depict the actions of the community system. The system is described in terms of its resources including the propensity to trigger community action and collaboration among diverse groups. The community is profiled with respect to its ability to respond. The system defines the trigger mechanisms that are considered to be the drivers of collaborative action. A simulation model is presented to enact the system emergencies, community profiles, and collaborative response. The results develop an improved understanding of conditions that engage community collaborative actions as illustrated by examples from community research in the EnRiCH and the C-Change community research projects. | ||||
| Address | Telfer School of Management, University of Ottawa, Canada; Interdisciplinary Faculty of Health Sciences, University of Ottawa, Canada; Natural Resources Institute, University of Manitoba, Canada; Department of Finance and Management Science, Saint Mary's University, Canada | ||||
| Corporate Author | Thesis | ||||
| Publisher | Karlsruher Institut fur Technologie | Place of Publication | KIT; Baden-Baden | Editor | T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9783923704804 | Medium | |
| Track | Social Media | Expedition | Conference | 10th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 677 | |||
| Share this record to Facebook | |||||
| Author |
Francisco José Quesada Real; Fiona McNeill; Gábor Bella; Alan Bundy | ||||
| Title | Identifying Semantic Domains in Emergency Scenarios | Type | Conference Article | ||
| Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
| Volume | Issue | Pages | 1130-1132 | ||
| Keywords | Semantic domains, domain adaptation, emergency domains categorisation | ||||
| Abstract | Emergency scenarios are characterised by the participation of multiple and diverse organisations which come from different areas. This diversity is enriching in terms of expertise and approaches to tackle problems, however, it also provokes misunderstandings caused by semantic interoperability problems. There are some approaches which propose tackling these problems by using domain adaptation algorithms. Nevertheless, it is not trivial their application in emergency scenarios where the term “domain” is used in many different ways, not being clear either what it means or which domains are involved in these scenarios. In this paper, we identify semantic domains involved in emergency scenarios by analysing papers published in proceedings of ISCRAM and ISCRAM-med conferences. As a result, a categorisation of these domains has been developed, with the aim of providing a resource that can be used by domain adaptation algorithms to tackle problems such as those involving semantic interoperability. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-692-12760-5 | Medium | |
| Track | Poster | Expedition | Conference | ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2188 | |||
| Share this record to Facebook | |||||
| Author |
Hannah Van Wyk; Kate Starbird | ||||
| Title | Analyzing Social Media Data to Understand How Disaster-Affected Individuals Adapt to Disaster-Related Telecommunications Disruptions | Type | Conference Article | ||
| Year | 2020 | Publication | ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2020 |
| Volume | Issue | Pages | 704-717 | ||
| Keywords | Telecommunications, Adaptations, Social Media, Cellular Phone Service, Wi-Fi Access. | ||||
| Abstract | Information is a critical need during disasters such as hurricanes. Increasingly, people are relying upon cellular and internet-based technology to communicate that information--modalities that are acutely vulnerable to the disruptions to telecommunication infrastructure that are common during disasters. Focusing on Hurricane Maria (2017) and its long-term impacts on Puerto Rico, this research examines how people affected by severe and sustained disruptions to telecommunications services adapt to those disruptions. Leveraging social media trace data as a window into the real-time activities of people who were actively adapting, we use a primarily qualitative approach to identify and characterize how people changed their telecommunications practices and routines--and especially how they changed their locations--to access Wi-Fi and cellular service in the weeks and months after the hurricane. These findings have implications for researchers seeking to better understand human responses to disasters and responders seeking to identify strategies to support affected populations. | ||||
| Address | University of Washington; University of Washington | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-27-64 | ISBN | 2411-3450 | Medium | |
| Track | Social Media for Disaster Response and Resilie | Expedition | Conference | 17th International Conference on Information Systems for Crisis Response and Management | |
| Notes | hcvw@uw.edu | Approved | no | ||
| Call Number | Serial | 2265 | |||
| Share this record to Facebook | |||||
| 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 | ||
| Share this record to Facebook | |||||
| Author |
Hongmin Li; Doina Caragea; Cornelia Caragea | ||||
| Title | Towards Practical Usage of a Domain Adaptation Algorithm in the Early Hours of a Disaster | Type | Conference Article | ||
| Year | 2017 | Publication | Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2017 |
| Volume | Issue | Pages | 692-704 | ||
| Keywords | Twitter; Domain adaptation; Disaster; Classification | ||||
| Abstract | Many machine learning techniques have been proposed to reduce the information overload in social media data during an emergency situation. Among such techniques, domain adaptation approaches present greater potential as compared to supervised algorithms because they don't require labeled data from the current disaster for training. However, the use of domain adaptation approaches in practice is sporadic at best. One reason is that domain adaptation algorithms have parameters that need to be tuned using labeled data from the target disaster, which is presumably not available. To address this limitation, we perform a study on one domain adaptation approach with the goal of understanding how much source data is needed to obtain good performance in a practical situation, and what parameter values of the approach give overall good performance. The results of our study provide useful insights into the practical application of domain adaptation algorithms in real crisis situations. | ||||
| Address | Kansas State University; University of North Texas | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Albi, France | Editor | Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | Medium | ||
| Track | Social Media Studies | Expedition | Conference | 14th International Conference on Information Systems for Crisis Response And Management | |
| Notes | Approved | no | |||
| Call Number | ISCRAM @ idladmin @ | Serial | 2057 | ||
| Share this record to Facebook | |||||
| Author |
Hongmin Li; Nicolais Guevara; Nic Herndon; Doina Caragea; Kishore Neppalli; Cornelia Caragea; Anna Squicciarini; Andrea H. Tapia | ||||
| Title | Twitter Mining for Disaster Response: A Domain Adaptation Approach | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Disaster Response; domain adaptation; tweet classification | ||||
| Abstract | Microblogging data such as Twitter data contains valuable information that has the potential to help improve the speed, quality, and efficiency of disaster response. Machine learning can help with this by prioritizing the tweets with respect to various classification criteria. However, supervised learning algorithms require labeled data to learn accurate classifiers. Unfortunately, for a new disaster, labeled tweets are not easily available, while they are usually available for previous disasters. Furthermore, unlabeled tweets from the current disaster are accumulating fast. We study the usefulness of labeled data from a prior source disaster, together with unlabeled data from the current target disaster to learn domain adaptation classifiers for the target. Experimental results suggest that, for some tasks, source data itself can be useful for classifying target data. However, for tasks specific to a particular disaster, domain adaptation approaches that use target unlabeled data in addition to source labeled data are superior. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1234 | |||
| Share this record to Facebook | |||||
| Author |
Kees Boersma; Jeroen Wolbers; Pieter Wagenaar | ||||
| Title | Organizing emergent safety organizations: The travelling of the concept 'netcentric work' in the Dutch safety sector | Type | Conference Article | ||
| Year | 2010 | Publication | ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings | Abbreviated Journal | ISCRAM 2010 |
| Volume | Issue | Pages | |||
| Keywords | Information systems; Common operational picture; Local adaptation; Netherlands; Public safety; Safety organizations; Safety region; Sharing information; Work principle; Commerce | ||||
| Abstract | This paper is about the introduction of netcentric work in the public safety sector in the Netherlands. The idea behind netcentric work is that a common operational picture will help the professionals to overcome problems with sharing information during crisis. In this WIP paper we will pay attention to netcentric work principles and the dilemma of standardization of technologies versus local adaptation. In the Netherlands the government has chosen to introduce netcentric work via a Platform in which various options are discussed among members of Dutch safety regions. The outcome is a process of negotiation in what we call trading zones. In these trading zones netcentric work is (re)defined. Using theoretical concepts like soft-bureaucracy we show in this paper how netcentric work eventually is not about technology in the first place but a negotiated new way of working and organizing. Further research is needed to understand the full implications of netcentric work for the administration and organization of safety. | ||||
| Address | Faculty of Social Sciences, VU University, Amsterdam, Netherlands | ||||
| Corporate Author | Thesis | ||||
| Publisher | Information Systems for Crisis Response and Management, ISCRAM | Place of Publication | Seattle, WA | Editor | S. French, B. Tomaszewski, C. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | Medium | ||
| Track | Open Track | Expedition | Conference | 7th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 334 | |||
| Share this record to Facebook | |||||
| Author |
L.T. Darryl Diptee; Scott McKenzie | ||||
| Title | The systems thinking approach of beyond-line-of-sight command and control | Type | Conference Article | ||
| Year | 2012 | Publication | ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2012 |
| Volume | Issue | Pages | |||
| Keywords | Electric network topology; Information systems; Military applications; System theory; Adaptation; Beyond line of sight; Blos C2; Command and control; Layered model; Synergy; Systems thinking; Command and control systems | ||||
| Abstract | Effective command and control (C2) is necessary to achieve and maintain superiority in military engagements. C2 is well documented in the literature and is a major focus in the military arena; however, the conventional military network topology is increasingly becoming a liability and ineffective in the new age of asymmetric warfare. The beyond-line-of-sight command and control (BLOS C2) concept is a radical shift towards a seamless joint network topology, which will dramatically increase tactical C2 across military service branches, equipment types, and geographical locations. Though BLOS C2 is still in its testing phase, this paper examines the systems thinking approach of BLOS C2 with respect to layered models, adaptation, and synergy. The implementation of the BLOS C2 “tactical Wi-Fi” concept helps fill a Central Command (CENTCOM) capability gap in support of a Contingency Plan (CONPLAN) that provides Navy Forces Central Command (NAVCENT) with a robust force protection system. © 2012 ISCRAM. | ||||
| Address | Naval Postgraduate School, United States | ||||
| Corporate Author | Thesis | ||||
| Publisher | Simon Fraser University | Place of Publication | Vancouver, BC | Editor | L. Rothkrantz, J. Ristvej, Z.Franco |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9780864913326 | Medium | |
| Track | Inter-Organizational Exercises and Operations | Expedition | Conference | 9th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 99 | |||
| Share this record to Facebook | |||||
| Author |
Marlen Hofmann; Hans Betke; Stefan Sackmann | ||||
| Title | Automated Analysis and Adaptation of Disaster Response Processes with Place-Related Restrictions | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Business Process Management; Disaster response management; Process Adaptation; Process Analysis; Workflow Management Systems | ||||
| Abstract | For recent years, disaster response management is considered as a promising field for applying methods and tools from business process management. Especially the development of adaptive workflow management systems (WfMS) brought a process-oriented management of highly dynamic disaster response processes (DRP) within tangible reach. However, time criticality, unpredictability or complex and changing disaster reality make it impossible to analyze and adapt ongoing DRP within reasonable time manually. Hence, to foster the application of disaster response WfMS in practice, it becomes mandatory to develop methods supporting an (semi-)automated analyses and adaption of ongoing DRP. Addressing this research gap, we present a novel method called DRP-ADAPT which analyzes given DRP models with respect to place-related conflicts and resolves inoperable response activities (semi-)automatically by process adaptation. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Decision Support Systems | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1278 | |||
| Share this record to Facebook | |||||
| Author |
Marlen Hofmann; Stefan Sackmann; Hans Betke | ||||
| Title | Using Precedence Diagram Method in Process-Oriented Disaster Response Management | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | disaster logistics; Disaster response management; disaster response processes; precedence diagram method; Process Adaptation | ||||
| Abstract | When planning and modeling disaster response processes (DRP), the unpredictability of disasters precludes accounting for all eventualities in advance. DRPs are thus typically concretized and adapted after the disaster and during the process?s run-time. Since time is critical and uncertainty typical, planning of DRPs requires methods and tools that support disaster managers in process analysis, process adaptation, and decision making. This contribution presents an approach for identifying concurrent activities that, in needing identical resources at the same time in different locations, are jeopardized by such place-related conflicts. As solution, the approach allows managers to calculate valid execution sequences, eliminate place-related conflicts, and prioritize activities by total execution time. Results are shown to form a novel, reliable basis for contributing to disaster managers? decision support. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Decision Support Systems | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1290 | |||
| Share this record to Facebook | |||||
| Author |
Muhammad Imran; Prasenjit Mitra; Jaideep Srivastava | ||||
| Title | Cross-Language Domain Adaptation for Classifying Crisis-Related Short Messages | Type | Conference Article | ||
| Year | 2016 | Publication | ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2016 |
| Volume | Issue | Pages | |||
| Keywords | Social Media; Tweets Classification; Domain Adaptation | ||||
| Abstract | Rapid crisis response requires real-time analysis of messages. After a disaster happens, volunteers attempt to classify tweets to determine needs, e.g., supplies, infrastructure damage, etc. Given labeled data, supervised machine learning can help classify these messages. Scarcity of labeled data causes poor performance in machine training. Can we reuse old tweets to train classifiers? How can we choose labeled tweets for training? Specifically, we study the usefulness of labeled data of past events. Do labeled tweets in different language help? We observe the performance of our classifiers trained using different combinations of training sets obtained from past disasters. We perform extensive experimentation on real crisis datasets and show that the past labels are useful when both source and target events are of the same type (e.g. both earthquakes). For similar languages (e.g., Italian and Spanish), cross-language domain adaptation was useful, however, when for different languages (e.g., Italian and English), the performance decreased. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1396 | |||
| Share this record to Facebook | |||||
| Author |
Randal A. Collins | ||||
| Title | Adaptation: A Proposal to Replace Recovery in the Phases of Emergency Management | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the ISCRAM Asia Pacific Conference 2022 | Abbreviated Journal | Proc. ISCRAM AP 2022 |
| Volume | Issue | Pages | 130-137 | ||
| Keywords | Adaptation; Recovery; Change; Disaster; Emergency Management; Transformation; Resilience | ||||
| Abstract | Mitigation, preparedness, response, and recovery are the four phases of emergency management that have arguably been unchanged since their inception nearly 43 years ago. This paper proposes to replace recovery with adaptation as the post incident phase of emergency management. Recovery focuses on a return to normal while adaptation better encompasses acknowledgement, healing, strengthening, and improving quality of life for a more resilient outcome. This paper reviews seminal work within emergency management and work pertaining to other types of adaptation to better comprehend adaptation as applied to emergency management. | ||||
| Address | Foundation for the Research and Advancement of Emergency Management | ||||
| Corporate Author | Thesis | ||||
| Publisher | Massey Unversity | Place of Publication | Palmerston North, New Zealand | Editor | Thomas J. Huggins, V.L. |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-473-66845-7 | Medium | |
| Track | Building Disaster Resilience | Expedition | Conference | ||
| Notes | Approved | no | |||
| Call Number | ISCRAM @ idladmin @ | Serial | 2487 | ||
| Share this record to Facebook | |||||
| Author |
Reza Mazloom; HongMin Li; Doina Caragea; Muhammad Imran; Cornelia Caragea | ||||
| Title | Classification of Twitter Disaster Data Using a Hybrid Feature-Instance Adaptation Approach | Type | Conference Article | ||
| Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
| Volume | Issue | Pages | 727-735 | ||
| Keywords | Tweet classification, Domain adaptation, Matrix factorization, k-Nearest Neighbors, Disaster response | ||||
| Abstract | Huge amounts of data that are generated on social media during emergency situations are regarded as troves of critical information. The use of supervised machine learning techniques in the early stages of a disaster is challenged by the lack of labeled data for that particular disaster. Furthermore, supervised models trained on labeled data from a prior disaster may not produce accurate results, given the inherent variation between the current and the prior disasters. To address the challenges posed by the lack of labeled data for a target disaster, we propose to use a hybrid feature-instance adaptation approach based on matrix factorization and the k nearest neighbors algorithm, respectively. The proposed hybrid adaptation approach is used to select a subset of the source disaster data that is representative for the target disaster. The selected subset is subsequently used to learn accurate Naive Bayes classifiers for the target disaster. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-692-12760-5 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2146 | |||
| Share this record to Facebook | |||||
| Author |
Xiaodan Yu; Deepak Khazanchi | ||||
| Title | Patterns of Information Technology (IT) Adaptation in Building Shared Mental Models for Crisis Management Teams | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | case study; Crisis Management; information technology adaptation; Shared mental models | ||||
| Abstract | One of the essential tasks of crisis management is to develop shared mental models (SMM) among teams and members about the crisis at hand, i.e. shared understanding of the task, process, technology and the teams. This is essential for developing an effective crisis management strategy. In this paper we draw lessons from our studies of distributed teams and their adaptation of IT capabilities to impact shared understanding. In particular, we discuss how patterns of the interplay between IT adaptation and SMM development have implications for crisis management teams. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Open Track | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1244 | |||
| Share this record to Facebook | |||||
| Author |
Xukun Li; Doina Caragea; Cornelia Caragea; Muhammad Imran; Ferda Ofli | ||||
| Title | Identifying Disaster Damage Images Using a Domain Adaptation Approach | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages | |||
| Keywords | image classification, disaster damage, domain adaptation, domain adversarial neural networks. | ||||
| Abstract | Approaches for effectively filtering useful situational awareness information posted by eyewitnesses of disasters, in real time, are greatly needed. While many studies have focused on filtering textual information, the research on filtering disaster images is more limited. In particular, there are no studies on the applicability of domain adaptation to filter images from an emergent target disaster, when no labeled data is available for the target disaster. To fill in this gap, we propose to apply a domain adaptation approach, called domain adversarial neural networks (DANN), to the task of identifying images that show damage. The DANN approach has VGG-19 as its backbone, and uses the adversarial training to find a transformation that makes the source and target data indistinguishable. Experimental results on several pairs of disasters suggest that the DANN model generally gives similar or better results as compared to the VGG-19 model fine-tuned on the source labeled data. |
||||
| Address | Department of Computer Science, Kansas State University, United States of America;Department of Computer Science, University of Illinois at Chicago, United States of America;Qatar Computing Research Institute, Hamad Bin Khalifa University, Qatar | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1853 | |||
| Share this record to Facebook | |||||