The Experts below are selected from a list of 107928 Experts worldwide ranked by ideXlab platform
Frederick Benaben - One of the best experts on this subject based on the ideXlab platform.
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A new emergency decision support system: the automatic interpretation and contextualisation of events to model a Crisis Situation in real-time
Decision Support Systems, 2020Co-Authors: Audrey Fertier, Aurelie Montarnal, Sébastien Truptil, Anne-marie Barthe-delanoë, Frederick BenabenAbstract:This paper studies, designs and implements a new type of emergency decision support system that aims to improve the decision-making of emergency managers in Crisis Situations by connecting them to new, multiple data sources. The system combines event-driven and model-driven architectures and is dedicated to Crisis cells. After its implementation, the system is evaluated using a realistic Crisis scenario, in terms of its user interfaces, its ability to interpret data in real time and its ability to manage the 4Vs of Big Data. The input events correspond to traffic measurements, water levels, water flows, water predictions and flow predictions made available by French official services. The main contributions of this study are: (i) the connection between a complex event processing engine and a graph database containing the model of the Crisis Situation and (ii) the continuous updating of a common operational picture for the benefit of emergency managers. This study could be used as a framework for future research works on decision support systems facing complex, evolving Situations.
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actionable collaborative common operational picture in Crisis Situation a comprehensive architecture powered with social media data
Working Conference on Virtual Enterprises, 2019Co-Authors: Julien Coche, Aurelie Montarnal, Andrea H. Tapia, Frederick BenabenAbstract:Previous works in social media processing during Crisis management highlight a paradox: citizens are extensively sharing data from the field of the Crisis, while decision-makers are looking for information about the emerging risks they need to address. Several tools already exist to help taking advantage of this new important source of data. However, few made their way to decision-makers, mainly because they remain resource-consuming. That is why the question of a tool, able to process social media in near-real time, to deliver actionable information from the field is still pending. Based on a state of the art of the Natural Language Processing tools and systems dedicated to the use of social media data to improve the Situational awareness of the decision-makers, this paper aims to describe a way to provide them with a first comprehensive system which asset is to completely address the challenge, from the collection of the data to their interpretation and understanding and finally offer Situational models. In this sense, the paper focuses on the thorough detail of the business and consequent technical challenges that are raised, and a work in progress proposal to address them in a comprehensive manner.
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Towards an organizational and socio-technical context-aware adaptation of emergency plans
2018Co-Authors: Anne-marie Barthe-delanoë, Sébastien Truptil, Nelly Olivier-maget, Frederick BenabenAbstract:In France, facilities listed under environment protection regulations are required to draw up emergency plans. During a Crisis Situation, facing an unexpected event, these plans may be irrelevant. They have to be adapted to the current Crisis Situation and its observed or anticipated evolutions, using data emitted by the Crisis ecosystem. But this adaptation requires lots of effort and is time-consuming. This article aims at presenting an approach to ensure the dynamic adaptation of emergency plans. We propose to identify generic configuration variables (representing interactions of physical phenomena and human factors on the facility) and to feed these configuration variables by collecting and processing data emitted by sensors, social networks, official reports, etc. Therefore, emergency plans could natively integrate agility by their ability to detect and take into account a change in the Crisis Situation and decision makers will be supported since the early stage of the Crisis response
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Automated Emergence of a Crisis Situation Model in Crisis Response Based on Tweets
2017Co-Authors: Aurelie Montarnal, Shane Halse, Andrea Tapia, Sébastien Truptil, Frederick BenabenAbstract:During a Crisis, being able to understand quickly the Situation on-site is crucial for the responders to take relevant decisions together. Social media, in particular Twitter, have proved to be a means for rapidly getting information from the field. However, the deluge of data is heterogeneous in many ways (location, trust, content, vocabulary, etc.), and getting a model of the Crisis Situation still requires laborious human actions. In addition, depending on which kind of information is mined from them, tweets have to be handle one-by-one (e.g. find victims), or as a whole - amount of tweets - (e.g. occurence of an event). This paper proposes a framework for automatically extracting, interpreting and aggregating streams of tweets to characterize Crisis Situations. It is based on a specific metamodel that determines the different concepts required to model a Crisis Situation.
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PRO-VE - Automated Emergence of a Crisis Situation Model in Crisis Response Based on Tweets
Collaboration in a Data-Rich World, 2017Co-Authors: Aurelie Montarnal, Shane Halse, Sébastien Truptil, Andrea H. Tapia, Frederick BenabenAbstract:During a Crisis, being able to understand quickly the Situation on-site is crucial for the responders to take relevant decisions together. Social media, in particular Twitter, have proved to be a means for rapidly getting information from the field. However, the deluge of data is heterogeneous in many ways (location, trust, content, vocabulary, etc.), and getting a model of the Crisis Situation still requires laborious human actions. In addition, depending on which kind of information is mined from them, tweets have to be handle one-by-one (e.g. find victims), or as a whole - amount of tweets - (e.g. occurence of an event). This paper proposes a framework for automatically extracting, interpreting and aggregating streams of tweets to characterize Crisis Situations. It is based on a specific metamodel that determines the different concepts required to model a Crisis Situation.
A. A. Habu - One of the best experts on this subject based on the ideXlab platform.
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IMPACT OF INSECURITY ON SCHOOL ATTENDANCE OF JUNIOR SECONDARY SCHOOL STUDENTS IN MAIBUGURI METROPOLIS, BORNO STATE, NIGERIA
Sokoto Educational Review, 2019Co-Authors: U. Abdullahi, T. G. Atsua, B. G. Amuda, A. A. HabuAbstract:The study addressed three questions, what is the level of school attendance under the Crisis Situation in Maiduguri metropolis? Are parents and teachers willing to send back their children to the affected schools? Does insecurity have a significant impact on attendance of school children? Impact of Insecurity Questionnaire (IIQ) was developed for the study. The alpha reliability of the questionnaire was .965. It was administered to 225 parents and teachers in 21 junior secondary schools in Maiduguri, Borno state that were affected in the activities of Boko Haram in the metropolis. The responses to the questionnaire were summarized using percentages. Chi-square was computed to test for differences in responses on the impact of insecurity on school attendance. The students were found the level of school attendance under the Crisis Situation in Maiduguri metropolis has been low but that of male students seems to be lower than that of female students. Parents and teachers were willing to send their children back to the affected schools. The impact of insecurity on school attendance was found to be significant.
Aurelie Montarnal - One of the best experts on this subject based on the ideXlab platform.
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A new emergency decision support system: the automatic interpretation and contextualisation of events to model a Crisis Situation in real-time
Decision Support Systems, 2020Co-Authors: Audrey Fertier, Aurelie Montarnal, Sébastien Truptil, Anne-marie Barthe-delanoë, Frederick BenabenAbstract:This paper studies, designs and implements a new type of emergency decision support system that aims to improve the decision-making of emergency managers in Crisis Situations by connecting them to new, multiple data sources. The system combines event-driven and model-driven architectures and is dedicated to Crisis cells. After its implementation, the system is evaluated using a realistic Crisis scenario, in terms of its user interfaces, its ability to interpret data in real time and its ability to manage the 4Vs of Big Data. The input events correspond to traffic measurements, water levels, water flows, water predictions and flow predictions made available by French official services. The main contributions of this study are: (i) the connection between a complex event processing engine and a graph database containing the model of the Crisis Situation and (ii) the continuous updating of a common operational picture for the benefit of emergency managers. This study could be used as a framework for future research works on decision support systems facing complex, evolving Situations.
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actionable collaborative common operational picture in Crisis Situation a comprehensive architecture powered with social media data
Working Conference on Virtual Enterprises, 2019Co-Authors: Julien Coche, Aurelie Montarnal, Andrea H. Tapia, Frederick BenabenAbstract:Previous works in social media processing during Crisis management highlight a paradox: citizens are extensively sharing data from the field of the Crisis, while decision-makers are looking for information about the emerging risks they need to address. Several tools already exist to help taking advantage of this new important source of data. However, few made their way to decision-makers, mainly because they remain resource-consuming. That is why the question of a tool, able to process social media in near-real time, to deliver actionable information from the field is still pending. Based on a state of the art of the Natural Language Processing tools and systems dedicated to the use of social media data to improve the Situational awareness of the decision-makers, this paper aims to describe a way to provide them with a first comprehensive system which asset is to completely address the challenge, from the collection of the data to their interpretation and understanding and finally offer Situational models. In this sense, the paper focuses on the thorough detail of the business and consequent technical challenges that are raised, and a work in progress proposal to address them in a comprehensive manner.
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Automated Emergence of a Crisis Situation Model in Crisis Response Based on Tweets
2017Co-Authors: Aurelie Montarnal, Shane Halse, Andrea Tapia, Sébastien Truptil, Frederick BenabenAbstract:During a Crisis, being able to understand quickly the Situation on-site is crucial for the responders to take relevant decisions together. Social media, in particular Twitter, have proved to be a means for rapidly getting information from the field. However, the deluge of data is heterogeneous in many ways (location, trust, content, vocabulary, etc.), and getting a model of the Crisis Situation still requires laborious human actions. In addition, depending on which kind of information is mined from them, tweets have to be handle one-by-one (e.g. find victims), or as a whole - amount of tweets - (e.g. occurence of an event). This paper proposes a framework for automatically extracting, interpreting and aggregating streams of tweets to characterize Crisis Situations. It is based on a specific metamodel that determines the different concepts required to model a Crisis Situation.
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PRO-VE - Automated Emergence of a Crisis Situation Model in Crisis Response Based on Tweets
Collaboration in a Data-Rich World, 2017Co-Authors: Aurelie Montarnal, Shane Halse, Sébastien Truptil, Andrea H. Tapia, Frederick BenabenAbstract:During a Crisis, being able to understand quickly the Situation on-site is crucial for the responders to take relevant decisions together. Social media, in particular Twitter, have proved to be a means for rapidly getting information from the field. However, the deluge of data is heterogeneous in many ways (location, trust, content, vocabulary, etc.), and getting a model of the Crisis Situation still requires laborious human actions. In addition, depending on which kind of information is mined from them, tweets have to be handle one-by-one (e.g. find victims), or as a whole - amount of tweets - (e.g. occurence of an event). This paper proposes a framework for automatically extracting, interpreting and aggregating streams of tweets to characterize Crisis Situations. It is based on a specific metamodel that determines the different concepts required to model a Crisis Situation.
Silke Schmidt - One of the best experts on this subject based on the ideXlab platform.
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Trusting Facebook in Crisis Situations: The Role of General Use and General Trust Toward Facebook.
Cyberpsychology behavior and social networking, 2016Co-Authors: Hermann Szymczak, Pinar Kücükbalaban, Sandra Lemanski, Daniela Knuth, Silke SchmidtAbstract:Abstract An important concept that has been rather neglected in research on social media is the concept of trust. Although there is a considerable amount of research on online trust in general, little has been done in the area of social media. As a Situation of risk is necessary for trust, the perceived trustworthiness of Facebook in Crisis Situations was examined in this study. A sample of 340 European Facebook users were questioned as part of a large European study about social media in the context of emergency Situations. We found that participants' general trust toward Facebook as a medium predicted to a significant degree how much they would trust Facebook in a Crisis Situation. General use of Facebook and dispositional trust were also significantly associated with trust toward Facebook in a Crisis Situation.
Sébastien Truptil - One of the best experts on this subject based on the ideXlab platform.
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A new emergency decision support system: the automatic interpretation and contextualisation of events to model a Crisis Situation in real-time
Decision Support Systems, 2020Co-Authors: Audrey Fertier, Aurelie Montarnal, Sébastien Truptil, Anne-marie Barthe-delanoë, Frederick BenabenAbstract:This paper studies, designs and implements a new type of emergency decision support system that aims to improve the decision-making of emergency managers in Crisis Situations by connecting them to new, multiple data sources. The system combines event-driven and model-driven architectures and is dedicated to Crisis cells. After its implementation, the system is evaluated using a realistic Crisis scenario, in terms of its user interfaces, its ability to interpret data in real time and its ability to manage the 4Vs of Big Data. The input events correspond to traffic measurements, water levels, water flows, water predictions and flow predictions made available by French official services. The main contributions of this study are: (i) the connection between a complex event processing engine and a graph database containing the model of the Crisis Situation and (ii) the continuous updating of a common operational picture for the benefit of emergency managers. This study could be used as a framework for future research works on decision support systems facing complex, evolving Situations.
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Towards an organizational and socio-technical context-aware adaptation of emergency plans
2018Co-Authors: Anne-marie Barthe-delanoë, Sébastien Truptil, Nelly Olivier-maget, Frederick BenabenAbstract:In France, facilities listed under environment protection regulations are required to draw up emergency plans. During a Crisis Situation, facing an unexpected event, these plans may be irrelevant. They have to be adapted to the current Crisis Situation and its observed or anticipated evolutions, using data emitted by the Crisis ecosystem. But this adaptation requires lots of effort and is time-consuming. This article aims at presenting an approach to ensure the dynamic adaptation of emergency plans. We propose to identify generic configuration variables (representing interactions of physical phenomena and human factors on the facility) and to feed these configuration variables by collecting and processing data emitted by sensors, social networks, official reports, etc. Therefore, emergency plans could natively integrate agility by their ability to detect and take into account a change in the Crisis Situation and decision makers will be supported since the early stage of the Crisis response
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Automated Emergence of a Crisis Situation Model in Crisis Response Based on Tweets
2017Co-Authors: Aurelie Montarnal, Shane Halse, Andrea Tapia, Sébastien Truptil, Frederick BenabenAbstract:During a Crisis, being able to understand quickly the Situation on-site is crucial for the responders to take relevant decisions together. Social media, in particular Twitter, have proved to be a means for rapidly getting information from the field. However, the deluge of data is heterogeneous in many ways (location, trust, content, vocabulary, etc.), and getting a model of the Crisis Situation still requires laborious human actions. In addition, depending on which kind of information is mined from them, tweets have to be handle one-by-one (e.g. find victims), or as a whole - amount of tweets - (e.g. occurence of an event). This paper proposes a framework for automatically extracting, interpreting and aggregating streams of tweets to characterize Crisis Situations. It is based on a specific metamodel that determines the different concepts required to model a Crisis Situation.
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PRO-VE - Automated Emergence of a Crisis Situation Model in Crisis Response Based on Tweets
Collaboration in a Data-Rich World, 2017Co-Authors: Aurelie Montarnal, Shane Halse, Sébastien Truptil, Andrea H. Tapia, Frederick BenabenAbstract:During a Crisis, being able to understand quickly the Situation on-site is crucial for the responders to take relevant decisions together. Social media, in particular Twitter, have proved to be a means for rapidly getting information from the field. However, the deluge of data is heterogeneous in many ways (location, trust, content, vocabulary, etc.), and getting a model of the Crisis Situation still requires laborious human actions. In addition, depending on which kind of information is mined from them, tweets have to be handle one-by-one (e.g. find victims), or as a whole - amount of tweets - (e.g. occurence of an event). This paper proposes a framework for automatically extracting, interpreting and aggregating streams of tweets to characterize Crisis Situations. It is based on a specific metamodel that determines the different concepts required to model a Crisis Situation.
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Interoperability of Information Systems in Crisis Management: Crisis Modeling and Metamodeling
2008Co-Authors: Sébastien Truptil, Frederick Benaben, Pierre Couget, Matthieu Lauras, Vincent Chapurlat, Hervé PingaudAbstract:In a Crisis Situation (natural disaster, industrial accident, etc.) several partners have to act simultaneously to solve the emergency Situation. Their coordination in such a context is a crucial point, especially in the first moments of the Crisis. Their interoperability (precisely their Information Systems interoperability) is a major component of the success of the network. ISyCri French project propose to tackle this topic according to two aspects: (i) responsiveness of the network (its ability to act rapidly and efficiently) and (ii) flexibility of the obtained system of systems (its ability to evolve and follow the changing Situation). This is so an agility problem of ISs of partners. This article presents the first results of this work: a metamodel of Crisis Situation and its ontological links with collaborative process design, and also the treatment of a first case of study, a NRBC exercise.