L.T. Darryl Diptee, & Jason Baker. (2013). Tackling wicked problems: Suicide in the US military. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 931–940). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Every 24 hours a member of the United States (US) Armed Forces commits suicide, while every hour a US veteran takes his own life. These statistics illuminate a deeply-rooted social crisis which eludes experts and military leaders to this day. Billions of dollars invested in suicide prevention seem to offer little relief for active duty servicemen and veterans alike. Military suicide is framed as a wicked problem and the new and exciting theory of Chronic Emotional Atrophy (CEA) is proposed to help explain causes of suicidal ideation in the military. A holistic crisis management strategy via information systems is presented in this work. Depressive symptoms exhibited by military members in emotionally suppressed environments closely parallel those phenomena exhibited by medical patients suffering from frontal lobe damage. The prospective psychiatric information system solution provides frontal lobe stimulation (FLS) to mitigate CEA and suicidal ideation.
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Julie Dugdale, Bernard Pavard, Nico Pallamin, Mehdi El Jed, & Laurent Maugan. (2004). Emergency fire incident training in a virtual world. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 167–172). Brussels: Royal Flemish Academy of Belgium.
Abstract: The effectiveness of 'close to reality' training simulations is due to the fact that they provide a sense of immersion and allow several participants to interact naturally. However, they are expensive, time-consuming, difficult to organise and have a limited scope. We present a virtual reality training simulator which overcomes these disadvantages. We describe the approach and methodology and conclude with a discussion of the most crucial challenges when developing such a system. In this paper we would like to introduce the notion of cultural technologies which produce a sense of social as well as cultural immersion. We will discuss the main ingredients of such an immersion, in particular the notion of situated virtual interaction (how interactions in a virtual world can be comparable with human interactions in real situations). We also discuss on the role of interfaces (real time motion capture) and emotional expression in the design of such environments. © Proceedings ISCRAM 2004.
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Siska Fitrianie, & Leon J.M. Rothkrantz. (2007). An automated crisis online dispatcher. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 525–536). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: An experimental automated dialogue system that plays the role of a crisis hotline dispatcher is currently developed. Besides controlling the communication flow, this system is able to retrieve information about crisis situations from user's input. It offers a natural user interaction by the ability to perceive and respond to human emotions. The system has an emotion recognizer that is able to recognize the emotional loading from user's linguistic content. The recognizer uses a database that contains selected keywords on a 2D “arousal” and “valence” scale. The output of the system provides not only the information about the user's emotional state but also an indication of the urgency of his/her information regarding to crisis. The dialogue system is able to start a user friendly dialogue, taking care of the content, context and emotional loading of user's utterances.
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Rajesh M. Hegde, B.S. Manoj, Bashkar D. Rao, & Ramesh R. Rao. (2006). Emotion detection from speech signals and its applications in supporting enhanced QoS in emergency response. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 82–91). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Networking in the event of disasters requires new hybrid wireless architectures such as Wireless Mesh Networks (WMNs). Provisioning Quality of Service (QoS) in such networks which are quickly deployed during emergencies demand radical solutions. In this paper, we provide a new QoS approach for voice calls over a wireless mesh networks during emergency situations. According to our scheme, the contention and back-off parameters are modified based on the emotion content in the voice streams. This paper also looks at methods for detecting emotion from an incoming voice call using the speech signal. The issues of interest in such situations are whether the caller is in a state of extreme panic, moderate panic, or in a normal state of behavior. The communication network behavior should be modified to provide differentiated QoS for calls based on the degree of emotion. We use several features extracted from the speech signal like the range of pitch variation, energy in the critical bark band, range of the first three formant variations, and speaking rate among others to discriminate between the three emotional states. At the back end the Gaussian mixture modeling techniques is used to model the three emotional states of the speaker. Since a large number of features increase the computational complexity and time, a feature selection technique is employed based on the Bhattacharya distance, to select the set of features that give maximum discrimination between the classes. These set of features are employed to simulate an emotion recognition system. The results indicate a promising emotion detection rate for the three emotions. We also present the early results on detecting the emotion content in the speech and using this in the MAC layer differentiated QoS provisioning scheme. Our scheme provides an end-to-end delay performance improvement for panicked calls as high as 60% compared to normal calls.
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Shane Errol Halse, Andrea Tapia, Anna Squicciarini, & Cornelia Caragea. (2016). An Emotional Step Towards Automated Trust Detection in Crisis Social Media. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: To this date, research on crisis informatics has focused on the detection of trust in Twitter data through the use of message structure, sentiment, propagation and author. Little research has examined the effects of perceived emotion of these messages in the crisis response domain. Toward detecting useful messages in case of crisis, we examine perceived emotions of these messages and how the different emotions affect the perceived usefulness and trustworthiness. Our analysis is carried out on two datasets gathered from Twitter concerning hurricane Sandy in 2012 and the Boston Bombing 2013. The results indicate that there is a significant difference in the perceived emotions that contribute towards the perceived trustworthiness and usefulness. This could have impacts on how messages from social media data are analyzed for use in crisis response.
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Zhenke Yang, & Leon J.M. Rothkrantz. (2007). Emotion sensing for context sensitive interpretation of crisis reports. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 507–514). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The emotional qualities of a report play an important role in the evaluation of eye witness reports in crisis centers. Human operators in the crisis center can use the amount of anxiety and stress detected in a spoken report to rapidly estimate the possible impact and urgency of a report and the appropriate response to the reporter. This paper presents ongoing work in automated multi-modal emotion sensing of crisis reports in order to reduce the cognitive load on human operators. Our approach is based on the work procedures adopted by the crisis response center Rijnmond environmental agency (DCMR) and assumes a spoken dialogue between a reporter and a crisis control center. We use an emotion model based on conceptual graphs that is continually evaluated while the dialogue continues. We show how the model can be applied to interpret crisis report in a fictional toxic gas dispersion scenario.
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