Thales Research and Technology

Delft, Netherlands

Thales Research and Technology

Delft, Netherlands
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Parent M.,Laval University | Gagnon J.-F.,Thales Research and Technology | Falk T.H.,MuSAE Laboratory | Tremblay S.,Laval University
Proceedings of the International ISCRAM Conference | Year: 2016

New technologies are available for emergency management experts to help them cope with challenges such as information overload, multitasking and fatigue. Among these technologies, a wide variety of physiological sensors can now be deployed to measure the Operator Functional State (OFS). To be truly useful, such measures should not only characterize the overall OFS, but also the specific dimensions such as stress or mental workload. This experiment aimed to (1) design a multi-dimensional model of OFS, and (2) test its application to an emergency management situation. First, physiological data of participants were collected during controlled experimental tasks. Then, a support vector classifier of mental workload and stress was trained. Finally, the resulting model was tested during an emergency management simulation. Results suggest that the model could be applied to emergency management situations, and leave the door open for its application to emergency response on the field.


Penders A.,Technical University of Delft | Varbanescu A.L.,University of Amsterdam | Pavlin G.,Thales Research and Technology | Sips H.,Technical University of Delft
ICPE 2017 - Proceedings of the 2017 ACM/SPEC International Conference on Performance Engineering | Year: 2017

Many situations in the security domain require decisionmaking based on complex data, i.e., many variables which need to be taken into account before adequate decisions can be made. For example, in a surveillance scenario, the size and complexity of the area of interest, the mix of objects, and the unexpected behavior of suspects are just a few examples of complex variables to be analyzed in the process. Existing decision support systems provide some analysis, but are typically limited in the complexity they can handle. Therefore, users end up with simplified models which often suffer in the accuracy of their decisions and, ultimately, may lead to incorrect decisions. In this work, we present a framework that can scale to cope with the complexity and time requirements of real-world scenarios, while remaining exible to handle the ad-hoc adaptation to the situation. We discuss the challenges and solutions for such a scalable and exible system, and validate it using a target tracking scenario in urban environments of different sizes. © 2017 ACM.


Martella C.,VU University Amsterdam | Van Steen M.,VU University Amsterdam | Van Halteren A.,VU University Amsterdam | Conrado C.,Thales Research and Technology | Li J.,Technical University of Delft
IEEE Communications Magazine | Year: 2014

We are only starting to understand how people behave when they are part of a crowd. This article presents a novel approach to the study and management of crowds. The approach comprises a device to be worn by individuals, an infrastructure to collect the information from the devices, a set of algorithms for recognizing crowd dynamics, and a set of feedback strategies to intervene in the crowd. A fundamental element of our approach is to consider crowds in terms of their texture. The crowd texture is represented through the proximity graph, a data structure that captures the spatial closeness relationship between individuals over time. We address its properties and limitations, a system architecture to measure and process it, and a few examples of insights that can be obtained from analyzing it. © 1979-2012 IEEE.


Krupenia S.S.,Thales Research and Technology | Aguero C.,Thales Research and Technology
ISCRAM 2012 Conference Proceedings - 9th International Conference on Information Systems for Crisis Response and Management | Year: 2012

We examined to what extent a MultiTouch Table (MTT) can support a collaborative Operational Planning Asset Distribution task as compared to traditional Spreadsheet methods. Participants were given different and complementary specialist roles and were then asked to distribute different sets of assets over an area of Operations with multiple known and unknown 'needs'. Additionally, participants had to satisfy a series of real time intelligence recommendations regarding potential needs. Of interest were subjective usability ratings and objective performance measures in terms of need fulfillment and satisfying intelligence recommendations. We found that on all but one usability measure participants rated the MTT more positively than the Spreadsheets. There was also a non-significant trend for greater needs fulfillment and resolving intelligence recommendations using the MTT than the spreadsheets. On the basis of the results we suggest that MTT technology offers a viable tool for supporting collaborative Asset Distribution tasks in general. © 2012 ISCRAM.


Pavlin G.,Thales Research and Technology | Claessens R.,Thales Research and Technology | De Oude P.,Thales Research and Technology | Costa P.C.G.,George Mason University
FUSION 2016 - 19th International Conference on Information Fusion, Proceedings | Year: 2016

This paper evaluates a probabilistic approach to data association in a class of tracking problems characterised through intermittent, sparse observations. Examples are tracking of a specific target, such as a suspicious person or a car in urban environments. The used data stems from disparate, often simple detectors, each capable of detecting one type of a feature, such as a license plate, car type, its color, etc. It is also assumed that the detectors are dispersed throughout the environment and have a limited range. Such partial observability combined with the inherent ambiguity of the detected features makes data association challenging. Traditional gating methods are in such settings often not suitable. This paper investigates a probabilistic approach to data association in a combination with Particle Filtering methods. We introduce a composite probabilistic sensor model which incorporates the knowledge about the ambiguity of the origin of an observation of a specific feature (e.g. a vehicle type, fragment of a license plate, etc.). The presented approach is based on canonical probabilistic models and provides a clear guidance for the determination of adequate modeling parameters. The impact of the proposed model is evaluated theoretically and empirically. Moreover, causal probabilistic models of dynamic processes are used for the identification of potentially critical modeling deficiencies and properties of the resulting systems while a testbed is used for empirical evaluation of the overall filtering performance under specific conditions. The experiments confirm the theoretically predicted properties and show that the presented modeling approach allows robust tracking also with ambiguous features. © 2016 ISIF.


Rondeel E.W.M.,Thales Research and Technology | Rondeel E.W.M.,Radboud University Nijmegen | van Steenbergen H.,Leiden University | Holland R.W.,Radboud University Nijmegen | van Knippenberg A.,Radboud University Nijmegen
Frontiers in Human Neuroscience | Year: 2015

The present study investigated resource allocation, as measured by pupil dilation, in tasks measuring updating (2-Back task), inhibition (Stroop task) and switching (Number Switch task). Because each cognitive control component has unique characteristics, differences in patterns of resource allocation were expected. Pupil and behavioral data from 35 participants were analyzed. In the 2-Back task (requiring correct matching of current stimulus identity at trial p with the stimulus two trials back, p -2) we found that better performance (low total of errors made in the task) was positively correlated to the mean pupil dilation during correctly responding to targets. In the Stroop task, pupil dilation on incongruent trials was higher than those on congruent trials. Incongruent vs. congruent trial pupil dilation differences were positively related to reaction time differences between incongruent and congruent trials. Furthermore, on congruent Stroop trials, pupil dilation was negatively related to reaction times, presumably because more effort allocation paid off in terms of faster responses. In addition, pupil dilation on correctly-responded-to congruent trials predicted a weaker Stroop interference effect in terms of errors, probably because pupil dilation on congruent trials were diagnostic of task motivation, resulting in better performance. In the Number Switch task we found higher pupil dilation in switch as compared to non-switch trials. On the Number Switch task, pupil dilation was not related to performance. We also explored error-related pupil dilation in all tasks. The results provide new insights in the diversity of the cognitive control components in terms of resource allocation as a function of individual differences, task difficulty and error processing. ©2015 Rondeel, van Steenbergen, Holland and van Knippenberg.


Conrado C.,Thales Research and Technology | De Oude P.,Thales Research and Technology
FUSION 2014 - 17th International Conference on Information Fusion | Year: 2014

This paper presents a scenario-based approach to deal with uncertainties in situation assessment problems. Scenario representation is based on causal models, whereas scenario generation involves the estimation of the states of model variables, done by means of observations and inferences of hidden states by using domain knowledge. Moreover, scenario management is addressed by means of a probabilistic framework involving Bayesian and credal networks, which allows the evaluation and ranking of scenarios according to likelihood, used to prioritize information to be presented to decision makers. The presented scenario approach also supports the adaptation of the reasoning models on the fly, as scenarios are generated and relevant information changes or becomes available. © 2014 International Society of Information Fusion.


Koudri A.,Thales Research and Technology | Cuccuru A.,CEA | Gerard S.,CEA | Terrier F.,CEA
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

Building complex real-time embedded systems requires assembly of heterogeneous components, possibly using various computation and communication models. A great challenge is to be able to design such systems using models where these heterogeneity characteristics are described precisely to assist the next step of the development including implementation or analysis. Although the new MARTE standard provides the core concepts to model real-time components using various communication paradigms, we state in this paper that MARTE extensions have still to be made and we propose to extract common features from several component based approaches in order to support finer compositions of heterogeneous sub-systems. © 2011 Springer-Verlag.


Labreuche C.,Thales Research and Technology | Grabisch M.,Paris-Sorbonne University
8th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2013 - Advances in Intelligent Systems Research | Year: 2013

This paper is devoted to the use of the GAI (Generalized Additive Independence) model in a Multi-Criteria Decision Making context. We first discuss on some new conditions (concerning the sign and monotonicity) to add on the terms appearing in a GAI model. Secondly, we propose some algorithms to propose the learning examples to change or remove, together with an explanation of this, when there are inconsistencies in the learning data. Finally, we propose some importance and interaction indices to interpret a GAI model. © 2013. The authors-Published by Atlantis Press.


Goujon B.,Thales Research and Technology | Labreuche C.,Thales Research and Technology
8th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2013 - Advances in Intelligent Systems Research | Year: 2013

The current approaches to construct a multi-criteria model based on a Choquet integral are split into two separate steps: construct first the utility functions and then the aggregation function. Unfortunately, the decision maker may feel some difficulties in addressing these tricky steps. In this paper, we propose a preference learning algorithm that constructs both the utility functions and the capacity from several preferences or evaluations. The algorithm is based on a fixed-point approach that transforms the global optimization learning problem into two iterative linear problems. Each problem objective is to minimize the number of non-validated learning examples. © 2013. The authors -Published by Atlantis Press.

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