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Sedki K.,University of Paris 13 | Sedki K.,Paris-Sorbonne University | Yahi S.,Domaine University Of Saint Jerome
Communications in Computer and Information Science

Value-based argumentation framework (VAF) is an extension of Dung argumentation framework where arguments promote specific values. In VAF, an argument a defeats b only if the value promoted by b is not preferred than the value promoted by a according to some total ordering on values given by a specific audience. However, despite the interesting idea of considering the preference relation between arguments’ values, VAF does not offer a way to express further requirements, like “no arguments promoting expensive value” or “if we accept arguments promoting expensive value, then we accept arguments promoting healthy value”. This paper extends VAF by incorporating some constraints, expressed as propositional formulas on either the arguments’ values or on the arguments. We propose two inference relations for defining some acceptability semantics in such constrained value-based argumentation framework (CVAF). The first inference relation is more prudent than the second one since it derives less arguments. © Springer International Publishing Switzerland 2016. Source

Rakotomamonjy T.,ONERA | Ouladsine M.,Domaine University Of Saint Jerome | Moing T.L.,ONERA
Control Engineering Practice

A simulation model, flight-dynamics oriented, of a flapping-wing micro aerial vehicle (MAV) is presented here. The model, based on animal flapping flight, integrates the aerodynamic forces computed along each wing to determine the global motion of the MAV with respect to an inertial reference frame. After some analytic simplifications, and taking into account the periodic nature of the system inputs, an averaged model is derived, and a simple, nonlinear closed-loop control law is designed for the dynamics along the vertical and pitch axis, allowing an efficient stabilization of the naturally unstable model. © 2010 Elsevier Ltd. Source

Mercantini J.-M.,Domaine University Of Saint Jerome
Intelligent Systems Reference Library

The purpose of this chapter is to show that cognitive approaches can offer very powerful engineering environments to tackle issues raised by risk management. The investigated issue is the planning of actions to fight accidental marine pollutions. The response proposed is a software tool (GENEPI) to support stakeholders to plan fight actions during emergency situations or crisis management with the objective to minimize pollution impacts. From a methodological perspective, the chapter shows the importance to develop ontologies (i) for structuring a domain as perceived by its actors and (ii) for building computer tools aimed to support problem solving in that domain. Such tools are imbued of the knowledge shared by the actors of the domain, what make them more effective within critical situations. The methodological process is based on the Knowledge Engineering method: “Knowledge Oriented Design” (KOD), which is founded on the fields of linguistics and cognitive anthropology. The resulting ontology, the architecture of the software tool and the plan generation mechanism are presented and discussed. © Springer-Verlag Berlin Heidelberg 2015. Source

Mercantini J.M.,Domaine University Of Saint Jerome
Intelligent Systems Reference Library

The introduction chapter is a discussion about the title of the book. Why having associated the concepts of Risk and Cognition? What are the implications of this association? The responses to these questions have strong consequences on how to apprehend critical problems that emerge (or could emerge) within various activity domains. The chapter presents the two concepts of risk and cognition, and it highlights and analyses relations linking them. The complexity of the risk concept is tackled via historical, ontological and conceptual approaches. The cognition concept is defined and the filiation bonds between Cognition, Cognitive Science, Cognitive Engineering and Knowledge Engineering are presented. The set of cognition concepts defines a coherent field of interdisciplinary knowledge (scientific, methodological and technical), which provides operational tools for the analysis and the design of complex systems (or organizations) where risks are prominent. © Springer-Verlag Berlin Heidelberg 2015. Source

Ismail A.,Domaine University Of Saint Jerome | Quafafou M.,Domaine University Of Saint Jerome | Nachouki G.,LINA Laboratory | Hajjar M.,Lebanese University
Journal of Emerging Technologies in Web Intelligence

Peer-to-peer (P2P) computing is currently attracting enormous attention. P2P systems have emerged as a popular way to share huge volumes of data. In such systems each peer is a database management system in itself, ex-posing its own schema. A fundamental problem that confronts peer-to-peer applications is the efficient location of the node that stores a desired data item. In such settings, the main objective is the efficient search across peer databases by processing each incoming query without overly consuming bandwidth. In this paper, we propose an architecture based on (super-)peers, and we focus on query routing. Our approach considers that (super-)Peers having similar interests are grouped together for an efficient query routing method. In such groups, called Knowledge-Super-Peers (KSP), super-peers submit queries that are often processed by members of this group. A KSP is a specific super-peer which contains knowledge about: 1. its superpeers and 2. The others super-peers. Knowledge is extracted by using data mining techniques (e.g. decision tree algorithms) starting from queries of peers that transit on the network. The advantage of this distributed knowledge is that, it avoids to making semantic mapping, between heterogeneous data sources owned by (super-)peers, each time the system decides to route query to other (super-)peers. The set of KSP improves the robustness in queries routing mechanism and scalability in P2P Network. Compared with a baseline approach, our proposal shows a better performance using a new simulator with respect to important criteria such as response time, precision and recall. © 2011 ACADEMY PUBLISHER. Source

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