Extracting constraints from direct detection searches of supersymmetric dark matter in the light of null results from the LHC in the squark sector

The comparison of the results of direct detection of Dark Matter, obtained with various target nuclei, requires model-dependent, or even arbitrary, assumptions. Indeed, to draw conclusions either the spin-dependent (SD) or the spin-independent (SI) interaction has to be neglected. In the light of the null results from supersymmetry searches at the LHC, the squark sector is pushed to high masses. We show that for a squark sector at the TeV scale, the framework used to extract contraints from direct detection searches can be redefined as the number of free parameters is reduced. Moreover, the correlation observed between SI and SD proton cross sections constitutes a key issue for the development of the next generation of Dark Matter detectors.Comment: Figure 3 has been updated. Conclusions unchange

Modélisation, classification et propagation dans des réseaux d'influence

The cognitive map model provides a user a solution to visualize the influences between different notion, and to compute the propagation of influences on a target. Like cognitive maps, our model offers a graphical representation of influences between notions. The distinctive feature of our model is that on a unique support, each notion is precisely defined by conceptual graphs. The combination of operations of cognitive maps and operations of conceptual graphs provides a powerful method to make decision. Firstly, the definition of a notion and the projection provides a solution to compute semantically linked notions. Secondly, original propagations can be computed from such semantically linked notions

Les cartes cognitives hiérarchiques

Une carte cognitive fournit une représentation graphique d’un réseaud’influence entre des concepts. Les cartes cognitives de dimensions importantes ont l’inconvénient d’être difficiles à appréhender, interpréter et exploiter. Cet article présente un modèle de cartes cognitives hiérarchiques permettant au concepteur d’effectuer des regroupements de concepts qui sont ensuite utilisés dans un mécanisme permettant à l’utilisateur d’obtenir des vues partielles et synthétiques d’une carte

Contextual Cognitive Map

The model of cognitive maps introduced by Tolman [1] provides a representation of an influence network between notions. A cognitive map can contain a lot of influences that makes difficult its exploitation. Moreover these influences are not always relevant for different uses of a map. This paper extends the cognitive map model by describing the validity context of each influence with a conceptual graph. A filtering mechanism of the influences according to a use context is provided so as to obtain a simpler and more adjusted map for a user. A prototype that implements this model of contextual cognitive map has been developed

A useful logical semantics of UML for querying and checking UML class diagram

Date du colloque : 01/2009International audienc

Using UML Class Diagram as a Knowledge Engineering Tool

Date du colloque : 05/2000International audienc

On commutativity based edge lean search

Exploring a graph through search is one of the most basic building blocks of various applications. In a setting with a huge state space, such as in testing and verification, optimizing the search may be crucial. We consider the problem of visiting all states in a graph where edges are generated by actions and the (reachable) states are not known in advance. Some of the actions may commute, i.e., they result in the same state for every order in which they are taken (this is the case when the actions are performed independently by different processes). We show how to use commutativity to achieve full coverage of the states while traversing considerably fewer edges