Improving the Performances of Asynchronous Search Algorithms in Scale-Free Networks Using the Nogood Processor Technique

The scale-free graphs were proposed as a generic and universal model of network topologies that exhibit power-law distributions in the connectivity of network nodes. In recent years various complex networks were identified as having a scale-free structure. Little research was done concerning the network structure for DisCSP, and in particular, for scale-free networks. The asynchronous searching techniques are characterized by the occurrence of nogood values during the search for a solution. In this article we analyze the distribution of nogood values to agents and the way how to use the information from the nogood; that is called the nogood processor technique. We examine the effect of nogood processor for networks that have a scale-free structure aiming to develop search algorithms specialized for scale-free networks of constraints, algorithms that require minimum costs for obtaining the solution. We develop a novel way for distributing nogood values to agents, thus obtaining a new hybrid search technique that uses the information from the stored nogoods. The experiments show that it is more effective for several families of asynchronous techniques; we perform tests with the model running on a cluster of computers. Also, we examine the effect of synchronization of agents' execution and of processing messages by packets in scale-free networks

Algorithmes pour le traitement des distorsions de forme de raie en Spectroscopie et Imagerie Spectroscopique par Résonance Magnétique

Magnetic Resonance Spectroscopy (MRS) and Spectroscopic Imaging (MRSI) play an emerging role in clinical assessment, providing in vivo estimation of disease markers while being non-invasive and applicable to a large range of tissues. However, static magnetic field inhomogeneity, as well as eddy currents in the acquisition hardware, cause important distortions in the lineshape of acquired NMR spectra, possibly inducing significant bias in the estimation of metabolite concentrations. In the post-acquisition stage, this is classically handled through the use of pre-processing methods to correct the dataset lineshape, or through the introduction of more complex analytical model functions. This thesis concentrates on handling arbitrary lineshape distortions in the case of quantitation methods that use a metabolite basis-set as prior knowledge. Current approaches are assessed, and a novel approach is proposed, based on adapting the basis-set lineshape to the measured signal.Assuming a common lineshape to all spectral components, a new method is derived and implemented, featuring time domain local regression (LOWESS) filtering. Validation is performed on synthetic signals as well as on in vitro phantom data. Finally, a completely new approach to MRS quantitation is proposed, centred on the use of the compact spectral support of the estimated common lineshape. The new metabolite estimators are tested alone, as well as coupled with the more common residual-sum-of-squares MLE estimator, significantly reducing quantitation bias for high signal-to-noise ratio data.La Spectroscopie et l'Imagerie Spectroscopique de Résonance Magnétique (ISRM) jouent un rôle émergent parmi les outils cliniques, en donnant accès, d'une manière complètement non-invasive, aux concentrations des métabolites in vivo. Néanmoins, les inhomogénéités du champ magnétique, ainsi que les courants de Foucault, produisent des distorsions significatives de la forme de raie des spectres, induisant des conséquences importantes en termes de biais lors de l'estimation des concentrations. Lors des traitements post-acquisition, cela est habituellement traité à l'aide des méthodes de pré-traitement, ou bien par l'introduction de fonctions analytiques plus complexes. Cette thèse se concentre sur la prise en compte de distorsions arbitraires de la forme de raie, dans le cas des méthodes qui utilisent une base de métabolites comme connaissance a priori. L'état de l'art est évalué, et une nouvelle approche est proposée, fondée sur l'adaptation de l'amortissement de la base des métabolites au signal acquis. La forme de raie présumée commune à tous les métabolites est estimée et filtrée à l'aide de la méthode LOWESS. L'approche est validée sur des signaux simulés, ainsi que sur des données acquises in vitro. Finalement, une deuxième approche novatrice est proposée, fondée sur l'utilisation des propriétés spectrales de la forme de raie commune. Le nouvel estimateur est testé seul, mais aussi associé avec l'estimateur classique de maximum de vraisemblance, démontrant une réduction significative du biais dans le cas des signaux à haut rapport signal-sur-bruit

The Effects of Agent Synchronization in Asynchronous Search Algorithms

Abstract. The asynchronous searching techniques are characterized by the fact that each agent instantiates its variables in a concurrent way. Then, it sends the values of its variables to other agents directly connected to it by using messages. These asynchronous techniques have different behaviors in case of delays in sending messages. This article depicts the opportunity for synchronizing agents ’ execution in case of asynchronous techniques. It investigates and compares the behaviors of several asynchronous techniques in two cases: agents process the received messages asynchronously (the real situation from practice) and the synchronous case, when a synchronization of the agents ’ execution is done i.e. the agents perform a computing cycle in which they process a message from a message queue. After that, the synchronization is done by waiting for the other agents to finalize the processing of their messages. The experiments show that the synchronization of the agents ’ execution leads to lower costs in searching for solution. A solution for synchronizing the agents ’ execution is proposed for the analyzed asynchronous techniques.