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Seismic noise filtering based on Generalized Regression Neural Networks
No full textThis paper deals with the application of Generalized Regression Neural Networks to the seismic data filtering. The proposed system is a class of neural networks widely used for the continuous function mapping. They are based on the well known nonparametric kernel statistical estimators. The main advantages of this neural network include adaptability, simplicity and rapid training. Several synthetic tests are performed in order to highlight the merit of the proposed topology of neural network. In this work, the filtering strategy has been applied to remove random noises as well as source-related noises from real seismic data extracted from a field in the South of Algeria. The obtained results are very promising and indicate the high performance of the proposed filter in comparison to the well known frequency–wavenumber filte
Trabecular Texture Analysis Using Fractal Metrics for Bone Fragility Assessment
No full textThe purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an age-matched control group of 28 women using texture analysis based on fractals. Two pre-processing approaches are applied on radiographic images; these techniques are compared to highlight the choice of the pre-processing method. Furthermore, the values of the fractal dimension are compared to those of the fractal signature in terms of the classification of the two populations. In a second analysis, the BMD measure at proximal femur was compared to the fractal analysis, the latter, which is a non-invasive technique, allowed a better discrimination; the results confirm that the fractal analysis of texture on calcaneus radiographs is able to discriminate osteoporotic patients with femoral fracture from controls. This discrimination was efficient compared to that obtained by BMD alone. It was also present in comparing subgroups with overlapping values of BM
Reformulation de requêtes: Application aux systèmes de recherche d'information dans des documents XML
No full textLa problématique traitée dans le cadre de cet ouvrage se situe dans le contexte de la recherche d'information (RI), plus particulièrement la recherche d'information dans des documents XML. L'objectif de cet ouvrage est de proposer une solution pour adapter le processus de reformulation de requêtes, bien connu et bien établi dans les systèmes de recherche d'information plein texte, à la recherche d'information dans des documents XML. L'utilisation de la technique de réinjection de pertinence dans le contexte de la RI structurée nécessite la prise en charge de la dimension structurelle en plus de la dimension textuelle. Nous tentons d'apporter des réponses aux différentes questions posées, à savoir : Comment effectuer une reformulation de requêtes par réinjection de pertinence dans le contexte de la RI structurée? Comment extraire les meilleurs termes à partir d'unités d'information jugées pertinentes et non pertinentes par l'utilisateur, sachant que ces unités peuvent avoir différentes sémantiques? Quels poids doit-on assigner aux termes choisis dans les différents cas de figures? Comment intégrer l'information structurelle dans la génération de la nouvelle requête
Elaboration and characterization of a cellular glass based cullet loaded with carbon fibers
No full textStructural boundaries delimitation from aeromagnetic data using the horizontal gradient and the continuous wavelet transform : a case study of in Ouzzal area, west of Hoggar, Algeria
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Interlayer exchange coupling between FeCo and Co ultrathin films through Rh(001) spacers
No full textKinetic, equilibrium and thermodynamic study on the removal of Congo Red from aqueous solutions by adsorption onto apricot stone
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