We design numerical schemes for nonlinear degenerate parabolic systems with possibly dominant convection. These schemes are based on discrete BGK models where both characteristic velocities and the source-term depend singularly on the relaxation parameter. General stability conditions are derived, and convergence is proved to the entropy solutions for scalar equations.

We consider a coperative control approach to address safety and optimality issues for simple model of a car-like robot. The approach makes use of optimal syntheses and Krasovskii solutions to discontinuous ODEs.

We provide a general approach to deal with entropy solutions to scalar conservation laws presenting nonclassical shocks.

This paper presents a generalization of Kokaram's model for scratch lines detection on digital film materials. It is based on the assumption that scratch is not purely additive on a given image but shows also a destroying effect. This result allows us to design a more efficacious scratch detector which performs on a hierarchical representation of a degraded image, i.e., on its cross section local extrema. Thanks to Weber's law, the proposed detector even works well on slight scratches resulting completely automatic, except for the scratch color (black or white). The experimental results show that the proposed detector works better in terms of good detection and false alarms rejection with a lower computing time.

In this paper we discuss the structure of the factors of a QR- and a URV-factorization of a diagonal-plus -semiseparable matrix. The Q-factor of a QR-factorization has the diagonal-plus-semiseparable structure. The U- and V-factor of a URV-factorization are semiseparable lower Hessenberg orthogonal matrices. The strictly upper triangular part of the R-factor of a QR- and of a URV-factorization is the strictly upper triangular part of a rank-2 matrix. This latter fact provides a tool to construct a fast QR-solver and a fast URV-solver for linear systems of the form (D + S)x = b. c 2003 Elsevier B.V. All rights reserved.

We introduce a functional for image segmentation which takes into account the transparencies (or shadowing) and the occlusions between objects located at different depths in space. By minimizing the functional, we try to reconstruct a piecewise smooth approximation of the input image, the contours due to transparencies, and the contours of the objects together with their hidden portions. The functional includes a Mumford-Shah type energy and a term involving the curvature of the contours. The variational properties of the functional are studied, as well as its approximation by Gamma-convergence. The comparison with the Nitzberg-Mumford variational model for segmentation with depth is also discussed.

In this paper we construct a de la Vallée Poussin approximation process for orthogonal polynomial expansions. Our construction is based on convolution structures which are established by the orthogonal polynomial system. We show that our approach leads to a natural generalization of the de la Vallee Poussin approximation process known from the trigonometric case. Finally we consider Jacobi polynomials and the generalized Chebyshev polynomials expansions as examples.

The purpose of this paper is to show the theoretical soundness of a variational method proposed in image processing for supervised classification. Based on works developed for phase transitions in fluid mechanics, the classification is obtained by minimizing a sequence of functionals. The method provides an image composed of homogeneous regions with regular boundaries, a region being defined as a set of pixels belonging to the same class. In this paper, we show the Gamma-convergence of the sequence of functionals which differ from the ones proposed in fluid mechanics in the sense that the perturbation term is not quadratic but has a finite asymptote at infinity, corresponding to an edge-preserving regularization term in image processing.

We consider a model for detecting corrosion on the (inaccessible) conducting top side of a metallic plate. We suppose that the effects of corrosion attack consist in material loss. The perturbation so induced in the geometry of the plate is described by a positive function $\theta$. We prove that a suitable data set, collected on the bottom side of the plate, identifies $\theta$ uniquely.

Nel presente lavoro si studia lo scheduling nelle celle robotizzate in presenza di un braccio meccanico che deve eseguire operazioni di load, process e unload su macchine a controllo numerico. Viene studiata la complessità del problema quando l'obiettivo è la minimizzazione del tempo di completamento delle lavorazione relative ai pezzi nello shop. Per questo problema viene sviluppata un'euristica e se ne mostra il comportamento sperimentale.

Dynamic magnetic resonance imaging with contrast agent is a very promising technique for mammography. A temporal sequence of magnetic resonance images of the same slice are acquired following the injection of a contrast agent in the blood stream. The image intensity depends on the local concentration of the contrast agent so that tissue perfusion can be studied using the image sequence. A new statistical method of analyzing such sequences is presented. The method is developed within the Bayesian framework. A specific statistical model is used to take into account image degradation. In addition, a suitable Markov random field allows us to model some relevant ``a priori'' information on the quantities to be estimated. Inference is based on simulations from the posterior distribution obtained by means of Markov chain algorithms. The issue of hyper-parameter estimation is also addressed. Image classification is also performed by means of a new Bayesian method. Some results obtained from sequences of dynamic magnetic resonance images of human breasts will be illustrated.

Nel presente lavoro ci si occupa dello scheduling su griglie computazionali, fornendo un modello basato sul problema del rectangle packing. Viene fornita un'ampia sperimentazione, anche in presenza di malleabilità dei task da schedulare.

Questo lavoro si occupa di graph coloring. In particolare viene proposto un algoritmo di branch and bound troncato in grado di calcolare buoni lower bound sul numero cromatico di un grafo e spesso fornisce la soluzione ottima.

Nel presente lavoro studiamo problemi di localizzazione stocastica.