This paper is a testimony on the relations between the Internet users and their governments in France during the last decade. It shows the complexity of communication between two worlds that are strangers to each other. Since most of the confrontation occurred over law proposals, it analyses their impact on Internet users and focuses on two examples. These example show the failure of Internet as a political medium. French politicians do not seem to want an active participation of the citizens in decisionmaking processes. In order to end this paper on an optimistic note, the last section enumerates the achievements of egovernment which contributed preparing for a better democracy by increasing transparency, accountability, and education. This might push citizens to ask for more.

In large Quantum Key Distribution (QKD)-based networks, intermediate nodes are necessary because of the short length of QKD links. They have tendency to be used more than classical networks. A realistic assumption is that there are eavesdropping operations in these nodes without knowledge of legitimate network participants. We develop a QKD-based network framework. We present a percolation-based approach to discuss about conditions of extremely high secret key transmission. We propose also an adaptive stochastic routing algorithm that helps on protecting keys from reasonable eavesdroppers in a dense QKD network. We show that under some assumptions, one could prevent eavesdroppers from sniffing the secrets with an arbitrarily large probability.

We present an identification and authentification system based on hand modality which is part of a reference system for all modalities developed within the Biosecure consortium. It relies on simple geometric features extracted from hand boundary. The different steps of this system are detailed, namely: pre-processing, feature extraction and hand matching. This system has been tested on the Biosecure hand database which consists of 4500 hand images of 750 individuals. Results are detailed with respect to different enrolment conditions such as population size, enrolment size, and image resolution.

This paper is concerned itself with the analysis of the two-phase Mumford-Shah model also known as the active contour without edges model introduced by Chan and Vese. It consists of approximating an observed image by a piecewise constant image which can take only two values. First we show that this model with the $L^1$-norm as data fidelity yields a contrast invariant filter which is a well known property of morphological filters. Then we consider a discrete version of the original problem. We show that an inclusion property holds for the minimizers. The latter is used to design an efficient graph-cut based algorithm which computes an exact minimizer. Some preliminary results are presented.

Model checking is a formal verification technique that allows to automatically prove that a system’s behavior is correct. However it is often prohibitively expensive in time and memory complexity, due to the so-called state space explosion problem. We present a generic multi-threaded and distributed infrastructure library designed to allow distribution of the model checking procedure over a cluster of machines. This library is generic, and is designed to allow encapsulation of any model checker in order to make it distributed. Performance evaluations are reported and clearly show the advantages of multi-threading to occupy processors while waiting for the network, with linear speedup over the number of processors.

This paper investigates the problem of secret key transmissions for an arbitrary Alice-Bob pair in Quantum Key Distribution-based networks. We develop a realistic QKD-based network framework and we show that the key transmission problem on such a framework can be considered as a variant of the classical percolation problem. We also present an adaptive stochastic routing algorithm protect from inevitable eavesdroppers. Simulations were carried out not only to validate our approach, but also to compute critical parameters ensuring security. These results show that large quantum networks with eavesdroppers do provide security.

Implementing binary methods in traditional object oriented languages is difficult: numerous problems arise, such as typing (covariance vs. contra-variance of the arguments), polymorphism on multiple arguments (lack of multi-methods) etc. The purpose of this paper is to demonstrate how those problems are either solved, or nonexistent in the Common Lisp Object System (CLOS). Several solutions for different levels of binary methods support in CLOS are proposed. They mainly consist in re-programming a binary method specific object system through the CLOS meta-object protocol.

It is well-known that Total Variation (TV) minimization with L2 data fidelity terms (which corresponds to white Gaussian additive noise) yields a restored image which presents some loss of contrast. The same behavior occurs for TVmodels with non-convex data fidelity terms that represent speckle noise. In this note we propose a new approach to cope with the restoration of Synthetic Aperture Radar images while preserving the contrast.

This paper deals with the total variation minimization problem in image restoration for convex data fidelity functionals. We propose a new and fast algorithm which computes an exact solution in the discrete framework. Our method relies on the decomposition of an image into its level sets. It maps the original problems into independent binary Markov Random Field optimization problems at each level. Exact solutions of these binary problems are found thanks to minimum cost cut techniques in graphs. These binary solutions are proved to be monotone increasing with levels and yield thus an exact solution of the discrete original problem. Furthermore we show that minimization of total variation under $L^1$ data fidelity term yields a self-dual contrast invariant filter. Finally we present some results.

In Part II of this paper we extend the results obtained in Part I for total variation minimization in image restoration towards the following directions: first we investigate the decomposability property of energies on levels, which leads us to introduce the concept of levelable regularization functions (which TV is the paradigm of). We show that convex levelable posterior energies can be minimized exactly using the level-independant cut optimization scheme seen in part I. Next we extend this graph cut scheme optimization scheme to the case of non-convex levelable energies. We present convincing restoration results for images corrupted with impulsive noise. We also provide a minimum-cost based algorithm which computes a global minimizer for Markov Random Field with convex priors. Last we show that non-levelable models with convex local conditional posterior energies such as the class of generalized gaussian models can be exactly minimized with a generalized coupled Simulated Annealing.