Application du recuit simulé à la synthèse d’antennes en réseau constituées d’éléments annulaires imprimés

This publication consists of an analysis and a synthesis by the amplitude law of linear and planar ring printed antennas array. The analysis of the structure is based on the modified cavity model which allows taking into account the fringing fields effects. The synthesis problem is solved by the simulated annealing method based on a random process research controlled by temperature parameter. The feeding network amplitude permitting to produce an optimal radiation pattern is then given. Various synthesis results for linear and planar arrays are presented.     

Morphological evolution of edge-hillocks on single-crystal films having anisotropic drift-diffusion under the capillary and electromigration forces

The morphological evolution of hillocks at the unpassivated sidewalls of single-crystal metallic thin film interconnects is investigated via computer simulations using the free-moving boundary value problem. The effect of drift-diffusion anisotropy on the development of surface topographical scenarios is fully explored under the action of electromigration and capillary forces, utilizing numerous combinations of the surface texture, the drift-diffusion anisotropy and the direction of the applied electric field. The simulation studies yield analytical relationships for the velocity of the surface solitary waves and the drift velocity of electromigration-induced internal voids as a function of the applied current densities, which contain intrinsic and structural properties of the single-crystal thin films. The threshold value of the applied current density, above which electromigration-induced internal voids can be formed and may cause the catastrophic failure of interconnects by breaching, also appears explicitly in this relationship.     

Visual reasoning about social networks using centrality sensitivity

In this paper, we study the sensitivity of centrality metrics as a key metric of social networks to support visual reasoning. As centrality represents the prestige or importance of a node in a network, its sensitivity represents the importance of the relationship between this and all other nodes in the network. We have derived an analytical solution that extracts the sensitivity as the derivative of centrality with respect to degree for two centrality metrics based on feedback and random walks. We show that these sensitivities are good indicators of the distribution of centrality in the network, and how changes are expected to be propagated if we introduce changes to the network. These metrics also help us simplify a complex network in a way that retains the main structural properties and that results in trustworthy, readable diagrams. Sensitivity is also a key concept for uncertainty analysis of social networks, and we show how our approach may help analysts gain insight on the robustness of key network metrics. Through a number of examples, we illustrate the need for measuring sensitivity, and the impact it has on the visualization of and interaction with social and other scale-free networks.     

Service Oriented Approach State of the Art

For many years, computer systems have emerged; they now occupy an important place in our daily lives. The growing needs and ever increasing use of computer systems have made application development more and more complicated, The complexity of these applications poses problems such as reuse, installation, administration and evolution of applications. The development of applications is related to the evolution of paradigms and approaches to developing them. This paper presents different approaches and paradigms of development starting with the procedural approach, coming up for service, through the component and object-oriented approaches. Also, for each of the approaches we determine the advantages and limitations.     

Experimental analysis of fuel from fish processing industry waste in a diesel engine

In the present work, biofuel derived from industrial fish processing industry waste is used in diesel engines to study its suitability . Biofuel from industry fish waste is produced through catalytic cracking, and its quality has been improved through distillation. A single cylinder 4.5 kW at 1500 rpm was used to find the suitability of biofuel and undistilled biofuel in diesel engine. Experimental results show that the brake thermal efficiency of biofuel and undistilled biofuel is similar. Brake thermal efficiency for diesel, undistilled biofuel and biofuel is 29.98, 32.12 and 32.4%, respectively, at 80% load. Carbon monoxide, unburnt hydrocarbons, particulate matter and oxides of nitrogen emissions increase with undistilled biofuel compared to biofuel. There is a small reduction in carbon dioxide emission with undistilled biofuel compared to biofuel. Even though the cylinder pressure is high with undistilled biofuel, the intensity of premixed combustion is lower than distilled biofuel. The ignition delay and combustion duration increase with undistilled biofuel. Finally, it is concluded that the fuel derived from fish processing industry waste can be used as a fuel for diesel engine after distillation.     

Coverage-guided test generation for continuous and hybrid systems

In this paper, we describe a formal framework for conformance testing of continuous and hybrid systems, using the international standard ‘Formal Methods in Conformance Testing’ FMCT. We propose a novel test coverage measure for these systems, which is defined using the star discrepancy notion. This coverage measure is used to quantify the validation ‘completeness’. It is also used to guide input stimulus generation by identifying the portions of the system behaviors that are not adequately examined. We then propose a test generation method, which is based on a robotic motion planning algorithm and is guided by the coverage measure. This method was implemented in a prototype tool that can handle high dimensional systems (up to 100 dimensions).     

On basic properties of fault-tolerant multi-topology routing

Multi-topology routing has recently gained popularity as a simple yet efficient traffic engineering concept. Its basic purpose is to separate different classes of network traffic, which are then transported over disjoint logical topologies. Multi-topology routing is used as a basis for implementation of an IP fast reroute scheme called Multiple Routing Configurations (MRC).MRC has a range of attractive properties, but they do come at a cost. In order to guarantee recovery from any single link or node failure in the network, MRC has to maintain several logical topologies and thus an increased amount of routing information. The number of the logical topologies in MRC need not be large; even simple heuristic algorithms often yield good results in practice. However, why this is the case is not fully understood yet.In this paper, we introduce a theoretical framework for fault-tolerant multi-topology routing (FT-MTR). MRC is a practical implementation of FT-MTR in connectionless IP networks. We use FT-MTR to study how the internal topological structure of the communication network relates to two important problems. The first problem is minimizing the number of logical topologies and thus the routing state in FT-MTR. We show how to use the sets of nodes that separate the topology graph to devise an advanced heuristic for “intelligent” construction of the logical topologies. Finding the separating sets in a topology graph is computationally demanding; we present an algorithm that performs well in tested real network topologies. We evaluate the separation-set based heuristic for the logical topology construction and show that it outperforms the known MRC heuristics.The second problem is the FT-MTR load distribution after a failure. We use the separating sets to devise a novel algorithm for failure load distribution. This algorithm does not require knowledge of the traffic demand matrix, still, our tests indicate that it performs as good as, or better than, known MRC load-distribution algorithms that do require the demand matrix as input.     

Real object recognition using moment invariants

Moments and functions of moments have been extensively employed as invariant global features of images in pattern recognition. In this study, a flexible recognition system that can compute the good features for high classification of 3-D real objects is investigated. For object recognition, regardless of orientation, size and position, feature vectors are computed with the help of nonlinear moment invariant functions. Representations of objects using two-dimensional images that are taken from different angles of view are the main features leading us to our objective. After efficient feature extraction, the main focus of this study, the recognition performance of classifiers in conjunction with moment-based feature sets, is introduced     

Automatic speech recognition system for Tunisian dialect

Although Modern Standard Arabic is taught in schools and used in written communication and TV/radio broadcasts, all informal communication is typically carried out in dialectal Arabic. In this work, we focus on the design of speech tools and resources required for the development of an Automatic Speech Recognition system for the Tunisian dialect. The development of such a system faces the challenges of the lack of annotated resources and tools, apart from the lack of standardization at all linguistic levels (phonological, morphological, syntactic and lexical) together with the mispronunciation dictionary needed for ASR development. In this paper, we present a historical overview of the Tunisian dialect and its linguistic characteristics. We also describe and evaluate our rule-based phonetic tool. Next, we go deeper into the details of Tunisian dialect corpus creation. This corpus is finally approved and used to build the first ASR system for Tunisian dialect with a Word Error Rate of 22.6%.     

Self-calibration of stationary non-rotating zooming cameras

This paper proposes a new method for self-calibrating a set of stationary non-rotating zooming cameras. This is a realistic configuration, usually encountered in surveillance systems, in which each zooming camera is physically attached to a static structure (wall, ceiling, robot, or tripod). In particular, a linear, yet effective method to recover the affine structure of the observed scene from two or more such stationary zooming cameras is presented. The proposed method solely relies on point correspondences across images and no knowledge about the scene is required. Our method exploits the mostly translational displacement of the so-called principal plane of each zooming camera to estimate the location of the plane at infinity. The principal plane of a camera, at any given setting of its zoom, is encoded in its corresponding perspective projection matrix from which it can be easily extracted. As a displacement of the principal plane of a camera under the effect of zooming allows the identification of a pair of parallel planes, each zooming camera can be used to locate a line on the plane at infinity. Hence, two or more such zooming cameras in general positions allow the obtainment of an estimate of the plane at infinity making it possible, under the assumption of zero-skew and/or known aspect ratio, to linearly calculate the camera's parameters. Finally, the parameters of the camera and the coordinates of the plane at infinity are refined through a nonlinear least-squares optimization procedure. The results of our extensive experiments using both simulated and real data are also reported in this paper.