The current landmine clearance methods mostly rely on the manual use of metal detectors (MDs) and on the deminer’s experience in differentiating between the sounds emitted due to the presence of a landmine or of harmless clutter. This process suffers from high false-alarm rates, which renders the demining effort slow and costly. In this paper, we report our attempts in using machine learning for decision making in the demining process. We have created our own database of the MD responses corresponding to landmines and/or clutter. A robotic rail is designed and assembled to accurately measure these responses and build the database. Several machine learning models are then developed using the database with the aim of detecting the presence of landmines and classifying them. It is shown that the classification algorithms lead to accurately discriminating the landmines and distinguishing between different buried objects including mines or other items based on the metal detector delivered data or signature.

In this paper, we first provide a unified algorithm for computing simple forms for systems of pseudo-linear equations. We prove that the existing methods for linear differential and difference systems can be extended to handle more general pseudo-linear systems. We explain how the reduction to a simple form can be used to compute efficiently local data for a system of pseudo-linear equations. We then propose an alternative, again based on simple forms, to previous algorithms for computing rational solutions of pseudo-linear systems. Moreover we develop a new algorithm for computing rational solutions of systems in two variables composed of linear differential and difference equations. Finally, we show that this algorithm can be generalized to the case of a system of partial pseudo-linear equations. All the algorithms described in this paper have been implemented in Maple and some examples of computations are provided.

Advanced antenna arrays at the base stations are one of the key techniques to improve the downlink capacity of WCDMA cellular systems. Traditionally, linear and circular arrays are used to form the beams. In this paper, cylindrical antenna arrays with various types of input excitations are proposed, and the beam steering adaptive antenna technique is considered. The user capacity per cell among the linear, circular, and cylindrical arrays is presented and compared in a simulation environment supporting various types of adaptive antennas, soft/softer handover, and multiple services. A notable superiority of the proposed cylindrical antenna arrays was demonstrated by the simulation results.

Evaluation systems for handicapped people through adapted interface are used to measure of people motor disability parameters and to provide assistance. In this work, a friendly reconfigurable evaluation and assistance platform for handicapped people is presented. A set of interfaces (mouse, joysticks, etc.) is used for controlling the pointing system. Different systems can be controlled (PCs cursor, robot Khepera, electric wheelchair). The main characteristics of this platform are the availability of several interface devices, exercises interaction with 2D models or 3D models, the saving of experimental data, the easy configuration of different scenarios, and the remote access capabilities. The system is illustrated through an implementation example and preliminary results are shown on a child with cerebral palsy