The annealing and relaxation of internal stresses in optical fibers are investigated. An empirical equation representing the relaxation is fitted and a result concerning the lifetime of optical-fiber cables is deduced.

International audienceThe variety of wireless communication standards and their corresponding applications requires more and more flexible, yet efficient, implementations. The emerging flexibility need induces a new challenge when added to the ever increasing requirements in terms of high throughput and low complexity. This paper presents a design of an application-specific processor dedicated for a minimum mean square error interference cancellation (MMSE-IC) linear equalizer (LE) used in iterative multi-input multi-output (MIMO) turbo receiver. The explored design approach applies static scheduling of datapath control signals. The proposed architecture supports the requirements of flexibility for different MIMO system configurations concerning channel time selectivity and transmission diversity. In order to evaluate the efficiency of the adopted architecture model for this kind of applications and requirements, a fair comparison is conducted with a state-of-the-art application specific instruction-set processor (ASIP) implementation. The obtained results illustrate a significant performance improvement in terms of execution time and implementation area while using identical computational resources and supporting same flexibility parameters

This paper presents a numerical solution, using MATLAB, of the electrostatic potential in a pn junction, which obeys Poisson's equation. This numerical method is based on the Newton-Raphson technique and is useful for educational purposes. It can be incorporated in an undergraduate course on semiconductor devices to demonstrate the applications of numerical analysis techniques in device physics. It may also be appropriate for a section on numerical analysis techniques in an engineering mathematics course.

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Abstract:Moving foreground detection is a very important step for many applications such as human behavior analysis for visual surveillance, model-based action recognition, road traffic monitoring, etc. Background subtraction is a very popular approach, but it is difficult to apply given that it must overcome many obstacles, such as dynamic background changes, lighting variations, occlusions, and so on. In the presented work, we focus on this problem (foreground/background segmentation), using a type-2 fuzzy modeling to manage the uncertainty of the video process and of the data. The proposed method models the state of each pixel using an imprecise and adjustable Gaussian mixture model, which is exploited by several fuzzy classifiers to ultimately estimate the pixel class for each frame. More precisely, this decision not only takes into account the history of its evolution, but also its spatial neighborhood and its possible displacements in the previous frames. Then we compare the proposed method with other close methods, including methods based on a Gaussian mixture model or on fuzzy sets. This comparison will allow us to assess our method's performance, and to propose some perspectives to this work.