In this paper, the random access procedure of Universal Mobile Telecommunications System network is investigated. We have proposed a model based on communicating timed automata that represents the main functions related to the random access procedure including the user equipment, the base station (node B or BTS), and the channel. Then, we have used computational tree logic formula to specify the proprieties to be verified. The model and the formulas serve as inputs to the model checker, which is used as a verification engine, ie, UPPAAL and SPIN. The formal verification approach shows that the protocol has several drawbacks that may not be detected by simulation.

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Shadows cause problems in many remote sensing applications like images segmentation, objects extraction and stereo vision. This paper presents a new and an automatic approach to detect and remove shadows from pair of dense urban very high resolution (VHR) remote sensing images. The main contribution of this paper is twofold. First, a proposed approach is efficient to restore objects hidden by shadows, second, it improves a stereo matching process. We have chosen to operate on Ikonos pairs as an example of urban remote sensing images, for that, shadow detection is achieved using a new technique of property based method, operating directly in red, green and blue colour space (RGB). Shadow removal proposed technique aims to produce a needed amount of light to the shadow regions by multiplying the shadow regions by constants, after that, the shadow edge correction is applied to reduce the errors due to diffusion in the shadow boundary. Once pair of shadow free images is recovered, we apply a stereo matching process using a Hopfield neural technique in order to find homologous regions. Our results from different urban pairs show the effectiveness, the simplicity and the fastness of the proposed approach to reveal details hidden by shadows and to obtain a high stereo matching rate.