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International audience; Recently, the home healthcare system has emerged as one of the most useful technology for e-healthcare. Contrary to classical recording methods of patient's medical data, which are, based on paper documents, nowadays all this sensitive data can be managed and forwarded through digital systems. These make possible for both patients and healthcare workers to access medical data or receive remote medical treatment using wireless interfaces whenever and wherever. However, simplifying access to these sensitive and private data can directly put patient's health and life in danger. In this paper, we propose a secure and lightweight biometric-based remote patient authentication scheme using elliptic curve encryption through which two mobile healthcare system communication parties could authenticate each other in public mobile healthcare environments. The security and performance analysis demonstrate that our proposal achieves better security than other concurrent schemes, with lower storage, communication and computation costs.

The objective of this work is to analyze the dynamic behavior (modal behavior) of the "Oued Taht" arch dam located at MASCARA, taking into consideration the effect of soil-fluid-structure interaction. The finite element code "Ansys" was chosen for the dynamic modeling of the dam that is the subject of this study. Three hypotheses were used for soil-structure interaction modeling; model with embedded base which corresponds to the case where the phenomenon of interactions soil-structure is neglected, model with ground of foundation without mass which consists in taking into account the kinematic component of interaction soil structure and neglecting the inertial component and the model with foundation soil with mass where the two components of soil-structure interaction are taken into account. For the fluid, the model of added masses (equivalent to the westergaard approach) using the SURF element available in the Ansys code library was used. A comparison between the different models of the "Oued Taht" dam was made; it has been found that the taking into account of the soil-fluid-structure interaction phenomenon modifies the period of the system and that the modeling of the dam with and without fluid gives a very important difference of the periods. The results obtained were compared with those of the "Brezina" dam, which is a gravity dam located in BAYADH. The work has shown that the periods of the "Oued Taht" dam with soil-fluid-structure interaction modeling are very out of phase with the periods without fluid modeling (taking into account only the soilstructure interaction phenomenon). which is not the case for the Brezina dam where the periods for the two models are getting closer. The periods between the two models mentioned before are close to the dam of Brézina because the latter is a dam which participates much more by its own weight than by its vault (thickness of the vault varies between 36.3 m at the base and 5m in crest) which is the opposite for the dam "Oued Taht" which participates by its vault (constant thickness of 7 m) thus the membrane effect is present, which is translated by the shift of the periods between the empty case and the filled case.

International audience; Nowadays, there are many causes of daily traffic accidents, one of them is the loss of concentration while driving due to drowsiness, followed by sleep while driving. Sleeping means the nap; no more than a few seconds, but it is enough to create a traffic accident, in which the driver and the clashes may lose their lives. In this context, there is a host and considerable research efforts made in designing driver monitoring systems with the aim to reduce the vehicular accidents posing a challenging issue for the society. Several drowsiness detection techniques have been proposed in the literature, including artificial neural network, image processing, and physiological measurement techniques. Among the proposed solutions, the electroencephalographic (EEG) measurement is one of the reliable techniques. Nevertheless, the brain signals can be easily contaminated by many artifact types arising from cardiac (ECG), muscles (EMG), and ocular activities (EOG). From these physiological artifacts, ocular activities are one of the most eminent over other noise sources. In this paper, we provide a comprehensive survey, which covers the vast existing techniques of removing ocular artifacts from EEG recordings for driver's drowsiness detection systems. We propose a novel taxonomy of solutions and we compare them with respect to relevant criteria.