Despite technological advancements, chemical and process industries are still prone to accidents due to their complexity and hazardous installations. These accidents lead to significant losses that represent economic losses and most importantly human losses. Risk management is one of the appropriate tools to guarantee the safe operations of these plants. Risk analysis is an important part of risk management, it consists of different methods such as Fault tree, Bow-tie, and Bayesian network. The latter has been widely applied for risk analysis purposes due to its flexible and dynamic structure. Bayesian networks approaches have shown a significant increase in their application as shown by in the publication in this field. This paper summarizes the result of a literature review performed on Bayesian network approaches adopted to conduct risk assessments, safety and risk analyses. Different application domains are analysed (i.e. accident modelling, maintenance area, fault diagnosis) in chemical and process industries from the year 2006 to 2018. Furthermore, the advantages of different types of Bayesian networks are presented.

The software evolution process means the continuous control of functional and non -functional software characteristics by the change of its code without changing the properties of its quality neither the quality of its architecture. Therefore, the most important problem to be treated is how to limit the progressive shifting between the planned and the implemented architecture during the software evolution process. This phenomenon called the erosion of software architecture, often appears unexpectedly and must be controlled. In this paper, we have proposed an approach to detect erosion problems by representing tactical, strategic, and operational architectural constraints at different abstraction levels. These constraints are specified by the use of the Alloy constraint language in order to restore the deviations that may affect the description of the software architecture during the development steps. Our goal is to control architecture quality by limiting the occurrence and impact of erosion, which means the control of architecture conformance during system development and maintenance activities.

The estimation of average lifetime has been considered as a serious reliability concern for VLSI components. However, with the tremendous downscaling of MOSFET devices, it becomes very difficult to predict such measure with satisfactory precision due to the amplified parasitic effects at the deep scale level. The present work aims at investigating the efficiency of adaptive neuro-fuzzy inference system approach as a predictor of junctionless gate all around MOSFET device lifetime. Our predictions are compared versus the numerical results obtained by ATLAS simulator, where a good agreement is obtained.

Field observations and sedimentological analyses of alluvial terraces of the O. Gourzi (Batna, NE Algeria) lead us to consider sediments as dominated by clayey and silty-sandy fractions overlain by gravel and calcareous coarser fractions. Moderate CaO₃ contents would have resulted from the dissolution of the nearby carbonate relieves. They are mainly composed of Maastrichtian limestones. The distribution of the mineral fraction led us to identify 07 levels including horizons of coarse fractions alternating with layers rich in sand and silt with a roughly constant clay fraction through the stratigraphic column. Kurtosis values, frequency histograms of a prokurtic type, rarily mesokurtic, mark a constant power mode for the transport agent. Classification indices indicate poorly- to moderately sorted material, indicating a turbiditic depositional environment. Quartz grain nature and morphoscopy refer to Miocene sandstones as a potential origin. The ferruginous coating is due to the initiating pedogenesis.

The Internet of Things (IoT) vision is a groundbreaking networking evolution that connects all things that were not meant to be connected to the Internet. Thus, identification technologies and Internet-enabled wireless sensor nodes will be incorporated in homes, cities, vehicles, watches, etc. making them uniquely identified and able to process and communicate information via Internet. Hence, the emergence of the Internet of Things paradigm will bring a lot of smartness to our daily life and will improve the way people monitor their goods, expenses, environment and health status. The smart connected things in the IoT interact with each other and/or with the regular Internet hosts according to two communications styles: Thing-to-Thing(s) (T2T) and Human-to-Thing (H2T). Enabling security for such communications is a real issue especially in H2T interactions. This is mainly due to scarce resources of the connected objects and the asymmetric nature of the communications between those smart things and the ordinary Internet hosts. In this paper we address this problematic and we propose an asymmetric security model that mitigates H2T communication heterogeneities and provides reasonable security costs.

Recently, the desire for a self-powered micro and nanodevices has attracted a great interest of using sustainable energy sources. Further, the ultimate goal of nanogenerator is to harvest energy from the ambient environment in which a self powered device based on these generators is needed. With the development of nanogeneratorbased circuits design and optimization, the building of new device simulator is necessary for the study and the synthesis of electromecanical parameters of this type of models. In the present article, both numerical modeling and optimization of piezoelectric nanogenerator based on zinc oxide have been carried out. They aim to improve the electromecanical performances, robustness, and synthesis process for nanogenerator. The proposed model has been developed for a systematic study of the nanowire morphology parameters in stretching mode. In addition, heuristic optimization technique, namely, particle swarm optimization has been implemented for an analytic modeling and an optimization of nanogeneratorbased process in stretching mode. Moreover, the obtained results have been tested and compared with conventional model where a good agreement has been obtained for excitation mode. The developed nanogenerator model can be generalized, extended and integrated into simulators devices to study nanogenerator-based circuits.

The major disadvantages of the conventional direct torque control (DTC) drive is the steady state ripples in torque and flux Using space vector control (SVM) method reduce the torque and stator flux ripples. In this paper, the use of SVM technique, a torque fuzzy controller is proposed to improve DTC performance and reduce significantly torque ripple. Simulation results will be presented and discussed to prove the effective new of the proposed