The magnetohydrodynamics (MHD) is an important interdisciplinary field. It is the interaction between an electromagnetic field and an electrically conducting fluid. Electromagnetic pumps are widely used for the transportation of the fluids in a variety of technological processes. The advantage of these devices is that permits the pumping of liquids without moving parts. The design of the pump is considered as an optimization problem where the objective function is the minimum of the MHD pump mass with both geometrical and electromagnetic contraints type. The obtained optimization results using the finite volume method with Matlab software show the performances of the used stochastic simulated annealing method.

This paper presents the optimization, elaboration and characterization of a new TCO (Transparent Conductive Oxides) electrode based on ITO/Ag/ITO multilayer design that enables overcoming the trade-off between the electrical and optical properties. A new hybrid approach combining the investigated design and Particle Swarm Optimization (PSO) technique is conducted with the aim of maximizing the Haacke Figures of merit (FoM). It is found that the optimized ITO/Ag/ITO tri-layered design paves a new path toward achieving a high FoM of 125 × 10-3Ω-1. Such improvement is attributed to the improved light management achieved by the efficient modulation of the Ag sub-layer geometry. Subsequently, the optimized multilayer design is fabricated using RF magnetron sputtering technique. The structural, optical and electrical properties associated with the deposited ITO/Ag/ITO multilayer structure are also analyzed. It is found that the fabricated TCO-based electrode shows a high transmittance over than 94.1% and a low sheet resistance of 4.5Ω × sq-1, which is in good agreement with the theoretical predictions. Therefore, the proposed design methodology based on experiments assisted by PSO metaheuristic approach offers exciting opportunities for bridging the gap between transparency and conductivity characteristics. This makes the elaborated ITO/Ag/ITO multilayer design suitable for high-performance optoelectronic applications.

With the huge increase of large-scale multimedia over Internet, especially images, building Content-Based Image Retrieval (CBIR) systems for large-scale images has become a big challenge. One of the drawbacks associated with CBIR is the very long execution time. In this article, we propose a fast Content-Based Image Retrieval system using Spark (CBIR-S) targeting large-scale images. Our system is composed of two steps. (i) image indexation step, in which we use MapReduce distributed model on Spark in order to speed up the indexation process. We also use a memory-centric distributed storage system, called Tachyon, to enhance the write operation (ii) image retrieving step which we speed up by using a parallel k-Nearest Neighbors (k-NN) search method based on MapReduce model implemented under Apache Spark, in addition to exploiting the cache method of spark framework. We have showed, through a wide set of experiments, the effectiveness of our approach in terms of processing time.

Risk mapping is the foundation of the risk prevention strategy. It allows for the understanding of all factors that may affect the activities. It is a collective decision based on negotiation between the actors. Argument-based negotiation accelerates the negotiation process and converges it toward a final and common decision. It is in this context that this paper aims to illustrate the contribution of the improved PCA and AHP tools, considered as arguments, to the classification of major accident risks.

The aim of this work is the phytochemical study of the butanolic extract of the aerial parts of Veronica rosea. Four compounds 1–4 have been isolated using different chromatographic methods. The structures of these compounds were determined by NMR spectral analysis and mass spectroscopy. The adsorption and anticorrosion effects of this extract were investigated towards the corrosion of copper in 1 M HNO3 aqueous by the weight loss technique and potentiodynamic polarization. The results showed that the butanolic extract is a good inhibitor and the inhibition efficiency increases with increasing of concentration of the inhibitor. The adsorption of this extract on the copper specimen surface was spontaneous and obeyed the Langmuir’s adsorption isotherm. Large value of adsorption equilibrium Constant (K ads = 35 L g-1) was obtained. The polarization experiments confirmed the data obtained by gravimetric weight-loss. Tafel plot of polarization curves indicates that the extract acts as a mixed type inhibitor.

Purpose The purpose of this paper is to propose a new managerial method to integrate the environmental dimension in the domino effects (DEs) analysis. Design/methodology/approach The proposed method is a three-step approach: identification of primary hazards in the form of potential events causing the DE, a mixed quantification (deterministic and probabilistic) of the risk of the DEs with a view to its control and capitalizing the results from the BLEVESOFT software as well as those relating to the probability of occurrence of the DEs in the form of a prioritized action plan dedicated to surrounding environments (proximity territory). Findings The primary hazards are technologically manageable at the studied system but are unpredictable if triggered at the environmental subsystem because they are difficult to be managed and often cause panic, which is a form of a very catastrophic DE. Research limitations/implications The research could affect members of the engineering and construction industry, and can be applied in several domains since it studies the DE phenomenon. which is a common problem especially in industrials plants. Practical implications The proposal method is applied in an industrial terminal in Algeria. Originality/value This paper presents an exploratory study of using a new managerial method that aims to combine the potentialities of geomatic sciences that allow the spatial representation of nearby territories to assess the severity of DEs through a deterministic approach, and the modeling of DEs as well as their analysis by a probabilistic approach.

Using a risk matrix for Risk mapping constitutes the basis of risk management strategy. It aims to classify the identified risks with regards to their management and control. This risk classification, which is based on the frequency and the severity dimensions, is often carried out according to a procedure founded on experts’ judgments. In order to overcome the subjectivity bias of this classification, this paper presents the contribution of the Principal Components Analysis (PCA) method: an exploratory method for graphing risks based on factors that allow a better visualized classification of scenarios accidents. Still, the commonly encountered problem in the data classified by the PCA method resides in the main factors of classification; we judged useful to frame these letters by an algebraic formulation to make an improvement of this classification possible. The obtained results show that the suggested method is a promising alternative to solve the recurring problems of risk matrices, notably in accident scenarios’ classification.