This article aims to prepare Ni-Al2O3 composite coatings from a conventional electroplating process. The coatings development parameters taken into account for this study of the corrosion resistance of these coatings are: Al2O3 concentration, bath temperature and current. The experimental tests are carried out by two lost mass and polarization techniques. The objective of the work is to determine the influence of elaboration parameters on the corrosion resistance of NiAl2O3 composite coatings. The study carried out in this article has show

Group B Streptococcus (GBS) can cause severe pneumonia, sepsis and meningitis in neonates and represents one of the most prevalent causes of invasive neonatal infections. Prenatal screening and prenatal antibiotic prophylaxis can prevent maternal transmission of Streptococcus agalactiae during delivery. The objective of this study was to determine the maternal risk of maternal carriage of group B Streptococcus over time, to offer reliable epidemiological data to the health staff working at maternity Meriem Bouatoura, Batna (Northeast Algeria) or even all maternity hospitalsin Algeria. In this prospective study, vaginalspecimens(lower third) were collected from 150 pregnant women. The samples were cultured on 5% sheep blood and Chromagar Orientation. The method of confirming the identification of GBS was he agglutination test using the PASTOREX® Strep Kit. The antibiotic susceptibility testing was performed using the Kirby Bauer method. A total of 150 patients were evaluated, on average in the 34th week of pregnancy. Fifteen patients were GBS positive, a percentage rate of 10%. In conclusion, regular vaginal culture screening in the third trimester of pregnancy is warranted, as well as evaluation of risk factors and need for antibiotic administration to infants at risk.

Biomedical domains are characterized by the presence of large amounts of high dimensional data and a lack of general theories to understand structural and functional components. Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decisionmaking process, from classification to diagnostic procedures. In this work, we develop a method based on a hybrid ANN. This method uses three different feed forward type multilayer neural networks, with the ability to classify ECGs as normal or carrying atrioventricular block (AVB). A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.05 being the desired output for a normal ECG, a value between 0.05 and 1 would infer an occurrence of an AVB. The results show that, this hybrid network has a good performance to detect AVBs. They show a sensibility of 98% and a specificity of 92%.

This papers deal with a new Adaptive Direct Power Control for Doubly-Fed Induction Generator of 1.5 MW. The main feature of the proposed strategy is based on the replacement of the fixed switching table by an adaptive one. The online update of the adaptive switching table depends on the reactive power variation and past switching sequences. The proposed adaptive direct power control is compared with Vector Control and Classical Direct Power Control. The robustness of the proposed control scheme against parameter, load and wind speed variations have done with success. The main performance of the Adaptive Direct Power Control strategy is the reduction of powers ripples, thus reduce of torque ripple on the shaft of the turbine.

This paper presents the particle swarm optimization (PSO) algorithm in conjuction with the fuzzy logic method in order to achieve an optimized tuning of a proportional integral derivative controller (PID) in the DTC control loops of dual star induction motor (DSIM). The fuzzy controller is insensitive to parametric variations, however, with the PSO-based optimization approach we obtain a judicious choice of the gains to make the system more robust. According to Matlab simulation, the results demonstrate that the hybrid DTC of DSIM improves the speed loop response, ensures the system stability, reduces the steady state error and enhances the rising time. Moreover, with this controller, the disturbances do not affect the motor performances.

This paper proposes a new wavelet family based on fractional calculus. The Haar wavelet is extended to fractional order by a generalization of the associated conventional low-pass filter using the fractional delay operator Z^-D. The high-pass fractional filter is then designed by a simple modulation of the low-pass filter. In contrast, the scaling and wavelet functions are constructed using the cascade Daubechies algorithm. The regularity and orthogonality of the obtained wavelet basis are ensured by a good choice of the fractional filter coefficients. An application example is presented to illustrate the effectiveness of the proposed method. Thanks to the flexibility of the fractional filters, the proposed approach provides better performance in term of image denoising.

In this paper, we propose a large-update primal-dual interior point algorithm for linear optimization. The method is based on a new class of kernel functions which differs from the existing kernel functions in which it has a double barrier term. The investigation according to it yields the best known iteration bound O( √ n log(n) log( n ε )) for large-update algorithm with the special choice of its parameter m and thus improves the iteration bound obtained in Bai et al. [2] for large-update algorithm.

The present work aims to investigate the feasibility to use date palm waste as reinforcement to improve durability and performance of concrete. Four formulations (0 wt %, 5 wt %, 10 wt % and 15 wt %) were prepared according to the date palm fibers weight contents. The performance of all these formulations was studied in terms of swelling, drying shrinkage, weight change, compressive strength and volume change. The investigations were performed by exposing the samples to various environments: immersion in water, drying, salts exposure and cyclic wetting/drying. The results revealed that mortar reinforced with date palm fibers offers better shrinkage prevention, and thus allows decreasing the cracking effect. Moreover, the composites prepared with high content of natural fibers showed better resistance against sulphuric acid attack and therefore better resistance to deterioration. A significant enhancement in mechanical behavior following alkali treatment was recorded. Finally, date palm fibers can mainly contribute for minimizing the deterioration of cement mortar composites following cyclic wetting and drying

La présente étude a pour objet la modélisation de la profondeur d’affouillement autour des piles de pont circulaires en Algérie (Zones semi-arides) par Réseaux de Neurone Artificiels (neuro- émulation). A la phase de prétraitement, la réduction de la dimensionnalité des entrées au modèle neuronal est effectuée par la méthode classique linéaire : l’analyse en composantes principales (ACP). Les résultats obtenus pour ce type de données ont montré que l’ACP fourni des modèles très performants.