Characterization of boride coatings on a ductile cast iron

In this work, the EN-GJS-400-15 cast iron was pack-borided in a powder mixture composed of 5% B₄C, 5% NaBF₄ and 90% SiC at the three temperatures: 900, 950 and 1000°C for 2, 4 and 6 h, respectively. The pack-borided EN-GJS-400-15 cast iron was characterized by the following experimental techniques: optical microscopy, XRD analysis and Microhardness Vickers tester. The growth kinetics of boride layers was also investigated. As a consequence, the boron activation energy was found to be 212.28 kJ mol^–1 for the EN-GJS-400-15 cast iron. Based on a regression model, a useful equation was derived to estimate the boride layer thickness as a function of the boriding parameters (time and temperature). A good agreement was then obtained between the predicted values of boride layers thicknesses and those measured experimentally. In addition, an iso-thickness diagram was proposed to be used as a simple tool to select the boride layers thicknesses according to the potential applications of EN-GJS-400-15 cast iron in industry.     

Using Fuzzy Cost‐Based FMEA,GRA and Profitability Theory for Minimizing Failures at a Healthcare Diagnosis Service

This paper proposes an integrated approach to identify, evaluate and improve the potential failures in a service setting. This integrated approach combines Fuzzy cost‐based service‐specific FMEA (FCS‐FMEA), Grey Relational Analysis (GRA) and profitability theory for better prioritization of the service failures by considering cost as an important issue and using the profitability theory in a way that the corrective actions costs are taken into account. Considering profitability with FCS‐FMEA and GRA reduces the losses caused by failure occurrence. Besides, a maximization linear mathematical problem is used to select the best mix of failures to be repaired. We apply our approach to an academic example concerning the potential failures diagnosis of the Internal Medicine service of a hospital located in Seoul, Korea. We applied our approach and solved the associated maximization problem by a commercial solver, producing an optimal solution which indicates the most convenient mix of failures to be repaired by considering available budget. Copyright © 2013 John Wiley & Sons, Ltd.     

Phenotypic Characterization and Genotypic Subtyping of Salmonella enterica Serovars Enteritidis and Gallinarum Isolated from Human and Poultry-Related Samples

This study aimed to assess the serotypes, antibiotic susceptibility, and molecular subtyping of Salmonella enterica isolated from food products and human patients with gastroenteritis. A total of 59 isolates were investigated, and the results revealed a predominance of S. Enteritidis with 57.63% (34/59) S. Gallinarum held second with 15.62% (5/32) of total food borne. While, isolates from humans showed 18.51% (5/27) of S. Typhimurium. High level of resistance to nalidixic acid was noted among food strains and 35.29% of human isolates were found to be multidrug resistant. Eight representative isolates were subtyping using three molecular approaches, ribotyping, Multilocus sequence typing (MLST) and Multiple-locus variable number tandem repeat analysis (MLVA). MLST showed three sequence types corresponding to two clonal complexes, (ST-78, CC-4) for S. Gallinarum, (ST-11, CC-4) for S. Enteritidis and (S-367, CC-37) for S. Cerro. While, MLVA generated six different profiles targeting nine loci for S. Enteritidis and S. Gallinarum.     

Thermo-mechanical characteristics of thermally aged polyethylene/polypropylene blends

Polyethylene (PE), polypropylene (PP) and their blends have attracted a lot of attention due to their potential industrial applications. Therefore, the current work has been carried out with the main objective of investigating the impact of the thermal aging/treatment and blend ratio (composition range) on the mechanical (tensile and hardness) and thermal characteristics (using thermogravimetric analysis in a dynamic air atmosphere) of PE, PP and PE/PP binary blends. Samples of PE/PP blends containing 100/00, 75/25, 50/50, 25/75 and 0/100 wt.% were prepared via injection moulding technique and thermally treated/aged at 100 °C for 0, 2, 4, 7, 14 days. The tensile measurements indicated that the yield strength and the modulus decrease with increasing PE content. It was also observed that PE, PP and their blends deform in ductile modes. They undergo a uniform yielding over a wide range of deformation, which is followed by strain hardening and then failure. The strain to break for pure PE is found to be much higher than that for pure PP and for their blends, intermediate values have been observed. The hardness measurements have also revealed that increasing PE content in PE/PP blends reduced the hardness value of PP, however, thermal aging at 100 °C has not affected the polymers hardness which holds also true for the tensile properties, showing a good correlation between tested mechanical properties. The thermogravimetric analysis (TGA) in a dynamic air atmosphere and derivative thermogravimetric analysis (DTA) were conducted to study the thermal degradation and stability of thermally unaged and aged PE, PP and PE/PP blends in terms of the initial (T_d and T_d(1%)) and final (T_d(99%)) decomposition temperatures and maximum decomposition rate temperature (T_max). All polymers start to decompose at no less than 365 °C. As for mechanical properties, the blend ratio has affected the thermal properties however, aging time has not.     

Electric load forecasting by using dynamic neural network

Electrical energy is fundamental for the wellbeing and for the economic development of any country. However, all countries must ensure access to essential resources and ensure the continuity of its supply. Due to the non-storable nature of electrical energy, the amount of consumed active power should always be equal the produced active power just to avoid power system frequency deviation problem. In order to keep the relationship production–consumption relation in compliance with different standards and to secure profitable operations of power system, electric load consumption must be predicted and controlled instantaneously. Several statistical and classical techniques are proposed in the literature but unfortunately all these methods are not accurate in a satisfactory manner. In this paper, a dynamic neural network is used for the prediction of daily power consumption. The suitability and the performance of the proposed approach is illustrated and verified with simulations on load data collected from French Transmission System Operator (RTE) website. The obtained results show that the accuracy and the efficiency are improved comparatively to conventional methods widely used in this field of research.     

Wavelet network for recognition system of Arabic word

Focusing on the development of new technologies of information, research in the speech communication field is an activity in full expansion. Several disciplines and skills interact in order to improve performance of Human Machine Communication Systems (HMC). In order to increase the performance of these systems, various techniques, including Hidden Markov Models (HMM) and Neural Network (NN), are implemented.     

Effect of seed coat fragments on cotton yarn structure: impact of fragment size,attached fibres and position within yarn core

Seed coat fragments are a major source of cotton yarn imperfections. This article discusses the factors influencing the disruption caused by seed coat fragments in ring-spun yarn structure with a focus on three characteristics: the fragment's size, the amount of fibres attached to it and its position relative to the yarn core. The three characteristics were investigated through two experiments involving various types of yarn defects and a range of ring-spun yarn counts. Results presented in this article indicate that the three factors considered have a significant influence on the intensity of the disruption the seed coat fragment causes in the yarn structure, and are determinant of the type of defect that this disruption engenders (short/long defect).     

Doubly-striped disk mirroring: Reliable storage for video servers

Disk striping is essential in Video-On-Demand servers to allow concurrent access for a large number of users to the same copy of a video object. On the other hand, disk striping makes the system more vulnerable to component failures. We propose a replication scheme for video content and an associated I/O scheduling algorithm that enables the system to tolerate a component failure. The scheme, called doubly-striped mirrors, compares favorably to other approaches for implementing redundancy such as RAID in terms of cost, bandwidth efficiency, buffer usage and system availability.     

Unsupervised Bayesian image segmentation using orthogonal series

This paper deals with the problem of unsupervised image segmentation which consists in first mixture identification phase and second a Bayesian decision phase. During the mixture identification phase, the conditional probability density function (pdf) and the a priori class probabilities must be estimated. The most difficult part is the estimation of the number of pixel classes or in other words the estimation of the number of density mixture components. To resolve this problem, we propose here a Stochastic and Nonparametric Expectation-Maximization (SNEM) algorithm. The algorithm finds the most likely number of classes, their associated model parameters and generates a segmentation of the image by classifying the pixels into these classes. The non-parametric aspect comes from the use of the orthogonal series estimator. Experimental results are promising, we have obtained accurate results on a variety of real images.     

Synergistic verification and validation of systems and software engineering models

In this paper, we present a unified approach for the verification and validation of software and systems engineering design models expressed in UML 2.0 and SysML 1.0. The approach is based on three well-established techniques, namely formal analysis, programme analysis and software engineering (SwE) techniques. More precisely, our contribution consists of the synergistic combination of model checking, static analysis and SwE metrics that enables the automatic and efficient assessment of design models from static and dynamic perspectives. Additionally, we present the design and implementation of an automated computer-aided assessing framework integrating the proposed approach. Moreover, we discuss the related technical details and the underlying synergism. Finally, we illustrate the proposed approach by assessing a design case study that is composed of state machine and sequence diagrams.