Dans cet article, l’objectif est de fournir aux chercheurs intéressés par la compétence interculturelle des pistes de réflexion sur son évaluation. Il s’agit de porter un regard analytique sur ce construit multidimensionnel tel qu’il est approché dans les différentes recherches. La clarification du concept nous permettra de dresser les modalités de son évaluation, leurs avantages ainsi que leurs limites tout en tenant compte des considérations méthodologiques garantissant leur validité et fiabilité selon le contexte de la recherche. Notre but est de dépasser une vision réductrice du concept altérant son opérationnalisation et de proposer des alternatives que le chercheur pourrait adopter.

La présente contribution a pour objectif de déterminer la place de l’écrit par rapport à l’oral dans le système éducatif algérien ainsi que de rendre compte de la manière dont la pédagogie du projet permet le développement des compétences de compréhension et de production de l’écrit. Pour ce faire, nous avons pris les programmes du cycle moyen du système éducatif algérien comme objet d’étude. Dans un premier temps, nous avons analysé les programmes, manuels scolaires, et guides des professeurs, dans le but de déterminer l’importance accordée par les instances éducatives aux deux compétences (écrit, oral). Nous avons expliqué, dans un second temps, à travers la présentation d’un exemple de projet comment la pédagogie du projet permet-elle un meilleur développement de la compétence de l’écrit.

Le présent article tend à spéculer sur l’importance des instances narratives scellant le discours littéraire dans l’entreprise traductionnelle. Sa nécessité tient dans la considération que les traducteurs sont invités à cerner l’exhaustivité et la profondeur du travail littéraire pour une appréhension optimale de leur exercice. Pour ce faire, nous proposons de mettre en exergue la triade narratologique faisant office de soubassement théorique (modes/perspectives/niveaux) en la mettant en corrélation avec l’øe}uvre qui nous servira de corpus à savoir « les ailes brisées » de Gibran Khalil Gibran traduite de l’arabe par Thierry Gillyboeuf afin de rendre compte de la matérialisation et la conformité de ces mêmes instances dans le texte cible.

This article is a reflection on the interculturality/contextualization duo in the relationship between the Algerian education system with the French language. The first step is to study the degree of conformity between the intercultural/contextual aims presented in official discourses and texts, and their transposition into French textbooks. Secondly, we will identify suggestions likely to enhance contextualization and interculturality through the texts and comprehension activities presented in the textbooks. Our aim is to provide the teachers with suggestions/tools to raise their learners’ intercultural awareness and enable them to be intercultural mediators.

Dans cette thèse, nous nous sommes intéressés à un modèle de gestion des connaissances des entreprises industrielles. Certaines tâches manufacturières impliquent un niveau élevé de connaissance tacite des opérateurs qualifiés. L’industrie a besoin des méthodes fiables pour la capture et l’analyse de ces connaissances tacites afin qu’elles puissent être partagées et sans aucune perte. Nous proposons, un modèle de gestion contenant deux processus de gestion, le premier processus est la capitalisation des connaissances basée sur une tâche industrielle. Nous avons utilisé une combinaison de deux méthodologies : une méthodologie d’ingénierie de connaissances CommonKADS et une méthodologie d’élicitation des connaissances MACTAK. Dans la phase de modélisation, nous avons utilisé deux différentes techniques de modélisation, une modélisation basée sur les connaissances d’expert et la deuxième une représentation ontologique. Ce modèle facilite la capture des connaissances d’experts et transforme les connaissances tacites en explicites avec une maximisation des règles de production. Le deuxième processus concerne le partage des connaissances à base d’une ontologie des Tâches Manufacturières MATO en identifiant un ensemble des concepts de fabrication et leurs relations, cette ontologie proposée facilite le partage des connaissances entre les tâches de fabrication et aide à partager et à réutiliser les connaissances durant l’exécution des tâches. Ensuite, une application proposée pour le diagnostic de système d’alarme dans une centrale thermique a été présentée pour démontrer l’importance et l’apport de l’ontologie.

This study discusses the design of the Maximum Power Point Tracking (MPPT) technique for photovoltaic (PV) systems employing a modified incremental conductance (IncCond) algorithm to extract maximum power from a PV module. A PV module, a DC-DC converter, and a resistive load constitute the PV system. In the scientific literature, it is well-documented that typical MPPT algorithms have significant drawbacks, such as fluctuations around the MPP and poor tracking during a sudden change in atmospheric conditions. To solve the deficiencies of conventional methodology, a novel modified IncCond method is proposed in this study. The simulation results demonstrate that the updated IncCond algorithm presented allows for less oscillation around the maximum power point (MPP), a rapid dynamic response, and superior performance.

Nowadays, solar energy, which is the direct conversion of light into electricity, occupies a very important place among renewable energy resources due to its daily availability in most regions of the globe. Therefore, the wise exploitation of this clean energy will ultimately drive to cover all needed demands [1, 2]. This paper deals with the design of Maximum Power Point Tracking (MPPT) technique for photovoltaic (PV) system using a modified incremental conductance (IncCond) algorithm to extract maximum power from PV module. The considered PV system consists of a PV module, a DC-DC converter and a resistive load. In the literature, it is known that the conventional MPPT algorithms suffer from serious disadvantages such as fluctuations around the MPP and slow tracking during a rapid change in atmospheric conditions. Therefore, in this paper, and attempting to overcome the shortcomings of conventional approach. In this work, a new modified incremental conductance algorithm is proposed to find the Maximum Power Point Tracking (MPPT) of the Photovoltaic System. Simulation tests with different atmospheric conditions are provided to demonstrate the validity and the effectiveness of the proposed algorithm.

The automation of manufacturing systems is a major obligation to the developments because of exponential industrial equipment, and programming tools, so that growth needs and customer requirements. This automation is achieved in our work through the application programming tools from Siemens, which are PCS 7 (Process Control System) for industrial process control and FuzzyControl++ for fuzzy control. An industrial application is designed, developed and implemented in the cement factory in Ain-Touta (S.CIM.AT) located in the province of Batna, East of Algeria. Especially in the cement mill which gives the final product that is the cement.

Nowadays, machine learning has emerged as a promising alternative for condition monitoring of industrial processes, making it indispensable for maintenance planning. Such a learning model is able to assess health states in real time provided that both training and testing samples are complete and have the same probability distribution. However, it is rare and difficult in practical applications to meet these requirements due to the continuous change in working conditions. Besides, conventional hyperparameters tuning via grid search or manual tuning requires a lot of human intervention and becomes inflexible for users. Two objectives are targeted in this work. In an attempt to remedy the data distribution mismatch issue, we firstly introduce a feature extraction and selection approach built upon correlation analysis and dimensionality reduction. Secondly, to diminish human intervention burdens, we propose an Automatic artificial Neural network with an Augmented Hidden Layer (Auto-NAHL) for the classification of health states. Within the designed network, it is worthy to mention that the novelty of the implemented neural architecture is attributed to the new multiple feature mappings of the inputs, where such configuration allows the hidden layer to learn multiple representations from several random linear mappings and produce a single final efficient representation. Hyperparameters tuning including the network architecture, is fully automated by incorporating Particle Swarm Optimization (PSO) technique. The designed learning process is evaluated on a complex industrial plant as well as various classification problems. Based on the obtained results, it can be claimed that our proposal yields better response to new hidden representations by obtaining a higher approximation compared to some previous works.

This paper investigates capacity planning with outsourcing under reliability-maintenance constraints. The considered supply-chain consists of a single-manufacturer and multiple-subcontractors. The manufacturer’s company is composed of a single unit subject to random failures. Corrective maintenance is endorsed when failures occur, and preventive maintenance can be carried out to reduce the degradation. The high in-house costs and the incapacity motivate the manufacturer outsourcing to independent subcontractors. In addition, based on the principle of comparative advantage, the manufacturer balances between in-house capacities and outsourcing services, which minimises the total cost. The aim is to propose a new policy based on the combination between integrated-maintenance and outsourcing policies. A mathematical model and an optimisation procedure have been developed in order to determine the best in-house production-maintenance and outsourcing plans for the manufacturer while minimising the total cost. In order to show the applicability of our approach, we conduct experimentations to study the management insights.

L’évolution récente des moyens de la communication sans fil a permet la manipulation de l’information à travers des unités de calculs portables, appelés capteurs. Ces derniers, qui ont des caractéristiques particulières, sont capables de récolter, de traiter et de transmettre des données environnementales d’une manière autonome.Dans ce livre sont introduites les connaissances de base nécessaires à la bonne compréhension des capteurs intelligents, des réseaux de capteurs et les différents types protocoles de routage spécifiques aux réseaux de capteurs. Nous fournirons ainsi les définitions généralement acceptées par ce type de réseau. Nous aborderons également par une description succincte les principales caractéristiques, contraintes et facteurs conceptuels qui surviennent dans ces réseaux. Nous présenterons ensuite les différentes orientations prises aux applications des réseaux de capteurs.

A recent study from GLOBOCAN disclosed that during 2018 two million women worldwide had been diagnosed with breast cancer. Currently, mammography, magnetic resonance imaging, ultrasound, and biopsies are the main screening techniques, which require either, expensive devices or personal qualified; but some countries still lack access due to economic, social, or cultural issues. As an alternative diagnosis methodology for breast cancer, this study presents a computer-aided diagnosis system based on convolutional neural networks (CNN) using thermal images. We demonstrate that CNNs are faster, reliable and robust when compared with different techniques. We study the influence of data pre-processing, data augmentation and database size on several CAD models. Among the 57 patients database, our CNN models obtained a higher accuracy (92%) and F1-score (92%) that outperforms several state-of-the-art architectures such as ResNet50, SeResNet50, and Inception. This study exhibits that a CAD system that implements data-augmentation techniques reach identical performance metrics in comparison with a system that uses a bigger database (up to 33%) but without data-augmentation. Finally, this study proposes a computer-aided system for breast cancer diagnosis but also, it stands as baseline research on the influence of data-augmentation and database size for breast cancer diagnosis from thermal images with CNNs

A comparative study between a set of chosen machine learning tools for direct remaining useful life prediction is presented in this work. The main objective of this study is to select the appropriate prediction tool for health estimation of aircraft engines for future uses. The training algorithms are evaluated using “time-varying” data retrieved from Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) developed by NASA. The training and testing processes of each algorithm are carried out under the same circumstances using the similar initial condition and evaluation sets. The results prove that among the studied training tools, Support vector machine (SVM) achieved the best results.

Requirements of users in developing countries differ from those of developed countries. This difference can be seen through wheelchair displacement in infrastructures that don’t meet international standards. However, developing countries are obliged to purchase products from developed countries that don’t necessarily meet all user’s requirements. The modification of these requirements will generate disruption on all the supply chain. This paper proposes a model for optimising the cost of requirement modification on the supply chain and seeks to evaluate the introduction of a new requirement on an existing product/process. This model is adapted to the redesign and development of products, such as wheelchairs, satisfying specific Algerian end-user requirements.