This work presents the prediction of the rate of progression in oil drilling based on random forest algorithm, which is part of the family of ensemble machine learning. The ROP parameter plays a very important role in oil drilling, which has a great impact on drilling costs, and its prediction allows drilling engineers to choose the best combination of input parameters for better progress in drilling operations. To resolve this problem, several works have been realized with the different modeling techniques as machine learning: RNAs, Bayesian networks, SVM etc. The random forest algorithm chosen for our model is better than the other MLS techniques. in speed or precision, following what we found in the literature and tests done with the open source machine learning tool on historical oil drilling logs from fields of Hassi Terfa located in southern Algeria.

In this work a new data-driven approach for Remaining Useful Life estimation of aircraft engines is developed. The proposed approach is a regularized Single Hidden Layer Feedforward Neural network (SLFN) with incremental constructive enhancements. The training rules of this algorithm are inspired form different Extreme Learning Machine (ELM) variants. Particle Swarm Optimization (PSO) algorithm is integrated to enhance tracking ability of the best regularization parameter to reduce the norm of the tuned weights. The proposed approach is evaluated using C-MAPSS (Commercial Modular Aero-Propulsion System Simulation) dataset and compared to its other derivatives and proved its accuracy. C-MAPSS software has revisions in military and civil applications. In this paper, the military version of its application is the used one.

In this work a new data-driven approach for Remaining Useful Life estimation of aircraft engines is developed. The proposed approach is a regularized Single Hidden Layer Feedforward Neural network (SLFN) with incremental constructive enhancements. The training rules of this algorithm are inspired form different Extreme Learning Machine (ELM) variants. Particle Swarm Optimization (PSO) algorithm is integrated to enhance tracking ability of the best regularization parameter to reduce the norm of the tuned weights. The proposed approach is evaluated using C-MAPSS (Commercial Modular Aero-Propulsion System Simulation) dataset and compared to its other derivatives and proved its accuracy. C-MAPSS software has revisions in military and civil applications. In this paper, the military version of its application is the used one.

In this work a new data-driven approach for Remaining Useful Life estimation of aircraft engines is developed. The proposed approach is a regularized Single Hidden Layer Feedforward Neural network (SLFN) with incremental constructive enhancements. The training rules of this algorithm are inspired form different Extreme Learning Machine (ELM) variants. Particle Swarm Optimization (PSO) algorithm is integrated to enhance tracking ability of the best regularization parameter to reduce the norm of the tuned weights. The proposed approach is evaluated using C-MAPSS (Commercial Modular Aero-Propulsion System Simulation) dataset and compared to its other derivatives and proved its accuracy. C-MAPSS software has revisions in military and civil applications. In this paper, the military version of its application is the used one.

The main objective of this works is to study and improve the performances of the Single hidden Layer Feedforward Neural network (SLFN) for the application of Remaining Useful Life (RUL) prediction of aircraft engines. The most common problems in SLFNs based old training algorithms such as backpropagation are time consuming, over-fitting and the appropriate network architecture identification. In this paper a new incremental constructive learning algorithm based on Extreme Learning Machine algorithm is proposed for founding the appropriate architecture of a neural network under less computational costs. The aim of the proposed training approach is to study its maximum capabilities during RUL prediction by reducing over-fitting and human intervention. The performances of the proposed approach which are evaluated on C-MAPPS dataset and compared with its original variant from the literature. Experimental results proved that the new algorithm outperforms the old one in many metrics evaluations.

The main objective of this works is to study and improve the performances of the Single hidden Layer Feedforward Neural network (SLFN) for the application of Remaining Useful Life (RUL) prediction of aircraft engines. The most common problems in SLFNs based old training algorithms such as backpropagation are time consuming, over-fitting and the appropriate network architecture identification. In this paper a new incremental constructive learning algorithm based on Extreme Learning Machine algorithm is proposed for founding the appropriate architecture of a neural network under less computational costs. The aim of the proposed training approach is to study its maximum capabilities during RUL prediction by reducing over-fitting and human intervention. The performances of the proposed approach which are evaluated on C-MAPPS dataset and compared with its original variant from the literature. Experimental results proved that the new algorithm outperforms the old one in many metrics evaluations.

A reverse logistics planning problem is modeled and analyzed. The model considers returns of a particular electronic device from customers. Some of the collected products are remanufactured or refurbished. Others are disassembled for their key parts which can be considered as good as new. New products are assembled either using new parts or extracted ones. There are two types dynamic demands: demands for remanufactured/refurbished products and demands for new products. Demand of remanufactured/refurbished products can be satisfied using new products in case of shortage. This is a one way downward substitution. The objective is to minimize total costs while satisfying all demands. This problem is formulated as a MILP. The numerical results show that: i) it is hard for a solver to find optimal solutions for the problem in reasonable computational times for several instances with relatively small time horizons and ii) substitution is justified for a certain range of cost and demand parameters.

A reverse logistics planning problem is modeled and analyzed. The model considers returns of a particular electronic device from customers. Some of the collected products are remanufactured or refurbished. Others are disassembled for their key parts which can be considered as good as new. New products are assembled either using new parts or extracted ones. There are two types dynamic demands: demands for remanufactured/refurbished products and demands for new products. Demand of remanufactured/refurbished products can be satisfied using new products in case of shortage. This is a one way downward substitution. The objective is to minimize total costs while satisfying all demands. This problem is formulated as a MILP. The numerical results show that: i) it is hard for a solver to find optimal solutions for the problem in reasonable computational times for several instances with relatively small time horizons and ii) substitution is justified for a certain range of cost and demand parameters.

A reverse logistics planning problem is modeled and analyzed. The model considers returns of a particular electronic device from customers. Some of the collected products are remanufactured or refurbished. Others are disassembled for their key parts which can be considered as good as new. New products are assembled either using new parts or extracted ones. There are two types dynamic demands: demands for remanufactured/refurbished products and demands for new products. Demand of remanufactured/refurbished products can be satisfied using new products in case of shortage. This is a one way downward substitution. The objective is to minimize total costs while satisfying all demands. This problem is formulated as a MILP. The numerical results show that: i) it is hard for a solver to find optimal solutions for the problem in reasonable computational times for several instances with relatively small time horizons and ii) substitution is justified for a certain range of cost and demand parameters.

Ce livre présente un système de coordonnées virtuelles appelé VCSCClockwise. Ce dernier est libre-GPS et sans points de référence aidant à créer les coordonnées virtuelles. En se basant sur la notion de cluster, ce système fonctionne parfaitement dans un réseau homogène avec une forte connectivité en produisant trois coordonnées virtuelles uniques associées à chaque nøe}ud-capteur dans le réseau. Declivity est un protocole de routage géographique utilisé pour tester et évaluer ce système de coordonnées virtuelles. Ce protocole peut choisir le chemin le plus court avec le minimum de dissipation de l’énergie. En plus, la livraison est toujours garantie que se soit dans un réseau homogène avec une forte densité ou non.

It is always difficult to identify the most recent works that have been published, especially those published in recent years, due to delays in putting publications online, citations indexe, etc. Scientometry offers to researchers various concepts, models and techniques that can be applied to knowledge management (KM) in order to explore its foundations, its state, its intellectual core, and its potential future development. To this end, we have developed a scientometric KM framework to calculate the scientometric indexes related to a query introduced in the Scopus database, to facilitate research and monitoring of productivity and collaboration between the authors of KM in particular and also the dissemination of knowledge. The works between 2014 and 2019 are taken, the industry of services was omitted. It might help the decision makers and researchers to optimize their time and efforts. We used Unified Modeling Language (UML) to translate the development ideas of the scientometric framework structure into diagrams, and Delphi 7 to calculate the indexes and ensure other operations of research (about: articles, their authors, conferences, etc). This framework is only valid for Excel files extracted from Scopus or similar format. Finally, the relation between KM and industry 4.0 was established on found articles in Scopus.

It is always difficult to identify the most recent works that have been published, especially those published in recent years, due to delays in putting publications online, citations indexe, etc. Scientometry offers to researchers various concepts, models and techniques that can be applied to knowledge management (KM) in order to explore its foundations, its state, its intellectual core, and its potential future development. To this end, we have developed a scientometric KM framework to calculate the scientometric indexes related to a query introduced in the Scopus database, to facilitate research and monitoring of productivity and collaboration between the authors of KM in particular and also the dissemination of knowledge. The works between 2014 and 2019 are taken, the industry of services was omitted. It might help the decision makers and researchers to optimize their time and efforts. We used Unified Modeling Language (UML) to translate the development ideas of the scientometric framework structure into diagrams, and Delphi 7 to calculate the indexes and ensure other operations of research (about: articles, their authors, conferences, etc). This framework is only valid for Excel files extracted from Scopus or similar format. Finally, the relation between KM and industry 4.0 was established on found articles in Scopus.

It is always difficult to identify the most recent works that have been published, especially those published in recent years, due to delays in putting publications online, citations indexe, etc. Scientometry offers to researchers various concepts, models and techniques that can be applied to knowledge management (KM) in order to explore its foundations, its state, its intellectual core, and its potential future development. To this end, we have developed a scientometric KM framework to calculate the scientometric indexes related to a query introduced in the Scopus database, to facilitate research and monitoring of productivity and collaboration between the authors of KM in particular and also the dissemination of knowledge. The works between 2014 and 2019 are taken, the industry of services was omitted. It might help the decision makers and researchers to optimize their time and efforts. We used Unified Modeling Language (UML) to translate the development ideas of the scientometric framework structure into diagrams, and Delphi 7 to calculate the indexes and ensure other operations of research (about: articles, their authors, conferences, etc). This framework is only valid for Excel files extracted from Scopus or similar format. Finally, the relation between KM and industry 4.0 was established on found articles in Scopus.

It is always difficult to identify the most recent works that have been published, especially those published in recent years, due to delays in putting publications online, citations indexe, etc. Scientometry offers to researchers various concepts, models and techniques that can be applied to knowledge management (KM) in order to explore its foundations, its state, its intellectual core, and its potential future development. To this end, we have developed a scientometric KM framework to calculate the scientometric indexes related to a query introduced in the Scopus database, to facilitate research and monitoring of productivity and collaboration between the authors of KM in particular and also the dissemination of knowledge. The works between 2014 and 2019 are taken, the industry of services was omitted. It might help the decision makers and researchers to optimize their time and efforts. We used Unified Modeling Language (UML) to translate the development ideas of the scientometric framework structure into diagrams, and Delphi 7 to calculate the indexes and ensure other operations of research (about: articles, their authors, conferences, etc). This framework is only valid for Excel files extracted from Scopus or similar format. Finally, the relation between KM and industry 4.0 was established on found articles in Scopus.

It is always difficult to identify the most recent works that have been published, especially those published in recent years, due to delays in putting publications online, citations indexe, etc. Scientometry offers to researchers various concepts, models and techniques that can be applied to knowledge management (KM) in order to explore its foundations, its state, its intellectual core, and its potential future development. To this end, we have developed a scientometric KM framework to calculate the scientometric indexes related to a query introduced in the Scopus database, to facilitate research and monitoring of productivity and collaboration between the authors of KM in particular and also the dissemination of knowledge. The works between 2014 and 2019 are taken, the industry of services was omitted. It might help the decision makers and researchers to optimize their time and efforts. We used Unified Modeling Language (UML) to translate the development ideas of the scientometric framework structure into diagrams, and Delphi 7 to calculate the indexes and ensure other operations of research (about: articles, their authors, conferences, etc). This framework is only valid for Excel files extracted from Scopus or similar format. Finally, the relation between KM and industry 4.0 was established on found articles in Scopus.

It is always difficult to identify the most recent works that have been published, especially those published in recent years, due to delays in putting publications online, citations indexe, etc. Scientometry offers to researchers various concepts, models and techniques that can be applied to knowledge management (KM) in order to explore its foundations, its state, its intellectual core, and its potential future development. To this end, we have developed a scientometric KM framework to calculate the scientometric indexes related to a query introduced in the Scopus database, to facilitate research and monitoring of productivity and collaboration between the authors of KM in particular and also the dissemination of knowledge. The works between 2014 and 2019 are taken, the industry of services was omitted. It might help the decision makers and researchers to optimize their time and efforts. We used Unified Modeling Language (UML) to translate the development ideas of the scientometric framework structure into diagrams, and Delphi 7 to calculate the indexes and ensure other operations of research (about: articles, their authors, conferences, etc). This framework is only valid for Excel files extracted from Scopus or similar format. Finally, the relation between KM and industry 4.0 was established on found articles in Scopus.

This article showcases the adaptability of existing mobility devices for the Algerian disabled population. It aims to develop a behavior model of disabled Algerian persons through (1) development of a theoretical model based on literature review and (2) improvement of this model by using local collected data from our developed questionnaire.