Publications
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Sim-optimization hybrid approach for scheduling randomly deteriorating treatment tasks in horticulture
In this paper, we study the problem of scheduling robotized tasks in the context of Agriculture 4.0. The objective is to optimize the treatment tasks of plants against an evolving disease (mildew) within a greenhouse. The treatment is performed using a type-C ultraviolet radiation (UV-C) by a UV-Robot. We propose a semi-dynamic simulation-optimization approach based […]
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Modeling and simulation of human behavior impact on production throughput
The development of new technologies generates intelligent, complex, and collaborative production systems. Several research works want to improve the production performances while improving the comfort of the human operator. However, it is not obvious to define optimal strategies of operations planning and control that consider the unexpected and variable character of human operators. It is […]
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Human-centred assembly and disassembly systems: a survey on technologies, ergonomic, productivity and optimisation
Despite the increasing use of automation in the current industry 4.0 context, manual assembly and disassembly tasks are still common and in some situations even unavoidable. The interaction between humans and other elements of the Assembly and Disassembly Systems (ADS) has been discussed in the scientific literature with the dual objective of optimising human well-being […]
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Simulation and Optimisation of a Failure-Prone Disassembly-Reconditioning-Assembly System
This paper deals with the simulation and optimisation of disassembly-reconditioningassembly system (DRAS) taken into account random machines failures and repairs. The proposed system is composed of one disassembly machine, two parallel structures, one assembly machine and stocks to store the used products, components and finished product. In this study a complete disassembly and assembly process […]
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Ikigai assessment in a western work context
The measurement of well-being is widely studied in the literature but may still benefit from a multicultural viewpoint. We present a new approach by measuring the ikigai of individuals. Ikigai is part of the Japanese philosophy of life purpose and well-being. Japanese research offers the Ikigai-9 scale (Imai, 2012) based on a three-dimensional model measuring: […]
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Deep transferable learning on heartbeat classification for imbalance dataset
Electrocardiogram (ECG) data recorded by medical devices are hard to analyze manually. Therefore, it is important to analyze and categorize each heartbeat using machine learning. Recently, advancements in machine learning have made classification of complex data easy and fast. However, these machine learning algorithms require sufficient amount of training data and have limited performance in […]
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Conception universelle, lead user et intelligence émotionnelle
L’objet de cette conférence était de présenter les résultats de notre étude portant sur l’identification des caractéristiques des lead users, à soir l’empathie et la compétence dans le domaine.
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Impliquer les managers dans le développement des compétences de leurs équipes avec l’intégration de dynamiques apprenantes: construire des environnements capacitants
Comprendre comment l’idée d’environnement capacitant revisite les modalités de management
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Buckling of Timoshenko beam under two-parameter elastic foundations
This paper exposes buckling solutions of a plane, quasi-static Timoshenko beam with small transformation subjected to a longitudinal force and surrounded by an elastic wall modeled by two-parameter elastic foundations. A non-dimensional analysis of associated Haringx and Engesser model is performed and buckling stress and shape are exposed analytically. Relations for rigidity of the wall […]
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Community-based method for extracting backbones
Networks are an adequate representation for modeling and analyzing a great variety of complex systems. However, understanding networks with millions of nodes and billions of connections can be pretty challenging due to memory and time constraints. Therefore, selecting the relevant nodes and edges of these large-scale networks while preserving their core information is a major […]
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Improved Hourly Prediction of BIPV Photovoltaic Power Building Using Artificial Learning Machine: A Case Study
In the energy transition, controlling energy consumption is a challenge for everyone, especially for BIPV (Building Integrated Photovoltaics) buildings. Artificial Intelligence is an efficient tool to analyze fine prediction with a better accuracy. Intelligent sensors are implemented on the different equipments of a BIPV building to collect information and to take decision about the energy […]
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