Publications
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Développement d’une nouvelle méthode numérique basée sur l’arithmétique des intervalles pour la reconstruction de matrice Origine/Destination
La matrice Origine/Destination (OD) revêt une importance capitale dans le dimensionnement et la planification d’un système de transport. L’estimation des matrices OD est principalement réalisée par les gestionnaires de réseau à partir de données issues d’enquêtes. Le déploiement massif d’outils numériques permet l’acquisition automatique de données en temps réel comme la billettique. Il génère une […]
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Resource-Constrained EXtended Reality Operated With Digital Twin in Industrial Internet of Things
EXtended Reality (XR) alongside the Digital Twin (DT) in Industrial Internet of Things (IIoT) emerges as a promising next-generation technology. Its diverse applications hod the potential to revolutionize multiple facets of Industry 4.0 and serve as a cornerstone for the rise of Industry 5.0. However, current systems are still not effective in providing a high-quality […]
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Hybrid Metaheuristics for Industry 5.0 Multi-Objective Manufacturing and Supply Chain Optimization
Industry 5.0 ushers in a new era of manufacturing, with the integration of sophisticated technology and human know-how, emphasising durable, customised and resilient industrial techniques. Multi-Objective Optimization (MOO) becomes a crucial instrument for tackling the complicated balance between efficiency, cost, quality, and sustainability. This article introduces a new method combining mathematics and swarm intelligence to […]
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Supply Chain 5.0: Vision, Challenges, and Perspectives
The recent technological advancements have transformed modern supply chains into complex networks. Consequently, today’s supply chain systems are facing several challenges, including limited visibility in both upstream and downstream supply chains, lack of trust among the different stakeholders, as well as transparency and traceability. The application of the Internet of Things can enable companies to […]
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Optimal placement and sizing of distributed generation for power factor improvement
This study employs the Forward-Backward Sweep (FBS) method in conjunction with the Sea Horse Optimization (SHO) algorithm to optimize the sizing and placement of Distributed Generators (DGs) in a distribution network for the intended case study. Through the integration of MATPOWER toolbox in MATLAB and Torrit software, the network is systematically evaluated under four scenarios […]
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Advancing Manufacturing Efficiency: Multi-Objective Optimization in the Industry 5.0 Era
This paper explores the transition to Industry 5.0, highlighting its focus on sustainable, human-centred and resilient industrial progress. In this new era, the integration of advanced technology with human expertise is crucial, emphasising the importance of balancing efficiency, cost, quality, and sustainability. At the heart of this research is Multi- Objective Optimisation (MOO), which is […]
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Classification of whispering gallery modes for cladded systems
A classification of whispering gallery modes has been proposed between three types : core modes, cladding modes and composed modes. While core modes or cladding modes are interesting to generate with a sensor purpose, composed modes propagate in both core and coating and therefore should be avoided. In this paper, a theoretical and numerical study […]
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Online human motion analysis in industrial context: A review
Human motion analysis plays a crucial role in industry 4.0 and, more recently, in industry 5.0 where humancentered applications are becoming increasingly important, demonstrating its potential for enhancing safety, ergonomics and productivity. Considering this opportunity, an increasing number of studies are proposing works on the analysis of human motion in an industrial context, taking advantage […]
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Determinant Factors of Teaching Performance in COVID-19 Context
COVID-19 pandemic still impact higher education system, stakeholders and environment all around the world. Students, teachers, academic institutions and education decision makers were shocked by an atypical new context they promptly put in face, asking drastic change in behavior and procedures at individual, familial and institutional levels. Full lockdown and closing campuses enforced students and […]
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Synthetic datasets for 6D Pose Estimation of Industrial Objects: Framework, Benchmark and Guidelines
This paper falls within the industry 4.0 and tackles the challenging issue of maintaining the Digital Twin of a manufacturing warehouse up-to-date by detecting industrial objects and estimating their pose in 3D, based on the perception capabilities of the robots moving all along the physical environment. Deep learning approaches are interesting alternatives and offer relevant […]
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Industrial Object Detection Leveraging Synthetic Data for Training Deep Learning Models
The increasing adoption of synthetic training data has emerged as a promising solution in various domains, owing to its ability to provide accurately labeled datasets at a lower cost compared to manually annotated real-world data. In this study, we explore the utilization of synthetic data for training deep learning models in the field of industrial […]
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Travail de garde et enjeux d’apprentissage chez les bergers et éleveurs pastoraux : une approche didactique professionnelle de l’expérience pastorale
Cet article s’intéresse aux savoirs issus de l’expérience des bergers qui ont la charge de garder les troupeaux en estive. Partant du constat d’un “malaise professionnel” principalement incarné dans la relation difficile aux éleveurs qui leur confient leurs bêtes et ancré dans le manque de structuration de la profession de berger, cette contribution s’appuie sur […]