Publications
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Trustworty Smart CPS
Application on Autonomous Decisions Using Formal Methods
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Characterizing the Culture of Teal Organizations
Teal organizations arose around the world in the last decades and were recently described as potentially announcing a new stage of evolution for human organizations. They are characterized by three defining features: Self-management, Wholeness, and Evolutionary purpose. As the emergence of such organizations echoes other signs of change in the workplace and in society, we […]
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Optimizing Comfort and Energy Efficiency: The Impact of Model Accuracy on Mutli-Objective MPC
Buildings are responsible for ∼30% of primary energy consumption, mainly because of Heating, Ventilation, and Air Conditioning (HVAC) systems. The usual ON/OFF controller tends to react to occupancy presence, causing discomfort and energy waste. Furthermore, these controllers usually focus on thermal comfort and disregard other comforts, such as air quality, visual, etc. due to their […]
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Vers l’amélioration de l’intelligence collective dans un environnement virtuel
L’intelligence collective est une mesure prédictive de la capacité d’un groupe à accomplir une grande variété de tâches. C’est un indicateur important à prendre en compte pour le fonctionnement efficace d’un groupe. Plusieurs études ont examiné la fiabilité de cet indicateur dans divers environnements, notamment en condition de face-à-face, à travers une communication à distance, […]
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Metaheuristics and Machine Learning Convergence: A Comprehensive Survey and Future Prospects
The integration of machine learning techniques with optimization algorithms has garnered increasing interest in recent years. Two primary purposes emerge from the literature: leveraging metaheuristics in machine learning applications such as regression, classification, and clustering, and enhancing metaheuristics using machine learning to improve convergence time, solution quality, and flexibility. Machine learning techniques offer real-time decision-making […]
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Ordonnancement d’atelier de production flexible sous incertitude du comportement humain
Ce travail traite de l’ordonnancement d’atelier de production flexible sous incertitude du comportement humain. Il met en avant l’importance de prendre en compte le comportement humain dans les systèmes de production modernes, notamment dans le cadre de l’Industrie 5.0. L’étude propose une modélisation du comportement humain via un processus de Markov, distinguant les états productifs […]
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Ordonnancement résilient d’un atelier de type job shop flexible
Ce travail traite de l’optimisation de l’ordonnancement en milieu industriel en intégrant des aspects humains et environnementaux. Le premier document explore l’impact du comportement humain imprévisible sur la productivité d’un atelier flexible, en modélisant les travailleurs avec un processus de Markov et en optimisant leur affectation via un modèle mathématique non linéaire. Le second document […]
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Supply Chain Optimization with the Digital Twin: Case study of a warehouse
In a complex logistics landscape, the need for efficient and optimized Supply Chain’s (SC’s) is becoming increasingly important. This is crucial to creating an efficient SC and ensuring consistent, optimized use of resources. Efficient logistics management is essential if companies are to maintain their competitiveness in the marketplace. Digital technologies, such as digital warehouses, are […]
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Industrial Process Optimization with Digital Twin Solutions: Modeling, Monitoring and Decision-Making. Application to a water filtration unit.
The digital transformation of industry is an essential pillar of the global economy, aimed at improving productivity, promoting sustainable development and optimizing industrial performance. It relies on the use of advanced technologies such as cyber-physical systems, artificial intelligence and the Internet of Things, which make industrial systems not only more complex, but also more communicative, […]
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Medical Compression Prototype in a Wireless Sensor network
Medical Compression Prototype in a Wireless Sensor network (Submitted).
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Effet de la complexité du réseau LSTM sur l’explicabilité en Maintenance Prédictive
La nature complexe des données en maintenance prédictive impose souvent l’utilisation de modèles d’apprentissage profonds. Malgré leur efficacité dans la prédiction du RUL (durée de vie résiduelle des machines), ces « boites noires » fournissent des résultats qui ne sont pas directement compréhensibles. Ainsi, des méthodes XAI post hoc sont gé néralement utilisées pour les […]
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Hyperparameter Impact on Computational Efficiency in Federated Edge Learning
The heterogeneity induced by the federated edge learning execution environment poses many performance challenges. Indeed, a balance between efficient resource usage and inference accuracy must be found. Our work therefore aims at characterizing the hyperparameter influence by creating a variety of simulated execution circumstances. We designed an experimentation platform to simulate the execution of a […]
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