Publications
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Fault Diagnosis using Deep Neural Networks for Industrial Alarm Sequence Clustering
Significant progress has been made in the field of industrial alarm management systems (AMS) in terms of diagnostic and prognostic accuracy. However, persistent challenges, such as poorly configured alarm setups and floods, contribute to an increased number of false alarms, consequently reducing the efficiency of the monitoring system. In addition, more sophisticated models and interactive […]
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LoRaCAPS: Congestion-Aware Path Selection Protocol for Offshore LoRaWAN Networking
LoRaWAN technology plays a pivotal role in enabling data transmission from IoT devices across various industries. In the maritime sector, applications such as operational monitoring and environmental surveillance depend critically on reliable data communication. However, wireless data transmission at sea presents significant challenges, including limited device battery life, harsh weather conditions, and interference from vessels. […]
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Multi Objective Optimization of Human-Robot Collaboration: A Case Study in Aerospace Assembly Line
Collaborative robotics is becoming increasingly prevalent in industry 5.0, leading to a growing need to improve interactions and collaborations between humans and robots. However, the current approach to defining the sharing of responsibilities between humans and robots is empirical and uses the robot as an active fixture of parts, which is a sub-optimal method for […]
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An improved 3D skeletons UP-Fall dataset : enhancing data quality for efficient impact fall detection
Detecting impact where an individual makes contact with the ground within a fall event is crucial in fall detection systems, particularly for elderly care where prompt intervention can prevent serious injuries. The UP-Fall dataset, a key resource in fall detection research, has proven valuable but suffers from limitations in data accuracy and comprehensiveness. These limitations […]
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Proteus effect: how avatars influence the way we behave
Poster présenté au RJC en IHM 2024 sur le projet de thèse d’Anna Martin Coesel
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Designing Secure and Smart Supply Chains: A Roadmap
The supply chain (SC) comprises all the vital stages a product goes through to its final destination, forming a value chain. In this article, our primary focus is on integrating Internet of Things, artificial intelligence, and blockchain technology to design secure and smart SC systems.
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Remaining useful life prediction with uncertainty quantification using evidential deep learning
Predictive Maintenance presents an important and challenging task in Industry 4.0. It aims to prevent premature failures and reduce costs by avoiding unnecessary maintenance tasks. This involves estimating the Remaining Useful Life (RUL), which provides critical information for decision makers and planners of future maintenance activities. However, RUL prediction is not simple due to the […]
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Transitioning from AGVs to AIVs in Integrated Job Shop Scheduling with Transportation Tasks: aMulti-agent Simulator for Comparative Analysis
Optimizing job shop scheduling in modern factories demands flexibility and adaptability to handle unexpected events and Unmanned Ground Vehicles (UGVs) limitations. This paper addresses these challenges by introducing a novel multi-agent simulator for the Job Shop Scheduling Problem (JSSP) with UGVs handling transportation tasks. The simulator, designed with Netlogo, incorporates real-world constraints, such as collision […]
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La construction circulaire en action
Engagé dans une démarche de baisse de son impact environnemental, le secteur de la construction s’applique à passer d’un modèle économique linéaire « fabriquer, consommer, jeter » à un modèle circulaire, favorisant le réemploi, la durabilité et la réversibilité. Alors que la pénurie de matériaux est de plus en plus préoccupante, il est essentiel d’anticiper […]
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Multimodal transportation network for bio-waste collection: the case of Normandy
In this paper, we introduce a new topology, connected-hubs, to the multimodal transportation literature. As strategic planning, the multimodal transportation network design decides the locations of consolidation centers and the routes between the origins and the destinations with the minimum of total cost. Most existing papers formulate the problem based on the hub-and-spoke topology, while […]
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Dataset of an operating education modular building for simulation and artificial intelligence
Improving energy efficiency in the building sector is a subject of significant interest, considering the environmental impact of buildings. Energy efficiency involves many aspects, such as occupant comfort, system monitoring and maintenance, data treatment, instrumentation… Physical modeling and calibration, or artificial intelligence, are often employed to explore these different subjects and, thus, to limit energy […]
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Graph Transformer Mixture-of-Experts (GTMoE) for 3D Hand Gesture Recognition
Mixture-of-experts (MoE) architectures have gained popularity in achieving high performance in a wide range of challenging tasks in Large Language Modeling (LLM) and Computer Vision, especially with the rise of Mixture-of-Experts with Mixtral/Mistral-7B Transformers. In this work, we propose the Graph Transformer Mixture-of-Experts (GTMoE) deep learning architecture to enhance the ability of the Transformer model […]
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