Publications
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Exploring human-machine collaboration in industry: a systematic literature review of digital twin and robotics interfaced with extended reality technologies
This systematic literature review presents the latest advancements and insights about digital twin technology and robotics interfaced with extended reality in the context of Industry 4.0. As the extended reality technologies emerge, it results in an increasing overlap between digital twins and human-robot interactions in industrial settings, promoting collaboration between operators and cobots in manufacturing […]
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RUL Prediction with Encoding and Spatial-Temporal Deep Neural Networks
The objective of this paper is to design and develop an approach to estimate the Remaining Useful Life (RUL) of an industrial equipment evolving in a Cyber-Physical System (CPS). To do so, this work aims to predict failures and malfunctions of an industrial equipment, as well as evaluating all the main underlying causes. The system […]
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Réseau antagoniste génératif pour la fusion spatio-temporelle d’images satellitaires multi-spectrales
Résumé – Dans cet article, nous étudions la fusion spatio-temporelle d’une série temporelle d’images multi-spectrales avec une série temporelle d’images hyper-spectrales. Nous proposons pour cela une nouvelle approche fondée sur un réseau antagoniste génératif (GAN). Notre contribution principale réside dans le fait que le GAN prend en entrée des images satellitaires plutôt que du bruit. […]
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Determinantes do Trabalho
Cuvelier, L., Nascimento, A., & Fourrièrre, J. (2023). Determinantes do Trabalho. In R. Rocha (Ed.), Dicionário de Ergonomia e Fatores Humanos.
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A SPARQL-based framework to preserve privacy of sensitive data on the semantic web
Over the last few years, the web of data has been evolved. Indeed, it allows sharing of a significant interconnection of a huge amount of data in several domains and it keeps increasing continuously. Due to the confidential nature of some data, sectors such as health, financial, and government, it have limited participation with fewer […]
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Towards the Development of a Digital Twin for Micro Learning Factory: A Proof of Concept
The Learning Factory concept has gained importance in recent years to improve manufacturing education and prepare students for the workforce. Digital Twin (DT) technology is considered as a crucial tool to enhance the Learning Factory experience. Due to the novelty of this topic, there is limited research on developing DTs specifically for this purpose. Currently, […]
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Distributed dynamics scheduling based reinforcement learning: importance and challenges
When it comes to scheduling choices inside complex industrial systems, the dynamic job shop scheduling problem (DJSSP) poses substantial difficulties. Deep learning, artificial intelligence (AI), and reinforcement learning approaches have all shown promising solutions in recent years to enhance the effectiveness and performance of DJSSP systems. This study provides a detailed analysis of the DJSSP […]
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Machine Learning for Predicting Personality Traits from Eye Tracking
Recently, personality prediction holds significant importance in human centered systems, particularly in decision support systems, the smart industry, and the development of human machine interfaces. Eyes can reveal deep insights into a person’s personality, so people’s visual behavior could better reflect their personality. In this research, we demonstrate that machine learning techniques can predict individual […]
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Comparative Study of Waste Management Systems in Algeria and Other Countries : a literature review
Waste management holds significant importance for developing countries due to its impact on the environment, health, and economy. Insufficient waste management practices can result in pollution, disease outbreaks, greenhouse gas emissions, and social conflicts. Consequently, developing countries must make strategic decisions to enhance their waste management systems and practices. This article aims to examine waste […]
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lectric Vehicle Route Simulation: A Preliminary Approach
This article presents a NetLogo-based multi-agent simulator developed to optimize route and task planning using electric vehicles for travel between branches of Société Générale. The simulator takes into account constraints linked to the limited autonomy of electric vehicle batteries in the dense urban context of branches. We carried out simulation tests to evaluate the simulator’s […]
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Contribution to Maintenance 4.0 by Monitoring and Prognosis of Industrial Installations by Digital Twin: Case Study on Wastewater Filtration Pilot
The digital solutions have taken an advance during the digital transition in the industrial development, the use of new technologies has allowed to better understand the behavior of the different parts of an industrial installation and to verify the interactions between the adjustment parameters and the optimal functioning of the production units and their impact […]
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Errare humanum est, perseverare autem diabolicum: A Follow-Up Study on the Human-Likeness of an AI Othello Player
Othello, also known as Reversi, is a popular 2-players board game. Olivaw is an intelligent agent playing Othello. Compared to the most famous ones (such as Saio), it exploits limited resources by autonomously learning how to improve its gameplay by playing against itself. In previous occasions, Othello players reported the impression of a sort of […]
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