Publications
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A Survey on Energy Storage: Techniques and Challenges
Intermittent renewable energy is becoming increasingly popular, as storing stationary and mobile energy remains a critical focus of attention. Although electricity cannot be stored on any scale, it can be converted to other kinds of energies that can be stored and then reconverted to electricity on demand. Such energy storage systems can be based on […]
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A MILP for Green Scheduling Integrating Human Factors
The Flexible Job Shop Scheduling Problem (FJSSP) has been widely studied in last decades. The emergence of technological advancements in the context of Industry 4.0 has brought many changes and made production scheduling more and more efficient. Today’s Industry 5.0 paradigm pays great attention to human factors and environmental considerations to enhance the system’s sustainability […]
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Planification multi-période, multi-sourcing d’approvisionnements avec délais stochastiques, prix dégressifs et coûts de flexibilité de livraison
L’objectif de ce travail est d’étudier le problème du réapprovisionnement multi-période avec des fournisseurs multiples sous des délais stochastiques et d’étudier les effets de la limite de capacité des fournisseurs, de la politique de prix dégressive et du coût de flexibilité de livraison.
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It’s not Just What You Do but also When You Do It: Novel Perspectives for Informing Interactive Public Speaking Training
Most of the emerging public speaking training systems, while very promising, leverage temporal-aggregate features, which do not take into account the structure of the speech. In this paper, we take a different perspective, testing whether some well-known socio-cognitive theories, like first impressions or primacy and recency effect, apply in the distinct context of public speaking […]
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AI-Powered Diagnosis of Skin Cancer: A Contemporary Review, Open Challenges and Future Research Directions
The proposed research aims to provide a deep insight into the deep learning and machine learning techniques used for diagnosing skin cancer. While maintaining a healthy balance between both Machine Learning as well as Deep Learning, the study also discusses open challenges and future directions in this field. The research includes a comparison on widely […]
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Epileptic Seizure Detection Using the EEG Signal Empirical Mode Decomposition and Machine Learning
Epileptic seizures affect millions of people worldwide. Medical treatments exist to help lessen the severity of the damage caused by these seizures. However, people with epilepsy still struggle with unexpected seizures. People who experience epileptic seizures have Electroencephalogram (EEG) signals that show different features in comparison to a healthy brain. In this study, EEG signals […]
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Heart Disease Identification Based on Butterfly Optimization and Machine Learning
This paper aims to make use of The Physionet Challenge 2016 collection of normal and abnormal heart sound recordings that were classified by automated identification of PCG sounds to help detect heart diseases earlier and prevent incidents. People with heart diseases have been increasing and most of them lead to fatalities so the detection of […]
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Digital Twin of an Industrial Workstation: A Novel Method of an Auto-Labeled Data Generator using Virtual Reality for Human Action Recognition in the Context of Human Robot Collaboration
The recognition of human actions based on artificial intelligence methods to enable Human-Robot Collaboration (HRC) inside working environments remains a challenge, especially because of the necessary huge training datasets needed. Meanwhile, Digital Twins (DT) of human centered productions are increasingly developed and used in the design and operation phases. As instance, DT are already helping […]
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Jumeaux numériques pour l’enseignement
Présentation du projet JENII, état de l’art S. Fernagu, Directrice de recherche au CESI- Paris :« Implication de l’usage des jumeaux numériques sur l’enseignement et l’apprentissage professionnels ».Vous la/le retrouverez ici : http://pod.univ-cotedazur.fr/video/16519-fernagu-jumeaux-numeriquesv2mp4/
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Decision-making in the context of Industry 4.0: Evidence from the textile and clothing industry
Industry 4.0 arrives with a multitude of technological advances which impact the different components of a product’s value chain. Most existing research investigate the application of Industry 4.0 technologies in various parts of the manufacturing process. However, there is still a lack of comprehensive research on the impact of Industry 4.0 technologies on decision-making and […]
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Flexible job shop scheduling problem under Industry 5.0: A survey on human reintegration, environmental consideration and resilience improvement
The Job Shop Scheduling Problem (JSSP) has been widely studied in recent decades. Various approaches have been proposed to support scheduling decisions according to the evolving production environment. The emergence of technological advancements in the context of Industry 4.0 has brought many changes and made production scheduling more and more efficient. Today’s Industry 5.0 environment […]
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Detecting Dynamic Patterns In Dynamic Graphs Using Subgraph Isomorphism
Graphs have been used in different fields of research for performing structural analysis of various systems. In order to compare the structure of two systems, the correspondence between their graphs has to be verified. The problem of graph matching, especially subgraph isomorphism (SI), has been well studied in case of static graphs. However, many applications […]
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