Publications
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Investigating the Optimal DOD and Battery Technology for Hybrid Energy Generation Models in Cement Industry Using HOMER Pro
The cement industry is a major energy consumer, with most of its costs associated with fuel and energy requirements. While traditional thermal power plants generate electricity, they are both harmful and inefficient. In this study, battery depth of discharge (DOD) is evaluated for four different battery technologies in the context of the cement industry. The […]
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PUF-based mutual authentication and session key establishment protocol for IoT devices
The Internet of things (IoT) is an indispensable part of our daily lives, bringing us many conveniences, including e-commerce and m-commerce services. Unfortunately, IoT networks suffer from several security issues, such as privacy, access control, and authentication. However, due to the limited computation resources, remote authentication between IoT devices and servers is vulnerable to being […]
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Feasibility for the Recovery of Excavated Soils in Compressed Earth Blocks as a Sustainable Building Material
Abstract: Soil is continuously excavated for development activities in urban and rural areas and treated as waste. This study investigates the characteristics of urban soils excavated from earthworks of buildings in the Brittany region of France for their perspective reuse in earthen construction materials to valorize soil waste and provide a sustainable building material locally. […]
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FedGA-Meta: Federated Learning Framework using Genetic Algorithms and Meta-Learning for Aggregation in Industrial Cyber- Physical Systems
In Industry 4.0, factories encounter significant challenges in making informed decisions to maintain or enhance their industry standing. By utilizing machine learning (ML), they can improve product quality, decrease production downtime, and boost operational efficiency. However, acquiring datasets with sufficient variation and diversity to train a robust neural network centrally is a challenge within the […]
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Automated Categorization of Multiclass Welding Defects Using the X-ray Image Augmentation and Convolutional Neural Network
The detection of weld defects by using X-rays is an important task in the industry. It requires trained specialists with the expertise to conduct a timely inspection, which is costly and cumbersome. Moreover, the process can be erroneous due to fatigue and lack of concentration. In this context, this study proposes an automated approach to […]
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Problem-based learning analysis using capability approach
Based on research conducted with undergraduated students in French Engineering School, we propose to highlight the conditions under which problem-based learning (PBL) can be favorable to student’s learning based on the method of analysis resulting from the capability approach (Sen, 2001). PBL appears in the literature to be an adapted way to tend to, among […]
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Verbalizing the sensitive dimensions of activity in work situations
Verbalizing the sensitive dimensions of activity in work situations
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Is Lead-Userness a trait or a state?
Lead users are invaluable resources to generate user centric radical innovation, but they remain difficult to detect and recruit in the general population. Lead userness, which draws both on the ability to identify unstated customer needs and find creative solutions to those needs, has been conceptualized as domain-dependent: this means that a lead user may […]
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Consensus de partitions en NLP pour une Revue systématique de la littérature autour de l’XAI du biais et de l’équité
Ce travail présente une analyse comparative d’une bibliographie autour du biais de l’équité et de l’explicabilité des algorithmes de l’IA entre 2015 et 2022. Par trois approches de Traitement Automatique du Langage Naturel, nous avons extrait différents sujets traités par cette bibliographie. Ces trois approches nous ont également fourni trois partitions. Dans l’optique d’éviter de […]
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Predictive Maintenance in the Industrial Sector: A CRISP-DM Approach for Developing Accurate Machine Failure Prediction Models
In production systems, avoiding repeated failures is crucial for reducing costs and preventing downtime. Industry 4.0 technologies have enabled companies to collect and analyze real-time data from machines, which helps in identifying and preventing potential problems. By using metrics like MTBF and MTTR and analyzing past failures, we can develop predictive models to prevent future […]
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Proteus the origin story: how users conform their behavior to the appearance of their avatars
Depuis leur émergence, les environnements virtuels représentent un outil innovant pour étudier le comportement humain dans des situations impossibles à simuler autrement. L’une de ces situations est l’incarnation d’un corps virtuel entièrement différent du nôtre (i.e. un avatar). L’étude de ce cas a permis de mettre en évidence l’existence de l’effet Proteus : le fait […]
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