Publications
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Towards deep learning methods to improve photovoltaic prediction and building decarbonization in benchmarking study
High energy demand, energy transition, energy consumption control are challenges for the future, especially for Building Integrated Photovoltaic (BIPV). There is a great potential to harvest large amounts of photovoltaic (PV) energy on horizontal and vertical surfaces. However, this high potential is often hindered by the slow deployment of these panels, the complex integration into […]
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T2S-MAKEP and T2T-MAKEP: A PUF-based Mutual Authentication and Key Exchange Protocol for IoT devices
Nowadays, more constrained devices are becoming connected, building an extensive Internet of Things (IoT) network, but suffering from many security issues. In particular, authentication has become a severe research challenge for IoT systems. Furthermore, confidentiality, integrity, and availability are considered the core underpinnings of information security in general. Unfortunately, deploying conventional authentication protocols for IoT […]
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Toward a digital twin IoT for the validation of AI algorithms in smart-city applications
Thedevelopmentofdigitaltwinsforroadtraffichasgarnered significant attention within the scientific community, particularly in the realms of virtualization and the Internet of Things (IoT). The implemen- tation of a digital twin for automobiles offers a virtual replica, capable of discerning the precise location, status, and real-time behavior of each vehicle present in the road traffic network. The primary objective of […]
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Deep Reinforcement Learning for multiobjective Scheduling in Industry 5.0 Reconfigurable Manufacturing Systems
In today’s manufacturing environment, the need to respond quickly to changing market demands is critical. Reconfigurable Manu- facturing Systems (RMS) represent a monumental step towards realis- ing this requirement, providing an agile and cost-effective framework to accommodate changing production needs. The dynamic nature of RMS requires the integration of robust learning algorithms to continuously op- […]
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Can Teal practices increase employees’ work engagement?
Because engaged employees work with passion, in deep connection with their company and are innovative, they may drive their organization’s performance. Teal organizations, which implement original and inspiring ways of working, appear particularly favourable to create and support engagement in the long run. The aim of this paper is twofold: first, to study engagement drivers […]
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Building a positive corporate governance
Organizations are subject to a dual movement of evolution: in the short term, they must adapt to fluctuations of the economic, geopolitical, energy, health, situations and so on. In the long term, they must be part of major societal and environmental transformations. Corporate governance must assume this dual mission of strategic decision and social responsibility, […]
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What are the drivers of competence management?
Globalization and technological transformations emphasize the need for developing new skills and acting at the peak of one’s capacities. Competence is defined as the combination of external and individual resources to fulfill one’s job demands and contribute to the organization’s purpose. It corresponds to feeling effective and efficient in one’s actions. As such, competence is […]
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CG-MER: A Card Game-based Multimodal dataset for Emotion Recognition
The field of affective computing has seen significant advancements in exploring the relationship between emotions and emerging technologies. This paper presents a novel and valuable contribution to this field with the introduction of a comprehensive French multimodal dataset designed specifically for emotion recognition. The dataset encompasses three primary modalities: facial expressions, speech, and gestures, providing […]
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Intrusion Detection System for IoT based on Complex Networks and Machine Learning
Network Intrusion Detection Systems (NIDS) are critical tools for detecting and preventing cyber-attacks in computer networks. Traditional rule-based NIDS can be limited in their ability to detect complex and sophisticated attacks. However, recent advancements in Artificial Intelligence (AI), such as deep learning algorithms, have provided new methods for enhancing NIDS capabilities, improving detection rates, reducing […]
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The Value of Extended Reality Techniques to Improve Remote Collaborative Maintenance Operations: A User Study
In the Architecture, Engineering and Construction (AEC) sector, data extracted from building information modelling (BIM) can be used to create a digital twin (DT). The algorithms of a BIM-based DT can facilitate the retrieval of information, which can then be used to improve building operation and maintenance procedures. However, with the increased complexity and automation […]
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Modelling the “transactive memory system” in multimodal multiparty interactions
Transactive memory system (TMS) is a team emergent state representing the knowledge of each member about “who knows what” in a team performing a joint task. We present a study to show how the three TMS dimensions Credibility, Specialisation, Coordination, can be modelled as a linear combination of the nonverbal multimodal features displayed by the […]
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Exploring the Activities and Outcomes of Living Labs: Insights for meeting stakeholder expectations
Open innovation is a key concept in innovation management that encourages collaboration, knowledge sharing, and co-creation. Living Labs, as collaborative innovation structures, are well-suited for implementing open innovation. They serve as user-centered ecosystems for testing and validating user-oriented solutions in real-life conditions. While existing literature explores various dimensions of Living Labs, empirical research on practical […]
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