Publications
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BootBOGS: Hands-on optimizing Grid Search in hyperparameter tuning of MLP
Neural networks are widely used in the literature in a variety of fields and for a large number of applications. A major challenge in their use is the need to identify and process hyperparametric values. Grid Search is a widely used technique for meeting this task. It systematically searches for values in a predefined range […]
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Very short-term prediction of photovoltaic energy in the winter building for an automatic energy management system
In the context of the energy transition, renewable energies have an important role to play. This is particularly true of photovoltaic (PV) energy. The use of PV energy in buildings is becoming increasingly common nowadays. Buildings integrated PV (BIPV) represent a major advantage in this respect, thanks to their high PV energy harvesting capacity. However, […]
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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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Optimal Deployment of Fog-Based Solution for Connected Devices in Smart Factory
Internet of Things (IoT) is commonly used in Industry-4.0/5.0, but it generates an excessive amount of data that affects quality of service (QoS). To address this challenge, Fog-based architectures have emerged as an alternative solution. However, its deployment can be challenging, particularly when dealing with mobile connected devices like robots. To optimize the deployment 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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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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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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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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EXPERIMENTAL EVALUATION OF INTERFACE ADHESION OF A FLAX FIBER COMPOSITE PATCH WITH EPOXY AND POLYURETHANE ADHESIVES FOR THE REINFORCEMENT OF STEEL STRUCTURES
Using fiber-reinforced composite patches for repairing damaged structures made of metal or/and concrete is an interesting and widely available solution on the market using synthetic materials. These repairing patches are bonded on the structures’ surfaces to increase their strength against internal stresses, as well as protect them from external physico-chemical attacks, thereby limiting crack propagation. […]
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ECG based Apnea Detection by Multirate Processing Hybrid of Wavelet-Empirical Decomposition Hjorth Features Extraction and Neural Networks
Sleep Apnea (SA) can cause health complications including heart stroke and neurological disorders. The Polysomnography (PSG) test can detect the severity of sleep disturbance. However, it is expensive and requires a dedicated sleep laboratory and expertise to examine the patients. Therefore, it is not available to a large population in developing countries. This leads to […]
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