Articles dans des revues internationales ou nationales avec comité de lecture
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Online human motion analysis in industrial context: A review
Human motion analysis plays a crucial role in industry 4.0 and, more recently, in industry 5.0 where humancentered applications are becoming increasingly important, demonstrating its potential for enhancing safety, ergonomics and productivity. Considering this opportunity, an increasing number of studies are proposing works on the analysis of human motion in an industrial context, taking advantage […]
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Determinant Factors of Teaching Performance in COVID-19 Context
COVID-19 pandemic still impact higher education system, stakeholders and environment all around the world. Students, teachers, academic institutions and education decision makers were shocked by an atypical new context they promptly put in face, asking drastic change in behavior and procedures at individual, familial and institutional levels. Full lockdown and closing campuses enforced students and […]
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Deep Learning Based on EfficientNet for Multiorgan Segmentation of Thoracic Structures on a 0.35 T MR-Linac Radiation Therapy System
The advent of the 0.35 T MR-Linac (MRIdian, ViewRay) system in radiation therapy allows precise tumor targeting for moving lesions. However, the lack of an automatic volume segmentation function in the MR-Linac’s treatment planning system poses a challenge. In this paper, we propose a deep-learning-based multiorgan segmentation approach for the thoracic region, using EfficientNet as […]
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EEG-based Emotion Recognition Using Modified Covariance and Ensemble Classifiers
The Electroencephalography (EEG)-based precise emotion identification is one of the most challenging tasks in pattern recognition. In this paper, an innovative EEG signal processing method is devised for an automated emotion identification. The Symlets-4 filters based « Multi Scale Principal Component Analysis » (MSPCA) is used to denoise and reduce the raw signal’s dimension. Onward, the « Modified […]
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An overview on human-centred technologies, measurements and optimisation in assembly systems.
This paper offers an in-depth examination of the ergonomics of human-centred assembly systems in Industry 4.0, where manual tasks remain essential. The use of advanced technologies such as motion capture (MOCAP) and virtual reality (VR) is analysed as ways to enhance system efficiency and improve worker well-being. The paper highlights the importance of optimising assembly […]
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Photogrammetry and deep learning for energy production prediction and building-integrated photovoltaics decarbonization
Building-Integrated photovoltaics (BIPV) have emerged as a promising sustainable energy solution, relying on accurate energy production predictions and effective decarbonization strategies for efficient deployment. This paper presents a novel approach that combines photogrammetry and deep learning techniques to address the problem of BIPV decarbonization. The method is called BIM-AITIZATION referring to the integration of BIM […]
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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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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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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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