Publications
-
Towards Green AI : Assessing the Robustness of Conformer and Transformer Models under Compression
Today, transformer and conformer models are commonly used in end-to-end speech recognition. Generally, conformer models are more efficient than transformers, but both suffer from large sizes, and expensive computing cost making their use environmentally unfriendly. In this paper, we propose compressing these models using quantization and pruning, evaluating size and computing time improvements while monitoring […]
-
Adaptative Reinforcement Learning Approach for Predictive Maintenance of a Smart Building Lighting System
Due to advancements in sensing technologies, enhanced IoT architectures, and expanded connectivity options, predictive maintenance has emerged as a compelling solution within the context of Industry 4.0 for industrial systems. However, within this landscape, such as in Smart Buildings (SBs), the lack of failure data poses a significant challenge for implementing traditional data-based approaches documented […]
-
Additive Manufacturing Awareness For Engineering Education in France
Additive manufacturing (AM) is one of the pillars of the Industry 4.0. Compared to traditional manufacturing, AM is a layer-by-layer construction; it provides a prototype before producing in order to optimize the design and avoid the stock market and uses strictly necessary material, which can be recyclable, at the benefit of leaning towards local production, […]
-
Requirements engineering and user needs analysis
This chapter aims to provide guiding concepts to understand Requirements Engineering and User Needs Analysis, including methodological insights regarding the process and the object of study: focusing on different kinds of needs, including motivational needs, stimulating innovation, and anticipating future needs at the individual and societal levels. This chapter builds on several previous publications by […]
-
Federated Learning Survey: A Multi-Level Taxonomy of Aggregation Techniques, Experimental Insights, and Future Frontiers
The emerging integration of IoT (Internet of Things) and AI (Artificial Intelligence) has unlocked numerous opportunities for innovation across diverse industries. However, growing privacy concerns and data isolation issues have inhibited this promising advancement. Unfortunately, traditional centralized machine learning (ML) methods have demonstrated their limitations in addressing these hurdles. In response to this ever-evolving landscape, […]
-
Reinforcement learning for HVAC control in intelligent buildings: A technical and conceptual review
Heating, Ventilation and Air Conditioning (HVAC) systems in buildings are a major source of global operational CO2 emissions, primarily due to their high energy demands. Traditional controllers have shown effectiveness in managing building energy use. However, they either struggle to handle complex environments or cannot incorporate learning from experience into their decision-making processes, leading to […]
-
From social manufacturing and entrepreneurship to social open innovation: Exploring the role of fabrication laboratories
The research aims to shed light on the role of open innovation in addressing social and economic challenges. It focuses on 3D-based fabrication laboratories (fablabs) and attempts to identify the mechanisms through which the latter facilitates the diffusion and promotion of (open) innovations. The findings reveal how fablabs and additive manufacturing (AM) enable the scaling […]
-
LEAN-BIM SYNERGY IN THE CONSTRUCTION DESIGN PHASE: AUTO-GENERATION AND EVALUATION OF THERMAL ALTERNATIVES
This study explores the integration of Lean principles with Building Information Modeling (BIM) to enhance decision-making in the relatively unexplored field of thermal design for construction projects. Recognizing the limitations of current design processes, characterized by insufficient alternatives and a lack of team collaboration, we introduce a new decision-making tool. This tool centers on a […]
-
Sampled-Data Observer Design for Linear Kuramoto-Sivashinsky Systems with Non-Local Output
The aim of this paper is to provide a novel systematic methodology for the design of sampled-data observers for Linear Kuramoto-Sivashinsky systems (LK-S) with non-local outputs. More precisely, we extend the systematic sampled-data observer design approach which is based on the use of an Inter-Sample output predictor to the class of LK-S systems. By using […]
-
Impact of polypropylene fibers on the rheological, mechanical, andthermal properties of self-compacting concrete
The objective of this experimental investigation is to examine the impact of using polypropylene fibers on the properties of self-compacting concrete (SCC). Five mixtures were prepared, one reference concrete (without fibers) and four other SCC containing, 0.05,0.1, 0.15, and 0.2% of polypropylenes fibers. Rheological (slump flow, yield stress, and plastic viscosity) and mechanical (compressivestrength) properties […]
-
Meeting the challenges of effective readiness for change in a global context
The aim of this paper is to address the potential impact of perceptions on individual readiness for change. Based on a quantitative survey of 310 executives from Anglo Saxon countries, North and Latin Europe, Arabian countries, and Far East Asian countries, identified via multi stage sampling, we compare the impact of employees’ cultural factors (cultural […]
Chargement en cours…
Erreur : tout le contenu a été chargé.