Publications
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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 […]
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Simultaneous Backward Reduction algorithm for disassembly lot-sizing under random ordering lead time
In order to meet item demands, end-of-life (EOL) product and subassembly ordering and disassembly schedules are determined by disassembly lot sizing, which is the subject of this study. We take into consideration a stochastic version with undetermined ordering lead time (OLT). In this case, OLT stands for the amount of time that passes between placing […]
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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 […]
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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 […]
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Bi-Objective Multi-Period Multi-Sourcing Supply Planning with Stochastic Lead-Times, Degressive Pricing, and Carbon Footprint
This article studies a bi-objective stochastic optimization problem for multi-period multi-sourcing supply planning. The formulated problem accounts for stochastic lead times, degressive pricing, holding and backlog costs, delivery flexibility costs, as well as both holding and transportation carbon footprint. The first objective is to minimize the expected total cost, while the second objective is to […]
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Maturity Measurement Framework for Evaluating BIM-Based AR/VR Systems Adapted from ISO/IEC 15939 Standard
This article proposes a framework for evaluating the maturity of BIM-based augmented and virtual reality systems by defining indicators based on the ISO/IEC 15939 standard. These indicators aim to provide a more comprehensive assessment of system maturity by combining results from various measurements, while differentiating between sub-criteria, criteria, and maturity aspects. This framework not only […]
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Modeling Distributed and Flexible PHM Framework based on the Belief Function Theory
This paper explores the integration of the belief function theory within the domain of Prognostics and Health Management (PHM), offering a novel approach to decision-making under conditions of uncertainty and incomplete information. Central to our methodology is the modeling of beliefs and uncertainties through belief mass functions, enabling the representation and aggregation of diverse information […]
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PMoET: Going Wider than Deeper using the Parallel Mixture-of-Experts Transformer for 3D Hand Gesture Recognition
Mistral AI (Artificial Intelligence) Startup has released MixtralTransformers based on a Mixture of Experts layer (MoE). MoE architectures have gained prominence in both Large Language Modeling (LLM) and Computer Vision due to their ability to scale efficiently by dynamically selecting an ensemble of specialized sub-models (a group of experts) for different inputs rather than using […]
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Enhanced multi-horizon occupancy prediction in smart buildings using cascaded Bi-LSTM models with integrated features
Accurate occupancy prediction in smart buildings is crucial for optimizing energy management, improving occupant comfort, and effectively controlling building systems, particularly for short- and long-term horizons. Recently, deep learning-based occupancy prediction methods have gained considerable attention. However, the full potential of these methods remains under explored in terms of model architecture variations and prediction horizons. […]
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Online Phishing Detection: A Heuristic-Based Machine Learning Framework
The prevalence of phishing attacks has exhibited a marked rise in recent years, posing significant threats to the confidentiality, integrity, and availability of sensitive data at both individual and organizational levels. This escalating threat underscores the critical need for automated and real-time detection of phishing web pages. This paper proposes a novel machine-learning framework that […]
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Optimizing Comfort and Energy Efficiency: The Impact of Model Accuracy on Mutli-Objective MPC
Buildings are responsible for ∼30% of primary energy consumption, mainly because of Heating, Ventilation, and Air Conditioning (HVAC) systems. The usual ON/OFF controller tends to react to occupancy presence, causing discomfort and energy waste. Furthermore, these controllers usually focus on thermal comfort and disregard other comforts, such as air quality, visual, etc. due to their […]
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Metaheuristics and Machine Learning Convergence: A Comprehensive Survey and Future Prospects
The integration of machine learning techniques with optimization algorithms has garnered increasing interest in recent years. Two primary purposes emerge from the literature: leveraging metaheuristics in machine learning applications such as regression, classification, and clustering, and enhancing metaheuristics using machine learning to improve convergence time, solution quality, and flexibility. Machine learning techniques offer real-time decision-making […]
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