Publications
-
Potatoes Supply Chain Challenges and Opportunities in Algeria : A literature Review
The Agri-Food Supply Chain (AFSC) has become a focal point of attention in recent times due to the intersection of technology and integrated Supply Chain (SC) performance. Current research endeavors aim to minimize waste, maximize yield, and enhance planning while ensuring chain traceability and maintaining product price equilibrium. This paper offers a comprehensive summary of […]
-
Distributed dynamics scheduling based reinforcement learning: importance and challenges
When it comes to scheduling choices inside complex industrial systems, the dynamic job shop scheduling problem (DJSSP) poses substantial difficulties. Deep learning, artificial intelligence (AI), and reinforcement learning approaches have all shown promising solutions in recent years to enhance the effectiveness and performance of DJSSP systems. This study provides a detailed analysis of the DJSSP […]
-
Machine Learning for Predicting Personality Traits from Eye Tracking
Recently, personality prediction holds significant importance in human centered systems, particularly in decision support systems, the smart industry, and the development of human machine interfaces. Eyes can reveal deep insights into a person’s personality, so people’s visual behavior could better reflect their personality. In this research, we demonstrate that machine learning techniques can predict individual […]
-
Comparative Study of Waste Management Systems in Algeria and Other Countries : a literature review
Waste management holds significant importance for developing countries due to its impact on the environment, health, and economy. Insufficient waste management practices can result in pollution, disease outbreaks, greenhouse gas emissions, and social conflicts. Consequently, developing countries must make strategic decisions to enhance their waste management systems and practices. This article aims to examine waste […]
-
lectric Vehicle Route Simulation: A Preliminary Approach
This article presents a NetLogo-based multi-agent simulator developed to optimize route and task planning using electric vehicles for travel between branches of Société Générale. The simulator takes into account constraints linked to the limited autonomy of electric vehicle batteries in the dense urban context of branches. We carried out simulation tests to evaluate the simulator’s […]
-
SPDGAN: A Generative Adversarial Network based on SPD Manifold Learning for Automatic Image Colorization
This paper addresses the automatic colorization problem, which converts a gray-scale image to a colorized one. Recent deep-learning approaches can colorize automatically grayscale images. However, when it comes to different scenes which contain distinct color styles, it is difficult to accurately capture the color characteristics. In this work, we propose a fully automatic colorization approach […]
-
Contribution to Maintenance 4.0 by Monitoring and Prognosis of Industrial Installations by Digital Twin: Case Study on Wastewater Filtration Pilot
The digital solutions have taken an advance during the digital transition in the industrial development, the use of new technologies has allowed to better understand the behavior of the different parts of an industrial installation and to verify the interactions between the adjustment parameters and the optimal functioning of the production units and their impact […]
-
A Conceptual Framework for MaturityEvaluation BIM-based AR/VR Systems
Maturity evaluation of BIM-based Augmented Reality (AR) and Virtual Reality (VR) systems is a challenging issue that requires ensuring their effectiveness and reliability. However, the lack of appropriate evaluation methods, tools, and standards for these systems makes this task even more complex. In this context, this paper proposes a conceptual framework for evaluating the maturity […]
-
Towards the Development of a Digital Twin for Micro Learning Factory: A Proof of Concept
The Learning Factory concept has gained importance in recent years to improve manufacturing education and prepare students for the workforce. Digital Twin (DT) technology is considered as a crucial tool to enhance the Learning Factory experience. Due to the novelty of this topic, there is limited research on developing DTs specifically for this purpose. Currently, […]
-
D-STGCNT: A Dense Spatio-Temporal Graph Conv-GRU Network based on Transformer for Assessment of Patient Physical Rehabilitation
This paper tackles the challenge of automatically assessing physical rehabilitation exercises for patients who perform the exercises without clinician supervision. The objective is to provide a quality score to ensure correct performance and achieve desired results. To achieve this goal, a new graph-based model, the Dense Spatio-Temporal Graph Conv-GRU Network with Transformer, is introduced. This […]
-
Investigation of Input Feature Combinations Considering Occupant Behavior for Modelling Indoor Air Temperature in a Classroom
This study investigated the performance of artificial neural networks and random forests with various combinations of input variables in modelling indoor air temperature in a classroom. The data collection methodology was designed to investigate key input parameters, including indoor air data, classroom occupancy, and occupant behavior factors such as windows, doors, blind operation, and occupant […]
-
Fault Prediction in a Smart Building Lighting System
With the advances in many areas such as sensing technologies, new connectivity options and improved IoT architectures, predictive maintenance is considered as a promising solution for the maintenance of Smart Buildings (SBs). However, because of the lack of failure data for these systems, the approaches in the literature, which are mostly data-based approaches, are not […]
Loading…
Erreur : tout le contenu a été chargé.