Publications
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A Novel Integration Technique for Optimal Location & Sizing of DG Units With Reconfiguration in Radial Distribution Networks Considering Reliability
This paper introduces an advanced approach for optimizing the distribution network reconfiguration (DNR) with the placement and sizing of multiple types of distributed generators (DGs). The method employs the ant colony optimization algorithm (ACOA), which is an innovative adaptive optimization algorithm, while also considering the system’s reliability. The primary objectives of the optimization problem are […]
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ELSO: A Blockchain-Based Technique for a Reliable and Secure Healthcare Information Exchange
Nowadays, healthcare takes a great attention from people and governments due to the emergence of new diseases and viruses. Health Information Exchange (HIE) allows doctors, clinicians, and healthcare facilities (HCF) to exchange and share patient records according to patient permission. Unfortunately, the HIE systems suffer from several challenges such as security, privacy, latency, throughput, and […]
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Hybrid Data-Driven and Knowledge-Based Predictive Maintenance Framework in the Context of Industry 4.0
The emergence of Industry 4.0 has heralded notable progress in manufacturing processes, utilizing sophisticated sensing and data analytics technologies to maximize efficiency. A vital component within this model is predictive maintenance, which is instrumental in ensuring the dependability and readiness of production systems. Nonetheless, the heterogeneous characteristics of industrial data present obstacles in realizing effective […]
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Can Teal practices increase employees’ work engagement?
Because engaged employees work with passion, in deep connection with their company and are innovative, they may drive their organization’s performance. Teal organizations, which implement original and inspiring ways of working, appear particularly favourable to create and support engagement in the long run. The aim of this paper is twofold: first, to study engagement drivers […]
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Building a positive corporate governance
Organizations are subject to a dual movement of evolution: in the short term, they must adapt to fluctuations of the economic, geopolitical, energy, health, situations and so on. In the long term, they must be part of major societal and environmental transformations. Corporate governance must assume this dual mission of strategic decision and social responsibility, […]
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What are the drivers of competence management?
Globalization and technological transformations emphasize the need for developing new skills and acting at the peak of one’s capacities. Competence is defined as the combination of external and individual resources to fulfill one’s job demands and contribute to the organization’s purpose. It corresponds to feeling effective and efficient in one’s actions. As such, competence is […]
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A Collaborative Real-Time Object Detection and Data Association Framework for Autonomous Robots Using Federated Graph Neural Network
Autonomous robotics require secure and decentralized decision-making systems that ensure data privacy and computational efficiency, especially in critical areas. Current centralized models or human input are associated with data breaches and security vulnerabilities. To counter these, we propose CoRODDA, a dedicated framework combining federated learning and graph neural networks. It enhances object detection and data […]
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Securing Autonomous Vehicles: Fundamentals, Challenges, and Perspectives
This paper introduces a comprehensive methodology aimed at enhancing security and immunity in automotive networks, placing a primary focus on the detection, prediction, and forecasting of errors in autonomous vehicles. Conventional approaches to vehicle cybersecurity often struggle to keep pace with evolving threats and provide effective error detection mechanisms. Our proposed methodology seeks to bridge […]
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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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A Framework for Building Point Cloud Cleaning, Plane Detection and Semantic Segmentation
This paper presents a framework to address the challenges involved in building point cloud cleaning, plane detection, and semantic segmentation, with the ultimate goal of enhancing building modeling. We focus in the cleaning stage on removing outliers from the acquired point cloud data by employing an adaptive threshold technique based on z-score measure. Following the […]
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Towards Hybrid Predictive Maintenance for Aircraft Engine: Embracing an Ontological-Data Approach
This article introduces a novel Remaining Useful Life (RUL) estimation method using Machine Learning techniques, guided by domain knowledge, and applied to a dataset of aircraft engines (C-MAPSS). Predictive maintenance, or prognostics, offers the opportunity to predict the lifespan of aircraft engines, thereby reducing costs, minimizing breakdowns, and ensuring their reliability. While existing solutions in […]
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