A5032138906- Microgrid Control and Optimization
- Photovoltaic System Optimization Techniques
- Smart Grid Energy Management
- Wind Turbine Control Systems
- Digital Transformation in Industry
- Big Data and Business Intelligence
- User Authentication and Security Systems
- Hybrid Renewable Energy Systems
- Solar Radiation and Photovoltaics
- Quality and Supply Management
- IoT and Edge/Fog Computing
- COVID-19 diagnosis using AI
- Multilevel Inverters and Converters
- Brain Tumor Detection and Classification
- Energy Efficient Wireless Sensor Networks
- Advanced Battery Technologies Research
- Security in Wireless Sensor Networks
- Advanced Authentication Protocols Security
- Optimal Power Flow Distribution
- Frequency Control in Power Systems
- Antenna Design and Analysis
- Solar Thermal and Photovoltaic Systems
- Power Systems and Renewable Energy
- BIM and Construction Integration
- Blockchain Technology Applications and Security
Moroccan Foundation for Advanced Science, Innovation and Research
2022-2024
École Supérieure de Gestion et des Sciences de l'Informatique
2024
Mohammed V University
2024
National School of Mineral Industry
2022
University of Naples Federico II
2022
Federico II University Hospital
2022
Hassan II Academy of Science and Technology
2022
SMART Reading
2020
École Marocaine des Sciences de l'Ingénieur
2018
Mohamed I University
2009
In the realm of medicine, artificial intelligence (AI) has emerged as a transformative force, harnessing power to convert raw data into meaningful insights. Rather than supplanting discernment physicians, AI serves an unprecedented enabler, equipping them with unimaginable tools. Its far-reaching applications encompass drug discovery, disease diagnosis, prognosis, treatment optimization, and outcome prediction. This technological revolution owes much prowess machine learning algorithms,...
This paper presents a dual-layer approach for managing and controlling an AC Microgrid (MG). The MG integrates Photovoltaic System (PVS), Wind Turbine (WTS), Battery Storage (BSS), all interconnected with the utility grid. is structured into Control Layer (CL) Energy Management (EMS-L). CL proposes efficient model coupled system control, ensuring high power quality microgrid. employs Particle Swarm Optimization (PSO) algorithm to optimize set point tracking performance. Simultaneously, EMS-L...
In response to the escalating global energy crisis, motivation for this research has been derived from need sustainable and efficient solutions. A gap in existing renewable systems, particularly terms of stability efficiency under variable environmental conditions, recognized, leading introduction a novel hybrid system that combines photovoltaic (PV) wind energy. The innovation study lies methodological approach adopted, integrating dynamic modeling with sophisticated control mechanism. This...
Background: This study evaluates the performance of a vision transformer (ViT) model, ViT-b16, in classifying ischemic stroke cases from Moroccan MRI scans and compares it to Visual Geometry Group 16 (VGG-16) model used prior study. Methods: A dataset 342 scans, categorized into ‘Normal’ ’Stroke’ classes, underwent preprocessing using TensorFlow’s tf.data API. Results: The ViT-b16 was trained evaluated, yielding an impressive accuracy 97.59%, surpassing VGG-16 model’s 90% accuracy....
This paper proposes a new contribution in the field of optimizing control techniques for wind systems to enhance quality energy produced grid. Although Sliding Mode technique, whether classical or involving use artificial intelligence, has shown interesting results, its main drawback lies oscillation phenomenon commonly referred as "chattering." affects accuracy and robustness system, well parametric variation system. In this work, we propose solution that combines two nonlinear based on...
The integration of renewable sources and energy storage in residential microgrids offers efficiency emission reduction potential. Effective management is vital for optimizing resources lowering costs. In this paper, we propose a novel approach, combining the imperialist competitive algorithm (ICA) with particle swarm optimization (PSO) as ICA-PSO to enhance management. proposed system operates an offline mode, anticipating data upcoming 24 h, including consumption predictions, tariff rates,...
To propel us toward a greener and more resilient future, it is imperative that we adopt renewable sources implement innovative sustainable solutions in response to the escalating energy crisis. Thus, energies have emerged as viable solution global crisis, with photovoltaic being one of prominent this regard. This paper represents significant step desired direction by focusing on detailed, comprehensive dynamic modeling efficient control (PV) systems grid-connected sources. The ultimate goal...
This work demonstrates that a control strategy like MPC optimized by the PSO algorithm is more optimal than traditional controllers PI controllers. Comparing active power or torque electromagnetic obtained through these strategies to reference provided DFIG, it was observed this plan can significantly enhance system's productivity. Through constant modification of regulation, maintain operation even under varying wind conditions. not only ensuring maximum generation but also reduces impact...
The Internet of Things (IoT) concept is tremendously applied in our current daily lives. IoT involves Radio Frequency Identification (RFID) as a part the infrastructure that helps with data gathering from different types sensors. In general, security worries have increased significantly these technologies become more common. For this reason, manifold realizations and studies been carried out to address matter. work, we tried provide thorough analysis cryptography-based solutions for RFID...
This study presents a comprehensive exploration of deep learning models for precise brain ischemic stroke classification using medical data from Morocco. Following the OSEMN approach, our methodology leverages transfer with VGG-16 architecture and employs augmentation techniques to enhance model performance. Our developed achieved remarkable validation accuracy 90%, surpassing alternative state-of-theart (ResNet50: 87.0%, InceptionV3: 82.0%, VGG-19: 81.0%). Notably, all were rigorously...