24 hasil untuk "Mehdi Adda"
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Artikel Jurnal
GridSecSim: A Hybrid Cyber-Physical Co-Simulation Platform Integrating GridLAB-D and NS-3 for Cyberattack Simulation and Real-Time Intrusion Detection in Smart Grids
The convergence of physical and cyber domains in smart electrical grids exposes Advanced Metering Infrastructure (AMI) to sophisticated cyberattacks with severe potential operational consequences. Evaluating detection mechanisms under realistic, reproducible conditions remains challenging: purely…
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HEAD Metamodel: Hierarchical, Extensible, Advanced, and Dynamic Access Control Metamodel for Dynamic and Heterogeneous Structures
The substantial advancements in information technologies have brought unprecedented concepts and challenges to provide solutions and integrate advanced and self-ruling systems in critical and heterogeneous structures. The new generation of networking environments (e.g., the Internet of Things…
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HEAD Access Control Metamodel: Distinct Design, Advanced Features, and New Opportunities
Access control (AC) policies are a set of rules administering decisions in systems and they are increasingly used for implementing flexible and adaptive systems to control access in today’s internet services, networks, security systems, and others. The emergence of the current generation of…
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From Data Silos to Health Records Without Borders: A Systematic Survey on Patient-Centered Data Interoperability
The widespread use of electronic health records (EHRs) and healthcare information systems (HISs) has led to isolated data silos across healthcare providers, and current interoperability standards like FHIR cannot address some scenarios. For instance, it cannot retrieve patients’ health records if…
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On Predictive Maintenance in Industry 4.0: Overview, Models, and Challenges
In the era of the fourth industrial revolution, several concepts have arisen in parallel with this new revolution, such as predictive maintenance, which today plays a key role in sustainable manufacturing and production systems by introducing a digital version of machine maintenance. The data…
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Artikel Jurnal
Machine learning-based state of charge estimation: A comparison between CatBoost model and C-BLSTM-AE model
The State of Charge (SOC) is a key metric within a Lithium-ion battery management system (BMS). Accurate SOC estimation is essential for enhancing battery longevity and ensuring user safety, making it a critical component of an effective BMS. Although SOC estimation has become an active research…
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Survey on Knowledge Representation Models in Healthcare
Knowledge representation models that aim to present data in a structured and comprehensible manner have gained popularity as a research focus in the pursuit of achieving human-level intelligence. Humans possess the ability to understand, reason and interpret knowledge. They acquire knowledge…
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Machine Learning and Smart Devices for Diabetes Management: Systematic Review
(1) Background: The use of smart devices to better manage diabetes has increased significantly in recent years. These technologies have been introduced in order to make life easier for patients with diabetes by allowing better control of the stability of blood sugar levels and anticipating the…
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Artikel Jurnal
Toward smart railway maintenance: AI-enhanced Non-Destructive Evaluation using Vision Transformers and CNNs for fastener defect detection
Predictive health management and maintenance of transport infrastructure are critical for preventing accidents and service disruptions. Applying Non-Destructive Evaluation (NDE) and imaging techniques is essential for identifying irregularities without causing harm. This research utilizes…
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Smart Defect Detection in Aero-Engines: Evaluating Transfer Learning with VGG19 and Data-Efficient Image Transformer Models
This study explores the impact of transfer learning on enhancing deep learning models for detecting defects in aero-engine components. We focused on metrics such as accuracy, precision, recall, and loss to compare the performance of models VGG19 and DeiT (data-efficient image transformer)…
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Optimizing Virtual Power Plant Management: A Novel MILP Algorithm to Minimize Levelized Cost of Energy, Technical Losses, and Greenhouse Gas Emissions
The modern energy landscape is undergoing a significant transformation towards cleaner, decentralized energy sources. This change is driven by environmental and sustainability needs, causing traditional centralized electric grids, which rely heavily on fossil fuels, to be replaced by a diverse…
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Reviewing Federated Machine Learning and Its Use in Diseases Prediction
Machine learning (ML) has succeeded in improving our daily routines by enabling automation and improved decision making in a variety of industries such as healthcare, finance, and transportation, resulting in increased efficiency and production. However, the development and widespread use of this…
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Artikel Jurnal
HP_FLAP: homomorphic and polymorphic federated learning aggregation of parameters framework
Abstract Protecting user privacy is essential in machine learning research, especially in the context of data collection. Federated learning (FL), which trains models across decentralized devices without sharing raw data, has emerged as a promising solution. However, FL is still vulnerable to…
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Artikel Jurnal
From data to medical context: the power of categorization in healthcare
In the rapidly evolving healthcare domain, the ability to structure and interpret contextual medical data is crucial for delivering personalized and efficient patient care. While many existing studies attempt to define medical context through diverse categorizations, they often lack completeness or…
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Developing Contextual Ontology for Chronic Diseases: AI-Enhanced Extension and Prediction in an Asthma Case Study
The growing complexity and interdependence of healthcare data, especially for chronic diseases such as asthma, demand innovative approaches for effective knowledge representation. This study introduces a general contextual ontology model for chronic diseases, extended specifically to asthma…
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Centralized vs. Decentralized Electric Grid Resilience Analysis Using Leontief’s Input–Output Model
Escalating events such as extreme weather conditions, geopolitical incidents, acts of war, cyberattacks, and the intermittence of renewable energy resources pose substantial challenges to the functionality of global electric grids. Consequently, research on enhancing the resilience of electric…
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Smart Wearables for the Detection of Occupational Physical Fatigue: A Literature Review
Today’s world is changing dramatically due to the influence of various factors. Whether due to the rapid development of technological tools, advances in telecommunication methods, global economic and social events, or other reasons, almost everything is changing. As a result, the concepts of a…
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Comparison between Blockchain P2P Energy Trading and Conventional Incentive Mechanisms for Distributed Energy Resources—A Rural Microgrid Use Case Study
Peer-to-Peer (P2P) energy trading is a new financial mechanism that can be adopted to incentivize the development of distributed energy resources (DERs), by promoting the selling of excess energy to other peers on the network at a negotiated rate. Current incentive programs, such as net metering…
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Dynamic Charging Optimization Algorithm for Electric Vehicles to Mitigate Grid Power Peaks
The rapid proliferation of electric vehicles (EVs) presents both opportunities and challenges for the electrical grid. While EVs offer a promising avenue for reducing greenhouse gas emissions and dependence on fossil fuels, their uncoordinated charging behavior can strain grid infrastructure, thus…
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Artikel Jurnal Teks lengkap
Smart Wearables for the Detection of Cardiovascular Diseases: A Systematic Literature Review
Background: The advancement of information and communication technologies and the growing power of artificial intelligence are successfully transforming a number of concepts that are important to our daily lives. Many sectors, including education, healthcare, industry, and others, are benefiting…