federated learning

Interpretable Federated Deep Learning with Double-Structured Orthogonal Matching Pursuit for Downlink Channel Estimation in Multi-RIS mm-Wave Massive-MIMO OFDM Systems

Introduction to artificial intelligence and machine learning

Artificial Intelligence-Based Alzheimer’s Disease Classification Using Brain MRI: A Review of Machine Learning, Deep Learning and Emerging Intelligent Approaches

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects memory, reasoning, language, and other cognitive functions. Early identification is important because structural brain changes may occur before severe clinical symptoms become evident. Magnetic Resonance Imaging (MRI) provides detailed an...

Optimal estimation in private distributed functional data analysis

We systematically investigate the preservation of differential privacy in functional data analysis, beginning with functional mean estimation and extending to varying coefficient model estimation. Our work introduces a distributed learning framework involving multiple servers, each responsible for collecting several sp...

Optimal estimation in private distributed functional data analysis

We systematically investigate the preservation of differential privacy in functional data analysis, beginning with functional mean estimation and extending to varying coefficient model estimation. Our work introduces a distributed learning framework involving multiple servers, each responsible for collecting several sp...

Federated learning for secure and privacy-preserving edge AI in smart cities’ wastewater management systems

The rapid evolution of smart cities has significantly transformed wastewater management systems through the integration of real-time monitoring, intelligent control, and data-driven decision-making. However, conventional centralized artificial intelligence (AI) frameworks face critical limitations, including data priva...

PrivFL-SMPC: Privacy-aware federated learning using secure multi-party computation for collaborative diabetes diagnosis in the cloud

Collaborative analytics across multiple healthcare institutions has become increasingly important for developing accurate predictive models while preserving patient privacy. Conventional centralized machine learning approaches require data sharing, creating significant privacy, security, and regulatory challenges. To a...

AI for Surface Water Quality Prediction: A Comprehensive Review

Artificial intelligence for surface water quality prediction has evolved rapidly from classical regression and ensemble learning toward deep sequence, graph-based, physics-informed, and representation-learning approaches, while a largely disconnected systems literature has matured around digital twins, edge intelligenc...

Communication-efficient Federated Transfer Learning for real-time intrusion detection in agricultural IoT systems

The rapid deployment of Agricultural Internet of Things (Ag-IoT) networks has introduced significant security challenges, mainly due to their limited computational resources and operation in remote environments. These constraints, combined with the critical nature of agricultural data and operations, make Ag-IoT system...

Fuzzy Delphi-based Assessment of Privacy-Aware Healthcare Monitoring Architectures in Remote and Resource-Constrained Areas

Intelligent healthcare monitoring in geographically isolated communities requires solutions that can operate under limited digital infrastructure while maintaining privacy, regulatory compatibility, and public confidence. Selecting an appropriate system architecture is therefore particularly important in areas where co...

Robust Federated Learning for Intensive Care Unit Mortality Prediction Across a Heterogeneous Hospital Network

Federated learning (FL) allows clinical institutions to train a shared model without pooling patient records, but itdoes not by itself prevent leakage through exchanged updates; because this study uses neither secure aggregationnor differential privacy, this exposure is discussed as a limitation. FL robustness under co...

Advanced Technologies for Sustainable and Effective Waste Management Systems

Rapid urbanization, industrialization, and population growth have led to a significant rise in wastewater and solid waste generation, posing critical environmental and public health challenges worldwide. Conventional waste management systems, largely designed for disposal, are no longer sufficient to meet the demands...