federated learning

Understanding Federated Learning Through the Lens of Mechanism Design: The Role of Data Heterogeneity

Physics-Encoded Learning for DAS-Based Flow Allocation: A Comparative Study

Abstract Distributed Acoustic Sensing (DAS) has become an important surveillance technology for injection and production wells because it enables dense acoustic measurements along the wellbore using fiber-optic sensing channels. Each DAS channel behaves as a distributed strain-sensitive acoustic measurement over a fini...

EL-RAKHAWI PROTOCOL FOR PLANETARY PREVENTIVE HEALTH AND GLOBAL PANDEMIC SECURITY A Technically Rigorous Framework for Early Warning and Autonomous Response via Decentralized Genomic Surveillance, Predictive AI, and Distributed Biomanufacturing of Vaccines and Therapeutics

EL-RAKHAWI PROTOCOL FOR PLANETARY PREVENTIVE HEALTH V2.0Author: Dr. Mohamed Kamal Arafa El-Rakhawi | DOI: 10.5281/zenodo.23353602 A revolutionary closed-loop framework transforming pandemic response from reactive crisis management to proactive, autonomous prevention. Integrates six domains: (1) Decentralized genomic su...

Mapping Successful AI Application in Well Delivery to Domain Knowledge, SME Capacity in Operators and Their Suppliers

Abstract Major operators and service companies sustain deep expertise by funding robust hiring and training to develop in-house Subject Matter Experts (SMEs). Conversely, smaller players lack the capital for permanent specialist benches. Their fluctuating needs and limited funding force them to purchase knowledge from...

A privacy-preserving federated deep learning framework for real-time fraud detection in decentralized financial systems

The rapid growth of decentralized financial systems has introduced sophisticated fraud that conventional detection methods struggle to identify, due to fragmented data, strict privacy regulations, and the need for real-time response. This study proposes Federated Differentially Private Fraud Detection (FedDP-FD), a pri...

Artificial Intelligence and Data Science Applications in Anaerobic Digestion: Monitoring and Optimization Strategies

Abstract Anaerobic digestion (AD) is a significant biological process that transforms organic waste into renewable biogas and nutrient-dense digestate. This can be returned as fertilizer, which promotes waste management and renewable energy production. However, typical monitoring relies on offline laboratory measuremen...

FedCuraLM: Reliability-Calibrated and Resource-Aware Label Auditing with Small Language Models for Non-IID Federated AIoT

Federated Artificial Intelligence of Things (AIoT) activity-recognition systems learn from decentralized wearable and smart-home records with potentially incorrect labels, non-IID client distributions, and unequal edge-device resources.Our objective is to improve downstream learning from these labels while limiting har...

BANAR: Self-feedback stealthy backdoor attack in federated learning

Semantic communication for the internet of underwater things: Architectures, applications, challenges, and future directions

The Internet of Underwater Things (IoUT) supports marine sensing, environmental monitoring, subsea inspection, and autonomous underwater operations. However, IoUT communication is constrained by limited bandwidth, long propagation delay, time-varying underwater channels, intermittent connectivity, and strict energy bud...

AI‐Driven Multimodal Fusion for Predictive Disease Modeling and Clinical Insight Generation

Data-driven approaches in disease modeling have been one of the important criteria where artificial intelligence (AI), machine learning (ML), and big data analytics are some of the latest technologies for predicting and managing the different types of diseases. For these methodologies, diverse datasets have been integr...

Blockchain-Driven FL and Big Data Mining Concepts with Spatial Attention-Based Adaptive Deep Learning Model for Smart Tourism

In smart tourism planning, tourism-related devices are used to maintain tourist data and manage hotel room bookings. Smart tour management using deep learning models has overfitting issues due to the complexity of large-scale data. The major issues in traditional tourism sectors are data privacy, interoperability, and...

FedCardioGuard: Quality- and Uncertainty-Aware Personalized Federated Learning with Rare-Class Generalization Audits for ECG Classification