federated learning

Artificial Intelligence in Cloud Computing: A Systematic Literature Review of Applications, Challenges, and Future Directions

The integration of Artificial Intelligence (AI) with cloud computing has emerged as an important research area for developing scalable, intelligent, and automated computing environments. Cloud computing provides on-demand access to computing resources, storage, networking, and software services, while AI and Machine Le...

appunuarni1975-spec/FedIoMT-RPM: FedIoMT-RPM v3.1: Lightweight adaptive split federated learning for patient-independent ECG arrhythmia classification

Code and results for the revised manuscript "Lightweight adaptive split federated learning for patient-independent ECG arrhythmia classification" (Scientific Reports, second revision). Changes since v3.0: All methods re-run with seeds 0 to 5 (previously 0 to 2) under the inter-patient DS1/DS2 protocol of the MIT-BIH Ar...

Federated and Distributed Learning for Secure and Explainable Cyber Defense

This chapter examines federated and distributed learning as a foundation for secure, explainable cyber defense. Centralized AI models create privacy risks, single points of failure, and opaque decisions that resist interpretation. The authors combine federated learning with explainable AI techniques, including SHAP, LI...

ARTIFICIAL INTELLIGENCE IN FINANCIAL STATEMENT FRAUD DETECTION: A CRITICAL SYNTHESIS OF EMERGING TRENDS, METHODOLOGIES, AND FUTURE DIRECTIONS FOR U.S. PUBLICLY TRADED COMPANIES

Financial statement fraud causes systemic damage to U.S. capital markets, investor confidence, and the credibility of public company disclosures. Artificial intelligence (AI) offers promising new detection capabilities, yet its evidence base and operational readiness remain unevenly developed across the literature. Thi...

FFT-GA-BC: a fused federated transformer genetic algorithm framework with blockchain-secured, differentially private, homomorphically encrypted aggregation for mutation, phenotype, and binary-allele analysis

Federated learning enables cross-institutional clinical-genetics analytics without sharing raw patient data; yet, no existing framework integrates the full cryptographic stack–differential privacy, homomorphic encryption, and blockchain auditing—required for regulatory deployment. Here, we present FFT-GA-BC, a secure-b...

A Study on Trustworthy Aggregation Mechanisms for Blockchain-Based Federated Learning

To investigate how blockchain technology can improve the reliability, speed and legality of federated learning, this paper concentrates on the process of model combination in federated learning. By dealing with the problems of single vulnerable points and insufficient trust in centralized combination, the paper compreh...

CONCRETE, SCIENTIFIC AND INTEGRATIVE EDUCATION

CONCRETE, SCIENTIFIC AND INTEGRATIVE EDUCATIONA Proposal for Reorganizing Learning Based on Reality, Investigation, Demonstration, Science, Territory, and the Integration of Knowledge Author: Cláudio Vicente da SilvaLocation: Londrina, Paraná, BrazilDate: October 8, 2026 DESCRIPTION This work presents a proposal for th...

A federated learning framework for Non-IID data : data feature optimization and personalization strategy

medchain: reputation-driven committee-consensus federated learning for trustworthy healthcare blockchains

medchain v0.1.35 (2026-10-08) First public release. medchain implements reputation-driven, committee-consensus federated learning for trustworthy healthcare blockchains. This release finalises the v0.1.34 freeze candidate by completing the author and repository metadata and adding the release date required for archivin...

Inclusive Learning in Decentralized Metaverse Ecosystems

This chapter discusses ways decentralized metaverse classrooms promote inclusive, collaborative and learner-centered education at the same time bringing out challenges of accessibility, privacy, governance and equity. Based on contemporary literature on immersive learning, digital transformation and decentralized educa...

Systemic privacy risks of personal data exposure through conversational large language model agents

A conflict-of-evidence analysis reveals that privacy protections are particularly effective in structured environments with low risks, or with consumers actively responsible for maintaining them, but fail to adequately protect privacy in high-stakes domains without human control, technical safeguards, and legal liabili...

Early Diagnosis of Chronic Diseases Using AI-Enabled Wearable Devices

Chronic diseases such as cardiovascular disorders, diabetes, respiratory illnesses, neurological conditions, and sleep disorders require early diagnosis to improve patient outcomes and reduce healthcare costs. Recent advances in Artificial Intelligence (AI), wearable sensors, and the Internet of Medical Things (IoMT) h...