The Cognitive Federated Graph Learning (CFGL) framework is introduced to jointly optimise three interdependent resources in cognitive radio networks: (i) frequency channel allocation for secondary-user transmissions, (ii) routing paths for multi-hop packet traversal, and (iii) transmit-power budgets as determined by pe...
FLZT-IDS (Federated Learning with Zero-Trust for Intrusion Detection in IoT) employs gradient-deviation monitoring to mitigate the effects of heterogeneous client updates, while Graph Neural Networks and an Attention-based BiLSTM capture relational and temporal attack patterns.
Santosh Kumar Banbhrani, Chengyongxiao Wei, Muhammad Asad· Electronics· 0 citations
The Federated Logistics Operations Dataset (FLOD) is a large-scale real-world dataset designed to support research on distributed logistics optimization, predictive modeling, and industrial Internet of Things (IIoT) analytics. The dataset consists of 253,020 operational records collected from geographically distributed...
UK Healthcare Logistics Research Consortium· Zenodo (CERN European Organi...· 0 citations
The COVID-19 pandemic exposed persistent weaknesses in health-data interoperability, cybersecurity, provenance, cross-organizational governance, and continuity of digital care. This short communication presents an updated focused narrative synthesis and a five-layer governance framework for integrating blockchain and t...
G. Di Grezia, Alfredo Clemente, S. Dugheri et al.· Bioengineering· 0 citations
The chapter discusses how blockchain-based verifiable credentialing, federated learning, and immersive metaverse environments converge as a single architectural solution to three structural failures in modern digital education: centralised credential vulnerability, privacy personalisation trade-off, and lack of experie...
Anshul Ojha· Advances in computational in...· 0 citations
The rapid advancement of smart textiles, flexible electronics, Edge Artificial Intelligence, and Tiny Machine Learningis transforming wearable healthcare systems from passive sensing platforms into intelligent, real-time health monitoring ecosystems. This chapter explores the integration of e-textiles, textile-based bi...
Gaurav Kumar, Shikha Sharma· Advances in computational in...· 0 citations
The El-Rakhawi Grand Theory of Regenerative Cybernetic Infrastructure and Sovereign Computing (DOI: 10.5281/zenodo.23232575) reimagines Information Technology as a **decentralized, edge-intelligent planetary nervous system** operating in cybernetic harmony with human dignity and ecological boundaries. Built on six pill...
mohamed kamal arafa el-rakhawi· Zenodo (CERN European Organi...· 0 citations
Artificial Intelligence has emerged as a pivotal advancement in textile systems, integrating intelligent sensing, wearable computing, IoT, and machine learning applications on smart fabrics for real-time monitoring of object behavior through predictive analytics. The primary areas of application identified in the inves...
Ganesh P. Dawange, P. William· Advances in computational in...· 0 citations
The El-Rakhawi Theory of Harmonious Algorithmic Jurisprudence and Sovereign Legal Governance (DOI: 10.5281/zenodo.23239861) bridges Japanese legal AI precision with mathematical certainty, transforming algorithmic jurisprudence from probabilistic simulation into a verifiable cognitive infrastructure. Built on five pill...
mohamed kamal arafa el-rakhawi· Zenodo (CERN European Organi...· 0 citations
The evolution of flexible and stretchable electronics has reshaped traditional textiles into intelligent wearable devices that have benefits such as sensing, communicating, computing, and making decisions in real-time. Currently, e-textile technologies are still disparate, lacking integration of the smart features of e...
Sumit Kumar Kapoor· Advances in computational in...· 0 citations
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
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