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...
Graziella Di Grezia, Alfredo Clemente, Stefano 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
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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
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...
Asst Prof. Sunita Totade, Gauri B. Thakur, Neha C. Raut· International Journal of Adv...· 0 citations
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...
appunuarni1975-spec· Zenodo (CERN European Organi...· 0 citations
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...
Vishal Barot, Abu Sarwar Zamani, Ankit Modi et al.· Advances in computational in...· 0 citations
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026