A Lightweight Hybrid Authentication and Key Agreement Protocol for Decentralized Device-to-Device Communication with Post-Quantum Confidentiality. [PDF]
Savón-Berenguer A +3 more
europepmc +1 more source
Efficient and Secure Certificateless Proxy Re-Encryption
Ya Liu, Hongbing Wang, Chunlu Wang
openaire +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Blockchain-enabled data management system of internet of medical things. [PDF]
Xu T, Zhu G, Wei Q, Liu Y, Zhao L.
europepmc +1 more source
ABSTRACT Conceptual process design combines discrete configuration choices with continuous operating decisions, often yielding difficult mixed‐integer nonlinear or simulation‐based optimization problems. This work presents an exploratory computational assessment of Ising‐based solvers, simulated annealing, quantum annealing, and entropy computing, as ...
Yirang Park, David E. Bernal Neira
wiley +1 more source
A fully homomorphic encryption federated learning architecture for privacy preserving in industrial internet of things. [PDF]
Subhedar S, Parasar D.
europepmc +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Design of a multi-layered privacy-preserving architecture for secure medical data exchange in cloud environments. [PDF]
Muthuvel S, Priya S, Sampath Kumar K.
europepmc +1 more source
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Machine learning-driven adaptive parameter selection for homomorphic encryption in edge computing. [PDF]
Bouabidi HE +3 more
europepmc +1 more source

