Results 191 to 200 of about 1,117,093 (260)
A Perspective on Interactive Theorem Provers in Physics
Into an interactive theorem provers (ITPs), one can write mathematical definitions, theorems and proofs, and the correctness of those results is automatically checked. This perspective goes over the best usage of ITPs within physics and motivates the open‐source community run project PhysLean, the aim of which is to be a library for digitalized physics
Joseph Tooby‐Smith
wiley +1 more source
Intelligent Breathing Electronic Skin Inspired by Nepenthes for Active Sweat Management, Multimodal Sensing and High-Fidelity Electromyographic Teleoperation Using Machine Learning. [PDF]
Li Y +8 more
europepmc +1 more source
An on‐demand ultra‐reconfigurable intelligent vision system with hierarchical reconfigurability from device to system levels is demonstrated. Through co‐design of a multi‐paradigm device, reconfigurable circuits, and adaptive system architecture/algorithms, the system enables seamless switching among spiking, non‐spiking, neuromorphic imaging (NI), and
Biyi Jiang +7 more
wiley +1 more source
Multi-task meta-initialized DQN for fast adaptation to unseen slicing tasks in O-RAN. [PDF]
Zeng B, Niu X.
europepmc +1 more source
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas +6 more
wiley +1 more source
AI-enabled cybersecurity framework for future 5G wireless infrastructures. [PDF]
Alam A, Umer A, Ullah I, Alsayat A.
europepmc +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Hierarchical Model Selection and Control for Latency-Energy Optimization in MEC-Assisted Vehicular Networks. [PDF]
Song I, Kang S, Ros S, Kim S.
europepmc +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source

