Results 221 to 230 of about 267,596 (283)
Deep learning with fourier features for regressive flow field reconstruction from sparse sensor measurements. [PDF]
Nguyen PCH, Choi JB, Luu QT.
europepmc +1 more source
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai +10 more
wiley +1 more source
Assessing parameter identifiability of a hemodynamics PDE model using spectral surrogates and dimension reduction. [PDF]
Colebank MJ.
europepmc +1 more source
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Measurement of Form and Position Error of Small-Diameter Deep Holes Based on Collaboration Between a Lateral Confocal Displacement Sensor and Helical Scanning. [PDF]
Liu Y, Yu D, Du H, Chen T.
europepmc +1 more source
Inspired by the multi‐tissue architecture of the human fingertip dermis (A), this work introduces a mixture design using three PolyJet materials (AC/TM/GM) to expand the achievable elastomer property space (B). An inverse design pipeline (i‐Tac) is developed to map target optical/mechanical requirements to optimal material compositions (C), enabling ...
Wen Fan, Dandan Zhang
wiley +1 more source
Analysis of inverse problem for pseudo-hyperbolic equation under periodic boundary condition. [PDF]
Bağlan İ +4 more
europepmc +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Quantum speedup for nonreversible Markov chains. [PDF]
Claudon B, Piquemal JP, Monmarché P.
europepmc +1 more source

