Results 151 to 160 of about 361,038 (279)
A data‐efficient artificial intelligence‐assisted framework, which integrates experimental data with machine learning, is developed for the design of bimodal networked dielectric elastomers (DEs) as advanced artificial muscles. It adopts neural networks to predict DEs’ mechanical properties and support vector machines to classify electromechanical ...
Ofoq Normahmedov +8 more
wiley +1 more source
On the Optimal File Size of Capacity-Achieving Byzantine-Resistant Private Information Retrieval Schemes. [PDF]
Kruglik S, Kiah HM, Dau SH, Wang H.
europepmc +1 more source
Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing
This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang +6 more
wiley +1 more source
This work presents a robot‐assisted Doppler optical coherence tomography system for autonomous, wide‐field intraoperative assessment of microvascular anastomoses. Machine‐vision–guided probe positioning and adaptive scan planning enable three‐dimensional structural and hemodynamic imaging over extended vessel segments.
Xiaochen Li +10 more
wiley +1 more source
A Temperature Measurement and System Identification Method for Confined Cavity Explosions Based on an Improved Type C Thermocouple Sensor. [PDF]
Niu Z, Zhang J, Kong D, Jiang H, Kou M.
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
Direct Products for the Hamiltonian Density Property. [PDF]
Andrist RB, Huang G.
europepmc +1 more source
On plane polynomial vector fields and the Poincaré problem
Summary: We address the Poincaré problem, on plane polynomial vector fields, under some conditions on the nature of the singularities of invariant curves. Our main idea consists in transforming a given vector field of degree \(m\) into another one of degree at most \(m+1\) having its invariant curves in projective quasi-generic position. This allows us
openaire +3 more sources
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
High-Accuracy Wave Direction Estimation Using Kalman Fusion of Interferometric Measurements and Energy Field Reconstruction. [PDF]
Wang C, Li X, Xue L.
europepmc +1 more source

