Results 151 to 160 of about 361,038 (279)

Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

open access: yesAdvanced Intelligent Systems, EarlyView.
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

Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing

open access: yesAdvanced Intelligent Systems, EarlyView.
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

Robot‐Assisted Doppler Optical Coherence Tomography for Intraoperative Evaluation of Microvascular Anastomoses

open access: yesAdvanced Intelligent Systems, EarlyView.
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

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

open access: yesAdvanced Intelligent Systems, EarlyView.
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

On plane polynomial vector fields and the Poincaré problem

open access: yesElectronic Journal of Differential Equations, 2002
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

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

open access: yesAdvanced Intelligent Systems, EarlyView.
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

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