Results 141 to 150 of about 7,849 (183)

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

open access: yesAdvanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

open access: yesAdvanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song   +6 more
wiley   +1 more source

Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy

open access: yesAdvanced Intelligent Discovery, EarlyView.
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang   +9 more
wiley   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

open access: yesAdvanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi   +5 more
wiley   +1 more source

“It Is Much Safer to Be Sparse than Connected”: Safe Control of Robotic Swarm Density Dynamics with PDE Optimization with State Constraints

open access: yesAdvanced Intelligent Systems, EarlyView.
This paper proposes a novel control framework to ensure safety of a robotic swarm. A feedback optimization controller is capable of driving the swarm toward a target density while keeping risk‐zone exposure below a safety threshold. Theory and experiments show how safety is more effectively achieved for sparsely connected swarms.
Longchen Niu, Gennaro Notomista
wiley   +1 more source

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