Results 181 to 190 of about 151,967 (341)
The use of geometric uncertainty data in aero engine structural analysis and design
, 2013 A gas turbine disc has three critical regions for which lifing calculations are essential: the assembly holes or weld areas, the hub region, and the blade-disc attachment area.
Deshpande, Aditya S.
core
Advanced Science, EarlyView.An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen +7 more
wiley +1 more source
Advanced Science, EarlyView.A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou +3 more
wiley +1 more source
Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors
Advanced Science, EarlyView.Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu +4 more
wiley +1 more source
Advanced Science, EarlyView.A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu +5 more
wiley +1 more source
Loss function influence on hyperparameter optimization for observational healthcare prediction models. [PDF]
J Am Med Inform AssocVereijken F +3 more
europepmc +1 more source
A Generative Neuro‐Symbolic AI for Protein Sequence Design
Advanced Science, EarlyView.We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
Dynamic Modulus Prediction of Fiber-Reinforced Asphalt Mixtures Based on XGBoost Optimized by an Improved Black-Winged Kite Algorithm. [PDF]
Materials (Basel)Xu X, Pan S, Zhou C, Ge W, Wu X.
europepmc +1 more source
StackingNet: Collective Inference Across Independent AI Foundation Models
Advanced Science, EarlyView.ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li +4 more
wiley +1 more source
Explainable Clinical Decision Support for Metabolic Index Prediction in Gout Patients Using GA-Optimized Ensemble Learning Models. [PDF]
Diagnostics (Basel)Bal F, Cüre O.
europepmc +1 more source