Results 181 to 190 of about 1,780,354 (311)
Data-driven learning of structure augments quantitative prediction of biological responses. [PDF]
PLoS Comput BiolHa Y +9 more
europepmc +1 more source
Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
The effects of data-driven learning activities on EFL learners' writing development. [PDF]
Springerplus, 2016 Luo Q.
europepmc +1 more source
Advanced Engineering Materials, EarlyView.Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source
Ontology Driven Web Extraction from Semi-structured and Unstructured Data for B2B Market Analysis
, 2009 The Market Blended Insight project1 has the objective of improving the UK business to business marketing performance using the semantic web technologies.
Zuo, Landong +2 more
core
Systematic Data-Driven Continual Self-Learning.
, 2023 Datadrivna och självlärande system besitter en mycket stor outnyttjad potential för att förbättra automatisk kontroll och automatiskt beslutsfattande i komplexa industriella system. I mindre skala så har dessa metoder visats ha en viss potential rörande förbättrad prestanda för automatisk justering av komplexa distribuerande system.
openaire +2 more sources
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Data-Driven Learning in High-Resolution Activity Sampling From Patients With Bipolar Depression: Mixed-Methods Study. [PDF]
JMIR Ment Health, 2018 Rohani DA +4 more
europepmc +1 more source
Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
Advanced Engineering Materials, EarlyView.We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source