Results 61 to 70 of about 133,952 (267)

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, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Measurement Error Models with Nonconstant Covariance Matrices

Journal of Multivariate Analysis, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Arellano Valle, RB, Bolfarine, H, Gasco, L   +2 more
openaire   +5 more sources

Quantifying Adventitious Error in a Covariance Structure as a Random Effect [PDF]

Psychometrika, 2015
We present an approach to quantifying errors in covariance structures in which adventitious error, identified as the process underlying the discrepancy between the population and the structured model, is explicitly modeled as a random effect with a distribution, and the dispersion parameter of this distribution to be estimated gives a measure of ...
Wu, Hao, Browne, Michael W.
openaire   +2 more sources

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

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, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

High‐Temperature Nanoindentation of Metals: Assessing Thermal Drift, Frame Compliance, and Chemical Composition Effects on the Reported Mechanical Properties

Advanced Engineering Materials, EarlyView.
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova, Steffen Brinckmann, Ruth Schwaiger   +2 more
wiley   +1 more source

Evaluating Machine Learning Weather Models for Data Assimilation: Fundamental Limitations in Tangent Linear and Adjoint Properties

Geophysical Research Letters
Machine learning (ML) weather models like GraphCast and NeuralGCM show forecasting promise but face fundamental limitations for data assimilation (DA) integration.
Xiaoxu Tian, Daniel Holdaway, Daryl Kleist   +2 more
doaj   +1 more source

From Geometry to Function: Programmable Mechanical Response in 3D‐Printed Adipose‐Inspired Soft Metamaterials

Advanced Functional Materials, EarlyView.
Geometry‐driven design of soft cellular metamaterials is systematically investigated by combining experiments, finite element modeling, and statistical prediction. The study quantifies how unit cell geometry and material properties govern stiffness, instability, densification, and energy absorption.
Alice Berardo, Gianmarco Dolino, Damiano Coato, Paolo Gargiulo, Emanuele Luigi Carniel   +4 more
wiley   +1 more source

A New Data Assimilation Scheme: The Space-Expanded Ensemble Localization Kalman Filter

Advances in Meteorology, 2013
This study considers a new hybrid three-dimensional variational (3D-Var) and ensemble Kalman filter (EnKF) data assimilation (DA) method in a non-perfect-model framework, named space-expanded ensemble localization Kalman filter (SELKF).
Hongze Leng, Junqiang Song, Fengshun Lu, Xiaoqun Cao   +3 more
doaj   +1 more source

Comparing Background Error Covariance in WRF for Micro-Meteorological Simulations [PDF]

E3S Web of Conferences
Accurately representing background error covariances is crucial for data assimilation in numerical weather prediction models. This study compared the performance of the National Meteorological Center (NMC) and RandomCV methods for estimating background ...
Shu Hailong, Wang Yue, Guo Huichuang, Li Chaoqun, Song Zhen   +4 more
doaj   +1 more source

Quantum Error-Correcting Codes with a Covariant Encoding

Physical Review Letters
Given some group $G$ of logical gates, for instance the Clifford group, what are the quantum encodings for which these logical gates can be implemented by simple physical operations, described by some physical representation of $G$? We study this question by constructing a general form of such encoding maps. For instance, we recover that the $[[5,1,3]]$
Denys, Aurélie, Leverrier, Anthony
openaire   +4 more sources