Results 131 to 140 of about 1,079,927 (298)

On the mean squared error of the ridge estimator of the covariance and precision matrix

, 2017
W. N. Wieringen
semanticscholar   +1 more source

Low‐Angle Grain Boundaries and Re‐Segregation in Single‐Crystalline Ni‐Base Superalloys

Advanced Engineering Materials, EarlyView.
This work demonstrates that Re‐segregation at low‐angle grain boundaries (LAGBs) in Ni‐base superalloys is influenced by misorientation angle. Advanced microscopy and atom probe tomography reveal that higher misorientation angles increases Re‐segregation.
Alireza B. Parsa, Aparna Saksena, Alesander Kostka, Pascal Thome, Felicitas Scholz, Alexandre Mussi, Christoph Somsen, Baptiste Gault, Jan Frenzel, Gunther Eggeler   +9 more
wiley   +1 more source

Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in estimating the mean squared error of the least squares estimator in linear regression. [PDF]

PLoS One
Stolte M, Schreck N, Slynko A, Saadati M, Benner A, Rahnenführer J, Bommert A.   +6 more
europepmc   +1 more source

mean squared error of calibration

Citation: 'mean squared error of calibration' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.10151 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms ...
openaire   +1 more source

A Simplified Laminar Flow Model for the Pultrusion of Glass Fiber/Polyethylene Terephthalate Commingled Yarns

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, Nadège Bouchonneau, Christian Jochum, Donald Radford   +3 more
wiley   +1 more source

Karl Popper and the Mechanisms of Hydrogen Embrittlement

Advanced Engineering Materials, EarlyView.
Representation of the beginning of loss of ductility rather than embrittlement. Small concentrations of hydrogen in a diffusible form within iron are well‐established to harm the mechanical integrity of steels. There are theories that attempt to explain the pernicious role of hydrogen.
H. K. D. H. Bhadeshia
wiley   +1 more source

Real-World Implementation of a Neutrosophic Logarithmic Estimator for Population Mean Estimation under Stratified Random Sampling

Neutrosophic Sets and Systems
This paper addresses the problem of utilizing auxiliary information to estimate the population mean under neutrosophic stratified random sampling. Within the framework of neutrosophic statistics, we propose a neutrosophic combined logarithmic type ...
Deep Shikha, Shakti Prasad, Deepak Majhi, Housila P. Singh   +3 more
doaj   +1 more source

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

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

Leveraging generative neural networks for accurate, diverse, and robust nanoparticle design. [PDF]

Nanoscale Adv
Rahman T, Tahmid A, Arman SE, Ahmed T, Rakhy ZT, Das H, Rahman M, Azad AK, Wahadoszamen M, Habib A.   +9 more
europepmc   +1 more source