Results 241 to 250 of about 11,099,772 (293)
Investigating the Low‐Temperature Phase Stability of the Binary Ta–W System
Atomistic simulations show that the binary Ta–W system forms ordered intermetallic phases, B2‐TaW and D03‐TaW3, as 0 K ground states. Configurational entropy, however, lowers the free energy of the disordered bcc solid solution, which becomes the stable phase above about 400 K.
Klemens Lechner +7 more
wiley +1 more source
A Novel Approach to Estimate the Transition Temperature via Dynamic Nanoindentation
A new dynamic nanoindentation‐based method was developed that uses the stiffness ratio as an indicator of the elastic–plastic deformation contributions at different temperatures. The approach successfully identified transition temperatures in ferritic steel and distinguished them from continuously ductile austenitic steel.
Stefan Zeiler +4 more
wiley +1 more source
To enhance through‐thickness conductivity without sacrificing impregnation, large spherical graphite particles are intentionally employed in a low‐viscosity resin. Unlike finer conductive fillers, these particles remain outside the fiber bundles and accumulate in resin‐rich interlaminar regions during molding.
Keito Hosoe +6 more
wiley +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Journal of Management Analytics, 2021
Interpretive structural modeling (ISM) is an interactive process in which a malformed (bad structured) problem is structured into a comprehensive systematic model.
Alireza Amini, Moslem Alimohammadlou
openaire +1 more source
Interpretive structural modeling (ISM) is an interactive process in which a malformed (bad structured) problem is structured into a comprehensive systematic model.
Alireza Amini, Moslem Alimohammadlou
openaire +1 more source
2011
Structural equation modeling (SEM) is a multivariate statistical framework that is used to model complex relationships between directly and indirectly observed (latent) variables. SEM is a general framework that involves simultaneously solving systems of linear equations and encompasses other techniques such as regression, factor analysis, path ...
Catherine M, Stein +2 more
+5 more sources
Structural equation modeling (SEM) is a multivariate statistical framework that is used to model complex relationships between directly and indirectly observed (latent) variables. SEM is a general framework that involves simultaneously solving systems of linear equations and encompasses other techniques such as regression, factor analysis, path ...
Catherine M, Stein +2 more
+5 more sources
Structural Equation Modeling With Ωnyx
Structural Equation Modeling: A Multidisciplinary Journal, 2014Ωnyx is a free software environment for creating and estimating structural equation models (SEM). It provides a graphical user interface that facilitates an intuitive creation of models, and a powerful back end for performing maximum likelihood estimation of parameters. Path diagrams in Ωnyx can be exported to OpenMx, lavaan, and Mplus to allow an easy
von Oertzen, T. +2 more
openaire +2 more sources
Structural Equation Modeling with lavaan
2018This book presents an introduction to structural equation modeling (SEM) and facilitates the access of students and researchers in various scientific fields to this powerful statistical tool. It offers a didactic initiation to SEM as well as to the open-source software, lavaan, and the rich and comprehensive technical features it offers.
Gana, Kamel, Broc, Guillaume
openaire +2 more sources
Frequentist Model Averaging in Structural Equation Modelling
Psychometrika, 2019Model selection from a set of candidate models plays an important role in many structural equation modelling applications. However, traditional model selection methods introduce extra randomness that is not accounted for by post-model selection inference.
Jin, Shaobo, Ankargren, Sebastian
openaire +2 more sources
On the use of structural equation models for marketing modeling
International Journal of Research in Marketing, 2000We reflect on the role of structural equation modeling (SEM) in marketing modeling and managerial decision making. We discuss some benefits provided by SEM and alert marketing modelers to several recent developments in SEM in three areas: measurement analysis, analysis of cross-sectional data, and analysis of longitudinal data.
Steenkamp, J.E.B.M., Baumgartner, H.
openaire +2 more sources

