Sentence examples for characterization models are from inspiring English sources

Current swell and shrinkage characterization models are limited by both the lack of standardized tests and tests that employ volume changes in uniaxial direction.

A simple process-based terrain characterization model was developed to identify the occurrence of soils over a complex landscape.

In this paper, a novel and effective multi-dimensional quantitative characterization model was successfully established to investigate the synergistic excretion and conduct pharmacokinetic analysis of four bioactive ingredients in Radix Gentianae Macrophyllae by using HPLC-DAD and ATLD with aid of region selection.

Detailed sequence analysis and biophysical characterization of the structural models are used to predict membrane interaction mechanisms previously described for other FYVE domains and their subtle variations as well as novel mechanisms that seem to be specific to plants.

The constraints for characterization and modelling are discussed and the various protection measures for improved system-level ESD robustness are presented.

In addition, the reported results show that electrochemical measurements in molten oxides coupled with mass-transfer models are complementary characterization tools for oxygen chemistry.

Because composite reactive barriers are expected to operate for months or years, purely experimental characterization is not practical and models are needed to optimize the configurations and to confidently extrapolate experimental data.

Given their poor characterization in molecular terms, biophysical models are very useful to understand the systems level behaviour but often cannot provide a clear connection to a molecular mechanism.

A set of geometric-mechanical models are developed with characterization of the fibers/yarns and fabrics for available inputs, which make it feasible for practical applications.

Parametric models are advocated for characterization of the dynamics of fluidized beds when, for various reasons, long data records are not available or when the quality of the recorded signal is poor.

LCA regression models are used for characterization and validation.