• Journal of the Korean Electrochemical Society
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• v.23 no.4
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• pp.81-89
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• 2020

To understand the performance of the electrochemical device, the analysis of the mechanism of ionic conduction is important. However, due to the ionic interaction in the electrolyte and the complexity of the electrolyte structure, a clear analysis method of the ion conduction mechanism has not been proposed. Instead, a variety of mathematical models have been devised to explain the mechanism of ion conduction, and this review introduces the Arrhenius and Vogel-Tammann-Fulcher (VTF) model. In general, the above two mathematical models are used to describe the temperature dependence of the transport properties of electrolytes such as ionic conductivity, diffusion coefficient, and viscosity, and a suitable model can be determined through the linearity of the graph consisting of the logarithm of the moving property and the reciprocal of the temperature. Currently, many electrolyte studies are evaluating the suitability of the above two models for electrolytes by varying the composition and temperature range, and the ion conduction mechanism analysis and activation energy calculation are in progress. However, since there are no models that can accurately describe the transport properties of electrolytes, new models and improvement of existing models are needed.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.157-164
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• 2021

The aim of this study is to provide empirical evaluation of the accuracy of data-model fit using growing levels of invariance models. Overall model accuracy of factor solutions was evaluated by the examination of the order for testing three levels of measurement invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (∆𝛘²) between two groups, and root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI) were used to evaluate the all-model fits. Factorial invariance result revealed that stability of the models was varying over increasing levels of measurement as a function of variable-to-factor ratio (VTF), subject-to-variable ratio (STV), and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratio (3:1, 6:1, and 9:1), the models started to show accuracy over levels of measurement when STV ratio was 6:1. Yet, the frequency of stability models over 1000 replications increased (from 69% to 89%) as STV ratio increased. The models showed more accuracy at or above 39:1 STV.