• Kyungpook Mathematical Journal
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• v.55 no.3
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• pp.541-548
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• 2015

In this paper, concepts of quasi-normal and dually quasi-normal relations are introduced. Characterizations of these relations are obtained. In addition, particulary we show that the anti-order relation ${\nleqslant}$ ($={\leqslant}^C$) is a (dually) quasi-normal relation if and only if the partially ordered set (X, ${\leqslant}$) is an anti-chain.

• Advances in concrete construction
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• v.15 no.5
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• pp.349-358
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• 2023

Aim of this work is investigating effect of thickness-stretching formulation on the quasi three-dimensional analysis of micro plate based on a thickness-stretched and shear deformable model through principle of virtual work and micro-scale dependent constitutive relations. Governing differential equations are derived in terms of five unknown functions and the analytical solution is derived using Navier's technique. To explore effect of thickness stretching model on the static results, a comparison between the results with and without thickness stretching effect is presented.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.17 no.4
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• pp.395-407
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• 1988

Transient flow in a cold-water supply system for cooling the inside of a coal mining pit was numerically simulated. Properly designed and presetted pressure reducing valves control the level of pressures of the piping system at normal or emergent conditions Quasi-steady relations to simulate the valve motion are obtained and the transient performance of the valve is investigated in the present paper. The present method reasonably simulate transient phenomena in the system including the pressure reducing valve. Excessive valve motion and column separation are simulated when the flow is abruptly reduced. A calculated example of the real system is also presented. The simulation can be used for the safety-check and the guidance for design and operation in emergent cases of the system.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.269-278
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• 2011

There are many researches that have considered the distribution functions and appropriate covariates corresponding to the scores in order to improve the accuracy of a diagnostic test, including the ROC curve that is represented with the relations of the sensitivity and the specificity. The ROC analysis was used by the regression model including some covariates under the assumptions that its distribution function is known or estimable. In this work, we consider a general situation that both the distribution function and the elects of covariates are unknown. For the ROC analysis, the mixtures of normal distributions are used to estimate the distribution function fitted to the credit evaluation data that is consisted of the score random variable and two sub-populations of parameters. The AUC measure is explored to compare with the nonparametric and empirical ROC curve. We conclude that the method using normal mixtures is fitted to the classical one better than other methods.