• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.197-212
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• 2022

The study uses the audited financial statements of 26 Vietnamese commercial banks listed on the Ho Chi Minh City Stock Exchange (HOSE) and Hanoi Stock Exchange (HOSE) during the 2008-2018 period to estimate the system GMM model, which provides empirical evidence on the effect of the variables of customer deposit to total assets (DEPO) ratio, loan to assets (LTA) ratio, liquidity of commercial banks (LIQ), credit development (CRD) ratio, external funding (EFD) ratio, and credit loss provision (LLP) ratio on liquidity risk. The study confirms that commercial banks' internal factors play the most important role, and there is no empirical evidence on macro variables that affect liquidity risk. Finally, in accordance with the theoretical framework, the study uses an estimation method with the R language and the bootstrap methodology to give empirical proof of the nonlinear correlation and U-shaped graph between commercial bank size and liquidity risk. The importance of commercial bank size in absorbing and moderating the effects of liquidity shocks is demonstrated, however, excessive growth in commercial bank size would increase liquidity risk in commercial bank operations.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 춘계학술발표회논문집(1)
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• pp.292-297
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• 1997

An alternating conditional expectation (ACE) algorithm, a kind of non-parametric regression method, is proposed to generate empirical correlations automatically. The ACE algorithm yields an optimal relationship between a dependent variable and multiple independent variables without any preprocessing and initial assumption on the functional forms. This algorithm is applied to a collection of 12,879 CHF data points for forced convective boiling hi vertical tubes to develop a new critical heat flux (CHF) correlation. The meat root mean square, and maximum errors of our new correlation are -0.558%, 12.5%, and 122.6%, respectively. Our CHF correlation represents the entire set of CHF data with an overall accuracy equivalent to or better than that of three existing correlations.

• International Journal of Air-Conditioning and Refrigeration
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• 제12권4호
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• pp.192-197
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• 2004

A capillary tube, which is a common expansion device in small sized refrig-eration and air-conditioning systems, should be redesigned properly to establish an optimum operation cycle of a refrigerating system with alternative refrigerants. Based on experimental data for R-22, R-290, and R-407C, an empirical correlation is developed to predict mass flow rate through capillary tubes. Dimensionless parameters are derived from the Buckingham Pi theorem, considering the effects of operating conditions and capillary tube geometry on mass flow rate. Approximately $97\%$ of the present data are correlated within a relative deviation of $\pm\;10\%.$ The present correlation also predicts the data obtained from open literature within $\pm\;15\%.$ In addition, rating charts of refrigerant flow rate for R-12, R-22, R-134a, R-152a, R-407C, R-410A, R-290, and R-600a are developed.

• 산업공학
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• 제14권1호
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• pp.79-83
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• 2001

In this paper, we propose a simple method to reduce categorical variables into smaller, but significant numbers, and also demonstrate how the proposed method can be applied to the problem of reduction that empirical research often faces in the course of data processing. For the purpose, we introduce a concept of pseudo-correlation coefficient to make it possible to use factor analysis (FA) as a tool for reducing variables. The main idea of the concept is to deal with the measures of association of categorical variables in the sense of the concept of Pearson's correlation coefficient in order to meet the input requirement of FA. Upon examination of existing measures that could play as pseudo-correlation coefficients, Cramer's V coefficient is selected for the best result among them. To show the detailed procedure of the proposed method, a specific demonstration with the data from 329 R&D projects conducted in 18 private laboratories in electric and electronics industry is presented.

• 한국분무공학회지
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• 제18권1호
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• pp.35-43
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• 2013

The empirical correlations for the prediction of breakup length of liquid jet in uniform cross flow are reviewed and classified in this study. The breakup length of liquid jets in cross flow was normally discussed in terms of the distances from the nozzle exit to the column breakup location in the x and y directions, called as column fracture distance and column fracture height, respectively. The empirical correlations for the prediction of column fracture distance can be classified as constant form, momentum flux ratio form, Weber number form and other parameter form, respectively. In addition, the empirical correlations for the prediction of column fracture height can be grouped as momentum flux ratio form, Weber number form and other parameter form, respectively. It can be summarized that the breakup length of liquid jet in a cross flow is a basically function of the liquid to air momentum flux ratio. However, Weber number, liquid-to-air viscosity ratio and density ratio, Reynolds number or Ohnesorge number were incorporated in the empirical correlations depending on the investigators. It is clear that there exist the remarkable discrepancies of predicted values by the existing correlations even though many correlations have the same functional form. The possible reasons for discrepancies can be summarized as the different experimental conditions including jet operating condition and nozzle geometry, measurement and image processing techniques introduced in the experiment, difficulties in defining the breakup location etc. The evaluation of the existing empirical correlations for the prediction of breakup length of liquid jet in a uniform cross flow is required.

• 한국도로학회논문집
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• 제19권5호
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• pp.49-58
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• 2017

PURPOSES : The objective of this study is to develop a simple regression model in designing the asphalt concrete (AC) overlay thickness using the Mechanistic-empirical pavement design guide (MEPDG) program. METHODS : To establish the AC overlay design equation, multiple regression analyses were performed based on the synthetic database for AC thickness design, which was generated using the MEPDG program. The climate in Seoul city, a modified Hirsh model for determining dynamic modulus of asphalt material, and a new damaged master curve approach were used in this study. Meanwhile, the proposed rutting model developed in Seoul city was then used to calibrate the rutting model in the MEPDG program. The AC overlay design equation is a function of the total AC thickness, the ratio of AC overlay thickness and existing AC thickness, the ratio of existing AC modulus and AC overlay modulus, the subgrade condition, and the annual average daily truck traffic (AADTT). RESULTS : The regression model was verified by comparing the predicted AC thickness, the AADTT from the model and the MEPDG. The regression model shows a correlation coefficient of 0.98 in determining the AC thickness and 0.97 in determining AADTT. In addition, the data in Seoul city was used to validate the regression model. The result shows that correlation coefficient between the predicted and measured AADTT is 0.64. This indicates that the current model is more accuracy than the previous study which showed a correlation coefficient of 0.427. CONCLUSIONS:The high correlation coefficient values indicate that the regression equations can predict the AC thickness accurately.

• 한국도로학회논문집
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• 제12권2호
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• pp.115-121
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• 2010

입도조정기층 재료의 역학적 특성평가를 위하여 15개 시료에 대해 반복재하 삼축압축시험, CBR 시험, 투수계수시험을 수행하였다. 입도조정기층 재료의 CBR 값은 32~110 범위(평균 81)에서 매우 폭넓게 결정되었으며, 수침조건에서 팽창량은 0.04mm 이하로 나타났다. 입도조정기층 재료의 탄성계수는 체적응력의 영향을 매우 크게 받았으며 선형체적응력모델의 적용성이 가장 뛰어남을 확인하였다. 입도조정기층 재료의 탄성계수는 100MPa~600MPa, 모델계수 $k_1$은 80~270, 모델계수 $k_2$는 0.1~0.6 사이에서 결정 되었다. 체가름시험과 다짐시험에서 결정된 지수물성치로부터 입도조정기층 재료의 탄성계수를 결정하는 경험모형을 제안하였다. 제안된 경험모형의 결정계수는 모델계수 $k_1$ 결정에 있어서는 0.423, 모델계수 $k_2$ 결정에 있어서는 0.920, 응력단계별 탄성계수 결정에 있어서는 0.872로 평가되었다.

• 천문학논총
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• 제30권2호
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• pp.489-490
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• 2015

We present population synthesis models for the calcium II triplet (CaT), currently the most popular metallicity indicator, based on high-resolution empirical spectral energy distributions (SEDs). Our new CaT models, based on empirical SEDs, show a linear correlation below [Fe/H] ~ -0.5, but the linear relation breaks down in the metal-rich regime by converging to the same equivalent width. This relation shows good agreement with the observed CaT of globular clusters (GCs) in NGC 1407 and the Milky Way. However, a model based on theoretical SEDs does not show this feature of the CaT and fails to reproduce observed GCs in the metal-rich regime. This linear relation may cause inaccurate metallicity determination for metal-rich stellar populations. We have also confirmed that the effect of horizontal-branch stars on the CaT is almost negligible in models based on both empirical and theoretical SEDs. Our new empirical model may explain the difference between the color distributions and CaT distributions of GCs in various early-type galaxies. Based on our model, we claim that the CaT is not a good metallicity indicator for simple stellar populations in the metal-rich regime.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.1841-1851
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• 2018

For the safe and stable operation of the power system, accurate wind power prediction is of great significance. A wind power prediction method based on empirical mode decomposition and improved extreme learning machine is proposed in this paper. Firstly, wind power time series is decomposed into several components with different frequency by empirical mode decomposition, which can reduce the non-stationary of time series. The components after decomposing remove the long correlation and promote the different local characteristics of original wind power time series. Secondly, an improved extreme learning machine prediction model is introduced to overcome the sample data updating disadvantages of standard extreme learning machine. Different improved extreme learning machine prediction model of each component is established. Finally, the prediction value of each component is superimposed to obtain the final result. Compared with other prediction models, the simulation results demonstrate that the proposed prediction method has better prediction accuracy for wind power.

• Computers and Concrete
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• 제31권3호
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• pp.241-252
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• 2023

Corrosion of rebar is one of the major deteriorating mechanisms that affect the durability of reinforced concrete (RC) structures. The increase in CO₂ concentration in the atmosphere leads to early carbonation and deterioration due to corrosion in RC structures. In the present study, an attempt has been made to modify the existing carbonation depth prediction empirical model. The modified empirical model is verified from the carbonation data collected from selected RC structures of CSIR-SERC campus, Chennai and carbonation data available from the reported literature on in-situ RC structures. Attempt also made to study the carbonation depth in the laboratory specimens using oxygen permeability index (OPI) test. The carbonation depth measured from RC structures and laboratory specimens are compared with estimated carbonation depth obtained from OPI test data. The modified empirical model shows good correlation with measured carbonation depth from the identified RC structures and the reported RC structures from the literature. The carbonation depth estimated from OPI values for both in-situ and laboratory specimens show lesser percentage of error compared to measured carbonation depth. From the present investigation it can be said that the OPI test is the suitable test method for both new and existing RC structures and laboratory RC specimens.