• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.493-505
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• 1997

The analysis of binary data appears to many areas such as statistics, biometrics and econometrics. In many cases, data are often collected in which some observations are incomplete. Assume that the missing covariates are missing at random and the responses are completely observed. A method to Bayesian analysis of the binary regression model with incomplete data is presented. In particular, the desired marginal posterior moments of regression parameter are obtained using Meterpolis algorithm (Metropolis et al. 1953) within Gibbs sampler (Gelfand and Smith, 1990). Also, we compare logit model with probit model using Bayes factor which is approximated by importance sampling method. One example is presented.

• Nuclear Engineering and Technology
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• v.33 no.4
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• pp.409-422
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• 2001

The dynamic character of a system of the governing differential equations for the one- dimensional two-fluid model, where the momentum flux parameters are employed to consider the velocity and void fraction distribution in a flow channel, is investigated. In response to a perturbation in the form of a＇traveling wave, a linear stability analysis is peformed for the governing differential equations. The expression for the growth factor as a function of wave number and various flow parameters is analytically derived. It provides the necessary and sufficient conditions for the stability of the one-dimensional two-fluid model in terms of momentum flux parameters. It is demonstrated that the one-dimensional two-fluid model employing the physical momentum flux parameters for the whole range of dispersed flow regime, which are determined from the simplified velocity and void fraction profiles constructed from the available experimental data and $C_{o}$ correlation, is stable to the linear perturbations in all wave-lengths. As the basic form of the governing differential equations for the conventional one-dimensional two-fluid model is mathematically ill posed, it is suggested that the velocity and void distributions should be properly accounted for in the one-dimensional two-fluid model by use of momentum flux parameters.s.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.1
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• pp.244-254
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• 2002

To enhance the acceleration performance and fuel consumption rate of a vehicle, the torque converter is modified or newly-developed with reliable analysis model. Up to recently, the one dimensional performance model has been used for the analysis and design of torque converter. The model is described with constant parameters based on the concept of mean flow path. When it is used in practice, some experiential correction factors are needed to minimize tole estimated error. These factors have poor physical meaning and cannot be applied confidently to the other specification of torque converter. In this study, the detail dynamic model of torque converter is presented to establish the physical meaning of correction factors. To verify the validity of model, performance test was carried out with various input speed and oil temperature. The effect of oil temperature on the performance is analysed, and it is applied to the dynamic model. And, to obtain the internal flow pattern of torque converter, CFD(Computational Fluid Dyanmics) analysis is carried out on three-dimensional turbulent flow. Correction factors are determined from the internal flow pattern, and their variation is presented with the speed ratio of torque converter. Finally, the sensitivity of correction factors to the speed ratio is studied for the case of changing capacity factor with maintaining torque ratio.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.1
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• pp.102-111
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• 2014

An analytical model was developed to understand the physics and predict the functional performance of a pin puller. The formulated model is based on one-dimensional gas dynamics for an ideal gas. Resistive forces against pin shaft movement were measured in quasi-static mechanical tests, the results of which were incorporated into the model. The expansion chamber pressure and the pin shaft displacement were measured from an actual firing test and compared to the model prediction. The gas generation rate was adjusted by a correction factor, and the heat transfer rate was obtained through parametric analysis. The validity of the model is assessed for additional firing tests with different amounts of pyrotechnic charge. This model can provide knowledge on how the pin puller functions, and on which design parameters contribute the most to the actuation of the pin puller. Using this model, we estimate the functional safety factor by comparing the energy generated by the pyrotechnic charge to the energy required to accomplish the function.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.369-375
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• 2001

The statistical regression model is one of the most frequently used clinical analysis methods. It has basic assumption of linearity, additivity and normal distribution of data. However, most of biological data in medical field are nonlinear and unevenly distributed. To overcome the discrepancy between the basic assumption of statistical model and actual biological data, we propose a new analytical method based on artificial neural network. The newly developed multilayer perceptron(MLP) is trained with 120 data set (60 normal, 60 patient). On applying test data, it shows the discrimination power of 0.76. The diabetic risk factors were also identified from the MLP neural network model and the logistic regression model. The signigicant risk factors identified by MLP model were post prandial glucose level(PP2), sex(male), fasting blood sugar(FBS) level, age, SBP, AC and WHR. Those from the regression model are sex(male), PP2, age and FBS. The combined risk factors can be identified using the MLP model. Those are total cholesterol and body weight, which is consistent with the result of other clinical studies. From this experiment we have learned that MLP can be applied to the combined risk factor analysis of biological data which can not be provided by the conventional statistical method.

• The Journal of Industrial Distribution & Business
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• v.12 no.2
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• pp.41-52
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• 2021

Purpose: This study aims to provide implications for the government's housing supply policy by analyzing the factors that determine the type of real estate holding and household debt. This study started from the awareness that the determinants of household debt differ depending on the type of real estate holding. Research design, data and methodology: Real estate ownership type was classified and analyzed into 4 models: model 1 (1 household 1 house and self-resident), model 2 (1 household multiple real estate ownership and self-resident), model 3 (1 household 1 house and rent residence), model 4 (1 household holds a large number of real estate and rent residence). The analysis method used multiple regression analysis. The dependent variable was household total debt. As independent variables, household debt, annual gross household income, financial assets, real estate net assets, annual repayment, demographic & residential characteristics were used. Results: 1) Model 4 has the highest household debt and the highest gross income, Model 2 has the most real estate mortgage loans and real estate net asset, and Model 1 has the highest real estate mortgage payments. 2) The positive factor of common household debt determinants is real estate net assets, and the negative factor is financial assets. 3) It was the net assets of real estate that acted as a positive factor in common for the four models. In other words, the more financial assets, the less household debt. It was analyzed that the more net assets of real estate, the more household debt. The annual repayment of financial liabilities had no influence on household debt, while the annual repayment of loan liabilities and household debt had a positive relationship. Conclusions: 1) It is necessary to introduce benefits and systems that can increase the proportion of household financial asset. Specific alternatives include tax benefits and reduced fees for financial asset investment. 2) In the case where a homeless person prepares one house for one household, it is necessary to prepare various support measures according to the income level. The specific alternative is to give additional points for pre-sale or apply an interest rate cut incentive for mortgage loans.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.1-9
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• 2010

This paper suggests a mixed-effects model for analyzing split-plot data when there is a repeated measures factor that affects on the response variable. Covariance structures are discussed among the observations because of the assumption of a repeated measures factor as one of explanatory variables. As a plausible covariance structure, compound symmetric covariance structure is assumed for analyzing data. The restricted maximum likelihood (REML)method is used for estimating fixed effects in the model.

• IE interfaces
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• v.25 no.4
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• pp.441-449
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• 2012

Solar PV(photovoltaic) is paid great attention to as a possible renewable energy source to overcome recent global energy crisis. However to be a viable alternative energy source compared with fossil fuel, its market competitiveness should be attained. Grid parity is one of effective measure of market competitiveness of renewable energy. In this paper, we forecast the grid parity timing of solar PV energy in Korea using two factor learning curve model. Two factors considered in the present model are production capacity and technological improvement. As a result, it is forecasted that the grid parity will be achieved in 2019 in Korea.

• Korean Journal of Child Studies
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• v.26 no.1
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• pp.261-278
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• 2005

The purpose of this study was to demonstrate the paths among the risk-protective factors that related to the resilience based on the Challenge Model. The subjects for this study were 209 children from divorced families in the 4th, 5th, and 6th grades of elementary schools in Seoul and Gyunggi-do. As the results, there were 28 paths which affected the resilience of children from divorced families based on the Challenge Model. The protective factors were easy temperament, problem-focused coping style, parental support, peer's support, higher socio-economic status, experiences in therapy, presence of siblings, contact with adult caretakers. The risk factors were higher grade, emotion-focused coping style, and children's gender, especially girls. This result demonstrated that each risk and protective factor not only affected resilience separately but interacted with one another.

• Structural Engineering and Mechanics
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• v.12 no.4
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• pp.409-428
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• 2001

The characteristics of dynamic wheel loads of heavy vehicles running on bridge and rigid surface are investigated by using three-dimensional analytical model. The simulated dynamic wheel loads of vehicles are compared with the experimental results carried out by Road-Vehicles Research Institute of Netherlands Organization for Applied Scientific Research (TNO) to verify the validity of the analytical model. Also another comparison of the analytical result with the experimental one for Umeda Entrance Bridge of Hanshin Expressway in Osaka, Japan, is presented in this study. The agreement between the analytical and experimental results is satisfactory and encouraging the use of the analytical model in practice. Parametric study shows that the dynamic increment factor (DIF) of the bridge and RMS values of dynamic wheel loads are fluctuated according to vehicle speeds and vehicle types as well as roadway roughness conditions. Moreover, there exist strong dominant frequency resemblance between bounce motion of vehicle and bridge response as well as those relations between RMS values of dynamic wheel loads and dynamic increment factor (DIF) of bridges.