• Advances in aircraft and spacecraft science
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• v.6 no.4
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• pp.333-348
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• 2019

Low fuel regression rate is the main drawback of hybrid rocket which should be overcome. One of the improvement techniques to this problem is usage of a solid fuel grain with a complicated geometry port, which has been promoted owing to the recent development of additive manufacturing technologies. In the design of a hybrid rocket fuel grain with a complicated geometry port, the understanding of fuel regression behavior is very important. Numerical investigations of fuel regression behavior requires a capturing method of solid fuel surface, i.e. gas-solid interface. In this study, level set method is employed as such a method and the preliminary numerical tool for capturing a hybrid rocket solid fuel surface is developed. At first, to test the adequacy of the numerical modeling, the simulation results for circular port are compared to the experimental results in open literature. The regression rates and oxidizer to fuel ratios show good agreements between the simulations and the experiments, after passing enough time. However, during the early period of combustion, there are the discrepancies between the simulations and the experiments, owing to transient phenomena. Second, the simulations of complicated geometry ports are demonstrated. In this preliminary step, a star shape is employed as complicated geometry of port. The slot number effect in star port is investigated. The regression rate decreases with increasing the slot number, except for the star port with many slots (8 slots) in the latter half of combustion. The oxidizer to fuel ratio increases with increasing the slot number.

• Corrosion Science and Technology
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• v.19 no.6
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• pp.302-309
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• 2020

This study aimed to predict the pitting corrosion characteristics of AL-6XN super-austenitic steel using multiple linear regression. The variables used in the model are degree of sensitization, temperature, and pH. Experiments were designed and cyclic polarization curve tests were conducted accordingly. The data obtained from the cyclic polarization curve tests were used as training data for the multiple linear regression model. The significance of each factor in the response (critical pitting potential, repassivation potential) was analyzed. The multiple linear regression model was validated using experimental conditions that were not included in the training data. As a result, the degree of sensitization showed a greater effect than the other variables. Multiple linear regression showed poor performance for prediction of repassivation potential. On the other hand, the model showed a considerable degree of predictive performance for critical pitting potential. The coefficient of determination (R2) was 0.7745. The possibility for pitting potential prediction was confirmed using multiple linear regression.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.107-115
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• 2020

Support vector regression (SVR) is devised to solve the regression problem by utilizing the excellent predictive power of Support Vector Machine. In particular, the ⲉ-insensitive loss function, which is a loss function often used in SVR, is a function thatdoes not generate penalties if the difference between the actual value and the estimated regression curve is within ⲉ. In most studies, the ⲉ-insensitive loss function is used symmetrically, and it is of interest to determine the value of ⲉ. In SVQR (Support Vector Quantile Regression), the asymmetry of the width of ⲉ and the slope of the penalty was controlled using the parameter p. However, the slope of the penalty is fixed according to the p value that determines the asymmetry of ⲉ. In this study, a new ε-insensitive loss function with p1 and p2 parameters was proposed. A new asymmetric SVR called GSVQR (Generalized Support Vector Quantile Regression) based on the new ε-insensitive loss function can control the asymmetry of the width of ⲉ and the slope of the penalty using the parameters p1 and p2, respectively. Moreover, the figures show that the asymmetry of the width of ⲉ and the slope of the penalty is controlled. Finally, through an experiment on a function, the accuracy of the existing symmetric Soft Margin, asymmetric SVQR, and asymmetric GSVQR was examined, and the characteristics of each were shown through figures.

• Korea journal of population studies
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• v.11 no.1
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• pp.87-96
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• 1988

The subjects used in this study were chosen from self-employed women in Taegu City, Korea, Data for 415 respondents were collected by face-to-face interviews conducted during the period of November 10 through 23, 1987. There are three major purposes in this study : first, to describe the general characteristics of self-employed Korean women's fertility behavior ; second, to examine the determinants of fertility behavior among self-employed women : third, to explore the relative importance of the fertility determinants among the women. Regression analyses were introduced to test hypotheses. Nine variables, such as household income, educational attainment, mass media, abortion, the period of contraception practice, contraceptive expenses, the number of infant, deaths marital period, and age at first marriage were introduced as indicators in the regression. The results of this study show that there are negative relationships between the dependent variable of fertility and abortion, and the period of contraception practice. On the other hand, positive relationships between the dependent variable of fertility and the number of infant deaths, and marital period and age at first marriage are shown in this study. However, the results of this study show that there are insignificant relationships between socioeconomic variables and fertility. From the results of the F test to evaluate the significance of difference in $R^2$between two different regression equations, we have found that the regression equation including both socioeconomic variables and intermediate variables is misspecified to examine the determinants of fertility behavior among self-employed Korean women. That is, the F test shows that the regression equation including only intermediate variables as indicators is the best model for this study. Finally, the relative importance of the fertility determinants among self-employed women is found as follows : Age at the first marriage is the most influential variable in the fertility, and the next important factors are abortion, the period of contraception practice, the number of infant deaths, and marital period, in that order.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.293-308
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• 1997

Sliced inverse regression is a method for reducing the dimension of the explanatory variable X without going through any parametric or nonparametric model fitting process. This method explores the simplicity of the inverse view of regression; that is, instead of regressing the univariate output varable y against the multivariate X, we regress X against y. In this article, we propose bivariate sliced inverse regression, whose method regress the multivariate X against the bivariate output variables $y_1, Y_2$. Bivariate sliced inverse regression estimates the e.d.r. directions of satisfying two generalized regression model simultaneously. For the application of bivariate sliced inverse regression, we decompose the output variable y into two variables, one variable y gained by projecting the output variable y onto the column space of X and the other variable r through projecting the output variable y onto the space orthogonal to the column space of X, respectively and then estimate the e.d.r. directions of the generalized regression model by utilize two variables simultaneously. As a result, bivariate sliced inverse regression of considering the variable y and r simultaneously estimates the e.d.r. directions efficiently and steadily when the regression model is linear, quadratic and nonlinear, respectively.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.663-671
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• 2012

In the present study, a combined ratio cum regression estimator is proposed to estimate the population mean of the study variable in the presence of a non-response using an auxiliary variable under double sampling. The expressions of bias and mean squared error(MSE) based on the proposed estimator is derived under double (or two stage) sampling to the first degree of approximation. Some estimators are also derived from the proposed class by allocating the suitable values of constants used. A comparison of the proposed estimator with the usual unbiased estimator and other derived estimators is carried out. An empirical study is carried out to demonstrate the performance of the suggested estimator and of others; it is endow that the empirical results backing the theoretical study.

• Water for future
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• v.25 no.1
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• pp.93-100
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• 1992

A study on the Derivation of the Unit Hydrograph using Multiple Regression Moe이. The purpose of this study is to deriver an optimal unit hydrograph suing the multiple regression model, particularly when only small amount of data is available. The presence of multicollinearity among the input data can cause serious oscillations in the derivation of the unit hydrograph. In this case, the oscillations in the unit hydrograph ordinate are eliminated by combining the data. The data used in this study are based upon the collection and arrangement of rainfall-runoff data(1977-1989) at the Soyang-river Dam site. When the matrix X is the rainfall series, the condition number and the reciprocal of the minimum eigenvalue of XTX are calculated by the Jacobi an method, and are compared with the oscillation in the unit hydrograph. The optimal unit hydrograph is derived by combining the numerous rainfall-runoff data. The conclusions are as follows; 1)The oscillations in the derived unit hydrograph are reduced by combining the data from each flood event. 2) The reciprocals of the minimum eigen\value of XTX, 1/k and the condition number CN are increased when the oscillations are active in the derived unit hydrograph. 3)The parameter estimates are validated by extending the model to the Soyang river Dam site with elimination of the autocorrelation in the disturbances. Finally, this paper illustrates the application of the multiple regression model to drive an optimal unit hydrograph dealing with the multicollinearity and the autocorrelation which cause some problems.

• Journal of Korean Academy of Nursing
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• v.33 no.5
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• pp.625-632
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• 2003

Purpose: The purpose of this study was to assess the importance and sensitivity to nursing interventions of four nursing sensitive nursing outcomes selected from the Nursing Outcomes Classification (NOC). Outcomes for this study were 'Knowledge: Diet', 'Knowledge: Disease Process', 'Knowledge: Energy Conservation', and 'Knowledge: Health Behaviors'. Method: Data were collected from 183 nurses working in 2 university hospitals. Fehring method was used to estimate outcome and indicators' content and sensitivity validity. Multiple and stepwise regression were used to evaluate relationships between each outcome and its indicators. Result: Results confirmed the importance and nursing sensitivity of outcomes and their indicators. Key indicators of each outcomes were found by multiple regression. 'Knowledge: Diet' was suggested for adding new indicators because the variance explained by indicators was relatively low. Not all of the indicators selected for stepwise regression model were rated for highly in Fehring method. The R² statistics of the stepwise regression models were between 18 and 63% in importance by selected indicators and between 34 and 68% in contribution by selected indicators. Conclusion: This study refined what outcomes and indicators will be useful in clinical practice. Further research will be required for the revision of outcome and indicators of NOC. However, this study refined what outcomes and indicators will be useful in clinical practice.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.149-156
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• 2020

The study aims to investigate a close relation between macro and non-macro variables on stock performance of tourism companies in Korea. The sample used in this study includes monthly data from January 2001 to December 2018. The stock price index of the tourism companies as a dependent variable are obtained from Sejoong, HanaTour, and RedcapTour as three leading Korean tourism companies that have been listed on the Korea Stock Exchange. This study assesses the tourism stock performance using the quantile regression approach. This study also investigates whether global crisis events as the Iraq War and the global financial crisis as non-macro variables have a significant effect on the stock performance of tourism companies in Korea. The results show that the oil prices, exchange rate and industrial production have negative coefficients on stock prices of tourism companies, while the effects of tourist expenditure and consumer price index are positive and significant. We estimate the result of quantile regression that non-macro determinants have statistically a significant and negative effect on tourism stock performance because the global crisis could threaten traveler's safety and economy. Overall, empirical results suggest that the effects of macro and non-macro variables are statistically asymmetric and highly related to tourism stock performance.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.1
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• pp.76-83
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• 2016

The various model tests are carried out to estimate and verify a ship performance in the design stage. But in view of the cost, the model test should be applied to every project vessel is very inefficient. Therefore, other methods of predicting the maneuverability with confined data are required at the initial design stage. The purpose of this study is to estimate the hydrodynamic derivatives by using the multiple regression analysis and PMM test data. The characteristics of the stern shape which has an important effect on the maneuverability are applied to the regression analysis in this study. The correlation analysis is performed to select the proper hull form coefficients and stern shape factors used as the variables in the regression analysis. The comparative analysis of estimate results and model test results is conducted on two ships to investigate the effectiveness of the maneuvering hydrodynamic derivatives estimation applied the stern shape. Through the present study, it is verified that the estimation using the stern shape factors as the variables are valid when the stern shape factors are located in the center of the database.