• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.595-611
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• 2016

We use nonlinear regression models (such as the Hill Model) when we analyze data in toxicology and/or pharmacology. In nonlinear regression models an estimator of parameters and estimation of measurement about uncertainty of the estimator are influenced by the variance structure of the error. Thus, estimation methods should be different depending on whether the data are homoscedastic or heteroscedastic. However, we do not know the variance structure of the error until we actually analyze the data. Therefore, developing estimation methods robust to the variance structure of the error is an important problem. In this paper we propose a method to estimate parameters in nonlinear regression models based on a preliminary test. We define an estimator which uses either the ordinary least square estimation method or the iterative weighted least square estimation method according to the results of a simple preliminary test for the equality of the error variance. The performance of the proposed estimator is compared to those of existing estimators by simulation studies. We also compare estimation methods using real data obtained from the National Toxicology program of the United States.

• 한국노년학
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• v.38 no.4
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• pp.837-851
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• 2018

This study aimed to investigate the relationship between frailty and health care utilization in a cross-sectional design of a population-based sample of community-dwelling older adults. We used the data of 516 participants who dwell in Daejon, aged between 65 and 84 years old. Using K-frailty index, frailty status were measured and categorized as three groups: robust, prefrail, and frail. Logistic regression analysis was used to examine if frailty affects emergency department(ED) visit or hospitalization. In addition, negative binomial regression was used to examine the association between outpatient visits and frailty. Our results showed that the frail elderly increased the ED visit and the number of outpatient visit significantly after controlling for demographic characteristics, socioeconomic status, the number of chronic diseases, and self-rated health status. Considering that frailty is an important independent factor affecting health care utilization, more attention is required to prevent the frailty in our health care system.

• Korean Journal of Optics and Photonics
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• v.31 no.3
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• pp.125-133
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• 2020

An innovative method for separating overlapping latent fingerprints, using laser-induced plasma spectroscopy (LIPS) combined with multivariate analysis, is reported in the current study. LIPS provides the capabilities of real-time analysis and high-speed scanning, as well as data regarding the chemical components of overlapping fingerprints. These spectra provide valuable chemical information for the forensic classification and reconstruction of overlapping latent fingerprints, by applying appropriate multivariate analysis. This study utilizes principal-component analysis (PCA) and partial-least-squares (PLS) techniques for the basis classification of four types of fingerprints from the LIPS spectra. The proposed method is successfully demonstrated through a classification example of four distinct latent fingerprints, using discrimination such as soft independent modeling of class analogy (SIMCA) and partial-least-squares discriminant analysis (PLS-DA). This demonstration develops an accuracy of more than 85% and is proven to be sufficiently robust. In addition, by laser-scanning analysis at a spatial interval of 125 ㎛, the overlapping fingerprints were separated as two-dimensional forms.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Journal of The Korean Digital Architecture Interior Association
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• v.13 no.4
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• pp.51-60
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• 2013

With regard to urban culture this study aims to essential understanding and systematic approach to the culture. The "2012 Seoul Survey" report has been used to find out causality among the related variables. In the first place 'satisfaction of cultural condition' was operationally selected as a dependent variable for regression. For the purpose of controlling the third factors for ceteris paribus effect correlation analysis was previously done between the dependent variable and all other variables respectively, which resulted in two groups of variables: group (1) - 2 variables of very significant correlations(p-value<0.01) and (2) - the other 6 variables of significant correlations(p-value<0.05). Then hierarchical regression was adopted to these 2 groups to analyse statistical significance of independent variables, and multicollinearity(VIF; variance inflation factor). Additionally to OLS robust and bootstrapping regressions were done to confirm the validity of this model specification. At last a regression model specified by group (1) as independent variables(they are 'community spirit caring for women, the disabled, the poor and the old,' 'satisfaction of bicycle riding condition' shows that the variables have statistically significant and substantially strong effect on 'satisfaction of cultural condition.' This finding implies the following understanding; (1) urban festivals are regarded as the main of the urban culture as of now and this results from the low level of today's culture, (2) culture is telling and hearing stories but the influential relationship between urban culture and community spirit on the weak is negative, which says that the cultural perception among citizen is somewhat selfish and far from the essential understanding of the urban culture. In spite of restrictive external validity this finding can be used as a direction for promoting culture and a basis for related policy choice in cities.

• Corrosion Science and Technology
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• v.18 no.2
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• pp.61-71
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• 2019

Flow-Accelerated Corrosion (FAC) is a phenomenon in which a protective coating on a metal surface is dissolved by a flow of fluid in a metal pipe, leading to continuous wall-thinning. Recently, many countries have developed computer codes to manage FAC in power plants, and the FAC prediction model in these computer codes plays an important role in predictive performance. Herein, the FAC prediction model was developed by applying a machine learning method and the conventional nonlinear regression method. The random forest, a widely used machine learning technique in predictive modeling led to easy calculation of FAC tendency for five input variables: flow rate, temperature, pH, Cr content, and dissolved oxygen concentration. However, the model showed significant errors in some input conditions, and it was difficult to obtain proper regression results without using additional data points. In contrast, nonlinear regression analysis predicted robust estimation even with relatively insufficient data by assuming an empirical equation and the model showed better predictive power when the interaction between DO and pH was considered. The comparative analysis of this study is believed to provide important insights for developing a more sophisticated FAC prediction model.

• International Area Studies Review
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• v.16 no.1
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• pp.3-27
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• 2012

This paper adopts recently developed panel unit root test that is cross-sectionally robust. Cointegration test is also used to find whether regional house prices are in line with gross regional domestic production (GRDP) in the long run in Korea during 1989-2009. Based on the panel VECM and the panel ARDL models, we examine causal relationships among the variables and estimate the long-run elasticity. We find evidence of cointegration and bidirectional causal relationships between regional house prices and GRDP. The results of long-run estimates, using both fixed effect and ARDL models, show that house prices positively and significantly influence on the GRDP and vice versa. Together with these results, the findings of ARDL-ECM imply that there exists a long-run equilibrium relationship between house prices and regional economic variables even if there is a possibility of short-run deviation from its long-run path.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.33-41
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• 2018

The purpose of this study is to develop more accurate and robust emotion prediction neural network (EPNN) model by combining heart rate variability (HRV) and neural network. For the sake of improving the prediction performance more reliably, the proposed EPNN model is based on various types of activation functions like hyperbolic tangent, linear, and Gaussian functions, all of which are embedded in hidden nodes to improve its performance. In order to verify the validity of the proposed EPNN model, a number of HRV metrics were calculated from 20 valid and qualified participants whose emotions were induced by using money game. To add more rigor to the experiment, the participants' valence and arousal were checked and used as output node of the EPNN. The experiment results reveal that the F-Measure for Valence and Arousal is 80% and 95%, respectively, proving that the EPNN yields very robust and well-balanced performance. The EPNN performance was compared with competing models like neural network, logistic regression, support vector machine, and random forest. The EPNN was more accurate and reliable than those of the competing models. The results of this study can be effectively applied to many types of wearable computing devices when ubiquitous digital health environment becomes feasible and permeating into our everyday lives.

• 한국체육학회지인문사회과학편
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• v.57 no.6
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• pp.263-272
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• 2018

This study examined the association of gait variability and physical fitness with frailty status in older women. In a cross-sectional design, 168 elderly women, aged 65 years and older (75.07±5.40 years), measured body composition, gait parameters gait variability, physical fitness variables, MMSE-DS and CES-D. Subjects were classified as robust, pre-frail, and frailty based on the Fried et al.(2001) criteria for frailty weight loss, exhaustion, low hand-grip strength, low gait speed, and physical inactivity. Logistic regression analyses were used to determine the odds ratio (ORs) and 95% confidence interval (CI) of frailty status for having gait variability and physical fitness levels. Compared to the robust group (OR=1), the frailty group had significantly higher ORs of having terminal double limb stance (OR=1.48, 95% CI=0.10-2.21, p=.049), step cadence (OR=2.06, 95%CI=1.20-3.43, p=.009) variability, and significantly lower ORs of having upper-strength (OR=0.49, 95%CI=0.31-0.77, p=.002) even after adjusting for age, education, comorbidity, K-IADL, MMSE-KC and CES-D score. The finding of this study suggested that terminal double limb stance, step cadence and upper body muscular strength were independent predictors of frailty.

• Management & Information Systems Review
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• v.30 no.2
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• pp.257-275
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• 2011

The price relationship between the futures market and the underlying spot market has attracted the attention of academics, practitioners, and regulators due to their roles during periods of turbulence in financial markets. The purpose of this paper is to investigate the dynamic of price relationship(or lead-lag relationship) between Korean Treasury Bond futures market and spot market. To examine the nature of the price relationship, descriptive statistics, serial correlation, and cross-correlation are used as a preliminary statistics in the Korean Treasury Bond spot and futures market. Next, following Stoll-Whaley(1990) and Chan(1992), the multiple regression method is used to examine the lead-lag patterns between the two markets. The empirical results are summarized as follows. The mean returns of spot markets and future markets are positive(+) and negative(-) respectively and the standard deviation of both stock and futures returns increase through the sub-periods. For the most periods, there is negative skewness in the both markets. The zero excess kurtosis due to the heavy tails of the distribution are relatively large. The autocorrelations in the spot returns for the sample periods are positive in time lag 1, but the autocorrelations in the future returns shows no significant evidence. The results of the daily cross-correlations between the KTB spot and futures returns indicate that a lead-lag relationship don't exist for price changes of futures and spot markets as a preliminary analysis. Finally, empirical results of regression analysis for both market indicate that there is no evidence that the KTB futures lead the KTB spot market, or the KTB spot market lead the KTB futures market. These results are robust for all sub-periods.