• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.47-55
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• 2019

It is important to identify informative variables in high dimensional data analysis; however, it becomes a challenging task when covariates are contaminated by measurement error due to the bias induced by measurement error. In this article, we present a two-step approach for variable selection in the presence of measurement error. In the first step, we directly select important variables from the contaminated covariates as if there is no measurement error. We then apply, in the following step, orthogonal regression to obtain the unbiased estimates of regression coefficients identified in the previous step. In addition, we propose a modification of the two-step approach to further enhance the variable selection performance. Various simulation studies demonstrate the promising performance of the proposed method.

• Asian Journal of Business Environment
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• v.12 no.2
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• pp.1-12
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• 2022

Purpose: This study aims to analyze the inclusive growth in Central Sulawesi Province, an eastern province of Indonesia, up to the districts/cities level. The inclusive growth is analyzed by using Ramos, Ranieri, and Lammens' index that has three indicators which are employment, poverty, and income inequality. Research design, data, and methodology: This study uses panel data of 13 districts/cities in Central Sulawesi Province from 2015 to 2019. The statistical regression used is the panel regression method to analyze the determinants of inclusive growth there. Results: The study found that the average inclusive growth of districts/cities in Central Sulawesi is increasing from the low-level in 2015 to mid-level in 2019. The panel's data regression using fixed effect model FGLS-SUR found Investment (GFCF), Road Infrastructure, HDI, and Processing Industry have a significant positive effect. Regional minimum wage (RMW) has a significant negative effect. Government Expenditure on Education and Health Function has no significant positive effect on inclusive growth. Conclusions: throughout the study period, gini coefficient and poverty rate is slowly decreasing, while employment to population ratio remains volatile in districts/cities of Central Sulawesi.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.3
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• pp.144-150
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• 2006

Chemical characteristics and their interrelationships of 156 soils included by 74 sandy loam and 82 loam soils collected from plastic film house in Chungbuk area were investigated from 1998 to 2001. Seventeen chemical properties including pH, organic matter (OM), electrical conductivity (EC), inorganic nitrogen, available phosphorus, exchangeable cations, CEC, etc., were analyzed by correlation, standardized partial regression coefficient, and principal factor analysis. Standardized partial regression coefficients of chemical properties were estimated to determine the degree of contribution of EC and OM contents in soils. Principal factor analysis was applied to classify the studied chemical properties into different groups having similar chemical properties. The pH of experimental soils ranged from 4.24 to 7.14 and 4.95 to 7.35 for loam and sandy loam soils, respectively. The EC of soils varied from 0.93 to $15.65dS\;m^{-1}$ for loam and $0.91{\sim}22.30dS\;m^{-1}$ for sandy loam soils, respectively with significant differences among them. The EC measured by 1:5 $H_2O$ dilution method and saturation method were significantly related with 8.163 and 8.599 as the slopes of regression equation for loam and sandy loam soils, respectively. These slopes more than 8.0 in this regression equation was higher than the slope of 5.0 that is estimated from dilution coefficient suggesting that EC measured by 1:5 dilution method might be erratic. The standardized partial regression coefficient of different chemical properties for the estimation of EC was in the order of $NO_3{^-}$ > $Cl^-$ > OM > exchangeable Mg for loam soils and $NO_3{^-}$ > exchangeable Mg > $Cl^-$ for sandy loam soils. Contribution order of the chemical properties based on standardized partial regression coefficient differed 1:5 dilution method and saturation method, indicating that different chemical compounds might be present in the extract solutions of these two methods. Consequently the measurement of EC by saturation method was thought be still better for estimation of chemical property because accuracy of EC measurement by 1:5 dilution method can't be improved by any specific coefficient for adjustment of EC. Regardless of differences in soil textures and extraction methods, correlation coefficients between EC and the other chemical properties were routinely in the order of $NO_3{^-}$ > $Cl^-$ > degree of base saturation > exchangeable Mg > exchangeable Ca > $SO{_4}^{2-}$. The principal factor analysis revealed four factor groups of the chemical properties studied. The groups for sandy loam were as follows; ; 1. salt components, 2. soil reaction components, 3. fixed and adsorption components, 4. CEC components. The groupings of loam soils were similar to sandy loam except that exchangeable Na substituted the CEC of sandy loam.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.96-102
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• 2002

This study is on the estimation method of toot temperature for different tool nose radius and cutting conditions in turning. Experimental analysis has been performed in different cutting conditions such as cutting speed, feed rate, and depth of cut for the tool nose radius, 0.4R, 0.8R using SMC workpiece materials. Tool temperature is measured using a thermo-couple which is embedded in the insert tip. Using multiple linear regression method, the tool temperature can be determined as an exponential equation with cutting variables and tool nose diameters for the different tool materials. The equations determined in this study show a good correlation for the cutting conditions and can be used for a tool temperature estimation technique. The result indicates that the tool temperature decreases for increasing the tool nose radius in general. Also, nose radius hardly influences on the tool temperature compared with cutting speed, feed rate and depth of cut. This method will be useful for the estimation of tool life and temperature using limited experimental data for given cutting conditions.

• Journal of the Ergonomics Society of Korea
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• v.23 no.2
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• pp.37-54
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• 2004

Fuzzy theory provides an intelligence treatment model for judgement about information when it needs a solution or a decision making about vague problems. Therefore, fuzzy theory is used for appropriate evaluation and decision on obscure information as human's emotion in human factors, In previous study, fuzzy membership function is defined for judgement infOlmation as human's emotion then ultimate results are deducted through fuzzy inference model. This method uses general CWTent through literature review or max, min and average as representative statics value about considering variables. But, this method makes away with nonlinear's or inegular's factors of human sensibility. Accordingly, application of this method leads to considerable loss of information in the ultimate evaluation. For that reason, this method has a limitation in objective evaluation of human factors. So, this study focuses on development of fuzzy membership function, which evaluates human's emotion or feeling accurately and objectively. We used the regression analysis and reasoned a fuzzy membership function about the relation of the variables. Then we verified the adequacy with the reliability through the experiment after this.

• Child Health Nursing Research
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• v.24 no.2
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• pp.128-137
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• 2018

Purpose: To investigate factors that may affect the method of feeding among preterm infants at 4 weeks after discharge. Methods: This study included 222 mother-infant dyads born before a gestational age of 37 weeks. The feeding method and general medical characteristics of the participants were assessed at 4 weeks after discharge using a structured questionnaire. Multinomial logistic regression analysis was used to examine which factors were associated with breastfeeding at home. Results: Of the 222 infants who qualified for the study, 71 (32.9%) continued to receive breastmilk at 4 weeks post-discharge. Multinomial logistic regression analysis showed that breastfeeding at 4 weeks post-discharge was associated with higher breastfeeding self-efficacy, vaginal delivery (experience), direct breastfeeding in the neonatal intensive care unit (NICU), gestational age between 30 and 34 weeks, and breastmilk consumption in the NICU. The following factors were associated with mixed feeding at 4 weeks post-discharge: being employed, having higher breastfeeding self-efficacy, and direct breastfeeding in the NICU. Conclusion: NICU nurses should provide opportunities for direct breastfeeding during hospitalization and support breastfeeding to enhance breastfeeding self-efficacy. These factors may help to ensure the continuation of breastfeeding after discharge. Moreover, factors that affect breastfeeding should be considered when providing interventions.

• Journal of the Korea Institute of Building Construction
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• v.13 no.2
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• pp.148-158
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• 2013

Generally, building construction projects have a complex decision-making process because of the participation of various agents. In this situation, a final decision is arrived at by relying on subjective judgments based on the experience of project participants. For this reason, a method of assessing the objectivity of opinions is needed. In previous studies, the multi-criteria decision making method was applied to arrive at a final decision objectively, but this method has a limitation, in that the experience of each decision maker is not considered differently in the decision making process. Therefore, this study proposed a theoretical model using the S-shaped growth curve and regression analysis by building construction project type to quantitatively estimate decision-making reliability according to the experience of individual project participant`s. The developed model could be added to the Multi-criteria decision making method, and secure the objectivity and reliability of project participants' final opinion.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• Journal of Life Science
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• v.23 no.2
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• pp.306-310
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• 2013

We compared the efficacy of the competitive ELISA method for measuring the level of urinary aflatoxin M1 (AFM1) with that of the HPLC-fluorescence detector (HPLC-FLD) method. The recovery rate of AFM1 with the ELISA method was 105% (73-124%), and the coefficient of variation of the analysis was 6.85%. The ELISA method showed a 0.20 pg/ml and 0.62 pg/ml limit of detection and limit of quantitation, respectively. In correlation analysis, the two methods showed a very strong and statistically significant correlation (R=0.96, p<0.01). However, in spite of the strong correlation, the ELISA method tended to overestimate the urinary AFM1 concentration compared to the HPLC-FLD method. These results suggest that the competitive ELISA method may be a useful technique for measuring the AFM1 level in high-throughput urine samples, but it needs to be corrected with a regression equation from regression analysis with the HPLC-FLD method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.663-670
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• 2019

Corrective thermal performance analysis is required for power plants' turbine cycles to determine the performance status of the cycle and improve the economic operation of the power plant. We developed a sectional classification method for the main feed-water flow to make precise corrections for the performance analysis based on the Performance Test Code (PTC) of the American Society of Mechanical Engineers (ASME). The method was developed for the estimation of the turbine cycle performance in a classified section. The classification is based on feature identification of the correlation status of the main feed-water flow measurements. We also developed predictive algorithms for the corrected main feed-water through a Kernel Regression (KR) model for each classified feature area. The method was compared with estimation using an Artificial Neural Network (ANN). The feature classification and predictive model provided more practical and reliable methods for the corrective thermal performance analysis of a turbine cycle.