• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.387-393
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• 2021

In this study, finite element analysis was performed to evaluate a method of increasing the fatigue life of the pipe connection structure commonly used in the topside structure of offshore platforms. MSC Patran/Nastran, a commercial analysis program, was used, and the critical structural model was selected from the global analysis. To realize the stress concentration phenomenon according to the load, modeling using 8-node solid elements was implemented. The main loads were considered to be two lateral loads and a tensile load on a diagonal pipe. To check the hotspot stress at the main location, a 0.01 mm dummy shell element was applied. After calculating the main stress at the 0.5-t and 1.5-t locations, the stress generated in the weld was estimated through extrapolation. In some sections, this stress was observed to be below the fatigue life that should be satisfied, and reinforcement was required. For reinforcement, a bracket was added to reduce the stress concentration factor where the fatigue life was insufficient without changing the thickness or diameter of the previously designed pipe. Regarding the tensile load, the stress in the bracket toe increased by 23 %, whereas the stress inside and outside of the pipe, which was a problem, decreased by approximately 8 %. Regarding the flexural load, the stress at the bracket toe increased by 3 %, whereas the stress inside and outside of the pipe, which was also a problem, decreased by approximately 48 %. Owing to the new bracket reinforcement, the stress in the bracket toe increased, but the S-N curve itself was better than that of the pipe joint, so it was not a significant problem. The improvement method of fatigue life is expected to be useful; it can efficiently increase the fatigue life while minimizing changes to the initial design.

• Journal of Soil and Groundwater Environment
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• v.12 no.4
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• pp.1-7
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• 2007

Slug/bail tests were conducted in sand layer (sbt-1 well), silty sand layer (sbt-2 well), and mixed sand and silty sand layer (sbt-3 well). Hydraulic conductivity and specific storage coefficient were estimated through slug/bail tests. Pore volumes of groundwater level drawdown zone for bail test were estimated by using hydraulic conductivity and specific storage coefficient. KGS model was most suitable interpretation method of slug/bail tests. Average hydraulic conductivity for slug/bail tests were estimated to be $6.65{\times}10^{-5}$ m/sec in sbt-1 well, $6.33{\times}10^{-6}$ m/sec in sbt-2 well, and $3.72{\times}10^{-5}$ m/sec in sbt-3 well. Average specific storage coefficient for slug/bail tests were estimated to be 0.0225 in sbt-1 well, 0.0177 in sbt-2 well, and 0.0259 in sbt-3 well. Dimensionless time and dimensionless wellbore storage were estimated by use of transmissivity, storativity, test time, and specification of test wells. And, dimensionless drawdown were selected by parameter ${\alpha}\;and\;{\beta}$ parameter from Cooper et al. (1967). Radius of influence were estimated by estimated dimensionless time, dimensionless wellbore storage, and dimensionless drawdown. The average radius of influnce for slug/bail tests were estimated to be 1.377 m in sbt-1 well, 1.253 m in sbt-2 well, and 1.558 m in sbt-3 well. Pore volume at groundwater level drawdown zone by dummy withdrawal for bail tests were estimated to be $145,636cm^3$ in sbt-1 well, $71,561cm^3$ in sbt-2 well, and $100,418cm^3$ in sbt-3 well. Pore volume excepted well volume at groundwater level drawdown zone by dummy withdrawal for bail tests were estimated to be $145,410cm^3$ in sbt-1 well, $71,353cm^3$ in sbt-2 well, and $100,192cm^3$ in sbt-3 well.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.119-132
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• 2014

This study analyzed the failure prediction model of the firms listed on the KOSDAQ by considering whether there are embezzlement, malpractice and the largest shareholder changes or not. This study composed a total of 166 firms by using two-paired sampling method. For sample of failed firm, 83 manufacturing firms which delisted on KOSDAQ market for 4 years from 2009 to 2012 are selected. For sample of normal firm, 83 firms (with same item or same business as failed firm) that are listed on KOSDAQ market and perform normal business activities during the same period (from 2009 to 2012) are selected. This study selected 80 financial ratios for 5 years immediately preceding from delisting of sample firm above and conducted T-test to derive 19 of them which emerged for five consecutive years among significant variables and used forward selection to estimate logistic regression model. While the precedent studies only analyzed the data of three years immediately preceding the delisting, this study analyzes data of five years immediately preceding the delisting. This study is distinct from existing previous studies that it researches which significant financial characteristic influences the insolvency from the initial phase of insolvent firm with time lag and it also empirically analyzes the usefulness of data by building a firm's fail prediction model which considered embezzlement/malpractice and the largest shareholder changes as dummy variable(non-financial characteristics). The accuracy of classification of the prediction model with dummy variable appeared 95.2% in year T-1, 88.0% in year T-2, 81.3% in year T-3, 79.5% in year T-4, and 74.7% in year T-5. It increased as year of delisting approaches and showed generally higher the accuracy of classification than the results of existing previous studies. This study expects to reduce the damage of not only the firm but also investors, financial institutions and other stakeholders by finding the firm with high potential to fail in advance.

• Journal of Distribution Science
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• v.13 no.9
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• pp.47-57
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• 2015

Purpose - The aim of this paper is to investigate the explanatory power of the Pecking-order theory (the cost of financing increases with asymmetric information) among Korean retail firms from the perspective of debt capacity. According to the Pecking-order theory, a firm's first preference is to use internal funds for its capital needs, its next preference is the issuance of debt, and its last preference is the issuance of equity; this is due to the information asymmetry problem between existing shareholders and investors. However, prior empirical studies, such as Lemmon and Zender (2010), argue that the entire sample test for the Pecking-order theory could be misleading due to the different levels of debt issuance capability of each of the individual firms; in fact, they confirm that the explanatory power of the Pecking-order theory improves after taking into account the differences in debt capacity of the U.S. firms they examined. This paper implements a case study approach among Korean retail firms to examine the relationship between debt capacity and the explanatory power of the Pecking-order theory in Korea. Research design, data, and methodology - This study uses the sample of public retail firms on the Korea Composite Stock Price Index (KOSPI) from the time period of 1990 to 2013. We gather related financial and accounting statements from the financial information firm WISEfn. Credit rating information is provided by the Korea Investor Service. We employ the models of Lemmon and Zender (2010) and Son and Kim (2013) to measure a firm's debt capacity. Their logit models use the rating dummy variable as a dependent variable and incorporate other firm characteristics as independent variables to estimate debt capacity. To test the Pecking-order theory, we adopt variants of the financing deficit model of Shyam-Sunder and Myers (1999). In the test of the Pecking-order theory, we consider all of the changes in total debt obligations, current debt obligations, and long-term debt obligations. Results - Our main contribution to the literature is our confirmation of the predicted relationship between debt capacity and the explanatory power of the Pecking-order theory among Korean retail firms. The coefficients on financing deficits become greater as a firm's debt capacity improves. This is consistent with the results of Lemmon and Zender (2010). The coefficients on the square of the financing deficits are also negative for the firms in the largest debt capacity group, which is also consistent with the predictions in prior literature. Conclusions - This study takes a case study approach by examining Korean retail firms. We confirm that the Pecking-order theory explains the capital structure of retail firms more appropriately, after taking into account the debt capacity of each firm. This result suggests the importance of debt capacity consideration in the testing of the Pecking-order theory. Our result also implies that there has been a potential underestimation of the explanatory power of the Pecking-order theory in existing studies.

• Tuberculosis and Respiratory Diseases
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• v.41 no.5
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• pp.521-530
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• 1994

Background : The past studies on prediction formulas of pulmonary function parameters in healthy nonsmoking Korean adults have been performed in relatively small number of subjects and the reported results were restricted on a few parameters. Also there was no systematic investigation into the effect of smoking on pulmonary function parameters in smokers who have no respiratory symptoms. Therefore we attempted to establish prediction formulas of pulmonary function parameters and examined the effect of smoking on pulmonary function parameters. Methods We analyzed the result of parameters derived from the forced expiratory spirogram in 1,067 nonsmoking subjects from June in 1990 to December in 1991. They consisted of 306 males and 761 females and had neither respitatory symptoms nor history of respiratory disease. We derived prediction formulas by multiple linear regression method from their age, heights, and weights in each sex. To examine the effect of smoking on pulmonary function parameters, we classified 383 smoking men into three groups according to the past amount of smoking as follows : i.e. group of smokers who have smoked below 10 pack-years, 10-20 pack-years and above 20 pack-years. Regarding each group of past smoking as an independent dummy variable, we analyzed pulmonary function parameters including nonsmoking men as a baseline by multiple linear regression. We evaluated the smoking effect on pulmonary function parameters according to estimated p-value. Result : 1) Prediction formulas for pulmonary function parameters in each sex were derived. 2) The past smoking less than 10 pack-years does not give any effect on pulmonary function parameters. The past smoking of 10~20 pack-years showed significant negative correlation with $FEV_1$/FVC and FEF 25~75%, and the smoking above 20 pack years showed negative correlation with $FEV_1$ and $FEV_1$/FVC. Conclusion : We have got prediction formulas of pulmonary function parameters which is driven from forced expiratory spirogram in nonsmoking Korean adults by multiple linear regression from age, heights and weights of subjects. The past smoking more than 10 pack-years showed negative correlation with some pulmonary function parameters of airflow obstruction.

• Journal of Korean Society of Forest Science
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• v.75 no.1
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• pp.1-18
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• 1986

This study was initiated to estimate productivity of Quercus variabilis stand. However the practical objective of this study was to provide some information to establish the basis of selecting the suitable site for Quercus variabilis. The productivity measured in terms of DBH, height, basal area and stem volume was hypothesized, respectively, to be a function of a group of factors. This study considered 32 factors, 20 of which were related to the forest environmental factors such as tree age, latitude, percent slope, etc. and the rest of which were related to soil factors such as soil moisture, total nitrogen, available $P_2O_5$, etc. The data on 4 productivity measurements of Quercus variabilis growth and related factors cited were collected from 99 sample plots in Kyeongbook and chungbook provinces. Some factors considered were, in nature, discrete variables and the others continuous variables. Each kind of factor was classified into 3 or 4 categories and total numbers of such categories were eventually amounted to 110. Then each category was treated as an independent variable. This is amounted to saying that individual variable was treated a dummy variable and assigned a value 1 or 0. However the first category of each factor was deleted from the normal equation for statistical consideration. First of all, each of 4 productivity measurements of Quercus variabilis growth was regressed and, at the same time, those 110 categories. Secondly, the partial correlation coefficients were measured between each pair of 4 productivity measurements and 32 individual foctors. Finally, the relative scores were estimated in order to derive the category ranges. The result of these statistical analyses could be summarized as follows: 1) Growth measurement in terms of height seems to be a more significant criterion for estimation of productivity of Quercus variabilis. 2) Productivity of forest on stocked land may better be estimated in terms of forest environmental factors, on the other hand, that of unstocked land may be estimated in terms of physio-chemical factors of soil. 3) The factors that a strongly positive relation to all growth factors of tree are age group, effective soil, soil moisture, etc. This implies that these factors might effectively be used for criteria for selecting the suitable site for Quercus variabilis. 4) Parent rock, latitude, total nitrogen, age group, effective soil depth, soil moisture, organic matter, etc., had more significant category range for tree growth. Therefore, the suitable site for Quercus variabilis may be selected, based on this information. In conclusion, the above results obtained by the multivariable analysis can be not only the important criteria for estimating the growth of Quercus variabilis but also the useful guidance for selecting the suitable sites and performing the rational of Quercus variabilis forest.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.95-106
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• 2016

Air transportation demand is consistently increasing in Korea due to economic growth and low cost carriers. For this reason, airport expansion plans are being discussed in Korea. Therefore, it is essential to forecast reliable air transportation demand with adequate methods. However, most of the air transportation demand models in Korea has been developed by simple regression analysis with several dummy variables. Simple regression analysis without considering stationarity of time-series data can bring spurious outputs when a direct causal relationship between explanatory variables and dependent variable does not exist. In this paper, econometric model were developed for air transportation demand based on stationarity in time-series data. Unit root test and co-integration test are used for testing hypothesis of stationarity.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.41-72
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• 2003

The purposes of this paper are to build theoretical and empirically testable model to identify determining factors of ownership structure, and to analyze this model empirically using th Korea Stock Exchange panel data, and to test the impact of opening the stock market on the determinants of ownership structure. The determining factors of ownership structure identified in this paper include debt ratio, dividend, asset characteristics, profitability, growth business risk, size, institutional investors and chaebol-non chaebol dummy variable. Empirical panel estimation test reveals that this model can explain about $9\sim11%$ of the cross sectional variance in the equity ratio of large shareholders. The reasons that this model has too explanatory power are that some variables were measured with errors, and that there were some omitted variables in tested model. The regression results on the model variables ar generally in line with predictions. But the coefficient estimates on size is never significant. And it appears that the exogenous variable which explains opening the stock market has positive effect on the determinants of ownership structure.

• Journal of the Korean Vacuum Society
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• v.10 no.2
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• pp.145-154
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• 2001

A new type of modular mirror manipulator with independent adjustability was developed for the EPU6 beamline under construction at the Pohang Accelerator Laboratory. The mirror manipulator was designed so that the angular displacements of roll and pitch rotations do not introduce translational displacements and are independent with each other by positioning the mirror center to the center of a newly devised spherical joint. Manipulating its roll and pitch micrometers, the rotation angles of a dummy mirror were measured at an accuracy of 5 $\mu$rad using a gravity-referenced inclinometer. While the designed angular resolution was 3.937 $\mu$rad/$\mu\textrm{m}$, measured angular resolutions were 3.94 $\mu$rad/$\mu\textrm{m}$ for roll rotation and 3.85 $\mu$rad/$\mu\textrm{m}$ for pitch rotation. The effect of roll rotation on pitch angles was measured to be -3.18% and the effect of pitch rotation on roll angles was measured to be -5.21%. As the mirror manipulator was designed with emphases on independent adjustability and standardization, it results in eases of manufacturing, installation and adjustment as well as reductions of development period and design cost of mirror manipulators for various types of mirrors.