• East Asian Economic Review
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• v.23 no.4
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• pp.333-351
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• 2019

We use a data-mining bootstrap procedure to investigate the predictability test in the eight Asia-Pacific regional stock markets using in-sample and out-of-sample forecasting models. We address ourselves to the data-mining bias issues by using the data-mining bootstrap procedure proposed by Inoue and Kilian and applied to the US stock market data by Rapach and Wohar. The empirical findings show that stock returns are predictable not only in-sample but out-of-sample in Hong Kong, Malaysia, Singapore, and Korea with a few exceptions for some forecasting horizons. However, we find some significant disparity between in-sample and out-of-sample predictability in the Korean stock market. For Hong Kong, Malaysia, and Singapore, stock returns have predictable components both in-sample and out-of-sample. For the US, Australia, and Canada, we do not find any evidence of return predictability in-sample and out-of-sample with a few exceptions. For Japan, stock returns have a predictable component with price-earnings ratio as a forecasting variable for some out-of-sample forecasting horizons.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1053-1065
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• 2006

This paper proposes a method in one-way layouts for longitudinal data with informative drop-out. When dropouts are informative, that is, correlated with unobserved data and/or the previous observed data, the simple imputation methods such as 'last observation carried forward' (LOCF) methods would arise the bias of the testing models. The maximum likelihood procedure combined with a logit model for the drop-out process is proposed to test treatment effects for one factorial designs and compared with LOCF method in two examples.

• Journal of Society of Preventive Korean Medicine
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• v.3 no.1
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• pp.67-82
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• 1999

This study was performed to investigate out-of-pocket money among medical expenses of an oriental medical university hospital by the use of internal data of an oriental hospital because medical insurance program data could not show us insuree's out-of-pocket money among medical expenses. The purpose of this study was to analyze out-of-pocket money among medical expenses of ambulatory and hospitalized patients. Under this purpose, We analyzed actual medical expenses data of 1389 out-patients and 858 in-patients of the oriental medical university hospital with 90 beds that could be approach to internal data from July 1, 1998 to March 31, 1999. The major findings are as follows : 1. In ambulatory patients, the cost share ratio of insuree & that of insurer was 90 : 10 respectly. 2. In hospitalized patients, the cost share ratio of insuree & that of insurer was 72 : 28 respectly.

• Journal of Distribution Science
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• v.14 no.8
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• pp.9-21
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• 2016

Purpose - This research analyzes the impact of motivations to dine out and selected attributes of customers on customer satisfaction and loyalty. Based on collected data, this study aims to suggest effective marketing strategies to help manage traditional Korean food restaurants. Research design, data, and methodology - The data were collected from the customers who visited traditional Korean food restaurants in Jeon-Ju for two months from December, 2015. The available data were 402 from collected 450 customers' data and they were analyzed by using SPSS 19.0. Result - These are the results of data analysis. First, environmental, personal and perceived factors influence on the motivations to dine out at Korean food restaurants which affect customer satisfaction. Next, selected attributes from Korean food restaurants have impacts on customer satisfaction. Third, motivations to dine out Korean food restaurants affect customer loyalty. Moreover, physical environments, curiosity and need satisfactions, which are the selected attributes, have impacts on customer loyalty. Lastly, it has been identified that customer satisfaction in Korean food restaurants influences customer loyalty. Conclusions - Satisfaction and good brand image of Jeon-Ju will increase customers' intention to revisit. This study has found that high customer satisfaction leads to re-visitation.

• Journal of the East Asian Society of Dietary Life
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• v.24 no.3
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• pp.301-314
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• 2014

This study was conducted in order to measure changes in the dining out consumption behaviors of the elderly living in Korea. Data on 2,316 and 3,170 elderly aged over 50 years were extracted from the 2001 and 2011 KNHANES(Korea National Health and Nutrition Examination Surveys), respectively. The data were analyzed by gender, age, region area, marital status, educational level, household income, economic activity and subjective health status. Frequency of dining out was higher in males between 50~64 years of age, living in metropolitan area, well-educated, high-income, engaged in economic activity and healthy. As a result, these basic data can be used for analyzing the changes in dining out consumption behaviors by sociodemographic characteristics of people aged over 50 years and the elderly in Korea. In the results on the consumption rate of food service in the two groups, 'female' and '65~74 years old' showed the largest increases from 10 years, and thus should be the group that the food service industry focuses on to develop new marketing strategies suitable for the environment.

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.68-73
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• 2021

In this study, the detection of rubber o-ring defects was carried out using k-fold cross validation and Support Vector Machine (SVM) algorithm. The data process was carried out in 3 steps. First, we proceeded with a frame alignment to eliminate unnecessary regions in the learning and secondly, we applied gray-scale changes for computational reduction. Finally, data processing was carried out using image augmentation to prevent data overfitting. After processing data, SVM algorithm was used to obtain normal and defect detection accuracy. In addition, we applied the SVM algorithm through the k-fold cross validation method to compare the classification accuracy. As a result, we obtain results that show better performance by applying the k-fold cross validation method.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.03a
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• pp.81-88
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• 2001

Electrical resistivity is one of physical property of the earth and measured by electrical resistivity survey, electrical resistivity logging and laboratory test. Recently, electrical resistivity is widely used in determination of rock quality in road and railway tunnel design. To get more reliable rock quality data from electrical resistivity, it needs a lot of test and study on correlation of resistivity and rock quality. Firstly, we did rock property test in laboratory, such as uniaxial compressive strength(UCS), p wave velocity, Young's modulus and electrical resistivity. We correlate each test results and we found out that electrical resistivity has exponentially related to UCS and P wave velocity and linearly related to Young's modulus. And we accomplished electrical resistivity survey in field site and carried out electrical resistivity logging at in-situ area. Also we peformed rock classification, such as RQD, RMR and Q-system and we correlate electrical resistivity to rock classification results. We found out that electrical resistivity logging data are highly correlate to RQD, Q and RMR. Also we found out that electrical resistivity survey data are lower than electrical resistivity logging data when there are faults or fractures. And it cause electrical resistivity survey data to lowly correlate to RQD, Q and RMR.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.06b
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• pp.119-137
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• 2003

Electrical resistivity is one of physical property of the earth and measured by electrical resistivity survey, electrical resistivity logging and laboratory test. Recently, electrical resistivity Is widely used In determination of rock quality in road and railway tunnel design. To get more reliable rock quality data from electrical resistivity, it needs a lot of test and study on correlation of resistivity and rock quality. Firstly, we did rock property test In laboratory, such as uniaxial compressive strength(UCS), P wave velocity, Young's modulus and electrical resistivity. We correlate each test results and we found out that electrical resistivity has exponentially related to UCS and P wave velocity and linearly related to Young's modulus. And we accomplished electrical resistivity survey in field site and carried out electrical resistivity togging at In-situ area. Also we performed rock classification, such as RQD, RMR and Q-system and we correlate electrical resistivity to rock classification results. We found out that electrical resistivity logging data are highly correlate to RQD, Q and RMR. Also we found out that electrical resistivity survey data are lower than electrical resistivity logging data when there are faults or fractures. And it cause electrical resistivity survey data to lowly correlate to RQD, Q and RMR.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.333-342
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• 2018

The objective of this study was to investigate the problem behavior and its convergent factors in out-of-school adolescents, with a focus on gender differences. This study was a secondary data analysis study using out-of-school adolescents research data at Busan women and family development institute. The study was conducted in a total of 499 out-of-school adolescents (337 males, 162 females). The type of the 8 problem behaviors (run away from home, drop out, prostitution, violence, internet game addiction, theft, drug addiction, and smoking) were identified. The collected data were analyzed with multiple logistic regression. Among the problem behaviors of the participants, internet game addiction and theft were more significantly high in male out-of-school adolescents than female out-of-school adolescents. In internet game addiction, male out-of-school adolescents were 1.90 times higher than female out-of-school adolescents (p=.008, 95% CI=1.18-3.06). In theft, male out-of-school adolescents were 1.92 times higher than female out-of-school adolescents (p=.006, 95% CI=1.21-3.03). When the social measures were provided for those adolescents, a distinguished approach is required depending on the problem behavior and gender.

• Proceedings of the Safety Management and Science Conference
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• 2013.11a
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• pp.393-400
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• 2013

Globally, smart phones have been rapidly distributed, which has led to changes in people's life cycle. Most people who are under 60 are supposed to use smart phones. Additionally, as the ratio of people who are interested in physical exercise is increasing, some applications for smart phones can manage dividual's exercise with the web servers. However, most of them can only check how much individual works out and cannot compare other's body type and life environment. Moreover, users cannot share their own data with others. This paper proposed the system which can resolve those kinds of problems through data mining techniques. The suggested model will have ability to figure out the relation between body type and the amount of exercise, find out if his work is proper from the result of classification and can pick out the features which is common to people who have similar body type and the amount of workout by applying data mining techiques. This model also will be able to recommend the proper amount of workout to each individual in order that they keep good health state efficiently.