• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.214-222
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• 2018

The purpose of this study is to analyze the role of individualistic, family, and social characteristics of immigrant women on marriage on community integration. It is focused on exploring how the immigrant women on marriages' residential district differentiate community integration. The study adopts a questionnaire method in research of immigrant women on marriage in all parts of Korea. Data are collected from 163(Metropolitan Government & City), 182(Provincial Government) immigrant women on marriage for empirical analysis respectively. Technique used in analyzing data is Binary Logit Model primarily. In conclusion, on the results of test, it turned out to be strong significant influence on provincial regions than the metropolitan city regions statistically excepting family, and social characteristics.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.101-115
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• 2008

This study reports UTIS(Urban Traffic Information System), which has been generalized in developed countries through brisk research and development and is being promoted for introduction by National Police Agency and Road Traffic Authority to reduce the astronomical amount of social expenses including traffic congestion expenses. Also this study investigates the proper charges for using by the preestimate of demand and contentment according to methods of payment after the service is introduced. The results of this study are as follows. First, demand forecast model is constructed by Binary Logit Model. Second, forecast models of using aspects of UTIS service according to methods of payment are established by Ordered Probit Model. Third, the proper charges for using of UTIS service according to methods of payment are presented to the supplier in the aspects of users. For this, preferences by using aspects and methods of payment are captured. And unit elasticity of coefficient of utilization is understood through responsiveness analysis according to methods of payment.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.129-140
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• 2018

In this study, we analyzed the electric vehicle (EV) purchasing behavior with market segmentation in Seoul using the binary logit model. For the model estimation, the experimental design of SP survey generated 24 scenarios with purchase price, charging station availability, and driving range of EVs. The results of market segmentation analysis indicated that the owners of subcompact and compact size cars were primarily affected by the purchasing price while those of mid and full size cars were more sensitive to the charging station availability. By housing type, the charging station availability was the most important factor for the residents of apartment while the purchase price was the most important factor to choose the EVs. These results presented that the EV supply strategy of the automobile manufacturer should be diversified according to the marketing target and the expansion of the public charging infrastructure should be the top priority in the government policy.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.667-675
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• 2016

This study aims to investigate the effects of regular participation in physical activity on personal happiness by analyzing the "2014 National Leisure Sports Participation Survey". By using cross-tabulation and the binary logit model, it is found that there is a positive correlation between those two variables. The effect of positive affect on happiness index was found to be influenced by age, education level, occupation, income, marital status, appear. The results of the analysis of the relationship between the presence of sports facilities and the participation of regular physical activity using crosstab analysis and the analysis of physical activity showed positive relationship between two variables. Hence, it is expected that providing more opportunities to participate in sports programs can lead the public to more regular participation in physical activity.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.534-540
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• 2020

Like most developed countries, South Korea is experiencing a severe lack of seafarers. Because young people's demands for a high quality of life has led them to seek shore-based careers. The wage difference between seafaring and shore-based careers has been decreasing gradually, however South Korea's unique Boarding Service Reserve System Policy has helped recruit and retain young sailors and, since 2017, the government has focused on creating new jobs and stabilizing the status of irregular workers in both private and public sectors. It specifically established the Economic, Social & Labor Council to carefully analyze seafarers' employment stability, which previously had been overlooked in the country. This research used the Binary Logit Model (BLM) to analyze the determinants of seafarers' employment stability in both permanent and non-permanent positions. We found that seafarers' employment stability correlated highly with their education level. This means that seafarers who graduated from the above mentioned two maritime universities would have more job stablity than those who graduated from maritime high schools or general universities. Other independent variables, such as the shipping company, vessel, hip management companies, work assignment, rank, and license had no significant impact on employment stability.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.189-195
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• 2006

For the past decades, vehicle emissions has been a major source of air pollution in urban areas Vehicle inspection and maintenance (I/M) test programs were developed for major metropolitan areas to reduce urban air pollution. However. there are a few studies of exploring major factors to influence I/M test failure. This study develops a logit model to identify key factors affecting overall test failure, using the vehicle I/M test data from California in October 2002. The model results indicate that vehicle age, odometer reading, engine size, vehicle make, presences of emissions control equipment, and test types have significant effects on the probability of I/M test failure.

• The Korean Journal of Community Living Science
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• v.24 no.1
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• pp.51-70
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• 2013

The purpose of the study was to analyze the determinants on the absence of after-school care among elementary students. This study is based on the National Children and Youth Panel Survey(2010) data and analyzed through Binary Logit Model and Multinominal Logit Model. The Following results were obtained: First, school grades, the number of siblings, mother's education, family type by parental employment, family structure, family type by parental nativity, and family income, all affected the absence of after-school care. Second, the absence days of after-school care was affected by different factors. 1day-2days a week in absence of after-school was more likely to increase among children with more siblings and an older father. On the other hand, spending over 3-4days a week without after-school care was more likely to increase among mothers with lower education, dual-earner families, multicultural families, lower family incomes, small cities and rural areas. Based on the results of this study, we agree with the generalization and the diversification of after-school care policy for elementary school students.

• Journal of the Korean Home Economics Association
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• v.48 no.6
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• pp.83-101
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• 2010

Using the first wave of KLoSA(Korean Longitudinal study of Aging) beta version, this study analyzed factors affecting retirement adjustment by elapsed time from retiree's retirement through Binary Logit and Multinomial Logit Analysis. Participants were 1,780 retiree. The main results of this study were as follows : First, The retiree's education(-), health status(-), region(+), dwelling type(-), monthly household income(-), employment type before retirement(+), retirement reason(+), and the elapsed time from retirement(-) were affected whether they satisfied with pre-retirement or not. Second, The gender(-), age(-), and the region(+) were affected whether they satisfied with life after retirement or not. Third, The gender(-), age(-), education(+), heath status(+), dwelling type(+), monthly household income(+), retirement reason(-), and the elapsed time from retirement(+) were affected on their satisfaction after retirement compared to pre-retirement. Last, The different factors affected the life satisfaction after retirement by elapsed time from retirement.

• Health Policy and Management
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• v.25 no.4
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• pp.323-332
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• 2015

Background: Antibiotic resistance has been becoming serious challenge to human beings. Overuse of antibiotics, especially, for infants is concerned, but studies are very few for the prescribing pattern of antibiotic use for infants. This study analyzes prescribing patterns of antibiotics in outpatients of preschool children with acute respiratory tract infections in South Korea. Methods: Data are used from 2011 Health Insurance Review & Assessment Services-pediatric patients sample. Inclusion criteria is outpatient children (0 to 5 years) with top five frequent diseases. Prescription rates are analyzed by types of disease, provider, specialty, region, and ages. Binary or multinomial logit models are used to analyze determinants of providers' prescription pattern. Results: The main findings are as follows. First, distributions of prescription rates are shown as L-shape or M-shape depending on the types of disease. Second, the prescription variation is so large among providers, where providers are polarized as a group with low prescription rates and the other group with high prescription rates, though the shapes are shown diversified across types of disease. Third, prescription rates appear to be lower in pediatrics and higher in ENT (ear-nose-throat). Fourth, broad spectrum antibiotics are widely used among children. Finally, the logit analysis shows similar results with descriptive statistics, but partly different results across types of disease. Conclusion: Antibiotics for respiratory tract infections of infants are used excessively with a large variation among providers, and especially broad spectrum antibiotics are used. The prescription guideline for antibiotics should be provided for each specific disease to reduce antibiotic resistance in the future.

• Journal of Information Technology Application
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• v.1
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.