• Korean Journal of Culture and Social Issue
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• v.17 no.4
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• pp.435-459
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• 2011

The present study explored Korean parents' perceptions of and behavior toward game use among teenagers in Korea. A total of 600 Korean mothers of teenagers residing in Seoul and five other metropolitan areas participated in the survey. The survey was constructed based on five categories of variables, including the overall perception of games and game use, specific attitudes toward game use, cognitions about and attitudes toward game addiction, factors predicting parental monitoring of children's game use, and views and opinions about what needs to be done to promote healthy game cultures as well as to prevent problematic game use among teenagers in Korea. Results indicate that the respondents' overall perceptions of and attitudes toward games and game use are negative. In contrast, attitudes toward game use of the respondent's own child are contingent upon various comparison standards. Results also indicate that the respondents tend to overestimate the possibility that their own child is addicted to games, and their perceptions of game addiction are based on a narrow range of behavioral symptoms. Additional analyses indicate that parental monitoring of teenagers' game use can be predicted by the theoretical model driven from Ajzen(1991)'s theory of planned behavior. Finally, results also indicate that, in order to deal with the problems associated with teenagers' game use, proactive approaches to promote healthy game cultures as well as various initiatives to prevent problematic game use are necessary. Implications of the findings and future direction were discussed.

• 한국노년학
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• v.38 no.4
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• pp.1035-1055
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• 2018

The purpose of this study is to investigate the relationship between public care and family care. Public care for older adults began in 2008 with the implementation of the Long-Term Care insurance in South Korea. Although the expansion of public care has the purpose of reducing the care burden for the family, it is not easy to say whether the developments of public care system reduce the amount of family care for older family members. Theoretically, public care and family care are expected to have various relationships depending on the degree of the role and function(substitution, hierarchical compensatory, task specific, supplementation, complementarity). And literatures have showed inconsistent results depending on the country, data, and methods. In this study, we analyzed the relationship between two care types focusing on home care services for older persons. Analyses were based on data from the second(2008) to sixth(2016) waves of Korean Longitudinal Study of Ageing(KLoSA). To investigate elderly care dynamics in the households, we pooled the data for four changes between two periods(2008-2010, 2010-2012, 2012-2014, and 2014-2016). This study used an analytic sample of 262 older adults, who are aged 55 over and experienced public care at least one point of time. We used Fixed-Effects(FE) model to analyze the differences within the same individuals under the condition that time-invariant unobserved factors are controlled. This study distinguished the cases of entry into public care and other cases of exiting public care. The results showed that older people who are dependent on public care are less dependent on family care than before. In both entry and exit groups, negative relations were maintained, but in the entering stage of public care, the degree of negative relations was relatively small, whereas in the stage of maintaining or departing from public care, relatively negative relations were strong. At the beginning periods, even though public care increased, family care did not decrease significantly. On the other hand, at the time of ending public care and relying on family care, family care increased significantly. The results of this study show that the relationship between public care and family care is close to hierarchical compensatory model and varies according to the stage of caring transition. Also, it was found that the cases of transition from public care to family care have the biggest burden of elderly care than other groups.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Digital Convergence
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• v.11 no.6
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• pp.11-21
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• 2013

Though adolescents have the skillful ability to use internet and use it extensively, they have experienced sexually less than adults and are hard to have the right viewpoint toward sexuality. Because of these adolescents' characteristics, internet pornography cause them serious troubles with their sexual behavior. Based on the viewpoint, this research explores structural relationship among their sexual orientations, exposure to internet pornography, the sexual drive and behavior with PLS path modeling analysis. In result, androcentric and pornography-friendly sexual orientation have an influence on the exposure to internet pornography, in turn, the exposure to internet pornography affect the sexual drive and behavior directly and sexual behavior indirectly mediated by the drive. The significance of this research is to identify fact that sexual orientations, reconceptionalized from previous researches's dependent variables, predict the exposure to internet pro-pornographic and is to identify a popular myth indirectly that the exposure to internet pornography stimulates sexual drive to cause behavior, in turn leads to sex crimes finally.

• Journal of Technology Innovation
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• v.22 no.2
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• pp.185-220
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• 2014

The purpose of this study is to get a whole picture of financial conditions of the new and renewable energy sector which have been growing rapidly and predict bankruptcy risk quantitatively. There have been many researches on the methodologies for company failure prediction, such as financial ratios as predictors of failure, analysis of corporate governance, risk factors and survival analysis, and others. The research method for this study is Altman Z-score which has been widely used in the world. Data Set was composed of 121 companies with financial statements from KIS-Value. Covering period for the analysis of the data set is from the year 2006 to 2011. As a result of this study, we found that 38 percent of the data set belongs to "Distress" Zone (on alert) while 38% (on watch), summed into 76%, whose level could be interpreted to doubt about the sustainability. The average of the SMEs in wind energy sector was worse than that of SMEs in solar energy sector. And the average of the SMEs in the "Distress" Zone (on alert) was worse than that of the companies of large group in the "Distress" Zone (on alert). In conclusion, Altman Z-score was well proved to be effective for New & Renewable Energy Industry in Korea as a result of this study. The importance of this study lies on the result to demonstrate empirically that the majority of solar and wind enterprises are facing the risk of bankruptcy. And it is also meaningful to have studied the relationship between SMEs and large companies in addition to advancing research on new start-up companies.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.1
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• pp.42-62
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• 2012

This paper suggests a genuine method to estimate the agglomeration effects of Industrial Cluster focusing on the FOODPOLIS (KOREA NATIONAL FOOD CLUSTER). In this study, we will focus on two issues related to the clustering effect. First, Clusters affect productivity, and a cluster allows companies to operate more productively in inputs; accessing technology, human resource, information, services, and needed institutions. Second, we assume that the effects of Industrial Cluster can be estimated from measurement on differency of an added value between large-scale enterprises and smaller ones. To demonstrate effectiveness of this approach, the estimated effect was compared with that from the related study (A Mini-Cluster). Industry Clusters have been considered as critical factors for regional competitiveness and economic revitalization. For this, the government and local government should find a way and strategy to provide useful contents that can attract the participation of firms and to secure strategic positioning and competition strategies.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.2
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• pp.179-200
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• 2021

This study is aimed at analyzing cases of management focusing on a reading club using the blended learning at school library and the relevant programs of the free semester system. Therefore, the study has designed a research model for the blended-based management of school libraries, and cases of activities of reading clubs at school libraries for participants in programs linked with the free semester system have been analyzed. As a result of the analysis, first, the confidence level was satisfied in all areas of stability, consistency, predictability and verification on confidence level for related variables of the research model. Second, a meaningful relation has been verified in the correlation analysis between the blended activities and activities of the career search and the career design. Third, as a meaningful static effect has been shown in the contact-free activities in the areas of activities of the blended learning and activities of the career search and the career design, it was verified that programs linked with reading clubs of the free semester system have higher positive effects in the contact-free activities. Last but not least, programs related to local governments to support reading clubs at school libraries have been presented, and management of the blended learning at school libraries has been suggested.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.25-39
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• 2023

As the scope of supply chains expands globally, unpredictable risks continue to arise. The occurrence of these supply chain risks affects port cargo throughput and hinders port operation. In order to examine the impact of global supply chain risks on port container throughput, this study conducted an empirical analysis on the impact of variables such as the Global Supply Chain Pressure Index (GSCPI), Shanghai Container Freight Index (SCFI), Industrial Production Index, and Retail Sales Index on port traffic using the vector autoregressive(VAR) model. As a result of the analysis, the rise in GSCPI causes a short-term decrease in the throughput of Busan Port, but after a certain point, it acts as a factor increasing the throughput and affects it in the form of a wave. In addition, the industrial production index and the retail sales index were found to have no statistically significant effect on the throughput of Busan Port. In the case of SCFI, the effect was almost similar to that of GSCPI. The results of this study reveal how risks affect port cargo throughput in a situation where supply chain risks are gradually increasing, providing many implications for establishing port operation policies for future supply chain risks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.583-595
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• 2014

Currently, Korean transportation policies are aiming for increase of safety and environment-friendly and efficient operation, by avoiding construction and expansion of roads, and upgrading road alignments and facilities. This is revealed by that there have been 22 road expansion projects (30%) and 50 road improvement projects (70%) under the 3rd Five-Year Plan for National Highways ('11~'15), while there were 53 road expansion projects (71%) and 22 road improvement projects (29%) under the 2nd Five-Year Plan for National Highways. For more effective road improvement projects, there is a need of choosing projects after an objective and scientific safety assessment of each road, and assessing safety improvement depending on projects. This study is intended to develop a model for this road safety analysis and assessment. The major objective of this study is creating a road safety analysis and assessment model appropriate for Korean society, based on the HSM (Highway Safety Manual) of the U.S. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. The collected data was processed correlation analysis of each road element was implemented to see which factor had a big effect on traffic accidents. On the basis of these results, then, an accident model was established as a negative binomial regression model.Using the developed model, an Crash Modification Factor (CMF) which determines accident frequency changes depending on safety performance function (SPF) predicting the number of accident occurrence through traffic volume and road section expansion, road geometric structure and traffic properties, was extracted.

• The korean journal of orthodontics
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• v.31 no.3 s.86
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• pp.325-333
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• 2001

Optimal orthodontic treatment could be possible when a orthodontist can predict and control tooth movement by applying a planned force system to the dentition. The moment to force(M/F) ratio at the bracket, has been shown to be a primary determinate of the pattern of tooth movement. As various n/F ratios are applied to the bracket on the tooth crown, strain distribution in periodontium can be changed, and the center of rotation in tooth movement can be determined. It is, therefore, so important in clinicalorthodontics to know the strain distribution in a force system of a M/F ratio. The purpose of this study was to analyze the strain distribution in orthodontic force system by strain gauge attached to tooth root, and to evaluate the usage of the method. For this study, an experimental upper anterior arch model was constructed, where upper central incisors, on the root surface of which, 8 strain gauges were attached, were implanted In the photoelastic resin, as in the case of 4mm midline diastema. Three types of closing of upper midline diastema closure were compared : 1. with elastomeric chain(100g force) in no arch wire, 2. elastomeric chain in .016“ round steel wire, 3. elastomeric chain in .016”x.022“ rectangular steel wire. The results were as follows. 1. Strain distributions on labial, lingual, mesial and distal root surface of tooth were able to be evaluated with the strain gauge method, and the patterns of tooth rotation were understood by presuming the location of moment arm. 2. Extrusion and tipping movement of tooth was seen in closing in no arch wire, and intrusion and bodily movement was seen with steel arch wire inserted.