• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.267-280
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• 2013

College tuition is a significant economic, social, and political issue in Korea. We conduct a Bayesian analysis of a hierarchical model to address the factors related to college tuition based on a survey data collected by Statistics Korea. A binary response variable is selected depending on if more than 70% of tuition costs are supported by parents, and a hierarchical Probit model is constructed with areas as groups. A set of explanatory variables is selected from a factor analysis of available variables in the survey. A Markov chain Monte Carlo algorithm is used to estimate parameters. From the analysis results, income and stress are significantly related to college tuition support from parents. Parents with high income tend to support children's college tuition and students with parents' financial support tend to be mentally less stressed; subsequently, this shows that the economic status of parents significantly affects the mental health of college students. Gender, a healthy life style, and college satisfaction are not significant factors. Comparing areas in terms of the degrees of correlation between stress/income and tuition support from parents, students in Kangwon-do are the most mentally stressed when parents' support is limited; in addition, the positive correlation between parents support and income is stronger in big cities compared to provincial areas.

• Korean Journal of Plant Resources
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• v.25 no.4
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• pp.407-415
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• 2012

Pinus pumila, which occurs in the northeast Asia, is found limitedly in Daecheongbong area of Mt. Seorak in the South Korea. This population was chosen to study spatial pattern, genetic diversity and spatial genetic structure. There were 48 polymorphic and 30 monomorphic I-SSR markers. A total of 65 individuals which distributed in the study site (40 m ${\times}$ 70 m) showed weakly aggregate distribution (Aggregate Index = 0.871). A total of 40 genets were observed from 65 individuals through I-SSR genotype comparison. Proportion of distinguishable genotype (G/N), genotype diversity (D) and genotype evenness (E) were 61.5%, 0.977 and 0.909, respectively. In spite of the small number and the limited distribution, Shannon's diversity index (I = 0.567) was relatively high as compared with those of other plant species. Spatial autocorrelation using Tanimoto's distance showed that the genetic patch was established within 12 m. Based on Mantel tests, there was relatively low correlation between genetic distance and geographic distance. Therefore, it seems the P. pumila population was formed by many parent trees in early stage. For ex situ genetic conservation of P. pumila, the sampling strategy is efficient at least above 12 m between individual trees.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.424-435
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• 2020

The study was descriptive survey research for establishment of patient safety culture in small and medium-sized hospitals as providing baseline data of educational program regarding safe medication and prevention of near miss on medication, checking influencing factors of nurses near miss experience on medication in small and medium-sized hospital. The collected data was analyzed by SPSS/WIN 20.0 program to obtain mean, frequency, x²-test, independent t-test, one-way ANOVA, logistic regression. The influencing factors of near miss experience on medication was working department and patient safety culture among general characteristic. The nurses who were working in general ward had lesser chance to experience near miss rather than nurses working in special department (Odds ratio:2.23, 95%, Confidence Interval: 1.07~4.67, p=.032). The 1 point higher in patient safety culture, the lesser chance to experience in near miss (Odds ratio: 2.24, 95% Confidence Interval: 1.02~4.95, p=.045). To sum up the result of this study, nurses working in special department had higher chance to experience near miss rather than nurses working in general wards. The higher patient safety culture awareness was the lower near miss was experienced. Thus, miss surveillance system for improvement of nurses' patient safety culture awareness should be developed. Moreover, educational program for medication considering nurses' career and department' character should be requested with simulation training considering and theory education.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.5
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• pp.63-72
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• 2018

The purpose of this study was to analyze the survival rate and survival characteristics of young start-up entrepreneurs supported with public financing, by using non-parametric statistic of Kaplanr-Meier Analysis on non-financial data. Average survival periods of different survival characteristics have been estimated by dividing the age groups into 20s and 30s. After then, the main variables affecting the survival period have been analyzed. 3,825 firms guaranteed by Credit Guarantee Institutions in Korea were used as database for the analysis. 3,242 firms have survived while 583 firms have gone insolvent. The study period was from January 1, 2011 to December 31, 2017. Age-based breakdown of the business founders show that 3 variables in the 20s and 5 variables in the 30s are derived as the significant variables, resulting in the significant differences of each age group. In other words, the start-up support agencies and financial institutions need to develop a credit evaluation system that distinguishes the criteria of age range and find information that reflect the characteristics of entrepreneurs in their 20s as well as developing tailor-made financial products. Also, step-by-step support measures are required for the start-ups of high survival times and make them grow into promising SMEs. Meanwhile, non-financial support plans shall be invigorated along with the financial ones to help the start-ups of low survival times. This study is meaningful in that the survival analysis has been conducted by using the non-financial data of young start-up entrepreneurs. It is expected that the results of this analysis contribute to the enhancement of survival rate of start-ups by providing start-up support agencies and start-up business owners with the unique information of the survival characteristics.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of the Korea Institute of Building Construction
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• v.18 no.2
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• pp.151-159
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• 2018

Accident rate in the construction industry of South Korea is increasing every year, and it represents the highest percentage among industries. This shows that activities performed to prevent safety accidents in the country are not efficient when it comes to reduce the accident rate. In order to resolve this issue, a model for the prediction of human accidents should be established. In addition, it is required a quantification study based on pattern of human accidents. Therefore, the objective of this study is to quantify uncertainty of human accidents risk and predict how to change in various circumstances by using Monte Carlo Simulation. To achieve the objective, first, pattern of human accidents was defined. Second, insurance claim payout and information of human accidents during 14 years in construction site were collected. Third, descriptive analysis is conducted to determine the characteristics of the accident pattern. Fourth, to quantitatively analyze the pattern of the human accidents, the population of each accident occurrence and payout were estimated. Finally, estimated populations was analyzed according to characteristics of distribution by using Monte carlo simulation. In the future, this study can be used as a reference for developing the safety management checklist in construction site and development of prediction models of human accident.

• Survey Research
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• v.4 no.2
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• pp.63-86
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• 2003

The objective of this study was to investigate the existence of starting point bias in the bidding game contingent valuation elicitation technique when determining willingness to pay (WTP) for improving the qualify of running water in Seoul and its vicinity. Of all existing contingent techniques, the bidding game most closely mimics the normal price taking behavior in local markets. Three different starting points (low, medium and high) were used to determine WTP and the existence of starting point bias in the meanwhile respectively. The respondents were randomly assigned to the three different starting point groups in order to ensure homogeneity, so that any variation seen in WTP could be attributed to the starting point effects. And a pretested interviewer-administered questionnaire used to elicit WTP. Non-parametric test and the logit model were used to analyze the data for evidence of starting point bias. In this instance, the high starting point group had a high WTP, and low starting point group had a low WTP. This means there exist starting point bias in estimating WTP by bidding game in this instance. This finding might signal that people may actually be making up their minds on the maximum amount they are willing to pay for running water service as a bidding iterating is going on and is influenced by the starting point used in the bidding game. The problem of slaking point bias can be avoided if the respondent is asked directly for the maximum WTP without payment cards or a bidding game. But such a question is perceived as being very difficult to answer and this leads to problems of non-response and being unrealistic.

• Journal of Korean Society of Forest Science
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• v.87 no.2
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• pp.201-210
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• 1998

Sex ratios, and patterns of tree size and growth variation, resource allocation, spatial and age class distribution between the sexes were investigated in natural populations of the sexual trees, R. trichocarpa and R. sylvestris, and the mainly asexual, clonal tree, R. javanica of the dioecious Rhus (Anacardiaceae) distributed in Korea. Sex ratios for three species exhibited a significant degree of female bias, but among the populations, sex ratios were seen to vary quite widely. The measurement of tree size and annual increment of male trees in R. trichocarpa and R. sylvestris were significantly higher than those of female trees, but not significantly different in R. javanica. In all of the species, flowering branch number per individual and inflorescence number per branch of males outnumbered those of females. Branch number per individual, rachis(leaf) number per branch and rachis(leaf) number per inflorescence were more in females than in males. These results were considered as reproductive efforts to increase the pollen supply in males and the fruit production in females. Spatial distribution analysis in two different populations of R. trichocarpa indicated that males and females were randomly distributed in space, but seedlings were clumped around parental trees. Analysis of age class distributions between the sexual reproduction trees, R. triclaocarpa and R. sylvestris, and the asexual, clonal tree, R. javanica showed a different distribution in frequencies of males and females in each age class. These results showed that sexual and asexual reproduction tree species had almost different preference of habitats, and different sex ratio and annual growth.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.372-379
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• 2017

Software reliability factor during the software development process is elementary. Case of the infinite failure NHPP for identifying software failure, the occurrence rates per fault (hazard function) have the characteristic point that is constant, increases and decreases. In this paper, we propose a reliability model using the chi - square distribution which depends on the degree of freedom that represents the application efficiency of software reliability. Algorithm to estimate the parameters used to the maximum likelihood estimator and bisection method, a model selection based on the mean square error (MSE) and coefficient of determination($R^2$), for the sake of the efficient model, were employed. For the reliability model using the proposed degree of freedom of the chi - square distribution, the failure analysis using the actual failure interval data was applied. Fault data analysis is compared with the intensity function using the degree of freedom of the chi - square distribution. For the insurance about the reliability of a data, the Laplace trend test was employed. In this study, the chi-square distribution model depends on the degree of freedom, is also efficient about reliability because have the coefficient of determination is 90% or more, in the ground of the basic model, can used as a applied model. From this paper, the software development designer must be applied life distribution by the applied basic knowledge of the software to confirm failure modes which may be applied.

• Journal of Korea Water Resources Association
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• v.46 no.3
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• pp.315-326
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• 2013

Despite of the importance on the maintenance of a reservoir storage, relatively few studies have addressed the stochastic reliability analysis including uncertainty on the decrease of the reservoir storage by the sedimentation. Therefore, the stochastic gamma process under the reliability framework is developed and applied to estimate the reduction of the Soyang Dam reservoir storage in this paper. Especially, in the estimation of parameters of the stochastic gamma process, the Bayesian MCMC scheme using informative prior distribution is used to incorporate a wide variety of information related with the sedimentation. The results show that the selected informative prior distribution is reasonable because the uncertainty of the posterior distribution is reduced considerably compared to that of the prior distribution. Also, the range of the expected life time of the dead storage in Soyang Dam reservoir including uncertainty is estimated from 119.3 years to 183.5 years at 5% significance level. Finally, it is suggested that the improvement of the assessment strategy in this study can provide the valuable information to the decision makers who are in charge of the maintenance of a reservoir.