• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.668-677
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• 2012

This study analyzed the related factors affecting to perceived gastritis or perceived enteritis for 11,753 Korean high school seniors who participated in the 2009 Korea Youth Risk Behavior Web-based Survey (KYHRBWS). Of the subjects, 5,685 (47.6%)were male and 6,068(52.4%) were female and 8.7% of the students responded that they had suffered from gastritis or enteritis for a long time and the females had a slightly higher attack rate of gastritis or enteritis. Survey logistic regression models and decision tree analysis were used to calculate odd ratios and 95% confidence intervals. As a result, there was affecting to their stress and health behaviors in the risk of gastritis and enteritis, and that their lower level perceived health, smoking, heavy drinking or starting drinking before they were 13 years old and a higher level of perceived stress significantly affected the risk of gastritis or enteritis in the subjects(p<.001).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4641-4650
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• 2015

This study aims to further strengthen the medical expertise to offer specialized medical care specialization strategies to gain a competitive edge through the customer segmentation of the Regional Public Hospital. Investigation period was selected to study the inpatients 26,658 people January to December 2013. The method of analysis are Cluster analysis and Decision Tree Analysis. In conclusion, female, age over 60, and diseases in musculoskeletal system and connective tissue were commonly selected as identifiers of the target market of Regional Public Hospital. Customers in this target market are loyal to specialized medical service and keeping continuous relationship with these customers through communication and monitoring of results of provided medical service would be important because the effect of word of mouth propagated to other group of customers having equivalent scale of consumption is expected. And the concentration of the scope of medical service of Regional Public Hospital and the collaboration and mutual reliance of medical service under the strategic alliance with other institutions and private hospitals are also needed.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.639-647
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• 2009

From development of computer science, genetic algorithm has been applied to many fields for search like non-linear problem based on various variables and optimization process. Among others, in the data mining field, there are methods to select the best input variables for model accuracy and various predict models which were merged by using the genetic algorithm. In the meantime, to improve and preserve quality of the Hanwoo (Korean cattle) which is represented the agricultural industry in our country, we need to find out outstanding economical traits of Hanwoo in having specific genotype of single nucleotide polymorphism (SNP) which is inherited to next generation. According to, This research proposed the selecting method to find genotype of SNPs marker which affects economical traits of the Hanwoo by using the genetic algorithm. And we selected the best genotypes of the principal SNPs marker by applying to real data on Hanwoo genetic.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1063-1073
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• 2015

In the long-term care insurance (LTCI) system, National Health Insurance Service (NHIS) provide counseling services for beneficiaries and their family caregivers, which help them use LTC services appropriately. The purpose of this study was to develop a Target Selection Model for the Counseling Services based on needs of beneficiaries and their family caregivers. To develope models, we used data set of total 2,000 beneficiaries and family caregivers who have used the long-term care services in their home in March 2013 and completed questionnaires. The Target Selection Model was established through various data-mining models such as logistic regression, gradient boosting, Lasso, decision-tree model, Ensemble, and Neural network. Lasso model was selected as the final model because of the stability, high performance and availability. Our results might improve the satisfaction and the efficiency for the NHIS counseling services.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.311-328
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• 2005

This paper deals with a treatment of nonresponse in farm and fishery household economy surveys in Korea. Since the samples in two surveys were selected by stratified multi-stage sampling and weighted sample means has been used to estimate the population means, we choose a weighted hot-deck imputation method as an appropriate method for two surveys. We investigate the procedure of the weighted hot-deck as well as an adjusted jackknife method for variance estimation. Through an empirical study we found that the method worked very well in both mean and variance estimation in two surveys. In addition, we presented a procedure of forming imputation class and formed four imputation classes for each survey and then compared them with analysis. As a result, we presented two most efficient imputation classes for two surveys.

• The Korean Journal of Applied Statistics
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• v.24 no.3
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• pp.535-546
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• 2011

This study develops statistical models for the binary forecast of Asian dust days over South Korea in the winter season. For this study, we used three kinds of data; the rst one is the observed Asian dust days for a period of 31 years (1980 to 2010) as target values, the second one is four meteorological factors(near surface temperature, precipitation, snowfall, ground wind speed) in the source regions of Asian dust based on the NCEP reanalysis data and the third one is the large-scale climate indices. Four kinds of statistical models(multiple regression models, logistic regression models, decision trees, and support vector machines) are applied and compared based on skill scores(hit rate, probability of detection and false alarm rate).

• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.206-215
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• 2013

In recent years, many companies have heavily invested in introducing production informatization systems in order to strengthen the competitiveness and to satisfy consumer's desires in quickly changing market environment. However, it is not effective due to the lack of understanding of systems and of non-existence of an optimal system for each company. Therefore, in this paper, manufacturing companies were classified according to its properties; size of the firm, type of business, production method and job production. After that, a model has been built to calculate the production informatization level, and it has been applied to 450 companies. Results of 450 surveys would be the base for figuring out strategies of introducing the production informatization to the companies which are wishing to build production informatization systems. Finally, Developed in this paper rule base system refer customized guideline to company that wants to adapt production information system.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.317-325
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• 2020

The purpose of this study is to examine the current status and R&D activities of disabled enterprise, and to find ways to support R&D. Through this study, the company's demand for R&D and the characteristics of companies with active R&D activities were derived, and the research and development support plan was proposed by integrating them. As a result of comparing the location quotient (LQ) of small and medium-sized businesses and disabled enterprise by industry, the number of workers with disabilities showed great specialization by business type. R&D was active in companies with sales of over 2 billion won in four industries including manufacturing. As a result of the research, R&D support for disabled enterprise needs to be supported by categorizing them into field-hardened technology-oriented and innovative technology-oriented, depending on the type of business and the size of the company.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.243-248
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• 2018

The social activities of the elderly are important in successfully achieving aging by providing opportunities for social interaction to enhance life satisfaction. The purpose of this study is to identify the related factors of the elderly social activities and build a statistical classification model to predict social activities. Subjects were 1,864 elderly people (829 males, 1,035 females) who completed the community health survey in 2015. Outcome variables were defined as the experience of social activity during the past month(yes, no). The prediction model was constructed using decision tree model based on Classification and Regression Trees (CRT) algorithm. The results of this study were subjective health, frequency of meeting with neighbors, frequency of meeting with relatives, and living with spouse were significant variables of social participation. The most prevalent predictor was the subjective health level. In order to prepare for the successful aging of the super aged society based on the results of this study, social attention and support for the social activities of the elderly are required.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.795-801
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• 2013

Recently, support vector machine has been widely used in various application fields due to its superiority of classification performance comparing with decision tree and neural network. Since support vector machine is basically designed for the binary classification problem, output coding method to analyze the classification result of multiclass binary classifier is used for the application of support vector machine into the multiclass problem. However, previous feature selection method for output coding based support vector machine found the features to improve the overall classification accuracy instead of improving each classification accuracy of each classifier. In this paper, we propose the novel feature selection method to find the features for maximizing the classification accuracy of each binary classifier in output coding based support vector machine. Experimental result showed that proposed method significantly improved the classification accuracy comparing with previous feature selection method.