• Journal of dental hygiene science
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• v.13 no.3
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• pp.254-263
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• 2013

This study is to develop an evaluation index for infection control and to verify its validity by examining each set of weighted data collected from 121 infection control personnel at dental hospitals who agreed to the preliminary survey and advisory. The study was conducted from 14th December, 2010 to 31st January, 2011, and PASW Statistics 18.0 and AMOS 5.0 had been used for the statistical data analysis. As a result of the study, five evaluation factors with 21 sub-indicators have been identified at structural level, eight evaluation factors with 32 sub-indicators at processing level, and one evaluation fact with five sub-indicators at resulting level, total 14 evaluation factors with 58 sub-indicators throughout all levels. The path analysis added on the result that 'standard precautions ($x_1$)', 'infection control support system ($x_2$)', 'internal and external characteristics ($x_3$)' are exogenous variables that affect on other variables, and 'standard infection control ($y_1$)','Organization equipment management handwashing ($y_2$)', 'environmental infection control ($y_3$), 'personal protective equipment ($y_4$)', 'waste and laundry management ($y_5$)' are endogenous variables that are infulenced by others. The standardized metrics are more needed than anything else when examining on infection control. This study attempts to develop proper dental infection control metrics adequately adjusted for domestic circumstances, and therefore to contribute to effective systematic management and decision-making in infection control.

• Korean Journal of Poultry Science
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• v.43 no.4
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• pp.273-279
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• 2016

Recently, it was reported that certain polymorphisms in the growth hormone secretagogue receptor gene (GHSR) are associated with the growth of chickens. However, the correlation between GHSR polymorphisms and economic traits has not been investigated in Korean native chickens (KNCs). Therefore, the objective of this study was to confirm the suitability of the GHSR gene as a candidate for genomic selection and identify a genetic marker for KNCs. A total of 220 KNCs from six breeds raised at the National Institute of Animal Science were genotyped for the c.739+726 SNP in the GHSR gene using polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP), and the sequence for a subset of 30 birds was analyzed using direct sequencing. The association between the SNP genotypes and the economic traits of the KNCs was analyzed using the statistical package for the social science (SPSS) software program. The association analysis between the c.739+726T>C SNP and economic traits revealed that the SNP was significantly associated with body weight at 150 and 270 days (BW150 and BW270, respectively) in all KNCs (p<0.01), BW150 in KNC (Gary) (p<0.05), and egg production number in KNC (White, p<0.05). In addition, the SNPs discovered using direct sequencing (513A>G, 517A>T) had a significant effect on the body weight and egg production traits (p<0.05). In conclusion, these results might be useful as a basis for studies on the improvement of KNC breeds. Furthermore, these results suggest that the SNPs (c.739+726T>C, 513A>G, and 517A>T) located in the GHSR gene could be useful molecular genetic markers for KNCs.

• Korea journal of population studies
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• v.26 no.2
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• pp.1-32
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• 2003

An analysis on cause-specific mortality at the provincial level provides essential information for policy formulation and makes it possible to draw hypotheses regarding various diseases and causes of death. Although the mortality level and causes of death at the provincial level are determined by the multiple effects of socioeconomic, cultural, medical and ecological factors, this study primarily intends to examine similarities and differences of cause-specific mortality at the provincial level. Utilizing the registered death and the registered population as of 1998, the delayed death registration and unreported infant deaths were supplemented at the provincial level and age-standardized death rates and life tables were calculated. Regarding the mortality level due to all causes, major findings were as follow: (1) For both sexes as a whole, Seoul showed the lowest mortality level, and Jeonnam showed the highest mortality level; and (2) The differences of the mortality level among provinces were greater for males than females and for those less than 65 years than those 65 years and over. Regarding the cause-specific mortality level revealed in all indicators (cause-specific age-standardized mortality rates and the probability of dying at birth due to a specific cause for males, females, and both sexes combined respectively), the major findings were as follow: (1) The mortality level due to heart diseases was the highest in Busan and the lowest in Gangweon; (2) The mortality level due to liver diseases was the highest in Chonnam; and (3) The mortality level due to traffic accidents was the highest in Chungnam and the lowest in Inchon. As the mortality differentials at the provincial level are related to various factors, exploratory statistical analysis is attempted for the 25 explanatory variables including socioeconomic variables and 90 mortality variables. Mortality due to all causes are related to socioeconomic variables. Among cause-specific mortality, mortality due to liver diseases and traffic accidents is related to socioeconomic variables. Finally, the need to improve the quality of death certificate is discussed.

• Radiation Oncology Journal
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• v.25 no.3
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• pp.145-150
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• 2007

Purpose: To investigate the degree and effect of cyclooxygenase (COX)-2 expression on the survival of patients with glioblastoma multiforme (GM). Materials and Methods: Between 1997 and 2006, thirty consecutive GM patients treated with surgery and postoperative radiotherapy (dose range: $44{\sim}65.1$ Gy, median dose: 61.2 Gy) were included in the study. Three patients were excluded that discontinued radiotherapy before receiving a dose of 40 Gy due to mental deterioration. The expression of the COX-2 protein in surgical specimens was examined by immunohistochemical analysis. Survival analysis and verification were performed with respect to sex, age, performance status, resection extent, radiotherapy dose, and degree of COX-2 expression using the Kaplan-Meier method and the log rank test. Results: The median length of follow-up was 13.3 months (range:$6{\sim}83$ months). Staining for COX-2 was positive in all patient samples. Staining for COX-2 that was positive for over 75% of the tumor cells was found in 24 patients. Staining for COX-2 that was positive in less than 25% of tumor cells was found in 3 patients (10.0%), staining for COX-2 that was positive in 25 to 50% of tumor cells was found in 1 patient (3.3%), staining for COX-2 that was positive in 50 to 75% of tumor cells was found in 2 patients (6.7%) and staining for COX-2 that was positive in 75 to 100% of tumor cells was found in 24 patients (80.0%). The median survival and two-year survival rate were 13.5 months and 17.5%, respectively. The survival rate was influenced significantly by the degree of resection (tumor removal by 50% or more) and radiotherapy dose (59 Gy or greater) (p<0.05). The median survival of patients with staining for COX-2 that was positive in less than 75% of tumor cells and in at least 75% of tumor cells was 15.5 and 13.0 months, respectively (p>0.05), and the two-year survival for these groups was 33.3 and 13.3%, respectively (p>0.05). Conclusion: The absence of a statistical correlation between the degree of COX-2 expression and survival in GM patients, despite the high rate of COX-2 positive tumor cells in the GM patient samples, requires further studies with a larger series to ascertain the prognostic value of the degree of COX-2 expression in GM patients.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• The Journal of Korean Medicine
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• v.30 no.1
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• pp.109-119
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• 2009

Objectives: This study was aimed to clarity the relationship between the pattern of dampness-phlegm and metabolic syndrome in acute stroke patients. Methods: Three hundred fifty-nine subjects were recruited from the patients admitted to the Internal Medical Department at Kyunghee University Oriental Medical Center, Donggnk University Ilsan Oriental Medical Center, Kyungwon University Songpa Oriental Medical Center and Kyungwon University Incheon Oriental Medical Center from April 2007 to March 2008. We diagnosed dampness-phlegm by Oriental medical diagnosis and analyzed their characteristics with type of stroke, blood test result, Sasang constitution, lifestyle and metabolic syndrome. Results: I. On the demographic variables of the patients, the weight and body mass index, the rate of hypertension, diabetes mellitus, hyperlipidemia, silent infarction were significantly higher in dampness-phlegm group than in the control. 2. There was no significant difference of stroke type between the dampness-phlegm group and the control. 3. According to the blood test, the dampness-phlegm group showed higher total cholesterol, triglyceride, fasting blood sugar and lower high density lipoprotein cholesterol than the control group with statistical significance. 4. According to the Sasang constitution distribution, the rate of Tae-Eum was significantly higher in dampness-phlegm group than in the control. 5. According to lifestyle, smoking and drinking were significantly lower in the dampness-phlegm group than in the control. Otherwise, exercise and dietary habits showed no significant difference between the two groups. 6. There were much more patients diagnosed with metabolic syndrome in the dampness-phlegm group than in the control. 7. Metabolic syndrome, silent infarction and obesity showed close relationship with dampness-phlegm pattern in multivariate analysis. Conclusions: According to the analysis, the relationship between the patterns of dampness-phlegm and metabolic syndrome in acute stroke patients were clarified. These results can be utilized in the future as a basis material.

• Journal of Distribution Science
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• v.10 no.4
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• pp.37-45
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• 2012

The popularity of courier services in Korea has made it an essential part of the country's domestic logistics industry, bolstering the growth not only of the national economy, but also the quality of people's daily lives. An effective strategy for courier companies in Korea would be to provide high-quality services to their existing target markets with the goal of maximizing customer loyalty. This study investigates structural relationships between customer loyalty and service quality as a set of factors and between customer trust and customer satisfaction. These antecedent relationships will be used to understand the "performance formation model" through service quality. In this study, service quality, as a set of factors, is considered to be the independent variable, while customer satisfaction and customer trust are both treated as intervening variables. Finally, customer loyalty is the dependent variable. Following a review of the literature, this paper's proffered hypothesis will be investigated in terms of whether the independent and intervening variables significantly affect customer loyalty. A statistical analysis of the empirical research was carried out using both SPSS 18.0 and AMOS 18.0 The results of this study's empirical analysis show three conclusions. First, among the intervening variables (customer satisfaction and customer trust), customer satisfaction is significantly correlated with customer loyalty. Customer trust, however, was shown to have little or no relationship to customer loyalty. Second, the quality of service variable seems to influence customer satisfaction, customer trust, and customer loyalty. Third, with respect to the relationship of intervening variables, customer trust affects customer satisfaction. Thus, the companies that have a competitive advantage in Korea have successfully maximized customer loyalty for their existing customers. Courier companies will need to research and study customer needs. Therefore, this research suggests that effective courier service management can be better understood through the application of the service quality performance formation model, which can enhance the quality of service provided by domestic courier services. This research is limited to investigating qualitative variables, such as the service quality factors, customer satisfaction, and customer trust. It would be helpful for future research on courier services to consider quantitative variables, such as price and weight.

• Journal of agricultural medicine and community health
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• v.36 no.1
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• pp.1-12
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• 2011

Objectives: The purpose of this study was to find out the suicide ideation of high school students in urban and rural areas, and especially to research the relationship between suicide ideation, and general characteristics, characteristics of school life, and empirical characteristics of suicide. Methods: This research targeted four urban and four rural high schools in two cities. The study subjects were 1,114 students in urban area and 968 students in rural area, total 2,082 students. The survey was conducted from July 1, 2009 to July 31, 2009. For statistical analysis, chi-square test, t-test and ANOVA were used for investigating related factors with suicide ideation in urban and rural areas, respectively, with multiple logistic regression for multivariate analysis. Results: The results showed that 38.8% of respondents had suicide ideation within 1 year. The percentage of female students (44.8%) was significantly higher than that of male students (33.4%). However, there was no significant difference between urban (38.0%) and rural area (39.9%). The significant influencing factors on suicide ideation in multiple logistic regression were gender [female student OR(odds ratio)=1.80 (95% CI 1.31-2.47) compared with male student] and grade [second year OR=1.40 (95% CI 0.98-2.00), third year OR=2.15 (95% CI 1.49-3.12) compared with first year] in urban area. Those in rural area were gender [female student OR(odds ratio)=2.71 (95% CI 1.23-2.38) compared with male student], economic deterioration [yes OR=1.81 (95% CI 1.24-2.64) compared with no], and grade [second year OR=2.80 (95% CI 1.82-4.32), third year OR=3.84 (95% CI 2.52-5.87) compared with first year]. Conclusions: This study showed about 40% of high school students had suicide ideation within 1 year. A suicide prevention program may be implemented considering factors related with suicide ideation identified in this study.

• Journal of agricultural medicine and community health
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• v.42 no.3
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• pp.132-144
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• 2017

Objectives: The purpose of this study was to identify the association between satisfaction with assistive technology devices and psychosocial impact among some mentally or physically disabled children. Methods: The study subjects were 120 disabled children and their primary caregivers who were using rental assistive technology devices in Gwangju and Jeollanam-Do. Data were collected by structured questionnaire composed of general characteristics of subjects, characteristics related with using assistive devices. Quebec User Evaluation of Satisfaction with assistive Technology 2.0 (QUEST 2.0) and Psychosocial Impact of Assistive Device Scale (PIADS). The statistical analysis were performed by descriptive statistics, t-test, ANOVA and Pearson's correlational analysis. Results: The total mean score for QUEST 2.0 was $4.08{\pm}0.66$ (satisfaction with devices, $4.01{\pm}0.70$; satisfaction with the assistive devices service, $4.14{\pm}0.90$) and the mean of PIADS was $1.00{\pm}0.75$ (ability, $0.99{\pm}0.78$; adaptability, $1.04{\pm}0.86$; self-respect, $0.99{\pm}0.74$). The scores of PIADS was statistically significant difference according to usage time of assistive devices. The PIADS was significantly positive correlated with QUEST 2.0 Conclusions: The mentally or physically disabled children reported that the higher level of satisfaction and the more positive impact of psychosocial aspect with assistive technology devices. It would be necessary to perform further studies for addressing the effects of assistive technology devices.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.