• 한국노년학
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• v.40 no.4
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• pp.639-657
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• 2020

The purpose of this study is to analyze the effect of individual differences in recognition of retirement responsibility on financial preparedness for retirement and to examine moderating effect of income-level on the relationships between the two variables, using the 7th Korean Retirement and Income Study(KReIS). Two research methods, descriptive analysis and hierarchical multiple logistic regression(HMLR) analysis, have been conducted. The total number of sample was 3,869 subjects with an average age of 58.9 years and 55.3% males. The results show that only 35.8% of the respondents make financial plans for retirement, and 64.2% did not. Main findings are as follows. First, 65% of respondents take a responsibility for financial preparedness for retirement, compared to 37% in European countries. Second, people with responsibility for their own retirement are more likely to have a financial preparation for retirement than people who think others(family, society, government) have to take a responsibility for retirement instead of them. Third, there is a significant moderating effect of income-level on relationships between recognition of retirement responsibility and financial preparedness for retirement. As income level decreases, the moderating effect reduces the positive effect of recognition of retirement responsibility on financial preparedness for retirement and vice versa. Fourth, as income level increases and educational level is higher, the tendency to prepare financially for retirement is also increasing. Low-income and low-educated people are less likely to have a financial preparation for retirement than their counterparts. The findings suggest that it is necessary to design an effective incentive scheme for financial preparedness for retirement for low-income and low-educated people and to develop various policies and services to encourage them to prepare financially for retirement.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.143-159
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• 2017

Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.301-311
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• 2013

This study aims to analyze characteristics, health behaviors and health management level related to private health examination recipients in one general hospital. To achieve this, we analyzed 150,501 cases of private health examination data for 11 years from 2001 to 2011 for 20,696 participants in 2011 in a Dae-Jeon general hospital health examination center. The cluster analysis for classify private health examination group is used z-score standardization of K-means clustering method. The logistic regression analysis, decision tree and neural network analysis are used to periodic/non-periodic private health examination classification model. 1,000 people were selected as a customer management business group that has high probability to be non-periodic private health examination patients in new private health examination. According to results of this study, private health examination group was categorized by new, periodic and non-periodic group. New participants in private health examination were more 30~39 years old person than other age groups and more patients suspected of having renal disease. Periodic participants in private health examination were more male participants and more patients suspected of having hyperlipidemia. Non-periodic participants in private health examination were more smoking and sitting person and more patients suspected of having anemia and diabetes mellitus. As a result of decision tree, variables related to non-periodic participants in private health examination were sex, age, residence, exercise, anemia, hyperlipidemia, diabetes mellitus, obesity and liver disease. In particular, 71.4% of non-periodic participants were female, non-anemic, non-exercise, and suspicious obesity person. To operation of customized customer management business for private health examination will contribute to efficiency in health examination center.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of agricultural medicine and community health
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• v.24 no.2
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• pp.269-289
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• 1999

This study was conducted to examine the relationship among health concern, health practice and ADL of elderly staying at home in a rural community and their affecting factors. Data were collected through direct interviews made with 480 old people aged more than sixty-five from November 15, 1998 to December 20, 1998. Out of 189 male and 291 female, the high-level group that showed high health concern accounted for 44.4%, the medium-level group for 13.1%, and the low-level group for 42.5%, in the health practice, the high-level group accounted for 3.8%, the medium-level group for 18.8%, and the low-level group for 77.5%. In the self-rated health status, the high-level group accounted for 29.0%, the medium-level group for 31.0%, and the low-level group for 40.0%, and in the ADL, the high ADL group accounted for 91.5%, and the low-level ADL group for 8.5%. The result of the chi-square test showed that for male, there was a significant relation between the health concern and the health practice index score. In the relation between the health practice index score and the self-rated health status, there was significant positive relationship between health practice index and self-rated health status, and in the relation between the health practice Index score and the ADL, old people with higher health practices showed good ADL(but not significant). Old people with good ADL also showed good self-rated health status. In the multiple regression analysis where the health practice was used as a dependent variable, the health concern was added to the sociodemographic variables as an independent variables, a formula was formed for male old people only and ones with high concern in health showed good health practice. In the multiple logistic regression analysis where the sociodemographic variables to which the health practices was added were used as an independent variable and the ADL as a dependent variable, the ADL appeared to be not good if for male old people the living costs were born by their sons and daughters and as for female old people their ages increased, but it was good if old people had sources of health information such as hospitals or health centers. The self-rated health status was worse, for male old people, if they had short living costs or diseases and for female old people, if they had spouses, living costs born by their sons and daughters or diseases, but it was better, for male old people, if they had periodical gatherings or carried out health practices a lot, and for female old people, if they had sources of health information such as hospitals or health centers or carried out health practices a lot. In view of the results stated above, the higher the old people had health concern, the more they carried out health practices, and the more they carried out health practices, the better they had ADL and self-rated health status that served as the level of health. Further, the better ADL, the better self-rated health status.

• Journal of Hospice and Palliative Care
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• v.19 no.1
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• pp.61-69
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• 2016

Purpose: It is important to alleviate care burden for terminal cancer patients and their families. This study investigated the factors associated with care burden among family caregivers (FCs) of terminally ill cancer patients. Methods: We analyzed data from 289 FCs of terminal cancer patients who were admitted to palliative care units of seven medical centers in Korea. Care burden was assessed using the Korean version of Caregiver Reaction Assessment (CRA) scale which comprises five domains. A multivariate logistic regression model with stepwise variable selection was used to identify factors associated with care burden. Results: Diverse associating factors were identified in each CRA domain. Emotional factors had broad influence on care burden. FCs with emotional distress were more likely to experience changes to their daily routine (adjusted odds ratio (aOR), 2.54; 95% confidence interval (CI), 1.29~5.02), lack of family support (aOR, 2.27; 95% CI, 1.04~4.97) and health issues (aOR, 5.44; 2.50~11.88). Family functionality clearly reflected a lack of support, and severe family dysfunction was linked to financial issues as well. FCs without religion or comorbid conditions felt more burdened. The caregiving duration and daily caregiving hours significantly predicted FCs' lifestyle changes and physical burden. FCs who were employed, had weak social support or could not visit frequently, had a low self-esteem. Conclusion: This study indicates that it is helpful to understand FCs' emotional status and family functions to assess their care burden. Thus, efforts are needed to lessen their financial burden through social support systems.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.322-331
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• 2017

District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

• Journal of Nutrition and Health
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• v.47 no.4
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• pp.247-257
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• 2014

Purpose: It is reported that most senior people consume a high carbohydrate diet, while a high carbohydrate diet could contribute to the risk of chronic disease. The aim of this study is to determine whether a high carbohydrate diet can increase the risk of chronic disease in elderly Koreans. Methods: Using the 2007-2009 Korean National Health Nutrition Examination Survey data, out of a total of 3,917 individuals aged 65 and above, final 1,535 subjects were analyzed, divided by dietary carbohydrate energy ratio into two groups of moderate carbohydrate ratio (MCR, 55-70%) and excessive carbohydrate ratio (ECR, > 70%). All data were processed after the application of weighted value, using a general linear model or logistic regression. Results: Eighty one percent of elderly Koreans consumed diets with carbohydrate energy ratio above 70%. The ECR group included more female subjects, rural residents, lower income, and lower education level. The ECR group showed lower waist circumference, lower diastolic blood pressure, and lower frequency of consumption of meat and egg, milk, and alcohol. The intake of energy and most nutrients, with the exception of fiber, potassium, vitamin A, and carotene, was lower in the ECR group compared to the MCR group. When analyzed by gender, the ECR group showed lower risk of dyslipidemia in male and obesity in female subjects, even though the ECR group showed low intake of some nutrients. No difference in the risk of hypertension, diabetes, and anemia was observed between the two groups in male or female subjects. Conclusion: This result suggested that a high carbohydrate diet would not be a cause to increase the risk of chronic disease in the elderly. Further study is needed in order to determine an appropriate carbohydrate energy ratio for elderly Koreans to reduce the risk of chronic disease.

• Journal of agricultural medicine and community health
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• v.38 no.2
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• pp.116-129
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• 2013

Objectives: This study was performed to identify the associations of social capital with suicidal thoughts and attempts in Korean communities with poor health. Methods: We used the data from community health interviews conducted at 40 administrative sections (dong, eup, or myeon) with high mortality from August to October in 2010, 2011, and 2012 as part of the Health Plus Happiness Plus Projects in Gyeongsangnam-do Province. The 8,800 study subjects composed of 220 adults systematically sampled from each administrative section were asked if they had thought about suicide or had attempted suicide within 1 year. The social participation was measured with 'participation in formal and/or informal group' and trust using responses to three questions about trust of others. Results: The prevalence of suicidal ideation and attempt within 1 year were 10.4% and 0.8%, respectively. The logistic regression analysis revealed that those who participated in only informal groups, or had highest trust level reported less suicidal ideation, or attempt after adjusting for socio-demographic factors (sex, age, marital status, occupation, and food affordability), self-rated health, and health behaviors (smoking, alcohol drinking, and exercise). Conclusions: This study suggested social capital such as social participation and trust was associated with less suicide ideation and attempt. More studies are warranted for the association of social capital with suicidal behavior.

• Korean Journal of Social Welfare Studies
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• v.48 no.3
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• pp.171-208
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• 2017

The purpose of this study is to classify the underlying and parsimonious types of child maltreatment and examine whether the effects of risk factors on child maltreatment recurrence differ by type of maltreatment. We utilized the multiyear national administrative data from the National Child Maltreatment Information System collected by Child Protection Agency in Korea. Of 26,921 child maltreatment victims reported and substantiated on or after January 1, 2012, 1,447 children who had recurrence of child maltreatment until December 31, 2015 were selected as maltreatment recurrence group and 4,580 children who had not experienced maltreatment since first substantiation were assigned as maltreatment non-recurrence group. Latent class analysis(LCA) and latent transition analysis(LTA) were used to group children with similar maltreatment subtypes into discrete classes of child maltreatment recurrence. Logistic regression is employed to examine the association between the child maltreatment predominant types and risk factors for recurrence. Results of LCA and LTA showed four latent classes representing predominant type of child maltreatment: 'physical abuse predominant type', 'emotional abuse predominant type', 'sexual abuse predominant type', and 'neglect type'. Significant differences in the effect of risk factors among latent classes were found in child's age and gender, perpetrator's gender, family poverty, biological parent as the perpetrator, domestic violence toward partner, perpetrator's alcoholic problem, insufficient parenting skills, and out-of-home care service, Based on these findings, results suggested how the typology can be used to guide decision about who to target in prevention and intervention programs, and which features of risk factors to target. Practice and policy implications as well as further research tasks were discussed in the lights of searching for useful and important strategies to prevent recurrence of child maltreatment.