• International Commerce and Information Review
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• v.10 no.4
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• pp.457-491
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• 2008

As stage equipment export markets along with special lighting service lack the attraction for already globally established businesses, such markets can be viewed as an advantageous opportunity for SMEs as in general. In reality, global businesses tend to focus on large construction projects and this indicates relatively less substantial markets such as stage equipment and special lighting service export are more suitable for SME businesses. However, possible problems may be recognized as following; doubtful capabilities by such businesses to join in the vast and competitive global market and pursue manufacturing and service based export. This point is also supported by the fact that such in general SME businesses have substantially less experience in exporting products and services abroad. Realizing the distinctive features of the Korean economy, it is unarguable that every sector and area of global market must be regarded and monitored closely. Hence, it can be argued that there is an imminent need for establishment of supportive institution to assist export process of combination of stage equipments and special lighting service. This study emphasizes the need to improve export process of stage equipments, special lighting services as well as other related products and services which have been focused in domestic market only until now. Further, it also analyzed the potential prospect of such direction reconciling current crisis our manufacturing industry is facing. Even though it maybe regarded as one of the niche market for export of Korea in the short term view, stage equipment and special lighting service industry may rapidly grow as the global cultural industries have grown along with the increase of national income earnings overall. Due to such advantageous features, it can be expected that such industries will show strong growth in the near future. After analyzing the fact that Korea's plants (eg. powerplants) export sector is at its boom, there is a need to transform stage equipment and special lighting service export market into a primary market from a secondary(niche) market for SMEs. This study is viewed from the Korean economic and export sector aspect in the aim of seeking a solution to conquest our realistic limit in our export sector by developing a suitable export model. There have been cases of very few attempts to expand abroad by SMEs who have failed miserably due to their failure to adapt to foreign culture, practice and languages as well as substantial lack in experience in export marketing. Despite this, neglecting our manufacturing industry as it is which is showing its limit and problems is out of option therefore, it is imminent that we come up with an effective measure to address this problem and service export can be suggested as one of them. This study reveals manufacturing-service export model of stage equipment and special lighting service and its related areas is recognized as a field with a very strong future and furthermore, it is expected to bring synergy effects in manufacturing and services sector as well. Further, the operation strategy contains combination, composition and fusion(convergence) of manufacturing and service sectors which could derive various of export products which displays greater success probability or this export model. The outcome of this research is expected to become a useful source for enterprises related to such industry which are seeking a possible global expansion. Furthermore, it is also expected to become a catalyst which fastens the process of global expansion and not only that, we are firmly assured that this study will become an opportunity to improve our current policies and institutions related to this area's export market.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.89-111
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• 2008

Due to the development of digital technology, studies regarding smart wear integrating daily life have rapidly increased. However, consumer research about perception and attitude toward smart clothing hardly could find. The purpose of this study was to identify innovative characteristics and perceived risk of smart clothing and to analyze the influences of theses factors on product attitudes and intention to adopt. Specifically, five hypotheses were established. H1: Perceived attributes of smart clothing except for complexity would have positive relations to product attitude or purchase intention, while complexity would be opposite. H2: Product attitude would have positive relation to purchase intention. H3: Product attitude would have a mediating effect between perceived attributes and purchase intention. H4: Perceived risks of smart clothing would have negative relations to perceived attributes except for complexity, and positive relations to complexity. H5: Product attitude would have a mediating effect between perceived risks and purchase intention. A self-administered questionnaire was developed based on previous studies. After pretest, the data were collected during September, 2006, from university students in Korea who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the mean age of 21.3 years old. About 59.3% reported that they were aware of smart clothing, but only 9 respondents purchased it. The mean of attitudes toward smart clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively. Factor analysis using principal components with varimax rotation was conducted to identify perceived attribute and perceived risk dimensions. Perceived attributes of smart wear were categorized into relative advantage (including compatibility), observability (including triability), and complexity. Perceived risks were identified into physical/performance risk, social psychological risk, time loss risk, and economic risk. Regression analysis was conducted to test five hypotheses. Relative advantage and observability were significant predictors of product attitude (adj $R^2$=.223) and purchase intention (adj $R^2$=.221). Complexity showed negative influence on product attitude. Product attitude presented significant relation to purchase intention (adj $R^2$=.692) and partial mediating effect between perceived attributes and purchase intention (adj $R^2$=.698). Therefore hypothesis one to three were accepted. In order to test hypothesis four, four dimensions of perceived risk and demographic variables (age, gender, monthly household income, awareness of smart clothing, and purchase experience) were entered as independent variables in the regression models. Social psychological risk, economic risk, and gender (female) were significant to predict relative advantage (adj $R^2$=.276). When perceived observability was a dependent variable, social psychological risk, time loss risk, physical/performance risk, and age (younger) were significant in order (adj $R^2$=.144). However, physical/performance risk was positively related to observability. The more Koreans seemed to be observable of smart clothing, the more increased the probability of physical harm or performance problems received. Complexity was predicted by product awareness, social psychological risk, economic risk, and purchase experience in order (adj $R^2$=.114). Product awareness was negatively related to complexity, meaning high level of product awareness would reduce complexity of smart clothing. However, purchase experience presented positive relation with complexity. It appears that consumers can perceive high level of complexity when they are actually consuming smart clothing in real life. Risk variables were positively related with complexity. That is, in order to decrease complexity, it is also necessary to consider minimizing anxiety factors about social psychological wound or loss of money. Thus, hypothesis 4 was partially accepted. Finally, in testing hypothesis 5, social psychological risk and economic risk were significant predictors for product attitude (adj $R^2$=.122) and purchase intention (adj $R^2$=.099) respectively. When attitude variable was included with risk variables as independent variables in the regression model to predict purchase intention, only attitude variable was significant (adj $R^2$=.691). Thus attitude variable presented full mediating effect between perceived risks and purchase intention, and hypothesis 5 was accepted. Findings would provide guidelines for fashion and electronic businesses who aim to create and strengthen positive attitude toward smart clothing. Marketers need to consider not only functional feature of smart clothing, but also practical and aesthetic attributes, since appropriateness for social norm or self image would reduce uncertainty of psychological or social risk, which increase relative advantage of smart clothing. Actually social psychological risk was significantly associated to relative advantage. Economic risk is negatively associated with product attitudes as well as purchase intention, suggesting that smart-wear developers have to reflect on price ranges of potential adopters. It will be effective to utilize the findings associated with complexity when marketers in US plan communication strategy.

• Journal of Preventive Medicine and Public Health
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• v.27 no.2 s.46
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• pp.258-273
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• 1994

To compare the physical complaints of vinylhouse farmers with those of non-vinylhouse farmers, a personal interviews on 250 vinylhouse and 142 non-vinylhouse farmers were conducted in Sungjoo county in Kyungpook province selected by a random sampling from July 5 to July 10, 1993. Blood pressure of the subjects was also measured. Vinylhouse farmers had a higher average age, larger family size, shorter experience of farming, more working hours per day and working days per year and higher annual income than the non-vinylhouse farmers. The frequency of pesticide spray of the vinylhouse farmers was 3.4 times on the average in June 1993 as compared with 2.0 times of non-vinylhouse farmers, and 16.7 times for the vinylhouse farmers during the last one year while it was 8.3 times for the non-vinylhouse farmers in the same period. While 39.6% of vinylhouse farmers experienced pesticide intoxication symptoms such as headache, nausea, vomiting, dizziness, itching, and skin irritation, etc. during the month of June, 25.4% of non-vinylhouse farmers experienced such symptoms. The most frequent symptoms among eight symptoms that constitute the farmers' syndrome were lumbago, numbness of hand or foot, shoulder pain and dizziness regardless of sex and type of farming. Prevalence of the farmers' syndrome in male and female among vinylhouse farmers were 22.1%, 43.4%, respectively, and the prevalence in non-vinylhouse farmers was 23.2% for male and 50.7% for female. There was no statistically significant difference in the prevalence of farmers' syndrome between vinylhouse and non-vinylhouse farmers. However, the prevalence in female was about 2 times higher than that of male. When the effects of other factors were adjusted by multiple logistic regression for farmers' syndrome, the prevalence in female was 3.0 times higher than that of male. The prevalence of farmers' syndrome was increased as the age of farmers increased in both vinylhouse and non-vinylhouse farmers, and adjusted odds ratio of farmers' syndrome increased by 3% as the age increased by 1 year. Adjusted odds ratio for Farmers' syndrome in farmers who experienced pesticide intoxication during the month of June was 3.1 times higher than that of farmers who did not have such experience. While the prevalence of hypertension in male and female non-vinylhouse farmers were 22.4%, 13.7%, respectively, the prevalence in vinylhouse farmers were 13.5% for male and 12.0% for female. However, there was no association between farmers' syndrome and hypertension. It was found in this study that the vinylhouse farmers are at a high risk of pesticide intoxication, which is associated with tile common physical complaints. To reduce such risk it is necessary to develop farming methods which do not require the pesticide or may use less pesticide, a safer method of pesticide spraying, and the protective equipments which can be worn at a high temperature and have a better protective effect. Also education of farmers for the correct methods of ventilation after pesticide spraying in the vinylhouse and wearing the protective equipments may be considered as a supportive method. Since inappropriate posture at work and intensive labor may cause farmers' syndrome, it is recommended to develop farming tools which reduce physical burden and take a rest and exercise periodically during work. It is necessary to strengthen the hypertension management program of the Kyungpook province, because the prevalence of hypertension was as high as about 15%.

• Journal of Nutrition and Health
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• v.49 no.6
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• pp.495-505
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• 2016

Purpose: This study was conducted to investigate and analyze the association between stress from shift and non-shift work as well as the effects living habits have on eating habits in order to identify why and how workers can improve their health and form proper eating habits for higher working efficiency. Methods: The subjects of this study were 361 workers from K manufacturing company from April 7 to 11, 2014 and they were surveyed using a questionnaire. The subjects were divided into two groups according to working pattern: shift workers (n = 216) and non-shift workers (n = 110). Results: In the general characteristics, there were significant differences in age, work career, work time, marriage, monthly income, and education levels between the two groups. For healthy behaviors, significant differences in subjective health status, moderate physical activity, drinking, smoking, and sleep time were observed between shift workers and non-shift workers. For eating habits, scores of non-shift workers having a regular mealtime, balanced meal composition, and vegetable and seaweed intakes were significantly higher than those of shift workers. The sum score of dietary habits in non-shift workers was also significantly lower than that in shift workers (p < 0.05). Total job stress score did not significantly differ between the two groups. Conclusion: The sum of eating habit scores according to work types was $16.1{\pm}0.6$ in non-shift workers and $14.0{\pm}0.3$ in shift workers. These results suggest that it is necessary to provide food suitable to characteristics of different workers according to work type which should be provided along with daily nutrition counseling to help subjects recognize their status.

• Korean Journal of Agricultural Science
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• v.1 no.1
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• pp.91-116
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• 1974

Taiwan agricultural development in the last decade has not been changed much since the accomplishment of land reform program. This is mainly due to the rapid development taken place within industry that agricultural development can not keep pace with. The increasing gap of rural-urban income discrepancy has caused socio-psychological unstability among rural people and inspire wants of out-migration. From 1961 to 1970, population of the ten largest cities showed an annual growth rate of 4.05%, while the population of the remainder of Taiwan showed 2.06%. Assuming the natural increase rate of these two population sections are similar, the difference of rural and urban annual growth rate can be at tributed to the flow of people from rural to urban sectors. The main objective of this paper is to identify the amount of agricultural out-migration and its impact on agricultural development and agricultural extension programs. Specifically, the objectives are to examine (1) rural-urban population composition (2) rural out-migration estimation (3) changes of agricultural population, and (4) implications for agricultural development and extension programs Some of the important findings are listed below; (1) The average agricultural out migration of the period 1960-1969 is estimated at around 60,000 per year. Take Tainan prefecture for example, the Male-Female Migration Ratio is 0.39 for age 20-24, 0.55 for age 25-29, 0.90 for 30-34. It is understood between age 20 and 34, the rural female migration rate is higher than the rural male. (2) Based on the population growth rate of 1950-1969, agricultural population is projected for the period of 1953 to 1989. By 1978, the agricultural population will reach its peak and begin to dedaine from 1980. The projected agricultural population in 1989 is 5,847,566 which occupies 29% of the Taiwan total population. (3) Assuming area of cultivated land keep unchanged as 905,263 ha. in 1970, and tif we can eliminate all 72% of part-time farms, then the average farm acreage for hose full-time farms will be increased to 3.6 hactares. This is unlikely to happen before 1989 without the government interference. (4) Less than 10% of adult farmer s of age 25-64 in 1969 enrolled in Farm Discussion Club, only 5% of adult farm women enrolled in Home Economics Club, and 5% of rural youth enrolled in 4-H Club. These statistics show a fact that only few farmers are reached by extension workers. Based on findings in this paper, some important suggestions are listed for future agricultural development. (1) Improve agricultural structure by decreasing agricultural population (a) Encourage farmers with less than 0.5 ha. of land to seek jobs outside of agriculture (b) Encourage joint cultivation and farm mechanization (c) Discourage rural migrants to Keep farm land (d) Provide occupational guidance program through extension education programs (2) Establish future farmers settlement project to assure rural youth have enough resources for farming. (3) An optimum Population policy should be integrated into rural socio-economic development and national development programs.

• Journal of agricultural medicine and community health
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• v.25 no.1
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• pp.29-49
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• 2000

Objectives: To estimate the prevalence rate of hypertension, the changes of health behavior, and compliance for the drug treatment after diagnosed as hypertension. Methods: 7,030 persons who live in Cheonan City of Chungnam Province were selected by the cluster sampling method, and 5,372 persons were surveyed by questionnaire and health examination. This data is analyzed by Chi-square test on each variable. Results: 49.8%- of men and 38.8%- of women had been diagnosed as hypertension, and the prevalence rate of hypertension was significantly increased with aging in both gender. The prevalence rate tended to decrease in highly educated women group. Unemployed persons or obese persons showed relatively higher prevalence rate. The prevalence rate of hypertension increased in groups with higher total cholesterol levels over 240 mg/dl, and groups with glucose level over 200 mg/dl. 53.1%- of male patients and 66.6%- of female patients showed compliance for antihypertensive treatment. Compliance for treatment was higher in aged group or lower educated group in both gender. Among men, proportion of compliant subjects was higher in unemployed group(49.3%-), and lower in labor or primary industry than the others but among women, there was not any significant difference. And men with compliance for treatment had higher monthly income than the others, but women did not show any. Conclusion : This population had a high prevalence rate of hypertension which may lead to cardiovascular disease. Therefore health education programs and distribution of information must be emphasized in order to increase compliance to treatment and encourage the change of health behavior to promote health.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• Journal of Nutrition and Health
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• v.49 no.5
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• pp.347-357
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• 2016

Purpose: This study investigated bone mineral density and nutritional state according to consumption of milk in Korean postmenopausal women who drink coffee. Methods: Using the 2008~2009 Korean National Health & Nutrition Examination Survey data, a total of 1,373 postmenopausal females aged 50 yrs and over were analyzed after excluding those with diseases related to bone health. According to coffee and/or milk consumption, subjects were divided into four groups: coffee only, both coffee & milk, milk only, and none of the above. All data were processed after application of weighted values and adjustment of age, body mass index, physical activity, drinking, and smoking using a general linear model. For analysis of nutrient intake and bone density, data were additionally adjusted by total energy and calcium intake. Results: The coffee & milk group had more subjects younger than 65 yrs and higher education, urban residents, and higher income than any other group. The coffee only group showed somewhat similar characteristics as the none of the above group, which showed the highest percentage of subjects older than 65 and in a lower education and socio-economic state. Body weight, height, body mass index, and lean mass were the highest in coffee & milk group and lowest in the none of the above group. On the other hand, the milk only group showed the lowest values for body mass index and waist circumference, whereas percent body fat did not show any difference among the groups. The coffee and milk group showed the highest bone mineral density in the total femur and lumbar spine as well as the highest nutritional state and most food group intakes, followed by the milk only group, coffee only group, and none of the above group. In the assessment of osteoporosis based on T-score of bone mineral density, although not significant, the coffee and milk group and milk only group, which showed a better nutritional state, included more subjects with a normal bone density, whereas the none of the above group included more subjects with osteoporosis than any other group. Conclusion: Bone mineral density in postmenopausal women might not be affected by coffee drinking if their diets are accompanied by balanced food and nutrient intake including milk.

• 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.