• Journal of Technologic Dentistry
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• v.45 no.4
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• pp.95-101
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• 2023

Purpose: This study examines the clinical practice satisfaction and major satisfaction of dental technology students who have experienced clinical practice to identify whether there is an effect on employment intention of satisfaction level as a basis for increasing the employment rate of dental technicians. Methods: A survey was distributed among 150 dental technology students, and the data were analyzed using descriptive statistics and frequency and correlation analyses. Finally, multiple regression analysis was used to verify the research hypotheses. All statistical analyses were carried out using IBM SPSS Statistics ver. 27.0 (IBM). Results: The students exhibited high levels of satisfaction with their clinical practice (4.20) and dental technology major (4.07). Further analysis showed a positive correlation between intention to work in dental laboratories and satisfaction with a dental technology major (practice; r=0.437, p<0.05); clinical practice organization (r=0.682, p<0.05); and satisfaction with the clinical practice institution (r=0.650, p<0.05). Statistically significant positive associations (p<0.05) were also observed between clinical practice form and environment, satisfaction with dental technology major, and school region (i.e., metropolitan area). Conclusion: The findings of this study suggest that high levels of satisfaction with clinical practice and dental technology major can contribute to increased employment rates among dental technicians by promoting their intention to work in the related industry.

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.4
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• pp.222-228
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• 2023

Attrition is the loss of tooth hard tissue due to contact between teeth, and in severe cases, dentin is exposed, accompanied by selective corrosion and excessive wear of teeth, which is called cupping. If these lesions are left untreated, the size of the lesion gradually increases, breaking the unsupported enamel, resulting in a decrease in aesthetics and chewing function. In this case report, patients with cupping and enamel fracture due to severe attrition were directly restored using a resin with soft properties containing organic fillers. In the follow-up observation six years later, most of the filling of the occlusal surface was eliminated, but the filling on the buccal surfaces remained relatively intact, and it was confirmed that this type of resin was suitable for the area where the occlusal force was relatively weak rather than the area where the occlusal force was greatly applied.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.155-166
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• 2024

Purpose : This study aims to identify key factors for predicting dropout risk at the university level and to provide a foundation for policy development aimed at dropout prevention. This study explores the optimal machine learning algorithm by comparing the performance of various algorithms using data on college students' dropout risks. Methods : We collected data on factors influencing dropout risk and propensity were collected from N University. The collected data were applied to several machine learning algorithms, including random forest, decision tree, artificial neural network, logistic regression, support vector machine (SVM), k-nearest neighbor (k-NN) classification, and Naive Bayes. The performance of these models was compared and evaluated, with a focus on predictive validity and the identification of significant dropout factors through the information gain index of machine learning. Results : The binary logistic regression analysis showed that the year of the program, department, grades, and year of entry had a statistically significant effect on the dropout risk. The performance of each machine learning algorithm showed that random forest performed the best. The results showed that the relative importance of the predictor variables was highest for department, age, grade, and residence, in the order of whether or not they matched the school location. Conclusion : Machine learning-based prediction of dropout risk focuses on the early identification of students at risk. The types and causes of dropout crises vary significantly among students. It is important to identify the types and causes of dropout crises so that appropriate actions and support can be taken to remove risk factors and increase protective factors. The relative importance of the factors affecting dropout risk found in this study will help guide educational prescriptions for preventing college student dropout.

• 한국노년학
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• v.38 no.4
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• pp.1057-1081
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• 2018

This study analyzed the case of elderly care cluster in Gwangjin-gu to explore the possibilities of social economy as a provider of community-based social services. Community-based means the approach by which community organizations build a voluntary and collaborative network to enhance collective problem-solving abilities. Therefore, it is very likely that the social economy that emphasizes people, labor, community, and democratic principles can contribute to community-based social services. This study analyzed social economic network by using four characteristics of social economy suggested by OECD community economy and employment program as an analysis framework. The results of this study are as follows: First, it is found that social economy would hardly supply community-based social services through network cooperation because of a large variation in community identity, investment to new product, and labor protection. Second, community users are not the consumers of the social economy and the products of the social economy stay in market products only for the organizations in social economy. In order to create good services that meet the needs of residents, community development approaches are required at the same time. The importance of community space where local residents and social economy meet is derived. Third, public support such as purchasing support has weakened the ecosystem of social economy by making the distinction between public economy and social economy more obscure. On the other hand, public investment in community infrastructure is an indirect aid to social economy to communicate with residents and to promote good supply and consumption. In the end, community-based social services need a platform where the social economy and the people meet. This type of public investment can create the ecosystem of the social economy.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Korean Journal of Labor Studies
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• v.24 no.2
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• pp.95-136
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• 2018

As the number of precariats grows, their poor labor rights and working conditions are becoming issues of major concern all over the world but how to represent their interests is still controversial. Basically, the union is the institutional mechanism for representing the labor rights. However, it is difficult for workplaceand enterprise-based unions to fully represent the labor rights of precarious workers. Recently, so-called community unions have emerged in the United States, the United Kingdom, and Japan as independent organizations representing the rights of non-standard workers. Community unions refer to labor unions which organize precarious workers across firms at the regional level. They are known to be suitable for covering the unemployed, job seekers, indirect employment workers, short-term contract workers, and small-firm workers. In South Korea, since the financial crisis in 1997, a dramatic increase in the number of precariats leads to emergence of new types of trade unions such as the Youth Community Union, the Arbeit Workers' Union, the Artist Social Union and the Korea Musician's Union. They have engaged in various activities to guarantee the labor rights of precariats. Recently, researchers have also tried to identify defining characteristics of these new forms of unionism. To expand research on trade unionism in South Korea, this study compares two different types of community unions: the Youth Community Union and the Arbeit Workers' Union. We believe that this attempt can contribute to the research on the alternative labor movement. For this purpose, this study starts with theoretical discussions on community unions, and compares the Youth Community Union with the Arbeit Workers' Union based on the five characteristics of community unionism: membership and organization structure, the recognition struggle, the type or scope of interest, solidarity with other civic organizations, and the repertoire of resistance strategies. Based on this comparative analysis, this study seeks to foresee the possibility of how community unionism will develop in South Korean in the future.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Therapeutic Science for Rehabilitation
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• v.10 no.2
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• pp.75-93
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• 2021

Objective : The aim of this study was to identify subgroups of older adults with respect to their lifestyle patterns and examine the characteristics of each subgroup in order to provide a basic evidence for improving the health and quality of life. Methods : This cross-sectional study was conducted in South Korea. Community-dwelling older adults (n=184) above the age of 65 years were surveyed from April 2019 to May 2019. This study used latent profile analysis to examine the subgroups. Chi-squared (χ²) and multinomial logistic regression measures were then used to analyze individual characteristics and influencing factors. Results : The pattern of physical activity which is one of the lifestyle domains in elderly was categorized into three types: 'passive exercise type (31.1%)', 'low intensity exercise type (54.5%)', and 'balanced exercise type(14.5%)'. Activity participation was divided into three patterns: 'inactive type (12%)', 'self-management type (61%)', and 'balanced activity participation type (27%)'. In terms of nutrition, there were only two groups: 'overall malnutrition type (13.5%)' and 'balanced nutrition type (86.5%)'. Furthermore, as a result of the multinomial logistic regression analysis to understand the effects of lifestyle types on the health and quality of life of the elderly, it was confirmed that the health and quality of life were higher in those following an active and balanced lifestyle. In addition, gender, education level and residential area were analyzed as predictive factors. Conclusion : The health and quality of life of the elderly can be improved when they have balanced lifestyle. Therefore, an empirical and policy intervention strategy should be developed and implemented to enhance the health and quality of life of the elderly.

• Journal of Nutrition and Health
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• v.53 no.6
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• pp.596-612
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• 2020

Purpose: This study was conducted to evaluate the dietary behaviors of preschool children using the nutrition quotient for preschoolers (NQ-P) and investigate factors that influence NQ-P in preschool children. Methods: Subjects were 214 parents with children aged 3-5 years residing in Busan and Gyeongnam, Korea. The survey was conducted from March to April, 2019 using a questionnaire that included demographic characteristics, the NQ-P questions, and health consciousness. All data was statistically analyzed by the SPSS program (Ver 25.0) and the statistical differences in variables were evaluated by the chi-square test, Fisher's exact test, t-test, one-way ANOVA, and Tukey's multiple comparison test. Results: The mean score of NQ-P of the total subjects was 58.28, which was within the medium-low grade. The mean score of 'balance' was 60.08, 'moderation' was 47.64, and 'environment' was 67.83. The analysis of related-factors influencing NQ-P scores showed that there was a significant difference according to the frequency of dining out. The scores of the NQ-P (p < 0.05), moderation (p < 0.001), and environment (p < 0.05) were significantly higher in the 1-2 times per week group compare to 3-4 times and 5-6 times per week group. The scores of NQ-P (p < 0.01), environment (p < 0.01) were significantly higher in the high group of parents' health consciousness compared to the those with low health consciousness. Conclusion: According to the results of the evaluation by NQ-P, the dietary behaviors of preschool children residing in Busan and Gyeongnam need to be improved and monitored. For improving their eating behavior and nutritional health status, preschool children and their parents need proper nutrition education programs.

• Korean Journal of Legislative Studies
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• v.24 no.1
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• pp.67-101
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• 2018

The purpose of this study is to examine the significant factors having an effect on voting behavior of legislators in the FTA ratification votes of the 18th and 19th National Assembly. The previous studies show that the ideology and party affiliation of lawmakers are the most important factors influencing voting decisions of legislators. The study investigates whether these factors plays a significant role in voting on the FTA ratification. Statistical results show three important findings. First of all, we expected that the influence of the party variable be the most important factor due to the strong discipline of the Korean party. However, the results show that the constituency-interest variable is the most influential factor in the all analyses. Likewise, the results show that the influence of ideology variables on voting behaviors is very strong even though its impact is different by cases and models. This indicates that in the analysis of the voting behaviors of legislators, it is necessary to examine the effect of ideological variables in depth and in various ways. In addition, the results reasonably suggest that the party variable be consistently important even though its statistical significance is not shown in some models. Because the study analyzes the voting on the free trade agreement(FTA) bill, the results may not be commonly applicable to other voting behavior of legislator. Likewise, there is a limit to discussing the general characteristics of lawmakers based on the analysis on the 5 FTA ratifications. Nevertheless, the finding of the study is very significant. This is because it comprehensively analyzed the factors having an influence on the voting behavior of the legislators on FTA ratifications submitted to the National Assembly steadily since the 16th National Assembly. In addition, the study is very meaningful because it analyzed the ideological variables of the legislators in various perspectives considering that it is not easy in measuring the ideology of the lawmakers.