• Trans-
• /
• v.9
• /
• pp.37-66
• /
• 2020

Entering the 21st century, the flow of society and culture is emerging as a cultural phenomenon in which one experiences, enjoys, and experiences on one's own. This trend has emerged as community dance, which has been active since 2010. Community dances can be targeted by anyone and can be divided into children's, adult and senior citizens' dances depending on the characteristics and age of the group, allowing them to work in various age groups. It also refers to all kinds of dances for the happiness and self-achievement of everyone who can promote gender, race and religion health or meet the needs of expression and improve their physical strength at meetings by age group, from preschoolers to senior citizens. Community dance is a dance activity in which everyone takes advantage of their leisure time and voluntarily participates in joyous activities, making it expandable to lifelong education and social learning. It is a voluntary community gathering conducted by experts for the general public. The definition of community dance can be said to be the aggregate of physical activities that enrich an individual's daily life and enhance their social sense to create a bright society, while individuals achieve the goals of health promotion and aesthetic education. In the contemporary community dance, the dance experience in body and creativity as self-expression reflects the happiness perspective by exploring the positive psychological experience and influence of the participants in the process of participation, and participants have continued networking through online offline to enjoy the dance culture. Although research has been conducted in various fields for 10 years since the boom in community dance began, the actual methodology of the program has been insufficient to present the Feldenkrais Method, hoping that it will be used as a methodology necessary for local community dance, and will be used as part of the educational effects and choreography creation methods of artists that can improve the physical functional aspects of dance and give a sense of psychological stability.

• Journal of agricultural medicine and community health
• /
• v.46 no.3
• /
• pp.131-143
• /
• 2021

Objectives: This study aimed 1) to investigate high school students' reliability on COVID-19 responses in schools and private academies and 2) to identify the differences in COVID-19 prevention practice. Methods: This cross-sectional survey collected data from 200 high school respondents, using an anonymous online questionnaire designed by the Yonsei Global Health Center, from July 2 to 17, 2020 in this study. Chi-square tests were conducted to analyze the differences in preventative practices and practice rates between schools and private academies. Binary logistics regression analysis was conducted to identify the factor affecting the reliability of COVID-19 response. Results: These high school students reliabilityed the schools' COVID-19 response more than the private academy. In addition, students who studied only at school did more COVID-19 prevention practices than students who studied both at school and academy. There was a significant difference in avoiding public transportation (p=.028), sitting in one row while having a meal (p=.011) in the practice rates depending on the schools' COVID-19 response. A significant difference in Covering the mouth when coughing and sneezing (p-.041) was also found in the practice rates depending on the private academies' COVID-19 response. Conclusion: The reason why schools were more reliable than private academies was that there are health teachers. Because schools are supervised by the ministry of education, the Ministry of education and local government need to work together to manage and monitor the COVID-19 response in the academies through cooperation between two organizations. In addition, it is necessary to arrange a temporary circulation health teacher who will provide the COVID-19 prevention education at the academies.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.103-128
• /
• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.5
• /
• pp.257-269
• /
• 2021

This study aimed to secure basic data for the development and operation of well-aging education programs by analyzing the physical, mental, and socio-economic needs of well-aging education for successful aging. The research tool was developed as a questionnaire to investigate the perception of well aging and the needs of well-aging education in terms of physical, mental, and socio-economic aspects. In February 2021, 1949 adults over the age of 19 were surveyed through an online and mobile survey by Gallup Korea. Descriptive statistics analysis, variance analysis, Borich needs analysis, and IPA analysis were conducted to analyze the needs of well-aging education. The results revealed economic power, exercise, and chronic disease management to be high in terms of the overall priority of the education needs for well-aging, and infectious disease management, independence, and social responsibility were surveyed in the order of low education needs. In terms of economic power, education needs were highest among all age groups except for the middle-age group (35-49 years old), 82.4% of all respondents, and education needs for exercise and chronic disease management were highest in the middle-age group. Therefore, it is necessary to develop well-aging education programs for each life cycle. These results are expected to be used as empirical data in establishing a platform for developing and operating educational programs for well aging.

• Journal of agricultural medicine and community health
• /
• v.48 no.1
• /
• pp.28-40
• /
• 2023

Objectives: This study aimed to identify the level of self-assessment of life satisfaction and various factors related to the life satisfaction of Korean physicians. Methods: This study is a secondary data analysis using the 2016 Korean physician survey Korean Physician Survey(KPS) data collected by the Research Institute for Healthcare Policy of the Korean Medical Association. The member database(DB) of the Korean Medical Association was used for sampling and the target population was formed and surveyed by using stratified quota sampling. A questionnaire was sent by E-mail as an online survey method and was conducted for a total of 7 weeks from November 21, 2016 to January 8, 2017. The final number of respondents was 8,564 (response rate 13.8%). In this study, a total of 7,228 physicians, excluding residents and public health doctors who are currently treating patients directly, were studied. Factors affecting the life satisfaction of physicians were analyzed using ordinal logistic regression analysis. Results: The physical factors positively related to the life satisfaction of physicians were those who were in their 60s, female, and thought they had good health status. As for psychological factors, stress was low. As for economic factors, satisfaction with income was high. As for social factors, the physicians lived with their families and were satisfied with the time they could spend with them. Also, the physicians were satisfied with the social respect they received as a doctors. Conclusions: Based on the results of this study, it is thought that a multifaceted approach is needed to increase the life satisfaction of physicians.

• Korea Science and Art Forum
• /
• v.28
• /
• pp.105-116
• /
• 2017

This study is a basic research to suggest user-centered general hospital environmental design guidelines, which aims to analyze user's behavior characteristics across generation in general hospital. For this purpose, this study constructed an analysis tool through the literature review with regard to generation and behavior characteristics in general hospital. Besides, an online survey regarding user's behavior in general hospital was conducted targeting from 20s to 60s, 300 persons for each group, total 1,500 persons for about 3 weeks since September 1, 2016. The results of this study are as follows: (1) Based on the generation, there were significant differences in relevant categories of their visiting frequency, visiting purpose, visiting hour, transportation, companion, behavior during the wait and selection of a general hospital. (2) In all generation, they responded that they have visited once or twice per year. People in 20s and 30s responded that their visit for the hospital is to receive specific treatment, while other people in 40s, 50s and 60s visit the hospital majorly for routine check-ups. Therefore, it is imperative for a health check-up center to design an environmental plan that reflects the characteristics of elders in 40s, 50s and 60s. (3) People in 40s, 50s and 60s usually visit a general hospital in the mornings of weekdays, while generations in 20s and 30s responded that they mostly visit the hospital in the mornings of weekend. (4) When they visit a general hospital, people in their 20s are usually using public transportations, while people in their 30s to 60s are using their own vehicle. (5) People in their 20s majorly visited 'lobby'. In older generations, they tend to visit 'outpatient clinic'. Therefore, it is necessary to build an outpatient clinic environment that considers the elderly. (6) Patients majorly responded that they are using their cell phone, while waiting for their clinic call. In elder generations, they responded that they are more likely watching TVs, reading books/magazines or doing nothing. Therefore, it is essential to provide cell-phone related services and environmental supports. Visually attractive media can be utilized for this purpose.

• Journal of Nutrition and Health
• /
• v.45 no.6
• /
• pp.562-576
• /
• 2012

Han-sik is a term in Korean that may indicate any Korean dish or food. At present, there is no general consensus on the definition of Han-sik among scholars or professionals in related fields. The aim of this study was to investigate perceptions of Han-sik by professionals in the fields of food, nutrition, and culinary arts using 512 dishes and foods commonly consumed by Koreans using the 4th Korean National Health and Nutrition Survey. A total of 117 professionals out of 185 initially contacted professionals participated in this online survey. We calculated the rate of respondents with a positive answer, that is "It is Han-sik', on each dish and food from the 512 items in 28 dish groups. Items were categorized into five groups according to their Han-sik perception rate: over 90%, 75-89%, 50-74%, 25-49%, and below 25%. Most items in the three dish groups 'Seasoned vegetables, cooked (Namul Suk-chae)', 'Kimchis', and 'Salt-fermented foods (Jeotgal)' showed high perception rates of Han-sik, with a higher than 90% positive response. Items in 'Soups', 'Stews', and 'Steamed foods' dish groups also showed high perception rates of Han-sik. However, no item showed a greater than 90% Han-sik perception rate in 'Fried foods (Twigim)', 'Meat, poultry and fishes', 'Legumes, nuts, and seeds', 'Milk and milk products', 'Sugars and confectioneries', and 'Soup'. Most items in the 'Milk and milk products', 'Sugars and confectioneries', and 'Soup' groups belonged to the lowest perception rate of below 25%. There was a significant difference in the proportion of items perceived as Han-sik by the length of living abroad to (p < 0.05). In summary, the perception rate of Han-sik seemed to be affected by the cooking method, ingredients, and length of time living abroad by the professionals. Further studies targeting subjects with different characteristics and socioeconomic status are warranted to define the concept of Han-sik.

• Journal of Global Scholars of Marketing Science
• /
• v.20 no.2
• /
• pp.135-148
• /
• 2010

Arab boycotts of Danish products, Australian boycotts of French products and Chinese consumer aversion toward Japanese products are all examples of how adverse actions at the country level might impact consumers' behavior. The animosity literature has examined how consumers react to the adverse actions of other countries, and how such animosity impacts consumers' attitudes and preferences for products from the transgressing country. For example, Chinese consumers are less likely to buy Japanese products because of Japanese atrocities during World War II and the unjust economic dealings of the Japanese (Klein, Ettenson and Morris 1998). The marketing literature, however, has not examined how consumers react to adverse actions committed by their own country against other countries, and whether such actions affect their attitudes towards purchasing products that originated from the adversely affected country. The social psychology literature argues that consumers will experience a feeling called collective guilt, in response to such adverse actions. Collective guilt stems from the distress experienced by group members when they accept that their group is responsible for actions that have harmed another group (Branscombe, Slugoski, and Kappenn 2004). Examples include Americans feeling guilty about the atrocities committed by the U.S. military at Abu Ghraib prison (Iyer, Schamder and Lickel 2007), and the Dutch about their occupation of Indonesia in the past (Doosje et al. 1998). The primary aim of this study is to examine consumers' perceptions of adverse actions by members of one's own country against another country and whether such perceptions affected their attitudes towards products originating from the country transgressed against. More specifically, one objective of this study is to examine the perceptual antecedents of collective guilt, an emotional reaction to adverse actions performed by members of one's country against another country. Another objective is to examine the impact of collective guilt on consumers' perceptions of, and preference for, products originating from the country transgressed against by the consumers' own country. If collective guilt emerges as a significant predictor, companies originating from countries that have been transgressed against might be able to capitalize on such unfortunate events. This research utilizes the animosity model introduced by Klein, Ettenson and Morris (1998) and later expanded on by Klein (2002). Klein finds that U.S. consumers harbor animosity toward the Japanese. This animosity is experienced in response to events that occurred during World War II (i.e., the bombing of Pearl Harbor) and more recently the perceived economic threat from Japan. Thus this study argues that the events of Word War II (i.e., bombing of Hiroshima and Nagasaki) might lead U.S. consumers to experience collective guilt. A series of three hypotheses were introduced. The first hypothesis deals with the antecedents of collective guilt. Previous research argues that collective guilt is experienced when consumers perceive that the harm following a transgression is illegitimate and that the country from which the transgressors originate should be responsible for the adverse actions. (Wohl, Branscombe, and Klar 2006). Therefore the following hypothesis was offered: H1a. Higher levels of perceived illegitimacy for the harm committed will result in higher levels of collective guilt. H1b. Higher levels of responsibility will be positively associated with higher levels of collective guilt. The second and third hypotheses deal with the impact of collective guilt on the preferences for Japanese products. Klein (2002) found that higher levels of animosity toward Japan resulted in a lower preference for a Japanese product relative to a South Korean product but not a lower preference for a Japanese product relative to a U.S. product. These results therefore indicate that the experience of collective guilt will lead to a higher preference for a Japanese product if consumers are contemplating a choice that inv olves a decision to buy Japanese versus South Korean product but not if the choice involves a decision to buy a Japanese versus a U.S. product. H2. Collective guilt will be positively related to the preference for a Japanese product over a South Korean product, but will not be related to the preference for a Japanese product over a U.S. product. H3. Collective guilt will be positively related to the preference for a Japanese product over a South Korean product, holding constant product judgments and animosity. An experiment was conducted to test the hypotheses. The illegitimacy of the harm and responsibility were manipulated by exposing respondents to a description of adverse events occurring during World War II. Data were collected using an online consumer panel in the United States. Subjects were randomly assigned to either the low levels of responsibility and illegitimacy condition (n=259) or the high levels of responsibility and illigitemacy (n=268) condition. Latent Variable Structural Equation Modeling (LVSEM) was used to test the hypothesized relationships. The first hypothesis is supported as both the illegitimacy of the harm and responsibility assigned to the Americans for the harm committed against the Japanese during WWII have a positive impact on collective guilt. The second hypothesis is also supported as collective guilt is positively related to preference for a Japanese product over a South Korean product but is not related to preference for a Japanese product over a U.S. product. Finally there is support for the third hypothesis, since collective guilt is positively related to the preference for a Japanese product over a South Korean product while controlling for the effect of product judgments about Japanese products and animosity. The results of these studies lead to several conclusions. First, the illegitimacy of harm and responsibility can be manipulated and that they are antecedents of collective guilt. Second, collective guilt has an impact on a consumers' decision when they face a choice set that includes a product from the country that was the target of the adverse action and a product from another foreign country. This impact however disappears from a consumers' decision when they face a choice set that includes a product from the country that was the target of the adverse action and a domestic product. This result suggests that collective guilt might be a viable factor for company originating from the country transgressed against if its competitors are foreign but not if they are local.

• Cartoon and Animation Studies
• /
• s.41
• /
• pp.455-486
• /
• 2015

The 3D printing technology, which started from the patent registration in 1986, was a technology that did not attract attention other than from some companies, due to the lack of awareness at the time. However, today, as expiring patents are appearing after the passage of 20 years, the price of 3D printers have decreased to the level of allowing purchase by individuals and the technology is attracting attention from industries, in addition to the general public, such as by naturally accepting 3D and to share 3D data, based on the generalization of online information exchange and improvement of computer performance. The production capability of 3D printers, which is based on digital data enabling digital transmission and revision and supplementation or production manufacturing not requiring molding, may provide a groundbreaking change to the process of manufacturing, and may attain the same effect in the character merchandise sector. Using a 3D printer is becoming a necessity in various figure merchandise productions which are in the forefront of the kidult culture that is recently gaining attention, and when predicting the demand by the industrial sites related to such character merchandise and when considering the more inexpensive price due to the expiration of patents and sharing of technology, expanding opportunities and sectors of employment and cultivating manpower that are able to engage in further creative work seems as a must, by introducing education courses cultivating manpower that can utilize 3D printers at the education field. However, there are limits in the information that can be obtained when seeking to introduce 3D printers in school education. Because the press or information media only mentions general information, such as the growth of the industrial size or prosperous future value of 3D printers, the research level of the academic world also remains at the level of organizing contents in an introductory level, such as by analyzing data on industrial size, analyzing the applicable scope in the industry, or introducing the printing technology. Such lack of information gives rise to problems at the education site. There would be no choice but to incur temporal and opportunity expenses, since the technology would only be able to be used after going through trials and errors, by first introducing the technology without examining the actual information, such as through comparing the strengths and weaknesses. In particular, if an expensive equipment introduced does not suit the features of school education, the loss costs would be significant. This research targeted general users without a technology-related basis, instead of specialists. By comparing the strengths and weaknesses and analyzing the problems and matters requiring notice upon use, pursuant to the representative technologies, instead of merely introducing the 3D printer technology as had been done previously, this research sought to explain the types of features that a 3D printer should have, in particular, when required in education relating to the development of figure merchandise as an optional cultural contents at cartoon-related departments, and sought to provide information that can be of practical help when seeking to provide education using 3D printers in the future. In the main body, the technologies were explained by making a classification based on a new perspective, such as the buttress method, types of materials, two-dimensional printing method, and three-dimensional printing method. The reason for selecting such different classification method was to easily allow mutual comparison of the practical problems upon use. In conclusion, the most suitable 3D printer was selected as the printer in the FDM method, which is comparatively cheap and requires low repair and maintenance cost and low materials expenses, although rather insufficient in the quality of outputs, and a recommendation was made, in addition, to select an entity that is supportive in providing technical support.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.1-19
• /
• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.