• (The) Research of the performance art and culture
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• no.32
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• pp.489-524
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• 2016

This study examines the birth of a genre, the $Sekky{\bar{o}}bushi$ Misemono Opera, focusing on how it accepted and modernized Katarimono $Sekky{\bar{o}}bushi$. Unlike earlier studies, it argues that Terayama was clearly different from other first-generation Angura artists, in that he rebirthed the medieval story $Sekky{\bar{o}}bushi$ as a modern Misemono Opera. Shintokumaru (1978) was directed by Terayama $Sh{\bar{u}}ji$, a member of the first generation of Japan's 1960s Angura Theatre Movement. It takes as its subject the Katarimono $Sekky{\bar{o}}bushi$ Shintokumaru, a story set to music that can be considered an example of the modern heritage of East Asian storytelling. $Sekky{\bar{o}}$ Shintokumaru is set in Tennoji, Japan. The title character Shintoku develops leprosy as a result of his stepmother's curse and is saved through his fiancee Otohime's devoted love and the spiritual power of the Bodhisattva Avalokitesvara. In this work, Terayama combined the narrative style of $Sekky{\bar{o}}bushi$ with J.A. Caesar's shamanistic rock music and gave it the subtitle 'Misemono Opera by $Sekky{\bar{o}}bushi$'. He transforms its underlying theme, the principle of goddesses and their offspring in a medieval religious world and the modori (return) instinct, into a world of mother-son-incest. Also, the pedestrian revenge scene from $Sekky{\bar{o}}bushi$ is altered to represent Shintokumaru as a drag queen, wearing his stepmother's clothes and mask, and he unites sexually with Sensaku, his stepbrother, and ends up killing him. The play follows the cause and effect structure of $Sekky{\bar{o}}bushi$. The appearance of katarite, a storyteller, propelling the narrative throughout and Dr. Yanagida Kunio is significant as an example of the modern use of self-introduction as a narrative device and chorus. Terayama $Sh{\bar{u}}ji^{\prime}s$ memories of desperate childhood, especially the absence of his father and the Aomori air raids, are depicted and deepened in structure. However, seventeen years after Terayama's death, the version of the play directed by Ninagawa Yukio-based on a revised edition by Kishida Rio, who had been Terayama's writing partner since the play's premier-is the today the better-known version. All the theatrical elements implied by Terayama's subtitle were removed, and as a result, the Rio production misses the essence of the diverse experimental theatre of Terayama's theatre company, $Tenj{\bar{o}}$ Sajiki. Shintokumaru has the narrative structure characteristic of aphorism. That is, each part of the story can stand alone, but it is possible to combine all the parts organically.

• 한국노년학
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• v.37 no.1
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• pp.83-102
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• 2017

Expending on a life course perspective, this study explores the long-term and short-term reciprocity in parent-child relationships in Korean context. Since the reasons for providing filial support are believed to differ by gender, we focused on how a child's gender affects both types of reciprocity. Data were collected from middle-aged sons (N=726) and daughters (N=883) with at least one surviving parent. Logistic regression was then conducted in order to examine the relations between the support a child currently provides to parents and the current or previous support received from the parents. Dependent variables are financial and instrumental support that middle-aged child currently provide to the parents. The financial and instrumental support a child received from the parents within a year are included in the model as an independent variable to assess short-term reciprocity. The level of financial support a child has received during the transition to adulthood process is included in the model as a independent variable to explore long-term reciprocity. Result supports the existence of gender differences in the long-term reciprocity. Daughters provided instrumental support in response to the financial support that they had received from parents during the transition to adulthood process. However, for sons, this tendency was not found. When it comes to financial support, long-term reciprocity was observed neither for the sons nor for the daughters. Both sons and daughters are prone to provide financial support to the aged parents regardless of the level of financial support they had received during the transition to adulthood process. Short-term reciprocity was found both in sons and daughters. when they have been receiving a financial or an instrumental support from the aged parents within a year, they tend to provided instrumental support to the parents. This study shows that the aged parents still fulfill the reciprocal relationship to a certain degree. Secondly, we can conclude that the norm of reciprocity interplays with the norm of filial responsibility in contemporary Korea.

• The Journal of Korean society of community based occupational therapy
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• v.10 no.3
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• pp.63-74
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• 2020

Objective : The purpose of this study is to investigate the influence of internal shame and self-control on interpersonal relationships in stroke patients, and to provide evidence and information necessary for clinical trials by analyzing the relationship. Methods : For this study, 150 stroke patients receiving occupational therapy services at institutions where occupational therapists work in Jeollanam-do and Chungnam regions were targeted through email and mail from March 1, 2019 to April 30, 2019. The questionnaire was conducted using general characteristics, Relationship Change Scales(RCS), Self-Control Scales(SCS), and Internalized Shame Scale(ISS) questionnaire. Descriptive statistical analysis was performed for the general characteristics of the study subjects, and t-test and one-way batch variance analysis (ANOVA) were used to compare interpersonal relationships according to general characteristics. The relationship between internalized shame, self-control, and interpersonal competence was analyzed by Pearson's correlation coefficient, and multiple regression analysis was performed to determine the factors affecting interpersonal relationships of stroke patients. Results : As a result of comparing interpersonal competence according to general characteristics, significant differences were found in terms of age and education level. Interpersonal relationships and internalized shame, internalized shame and self-control showed a negative correlation, and self-control and interpersonal relationships had a positive correlation, but self-control was the sub-factors of interpersonal relationships such as openness, sensitivity, intimacy, It was not statistically significant with the communication item. In addition, the items of inadequacy (β =-0.32) and adventure seeking (β =-0.23), which are sub-areas of internalized shame, affect the negative direction, and physical activity (β =0.22), which is the sub-area of self-control and the self-centered (β =0.24) item was found to have an effect on the positive direction. Conclusion : Therefore, additional research is needed that can operate a rehabilitation treatment program that applies various psychological factors for the formation of interpersonal relationships among stroke patients.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.109-121
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• 2021

With the recent increase in senior retirement, and senior start-ups are becoming more active due to high interest in start-ups. Research on young entrepreneurship, including college students, is being actively conducted, but most of the preceding research on senior entrepreneurship was conducted mainly on personal characteristics and social environment, and there were not many empirical studies on the influencing factors of entrepreneurship support policies. In this study, research and discussion on the entrepreneurial support policy and entrepreneurial competence as the influencing factors of senior entrepreneurship. As the independent variable of this study, the founder's competency was adopted as two factors: technical competence and creative competency, and the entrepreneurial support policy was divided into education support and funding support. Mentoring was set as a controlling variable and entrepreneurial intention was set as a dependent variable. A total of 232 questionnaires collected from seniors in their 40s or older were empirically analyzed. To verify the hypothesis of the study, SPSS 23 was used for exploratory factor analysis and regression analysis, and Process 3.4 was used for moderation effect. As a result of the study, it was found that the factors of technical competence, creative competence, educational support, and funding all have a significant influence on the will of entrepreneurship. It was found that creative competency(𝛽=.318), funding support(𝛽=.188), educational support(𝛽=.152), and technical competence(𝛽=.139), in this order, influenced the entrepreneurial intention. It was verified that the moderating effect of mentoring was significant between technical competence, creative competence, and entrepreneurial intention, but the moderating effect of mentoring between educational support, funding and entrepreneurial intention was not. The implications of this study will contribute to the research of senior start-up support policies, institutional supplementation, and differentiated start-up support programs by studying the factors of senior start-up capabilities and start-up support policies. It is also believed that it will contribute to the search for ways to increase creative capabilities that have a high influence on the willingness to start a business and the expansion of mentoring functions.

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

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.1
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• pp.16-21
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• 2022

Objectives : The purpose of this study is to investigate depression and suicide ideation according to socioeconomic changes after COVID-19 among Korean adolescent. Methods : Data on the study population were obtained from the 16th Korea Youth Risk Behavior Web-based Survey (KYRBS). The KYRBS is a nationally representative sample of Korean adolescents (aged 12-18 years) that originally included over 103 questions in 15 domains of health-risk behaviors. In the 16th KYRBS, a total 54,948 students from 793 schools responded to the survey. Chi-square test and logistic regression analysis were conducted regarding depression and suicide ideation. Results : This study suggests that changes in the family household before and after COVID-19 pandemic are also affecting the mental health of the adolescents. The study shows that worse change of family household is significant associations with suicidal ideation and depression. Adolescents reporting worse (AOR 1.38; 95% CI 1.38-1.57) and much worse (AOR 2.07; 95% CI 1.87-2.29) were significantly more likely to report depression. Adolescents reporting worse (AOR 1.34; 95% CI 1.34-1.60) and much worse (AOR 2.01; 95% CI 1.76-2.29) were significantly more likely to report suicide ideation. Conclusions : In this study, it was confirmed that young people from socially disadvantaged backgrounds are at high risk of suicide ideation and more depression. The results of this study suggest that we should consider improving the screening and prevention of mental health problems for adolescents with poor socioeconomic changes of COVID-19.

• 한국노년학
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• v.40 no.4
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• pp.707-727
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• 2020

This study aims to empirically analyze the role that perception of the probability of lonely death among the elderly people living alone plays in the relationship between perceived social support and preference for institutional care based on Andersen's expanded Behavioral Model (2002). The subjects (n=676) of this study were the elderly people living alone, extracted from the "2018 Seoul Aging Survey." With "perceived social support" as an independent variable, "preference for institutional care" as a dependent variable, and "perception of the probability of lonely death" as a mediator variable, we conducted a Binary Logistic Regression to follow the three steps of analyzing mediation effect, as suggested by Baron and Kenny (1986). The results showed that perceived social support has a negative effect on the preference for institutional care and perception of the probability of lonely death among the elderly people living alone; at the same time, perception of the probability of lonely death was found to have a positive effect on their preference for institutional care. Lastly, perception of the probability of lonely death was found to partially mediate the effect of perceived social support among the elderly people living alone in terms of their preference for institutional care. Based on these findings, the practical implications of this study can be summarized as follows. First, various programs and support should be provided to the elderly people living alone in order to enhance the level of perceived social support, a factor that has been confirmed to increase preference for institutional care among the elderly people living alone. Second, as the perception of the probability of lonely death was confirmed to be a psychosocial factor of the preference for institutional care, we need to promote education and support for older people living alone to prepare them for lonely death. These efforts are expected to form a foundations for implementing a community-based integrated care system, "Aging in Place," which is the policy direction required for older people care.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.127-144
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• 2021

The purpose of this study is to derive service factors based on the "Rail Statistical Yearbook" data of railroad service providers from 1990 to 2019, and to analyze the effect of the service factors on the operating profit ratio(OPR), a representative management performance variable of railroad transport service providers. In particular, it has academic significance in terms of empirical research to evaluate whether the management innovation of the KoRail has changed in line with the purpose of establishing the corporation by dividing the research period into the first period (1990-2003) and the latter (2004-2019). The contents of this study investigated previous studies on the quality of railway passenger transportation service and analyzed the contents of government presentation data related to the management performance evaluation of the KoRail. As an empirical analysis model, a research model was constructed using OPR as a dependent variable and service factor variables of infrastructure, economy, safety, connectivity, and business diversity as explanatory variables based on the operation and management activity information during the analysis period 30 years. On the results of research analysis, OPR is that the infrastructure factor is improved by structural reform or efficiency improvement. And economic factors are the fact that operating profit ratio improves by reducing costs. The safety factor did not reveal the significant explanatory power of the regression coefficient, but the sign of influence was the same as the prediction. Connectivity factor reveals a influence on differences between first period and latter, but OPR impact direction is changed from negative in before to positive in late. This is an evironment in which connectivity is actually realized in later period. On diversity factor, there is no effect of investment share in subsidiaries and government subsidies on OPR.