• Journal of Korean Philosophical Society
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• v.105
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• pp.373-400
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• 2008

This essay is an analysis on Daoist deconstructivism and Confucian constructivism about music and language. (1) Daoist criticizes that the Confucian constructive music and language fail to describe original sounds and original facts of doing nothing (wuwei, 無爲). According to Daoist, music and language can be an instrument to describe true facts in the world. So Daoists try to attain a state of 'seeing things as things themselves (yiwuguanwu, 以物觀物)' by 'forgetting oneself (wangwo, 忘我).' (2) However Confucian music and language is a part of one's life. Confucians try to get truth, goodness, and beauty by exercising one's music and language. Confucian music is associated with political and moral development in society. The Confucian genres of poetry (shi, 詩), appealing letter (shu, 疏), declaring writing (biao, 表), record (ji, 記), and written words (ci, 詞) are processes of developing one's life. Further, Confucian rhetoric of 'Xing (興)' in writing poem shows that one's language can be developed in contexts of one's life. (3) Although music and language is associated with human subjective narratives as if Confucians say, diverse narratives of different subjectivity cannot appear in one's lives if all kinds of narrative is absorbed in Confucian absolute ideological slogan to devide things into good and bad. Accordingly, the Confucian view of music and language can develop diverse narratives when it does not show an inclination toward moral dichotomy preunderstood by Confucian ideology.

• 한국노년학
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• v.37 no.4
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• pp.871-891
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• 2017

The purpose of this paper is to reduce the reverse-causality and overestimate bias of analysis on how health affected middle-aged and elderly worker's early retirement. From the Korean Longitudinal Study of Ageing(KLoSA) panel data, I researched 1,049 people who were 45-52 years old in 2006. To eliminate the reverse-causality problem, I used the health data which is surveyed before retirement. To reduce bias, I controlled the health status when retirees worked. The main results are as follows. First, the worsened health still affects the hazard of early retirement, with reducing the endogeneity problem. Second, chronic illness is one of the strong predictors of early retirement to self-employed, and self-reported bad health is the main health predictor of wage workers. These results give two implications; first, the impact magnitude of the health indicator depends on employment type. Each employment type has different flexibility of working hours. It seems that the flexibility can reduce early retirement hazard with health problems. Self-employed, who has more flexibility of working hours can work until they have to stop working due to the serious health problem or doctor's advice. Second, to promote middle-aged and elderly workers to keep working, the long-term health policy which decreases chronic illness is needed.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.107-119
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• 2020

This study was designed to analyze the social and institutional problems that may arise in the early 2000s of the United States and in the scholarship program for university student-athletes by analyzing Dialogues in the Film [The Blind Side] and to derive the meaning of this to Korean society and education field. In summary, the first is that there is a need for fundamental change in the thinking about gender discrimination and racist expressions expressed in everyday life including a Sport field not only in the United states but also in Korean society. Second, the Korea University Sports Federation(KUSF), like NCAA, is working on the right to study and human rights of university athletes, but in the commercialism of modern sports related to the capitalism, these systems and regulations could be a bigger obstacle to the process of growing young players. And finally, like the case of "Flower-loving Ferdinand" who having a lot in common with the main character, Michael in the Film, I hope that there will be a "Sports Ferdinand" that likes the sport itself, which is fully satisfied with its life and lives happily even if it is not a sports star.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.1
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• pp.153-165
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• 2023

This study investigates learners' environmental literacy, classifies the results by factors of environmental literacy, and then investigates the differences in the students' environmental behavior practice experiences according to the classification by factor. The study was conducted with 47 6th grade students from D elementary school located in P metropolitan city as the subject of final analysis, and environmental literacy questionnaires and environmental behavior practice experience questionnaires were used as the main data. As a result of the study, the learners were classified into three groups according to the factors of environmental literacy, and they were respectively named as the "High environmental literacy group", "low environmental literacy group", and "Low Function and Affectif group". A Word network was formed using the descriptions of environmental behavior practice experiences for each cluster, and a Degree Centrality Analysis was performed to visualize and then analyze. As a result of the analysis, "High environmental literacy group" was confirmed, 1) recognized the subjects of environmental action practice as individuals and families, 2) described his experience of environmental action practice in relation to all elements of environmental literacy, and had a relatively pessimistic view. "low environmental literacy group", and "Low Function and Affectif group" were confirmed 1) perceive the subject of environmental behavior practice as a relatively social problem, 2) the description of the experience of environmental behavior practice is relatively biased specific factors, and the "Low Function and Affectif group" is particularly focused on the knowledge element. And 3) it was confirmed that they were aware of climate change from a relatively optimistic perspective. Based on this conclusion, suggestions were made from the perspective of environmental education.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.307-319
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• 2023

This study aims to explain the key concepts and principles of text-based generative artificial intelligence (AI) that has been receiving increasing interest and utilization, focusing on its application in science education. It also highlights the potential and limitations of utilizing generative AI in science education, providing insights for its implementation and research aspects. Recent advancements in generative AI, predominantly based on transformer models consisting of encoders and decoders, have shown remarkable progress through optimization of reinforcement learning and reward models using human feedback, as well as understanding context. Particularly, it can perform various functions such as writing, summarizing, keyword extraction, evaluation, and feedback based on the ability to understand various user questions and intents. It also offers practical utility in diagnosing learners and structuring educational content based on provided examples by educators. However, it is necessary to examine the concerns regarding the limitations of generative AI, including the potential for conveying inaccurate facts or knowledge, bias resulting from overconfidence, and uncertainties regarding its impact on user attitudes or emotions. Moreover, the responses provided by generative AI are probabilistic based on response data from many individuals, which raises concerns about limiting insightful and innovative thinking that may offer different perspectives or ideas. In light of these considerations, this study provides practical suggestions for the positive utilization of AI in science education.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.191-205
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• 2023

Artificial Intelligence (AI), especially in the domain of text-generative services, has witnessed a significant surge, with forecasts indicating the AI-as-a-Service (AIaaS) market reaching a valuation of $55.0 Billion by 2028. This research set out to explore the quality dimensions characterizing synthetic text media software, with a focus on four key players in the industry: ChatGPT, Writesonic, Jasper, and Anyword. Drawing from a comprehensive dataset of over 4,000 reviews sourced from a software evaluation platform, the study employed the Latent Dirichlet Allocation (LDA) topic modeling technique using the Gensim library. This process resulted the data into 11 distinct topics. Subsequent analysis involved comparing these topics against established AI service quality dimensions, specifically AICSQ and AISAQUAL. Notably, the reviews predominantly emphasized dimensions like availability and efficiency, while others, such as anthropomorphism, which have been underscored in prior literature, were absent. This observation is attributed to the inherent nature of the reviews of AI services examined, which lean more towards semantic understanding rather than direct user interaction. The study acknowledges inherent limitations, mainly potential biases stemming from the singular review source and the specific nature of the reviewer demographic. Possible future research includes gauging the real-world implications of these quality dimensions on user satisfaction and to discuss deeper into how individual dimensions might impact overall ratings.

• 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.

• The Korean Journal of Archival Studies
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• no.29
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• pp.3-33
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• 2011

No one can deny the harsh reality that archival culture has not yet been permeated extensively into all the spheres of our society. Only fragmented records in fixed areas are in the custody of archives. Records to build a living memory for the history of our present are hard to find or remain minimal, if anywhere. Above all, there are few records in archives concerned with the everyday life of common people. No consideration has not been made about the reason for being of archives, not to mention of the strategy for establishing the archival culture. Accordingly, a paradigm shift is required for archives directly connected with the everyday life of common people. Archives of everyday life means one which interprets the behaviour and experiences of individuals(groups) within the context of society through categorizing everyday life of common people into the lesser fields. And archives of everyday life also means an organization or facility/place which documents the everyday life of individuals(groups), and collect, appraise, select and preserve the records from the view point of humanities for the reconstruction of history from the bottom. Archives of everyday life is an attempt to reconstruct memory and records on behaviour by and torment of the common people in the modern history of Korea, on the basis of which we can seek out the oppressive structure in the daily life of capitalism. Archival community should discuss about what is the meaning of records in the age of democracy unlike that of authoritarian era. We also need to have definite direction on the what kinds of records are to be created and appraised from the standpoint of common people. We are to make it possible to create Zeitgeist in the tackle of records and archives' content. on this kind of attempt archival community could make a practical contribution forward a more advanced democracy, resulted in having an opportunity to change the essence of archives.

• Korean Journal of Environment and Ecology
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• v.24 no.2
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• pp.157-165
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• 2010

This study was carried out to suggest the basic data of planting method for construction of buffer green space based on the land use in case of reclaimed land by analyzing land structure, planting concept, and planting structure in buffer green space, Rokko Island, Kobe, Japan. Rokko Island(total area: 580ha) is divided into port and logistics industry area and urban area by constructing the box type large-scale buffer green space. The land structure of buffer green space were biased mounding type, parallel mounding type, and complex mounding type. The width of buffer green space was 50meters in case of northern area, from 28 to 32meters in case of eastern area, and 37.5meters in case of western area, and the slope of that was from 18 to 25 degrees and the height of that was from 2 to 15meters. There were applied landscape and buffer planting concept on the sea side area of northern buffer green space, on the other hand landscape and shade planting concept on the Inner city side area of that. According to the result of planting structure analysis of northern buffer green space, the main woody species were those of deciduous-evergreen species grow in warm-temperate forest zone such as Quercus glauca, Cinnamomum camphora, Machilus thunbergii, Elaeagnus maritima. The results of maximum number of species and planting density by $100mm^2$ was that 9 species 22 individuals in canopy layer, 9 species 15 individuals in understory layer, 3 species 67 individuals in shrub layer, and 14 species 104 individuals in total. The plant coverage of northern buffer green space based on the ecological planting method was from 69 to 139% in case of canopy layer, from 26 to 38% in case of understory layer, from 6 to 7% in case of shrub layer, and from 101 to 184% in total. Index of plant crown volume of northern buffer green space based on the ecological planting method was from 1.40 to $3.12m^3/m^2$ in case of canopy layer, from 0.43 to $0.55m^3/m^2$ in case of understory layer, $0.06m^3/m^2$ in case of shrub layer, and from 1.89 to $3.73m^3/m^2$ in total.

• Child Health Nursing Research
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• v.19 no.4
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• pp.262-269
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• 2013

Purpose: The aims of this study is to analysis the effects of obesity management programs for children and to measure the differences in the effects by type and dependent variables in order to analyze the structures of the programs. Methods: Sixty-one peer-reviewed journals including child obesity and intervention studies published between 2000 and 2010 were included for meta-analysis. Effect size and statistics of homogeneity were by STAT 10.0. Results: A total of 61 studies were used in the analysis, and the effect size of the independent studies was determined to be -0.23 (95% CI, -0.32 ~ -0.15). Serum Leptin and Insulin were the big effect size among the studies that used dependent variables. The theses used in the research did not display publishing bias. Conclusion: Obesity management programs that have been confirmed to be effective need to be developed into regional protocols. A continuous control of obese children and research for effective intervention program are in need.