• Korean Journal of Culture and Social Issue
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• v.13 no.4
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• pp.113-134
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• 2007

This study investigated body-related values, body-esteem, and the relationship between them based on the survey data drawn from female college students in three East Asian countries(Korea, Japan, and China). 168 Korean, 108 Chinese, and 152 Japanese female college students responded to questions designed to measure four sorts of body values (operability, inclination, locus of evaluation, and social utility) and four dimensions of body esteem (appearance, weight, health, overall). The results showed that body-related values and body-esteem differ among three countries. Japanese showed the highest acceptance level for the voluntary body alteration(operability), while chinese scored the lowest. Inclination to body appearance over health was higher in Korean than in Japanese and in Chinese. Korean also evaluated the importance of body appearance and its social utility the highest, followed by Japanese and Chinese. There were dramatic differences in body esteem between Korean and Japanese. Regarding body-esteem, Korean showed the highest appearance-esteem, but the health-esteem was the lowest. On the contrary, Japanese showed the highest health-esteem, but the appearance-esteem was lowest. Chinese showed the highest weight-esteem. Four sorts of body values showed significant correlations with appearance-esteem and weight-esteem, respectively but not with health-esteem. Overall, the result supported the prediction that different political, social, and economic backdrops in three countries would be related with different body-related values and body esteem in the female college students.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.29-42
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• 2023

In this paper, we propose a method to enhance the prediction accuracy of solar irradiance for three major South Korean cities: Seoul, Busan, and Incheon. Our method entails the development of five generative models-vanilla GAN, CTGAN, Copula GAN, WGANGP, and TVAE-to generate independent variables that mimic the patterns of existing training data. To mitigate the bias in model training, we derive values for the dependent variables using random forests and deep neural networks, enriching the training datasets. These datasets are integrated with existing data to form comprehensive solar irradiance prediction models. The experimentation revealed that the augmented datasets led to significantly improved model performance compared to those trained solely on the original data. Specifically, CTGAN showed outstanding results due to its sophisticated mechanism for handling the intricacies of multivariate data relationships, ensuring that the generated data are diverse and closely aligned with the real-world variability of solar irradiance. The proposed method is expected to address the issue of data scarcity by augmenting the training data with high-quality synthetic data, thereby contributing to the operation of solar power systems for sustainable development.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1281-1293
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• 2021

The recent launch of the GOCI-II enables South Korea to have the world's first capability in deriving the ocean color data at geostationary satellite orbit for about 20 years. It is necessary to develop a consistent long-term ocean color time-series spanning GOCI to GOCI-II mission and improve the accuracy through validation using in situ data. To assess the GOCI-II's early mission performance, the objective of this study is to compare the GOCI-II Chlorophyll-a concentration (Chl-a), Colored Dissolved Organic Matter (CDOM), and remote sensing reflectances (R_rs) through comparison with the GOCI data. Overall, the distribution of GOCI-II Chl-a corresponds with that of the GOCI over the Yellow Sea, Korea Strait, and the Ulleung Basin. In particular, a smaller RMSE value (0.07) between GOCI and GOCI-II over the summer Ulleung Basin confirms the GOCI-II data's reliability. However, despite the excellent correlation, the GOCI-II tends to overestimate Chl-a than the GOCI over the Yellow Sea and Korea Strait. The similar over-estimation bias of the GOCI-II is also notable in CDOM. Whereas no significant bias or error is found for R_rs at 490 nm and 550 nm (RMSE~0), the underestimation of R_rs at 443 nm contributes to the overestimation of GOCI-II Chl-a and CDOM over the Yellow Sea and the Korea Strait. Also, we show over-estimation of GOCI-II R_rs at 660 nm relative to GOCI to cause a possible bias in Total suspended sediment. In conclusion, this study confirms the initial reliability of the GOCI-II ocean color products, and upcoming update of GOCI-II radiometric calibration will lessen the inconsistency between GOCI and GOCI-II ocean color products.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.371-381
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• 2020

The Ministry of Environment (ME) is planning to adopt in 2020 the IUCN regional Red List for "Guidelines for listing and delisting rare & endangered species and management of endangered Species System". The ME designated 377 species of vascular plants on the regional Red List. In a previous study it had been suggested that 103 species from this list are candidates for the regional Red List. With respect to a possible Red List, we assessed 59 species (after excluding 34 additional NA species and ten endemic species). These assessments indicated that 16 species are at the "threatened" level. Of those, one species is Critically Endangered, ten are Endangered, and five are Vulnerable. A further four species are classified as Near Threatened, 30 as Of Least Concern, and nine as Data Deficient. We found that most of the assessments proposed by the Ministry of Environment were not supported by scientific data, including quantitative geographic data (over 70%) in Criteria B. In order to determine the endangered species belonging to the orchid family, it is necessary to obtain records of illegal activities or data on overcollection. The current problem with the Ministry of Environment Red List has been the lack of management of scientific data on species showing a trend in decreasing population in the mid- to long-term; thus, there is a lack of critical resources for policy-makers. The ME legally designated categories and assessment, and the lack of expertise in failing to comply with the legal law by itself. The key to presenting an accurate overview of the state of Korean flora is to fill the information gaps with respect to significant geographical and taxonomical biases in the quality and quantity of data. By regularly updating the qualified data, we will be able to track the changes in the conservation status of the flora and inform the necessary conservation policies.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Analyses & Alternatives
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• v.6 no.2
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• pp.79-115
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• 2022

This study aims to account for electoral choice in the 2020 presidential election by focusing on social identity which forms the basis for core partisan groups. Two views compete to explain the origins of polarization, policy versus party. One emphasizes policy as more influential in choosing presidential candidates. This follows the tradition of retrospective voting theory in which voters' choice rely on government performance. Incumbent president whose performance proves well are rewarded to be reelected. Policy performance is based on measures around distinctive preferences for government spending. Republican Individuals prefer individual responsibility to government support, while Democratic counterparts support government support. Another perspective put an emphasis on the role partisanship which favors in-party members and disfavors partisan out-groups. Interparty animosity plays the key role in determining electoral behavior. This study relies on the Views of the Electorate Research (VOTER) Survey which provides a panel data of several waves from 2011 to 2020. A comparative evaluation of two views highlights three findings. First, policy matters. Policy preferences of voters are the primary drives of political behavior. Electoral outcomes in 2020 turned out to be the results of policy considerations of voters. 53.7 percent of voters tilted toward individual responsibility voted for Trump, whereas 70.4 percent of those favorable views of government support than individual responsibility voted for Biden. Thus effects of policy correspond to a positive difference of 26.4 percent points. Second, partisanship effects are of similar extent in influencing electoral choice of candidates: Democrats are less likely to vote for Trump by 42.4 percent points, while Republicans are less likely to vote for Biden by 48.7 percent points. Third, animosity of Republicans toward Democrat core groups creates 26.5 percent points of favoring Trump over Biden. Democrat animosity toward Republican core groups creates a positive difference of 13.7 percent points of favoring Biden.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.172-189
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• 2023

This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.

• Journal of the Daesoon Academy of Sciences
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• v.41
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• pp.27-61
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• 2022

Documentation related to Mugeuk-do (Limitless Dao) is rare in comparison to other Korean new religions given that it has been open to the public and translated since the 1970s. Due to its rarity, the documentation has been used uncritically, without there being any comparative study or historical research. It is undeniable that distortions and fallacies are embedded in these documents, and this has resulted in quite a few problems in precisely understanding Mugeuk-do and Daesoon Jinrihoe (The Fellowship of Daesoon Truth), an order that has inherited the legacy of Mugeuk-do. In this regard, this study aims to critically define the characteristics and limitations of the major documents related to Mugeuk-do that were published by the colonial government in the 1920s~1930s and recorded by multiple orders in the 1970s-1980s through comparisons. An attempt to conduct this research allows for the discovery of a solution to the problem of uncritical usage of those materials. The documents produced by the colonial government that can be used as basic texts to study Mugeuk-do are The General Conditions of the Religion Mugeuk-do (無極大道敎槪況) and Unofficial Religions of the Korea (朝鮮の類似宗敎). These can be found through bibliography, comparison, and historical research. Chapters 6, 7, and 8 of The General Conditions of the Religion Mugeuk-do are a possible source on the order that reflects the circumstances of Mugeuk-do until 1925. In the case of Unofficial Religions of the Korea, if the descriptive perspective on unofficial religions is excluded, the articles written about the circumstances post 1925 have credibility. Another document that describes multiple orders and can be used as a basic text is chapter 2 of 'Progress of the Order' in Daesoon Jinrihoe's The Canonical Scripture. This is because its record precisely reflects the conditions of the era, with regard to the fact that it is the freest from distortions caused by changes in the belief system and it is less biased towards certain sects or denominations. Furthermore, the collection period of the articles is the earliest. Accordingly, as basic texts, Chapters 6, 7, and 8 of The General Conditions of the Religion Mugeuk-do and the articles from Unofficial Religions of the Korea after 1925, as well as chapter 2 of 'Progress of the Order' in The Canonical Scripture are appropriate for studying Mugeuk-do. In addition, Overview of Bocheonism, History of Jeungsan-gyo, and The True Scripture of the Great Ultimate can be utilized as references after removing distortions and fallacies through comparative study. Henceforth, relevant documents should be utilized to establish comprehensive data on Mugeuk-do through comparative and historical research.

• Korean Association of Arts Management
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• no.51
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• pp.135-166
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• 2019

Recently, the Japan Cultural Agency announced a plan for revitalizing the art market represented by reading museums (advanced art museums) to promote industry through strengthening the sustainability and economics of art museums. Along with these policy announcements, the Japanese cultural system and Bypyeongje are divided into pros and cons, and there has been a heightened opposition, which is now in a state where policy promotion has been temporarily suspended. The opposite reason is that it does not meet the museum's inherent purpose of preservation and lore, and the reason for favoring that commercialism can ruin the art world is that the Japanese art society is other than art museums and museums Also, it consists of non-profit organizations, art festival administration organizations, support staff, volunteers, etc., but because of the high subsidy bias, no real labor costs are paid, which means that it is virtually neglected. Also, there is a vigilance that the art society itself, which reduces its reliance on subsidies in response to social changes, can survive. Seeing that the situation is not much different from Japan, Korea is also actively discussing new establishments of the National Art Bank, performing art appraisal and evaluation functions for revitalizing art works, art loan, art trust, etc. There is. As it is difficult to solve realistic problems with subsidies from the future situation, it is difficult for us to expand investment in culture, and culture and economy are united and linked. You will find a plan to make it operational. In this regard, it is thought that the examination of the cultural and economic agency's strategy, represented by the Japanese advanced art museums, gives us a meaningful suggestion.