• Land and Housing Review
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• v.4 no.1
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• pp.107-117
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• 2013

This study aimed to assess the rental housing ABS in Korea, and to suggest ways of improving the structure of existing rental housing ABS. Thus, the three major assessment for existing public rental housing ABS case can be summarized as follows : First, when viewed in terms of the accounting treatment, rental housing ABS which use the future receivables as underlying asset, can not enjoy off-balance-sheet effect. Second, when viewed from the point of financing costs, the rental housing ABS interest rate being higher than unsecure bond is very unreasonable nevertheless the ABS being off-balanced. Third, when viewed from the liquidity effect, the originator (LH) use the ABS as a means of diversifying funding in a serious liquidity crisis situation. The Improvement of rental housing ABS based on the evaluation results can be summarized into two broad. First, it is a plan to handle the off-balance-sheet effect in a way of changing the accounting treatment of rental payment. Second, it is a plan to reducing the structuring cost and interest rate in ways of multi-asset securitization structure, self-trust structure, and adopting legal CB structure.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.133-138
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• 2016

As UAE has witnessed tremendous growth and diversification in its economy, logistics in particular has had great success as one of the first logistics clusters and hub to develop global business competitiveness but a few data and practical study related with logistics business competitiveness have existed due to lack of the openness in the region. In this sense, the purpose of this study was to carry out competitive analysis between UAE and not only major Middle East countries and but also Global countries using Porter's Diamond model. As a result of analysis with Middle East Countries such as Saudi Arabia, Qatar, UAE gained the highest score in factor conditions followed by logistics conditions, supported industries and demand conditions. UAE also is required to reduce cost and time of logistics process and get higher ease of international shipment, logistics competency and logistics timeliness. The logistics data set released from international and reputable bodies like WEF, OECD and IMD will assist to analyses logistics competitiveness among hub countries in future studies.

• The Southeast Asian review
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• v.28 no.2
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• pp.181-212
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• 2018

In 2017, the government of Duterte, in the second year of the ruling, more strongly promoted peace and order policies and expressed independent diplomacy as the chairman of ASEAN. He continued to fight against drugs and tried to increase his political legitimacy through the punishment for corrupt officials. He also declared martial law in the Mindanao region because of the dissolution of the Maute group, a Muslim terrorist organization, and strengthened counterterrorism cooperation externally. In addition, as to Communist militants, he took the initial reconciliation gesture and promoted peace negotiations, however, concluded the peace tide and started the suppression operation due to a series of bloodshed. He still has a strong drive in peace and order issues, backed up by high support rate, but it is becoming a factor of anxiety as the socioeconomically underprivileged and minority groups are increasingly alienated. As the chairman of ASEAN, Duterte has a certain distance from the United States, which is a firm ally, but has turned to increase familiarity with China and Russia, which can take substantial economic benefits. Through diversifying the external economic support and increase of tax revenue, the priority task was to establish the infrastructure. Although the Philippines, which has a high economic growth rate, has a strong expectation that it can establish a solid infrastructure, tax reforms should be successfully completed in order not to repeat the previous failures, which has traditionally increased foreign debt burden by relying on external resources. It seems that it is necessary to find the meeting point of the foreign policy of Duterte and new Korean government's New Southern Policy, and to find possible economic cooperation policies to improve Philippine infrastructure.

• Journal of Ginseng Culture
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• v.6
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• pp.116-134
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• 2024

This study aimed to identify the issues in Korean ginseng exports through analyzing the ginseng market. Therefore, the study examined the current ginseng production status in South Korea and China, the major ginseng-producing countries in Northeast Asia, including cultivated areas, harvested areas, and production volumes. For South Korea, specific data on ginseng, such as average prices, operating costs, and production costs, were compiled to demonstrate the production competitiveness of Korean ginseng from a production perspective. Furthermore, as major ginseng-exporting countries, South Korea, China, and Hong Kong's export trends, including export quantities, export values, and export prices, as well as crucial export items and tariff rates, were summarized to showcase the export competitiveness of Korean ginseng. Additionally, this study aimed to understand the consumption patterns of ginseng in China, Hong Kong, and Taiwan by presenting various cases and events in these countries. Based on information related to production, export, and consumption, this study identified obstacles in the ginseng export process, including market downturns, weakened price competitiveness of Korean ginseng, increased market share of competing products like Chinese and Western ginseng, a lack of promotion and marketing, and insufficient development and export of various ginseng products. In response, strategies for overcoming these obstacles were proposed, including diversifying exports, establishing effective production systems, enhancing quality and branding, strengthening promotion and marketing efforts, and developing various ginseng products.

• Journal of Music and Human Behavior
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• v.21 no.2
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• pp.135-157
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• 2024

In this study, the authors developed and implemented an online music-based support program to prevent burnout among university hospital nurses. This study involved 40 nurses from three university hospitals who shared their subjective experiences after participating in 8 music-based non-simultaneous online sessions. The responses were collected as qualitative data and analyzed using the qualitative content analysis method. The analysis identified 66 meaning units, 10 themes, and 3 categories, which included: 'Recovery of physical and psychological stability', 'Self-care and acceptance', and 'Rediscovery of pride and meaning as a nurse'. This study is significant for exploring the experiences of university hospital nurses who participated in a remotely implemented music-based psycho-emotional support program, with respect to burnout prevention. For future directions, we suggest a more in-depth exploration of specific burnout factors and an expansion of research through the diversification of research methods to refine programs aimed at alleviating nurse burnout.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.