• Journal of Contemporary Eastern Asia
• /
• v.16 no.1
• /
• pp.69-81
• /
• 2017

This study examines how South Korean governments responded to the outbreak of Middle East Respiratory Syndrome Coronavirus (MERS) using the adaptive governance framework. As of November 24, 2015, the MERS outbreak in South Korea resulted in the quarantine of about 17,000 people, 186 cases confirmed, and a death of 38. Although the national government had overall responsibility for MERS response, there is no clear understanding of how the ministries, agencies, and subnational governments take an adaptive response to the public health crisis. The paper uses the adaptive governance framework to understand how South Korean governments respond to the unexpected event regarding the following aspects: responsiveness, public learning, scientific learning, and representativeness of the decision mechanisms. The framework helps understand how joint efforts of the national and subnational governments were coordinated to the unexpected conditions. The study highlights the importance of adaptive governance for an effective response to a public-health related extreme event.

• East Asian Economic Review
• /
• v.19 no.1
• /
• pp.99-114
• /
• 2015

What explains the sharp increase in the Chinese economy's indebtedness, in particular the China's onshore corporate debt? Has the overall debt burden reached a threshold where it poses a systemic risk, thereby making the economy vulnerable to a "Lehman Moment" - with disorderly unwinding of the private sector and sovereign debt? What are the short and longer term implications of China's growing debt problems on domestic economic growth and the broader global political economy? What has Beijing done to ameliorate the problem, how effective were its efforts, and what must it do to deal with this problem?

• International Journal of Advanced Culture Technology
• /
• v.10 no.2
• /
• pp.154-161
• /
• 2022

The Korean government has recently invigorated the activities of public diplomacy. It is based on the Public Diplomacy Act enacted in 2016. However, there is a widespread concern that it was belatedly enacted and showed necessity to a revision. We believe that this paper contains three contributions which were not sufficiently addressed before. First, we identify the current state of public diplomacy-related legislation in Korea. Second, we argue the necessity to critically review the legal adequacy of Public Diplomacy Act with a consideration of rapidly changing external environment. Lastly, we propose several ways of revision for the future development of public diplomacy in Korea. When revising the Act, it is necessary to make clear a legal connection between the general law and the special law as in the case of the Korea Foundation Act and the Public Diplomacy Act. In this regard, it is worth examining the relationship between the Framework Act on International Development Cooperation and related norms. In addition, the role of the private sector and subnational governments should be expanded. For this purpose, a method and level of cooperation with the private sector should be clearly defined.

• Journal of Korean Society of Forest Science
• /
• v.111 no.4
• /
• pp.603-612
• /
• 2022

The study aims were to evaluate a machine-learning, algorithm-based, forest biomass-estimation model to estimate subnational forest biomass and to comparatively analyze REDD+ forest reference emission levels. Time-series Landsat satellite imagery and ESA Biomass Climate Change Initiative information were used to build a machine-learning-based biomass estimation model. The k-nearest neighbors algorithm (kNN), which is a non-parametric learning model, and the tree-based random forest (RF) model were applied to the machine-learning algorithm, and the estimated biomasses were compared with the forest reference emission levels (FREL) data, which was provided by the Paraguayan government. The root mean square error (RMSE), which was the optimum parameter of the kNN model, was 35.9, and the RMSE of the RF model was lower at 34.41, showing that the RF model was superior. As a result of separately using the FREL, kNN, and RF methods to set the reference emission levels, the gradient was set to approximately -33,000 tons, -253,000 tons, and -92,000 tons, respectively. These results showed that the machine learning-based estimation model was more suitable than the existing methods for setting reference emission levels.