• Journal of Korea Technology Innovation Society
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• v.14 no.3
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• pp.516-551
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• 2011

This study analysed the institutional evolution of Korea's international cooperation of science and technology (S&T) from the viewpoint of the historical institutionalism. For this, it examined Korea's institutions for international S&T cooperation by dividing the whole period from the Korean war to the present into five sub-periods; period of technology aids, technology transfer, mutual cooperation, expanded cooperation, and highly sophisticated cooperation, respectively. It, then, reviewed the evolving process and characteristics of each period. In this study, the structure (environment), the actor (government), the institution of higher rank (science & technology policy) were considered as variables influencing upon the institutions of the international S&T cooperation. Upon this assumption, this study analysed how and through what evolutionary process the international S&T cooperation institutions have evolved so far. This study obtained the following conclusions; First, the study confirmed the existence of the "institutional layering" in the institutions of the international S&T cooperation in Korea. The momentums for the change of the institutions of the international S&T cooperation stem from international environment and domestic economic environment. They influence upon economic policy, industrial policy, and S&T policy, which, together with the actor (the government), again brings about the institutional evolution of the international S&T cooperation. Second, the institutional evolution of the international S&T cooperation is taking place gradually. As mentioned above, the momentums for the change of the institutions of the international S&T cooperation originate from international and domestic macro environment. These momentums do not directly influence upon the institutions of the international S&T cooperation, rather they give indirect influence, through other related institutions, upon the institutions of the international S&T cooperation and make its gradual change or evolution. This is because the institutions of the international S&T cooperation have the "institutional layering".

• Journal of Preventive Medicine and Public Health
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• v.47 no.6
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• pp.298-308
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• 2014

Objectives: To assess the current public participation in-local health policy and its implications through the analysis of policy networks in health center programs. Methods: We examined the decision-making process in sub-health center installations and the implementation process in metabolic syndrome management program cases in two districts ('gu's) of Seoul. Participants of the policy network were selected by the snowballing method and completed self-administered questionnaires. Actors, the interactions among actors, and the characteristics of the network were analyzed by Netminer. Results: The results showed that the public is not yet actively participating in the local public health policy processes of decision-making and implementation. In the decision-making process, most of the network actors were in the public sector, while the private sector was a minor actor and participated in only a limited number of issues after the major decisions were made. In the implementation process, the program was led by the health center, while other actors participated passively. Conclusions: Public participation in Korean public health policy is not yet well activated. Preliminary discussions with various stakeholders, including civil society, are needed before making important local public health policy decisions. In addition, efforts to include local institutions and residents in the implementation process with the public officials are necessary to improve the situation.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.289-315
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• 2015

The Fixed book price policy, a portion of publication and printing promotion act applied from February 2003 in the South Korea, is a system of fixed book prices that administered by a government body. The publishing industries had been attempted to lower the discount rate and to extend the application scope. The amendment for the attempts was passed in April 2014, and implemented from November 2014. From the library point of view, this amendment caused a reduction of buying library materials. For this reason, the agenda about expansion of material budget in libraries has been recognized as the alternative. The purpose of this study is to analyze the stance and role of libraries as actors in the policy process. Based on this, this study also attempt to identify usefulness and improvement point of Policy Network Model. For this purpose, this study identifies actor's internal characteristics as an improvement point that previous studies did not identified.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.505-510
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• 2005

The RPO(randomized policy optimizer) algorithm, which utilizes probabilistic policy for the action selection, is a recently developed tool in the area of reinforcement learning, and has been shown to be very successful in several application problems. In this paper, we propose a modified RPO algorithm, whose critic network is adapted via RLS(Recursive Least Square) algorithm. In order to illustrate the applicability of the modified RPO method, we applied the modified algorithm to Kimura's robot and observed very good performance. We also developed a MATLAB-based animation program, by which the effectiveness of the training algorithms on the acceleration or the robot movement were observed.

• Journal of Korean Association for Spatial Structures
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• v.21 no.2
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• pp.41-48
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• 2021

A smart tuned mass damper (TMD) is widely studied for seismic response reduction of various structures. Control algorithm is the most important factor for control performance of a smart TMD. This study used a Deep Deterministic Policy Gradient (DDPG) among reinforcement learning techniques to develop a control algorithm for a smart TMD. A magnetorheological (MR) damper was used to make the smart TMD. A single mass model with the smart TMD was employed to make a reinforcement learning environment. Time history analysis simulations of the example structure subject to artificial seismic load were performed in the reinforcement learning process. Critic of policy network and actor of value network for DDPG agent were constructed. The action of DDPG agent was selected as the command voltage sent to the MR damper. Reward for the DDPG action was calculated by using displacement and velocity responses of the main mass. Groundhook control algorithm was used as a comparative control algorithm. After 10,000 episode training of the DDPG agent model with proper hyper-parameters, the semi-active control algorithm for control of seismic responses of the example structure with the smart TMD was developed. The simulation results presented that the developed DDPG model can provide effective control algorithms for smart TMD for reduction of seismic responses.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.467-476
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• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• Journal of Korea Game Society
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• v.10 no.3
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• pp.47-59
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• 2010

Differing from most of current studies which recognizing game item cash-trade as simple static system, this study approaches game item cash-trade as Complex Adaptive System through historical analysis. The item-trade is a complex phenomenon converging between cyber-economy and real-economy, and production and consumption process of game-item are evolving dynamically over time. The results are following: first, the early item-trade emerges in endogenously rather than results from purposed system designed by singular actor. Second, after the early item-trade, the trade system as a CAS which various voluntary actors(single user, factory, game company, user community, agency, etc.) participates in is self-organizing for trading safety and efficiency. Third, the complex adaptive item-trade system satisfies actor's needs interdependently and accelerate positive feedback powerfully. This study implies that purposeful control disregarding emergent adaptive item-trade system distorts system efficiency and can lead to unintended policy failure.

• The Korean Journal of Franchise Management
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• v.11 no.1
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• pp.45-60
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• 2020

Propose: The expansion of the delivery market in franchise business is a positive means of advertising and promotion for franchisees and contributes to substantial sales growth for stores. However, unrestricted and uncontrolled delivery sales and business activity of franchisee directly lead to encroachment of business territory between franchisees, resulting in increased operating costs of franchisees and conflicts between franchisees over rights and interests on franchise business. Moreover, in relation to the restrictions on the opening of competitors, it is incapacitating the law intent of prohibiting unfair encroachment of business territory, in the issue of the Fair Franchise Act in regard to guarantee of exclusive sales and business activity rights of franchisee. This study aims to point out major problems arising out of franchisee's infinite competition on delivery sales and business activity that are not restricted or controlled and then suggest legal supplements, policy tasks, and practical implications for improvement on the issues. Literature Review: In franchising business transactions, vertical restraints are associated with the exclusive territory establishment, control of transaction area, restriction of intangible sales and business activity of franchisee. Therefore, in the franchise business, it is necessary to take positive interpretation and application on e-commerce, the area of e-commerce, and delivery trading area and find proper and practical ways, by virtue of constructive attitude of each actor, to reduce the encroachment of business territory and various conflicts caused by unrestricted delivery trading area. Conclusion and suggestion: The finding shows that unrestricted or uncontrolled delivery sales and business activity of franchisees cause encroachment of business territory and many conflicts among franchisees. And this matters also weaken the legislation of the law on the protection of the business territory and can be negative factors that disrupt the protection of identity and sound development of the franchise industry in the long run. Therefore, in the franchise business, it is necessary to take positive interpretation and application on e-commerce, the area of e-commerce, and delivery trading area and find proper and practical ways, by virtue of constructive attitude of each actor, to reduce the encroachment of business territory and various conflicts caused by unrestricted delivery trading area.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.112-122
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• 2022

Food security and its sovereignty have become among the most important key issues due to changes in the international situation. Regarding these issues, many countries now give attention to smart agriculture, which would increase production efficiency through a data-based system. The Korean government also has attempted to promote smart agriculture by 1) implementing the agri-food ICT (information and communications technology) policy, and 2) increasing the R&D budget by more than double in recent years. However, its endeavors only centered on large-scale farms which a number of domestic farmers rarely utilized in their farming. To promote smart agriculture more effectively, we diagnosed the government R&D trends of smart agriculture based on NTIS (National Science and Technology Information Service) data. We identified the research trends for each R&D period by analyzing three pieces of information: the regional information, research actor, and topic. Based on these findings, we could suggest systematic R&D directions and implications.

• Information Systems Review
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• v.21 no.4
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• pp.125-141
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• 2019

With the advent of deep learning technology, which is represented by AlphaGo, artificial intelligence (A.I.) has quickly emerged as a key theme of digital transformation to secure competitive advantage for businesses. In order to understand the trends of A.I. based digital transformation, a clear comprehension of the A.I. business ecosystem should precede. Therefore, this study analyzed the A.I. business ecosystem from the multi-actor network perspective and identified the A.I. platform strategy type. Within internal three layers of A.I. business ecosystem (infrastructure & hardware, software & application, service & data layers), this study identified four types of A.I. platform strategy (Tech. vertical × Biz. horizontal, Tech. vertical × Biz. vertical, Tech. horizontal × Biz. horizontal, Tech. horizontal × Biz. vertical). Then, outside of A.I. platform, this study presented five actors (users, investors, policy makers, consortiums & innovators, CSOs/NGOs) and their roles to support sustainable A.I. business ecosystem in symbiosis with human. This study identified A.I. business ecosystem framework and platform strategy type. The roles of government and academia to create a sustainable A.I. business ecosystem were also suggested. These results will help to find proper strategy direction of A.I. business ecosystem and digital transformation.