• Proceedings of the KIEE Conference
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• summer
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• pp.701-703
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• 2004

Although the electricity market structure worldwide may be different in kinds, there generally exists long-term forward market and short-term spot market. Particularly, the bilateral contract in long-term forward market fixes the price between a genco and a customer so that the customer can avoid risks due to price-spike in spot market. The genco also can make an efficient risk-hedge strategy through this bilateral contract. In this paper, we propose a new mechanism for evaluating the optimal bilateral contract price using game theory. This mechanism makes a customer reveal his/her own willingness to purchase electricity so that a fair bilateral contract price can be derived.

• English Language & Literature Teaching
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• v.18 no.3
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• pp.121-134
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• 2012

The purpose of this study is to investigate the optimal conditions for designing tasks appropriate to the elementary classroom based on the correspondence with the national curriculum, integration among four skills (listening, speaking, reading, and writing), authenticity, and interactivity. For this study, two primary English teachers volunteered to participate in the case study conducted in the spring semester of the 2012 school year. Each class observed was composed of 29 and 30 sixth graders (12-year-old learners). Data were collected through classroom observation and lesson plans. Optimality theory was used to analyze data from the lessons. From the findings, the overall ranking of constraints is Curriculum ${\gg}$ Integration ${\gg}$ Authenticity ${\gg}$ Interactivity. It is also shown that for teacher 'L', the tasks such as 'guessing game', 'photo of me', and 'role play' were appropriate to help students ask questions and give reasons for their choices. As for teacher 'C', the tasks such as 'hand spans', 'transport survey', and 'picture telling' needed to be considered in order to help students understand and write comparative sentences.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.59-64
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to chose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state- action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem. we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL)as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• Journal of Korea Game Society
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• v.11 no.4
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• pp.37-48
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• 2011

As people increasingly play online games, numerous new features have been proposed to increase players' log-on time at online gaming sites. However, few studies have investigated why people continue to play certain online games. This research would verify that enjoyment experience could be explained by the conceptual framework. In the first, this study results indicate that customers would show a higher level of loyalty if they had an optimal experience with the games. The state of flow was felt when players were aware of opportunities for personal interaction and social interaction. The personal interaction could be motivated either to achieve the high cognitive performance or by providing the equity of distribution of the objective performance in order to examine players' cognitive performance; the social interaction can be motivated either to enhance a high level of self-esteem of player or to achieve the positive reputation in order to evaluate their self-esteem. This finding can answer the questions of what enjoyment experience is and why players are repeatedly playing specific online games.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.1
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• pp.48-54
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• 2008

MMORPGs may involve a great number of concurrent players, and those servers usually have to manage hundred, or even thousands of avatars co-existing in the same virtual world. So if failing to send a command or an event message, or sending it too late may cause damages to the avatar evolution(death, injury, loss of resources), and may result in unjustified penalties for the player. Many policies could be defined to realize a ranking evaluation of available servers. Unfortunately, due to the highly dynamic characteristics of server loads and network performances, any optimal allocation would soon become sub-optimal. In order to solve those problems we propose the "time-interval based fairness partitioning method"(TIP). TIP will distribute the avatar to the game server equally with time-interval in order to avoid the problems form the unfairness of game servers load.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.221-227
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• 2009

There are customer services jointly provided by two facilities so that each customer will complete the course made up of both facilities' sub-services. The two facilities are assumed invested respectively by an infrastructure owner and one subordinate facility owner, whose partnership is built on their capital investments. This paper presents a mathematical model of Stackelberg competition between the two facility owners to derive their optimal Nash equilibrium. In this study, each facility owner's profit is consisted of fixed revenue fractions of sold services, operating costs (including depreciation cost) and maintenance costs of her facility. The maintenance costs of one facility are incurred both by failures and deterioration due to usage. Moreover, for both facilities, failures are rectified immediately by minimal repairs and preventive maintenance is carried out at a fixed time epoch. Additional assumptions are also employed to develop the model such as customer arrivals are manipulated to follow a Poisson process, and each facility's lifetime is independently Weibull-distributed. The Stackelberg game proceeds as follows. At the first stage of decision making process, the infrastructure owner (acting as a leader) decides the allocation of revenue shares based on her self-interest. After observing the allocation of revenue shares, the subordinate facility owner determines her own optimal price of services. This paper investigates actions and reactions of the two partners in the system. Then analytical conditions are proposed to achieve a unique optimal Nash equilibrium. Finally, some suggestions for further research are discussed.

• Industrial Engineering and Management Systems
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• v.14 no.3
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• pp.248-274
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• 2015

This study discusses a contract to promote collection and recycling of used products in a green supply chain (GSC). A collection incentive contract is combined with a reward-penalty contract. The collection incentive contract for used products is made between a retailer and a manufacturer. The reward-penalty contract for recycling used products is made between a manufacturer and an external institution. A retailer pays an incentive for collecting used products from customers and delivers them to a manufacturer with a product order quantity under uncertainty in product demand. A manufacturer remanufactures products using recyclable parts with acceptable quality levels and covers a part of the retailer's incentive from the recycled parts by sharing the reward from an external institution. Product demand information is assumed as (i) the distribution is known (ii) mean and variance are known. Besides, the optimal decisions for product quantity, collection incentive of used products and lower limit of quality level for recyclable parts under decentralized integrated GSCs. The analysis numerically investigates how (1) contract for recycling activity, (ii) product demand information and (iii) quality of recyclable parts affect the optimal operation for each GSC. Supply chain coordination to shift IGSC is discussed by adopting Nash Bargaining solution.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.51-59
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• 2018

Despite the advantages of energy arbitrage using energy storage systems (ESSs), the high cost of ESSs has not attracted storage owners for the arbitrage. However, as the costs of ESS have decreased and the price volatility of the electricity market has increased, many studies have been conducted on energy arbitrage using ESSs. In this study, the existing two-period model is modified in consideration of the ESS cost and risk-free contracts. Optimal investment strategies that maximize the sum of external effects caused by price changes and arbitrage profits are formulated by market participants. The optimal amounts of ESS investment for three types of investors in three different market structures are determined with game theory, and strategies in the form of the mixed-complementarity problem are solved by using the PATH solver of GAMS. Results show that when all market participants can participate in investment simultaneously, only customers invest in ESSs, which means that customers can obtain market power by operating their ESSs. Attracting other types of ESS investors, such as merchant storage owners and producers, to mitigate market power can be achieved by increasing risk-free contracts.

• Journal of Korea Game Society
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• v.17 no.1
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• pp.89-98
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• 2017

This paper presents a novel ARAP (as-rigid-as-possible) approach to real-time simulation of physics-based deformation. To cope with one, two and three dimensional deformable bodies in an efficient, robust and uniform manner, we introduce a deformation graph of oriented particles and formulate the corresponding ARAP deformation energy. For stable time integration of the oriented particles, we develop an implicit integration scheme formulated in a variational form. Our method seeks the optimal positions and rotations of the oriented particles by iteratively applying an alternating local/global optimization scheme. The proposed method is easy to implement and computationally efficient to simulate complex deformable models in real time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.34-49
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• 2015

Market means of spectrum trading have been utilized as a vital method of spectrum sharing and access in future cognitive radio system. In this paper, we consider the spectrum trading with multiple primary carrier providers (PCP) leasing the spectrum to multiple secondary carrier providers (SCP) for a short period of time. Several factors including the price of the resource, duration of leasing, and the spectrum quality guides the proposed model. We formulate three trading policies based on the game theory for dynamic spectrum access in a LTE based cognitive radio system (CRS). In the first, we consider utility function based resource sharing (UFRS) without any knowledge of past transaction. In the second policy, each SCP deals with PCP using a non-cooperative resource sharing (NCRS) method which employs optimal strategy based on reinforcement learning. In variation of second policy, third policy adopts a Nash bargaining while incorporating a recommendation entity in resource sharing (RERS). The simulation results suggest overall increase in throughput while maintaining higher spectrum efficiency and fairness.