• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.973-982
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• 2009

Two losing games that can be combined, either by periodic alternation or by random mixture, to form a winning game are known as Parrondo games. We consider a collective version of Parrondo games in which players are allowed to choose the game to be played by the whole ensemble in each turn. In this paper, we analyze the long-range optimization strategy for all choices of the parameters and find the expected average profit in the steady state.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.424-427
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• 1995

In this paper, a control law based on the receding horizon concept which robustly stabilizes time-varying discrete linear systems, is proposed. A dynamic game problem minimizing the worst case performance, is adopted as an optimization problem which should be resolved at every current time. The objective of the proposed control law is to guarantee the closed loop stability and the infinite horizon $H^{\infty}$ norm bound. It is shown that the objective can be achieved by selecting the proper terminal weighting matrices which satisfy the inequality conditions proposed in this paper. An example is included to illustrate the results..

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.117-126
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• 2023

To improve the overall performance and realism of your game, it is important to calculate the trajectory of a projectile accurately and quickly. One way to increase realism is to use a ballistic model that takes into account factors such as air resistance, density, and wind when calculating a projectile's trajectory. However, the more these factors are taken into account, the more computationally time-consuming and expensive it becomes, creating a trade-off between overall performance and efficiency. Therefore, we present an optimal solution to find a balance between ballistic model accuracy and computation time. We perform ballistic calculations using numerical methods such as Euler, Velocity Verlet, RK2, RK4, and Akima interpolation, and measure and compare the computation time, memory usage (RSS, Resident Set Size), and accuracy of each method. We show developers how to implement more accurate and efficient ballistic models and help them choose the right computational method for their numerical applications.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.37-38
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• 2023

컴퓨터 부품의 고성능화로 점점 게임이 요구하는 사양이 높아지는 추세이다. 따라서 게임 개발에 있어 최적화가 필수적으로 요구된다. 본 논문에서는 '오브젝트 풀링'이라는 메모리 최적화 기법을 소개한다. 따라서 '오브젝트 풀링'을 적용한 탄막 게임을 만들어 메모리 최적화를 직접 구현해보고 연구한다.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.258-260
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• 2007

MAS based market simulator has attracted the attentions of people who are interested in using or developing electricity market simulator. MAS based approach makes it possible to model each market participant's strategic behaviors. Traditional market simulators have used optimization formulation to model market operation, which has been used since vertically integrated system. Optimization mainly uses cost minimization or welfare maximization of entire system. Therefore it is somehow difficult to model the independently strategic behaviors of market participants. MAS is one of AI technology based on distributed intelligence which makes it possible to model independently acting entities in competitive market. This paper proposes the method to model strategic participants in electricity market based on MAS.

• KIEE International Transactions on Power Engineering
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• v.3A no.1
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• pp.42-46
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• 2003

The economic operation of a utility in a deregulated environment brings about optimization problems different from those in vertically integrated one［1］. While each utility operates its own generation capacity to maximize profit, the market operator (or system operator) manages and allocates all the system resources and facilities to achieve the maximum social welfare. This paper presents a sequential application of non-cooperative and cooperative game theories in analyzing the entire power transaction process.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.9
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• pp.392-398
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• 2006

Maintenance scheduling of generating units (MSU) has strategic dimension in an oligopolistic market. Strategic MSU of gencos can affect a market power through capacity withdrawal which is related to bidding strategy in an generation wholesale market. This paper presents a combined framework that models the interrelation between competitive bidding and strategic MSU. The combined game model is represented as some sub-optimization problems of a market operator (MO) and gencos, that should be solved through bi-level optimization scheme. The gradient method with dual variables is also adopted to calculate a Nash Equilibrium (NE) by an iterative update technique in this paper. Illustrative numerical example shows that NE of a supply function equilibrium is obtained properly by using proposed solution technique. The MSU made by MO is compared with that by each genco and that under perfect competition market.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• Journal of Korea Game Society
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• v.17 no.4
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• pp.137-148
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• 2017

Since the power consumption of data centers is large and computer serves take a large portion of it, there have been much research on the power saving of servers in various ways recently. Among the units of severs CPU is one of major power consuming units. In this paper, a method of client-server assignment for minimizing the CPU power consumption of servers in a game server cluster is proposed. We model the client-server assignment problem as an optimization problem, and find a solution to the problem using a simulated annealing-based technique. One of major features of our method is to select a proper operating frequency according to the amount of load on a server. The selection of a lower frequency in case of low load will result in reducing power consumption. To our survey, little research on client-server assignment in consideration of power consumption has been carried out.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.210-212
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• 2016

Today, video games created via 3D softwares become a core part of the essential the video game contents field because their properties that can produce more easier than 2D games and can save budget of contents makings. It is very important that reducing polygon counts of 3D characters and environments for Gaming optimization. We can formulate elaborate 3D game models with low polygon counting in virtue of technological advancements, and these technologies continue to evolve. In 2012, Pixar made public Open subdivision which is the new technology to make high quality 3D models with low polygons and distributed that via Open source verification. This paper will compare and analyze the characteristics, and merits and demerits of these various kinds of these skills(Mesh smooth, Turbo Smooth, Open subdivision) and will inquire which method is the most efficient one to make 3D video games.