• Journal of Electrical Engineering and Technology
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• v.2 no.4
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• pp.494-499
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• 2007

In this paper, we have investigated how transmission network constraints can be modeled in an electricity market equilibrium model. Under Cournot competition assumption, a game model is set up considering transmission line capacity constraints. Based on locational marginal pricing principle, market clearing is formulated as a total consumers# benefit maximization problem, and then converted to a conventional optimal power flow (OPF) formulation with a linearized transmission model. Using market clearing formulation, best response analysis is formulated and, finally, Nash equilibrium is formulated. In order for illustration, a numerical study for a four node system with two generating firms and two loads are presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1738-1743
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• 2007

This paper addresses the bidding strategies of a pumped-storage hydro plant in an electricity market. Competitive bidding of pumping and generating of a pumped-storage plant is formulated in a game theoretic problem in accordance with the three different ownership of scheduling; Market Operator(MO), generating company(Genco), and combined type of MO and Genco. Optimal conditions for Nash Equilibrium are derived in the form of market prices during the scheduling periods. Simulation results show the different ownership models produce different schedules of pumping and generating, which correspond to the objective of the scheduling owner of a pumped-storage hydro plant.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.346-349
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• 1994

This paper is concerned with a motion control of a manipulator under parametric uncertainties and external disturbances. The parametric uncertainties are regarded as internally generated disturbances in the manipulator. Based on this idea, we formulate a model reference control problem with desired disturbance attenuation. The solution of this control problem not only reduces the worst-case effect on tracking error due to internal and external disturbances (combined disturbances) as much as possible, but also achieve optimal tracking when perturbations are absent. In order to solve the control problem which is formulated in this paper we reduce it to a constrained minmax cost control problem. A differential game theory is used to treat this constrained minmax cost control problem. The differential game theory leads to a sufficient condition for the global solvability of the model reference control problem with desired disturbance attenuation.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.5
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• pp.261-268
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• 2020

Genetic algorithms find the optimal solution by mimicking the evolution of natural organisms. In this study, the genetic algorithm was used to enable Pac-Man's reinforcement learning, and a simulator to observe the evolutionary process was implemented. The purpose of this paper is to reinforce the learning of the Pacman AI of the simulator, and utilize genetic algorithm and artificial neural network as the method. In particular, by building a low-power artificial neural network and applying it to a genetic algorithm, it was intended to increase the possibility of implementation in a low-power embedded system.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.143-154
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• 2015

This study aims to evaluate smartphone gaming controllers. Diffusion of smartphone makes its users to play smartphone games in ease and comfort and its built-in sensors deliver new gaming experience to the users. Based on the concept how the controller system is important, the current research also implies the importance of customizing service which gives users a selection to deploy a controller. To explore the interaction effect of controllers and customizing on interactivity, flow, usability, attitude, and intention, the research constructs 3(gyroscope, wheel, and button controllers) by 2(default and customizing setting) experimental design and forty college students played Gameloft's Asphalt 8: Airborne in a within subject design. The results showed that interaction effect and customizing main effect were not found, but controller main effect was statistically significant. Button controller is superior to those other two in more detail. It implies that it is still not useful to play new types of gaming controller, and a customizing service. It suggests that smartphone games should more focus on improving optimal user experience with built-in sensor controllers.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.6
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• pp.802-811
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• 2012

This study proposes an OMS/MP preparation methodology using a simulation method instead of a survey method. We applied our methodology to the next generation detection radar, providing reasonable peace- and war-time OMS/MP values. Based on these results, we propose the process to calculate RAM objective values. The previous survey method required to supplement its method since the method used data from a similar weapon system. In addition, the previous method didn't provide enough reliability for the future weapon system. Instead of using the previous survey method, we propose to use war game simulation, which provides a better OMS/MP values. Based on these results, we propose the logical consecutive process that prepares combat and simulation scenarios, peace- and war-time OMS/MP values and RAM objective values.

• 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.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.165-180
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• 2019

As game industry prospers, the negative side of games becomes highlighted as well as its contributions to economy growth. In spite of strong arguments for the necessity to regulations as a means to decrease addiction or overindulgence, research has produced future suggestions rather than quantifiable evidence. In this paper, we propose adopting a simulation approach in addition to quantitative approaches to better understand optimal regulatory levels since a simulation approach can visualize unexpected side effects of regulations. In this study, we suggest the application of an agent-based model (ABM) as a smart service to measure the effects of regulatory policies. We review cases applying ABM in various domains and consider the possibility of using an ABM to understand the effectiveness of web board-game regulations. We find that the ABM approach would be useful in several areas, such as the analysis of regulatory effects that reflect a variety of characteristics, the measurement of micro-regulatory effects, and the simulation of regulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4188-4206
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• 2016

Power control is widely used to reduce co-channel interference in wireless networks and guarantee the signal-to-interference plus noise ratio (SINR) of ongoing connections. This technique is also effective for wireless body area networks (WBANs). Although achieving satisfactory SINR is important for WBAN users, they may not be willing to achieve it at arbitrarily high power levels since power is a scarce resource in WBANs. Besides, for WBANs with different purposes, the QoS requirements and concern about the power consumption may be different. This motivates us to formulate the power control problem using the concepts from microeconomics and game theory. In this paper, the QoS objective is viewed as a utility function, which represents the degree of user satisfaction, while the power consumption is viewed as a cost function. The power control problem consequently becomes a non-cooperative multiplayer game, in which each player tries to maximize its net utility, i.e., the utility minus the cost. Within this framework, we investigate the Nash equilibrium existence and uniqueness in the game and derive the best response solution to reach the Nash equilibrium. To obtain the optimal transmission power in a distributed way, we further propose a utility-based and QoS-aware power control algorithm (UQoS-PCA). Tunable cost coefficient in UQoS-PCA enables this scheme to be flexible to satisfy diverse service requirements. Simulation results show the convergence and effectiveness of the proposed scheme as well as improvements over existing algorithm.

• 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.