• 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.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.106-108
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• 1997

Many new office buildings are being built as intelligent buildings equipped with building automation(HA) systems, office automation(OA) systems, and telecommunication(TC) systems in order to provide pleasant building environment and the ease of maintenance and facility management. Building control systems which are employed in intelligent buildings require varieties of advanced control systems and network systems for efficient integrated management. Design and installation of these types of advanced building control systems take a lot of efforts and also they are costly. In order to design these systems, it is necessary for the designers to have the integrated simulator including proper network system simulation. In this paper, the integrated simulator that consist of HVAC system, lighting system, elevator system, parking system based on the network system is presented. For the development of integrated simulator, AHENA which is the general-purpose software tool for a simulation with reinforced GUI is used.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.107-111
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• 1998

This paper presents a now approach to the design of intelligent contorl system for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. Moreover, We develop a Windows 95 version dynamic simulator which can simulate a track vehicle model in 3D graphics space. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The dynamic simulator for track vehicle is developed by Microsoft Visual C++. Graphic libraries, OpenGL, by Silicon Graphics, Inc. were utilized for 3D Graphics. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1384-1386
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• 2005

This paper focuses on development of load test simulator of a steam turbine-generator in a nuclear power plant. When load is taken off from electrical power network, it is very difficult to effectively control the steam flow to turbine of the nuclear turbine-generator, because of disturbances, such as electrical load and network unbalance on electrical network. Up to the present time, the conventional control system has been used for the load control on nuclear steam generator, owing to the easy control algorithms and the advantage which have been proven on the nuclear power plant. However, since there are problems with stability control during low power and start-up, only a highly experienced operator can operate during those procedures. Also, a great deal of time and an expensive simulator is needed for the training of an operator. The KEPRI is developed simulator for 600MW nuclear power plant to take a test of generator load rejection, throttle valve, and turbine load control. Total load test is implemented before start up.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.969-975
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• 2002

Visual effects are important cues for providing occupants with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant's posture, therefore, the total human body motion must be considered in a graphic simulator. A real-time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and lane-change for acquiring the accelerations of chassis of the vehicle model. A hybrid III 50%ile adult male dummy model was selected and modeled in an ellipsoid model. Multibody system analysis software, MADYMO, was used in the motion analysis of an occupant model in the seated position under the acceleration field of the vehicle model. Acceleration data of the head were collected as inputs to the viewpoint movement. Based on these data, a back-propagation neural network was composed to perform the real-time analysis of occupant motions under specified driving conditions and validated output of the composed neural network with MADYMO result in arbitrary driving scenario.

• Journal of IKEEE
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• v.15 no.1
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• pp.86-95
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• 2011

In this paper, we propose a testbed system for the crisis management system of the power grid(CMS-PG) using satellite communication network. For the verification of CMS-PG, the proposed system composed of the simulator of satellite communication network and the simulator of phase measurement unit. Proposed satellite communication simulator can evaluate the delay and the robustness of the communication according to the rainfall and the humidity of local site. And the proposed simulator can calculates the voltage stability by hardware implementation using FPGA. Using the proposed testbed system, we adapted its function of crisis management system for the conventional power grid.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.109-118
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• 1999

A graphic software is one of the most important components of the vehicle simulator. To increase a visual reality of the simulator, the graphic software should require several technologies such as three-dimensional graphics, graphic modeling of the vehicle and the environment, drivers biomechanical models, and real-time data processing. This study presents a real time graphic driving simulator of a construction vehicle. The graphic simulator contains the three models of the construction vehicle, the human, and the environment, and employes a neural network approach to decrease an on-line dynamic computation. An excavator model is represented using an object-oriented paradigm and contains the detailed information about a real-size vehicle. The human model is introduced for objective visual evaluations of the developed excavator model. Since the environment model plays an important role in a real-time simulator, a block-based approach is implemented and a text format is utilized for easier construction of environment. The simulation results are illustrated in order to demonstrate the applicability of developed models and the neural network approach.

• Proceedings of the IEEK Conference
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• 2000.06a
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• pp.248-251
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• 2000

The ATM-PON is regarded as an effective access network because the system transmits the various user's information through the passive optical splitter in a single platform. The ranging technology is to place all ONUs at the same distance virtually in order to form ATM-PON based on the Time Division Multiplexing (TDM). In This paper, We show the steps about ranging protocol based on ITU-T G.983.1 and ranging procedure modeling. Also, We implement the simulator that considers various environments to verify the time specifications of G.983.1. By using the simulator, We find out the wasted bandwidth which influences active ONUs during the ranging procedure.

• Proceedings of the KSR Conference
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• 2000.11a
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• pp.720-726
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• 2000

The advance of traction motor control technology and the complexity of the traction power supply system makes the simulation essential in determining the dimension of the traction power supply system. The conventional method, use of the simplified and/or empirical equations, becomes inadequate in optimization of the design. The simulator presented in this paper is a numerical time based simulator running on a PC. The input to the simulator includes the track data, the train characteristic, network data and operating data. Basically the simulator conducts train running simulation and loadflow study repeatedly. The principle algorithms and its output is discussed in the paper.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.157-164
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• 2022

The proposed privacy preserving scheme has identified the drawbacks of existing schemes in Vehicular Networks. This prototype enhances the number of nodes by decreasing the cluster size. This algorithm is integrated with the whale optimization algorithm and Block Chain Technology. A set of results are done through the NS-2 simulator in the direction to check the effectiveness of proposed algorithm. The proposed method shows better results than with the existing techniques in terms of Delay, Drop, Delivery ratio, Overhead, throughout under the denial of attack.