• Journal of the Korean Society for Precision Engineering
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• v.20 no.10
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• pp.98-104
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• 2003

Model structure of solenoid valve in the automatic transmission is determined as 5th order system by the signal error test. For determining parameter of the solenoid valve, parameters in time discrete model are searched by the least square method. By bilinear transform, we have found the model of solenoid valve in s domain. Afterward, experimental output data is compared with simulated output data by MATLAB having identified parameter. As the result, experimental data is agreed with simulated data very well.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.553-558
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• 2002

Physical sensor model in pushbroom satellite images can be made from sensor modeling by rotation parameters and attitude parameters on the satellite track. These parameters are determined by the information obtained from GPS, INS, or star tracker. Provided from satellite image, an auxiliary data error is connected directly with an error of rotation parameters and attitude parameters. This paper analyzed how obtaining satellite images influenced errors of rotation parameters and attitude parameters. furthermore, for detailed analysis, this paper generated simulated satellite image, which was changed variously by rotation parameters and attitude parameters of satellite sensor model. Simulated satellite image is generated by using high-resolution digital aerial image and DEM (Digital Elevation Model) data. Moreover, this paper determined correlation of rotation parameter and attitude parameters through error analysis of simulated satellite image that was generated by various rotation parameters and attitude parameters.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

• Journal of the Korean Society of Combustion
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• v.5 no.1
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• pp.55-66
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• 2000

A general purpose program for the analysis of flows in a gas turbine combustor is developed. The program uses non-staggered grids based on finite volume method and the cartesian velocities as primitive variables. A flow inside the C-type diffuser is simulated to check the boundary fitted coordinate. The velocity profiles at cross section agree well with experimental results. A turbulent diffusion flame behind a bluff body is simulated for the combustion simulation. Simulated results show good agreement with experimental data. Finally, a turbulent flow with swirl in a gas turbine combustor was simulated. The results show two recirculating region and simulated velocity fields agree well with experimental data. The distance between two recirculating regions becomes shorter as swirl angle increases. Swirl angle changes angular momentum and streamlines in flow fields.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.31-37
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• 2017

There are lots of combined battlefield elements which complete the war. It looks problematic when collecting and analyzing these elements and then predicting the situation of war. Commander's experience and military power assessment have widely been used to come up with these problems, then simulated combat training program recently supplements the war-game models through recording real-time simulated combat data. Nevertheless, there are challenges to assess winning factors of combat. In this paper, we characterize the combat element (ce) by clustering simulated combat data, and then suggest multi-layered artificial neural network (ANN) model, which can comprehend non-linear, cross-connected effects among ces to assess mission completion degree (MCD). Through our ANN model, we have the chance of analyzing and predicting winning factors. Experimental results show that our ANN model can explain MCDs through networking ces which overperform multiple linear regression model. Moreover, sensitivity analysis of ces will be the basis of predicting combat situation.

• Journal of Environmental Science International
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• v.16 no.10
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• pp.1127-1137
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• 2007

We focused on effects on data assimilation of simulated wind fields by using upper-air observations (wind profiler and sonde data). Local Analysis Prediction System (LAPS), a type of data assimilation system, was used for wind field modeling. Five cases of simulation experiments for sensitivity analysis were performed: which are EXP0) non data assimilation, EXP1) surface data, EXP2) surface data and sonde data, EXP3) surface data and wind profiler data, EXP4) surface data, sonde data and wind profiler data. These were compared with observation data. The result showed that the effects of data assimilation with wind profiler data were found to be greater than sonde data. The delicate wind fields in complex coastal area were simulated well in EXP3. EXP3 and EXP4 using wind profiler data with vertically high resolution represented well sophisticated differences of wind speed compared with EXP1 and EXP2, this is because the effects of wind profiler data assimilation were sensitively adjusted to first guess field than those of sonde observations.

• Atmosphere
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• v.31 no.4
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• pp.433-443
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• 2021

The wind speed and wind direction in Yeongdong are one of the crucial meteorological factors for forecasting snowfall in this area. To improve the snowfall forecast in Yeongdong region, Yeongdong Extreme Snowfall-Windstorm Experiment, YES-WEX was designed. We examined the wind field variation simulated with Local Data Assimilation and Prediction System (LDAPS) using observed wind field during YES-WEX period. The simulated wind speed was overestimated over the East Sea and especially 2 to 4 times in the coastal line. The vertical wind in Yeongdong region, which is a crucial factor in the snowfall forecast, was not well simulated at the low level (850 hPa~1000 hPa) until 12 hours before the forecast. The snowfall distribution was also not accurately simulated. Three hours after the snowfall on the East Sea coast was observed, the snowfall was simulated. To improve the forecast accuracy of snowfall in Yeongdong region, it is important to understand the weather conditions using the observed and simulated data. In the future, data in the northern part of the East Sea and the mountain slope of Taebaek observed from the meteorological aircraft, ship, and drone would help in understanding the snowfall phenomenon and improving forecasts.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.78-82
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• 2003

In this paper, simulated annealing technique was used to estimate the rock joint characteristics, RMR(rock mass rating) values, to overcome the defects of ordinary kriging. Ordinary kriging reduced the variance of data, so lost the characteristics of distribution. Simulated annealing technique could reflect the distribution feature and the spatial correlation of the original data. Through the comparisons between three times simulations, the uncertainty of the simulation could be quantified, and sufficient results were obtained.

• Journal of Engineering Education Research
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• v.15 no.4
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• pp.48-52
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• 2012

The purpose of this paper is to design and implement the user motion pattern control system for the simulated vehicle. After analyzing the user motion patterns in the system, the patterns are used to control the moving direction of the simulated vehicle such as forward, backward, turn right, turn left etc. The patterns in the system around are sent to the simulated vehicle in real time. In order to execute the suggested user motion pattern control system, the Kinect is used for executing the system. The Kinect recognizes the specified user motion patterns and it transmits the data to the user motion pattern control system. There are nine kinds of the user motion patterns in the system for controlling the simulated vehicle. In addition to this, some sensors are used to detect the condition of the simulated vehicle. GPS is also used to estimate the current location of the simulated vehicle and to obtain the driving information.

• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.1-7
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• 2022

A simulated radar terrain scan data generation method is employed for terrain following. This method scans the discrete terrain by sequentially radiating beams from the radar to the desired scan area with the same azimuth but varying elevation angles. The terrain data collected from the beam is integrated to generate the simulated radar terrain scan data, which comprises radar-detected points. However, these points can be located far from the beam centerline when the radar is far from them due to beam divergence. This paper proposes a geometry-based terrain scan data generation method for analysing simulated radar terrain scan data. The method involves detecting geometric points along the beam centerline, which forms the geometry-based terrain scan data. The analysis of the simulated radar terrain scan data utilising this method confirms that the beam width effects are accounted for in the results.