• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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• pp.15-22
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• 1999

In this study, a machining error estimation system far vertical lathes with structural deformation and geometric errors, is realized based on the virtual manufacturing technologies. The positional and directional errors of cutting tool are determined by considering the geometric errors and dimensions of machine components and by introducing the equilibrium condition between the cutting force and structural deformation. Especially, the machining errors of vertical lathes are estimated by using the prescribed cutting test(JIS B 6331). The system can be implemented to evaluate the machining accuracies of vertical lathes at the design process and to design the high precision vertical lathes.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.10a
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• pp.146-151
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• 1998

In this study, a machining error estimation system for vertical lathes with structural deformation and geometric errors, is realized based on the virtual manufacturing technologies. The positional and directional errors of cutting tool are determined by considering the geometric errors and dimensions of machine components and by introducing the equilibrium condition between the cutting force and structural deformation. specially, the machining errors of vertical lathes are estimated by using the prescribed cutting test(JIS B 6331). The system can be implemented to evaluate the machining accuracies of vertical lathes at the design process and to design the high precision vertical lathes.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2E
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• pp.71-80
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• 2002

This paper suggests the Cardioid beamforming algorithm of the doublet sensors employing DIFAR (directional frequency analysis and recording) sensor signals in the frequency domain. The algorithm enables target bearing estimation using the signals from directional sensors. The algorithm verifies its applicability by successfully estimating bearings of a target projecting ten narrow-band signals in shallow water. The estimated bearings agree very well with those from GPS (global positioning system) data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1°∼ 6.7°and 13.3∼43.6°, respectively. Estimation errors are caused by SNR (signal to noise ratio) degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.3
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• pp.103-109
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• 2003

The validity of measured data is fundamental factor for the power system automation Measured values could have errors that are caused by the communication errors and malfunctioning measuring devices. The accuracy and reliability of measured values at a substation is an important condition for robust and fault tolerant automata. Errors can be reduced by state estimation, however, global reliability of state estimation goes down in case of the existence of some bad data In this paper, a least square state estimation and bad sensor detection algorithm based on chi-square theory, ale proposed and it is applied to a domestic 154kV distribution substations. A simulator together with user friendly graphic users interface is developed using C language and Visual Basic. TCP/IP is equipped for future connection with other operation systems.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.54-57
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• 2002

In this paper model reference adaptive control (MRAC) of linear time-varying(LTV) systems is considered. MRAC for a linear time invariant(LTI) system does not assure the boundedness of the output and parameter estimation errors in the presence of time variations of the parameters. However, changing the adaptive laws such as use of $\sigma$-modification can result in the boundedness of the output and parameter estimation errors[5]. Together with the $\sigma$-modification in the adaptive law, we also modify the control law by adding an additional term to the standard control law. The additional term leads to smaller bounds of the output and parameter estimation errors when compared to the case where only the standard control law is applied.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.1-10
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• 2004

In the Korean Economically Active Population Survey(EAPS), the sample sizes for small areas are typically too small to provide reliable estimators because the EAPS has been designed to produce unemployment statistics for large areas such as Metropolitan Cities and Province. In this study, we consider the synthetic and composite estimators for the unemployment rate of small areas, and apply them to real data on Choongbook province which is from the Korean EAPS of December 2000. The mean square errors of these estimators were estimated by the Jackknife method, and the efficiencies of small area estimators were evaluated in terms of the relative standard errors and the relative root mean square errors. As a result, the composite estimator is much more efficient than other estimators and it turns out that the composite estimator can produce the reliable estimates of the unemployment rate of small areas under the current EAPS system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.133-139
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• 2011

Estimation of biomass carbon stock is an important research for estimation of public benefit of forest. Previous studies about biomass carbon stock estimation have limitations, which come from the used deterministic models. The most serious problem of deterministic models is that deterministic models do not provide any explanation about the relevant effects of errors. In this study, the effects of location errors were analyzed in order to estimation of biomass carbon stock of Danyang area using Monte Carlo simulation method. More specifically, the k-Nearest Neighbor(kNN) algorithm was used for basic estimation. In this procedure, random and systematic errors were added on the location of Sample plot, and effects on estimation error were analyzed by checking the changes of RMSE. As a result of random error simulation, mean RMSE of estimation was increased from 24.8 tonC/ha to 26 tonC/ha when 0.5~1 pixel location errors were added. However, mean RMSE was converged after the location errors were added 0.8 pixel, because of characteristic of study site. In case of the systematic error simulation, any significant trends of RMSE were not detected in the test data.

• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.45-50
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• 2011

Unknown morpheme errors in Korean morphological analysis are divided into two types: The one is the errors that a morphological analyzer entirely fails to return any morpheme sequences, and the other is the errors that a morphological analyzer returns incorrect combinations of known morphemes. Most previous unknown morpheme estimation techniques have been focused on only the former errors. This paper proposes a unknown morpheme estimation method which can handle both of the unknown morpheme errors. The proposed method detects Eojeols (Korean spacing units) that may include unknown morpheme errors using SVM (Support Vector Machine). Then, using CRFs (Conditional Random Fields), it segments morphemes from the detected Eojeols and annotates the segmented morphemes with new POS tags. In the experiments, the proposed method outperformed the conventional method based on the longest matching of functional words. Based on the experimental results, we knew that the second type errors should be dealt with in order to increase the performance of Korean morphological analysis.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.1
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• pp.65-73
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• 2007

This paper presents an on-line correction method of current measurement errors for a pure-integration-based flux estimation down to 1-Hz stator frequency. An observer-based approach is taken as one possible solution of eliminating the dc offset and the negative sequence component of unbalanced gains in the synchronous coordinate. At the same time, the positive sequence component estimation is performed by creating an error signal between a motor model reference and an estimated q-axis rotor flux established by a permanent magnet (PM) in the synchronous coordinate. The compensator utilizes a PI controller that controls the error signal to zero. The proposed technique further contains a residual error compensator to completely eliminate miscellaneous disturbances in the estimated flux. The developed algorithm has been implemented on a 1.1-kW permanent magnet synchronous motor (PMSM) drive to confirm the effectiveness of the proposed scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.722-727
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• 2010

This paper presents Dynamic-Simulation to estimate the inductance of a permanent magnet type transverse flux rotating motor by applying the real-time parameter estimation theory. As transverse flux rotating motor has the complex structure, it can be happen to some errors between real value and designed one with respect to the inductance. To reduce this kinds of errors, the real-time parameter estimation theory was applied to dynamic-simulation. And then, By comparing the estimated inductance and designed one, it is realized that the real-time parameter estimation theory can be applied in the permanent magnet type transverse flux rotating motor.