• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1765-1769
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• 2004

The number of parameters and the number of samples are the key point of trans-log cost function which studied recently. Most of models show that the number of parameters is more than the number of samples. Therefore, these studies gave unreliability of the estimation results. First, we surveyed theoretical cases and researches for the formulation of cost function of railroad industry. Second, we will suggest trans-log cost function by analyzing cost data of KNR. And, the cumulative data will be needed for the confidence of estimation results.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.418-423
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• 2005

In designing underground structure such as tunnels, estimating geotechnical characteristics of the ground is one of the most important and difficult tasks. In this paper, a methodology that can identify geotechnical parameters using only field-measured relative convergence displacements is presented. By using only relative convergence measurement data, inevitable errors in absolute convergence estimation can be avoided and in turn the parameter estimation process can be simplified. The methodology utilizes sensitivity relationship between static displacement measurements and geotechnical parameters. The feasibility and applicability of the proposed methodology is verified via a 3-d numerical example of a tunnel structure.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.542-543
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• 2014

In this paper, an estimation scheme based on an augmented sigma-point Kalman filter to estimate the state of charge (SOC) of the battery is presented, where the battery parameters of the series resistance ($R_o$), diffusion capacitance ($C_1$) and resistance ($R_1$) are also estimated through the recursive least squares (RLS) for better accuracy of the SOC. The effectiveness of the proposed method is verified by simulation results.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.6
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• pp.57-63
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• 1998

An adaptive control in the robotic GMA welding is employed to monitor information about weld characteristics and process parameters as well as to modify those parameters to hold weld quality within acceptable limits. Typical characteristics are the bead geometry, composition, microstructure, appearance, and process parameters which govern the quality of the final weld. The main objectives of this thesis are to realize the mapping characteristics of bead width through learning. After learning, the neural estimation can estimate the bead width desired form the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead width with reasonable accuracy and guarantee the uniform weld quality.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.983-984
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• 2011

An effective estimation method of equivalent circuit parameters of three-phase induction motor by using FEM is presented in this paper. Arbitrary three torque-speed points at asynchronous speed on the torque-speed curve are required by using time-stepping FEM, then the equivalent circuit parameters of IM can be calculated rapidly with presented method. After obtaining the equivalent circuit parameters, the general analysis method based on equivalent circuit can be used to get entire torque-speed curve very quickly. Although the purely numerical method such as FEM also can estimate torque-speed curve directly and accurately, however, usually this process is time consuming.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.138-143
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• 2000

In order to investigate the relationship between fabric sound parameters and subjective sensation, each sound from 60 fabrics was recorded and analyzed by Fast Fourier transform. Level pressure of total sound (LPT), three coefficients (ARC, ARF, ARE) of auto regressive models, loudness (Z), and sharpness (Z) by Zwickers model were estimated as sound parameters. For subjective evaluation, seven sensation (softness, loudness, sharpness, clearness, roughness, highness, and pleasantness) was rated by both semantic differential scale (SDS) and free modulus magnitude estimation (FMME). As the results, the ARC values were positively proportional to both LPT and loudness (Z) values. In both of SDS and FMME, softness, clearness, and pleasantness were negatively correlated with loudness, sharpness, roughness, and highness. In regression models, softness and clearness by FMME were negatively affected by LPT뭉 ARC, while loudness, sharpness, roughness, and highness were positively expected. Regression models for pleasantness showed low values for R2.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1264-1267
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• 2002

In order to achieve an advanced human-computer interface system, it is necessary to analyze and synthesize facial motions just as they are in an interactive way, and to protect them from unwanted use and/or illegal use for their privacy, various uses in applications and the costs of obtaining motion parameters. To estimate facial motion, a method of using skin color distribution, luminance, and geometrical information of a face is employed. Digital watermarks are embedded into facial motion parameters and then these parameters are scrambled so that it cannot be understood. Experimental results show high accuracy and efficiency of the proposed estimation method and the usefulness of the proposed watermarking method.

• Journal of KSNVE
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• v.2 no.3
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• pp.193-202
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• 1992

The unbalance response analysis is one of the essential area in the forced vibration analysis of rotor bearing systems because of it usefulness in balancing and diagnosis as well as identification of parameters involved in rotor bearing systems. However some unbalance responses are not measurable due to the fact that rotor bearing systems are often encapsulated by fixtures or safety protectors. In the present paper, an efficent estimation scheme for unmeasured unbalance responses in rotor bearing systems is developed. The fundamental fearture of the proposed method is characterized by the linear formulae to estimate the unbalance responses from the measured unbalance responses and the finite element auxilliary model equation which is constructed to be identical to the prototype excluding the uncertain parameters such as bearing coefficients. The identification formulae for bearing parameters are also derived by using the unbalance response and the finite elements auxiliary model. Simulation is provided to verify the effectiveness of the proposed method.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.273-282
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• 2003

The problem of estimating the parameters of k-population Weibull distributions is discussed under the prior of ordered scale parameters. Parameters are estimated by the Gibbs sampling method. Since the conditional posterior distribution of the shape parameter in the Gibbs sampler is not log-concave, the shape parameter is generated by the adaptive rejection sampling. Finally, we applied this estimation methodology to the data discussed in Nelson (1970).

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.241-250
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• 2016

In this paper, we consider statistical inferences on the estimation of the parameters of a Weibull distribution when data are randomly censored. Maximum likelihood estimators (MLEs) and approximate MLEs are derived to estimate the parameters. We consider two cases for the censoring model: the assumption that the censoring distribution does not involve any parameters of interest and a censoring distribution that follows a Weibull distribution. A simulation study is conducted to compare the performances of the estimators. The result shows that the MLEs and the approximate MLEs are similar in terms of biases and mean square errors; in addition, the assumption of the censoring model has a strong influence on the estimation of scale parameter.