• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.1-11
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• 2006

This paper presents a digital auto-focusing method using a priori estimated point-spread-functions (PSF) database. The proposed algorithm efficiently removes out-of-focus blur in a degraded input image by selecting the optimal PSF from the database. The database consists of optical characteristics of image formation system. The PSF selection Process is performed based on a novel focusing measure. The proposed method includes a spatially adaptive filter for removing both noise and ringing artifacts. Experimental results show that the proposed method efficiently removes out-of-focus blur using significantly reduced computational load compared with the existing method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1553-1556
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• 1997

In the paper, we porpose a new mehtod of extending PLS(Partial Least Squares) regressiion method to nonlinear framework and apply it to the estimation of product compositions in high-purity distillation column. There have veen similar efforets to overcome drawbacks of PLS by using nonlinear-mapping ability of meural networks, however, they failed to show great improvement over PLS since they focused only in capturing nonlinear functional relationship between input data, not on nonlinear correlation inthe data set. By incorporating the structure of Robust Auto Associative Networks(RAAN) into that of previous nonlinear PLS, we can handle nonlinear correlation as well as nonlinear functional relationship. The application result shows that the proposed method performs better than previous ones even for nonlinearities caused by changing operating conditions, limited observations, and existence of meas-unrement noises.

• Computational Structural Engineering
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• v.3 no.4
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• pp.143-148
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• 1990

The modal parameter estimations of linear multi-degree-of-freedom structural dynamic systems are carried out in time domain. For this purpose, the equation of motion is transformed into the auto regressive and moving average model with auxiliary stochastic input(ARMAX) model. The parameters of the ARMAX model are estimated by using the sequential prediction error method. Then the modal parameters of the system are obtained thereafter. Experimental results are given for a 3-story budding model subject to ground exitations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.51-56
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• 1998

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy logic controller(FLC). The quantitative relation between input and output variables of FLC is obtained by using a qualsi-linear fuzzy model, and an approximate transfer function of FLC is dervied from the comparison of it with the conventional PID controller. Then we analyze in detail the effects of scaling factor using this approximate transfer function and root locus method. Also we suggest an on-line tuning method for scaling factors which employs an sample performance function and a variable reference for tuning index.

• Journal of Welding and Joining
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• v.20 no.4
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• pp.538-543
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• 2002

M/S TB(Mash Seam Tailored Blank) is a production method for blanks by welding together blanks of different material, thickness and coating, and is an attractive method for manufacturing car body because it makes parts lighter and can save the cost and time to manufacture. However, there have not been quantified criteria to evaluate the quality of TB weld. This study introduced FHR (failure height ratio) in order to assess formability or/and weldability of the M/S welds and the applicability of FHR was confirmed by actual auto body forming and FLD tests. Furthermore, a new parameter, HN(heat number) based on the heat input of "$Q=I^2Rt$" was proposed and assessed. It was found that the concept of HN could be utilized to evaluate the soundness of M/S welds without any destructive tests.ive tests.

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.71-75
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• 2018

Image enhancement is a necessary end essential step after taking a picture with a digital camera. Many different photo software packages attempt to automate this process with various auto enhancement techniques. This paper provides and implements a system that can learn a user's preferences and apply the preferences into the process of image enhancement. Five major components are applied to the implemented system, which are computing a distance metric, finding a training set, finding an optimal parameter set, training and finally enhancing the input image. To estimate the validity of the method, we carried out user studies, and the fact that the implemented system was preferred over the method without learning user preferences.

• Nuclear Engineering and Technology
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• v.43 no.4
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• pp.343-354
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• 2011

It is critically important to identify unexpected loose parts in a nuclear reactor pressure vessel, since they may collide with and cause damage to internal structures. Mass estimation can provide key information regarding the kind as well as the location of loose parts. This study proposes a mass estimation method based on an artificial neural network (ANN), which can overcome several unresolved issues involved in other conventional methods. In the ANN model, input parameters are the discrete cosine transform (DCT) coefficients of the auto-power spectrum density (APSD) of the measured impact acceleration signal. The performance of the proposed method is then evaluated through application to a large-sized plate and a 1/8-scaled mockup of a reactor pressure vessel. The results are compared with those obtained using a conventional method, the frequency ratio (FR) method. It is shown that the proposed method is capable of estimating the impact mass with 30% lower relative error than the FR method, thus improving the estimation performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.890-896
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• 2022

In this paper, gimbal camera control through smart gloves was implemented to increase convenience and accessibility to the control of drones used in various fields. Smart gloves identify human gestures and transmit signals through Bluetooth. The received signal is converted into a signal suitable for the drone through a GCS (Gound Control Station). Signals from smart gloves are expressed in a quaternion method to prevent gimbal locks, but for gimbal cameras, conversion is required to use Roll, Pitch, and Yaw methods. The data conversion mission is performed in the GCS. The GCS transmits an input signal to the control board of the drone through Wi-Fi. The control board generates and outputs the transmitted signal in a PWM manner. The output signal is input to the gimbal camera through the SBUS method and controlled. The input signal of the smart glove averaged 0.093 s and up to 0.099 s to output to the gimbal camera, showing that there was no problem in real-time use.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.73-81
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• 2006

This paper proposes the improved orthogonal projection method as a new technique advancing the performance of the acoustic echo canceller. Comparing with the widely used NLMS adaptive algorithm which is simple and stable, it shows that this method has the improvement of the convergence speed for signals with the large auto-correlation, and has small computational quantities. In order to testify performances of the orthogonal projection method whom this paper proposes, we have coded a simulation program md executed computer simulations. We observed convergence curves by using two adaptive algorithm for noises and speeches. From simulation results for two input signals, the proposed method shows the high ERLE and the fast convergence and the stable operation in case of using speeches as well as noises.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.703-711
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• 2005

This paper proposes the improved orthogonal projection method as a new technique advancing the performance of the echo cancellation for speeches in the acoustic echo canceller. Comparing with the used NLMS adaptive algorithm, it shows that this method improves the performance of the echo cancellation for signals with the large auto-correlation. In order to testify performances of the orthogonal projection method whom this paper proposes, we have coded a simulation program and executed computer simulations. We observed convergence curves by using two adaptive algorithm for noises and speeches. From simulation results for two input signals, the proposed method shows the high ERLE and the fast convergence and the stable operation in case of using speeches as well as noises.