• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7941-7948
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• 2015

Rolling noises during train operation are caused by vibration excited from irregularities of surface roughness between wheel and rail. Therefore, a proper measurement and analysis techniques of acoustic roughness between wheel and rail surface are required for transmission, prediction, and analysis of the train rolling noise. However, since current measuring devices and methods use trolley-based manual handling devices, the measurements induce unstable measuring speed and vibrational interface that increases errors and disturbances. In this paper, a new automatic rail surface exploring platform with a speed controller has been developed for improving measurement accuracy and reducing inconsistency of measurements. In addition, we propose a data integration method of the rail surface roughness with multiple homogeneous displacement sensors and verified the accuracy of the integrated data through standard test-bed railway track investigation.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.05a
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• pp.74-77
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• 2000

The main objective of this paper is to design and test a new type of polymer ZnO surge arrester for AC power system of railroad vehicles. Metal oxide surge arrester for most electric power system applications, electric train and must not have explosive breakage of the housing to minimize damage to other equipment when subjected to internal high short circuit current. When breakdown of ZnO elements in a surge arrester occurs due to flashover, fault short current flows through the arrester and internal pressure of the arrester rises. The pressure rise can usually be limited by fitting a pressure relief diaphragm and transferring the arc from the inside to the outside of the housing. However, there is possibility of porcelain fragmentation caused by the thermal shock. pressure rise, etc. Non-fragmenting of the housing is the most desired way to prevent damage to other equipment. The pressure change which is occurred by flashover become discharge energy. This discharge energy raises to damage arrester housing and arrester housing is dispersed as small fragment. Therefore, the pressure relief design is requested to obstruct housing dispersion. The main research works are focused on the structure design by finite element method, pressure relief of module, and studies of performance of surge arrester for electric railway vehicle.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.9
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• pp.701-709
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• 2011

In semiconductor wafer fabrication, etching is one of the most critical processes, by which a material layer is selectively removed. Because of difficulty to correct a mistake caused by over etching, it is critical that etch should be performed correctly. This paper proposes a new approach for etch endpoint detection of small open area wafers. The traditional endpoint detection technique uses a few manually selected wavelengths, which are adequate for large open areas. As the integrated circuit devices continue to shrink in geometry and increase in device density, detecting the endpoint for small open areas presents a serious challenge to process engineers. In this work, a high-resolution optical emission spectroscopy (OES) sensor is used to provide the necessary sensitivity for detecting subtle endpoint signal. Partial Least Squares (PLS) method is used to analyze the OES data which reduces dimension of the data and increases gap between classes. Support Vector Machine (SVM) is employed to detect endpoint using the data after PLS. SVM classifies normal etching state and after endpoint state. Two data sets from OES are used in training PLS and SVM. The other data sets are used to test the performance of the model. The results show that the trained PLS and SVM hybrid algorithm model detects endpoint accurately.

• Journal of KIISE:Software and Applications
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• v.34 no.11
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• pp.953-960
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• 2007

To correctly detect muras, visual defects in TFT-LCD panels, image distortion occurring on the profess of capturing panels should be corrected. In general vision systems, there are several known methods to restore the observed image. However, the vignetting effect particularly shown only in panel images cannot be easily restored through traditional methods because it is combined with background non-uniformity due to the unique characteristic of panel. To increase the reliability of image restoration, the vignetting effect should be properly corrected after being separated from image background. Therefore, in this paper we present a new method to analyze and correct the vignetting effect of panel images using principal component analysis. Experimental results for a total of 175 test images showed that the average contrast error of the muras in the distorted images was reduced from 37% to 11% and the mura misidentification rate was decreased from 14.8% to 2.2% by image restoration.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.303-309
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• 2010

We proposes a new approach for testing the self visual-acuity by using the KS standard optotype. The proposed system provides their hand-gesture recognition method for the convenient response of subjects in the visual acuity measurement. Also, this system can measure a visual-acuity that excludes the examiner's subjective judgement or the subject's memorized guess, because of presenting a random optotype automatically by computer without a examiner. Especially, Our system guarantees the reliability by using the KS standard optotype and its presentation(KS P ISO 8596), which is defined by the Korea Standards Association in 2006. And the database management function of our system can provide the visual-acuity data to the EMR client easily. As a result, Our system shows the 98% consistency in the limit of the ${\pm}1$ visual-acuity level error by comparing the visual-acuity chart test.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.40-44
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• 2002

Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.353-365
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• 2008

The sample size in a clinical trial is determined by the hypothesis, the variance of observations, the effect size, the power and the significance level. Dropouts in clinical trials are inevitable, so we need to consider dropouts on the determination of sample size. It is common that some proportion corresponding to the expected dropout rate would be added to the sample size calculated from a mathematical equation. This paper proposes new equations for calculating sample size dealing with dropouts. Since we observe data longitudinally in most clinical trials, we can use a last observation to impute for missing one in the intention to treat (ITT) trials, and this technique is called last observation carried forward(LOCF). But LOCF might make deviations on the assumed variance and effect size, so that we could not guarantee the power of test with the sample size obtained from the existing equation. This study suggests the formulas for sample size involving information about dropouts and shows the properties of the proposed method in testing equality of means.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.10
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• pp.974-984
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• 2012

This research introduces a new method to attenuate flip-over vibration generation in the flat blade windshield wiper by adjusting the contact pressure between the windshield glass and the blade. The knocking force in the flip-over action of the blade is decreased by inducing gradual tilting-over along the rubber strip of the blade. This gradual tilting-over is induced by introducing a non-uniform contact pressure distribution between the blade and windshield glass. The contact pressure distribution is adjusted by controlling the unloaded profile of the body spring in the blade using a procedure proposed in a previous study. Two blades, one blade designed to generate a uniform pressure distribution and the other designed to generate non-uniform pressure distribution, are developed using the procedure. Contact pressure distributions of the developed blades are measured using a special device and compared with the intended distributions confirming the similarities between the two groups. Vertical and lateral vibrations of the two blades are measured under realistic operating condition simulated by a wiper test rig. The vertical vibrations of the blade with non-uniform contact pressure are substantially smaller than corresponding vibrations of the blade with uniform contact pressure over the entire rubber strip.

• Korean Journal of Clinical Laboratory Science
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• v.46 no.2
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• pp.54-58
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• 2014

This study aims to understand some related types (to DiSC behavioral ones) through an analysis about DiSC behavioral types of freshmen at the clinical pathology department in the University. In order to do that, a total of 34 male and female students were surveyed. General characteristics and DiSC behavioral types for the targeted students were analyzed for frequency and percentage. For the frequency, the Chi-square test was performed and the level of significance was set to p<0.05. For the elements to select the university at general characteristics from the result of this study, 21 students were found to have selected the university voluntarily (61.8%). For the information about the clinical pathology department, 14 students were found to be informed through media (41.2%) and 7 students were informed through their parents (20.6%). For the DiSC behavioral types of the students majoring in clinical pathology, 18 students were found to be I type (53.0%), 8 students were C type (23.5%), 5 students were S type (14.7%) and 3 students were D type (8.8%). The relevance between general characteristics and DiSC behavioral type were found to be insignificant. As this study is aimed, there is no significant relevance between general characteristics and DiSC behavioral types, but through an understanding of characteristics of the students majoring in the clinical pathology, helping freshmen who are taking their first steps to adapt themselves to a new environment by diagnosing and understanding their behavioral types, understanding behavioral styles of those four types and guiding them in a positive direction, the method should be considered to raise their satisfaction about the major.

• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1125-1134
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• 2007

In this paper, we propose a new approach for rotation invariant texture classification based on Gabor wavelet. Conventional methods have the low correct classification rate in large texture database. In our proposed method, we define two feature groups which are the global feature vector and the local feature matrix. The feature groups are output of Gabor wavelet filtering. By using the feature groups, we defined an improved discriminant and obtained high classification rates of large texture database in the experiments. From spectrum symmetry of texture images, the number of test times were reduced nearly 50%. Consequently, the correct classification rate is improved with $2.3%{\sim}15.6%$ values in 112 Brodatz texture class, which may vary according to comparison methods.