• International Journal of Aeronautical and Space Sciences
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• v.10 no.2
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• pp.77-85
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• 2009

A two-dimensional cross-section analysis program based on the finite element method has been developed for composite blades with arbitrary cross-section profiles and material distributions. The modulus weighted approach is used to take into account the non-homogeneous material characteristics of advanced blades. The CLPT (Classical Lamination Plate Theory) is applied to obtain the effective moduli of the composite laminate. The location of shear center for any given cross-sections are determined according to the Trefftz' definition while the torsion constants are obtained using the St. Venant torsion theory. A series of benchmark examples for beams with various cross-sections are illustrated to show the accuracy of the developed cross-section analysis program. The cross section cases include thin-walled C-channel, I-beam, single-cell box, NACA0012 airfoil, and KARI small-scale blades. Overall, a reasonable correlation is obtained in comparison with experiments or finite element analysis results.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.287-293
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• 2012

This paper presents an efficient image registration method by measuring the similarity, which is based on multi-dimensional intensity fluctuation. Multi-dimensional intensity which considers 4 directions of the image, is applied to reflect more properties in similarity decision. And an intensity fluctuation is also applied to measure comprehensively the similarity by considering a change in brightness between the adjacent pixels of image. The normalized cross-correlation(NCC) is calculated by considering an intensity fluctuation to each of 4 directions. The 5 correlation coefficients based on the NCC have been used to measure the registration, which are total NCC, the arithmetical mean and a simple product on the correlation coefficient of each direction and on the normalized correlation coefficient by the maximum NCC, respectively. The proposed method has been applied to the problem for registrating the 22 face images of 243*243 pixels and the 9 person images of 500*500 pixels, respectively. The experimental results show that the proposed method has a superior registration performance that appears the image properties well. Especially, the arithmetical mean on the correlation coefficient of each direction is the best registration measure.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.2
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• pp.128-137
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• 2018

In this paper, we propose a novel class separability measure for radar signals. To reduce the sensitivity of the relative aspect angle between a target and radar, to evaluate the discriminatory power of radar signals, the proposed method first calculates the correlation coefficients between two radar cross sections (RCSs) or linearly shifts one-dimensional (1D) radar signals (i.e., high-resolution range profiles (HRRPs)), or rotates two 2D radar signals (i.e., inverse synthetic aperture radar (ISAR) images). Then, it uses the maximum correlation coefficient when two radar signals are best aligned. Next, the proposed method obtains new correlation-based discriminant matrices (CDM) using maximum correlation coefficients. Finally, the cumulative distribution function (CDF) in the CDM and the value corresponding to the specific probability in the CDF are obtained, and this value represents the discriminatory power of the radar signal. Experimental results show that the proposed method can accurately measure the target separability.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2895-2898
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• 2003

In this study, our primary goal is to classify the EMG(electromyographic) signals including the specific patterns related to hand motions in an arm. To do this, the EMG recognition method based on the LP coefficients and delay between multi-channels obtained by cross-correlation function is presented. The study consists of three functional parts, which are pans for obtaining the EMG signals from am muscle, analyzing LP coefficients and delay parameter obtained by cross-correlation function, and recognizing specific patterns. In the experiment, the result of the present method is compared with the results of the conventional methods. We expect that the results of this study is very effective in the mobile computer and wearable computer environment.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.934-937
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• 1992

The partial discharge signal can be used as the detection signal of the deterioration of the power transformer insulation. Detecting this signal, the insulation failure and the point, in which the partial discharge is generated, could be predicted. In this paper, we study to predict the point, and find that the cross correlation method could predict the point accurately. Also, experimental system and the results are presented here.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.471-474
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• 2002

A new stereoscopic PIV has been constructed using two CCD cameras, stereoscopic photogrammetry, and 3D-PTV principle. The capability of the developed stereoscopic PIV was verified through a test on the Standard Images which are provided on the website of VSJ. The arrangement of the two cameras was based on angular position For the acquisition of 3D velocity vectors, 2D velocity vectors were obtained using the gray-level cross-correlation method from the two camera images and they were matched stereoscopically. The wake of a circular cylinder was measured and turbulent properties were presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.11
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• pp.979-981
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• 2013

In this paper, this study is aimed how to estimate the position of scattered pilot to be used to estimate channel in the OFDM System. The proposed method is possible to estimate the accurate position of scattered pilot to remove the phase error through cross-correlation between received signal and 4 symbol delay received signal.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.221-225
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• 1998

This paper is to present a method for recognizing an image of a tracking object by processing the image from a camera, whose attitude is controlled in inertial space with inertial co-ordinate system. In order to recognize an object, a pseudo-random M-array is attached on the object and it is observed by the camera which is controlled on inertial coordinate basis by inertial stabilization unit. When the attitude of the camera is changed, the observed image of M-array is transformed by use of affine transformation to the image in inertial coordinate system. Taking the cross-correlation function between the affine-transformed image and the original image, we can recognize the object. As parameters of the attitude of the camera, we used the azimuth angle of camera, which is de-fected by gyroscope of an inertial sensor, and elevation an91e of camera which is calculated from the gravitational acceleration detected by servo accelerometer.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.19 no.3
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• pp.334-342
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• 2012

Purpose: This descriptive study was done to identify the academic achievement, self-directed learning (SDL), and critical thinking disposition (CTD) of nursing students according to their learning styles. Method: The participants were 240 nursing students. Data were collected using structured questionnaires which included Kolb's Learning Style Inventory, Academic Achievement in Fundamental Nursing and Health Assessment, Self Directed Learning Readiness Scale, and California Critical Thinking Disposition Inventory. Data were analyzed using ${\chi}^2$ test, ANOVA, Pearson' correlation coefficients, and Spearman rank correlation coefficient. Results: One third of respondents were shown to be Convergers in their learning style (33.3%). The Academic Achievement of students who were Convergers was significantly higher than those who were Divergers or Accommodators (F=5.95, p=.001). The SDL and CTD of students who were Convergers were significantly higher than Divergers and Assimilators (F=9.67, p<.001 and F=8.42, p<.001). No significant correlations were found between Academic Achievement and SDL or CTD, but a statistically significant positive correlation was found between SDL and CTD (r=.68, p<.001). Conclusion: The findings of this study indicate that learning style influences academic achievement, SDL and CTD.