• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1151-1160
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• 2006

The similarity weight, the pearson's correlation coefficient, which is used in the recommender system has a weak point that it cannot predict all of the prediction value. The similarity weight, the vector similarity, has a weak point of the high MAE although the prediction coverage using the vector similarity is higher than that using the pearson's correlation coefficient. The purpose of this study is to suggest how to raise the prediction coverage. Also, the MAE using the suggested method in this study was compared both with the MAE using the pearson's correlation coefficient and with the MAE using the vector similarity, so was the prediction coverage. As a result, it was found that the low of the MAE in the case of using the suggested method was higher than that using the pearson's correlation coefficient. However, it was also shown that it was lower than that using the vector similarity. In terms of the prediction coverage, when the suggested method was compared with two similarity weights as I mentioned above, it was found that its prediction coverage was higher than that pearson's correlation coefficient as well as vector similarity.

• Journal of IKEEE
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• v.16 no.2
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• pp.153-158
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• 2012

A new diversity combining scheme is proposed for time-of-arrival (TOA) estimation of chirp signal in dense multipath channel. In the multipath channel, the performance of TOA estimation using conventional correlation matrix-based diversity combining scheme is degraded due to the lack of de-correlation effect. To increase the de-correlation effect, the proposed diversity scheme employs interleaving method based on the property of de-chirped signal. As a result, the proposed scheme increases de-correlation effect and also reduces the noise of TOA estimation. Finally, the diversity achieved from the proposed scheme improves TOA estimation performance. The de-correlation effect is analyzed mathematically. The estimation accuracy of the proposed diversity scheme is superior to that of conventional diversity scheme in multipath channel.

• Journal of the Korean Solar Energy Society
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• v.33 no.4
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• pp.101-110
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• 2013

The propose of this study is to understand the phenomenon of radiation and comparison of analysis of two methods. One is analysis method of same-time data and the another is analysis method of rank data. We confirmed that two methods of correlation analysis had the effectiveness and suitability. The followings are main results from this study. 1) The seasonal correlation coefficient of long and short-wave radiation is higher in winter than in summer because of high humidity in the summer season can makes easily cloud in the sky locally. 2) According to analysis method, there is big difference in correlation coefficient from 0.494(Analysis method of same-time data) to 0.967(Analysis method of rank data) with short-wave radiation by the location during summer. These results have significant value in solar radiation research and analysis. It has explored a new way for solar radiation research of analysis method as well.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.825-829
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• 2009

In this paper, we examine the fundamental performance of image coding schemes based on multipulse model. First, we introduce several kinds of pulse search methods (i.e., correlation method, pulse overlap search method and pulse amplitude optimization method) for the model. These pulse search methods are derived from auto-correlation function of impulse responses and cross-correlation function between host signals and impulse responses. Next, we explain the basic procedure of multipulse image coding scheme, which uses the above pulse search methods in order to encode the high frequency component of an original image. Finally, by means of computer simulation for some test images, we examine the PSNR(Peak Signal-to-Noise Ratio) and computational complexity of these methods.

• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.1-12
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• 2004

This paper estimated the arrival angle and electric wave delay time using the space method law and the directions of arrival (DOA) estimation algorithm in case of signal correlation. Space method law is the method used to repress cross correlation before applying the weight value to the receiving signal. The values of the diagonal elements in the correlation matrix were averaged to replace as the diagonal elements value. In the area of wireless communication or mobile communication, there are high correlations in case of low delay time difference in multiple waves. This causes the quality of the communication to drop due to interference with the desired signal elements. This paper estimated the arrival angle and electric wave delay time using the space method law and the MUSIC algorithm. With the arrival angle algorithm, the arrival angle cannot be estimated below 5 in case of signal correlations because the angle resolution capacity decreases accordingly. The super resolution capacity was estimated to determine the arrival angle below 5 in this paper. In addition, the proposed algorithm estimated the short delay time difference to be below 20ns.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.317-318
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• 2010

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.178-182
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• 2007

In this study, we evaluated current raingauge network of Soyanggang dam region applying spatial-correlation analysis and Entropy theory to recommend an optimized raingauge network. In the process of analysis, correlation distance of raingauge stations is estimated and evaluated via spatial-correlation method and entropy method. From this correlation distances, respective influencing radii of each dataset and each methods is assessed. The result of correlation and entropy analysis has estimated correlation distance of 25.546km and influence radius of 7.206km, deducing a decrease of network density from $224.53km^2$ to $122.47km^2$ which satisfy the recommended minimum densities of $250km^2$ in mountainous regions(WMO, 1994) and an increase of basin coverage from 59.3% to 86.8%. As for the elevation analysis the relative evaluation ratio increased from 0.59(current) to 0.92(optimized) resulting an obvious improvement.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.528-537
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• 2021

Face recognition has gained significant notice because of its application in many businesses: security, healthcare, and marketing. In this paper, we will present the recognition method using the combination of correlation filters (CF) and Support Vector Machine (SVM). Firstly, we evaluate the performance and compared four different correlation filters: minimum average correlation energy (MACE), maximum average correlation height (MACH), unconstrained minimum average correlation energy (UMACE), and optimal-tradeoff (OT). Secondly, we propose the machine learning approach by using the OT correlation filter for features extraction and SVM for classification. The numerical results on National Cheng Kung University (NCKU) and Pointing'04 face database show that the proposed method OT-SVM gets higher accuracy in face recognition compared to other machine learning methods. Our approach doesn't require graphics card to train the image. As a result, it could run well on a low hardware system like an embedded system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.279-282
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• 1996

The authors have already proposed a method for grouping of inputs of a logical circuit under test (LCUT) by use of M-sequence correlation. We call this method as input grouping (IG) method. In this paper, the authors propose a new method to estimate the faulty part in the circuit by use of IG when some information on the candidate of faulty part can be obtained beforehand. The relationship between IG and fault probabilities of a LCUT, and undetected fault ratios are investigated for various cases. Especially the investigation was made in case where the IG was calculated by use of n correlation functions (I $G_{inp}$). From the theoretical study and simulation results it is shown that the estimation error ratio of fault probabilities and undetected fault ratio of LCUT are sufficiently small even when only a part of correlation functions are used. It is shown that the number of correlation functions which are to be memorized to calculate IG can be considerably reducible from 2$^{n}$ - 1 to n by use of I $G_{inp}$. So this method would be very useful for a fault diagnosis of actual logic circuit.uit.

• Journal of Korea Water Resources Association
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• v.38 no.10 s.159
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• pp.851-859
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• 2005

Normalized cross-correlation (correlation coefficient) is a useful measure for pattern matching in PIV (Particle Image Velocimetry) analysis. Because it does not have a corresponding simple expression in frequency domain, several fast but inexact measures have been used. Among them, three measures of correlation for PIV analysis and the normalized cross-correlation were evaluated with a sample calculation. The test revealed that all other proposed correlation measures sometimes show inaccurate results, except the normalized cross-correlation. However, correlation coefficient method has a weakpoint that it requires so long time for calculation. To overcome this shortcoming, a fast and exact method for calculating normalized cross-correlation is suggested. It adopts Fast Fourier Transform (FFT) for calculation of covariance and the successive-summing method for the denominator of correlation coefficient. The new algorithm showed that it is really fast and exact in calculating correlation coefficient.