• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.259-267
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• 2009

Generalized Extreme Value (GEV) distribution is recommended for flood frequency and extreme rainfall distribution in many country. L-moment method is the most common estimation procedure for the GEV distribution. In this study, the relationships between the cross-site correlations between extreme events and the cross-correlation of estimators of L-moment ratios (L-moment Coefficient of Variation (L-CV) and L-moment Coefficient of Skewness (L-CS)) for data generated from GEV distribution were derived by Monte Carlo simulation. Those relationships were fit to the simple power function. In this Monte Carlo simulation, GEV+ distribution were employed wherein unrealistic negative values were excluded. The simple power models provide accurate description of the relationships between cross-correlation of data and cross-correlation of L-moment ratios. Estimated parameters and accuracies of the power functions were reported for different GEV distribution parameters combinations. Moreover, this study provided a description about regional regression approach using Generalized Least Square (GLS) regression method which require the cross-site correlation among L-moment estimators. The relationships derived in this study allow regional GLS regression analyses of both L-CV and L-CS estimators that correctly incorporate the cross-correlation among GEV L-moment estimators.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.172-176
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• 2000

A series of preliminary experiments were carried out to quantify the annoyance are noisiness caused by floor impact noise. From the results of the experiments. the heavy impact source was found to be felt louder and noisier than the light impact source. Measurements of noise were also conducted by a diagnostic system based on the model(the model consists of the autocorrelators and the cross-correlation for signals arriving at two ear entrants) of the human auditory-brain system. Physical factors in the model were calculated by use of the ACF(autocorrelation function) and IACF(interaural cross correlation function) of binaural signals. From the ACF/IACF analysis, it was found that perceived loudness of floor impact noise could be represented by the factors of the ACF/IACF model.

• The Journal of the Acoustical Society of Korea
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• v.20 no.7
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• pp.31-36
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• 2001

Passive sonar system forms the various beams in any desired directions to obtain the improvement in Signal-to-Noise (S/N) ratio, bearing detection and localization of targets, and the attenuation of interferences from other directions. The improvement of beamforming is very important to detect modern underwater targets as noise reduction technology leads to considerably low-level acoustic emissions in the long range in complex environmental sea. In this paper, we proposed the spatial cross correlation beamforming (SCCBF) algorithm using cross correlation matrix of individual hydrophone pairs of linear array sensors. By the theoretical analysis and simulation, the proposed SCCBF is demonstrated that its performances compared to conventional beamforming (CBF) output can be obtain above 3dB of array gain and about half of beam width represented the bearing accuracy in target detection. Also, this paper presents sea test result of linear passive sonar system that the proposed algorithm implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1138-1144
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• 2013

Cross-correlation functions of maximal period sequences have been studied for decades. In this paper, we find the cross-correlation values of non-linear sequences $S_a^r(t)=Tr_1^m\{[Tr_m^n(a{\alpha}^t+{\alpha}^{dt})]^r\}$ having the maximal period $2^n-1$ for Niho type decimation $d=2^{m-2}(2^m+3)$, where n=2m. In particular, we call d Niho type decimation in case $d{\equiv}1(mod\;2^m-1)$. And we analyze the cross-correlation distributions of $S_a^r(t)$ when the phase shift ${\tau}=(2^m+1)k(0{\leq}k{\leq}2^m-2)$ and provide experiment results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1417-1419
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• 2016

In order to improve the transmission performance of a chirp signal-based chirp spread spectrum system, the cross-correlation coefficient (CCC) should be carefully considered. In this paper, we derive the CCC for analyzing the transmission performance and propose the optimal chirp rate based on the analysis. The simulation results verify the mathematical derivations and show that the considered scheme can improve the performance by considering the CCC.

• Journal of Integrative Natural Science
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• v.9 no.1
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• pp.1-9
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• 2016

Leucine rich repeat kinase 2 (LRRK2) is a highly promising target for Parkinson's disease (PD) that affects millions of people worldwide. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of pyrrolopyrimidine-based selective LRRK2 kinase inhibitors. This study was performed to rationalize the structural requirements responsible for the inhibitory activity of these compounds. A reliable 3D-QSAR model was developed using comparative molecular field analysis (CoMFA) technique. The model produced statistically acceptable results with a cross-validated correlation coefficient ($q^2$) of 0.539 and a non-cross-validated correlation coefficient ($r^2$) of 0.871. Robustness of the model was further evaluated by bootstrapping and progressive scrambling analysis. This work could assist in designing more potent LRRK2 inhibitors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.733-738
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• 2002

Zero Cross-correlation Zone (ZCZ) code has a good performance in Multi-user CDMA system to get low correlation zone and reject co-channel interference. In this paper, we do analysis of spreading code design to obtain this kind of property of correlations with a complex spreading scheme and denote their effective performance for mobile communication system. In addition, a Jacket polyphase sequence is an example to show the improved performance and regular properties effective performance for mobile communication system. In addition, a Jacket polyphase sequence is as an example to show the improved performance and regular properties.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.133-136
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• 2007

Cross correlation of seismic-background motions (Campillo and Paul, 2003; Shapiro et al., 2005) is applied to observations from the Korean Meteorological Administration seismic network to estimate the short-period Rayleigh and Love wave dispersion characteristics of the region. Standard processing procedures are applied to the cross correlation, except that signal whitening is used in place of one-bit sampling to equalize power in signals from different times. Multiple-filter analysis is used to extract the group velocities from the estimated Green's functions, which are then used to image the spatially varying dispersion at periods between 0.5 and 20 sec. The tomographic inversion technique used inverts all periods simultaneously to provide a smooth dispersion curve as a function of period in addition to the usual smooth spatial image for a given period. The Gyeongsang Basin in the southeastern part of the peninsula is clearly resolved with lower group velocities.

• The Korean Journal of Food And Nutrition
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• v.29 no.5
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• pp.605-609
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• 2016

This study aimed to find the optimum instrumental test conditions for the Texture Profile Analysis (TPA) of cooked rice in order to predict the sensory texture attributes (hardness, adhesiveness, chewiness). Sensory evaluation was performed for three kinds of instant cooked rice with university students in their twenties and the results of the sensory evaluation were compared to instrumental TPA patterns. Using partial least squares regression, the instrumental TPA results at a cross-head speed of 1.0 mm/sec and a compression ratio of 70% proved to be an excellent predictor of the sensory attributes of hardness ($R^2=0.99$) and chewiness ($R^2=0.99$). The results at a cross-head speed of 0.5 mm/sec and compression ratio of 30% provided an excellent model for the prediction of sensory adhesiveness ($R^2=0.83$). In this experimental range, sensory hardness and chewiness showed a high correlation with instrumental TPA parameters (hardness, cohesiveness, adhesiveness, springiness, chewiness) with a high cross-head speed and compression ratio, while sensory adhesiveness showed a high correlation with the TPA parameters with a low cross-head speed and compression ratio.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.953-963
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.