• The Journal of Engineering Geology
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• v.32 no.4
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• pp.483-498
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• 2022

Soil moisture is defined as water in the pores of the soil's unsaturated zone, and it is closely related to various hydrological processes. This study aims to provide meaningful data by identifying factors affecting soil moisture through comparing soil moisture content and soil permeability in a study area covering six different land use types in an agricultural region that is highly dependent on groundwater. We conduct auto-correlation analysis, spectral density analysis, and cross-correlation analysis using time-series data. Soil moisture content shows to have weak auto-correlation and memory effects, and precipitation appears to have a substantial influence on soil moisture content. Saturation hydraulic conductivity does not vary markedly with changing land use, and instead appears to be affected by the inhomogenous soil structure.

• 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.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.2
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• pp.94-103
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• 1997

The WCHF-FSJTC (wavelet circular harmonic function frequency selective joint transform correlator) using th wavelet transformed CHF as the reference image in FSJTC is proposed for rotation invariant pattern recognition. Since the wavelet transform has the property of feature extraction, the proposed system can have the better DC (discrimination cpability) and the higher SNR(signal to noise ratio) compared with the conventional CHF-CJTC(circular harmonic function conventional joint transform correlator). And since the structure of the proposed system is FSJTC which can eliminate auto-correlation and cross-correlation between input images, it can eliminate false alarm caused by the overlapping among correlation peaks. The used wavelet functio is the morlet function, which is proper for the reference image used in this paper. the optimal dialation parameter and oscillation frequency of the wavelet function are also achieved with varying the parameters of the wavelet function. The computer simulation shows that the proposed system has the best performance when the dilation parameter is 0.8 and the oscillation frequency is 0.48.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.939-944
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• 2005

In this paper, a sound quality index for the evaluation of the vehicle intake noise was developed through a correlation analysis of the objective measurement and the subjective evaluation. First, intake orifice noise was measured at the wide-open throttle sweep condition. And then, the acoustic transfer function between intake orifice noise and interior noise was measured. Simultaneously, subjective evaluation was carried out with a 10-scale score by 8 special engineers. The correlation analysis between the psychoacoustic parameters derived from the measurement and the subjective evaluation was performed. The most critical factor was determined and the corresponding sound quality index for intake noise was obtained from the multiple factor regression analysis method. Finally, the effectiveness of the proposed index was validated.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.4
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• pp.80-88
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• 2003

Radar signal simulation is increasingly gaining in importance according as modem radar systems are more complex. Although computer performance has been advanced, it is difficult to implement the real-time simulation because the detailed model for the radar is necessary to get the desired accuracy. In order to achieve real time operation, we propose radar signal generation technique using ambiguity function, Instead of wellknown correlation method. The ambiguity function is the mathematical modeling of the signal processing procedure which is a simulation section to require the most computations.

• Journal of Soil and Groundwater Environment
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• v.16 no.2
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• pp.30-40
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• 2011

In this study, we compared the analysis results before and after the detrending for the data. According to the comparison results, correlation functions were not much changed while autocorrelation and spectral density functions were largely varied. Especially, time series data with a long-term variation trend showed a distinctive difference. This study demonstrated a usefulness of the detrending for a further analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.521-524
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• 2013

In this paper, the algorithm that recognizes the gesture by configuring the feature information obtained through Improved Higher Order Local Correlation Features as low dimensional gesture symbol was described. Since the proposed method doesn't require a lot of computations compared to the existing geometric feature based method or appearance based methods and it can maintain high recognition rate by using the minimum information, it is very well suited for real-time system establishment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.926-931
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• 1998

In this paper, a code sequence generation method of the Suehiro sequence is suggested. In this method, a code sequence is generated only with integer sums and modular techniques. the auto-correlation and cross-correlation characteristics of the sequence generated by the method are investigated. The sequence generated by the suggested method has the orthogonality and satisfies the mathematical lower bound of the cross-correlation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.9 s.90
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• pp.884-890
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• 2004

In this paper, an index for the evaluation of vehicle intake booming noise is developed through a correlation analysis of objective measurement data and subjective evaluation data. First, intake orifice noise is measured at the wide-open test condition. And then, acoustic transfer function between intake orifice noise and interior noise at the steady state condition is estimated. Simultaneously, subjective evaluation was carried out with a ten-scale score by 8 engineers. Next, the correlation analysis between the psycho-acoustic parameters derived from the measured data and the subjective evaluation is performed. The most critical factor was determined and the corresponding index for the intake booming noise is obtained from the multiple factor regression method. At last, the effectiveness of the proposed index is validated.

• Journal of Integrative Natural Science
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• v.5 no.2
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• pp.120-126
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• 2012

This paper describes the algorithm that lowers the dimension, maintains the gesture recognition and significantly reduces the eigenspace configuration time by combining the higher correlation feature information and Principle Component Analysis. Since the suggested method doesn't require a lot of computation than the method using existing geometric information or stereo image, the fact that it is very suitable for building the real-time system has been proved through the experiment. In addition, since the existing point to point method which is a simple distance calculation has many errors, in this paper to improve recognition rate the recognition error could be reduced by using several successive input images as a unit of recognition with K-Nearest Neighbor which is the improved Class to Class method.