• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.105-114
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• 2015

This paper presents a fast Time Difference of Arrival (TDOA) estimation for sound source localization. TDOA is the time difference between the arrival times of a signal at two sensors. We propose a partial cross correlation method to increase the speed of TDOA estimation for sound source localization. We do this by predicting which part of the cross correlation function contains the required TDOA value with the help of the signal energies, and then we compute the cross correlation function in that direction only. Experiments show approximately 50% reduction in the cross correlation computation time thereby increasing the speed of TDOA computation. This makes it very relevant for real world surveillance.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.157-167
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• 2017

This paper proposes a simple sound source localization (SSL) method based on signal energies comparison and partial cross correlation for TDOA computation. Many sound source localization methods include multiple TDOA computations in order to eliminate front-back confusion. Multiple TDOA computations however increase the methods' computation times which need to be as minimal as possible for real-time applications. Our aim in this paper is to achieve the same results of localization using fewer computations. Using three microphones, we first compare signal energies to predict which quadrant the sound source is in, and then we use partial cross correlation to estimate the TDOA value before computing the azimuth value. Also, we apply a threshold value to reinforce our prediction method. Our experimental results show that the proposed method has less computation time; spending approximately 30% less time than previous three microphone methods.

• Proceedings of the KIEE Conference
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• 1994.07b
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• pp.1649-1651
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• 1994

This paper presents a new method for estimating partial discharge position using improved cross-correlation technique and neural networks in the power transformer. When ultrasonic signal is occurred by partial discharge, we detected these signals and calculated cross-correlation values with Hamming window. Also, we estimated partial discharge position using neural network with cross-correlation values. In the result of case study, we can estimate more accurately the partial discharge position than any other algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.44-55
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• 1993

In this paper, we proposed a new optical method for the efficient recognition of Korean characters. There are six filters in the proposed method which employed the concepts of amplitude-modulated phase-only filter(AMPOF) and spatial frequency modulation(SFM). Here, amplitude modulation is used to achieve improved correlation discrimination and SFM is to reduce the number of filters. We also used a simplified synthetic discriminant function(SDF) for distortion invariance of input image. In order to recognize the partial rotation invariant Korean characters, the proposed distortion invariant minimum average correlation energy (MACE) filter is synthesized SFM, partial rotation invariant filter (PRIF), AMPOF and MACE for partial rotation invariance in the frequency domain. The advantage of the proposed filters is to supress the sidelobes of cross correlation peak away from the autocorrelation peak and to produce sharp correlation peaks. We performed simulation and optical experiment for some of Korea characters using the proposed method. The results show that the proposed method has more improved discriminant ability and reduced processing time than the conventional methods.

• 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.

• 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.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.781-784
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• 1994

Detecting partial discharge(PD) and locating its source are one of many diagnosis methods. Location the PD source is very important to reduce the time and cost of repairing power transformers. And to locate the PD source, the cross-correlation method is a well known one. But there many spurious peaks in cross-correlation, and occasionally, some peaks could be bigger than the true one. In order to analysis these spurious peaks and to reduce them, we have done many experiments and simulations. As the results we could reduce the spurious peaks, and get well defined cross-correlation from which it is easy to locate the PD source accurately.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1471-1477
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• 2006

Electrocorticogram (ECoG) was recorded in one young adult suffering from medically refractory partial seizures a few weeks before resection. ECoG of intractable focal epilepsy was analyzed usins AR model, wavelet analysis and cross-correlation analysis. The cross-correlation of the epileptic discharges was calculated between the electrodes in every unit of time, to get the phase shift. A contour map of the phase shift and the sequential two-dimensional phase shift maps were utilized to localize the epileptic foci and to study their propagation process. More than two epileptogenic foci were localized and two kinds of propagating process were shown. These investigations suggest that epileptic phenomena can be caused by at least two kinds of mechanisms in one patient.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.45-51
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• 1996

This paper presents a neural network approach for on-line estimation of partial discharge(PD) location using advanced correlation technique in power transformer. Ultrasonic sensors detect ultrasonic signals generated by a PD and the proposed method calculates time difference between the ultrasonic signals at each sensor pair using the cross-correlation technique applied by moving average and the Hamming window. The neural network takes distance difference as inputs converted from time difference, and estimates the PD location. Case studies showed that the proposed method using advanced correlation technique and a neural network estimated the PD location better than conventional methods.