• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.35-38
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• 2004

In this paper, we investigate and analyze the problems encountered in frame-based estimation of TDOA(Time Difference of Arrival) using CPSP function. Spectral leakage occurring in framing of a speech signal by a rectangular window makes estimation of CPSP spectrum inaccurate. Framing with a Hamming window to reduce the spectral leakage effect distorts the signal due to the different weighting at temporally same sample, which make the TDOA estimation using CPSP function inaccurate. In this paper, we solve this problem by reducing the dynamic range of the spectrum of a speech signal with preemphasis. Experimental results confirm that the framing of pre-emphasized microphone output with a rectangular window shows higher success ratio of TDOA estimation than any other framing methods.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.766-772
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• 1999

With the increase of portable system and high-density IC, power consumption of VLSI circuits is very important factor in design process. Power estimation is required in order to estimate the power consumption. A simple and correct solution of power estimation is to use circuit simulation. But it is very time consuming and inefficient way. Probabilistic method has been proposed to overcome this problem. Transition density using probability was an efficient method to estimate power consumption using BDD and Boolean difference. But it is difficult to build the BDD and compute complex Boolean difference. In this paper, we proposed Propowest. Propowest is building a digraph of circuit, and easy and fast in computing transition density by using modified COP algorithm. Propowest provides an efficient way for power estimation.

• Journal of Oral Medicine and Pain
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• v.33 no.3
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• pp.269-277
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• 2008

The purpose of this study was to estimate occlusal tooth wear and bruxism severity in TMD patients, and evaluate the effectiveness of the present age estimation method by occlusal tooth wear in TMD patients. Takei's age estimation method was applied to 163 subjects(56 controls, 107 TMD patients). The author analyzed the degree of occlusal tooth wear from the difference between estimated age and actual age. The obtained results were as follows: 1. In all age group, occlusal tooth wear in TMD patients is higher than those in asymptomatic controls. In 20's age group, a statistically significant difference was found. 2. In both gender, occlusal tooth wear in TMD patients is higher than those in asymptomatic control. In male, a significant difference was found. 3. Occlusal tooth wear in TMD patients with bruxism is significantly higher than that in control. 4. We found no significant difference in bruxism severity and occlusal tooth wear among the RDC/TMD subgroups. 5. Application of Takei's method would be still useful for age estimation in Korean. In case of age estimation of TMD patients using occlusal tooth wear, evaluation of the bruxism severity and appropriate correction according to age, sex and difference of geographical location should be considered.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.189-196
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• 2013

This paper presents a two-stage approach to detect pedestrians in video sequences taken from a moving vehicle. The first stage is a preprocessing step, in which potential pedestrians are hypothesized. During the preprocessing step, a difference image is constructed using a global motion estimation, vertical and horizontal edge maps are extracted, and the color difference between the road and pedestrians are determined to create candidate regions where pedestrians may be present. The candidate regions are refined further using the vertical edge symmetry features of the pedestrians' legs. In the next stage, each hypothesis is verified using the integral channel features and an AdaBoost classifier. In this stage, a decision is made as to whether or not each candidate region contains a pedestrian. The proposed algorithm was tested on a range of dataset images and showed good performance.

• Journal of Advanced Navigation Technology
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• v.20 no.2
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• pp.155-160
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• 2016

Recently, underwater acoustic communication (UWAC) has been studied by many scholars and researchers. In order to use UWAC, we need to estimate time difference between the two signals in underwater environment. Typically, there are major three methods to estimate the time-difference between the two signals such as estimating the arrival time of the first non-background segment and calculate the temporal difference, calculating the cross-correlation between the two signal to infer the time-lagged, and estimating the phase delay to infer the time difference. In this paper, we present calculating the cross-correlation between the two signals to infer the time-lagged to apply UWAC. We also present the experimental result of estimating the arrival time by using cross-correlation. We get EXCORR = 0.003055 second as the estimation error in mean absolute difference.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.1
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• pp.1-8
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• 2021

For the safe and reliable operation of lithium-ion batteries in electric vehicles or energy storage systems, having accurate information of the battery, such as the state of charge (SOC), is essential. Many different techniques of battery SOC estimation have been developed, such as the Kalman filter. However, when this filter is applied to multiple batteries, it has difficulty maintaining the accuracy of the estimation over all cells owing to the difference in parameter values of each cell. The difference in the parameter of each cell may increase as the operation time accumulates due to aging. In this paper, a novel deep neural network (DNN)-based SOC estimation method for multi-cell application is proposed. In the proposed method, DNN is implemented to determine the nonlinear relationships of the voltage and current at different SOCs and temperatures. In the training, the voltage and current data obtained at different temperatures during charge/discharge cycles are used. After the comprehensive training with the data obtained from the cycle test with a cell, the resulting algorithm is applied to estimate the SOC of other cells. Experimental results show that the mean absolute error of the estimation is 1.213% at 25℃ with the proposed DNN-based SOC estimation method.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.15-21
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• 2020

This paper presents the outlier detection algorithm in the estimation method of a source location and velocity based on two-step weighted least-squares method using time difference of arrival(TDOA) and frequency difference of arrival(FDOA) data. Since the accuracy of the estimated location and velocity of a moving source can be reduced by the outliers of TDOA and FDOA data, it is important to detect and remove the outliers. In this paper, the method to find the minimum inlier data and the method to determine whether TDOA and FDOA data are included in inliers or outliers are presented. The results of numerical simulations show that the accuracy of the estimated location and velocity is improved by removing the outliers of TDOA and FDOA data.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.297-312
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• 2000

A three stage sampling procedure designed to estimate the difference betweentwo normal means is proposed and evaluated within a unified decision-theoretic framework. Both point and fixed-width confidence interval estimation are combined in a single decision rule to make full use of the available data. Adjustments to previous solutions focusing on only one of the latter objectives are indicated. The sensitivity of the confidence interval for detecting shifts in true mean difference is also investigated Numerical and simulation studies are presented to supplement the theoretical results.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.8 s.239
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• pp.903-910
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• 2005

Inverse radiation problems are solved for estimating the boundary conditions such as temperature distribution and wall emissivity in axisymmetric absorbing, emitting and scattering medium, given the measured incident radiative heat fluxes. Various regularization methods, such as hybrid genetic algorithm, conjugate-gradient method and finite-difference Newton method, were adopted to solve the inverse problem, while discussing their features in terms of estimation accuracy and computational efficiency. Additionally, we propose a new combined approach that adopts the hybrid genetic algorithm as an initial value selector and uses the finite-difference Newton method as an optimization procedure.

• 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.