• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.70-76
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• 2012

In this paper, an automatic extraction method of glomerulus region from human renal tissue image is presented. The important information reflecting the state of kidneys richly included in the glomeruli, so it should be the first step to extract the glomerulus region from the renal tissue image for the further quantitative analysis of the renal condition. Especially, there is no clear difference between the glomerulus and other tissues, so the glomerulus region can not be easily extracted from its background by the existing segmentation methods. The outer edge of a glomerulus region is regarded as a common property for the regions of this kind ; a two- dimensional Gaussian distribution is used to convolve with an original image first and then the image is thresholded at this blurred image ; a closed curve corresponding to the outer edge can be obtained by usual pattern processing skills like thinning, branch-cutting, hole-filling etc., Finally, the glomerulus region can be obtained by extracting the area in the original image surrounded by the closed curve. The glomerulus regions are correctly extracted by 85 percentages and experimental results show the proposed method is effective.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.68-76
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• 2018

In this paper, we describe the correlation processing method of multi-polarization observation data of the Daejeon Correlator. VLBI observations include single or multiple polarized observations depending on the type of object. Polarization observations are performed to observe the characteristics of the object. During the observations of the celestial object, polarization measurements are also performed to determine the delay values and causes of changes in the object. Correlation processing of polarization observation data of the Daejeon correlator is proposed by OCTAVIA of a synchronous reproduction processing apparatus that outputs data input to each antenna unit by using an output bit selection function to convert bits and the order of the data streams is changed, And the input of the Daejeon correlator is configured to perform the polarization correlation processing by conducting correlation processing by setting the existing stream number to be the same. Correlation processing is conducted on the test data observed for the polarization correlation processing and it is verified through experiments that the polarization correlation processing method of the proposed Daejeon correlator is effective.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.682-685
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• 2004

This paper investigated a method for classifying emotional states by using pulse wave signal. It focused on finding effective features for emotional state classification. The emptional states considered here consisted of interest and neutral. Classification experiments utilized 65 and 60 samples of interest and neutral states respectively. We have investigated 19 features derived from pulse wave signals by using both time domain and frequency domain analysis methods with 2 classifiers of minimum distance (normalized Euclidean distanece) and ${\kappa}$-Nearest Neighbour. The Leave-one-out cross validation was used as an evaluation mehtod. Based on experimental results, the most efficient features were a combination of 4 features consisting of (i) the mean of the first differences of the smoothed pulse rate time series signal, (ii) the mean of absolute values of the second differences of thel normalized interbeat intervals, (iii) the root mean square successive difference, and (iv) the power in high frequency range in normalized unit, which provided 80.8% average accuracy with ${\kappa}$-Nearest Neighbour classifier.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.1
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• pp.94-100
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• 2007

MVRS's measuring principles are based on the Doppler principle. It measures the velocities near the muzzle using the doppler signal output from the antenna and then predicts the velocity of the bullet leaving the muzzle by performing the regression analysis on previous measured velocities. There are a number of error sources when calculating the muzzle velocity. Antenna has long term frequency stability error and the doppler signal from the antenna has noise. These two error sources influence the accuracy of estimated velocities from the doppler signal. Estimated velocity errors result in the random error of data statistics. And when performing a regression analysis these random error components are transferred to the fitting error component. This study also analyzed the error components according to the hardware limitations of MVRS-700 and the signal processing method, and presented the calculated uncertainty of muzzle velocity.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.3
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• pp.102-106
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• 2015

In order to avoid the electrical fire, AFCI(Arc Fault Cirruit Interrupter) has been obligated to be adopted in the United States of America since 2002. A study was carried out on how to detect Arc. In this paper, The propose is high-frequency signal detection methods and RSSI(Received Signal Strength Indication) signal processing algorithm for Arc detection. and the electrical characteristics were verifying.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2073-2074
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• 2011

In this study, an algorithm for diagnosis of dc motor with winding open fault is suggested. A dc motor used in this paper, is consisted of a permanent magnet field stator, double 16-turn series winding rotating armature with 12-slot, brush and 12-commutator, etc. A current signal of dc motor which has brushes and commutatorswas considered for fault diagnosis. By commutation, this current signal shows different wave form according to the fault condition of the motor. In this study, operation of the data was easily through simplification of the current signal by the signal processing. Computation method is presented reference value($C_{dv}$) for diagnosis of winding open fault and verified through experiments that can be diagnosed using the reference value($C_{dv}$).

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.385-391
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• 2007

A class D digital audio amplifier with small size, low cost, and high quality is positively necessary in the multimedia era. Since the digital audio amplifier is based on the PWM signal processing, it is improper to analyze the principle of signal generation using linear system theories. In this paper, a class D digital audio amplifier based ADSM (Advanced Delta-Sigma Modulation) is considered. We first model the digital audio amplifier and then explain the operation principle using variable structure control algorithm. Moreover, the ripple signal generated by the hysteresis in the comparator has a significant effect on the system performance. Thus, we present a method to find the magnitude and the frequency of the ripple signal using describing function. Finally, simulations and experiments are provided to show the validity of the proposed methods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.139-145
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• 2012

This paper shows a novel interference cancellation method of relay utilizing to the CGM algorithm in wireless communication environments. It is a problem that relay have interference cause by feedback signal of it. CGM algorithm obtained weight value that can remove the interference due to feedback signal of relay. In this paper, we confirm that performance of CGM algorithm is far superior with suitable cancellation value to remove the feedback signal. Also, we implement CGM module to verify the real-time processing of CGM algorithm using to DSP. Based on the analysis from computer simulation, it is observed that proposed algorithm is suitable for the relay in time-varying environment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.593-596
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• 2004

Hub bearings not only sustain the body of a car, but permit wheels to rotate freely. Excessive radial or axial load and many other reasons can cause defects to be created and grown in each component. Therefore, vibration and noise from unwanted defects in outer-race, inner-race or ball elements of a Hub bearing are what we want to detect as early as possible. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing signal has periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.70-75
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• 2000

After the patterning and probe process of wafer have been achieved, the dicing process is necessary to separate chips from a wafer. The dicing process cuts a wafer to lengthwise and crosswise direction to make many chips by using narrow circular rotating diamond blade. But inferior goods are made under the influence of complex dicing environment such as blade, wafer, cutting water and cutting conditions. This paper describes a monitoring algorithm using feature extraction in order to find out an instant of vibration signal change when bad dicing appears. The algorithm is composed of two steps: feature extraction and decision. In the feature extraction, two features processed from vibration signal which is acquired by accelerometer attached on blade head are proposed. In the decision. a threshold method is adopted to classify the dicing process into normal and abnormal dicing. Experiment have been performed for GaAs semiconductor wafer. Based upon observation of the experimental results, the proposed scheme shown a good accuracy of classification performance by which the inferior goods decreased from 35.2% to 12.8%.