• The Journal of the Korea Contents Association
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• v.15 no.1
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• pp.1-8
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• 2015

The purpose of this research is to identify the start and end point of TV program on Web TV. Until now, to replace realtime TV advertisement with Web TV advertisement, human work was the only way. To automatize the process, knowing the start and end point of TV program is the core technology. In this study, I extract 'Black level' between TV program and regard it as start & end point of program. The result of this study is showing that extracting 'Black level' can be a useful tool to define start & end point of TV program. And it will be also use an automatize replacement system for Web TV advertisement.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.570-575
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• 2002

This paper presents a new circular curve fitting approach of articulated manipulators, based on pseudoinverses. The paper aims at gaining the interpolation of circle from n data points, under the condition that the fitted circle should pass both a start point and an end point. In this paper, two algorithms of circular interpolation are presented. Prior to circular interpolation, are a spherical fitting should be performed, using least squares. In the first algorithm, the relationship between point data and normal vector on the sphere is used. In the second algorithm. the equation of plane which can be obtained from 3 points, i.e., a start point, an end point, and center of a sphere. The proposed algorithms are show to be efficient by using MATLAB-based simulation.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.93-101
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• 2021

Cardiac arrhythmias are common heart diseases and generally cause sudden cardiac death. Electrocardiogram (ECG) is an effective tool that can reveal the electrical activity of the heart and diagnose cardiac arrhythmias. We propose detection of P waves based on QRST cancellation zero-one substitution. After preprocessing, the QRST segment is determined by detecting the Q wave start point and T wave end point separately. The Q wave start point is detected by digital analyses of the QRS complex width, and the T wave end point is detected by computation of an indicator related to the area covered by the T wave curve. Then, we determine whether the sampled value of the signal is in the interval of the QRST segment and substitute zero or one for the value to cancel the QRST segment. Finally, the maximum amplitude is selected as the peak of the P wave in each RR interval of the residual signal. The average detection rate for the QT database was 97.67%.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.424-433
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• 2022

As the proportion of non-contact telemedicine increases and the number of electrocardiogram (ECG) data measured using portable ECG monitors increases, the demand for automatic algorithms that can precisely analyze vast amounts of ECG is increasing. Since the P, QRS, and T waves of the ECG have different shapes depending on the location of electrodes or individual characteristics and often have similar frequency components or amplitudes, it is difficult to distinguish P, QRS and T waves and measure each parameter. In order to measure the widths, intervals and areas of P, QRS, and T waves, a new algorithm that recognizes the start and end points of each wave and automatically measures the time differences and amplitudes between each point is required. In this study, the start and end points of the P, QRS, and T waves were measured using six Deep Neural Networks (DNN) that recognize the start and end points of each wave. Then, by synthesizing the results of all DNNs, 12 parameters for ECG characteristics for each heartbeat were obtained. In the ECG waveform of 10 subjects provided by Physionet, 12 parameters were measured for each of 660 heartbeats, and the 12 parameters measured for each heartbeat well represented the characteristics of the ECG, so it was possible to distinguish them from other subjects' parameters. When the ECG data of 10 subjects were combined into one file and analyzed with the suggested algorithm, 10 types of ECG waveform were observed, and two types of ECG waveform were simultaneously observed in 5 subjects, however, it was not observed that one person had more than two types.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.415-418
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• 1996

Etching Process, one of the most important process in semiconductor fabrication, has input control part of which components are pressure, gas flow, RF power and etc., and plasma gas which is complex and not exactly understood is used to etch wafer in etching chamber. So this process has not real-time feedback controller based on input-output relation, then it uses EPD(End Point Detection) signal to determine when to start or when to stop etching. Various type EPD controller control etching process using EPD signal obtained from optical intensity of etching chamber. In development EPD controller we concentrate on compensation of this signal intensity and setting the relative signal magnitude at first of etching. We compensate signal intensity using neural network learning method and set the relative signal magnitude using fuzzy inference method. Potential of this method which improves EPD system capability is proved by experiences.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.427-436
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• 2016

In general, QRS duration represent a distance of Q start and S end point. However, since criteria of QRS duration are vague and Q, S point is not detected accurately, arrhythmia classification performance can be reduced. In this paper, we propose extraction of Q, S start and end point RS feature based on phase transition tracking method after we detected R wave that is large peak of electrocardiogram(ECG) signal. For this purpose, we detected R wave, from noise-free ECG signal through the preprocessing method. Also, we classified QRS pattern through differentiation value of ECG signal and extracted Q, S start and end point by tracking direction and count of phase based on R wave. The performance of R wave detection is evaluated by using 48 record of MIT-BIH arrhythmia database. The achieved scores indicate the average detection rate of 99.60%. PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 premature ventricular contraction(PVC). The achieved scores indicate the average detection rate of 94.12% in PVC.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.252-257
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• 2000

This paper describes a look-ahead algorithm of PCNC(personal computer numerical control). The algorithm is based on acceleration/deceleration before interpolation never including a command error and determines a velocity value in end point of each block(or start point of each block). The algorithm is represented as following; 1) calculating two maximum arrival velocity(v1, v2) by a acceleration value, a command velocity and distance in a previous block and a next block, 2) getting a tangent velocity(v3) of the adjacent blocks, 3) choosing a minimum value among these three velocities, and 4) setting the value to a velocity of a start point of the next block(or a end point of the previous block). The proposed look-ahead algorithm was implemented and tested by using a commercial RTOS(real time operation system) on the MS-Windows NT 4.0 in a PC platform. For interfacing to a machine, a counter board, a DAC board and a DIO board were used. The result of the algorithm increased a machining precision and a machining speed in many short blocks.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.71-81
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• 2000

This paper describers a look ahead algorithm of PC-NC(personal computer numerical control). The algorithm is based on acceleration/deceleration before interpolation which doesn\`t include a command error and determines a feedrate value at the end point of each block(or start point of each block). The algorithm is represented as following; 1) calculating two maximum arrival feedrates(F$_1$,F$_2$) by an acceleration value, a command feedrate, and the distance of a NC block, 2) getting a tangent feedrate (F$_3$) of the adjacent blocks, 3) choosing a minimum value among these three feedrates, and 4) setting the value to a feedrate of a start point of the next block(or a end point of the previous block). The proposed look ahead algorithm was implemented and tested by using a commercial TROS(real time operation system) on the MS-Windows NT 4.0 in a PC platform. For interfacing to a machine, a counter board, a DAC board and a DIO board were used. The result of the algorithm increased a machining precision and a machining speed in many short blocks.

• Proceedings of the Acoustical Society of Korea Conference
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• 1992.06a
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• pp.23-28
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• 1992

The purpose of this paper is to develop a new adaptive echo canceller improving convergence speed and near-end-talker detection performance of the conventional echo canceller. In a conventional adaptive echo canceller, an adaptive digital filter with TDL(Tapped-Delay Line) structure modelling the echo path uses the LMS(Least Mean Square) algorithm to cote the coefficients, and NET detector using energy comparison method prevents the adaptive digital filter to update the coefficients during the periods of the NET signal presence. The convergence speed of the LMS algorithm depends on the eigenvalue spread ratio of the reference signal and NET detector using the energy comparison method yields poor detection performance if the magnitude of the NET signal is small. This paper presents a new adaptive echo canceller which uses the pre-whitening filter to improve the convergence speed of the LMS algorithm. The pre-whitening filter is realized by using a low-order lattice predictor. Also, a new NET signal detection algorithm is presented, where the start point of the NET signal is detected by computing the cross-correlation coefficient between the primary input and the ADF(Adaptive Digital Filter) output while the end point is detected by using the energy comparison method. The simulation results show that the convergence speed of the proposed adaptive echo canceller is faster than that of the conventional echo canceller and the cross-correlation coefficient yield more accurate detection of the start point of the NET signal.

• Korean Journal of Applied Biomechanics
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• v.29 no.4
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• pp.219-226
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• 2019

Objective: The purpose of this study is to provide a better understanding of short turn mechanism by describing short turns after kinematic analysis and provide skiers and winter sports instructors with data through which they are able to analyze right postures for turns in skiing in a systematic, rational and scientific manner. Method: For this, a mean difference of kinematic variables (ski-hip angle, ski-shoulder twist angle, pole checking angle, the center of gravity (CG) displacement, trunk forward lean angle) was verified against a total of 12 skiers (skilled and unskilled, 6 persons each), regarding motions from the up-start to down-end points for short turns. Results: There was no difference in a ski-hip twist angle. The ski-shoulder twist angle was large at the up-start point while a pole-checking angle was high at the down-end point in skilled skiers. Concerning the horizontal displacement of CG, skilled skiers were positioned on the right side at the upstart point. No significant difference was observed in the trunk forward lean angle. Conclusion: According to the ski-shoulder twist angle and CG horizontal displacement results, the upper body should be kept leant toward the pole. In addition, big turns should be made via edging and angulation. During pole checking, the hand holding the pole should be thrown and released toward a vector direction of the forearm.