• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4A
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• pp.375-382
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• 2010

This paper presents the extraction of natural frequencies and mode shapes of a cable-stayed bridge using data acquired from GNSS. The response signals of 6 GNSS measuring points installed at the Seohae cable-stayed bridge are used for analysis of dynamic characteristics. Using normalization process and a third order Butterworth filter for the measured signals, the related pass band's signals have been isolated. Then, the acceleration data by double differentiation for these signals are obtained. Total five natural frequencies have been extracted by the fast Fourier transform and compared to the results of different studies. For the acceleration obtained from GNSS signals, the mode shapes of the bridge have been successfully extracted by TDD technique.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.2
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• pp.115-123
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• 2009

In this paper, we extract the parasitic elements of the transmission line with the defected ground structure(DGS) and the short-circuited comb line section using the Short-Open Calibration(SOC). The scattering matrixes of short, open and the distributed elements in microstrip line are measured by full electro-magnetic(EM) simulator and Vector Network Analyser(VNA). The electro-magnetic effects of the proposed structures are considered by the II and T equivalent circuits with frequency independent elements, and the relations between the measured scattering parameters and the elements in the circuits are shown by performing 2 port network analysis. Moreover, to design the 2.4 GHz bandpass filter with second order butterworth prototype, the proposed methods are applied. As results, the measured $S_{11}$ and $S_{21}$ indicate -20 dB and -1.3 dB at center frequency, and these are shown within 5 % error compare to the predicted results at $0.5{\sim}5\;GHz$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4443-4449
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• 2011

ECG consists of various types of electrical signal on the heart, and feature point of these signals can be detected by analyzing the arrhythmia. So far, feature points extraction method for the detection of arrhythmia done in the many studies. However, it is not suitable for portable device using real time operation due to complicated operation. In this paper, R-peak were extracted using R-R interval and QRS width informations on patients. First, noise of low frequency bands eliminated using butterworth filter, and the R-peak was extracted by R-R interval moving average and QRS width moving average. In order to verify, it was experimented to compare the R-peak of data in MIT-BIH arrhythmia database and the R-peak of suggested algorithm. As a results, it showed an excellent detection for feature point of R-peak, even during the process of operation could be efficient way to confirm.