• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.51-58
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• 2008

This paper is a study of a prevention of power folding controller's thermal degradation. Power folding technology has been applied for many fields such as side rear vision mirror of vehicles, windshield wiper, antenna, power window. These controllers have been comprised with traditional DC moors, Switching electronic devices, and relays. But this methods have a limitation to overcome such problems of product reliability, endurance, noise margins. Therefore on this paper, to detect the movement of motor, sensing motor brush noise on a load sensing part has been used and controlling a precise RC timing control minimizes the thermal deterioration of motor. And using MOS FETs as a electronic switching device increases life-time and liability of control circuit. After testing such circuit and control method, repetition of operating time, cut-off time, wide operation voltage, power noise margin ware increased over eleven-fold.

• Journal of Korea Multimedia Society
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• v.12 no.3
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• pp.451-459
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• 2009

This paper presents an approach to detect premature ventricular contraction(PVC) using discrete wavelet transform and fuzzy neural network. As the input of the algorithm, we use 14 coefficients of d3, d4, and d5, which are transformed by a discrete wavelet transform(DWT). This paper uses a neural network with weighted fuzzy membership functions(NEWFM) to diagnose PVC. The NEWFM discussed in this paper classifies a normal beat and a PVC beat. The size of the window of DWT is $-31/360{\sim}+32/360$ second(64 samples) whose center is the R wave. Using the seven records of the MIT-BIH arrhythmia database used in Shyu's paper, the classification performance of the proposed algorithm is 99.91%, which outperforms the 97.04% of Shyu's analysis. Using the forty records of the M1T-BIH arrhythmia database used in Inan's paper, the classification performance of the proposed algorithm is 98.01%, which outperforms 96.85% of Inan's one. The SE and SP of the proposed algorithm are 84.67% and 99.39%, which outperforms the 82.57% and 98.33%, respectively, of Inan's study.

• Biomolecules & Therapeutics
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• v.15 no.3
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• pp.169-174
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• 2007

In the present study, we investigated the neuroprotective effects of standardized Ginkgo biloba extract (GBB) (total terpene trilactones, 13 ${\pm}$ 3%; biflavone, 4.5 ${\pm}$ 1.5%; flavonol glycoside, < 8%; proanthocyanidine, under detection limit) on ischemia-reperfusion-induced brain injury in the rats. Ischemia was induced by the intraluminal occlusion of the right middle cerebral artery for 2 h and reperfusion was continued for 22 h. GBB was orally administered, promptly prior to reperfusion and 2 h after. Total infarction volume in the ipsilateral hemispheres of ischemia-reperfusion rats were significantly reduced by treatment with GBB in a dose-dependent manner (P<0.05). The therapeutic time window of GBB was 3 h in this ischemia-reperfusion rat model. Furthermore, GBB also significantly inhibited increased neutrophil infiltration of ischemic brain tissue, as estimated by myeloperoxidase activity. These findings suggest that GBB plays a crucial protective role in ischemia-induced brain injury, in part, via inhibition of neutrophil infiltration, and suggest that this GBB could serve as a neuroprotective agent following transient focal ischemic brain injury.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.3 s.21
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• pp.41-51
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• 2002

Recently, many studies extracting the geography information using digital aerial image have been implemented. But it is very difficult that automatically recognizing objects using edge detection method on the aerial image, and so that work have practiced manually or semi-automatically. Therefore, in this study, we have removed impedimental elements for recognition using the image which overlapped the significant information bands of brightness-sliced aerial images, then have developed the algorithm which can automatically recognize and extract road information and we will try to apply that method when we develope a system. For this, first of all, we have developed the 'template conformal-transformation moving operator' for automatically recognizing crosswalk area from crosswalk band image and the 'window normal search algorithm' which is able to track road area based on long-side length of crosswalk, so that we have proposed the method that can extract directly the road information from the aerial image.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.5 s.311
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• pp.48-56
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• 2006

In this paper, we proposed the high quality audio watermarking algorithm using MDCT/IMDCT (Modified DCT/Inverse Modified DCT) with psychoacoustic model. Generally, a digital audio watermark is embedding the frequency domain after frequency transform of the digital audio data but the digital audio quality is affected by watermarking. In our scheme, the digital audio data is spread with PN((Pseudo Noise) code and then audio watermark is embedded in MDCT processing that refers psychoacoustic model. In MDCT processing, according to the shape of filter bank output, the block switching selects a window sequence that has 256, 1,024 or 2,048 points interval for high quality audio. The author confirm that when watermark weight ${\alpha}$ is 2.5 below, the detection ratio of watermark is a satisfied to SDMI's(Secure Digital Music Initiative) recommendation 50% above and SM is $50{\sim}68dB$ range with mainly 4 kind of attacks(Compression, Cropping, FFT and Echo).

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.275-280
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• 2013

In this paper, a new stereo object extraction algorithm using a block-based MSE (mean square error) algorithm and the configuration parameters of a stereo camera is proposed. That is, by applying the SSD algorithm between the initial reference image and the next stereo input image, location coordinates of a target object in the right and left images are acquired and then with these values, the pan/tilt system is controlled. And using the moving angle of this pan/tilt system and the configulation parameters of the stereo camera system, the mask window size of a target object is adaptively determined. The newly segmented target image is used as a reference image in the next stage and it is automatically updated in the course of target tracking basing on the same procedure. Meanwhile, a target object is under tracking through continuously controlling the convergence and FOV by using the sequentiall extracted location coordinates of a moving target.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.10 s.89
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• pp.952-960
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• 2004

PSK(Phase Shift Keying) is useful because of the power and spectral efficient modulation. In this paper, no additional hardware will be needed to support various transmit mode in the suggested DSP scheme. We design and implement the synchronization algorithm for M-ary PSK(M=2, 4) demodulator based on DSP scheme, instead of complex analog PSK demodulator. TMS320C6203 is used as DSP. We check the all kinds of waveforms via the graph view window after software programming the emulation on the DSP tool. The result of implementation proves that demodulator using the suggested algorithm has equal performance with demodulator using analog circuits.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.359-364
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• 2006

Interference can seriously degrade the performance of GPS receiver because GPS signal has extremely low power at earth surface. This paper presents a Narrowband Interference Excision Filter (NIEF) in frequency domain that removes narrowband interferences with small signal loss. A NIEF transforms the received GPS signals with interferences into the frequency domain with FFT and then compute statistics such as mean and standard deviation to determine an excision threshold. All spectrums exceeding the threshold are removed and the remaining spectrums are restored by IFFT. A NIEF effectively can remove various and strong interferences with a simple structure. However, the signal power loss is unavoidable during FFT and IFFT. Besides the hamming window and overlap technique, a threshold-whitening technique and an adaptive detection threshold are adopted to effectively reduce the signal power loss. The performance of implemented NIEF is evaluated using real signals obtained by 12 bit GPS signal acquisition board. The output of NIEF is fed into the Software Defined Receiver to evaluate the acquisition and tracking performance. Experimental results shows that many types of interference such as single-tone CWI, AM, FM, swept CWI and multi-tones CWI are effectively mitigated with small signal power loss.

• Smart Structures and Systems
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• v.25 no.3
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• pp.285-299
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• 2020

Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1222-1230
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• 2022

As the number of signal sources with low detectability by using various modulation techniques increases, research to classify signal modulation methods is steadily progressing. Recently, a Convolutional Neural Network (CNN) deep learning technique using FFT as a preprocessing process has been proposed to improve the performance of received signal classification in signal interference or noise environments. However, due to the characteristics of the FFT in which the window is fixed, it is not possible to accurately classify the change over time of the detection signal. Therefore, in this paper, we propose a CNN model that has high resolution in the time domain and frequency domain and uses wavelet transform as a preprocessing process that can express various types of signals simultaneously in time and frequency domains. It has been demonstrated that the proposed wavelet transform method through simulation shows superior performance regardless of the SNR change in terms of accuracy and learning speed compared to the FFT transform method, and shows a greater difference, especially when the SNR is low.