• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.287-292
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• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself, Through this process, we confirmed advantages/disadvantages of four algorithms and identified application methods of few algorithms.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.280-285
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• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself. Through this process, we comfirmed advantages/disadvantages of four algorithms and identified application methods of four algorithms.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.265-268
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• 2001

In content-based video data retrieval, the representative-frame is usually used. To do that, the skill of detection for scene change is needed. Generally the color histogram comparison is used, but sensitive to light variation and tends to miss the scene change of similar color histogram. This paper shows how to use both color histogram comparison and entropy to prevent the false-positive of scene change occurred by light variation. At the experiments, il is more powerful to light variation to use both color histogram comparison entropy than to use only color histogram comparison.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1238-1246
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• 1992

We developed a time comparison system using the ranging signal of the geostationary meteorological satellite(GMS). By using the system time comparison between the KRISS(Korea Research Institute of Standards and Science) cesium atomic clock and the GMS ranging signal has been carried out and the results have shown that the precision of time comparison at KRISS is about 10 ns. For the more accurate measurements we calibrated the receiver delay time between KRISS receiver and CRL(Communications Research Laboratory) receiver by using the portable GMS receiver.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2126-2130
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• 2003

In the integrated systems, that is integrated digital TV(DTV) internet and home automation, like home server, is needed integration of digital TV video signal and computer graphic signal. The graphic signal is operating at the high speed and has time-divide-stream. So the re-request of data is not easy at the time of error detection. therefore EDAC algorithm is efficient. In this paper, we show a scheme, that is integration of graphic and dtv format signal for DTV monitor display. This paper also presents the efficiency error detection auto correction(EDAC) for conversion of graphics signal to DTV video signal. A presented EDAC algorithms use the modified hamming code for enhancing video quality and reliability. A EDAC algorithm of this paper can detect single error, double error, triple error and more error for preventing from incorrect correction. And it is not necessary an additional memory. In this paper The comparison between digital TV video signal and graphic signal, a EDAC algorithm and a design of conversion graphic signal to DTV signal with EDAC function in DTV system is described.

• Journal of Magnetics
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• v.21 no.1
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• pp.115-124
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• 2016

The present study analyzes T1 TSE and T1 slice sel. IR (dark_fluid) signal strength according to the degree of gadolinium contrast agent dilution and analyzes the turbo factors with regard to changes in the maximum and overall signal strength to study correlations between changes and signal-to-noise ratios (SNRs) and compare peak-to-peak SNR (PSNR) enhancement in order to improve the quality of T1-weighted images. Enhancement TR (600 msec) evaluated to determine the T1 TSE turbo factor and obtain the maximum signal strength, T1WI were used sequentially to experiment with turbo factors_1-4. T1 slice sel. IR (dark-fluid) was used to sequentially test turbo factors_2-5 but not turbo factor_1 at a TR (1500 msec) and compare data at an increase in T1 of 900 msec. The T1 TSE was reduced according to the contrast agent concentration. Phantom signal strength increased, whereas turbo factors_1-4 exhibited maximum signal strength at a concentration of 3 mmol, followed by a gradual decrease. In the turbo factors_2-5, the signal strength increased sharply to maximum signal strength at 0.7 mmol, followed by a reduction. T1 TSE had a greater maximum signal strength than did T1 slice sel. IR (dark_fluid). A comparison of SNR found that T1 TSE imaging was superior (33.3 dB) in turbo factor_1 and T1 slice sel. IR (dark_fluid) was highest (33.9 dB) at turbo factor_5. A PSNR comparison analysis was not sufficient to distinguish between the images obtained with both techniques at 30 dB or higher under all experimental conditions.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.106-109
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• 2002

In the integrated systems, that is integrated digital TV(DTV) internet and home automation, like home server, is needed integration of digital TV video signal and computer graphic signal. The graphic signal is operating at the high speed and has time-divide-stream. So the re-request of data is not easy at the time of error detection. therefore EDAC algorithm is efficient. This paper presents the efficiency error detection auto correction(EDAC) for conversion of graphics signal to DTV video signal. A presented EDAC algorithms use the modified Hamming code for enhancing video quality and reliability. A EDAC algorithm of this paper can detect single error, double error, triple error and more error for preventing from incorrect correction. And it is not necessary an additional memory. In this paper The comparison between digital TV video signal and graphic signal, a EBAC algorithm and a design of conversion graphic signal to DTV signal with EDAC function is described.

• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.107-113
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• 2011

LSPR(Localized Surface Plasmon Resonance) sensor measures the refractive index change on the sensor surface. The detection of biological reaction with the unknown refractive index needs to be converted into the signal sensitivity for the refractive index change for comparison with other measurements. To find the signal sensitivity, the three steps of signal processing are proposed, which are signal modeling, signal calibration and signal normalization of LSPR sensor. The detected signal of biotin-streptavidin interaction has been converted into unit of [RU](Resonance Unit) using the proposed method. The converted signal directly can be compared with the other sensors including commercialized one.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.705-708
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• 2003

In this paper, we have evaluated the methods to generate the reference signal for the diagnosis of multi-channel signals. The channel signal integrity can be known by the difference between the reference signal and each channel value. The generation method of reference signal is important in the diagnosis of multi-channel measurement system. The continuous weighting average method rejects the abnormal signal using weighting method and makes the reference signal using sumation of all channel values. This gives the simple and reasonable reference signal. The principle component analysis, one of the multivariate analysis methods, and the neural network method give the reliable reference signal by using signal models, and learning algorithm. Two methods can make the reliable reference if all signals are normal, but any signal having the drift have an effect on the reference.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.306-308
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• 2005

The vehicle detection method using pulse radar has the advantage of maintenance in comparison with loop detection method. We have the information about the vehicle being and position by dividing the signals into sectors in accordance with SSC method, and by applying the discriminant function based on stochastical data. We also reduce the signal processing time.