• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.44-50
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• 2002

The fast Fourier transform (FFT) is a good method to estimate spectral density, but the frequency resolution is limited to the sampling window, and thus the precise characteristics of the spectral density for short signals are not clear. To solve the limitation, a multiple band-pass filter was introduced to estimate the precise time course of the spectral density for flash visual evoked potentials (VEPs). Signals were recorded during -200 and 600 ms using balanced noncephalic electrodes, and sampled at 1 K Hz in 12 bits. With 1 Hz and 10 ms resolutions, spectral density was estimated between 10 and 100 Hz. Background powers at the alpha-and beta-bands were high over the posterior scalp, and powers around 200ms were evoked at the same bands over the same region, corresponding to P110 and N165 of VEPs. normalized's spectral density showed evoked powers around 200 ms and suppressed powers following the evoked powers over the posterior scalp. The evoked powers above the 20Hz band were not statistically significant. However, the gamma band was significantly evoked intra-individually; details in the gamma bands were varied among the subjects. Details of spectral density were complicated even for a simple task such as watching flashes; both synchronization and desynchronization occurred with different distributions and different time courses.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.241-242
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• 2009

• Journal of Ocean Engineering and Technology
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• v.20 no.5 s.72
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• pp.36-41
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• 2006

The main object of this study is to develop an accurate and convenient method for the response analysis of offshore structures in real sea states. A numerical procedure is described for predicting the motion responses and tension variations of the ISSC TLP in multi-directional irregular waves. The developed numerical approach in the frequency domain is based on acombination of the three dimensional source distribution method, the dynamic response analysis method, and the spectral analysis method. Frequency domain analysis in the multi-directional irregular waves is expanded to a time domain analysis by using a convolution integral after obtaining the impulse response by Fourier transformation. The results of the comparison between responses in the frequency and time domain confirmed the validity of the proposed approach.

• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.405-416
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• 2015

This paper developed a method analyze drivers' response characteristics using spectral analysis with car following data. Cross-correlation function and cross spectrum are produced by Fourier transform from speed fluctuations of leading vehicle and following vehicle during the designated time ${\tau}$. Based on the analysis data, a process to calculate the reaction time and stimulus-adaption index of following vehicle was developed and 170 cases of field data was applied. It was reported average of 0.654 and 2.091 seconds of stimulus-adaption index and reaction time respectively. In conclusion, the developed indexes might contribute to enhance vehicle control of autonomous vehicle more efficient and safer.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.83-91
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• 1997

A reactor vibration monitoring has been performed using neutron noise obtained from excore detectors for the safety operation, Traditionally, the spectral estimator based on Fourier analysis has been widely used in the noise analysis of the reactor system. If the bias is too severe, the resolution would not be adequate for a given application. One major motivation for the current interests in the parametric approach to spectral estimation is the apparent higher resolution achievable with these modern techniques. In considering an unbias, a consistency, an efficency, and a minimum lower bound of the statictic estimation, an AR model is appropriate for noise spectral estimation with sharp peaks but not deep valley. In order to select an appropriate model order, the lag value of autocorrleaton function is applied. Burg method to trace the vibration mode of RPV internal is the most sucuessful.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1628-1628
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• 2001

Near infrared (NIR) spectroscopy is a powerful technique for non-destructive analysis that can be obtained in a wide range of environments. Recently, NIR measurements have been utilized as probe for quantitative analysis in agricultural, industrial, and medical sciences. In addition, it is also possible to make practical application on NIR for molecular structural analysis. In this work, Fourier transform near infrared (FT-NIR) measurements were carried out to utilize extensively in the relative amounts of different secondary structures were employed, such as Iysozyme, concanavalin A, silk fibroin and so on. Several broad NIR bands due to the protein absorption were observed between 4000 and $5000\;^{-1}$. In order to obtain more structural information from these featureless bands, second derivative and Fourier-self-deconvolution procedures were performed. Significant band separation was observed near the feature at $4610\;^{-1}$ ,. Particularly the peak intensity at $4525\;^{-1}$ shows a characteristic change with thermal denaturation of fibroin. The structural information can be also obtained by mid-IR and CD spectral. Correlation of NIR spectra with protein structure is discussed.

• Journal of IKEEE
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• v.23 no.3
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• pp.805-810
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• 2019

We present a time-frequency analysis algorithm based on the multitaper method and the state-space frameworks. In general, time-frequency representations have a trade-off between the time duration and the spectral bandwidth by the uncertainty principle. To optimize the trade-off problems, the short-time Fourier transform and wavelet based algorithms have been developed. Alternatively, the authors proposed the state-space frameworks based on the multitaper method in the previous work. In this paper, we develop a real-time algorithm to estimate variances and spectrum using the state-space framework. We test our algorithm in spectral analysis of simulated data.

• Journal of Plant Biotechnology
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• v.43 no.3
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• pp.383-390
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• 2016

To determine whether FT-IR spectral analysis based on multivariate analysis could be used to discriminate Chinese cabbage breeding line at metabolic level, whole cell extracts of nine different breeding lines (three paternal, three maternal and three $F_1$ lines) were subjected to Fourier transform infrared spectroscopy (FT-IR). FT-IR spectral data of Chinese cabbage plants were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA). The hierarchical dendrograms based on PLS-DA from two of three cross combinations showed that paternal, maternal, and their progeny $F_1$ lines samples were perfectly separated into three branches in breeding line dependent manner. However, a cross combination failed to fully discriminate them into three branches. Thus, hierarchical dendrograms based on PLS-DA of FT-IR spectral data of Chinese cabbage breeding lines could be used to represent the most probable chemotaxonomical relationship among maternal, paternal, and $F_1$ plants. Furthermore, these metabolic discrimination systems could be applied for rapid selection and classification of useful Chinese cabbage cultivars.

• Korean Journal of Optics and Photonics
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• v.23 no.6
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• pp.246-250
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• 2012

We derive analytical expressions for the output spectral density and the noise power $P_{\beta}$ in noise loading analysis using Volterra kernels to characterize fiber nonlinearities. The bandwidth of the input noise source has little effect on $P_{\beta}$, but the power of the input noise source and the dispersion parameter value of the fiber have a significant effect on $P_{\beta}$. The Volterra method predicts ${\Delta}P_{\beta}[dB]$ = 30 dB/decade, which agrees very accurately over a wide range of fiber parameters compared with the numerical results by the split-step Fourier method. Therefore the Volterra method could be useful to predict the performance of a dense WDM system when we plan to upgrade fiber or increase signal power.

• Speech Sciences
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• v.7 no.1
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• pp.17-29
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• 2000

The STC(Sinusoidal Transform Coding) is a vocoding technique that uses a sinusoidal speech model to obtain high- quality speech at low data rate. It models and synthesizes the speech signal with fundamental frequency and its harmonic elements in frequency domain. To reduce the data rate, it is necessary to represent the sinusoidal amplitudes and phases with as small number of peaks as possible while maintaining the speech quality. As a basic research to develop a low-rate speech coding algorithm using the sinusoidal model, in this paper, we investigate the speech quality depending on the number of sinusoids. By varying the number of spectral peaks from 5 to 40 speech signals are reconstructed, and then their qualities are evaluated using spectral envelope distortion measure and MOS(Mean Opinion Score). Two approaches are used to obtain the spectral peaks: one is a conventional STFT (Short-Time Fourier Transform), and the other is a multiresolutional analysis method.