• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.959-966
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• 2010

Quantitative ultrasound analysis provides fundamental information of various ultrasound parameters using spectral information of the short-gated radiofrequency(RF) data. Therefore, accurate extraction of spectral information from backscattered RF signal is crucial for further analysis of medical ultrasound parameters. In this paper, we propose two techniques for calculating a more accurate power spectrum which are based on the phase-compensation using the normalized cross-correlation to minimize estimation errors due to phase variations, and the weighted averaging technique to maximize the signal-to-noise ratio(SNR). The simulation results demonstrate that the proposed method estimates better results with 10% smaller estimation variances compared to the conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.9 no.3
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• pp.11-23
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• 1990

In order to investigate the acoustical characteristics of the Hae-keum (Korean traditional musical instrument) tone quality, the spectrum and wave form of Hae-keum sounds were analyzed by the FFT Analyzer. The analysis was carried out by the varying of the tension of Hae-keum strings, the positions of bridge and the top plate's thickness of Hae-keum respectively. According to the experiment, the following results are obtained ; the over tone's amplitude nearby the top plate resonance frequency is greater than the fundamental tone's amplitude because the top plate resonance frequency is higher than the fundamental tone's frequency. Tone qualities are better when the bridge is situated in the middle of top plate and the tension of strings is larger. The inharmonicity coefficient of the Hae-keum's second string is 0.049 cents/$n^2$. The brilliance and richness is poor, because we seldom found the over tone over 5kHz and the inharmonicity of the Hae-keum is greater than that of a violin. Also we confirmed that we are able to get the best tone quality in 4.5mm thickness of the Hae-keum's top plate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.947-950
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• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Sleep Medicine and Psychophysiology
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• v.19 no.1
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• pp.11-17
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• 2012

Objective: Among various methods developed to quantitatively explore electroencephalograms (EEG), we focused on a wavelet method that was known to yield robust results under nonstationary conditions. The aim of this study was thus to introduce the wavelet method and demonstrate its potential use in clinical sleep studies. Method: This study involved artificial EEG specifically designed to validate the wavelet method. The method was performed to obtain time-dependent spectral power and phase angles of the signal. Synchrony of multichannel EEG was analyzed by an order parameter of the instantaneous phase. The standard methods, such as Fourier transformation and coherence, were also performed and compared with the wavelet method. The method was further validated with clinical EEG and ERP samples available as pilot studies at academic sleep centers. Result: The time-frequency plot and phase synchrony level obtained by the wavelet method clearly showed dynamic changes in the EEG waveforms artificially fabricated. When applied to clinical samples, the method successfully detected changes in spectral power across the sleep onset period and identified differences between the target and background ERP. Conclusion: Our results suggest that the wavelet method could be an alternative and/or complementary tool to the conventional Fourier method in quantifying and identifying EEG and ERP biomarkers robustly, especially when the signals were nonstationary in a short time scale (1-100 seconds).

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.2
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• pp.153-160
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• 2015

The objective of this study is to construct the TPU aerodynamic database with wind tunnel test data of overall wind loads and responses on tall buildings. In this study, wind tunnel tests were conducted to investigate characteristics of wind forces and the effect of wind load combination by cross-correlation analysis among along-wind overturning moment, across-wind overturning moment and torsional moment on a tall building with various side ratios(D/B=0.33, 0.50, 0.77, 0.83, 0.91, 1.0, 1.1, 1.2, 1.3, 2.0 and 3.0) for different terrain roughnesses. The results of wind tunnel tests were compared with those of past literatures. As a result, there was no significant effects of changing of terrain roughnesses on moment coefficients and power spectral densities of across-wind overturning moment coefficients and torsional moment coefficients with various side ratios. Further, these results were good agreement with those of past literatures. From cross-correlation analysis, the across-wind overturning moment coefficients were highly correlated with the torsional moment coefficients. The results of this study will be helpful for practical designers in preliminary design stage.

• Economic and Environmental Geology
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• v.36 no.3
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• pp.213-223
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• 2003

We estimated the Moho depth of Korean Peninsula from gravity anomalies and digital elevation model. The satellite radar altimetry-derived global free-air gravity model was used to ensure the homogeneity in both data and frequency domains of the original data. Two different methods were implemented to calculate the Moho depth; the wavenumber correlation analysis (Kim et al., 2000a) and the power spectrum analysis. The former method calculates depth-to-the-Moho by correlating topographic gravity effect with free-air gravity anomaly in the wavenumber domain under the assumption that the study area is not isostatically compensated. The latter one, on the other hand, considers the different density layers (i.e., Conrad and Moho), using complete Bouguer gravity anomaly in the Frequency domain of the Fourier transform. The correlation coefficient of the two Moho model is 0.53, and methodology and numerical error are mainly responsible for any mismatch between the two models. In order to integrate the two independentely-estimated models, we applied least-squares adjustment using the differenced depth. The resultant model has mean and standard deviation Moho depths of 32.0 km and 2.5 km with (min, max) depths of (20.3, 36.6) kms. Although this result does not include any topographic gravity effect, however, the validity of isostasy and the role of local stress field in the study area should be further studied.

• Economic and Environmental Geology
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• v.40 no.6
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• pp.751-759
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• 2007

To better understand the subsurface geological structure of the Kunsan Basin in the Yellow Sea, the mean depths of the density discontinuous layers (DDLs) of the Kunsan Basin were calculated by power spectrum analysis using satellite altimetry gravity data. The calculated mean depths of DDLs were -1.1km, -3.4km, -9.1km and -31.0km. The mean depth of -1.1km DDL was interpreted as regional unconformity shown in about 1 second in two way travel time (TWTT) in the seismic reflection profiles, and the mean depth of -3.4km DDL was also interpreted as top of the acoustic basement in the seismic reflection profiles. Comparing with well data, seismic reflection profiles and regional geology in the study area, the mean depth of -9.1km DDL was interpreted as top of the igneous origin basement. This means that the acoustic basement of the study area is composed mainly of sediments which are disregarded in previous study. The mean depth of -31.0km DDL was interpreted as the Moho discontinuity because this mean depth is similar to one of the normal continental crust thickness. The detection of top of the igneous origin basement suggests that oil gas potential analysis in Kunsan Basin needs to be extended to the deeper part of sediments (acoustic basement).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2755-2760
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• 2010

The moxibustion therapy of orient medical is well known. Moxibustion method is used to burning moxibustion. The variation factors of the moxibustion stimulation for body can be applied to the electronic moxibustion method. This study is to analyze and examine the electroencephalogram(EEG) variations for moxibustion stimulation. In experiment, we divided six healthy male subjects into two same sized groups : with and without stimuli. The given stimuli are the moxibustion for CV4(Kwan-Won), CV8(Shin-Guel), and CV12(Jung-wan) acupuncture points. We have analyzed the power spectrum for ${\alpha}$, ${\beta}$, ${\delta}$, ${\Theta}$ waves and the average EEG variation level and each channels variation level of EEG. The result was that the moxibustion stimulation decreased the EEG levels of parietal lobe(ch 2, 3, 6, 7) according to the somatosensory system. And the apparent different points are that mild-heat($42{\sim}44^{\circ}C$) stimulation generating ${\alpha}$-wave is increased and ${\beta}$-wave is decreased, also slight-hot($45{\sim}48^{\circ}C$) stimulation made ${\alpha}$-wave decrease and ${\beta}$-wave increase for occipital lobe(ch 4,8) on the simulation group.

• Sleep Medicine and Psychophysiology
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• v.28 no.2
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• pp.78-85
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• 2021

Objectives: When elderly patients show depressive symptoms, discrimination between depressive disorder and prodromal phase of Alzheimer's disease is important. We tested whether a quantitative electroencephalogram (qEEG) marker was associated with cerebral amyloid-β (Aβ) deposition in older adults with depression. Methods: Non-demented older individuals (≥ 55years) diagnosed with depression were included in the analyses (n = 63; 76.2% female; mean age ± standard deviation 73.7 ± 6.87 years). The participants were divided into Aβ+ (n = 32) and Aβ- (n = 31) groups based on amyloid PET assessment. EEG was recorded during the 7min eye-closed (EC) phase and 3min eye-open (EO) phase, and all EEG data were analyzed using Fourier transform spectral analysis. We tested interaction effects among Aβ positivity, condition (EC vs. EO), laterality (left, midline, or right), and polarity (frontal, central, or posterior) for EEG alpha band power. Then, the EC-to-EO alpha reactivity index (ARI) was examined as a neurophysiological marker for predicting Aβ+ in depressed older adults. Results: The mean power spectral density of the alpha band in EO phase showed a significant difference between the Aβ+ and Aβ- groups (F = 6.258, p = 0.015). A significant 3-way interaction was observed among Aβ positivity, condition, and laterality on alpha-band power after adjusting for age, sex, educational years, global cognitive function, medication use, and white matter hyperintensities on MRI (F = 3.720, p = 0.030). However, post-hoc analyses showed no significant difference in ARI according to Aβ status in any regions of interest. Conclusion: Among older adults with depression, increased power in EO phase alpha band was associated with Aβ positivity. However, EC-to-EO ARI was not confirmed as a predictor for Aβ+ in depressed older individuals. Future studies with larger samples are needed to confirm our results.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.52-60
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• 2003

Objectives: Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or relative power of theta waves more than 23% was regarded as stage 1 sleep. SEM(slow eye movement) was defined as the duration of both-eye movement ranging from 1.5 to 4 seconds, and was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3% and Cohen’s Kappa was 0.586 (p<0.01). A significant portion (32%) of automatically detected stage 1 sleep included SEM. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.