• Ecology and Resilient Infrastructure
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• v.8 no.3
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• pp.143-153
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• 2021

The growth inhibition effects of M. aeruginosa were verified using large volume (7.2 L) of algae samples and ultrasonication (high frequency of 1.6 MHz vs. low frequency of 23 kHz) in lab-scale experiment. The chlorophyll-a (chl-a) and cell number decreased gradually after 6 hr sonication with high frequency of 1.6 MHz whereas both decreased sharply after 6 hr sonication with low frequency of 23 kHz. Additionally, the first order degradation coefficient (k) values after sonication were greater than those during sonication. These results indicate that relatively low sonication energy per volume may affect the cell membrane and internal organs of M. aeruginosa in a slow and retarded manner and resulted in gradual decrease of cell numbers of M. aeruginosa. Based on the comparison of chl-a and cell number of M. aeruginosa after sonication, low frequency of 23 kHz is superior for growth inhibition of M. aeruginosa, since low frequency of 23 kHz easily penetrates the cell membrane and ruptures the internal organs including gas vesicles. As is evident in SEM and TEM images, ruptured cell membranes were clearly observed for low frequency of 23 kHz. Finally, the microcystin-LR in water is not detected and considered to be harmless in aquaculture systems.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.326-334
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• 2022

In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

• The Journal of the Acoustical Society of Korea
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• v.32 no.1
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• pp.14-21
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• 2013

The erosion, suspension, and transport of sediment frequently occur in the coastal waters and estuarine. These processes often generate the so-called fluid mud layer, which is defined as a high-concentration aqueous suspension of fine grained sediment (> 10 g/l), consisting mainly of silt and clay-size particles. Therefore the high-resolution ultrasound is mostly used to detect or monitor the fluid mud layer. Because the sound attenuation tends to increase rapidly with the suspended sediment concentration, it is necessary to consider the accurate attenuation correction to estimate the backscattering strengths from the suspended sediment layers. In this paper, the volume backscattering strengths with various suspended sediment concentrations were measured using 5-MHz ultrasound signal in a small-scale water tank. The sound attenuation due to the viscosity and scattering from suspended sediment particles was predicted by the Richard's model and applied to the sonar equation to estimate the volume backscattering strengths from the suspended sediment concentrations. For the case that the additional attenuation was not considered, the volume backscattering strengths increased to the concentration of 20 g/l, and over this point, the backscattering strengths were roughly constant. However, for the case that the attenuation due to the suspended sediment concentration was considered, the backscattering strengths increased with the concentration.

• Progress in Medical Physics
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• v.21 no.3
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• pp.239-245
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• 2010

The purpose of this study is to comprehensively compare and evaluate the characteristics of image quality for digital mammography systems which use a direct and indirect conversion detector. Three key metrics of image quality were evaluated for the direct and indirect conversion detector, the modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), which describe the resolution, noise, and signal to noise performance, respectively. DQE was calculated by using a edge phantom for MTF determination according to IEC 62220-1-2 regulation. The contrast to noise ratio (CNR) was evaluated according to guidelines offered by the Korean Institute for Accreditation of Medical Image (KIAMI). As a result, the higher MTF and DQE was measured with direct conversion detector compared to indirect conversion detector all over spatial frequency. When the average glandular dose (AGD) was the same, direct conversion detector showed higher CNR value. The direct conversion detector which has higher DQE value all over spatial frequency would provide the potential benefits for both improved image quality and lower patient dose in digital mammography system.

• Journal of the Korean Vacuum Society
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• v.15 no.4
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• pp.331-337
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• 2006

Cavity-type beam position monitors were developed in collaboration with KEK to use for the future accelerators such as international linear collider (ILC) or x-ray free electron laser (XFEL) in PAL. BPM components such as BPM cavity, beam tubes, waveguides and feedthroughs were assembled by brazing at the same time to reduce mechanical errors during the fabrication. There are four screwed pins around outer rim of the cavity for the tuning of cavity frequency and x-y isolation. The resonance frequency of BPM is 6.422 GHz, the inner diameter of cavity is 53.822 mm, and the range of mechanical adjusting is $+ / - 250{\mu}m$. The x-y isolation was measured better than -40 dB after tuned. Test results of signal forms, x-y isolations, sensitivities are satisfied within requirements for the KEK ATF2 beam line.

• 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).

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.68-77
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• 2008

We have developed an inversion algorithm for loop-loop electromagnetic (EM) data, based on the localised non-linear or extended Born approximation to the solution of the 2.5D integral equation describing an EM scattering problem. Source and receiver configuration may be horizontal co-planar (HCP) or vertical co-planar (VCP). Both multi-frequency and multi-separation data can be incorporated. Our inversion code runs on a PC platform without heavy computational load. For the sake of stable and high-resolution performance of the inversion, we implemented an algorithm determining an optimum spatially varying Lagrangian multiplier as a function of sensitivity distribution, through parameter resolution matrix and Backus-Gilbert spread function analysis. Considering that the different source-receiver orientation characteristics cause inconsistent sensitivities to the resistivity structure in simultaneous inversion of HCP and VCP data, which affects the stability and resolution of the inversion result, we adapted a weighting scheme based on the variances of misfits between the measured and calculated datasets. The accuracy of the modelling code that we have developed has been proven over the frequency, conductivity, and geometric ranges typically used in a loop-loop EM system through comparison with 2.5D finite-element modelling results. We first applied the inversion to synthetic data, from a model with resistive as well as conductive inhomogeneities embedded in a homogeneous half-space, to validate its performance. Applying the inversion to field data and comparing the result with that of dc resistivity data, we conclude that the newly developed algorithm provides a reasonable image of the subsurface.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.

• Journal of Sensor Science and Technology
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• v.10 no.4
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• pp.250-258
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• 2001

In this study, a lightning warning system (LWS) which can predict a lightning return stroke is developed, and the LWS is based on the measurement of electric field intensity at the ground level. The LWS consist of a rotation-type field mill as an electric field sensor, an impedance changer, a two-stage amplifier, and a microprocessor unit. From the calibration experiment, the frequency bandwidth and the maximum resolution of the LWS are $DC{\sim}200\;[Hz]$ and 73 [V/m], respectively. Also, the LWS can measure the electric field strength caused by a thunderstorm up to 18.7 [kV/m] at the ground. To ensure the sensing ability of the developed LWS in an actual situation, computer simulation using thundercloud models was carried out, and the result showed that the LWS can monitor the movement of thunderclouds within 6 [km] from the observation site.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.1957-1964
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• 1994

In this thesis, a Synthetic Aperture Rarar Processor that is possible real-time handling is implemented using CW(Continuose Wave) laser as a light source, CCD(charge Coupled Device) as a time integrator, and AOD(Acousto-Optic Device) as the space integrator. One of the advantages of the proposed system is that it does not require driving circuits of the light source. To implement the system, the linear frequency modulation(chirp) technique has been used for radar signal. The received data for the unit target was processed using 7.80 board and accompanying electronic circuits. In order to reduce the smear effect of the focused chirp signal which occurs Bragg diffrection angle of the AOD has been utilized to make sharp pulses of the laser source, and the pulse made synchronized with the chirp signal. Experiment and analysis results of the data and images detected from CCD of the proposed SAR system demonstrated that detection effect is degrated as the unit target distance increases, and the resolving power is improved as the bandwidth of the chirp signal increases. Also, as the pulse width of the light source decreases, the smear effect has been reduced. The experimental results assured that the proposed system in this papre can be used as a real time SAR processor.