• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.10
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• pp.1184-1193
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• 2010

The upper frequency of international EMC regulations is being expanded above 1 GHz. Radiated emissions above 1 GHz are different from those below 1 GHz that is existing upper regulation frequency, and which have lower field strength and sharper and tilted beam-width, relatively. In this paper, an effective evaluation method to be used above 1 GHz is studied using an offset parabola antenna system having a double-ridged horn antenna as a feed. First, simple model is proposed for calculating antenna factor and field uniformity of the parabola antenna system, and then real radiated emission and radiated susceptibility measurements are performed using a constant noise emitter and the suggested antenna system. The results show that the proposed antenna system has higher gain and power efficiency, and wider field uniformity relative to a conventional double-ridged horn antenna. Therefore, it is confirmed that the proposed system can be effectively used for EMC measurements above 1 GHz.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.1-8
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• 2023

If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

• Journal of Radiation Protection and Research
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• v.35 no.2
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• pp.69-76
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• 2010

Prototype double-scattering Compton camera, which consists of three gamma-ray detectors, that is, two double-sided silicon strip detectors (DSSDs) as scatterer detectors and a NaI(Tl) scintillation detector as an absorber detector, could provide high imaging resolution with a compact system. In the present study, the energy resolution and the timing resolution of component detectors were measured, and the parameters affecting the energy resolution of the DSSD were examined in terms of equivalent noise charge (ENC). The energy resolutions of the DSSD-1 and DSSD-2 were, in average, $25.2keV{\pm}0.8keV$ FWHM and $31.8keV{\pm}4.6keV$ FWHM at the 59.5 keV peak of $^{241}Am$, respectively. The timing resolutions of the DSSD and NaI(Tl) scintillation detector were 57.25 ns FWHM and 7.98 ns FWHM, respectively. In addition, the Compton image was obtained for a point-like $^{137}Cs$ gamma source with double-scattering Compton camera. From the present experiment, the imaging resolution of 8.4 mm FWHM (angular resolution of $8.1^{\circ}$ FWHM), and the imaging sensitivity of $1.5{\times}10^{-7}$ (intrinsic efficiency of $1.9{\times}10^{-6}$) were obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.633-639
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• 2018

High-resolution images using remote sensing (RS) is importance to secure for spatial classification depending on the characteristics of the complex and various factors that make up the river environment. The purpose of this study is to evaluate the accuracy of the classification results and to suggest the possibility of applying the high resolution hyperspectral images obtained by using the drone to perform spatial classification. Hyperspectral images obtained from study area were reduced the dimensionality with PCA and MNF transformation to remove effects of noise. Spatial classification was performed by supervised classifications such as MLC(Maximum Likelihood Classification), SVM(Support Vector Machine) and SAM(Spectral Angle Mapping). In overall, the highest classification accuracy was showed when the MLC supervised classification was used by MNF transformed image. However, it was confirmed that the misclassification was mainly found in the boundary of some classes including water body and the shadowing area. The results of this study can be used as basic data for remote sensing using drone and hyperspectral sensor, and it is expected that it can be applied to a wider range of river environments through the development of additional algorithms.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.77-83
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• 2015

Leaf water content is one of important indicators that shows states of vegetation. It is important to monitor vegetation water content using remote sensing for forest management. In this study, we investigated the degree of water stress in Korean peninsula with Normalized Difference Water Index (NDWI) to study the water content of vegetation canopy. We calculated the NDWI using SPOT/VEGETATION S10 channel data over forest from 1999 to 2013. We calculated Simple Moving Average (SMA) to remove temporal noises of NDWI in time series, and used standardized anomaly to investigate temporal changes. We classified the NDWI anomalies into three scales (low, moderate, and high) in order to monitor intuitively. We also investigated suitability of the NDWI as an evaluation criterion about water stress of vegetation canopy by comparing and verifying forest fires damaged area over 150 ha. Consequently, huge forest fire occurred 24 times during the study period. Also, negative anomalies appeared in every forest fire location and their neighboring areas. In particular, we found huge forest fires where NDWI anomalies were in 'high' scale.

• Journal of the Korean GEO-environmental Society
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• v.15 no.5
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• pp.31-37
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• 2014

In situ investigations and laboratory tests using elastic wave have become popular in geotechnical and geoenvironmental engineering. Propagation velocity of elastic wave is the key index to evaluate the ground characteristics. To evaluate this, various methods were used in both time domain and frequency domain. In time domain, the travel time can be found from the two points that have the same phase such as peaks or first rises. Cross-correlation can also be used in time domain by evaluating the time shift amount that makes the product of signals of input and received waveforms maximum. In frequency domain, wave propagation velocity can be evaluated by computing the phase differences between the source and received waves. In this study, wave propagation velocity evaluated by the methods listed above were compared. Bender element tests were conducted on the specimens cut from the undisturbed hand-cut block samples obtained from Block 37 excavation site in Chicago, IL, US. The evaluation methods in time domain provides relatively wide range of wave propagation velocities due to the noise in signals and the sampling frequency of data logger. Frequency domain approach provides relatively accurate wave propagation velocities and is irrelevant to the sampling frequency of data logger.

• The Journal of Korean Institute of Information Technology
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• v.15 no.12
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• pp.157-164
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• 2017

Mobile ECG signal measurement is a technique to measure small signals of several mV, and many studies have been conducted to remove noise including wandering scheme. Removal of the equipotential line noise caused by shaking or movement of the electrode cable is one of the core research contents for the electrocardiogram measurement. In this study, we proposed a modified step-size of combined NLMS(normalized least squares) and DLMS(delayed least squares) adaptive filter to eliminate baseline noise from ECG signals. The proposed method mainly adjusts initial filter step-size to reduce distortion of original ECG signals characteristic after eliminating baseline noise. The modified filter step-size is scaled by filter order size and distortion minimization factor. This method is suitable for portable ECG device with a small processor and less power consumption. This technique also decreases computation time which is essential for real-time filtering. The proposed filter also increase the signal to noise ratio (SNR) compared to conventional NLMS filter.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4A
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• pp.507-515
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• 2008

In this study, a method predicting the displacement response of structures from the measured dynamic strain signal is proposed by using mode decomposition technique. Evaluation of bridge stability is normally focused on the bridge completed. However, dynamic loadings including wind and seismic loadings could be exerted to the bridge under construction. In order to examine the bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. Because it may be not easy for the displacement response to be acquired directly on site, an indirect method to predict the displacement response is needed. Thus, as an alternative for predicting the displacement response indirectly, the conversion of the measured strain signal into the displacement response is suggested, while the measured strain signal can be obtained using fiber optic Bragg-grating (FBG) sensors. As previous studies on the prediction of displacement response by using the FBG sensors, the static displacement has been mainly predicted. For predicting the dynamic displacement, it has been known that the measured strain signal includes higher modes and then the predicted dynamic displacement can be inherently contaminated by broad-band noises. To overcome such problem, a mode decomposition technique was used. Mode decomposition technique estimates the displacement response of each mode with mode shape estimated to use POD from strain signal and with the measured strain signal decomposed into mode by EMD. This is a method estimating the total displacement response combined with the each displacement response about the major mode of the structure. In order to examine the mode decomposition technique suggested in this study model experiment was performed.