• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.04b
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• pp.168-171
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• 2000

Underwater acoustic communications have made considerable advances in the past decade. The purpose of this paper is to achieve the underwater communication by ultrasonic sensors and to investigate conditions of good underwater acoustic communicators. As a result of this experiments, the ultrasonic sensors, MA40E7R/S, made by Nicera can be used as ultrasonic transducers for underwater communication using AM(Amplitude Modulation) signal and Transmission Loss is 17.328[dB] at 65[cm]. To make a good underwater communicator, proper diameter of disk PZT transduers is the one of most important factors, because radiation of acoustic wave depends on proper diameter of transduers and the transmission loss strongly depends on the spreading loss.

• Journal of Ship and Ocean Technology
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• v.1 no.1
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• pp.15-25
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• 1997

A series of towing tank tests were carried out for 18 full ship models of high block coefficients. The resistance coefficients and wake distribution at the propeller plane were measured and carefully examined. Regression analysis was employed to find out the relationships with the hull form parameters. Equations for wave resistance coefficient, form factor, and nominal wake are given. A harmonic analysis of measured wake was performed to look into the influence of the local stern shape on the magnitude of fluctuating wake components at three different radii. The amplitude of wake harmonics was also expressed by regression quations. It was found that the regression formulas were very useful in estimating resistance and circumferential wake characteristics of full ship models. It was also considered that the formulas presented in this paper could be utilized in the hull form improvement in a preliminary design.

• Journal of Veterinary Clinics
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• v.16 no.2
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• pp.523-528
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• 1999

Subaortic stenosis in a 2.9kg, 3-month-old pug dog and a 11 kg, 4-month-old Rott -weiler dog showing signs of dyspnea, tachypnea, anorexia, exercise intolerance and depression was diagnosed with electrocardiography, thoracic radiography and ultrasonographic evaluation. In electrocardiography, PR interval widening, R wave amplitude increase in lead II in case 2, ST segment depression and left axis deviation in case 1 and 2 were identified. In thoracic radiographs, enlarged left ventricle and atrium, caudal displacement of left crus of diaphragm and caudal part of cranial mediastinum widening were identified in ventrodorsal view. In lateral view, left ventricular enlargement, secondary dorsal deviation of trachea and post-stenotic dilation of aorta were seen. Also, edematous pulmonary changes were shown in peri-hilar area. In ultrasonographic examination, left ventricular dilatation, pericardial effusion and subaortic valvular ridge were seen with real time B-mode in right parasternal long axis view. Aortic valve regurgitation was identified in color-Doppler mode.

• Toxicological Research
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• v.29 no.3
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• pp.211-215
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• 2013

The trace toxic metal copper was assayed using mercury immobilized on a carbon nanotube electrode (MCW), with a graphite counter and a reference electrode. In this study, a macro-scale convection motor was interfaced with a MCW three-electrode system, in which a handmade MCW was optimized using cyclic- and square-wave stripping voltammetry. An analytical electrolyte for tap water was used instead of an expensive acid or base ionic solution. Under these conditions, optimum parameters were 0.09 V amplitude, 40 Hz frequency, 0.01 V incremental potential, and a 60-s accumulation time. A diagnostic working curve was obtained from 50.0 to 350 ${\mu}g/L$. At a constant Cu(II) concentration of 10.0 ${\mu}g/L$, the statistical relative standard deviation was 1.78% (RSD, n = 15), the analytical accumulation time was only 60 s, and the analytical detection limit approached 4.6 ${\mu}g/L$ (signal/noise = 3). The results were applied to non-treated drinking water. The content of the analyzed copper using 9.0 and 4.0 ${\mu}g/L$ standards were 8.68 ${\mu}g/L$ and 3.96 ${\mu}g/L$; statistical values $R^2$ = 0.9987 and $R^2$ = 0.9534, respectively. This method is applicable to biological diagnostics or food surveys.

• Journal of the Korean Wood Science and Technology
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• v.43 no.5
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• pp.539-547
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• 2015

To investigate dimensional responses of wood under dynamic temperature condition, poplar (populous euramericana Cv.) specimens, 20 mm in radial (R) and tangential (T) directions with two thicknesses of 4 and 10 mm along the grain, were exposed to cyclic temperature changes in square wave between $25^{\circ}C$ and $40^{\circ}C$ at 60% relative humidity (RH) for three different cycling periods of 6 h, 12 h and 24 h. R and T dimensional changes measured during the cycling gave the following results: 1) Transverse dimensional changes of the specimens were generally square but at an opposite phase and lagged behind the imposed temperature changes. The phase lag was inversely correlated with cycling period, but positively related to specimen thickness, while the response amplitude was directly proportional to cycling period, but in a negative correlation with specimen thickness. 2) The specimens showed swelling hysteresis behavior. The heat shrinkage coefficient (HSC) became greater as cycling period increased or specimen thickness decreased. 3) Dimensional changes of the specimens produced deformation accumulation during repeated adsorption and desorption. The deformation accumulating ratio decreased with an increase in cycling period and specimen thickness. 4) Wood suffered 1.5 times as many dimensional changes per unit temperature variation as per unit humidity variation, and this deformation behaved even more seriously under static condition.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.317-325
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• 2008

The electrocardiogram (ECG) measurement system consists of I/O interface to input the ECG signals from two electrodes, FPGA (Field programmable gate arrays) module to process the signal conditioning, and real time module to control the system. The algorithms based on wavelet transform were developed to remove the noise of the ECG signals and to determine the QRS-waves. Triangular wave tests were conducted to determine the optimal factors of the wavelet filter by analyzing the SNRs (signal to noise ratios) and RMSEs (root mean square errors). The hybrid rule, soft method, and symlets of order 5 were selected as thresholding rule, thresholding method, and mother wavelet, respectively. The developed wavelet filter showed good performance to remove the noise of the triangular waves with 10.98 dB of SNR and 0.140 mV of RMSE. The ECG signals from a total of 6 subjects were measured at different measuring postures such as lying, sitting, and standing. The durations of QRS-waves, the amplitudes of R-waves, the intervals of RR-waves were analyzed by using the finite impulse response (FIR) filter and the developed wavelet filter. The wavelet filter showed good performance to determine the features of QRS-waves, but the FIR filter had some problems to detect the peaks of Q and S waves. The measuring postures affected accuracy and precision of the ECG signals. The noises of the ECG signals were increased due to the movement of the subject during measurement. The results showed that the wavelet filter was a useful tool to remove the noise of the ECG signals and to determine the features of the QRS-waves.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.71-81
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• 2021

This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1728-1736
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• 2015

Several algorithms have been developed to classify arrhythmia which either rely on specific ECG(Electrocardiogram) database. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extracting minimal feature. In this paper, we propose arrhythmia classification method using QRS Pattern of ECG signal according to personalized type. For this purpose, we detected R wave through the preprocessing method and define QRS pattern of ECG signal by QRS feature Also, we detect and modify by pattern classification, classified arrhythmia duplicated QRS pattern in realtime. Normal, PVC, PAC, LBBB, RBBB, Paced beat classification is evaluated by using 43 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.98%, 97.22%, 95.14%, 91.47%, 94.85%, 97.48% in PVC, PAC, Normal, BBB, Paced beat classification.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.11
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• pp.680-688
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• 2005

The electrical current generated by heart creates not only electric potential but also a magnetic field. We have observed electrophysiological phenomena of the heart by measuring components of magnetocardiogram(MCG) using 61 channel superconducting quantum interference device(SQUD) system. We have analyzed the possibility and characteristics of MCG parameters for diagnosis of ischemic heart disease. A technique for automatic analysis of MCG signals in time domain was developed. The methods for detecting the position, the interval, the amplitude ratio, and the direction of single current dipole were examined in the MCG wave. The position and interval parameters were obtained by calculating the gradients of a envelope curve which could be formed by the difference between the maximum and minimum envelope of multi-channel MCG signals. We show some differences of the frequency contour map between the normal MCG and the abnormal (ischemic heart disease) MCG. The direction of single current dipole can be defined by rotating the magnetic field according to Biot-Savart's law at each point of MCG signals. In this study, we have examined the direction of single current dipole from searching for the centroids of positive and negative magnetic fields. The amplitude ratio parameters for measuring 57 deviation consisted of A$_{T}$/A$_{R}$ and other ratios. and We developed a new analysis method, which is based on the frequency contour map of electromagnetic field. Using theses parameters, we founded significant differences between normal subjects and ischemic patients in some parameters.

• Geophysics and Geophysical Exploration
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• v.12 no.3
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• pp.246-254
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• 2009

We developed a novel polarization filter to separate linearly polarized waves from elliptically polarized waves in an infinite homogeneous medium and at the free surface using methods of multicomponent complex trace analysis. Sensitivity to filter parameters were examined using synthetic data simulating particle motions in a homogeneous medium. For known amplitude ratios of horizontal-to-vertical components of P and Rayleigh waves $C_L$ and $C_R$, respectively, the polarization filter precisely removes Rayleigh waves. Errors in the vertical and horizontal components of the filtered results increase with the ratio $C_R$/$C_L$ and the product $C_R$.$C_L$, respectively. The vertical component errors also increase rapidly as the ratios of applied-to-modeled values of $C_L$ and $C_R$ ($C_L'$/$C_L$ and $C_R'$/$C_R$) decrease, and are sensitive to $C_R'$/$C_R$ and $C_L'$/$C_L$ for small and large incidence angles, respectively. Errors of the filter are exactly the same for shear waves when the incidence angle is the supplementary of P-wave incidence angle.