• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.38-43
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• 2013

In this study, the artery's compliance model and the pulsation waveform model was proposed to estimate blood pressure without applying HPF (High Pass Filter) on signal measured by the oscillometric method. The method proposed in the study considered two ways of estimating blood pressure. The first method of estimating blood pressure is by comparing and analyzing changes in pulsation waveform's dicrotic notch region during each cardiac period. The second method is by comparing and analyzing morphological changes in the pulsation waveform during each cardiac period, which occur in response to the change in pressure applied on the cuff. To implement these methods, we proposed the compliance model and the pulsation waveform model of the artery based on hemodynamic theory, and then conducted various simulations. The artery model presented in this study only took artery's compliance into account. Then, a pulsation waveform model was suggested, which uses characteristic changes in the pulsation waveform to estimate blood pressure. In addition, characteristic changes were observed in arterial volume by applying artery's pulsation waveform to the compliance model. The pulsation waveform model was suggested to estimate blood pressure using characteristic changes of the pulsation waveform in the arteries. This model was composed of the sum of sine waves and a Fourier's series in combination form up to 10th harmonics components of the sinusoidal waveform. Then characteristic of arterial volume change was observed by inputting pulsation waveform into the compliance model. The characteristic changes were also observed in the pulsation waveform by mapping the arterial volume change in accordance with applied cuff's pressure change to the pulsation waveform's change according to applied pressure changes by cuff. The systolic and diastolic blood pressures were estimated by applying positional change of pulsation waveform's dicrotic notch region.

• Journal of the Optical Society of Korea
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• v.19 no.4
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• pp.363-370
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• 2015

The current waveform model of a laser altimeter is based on a Gaussian laser beam of fundamental mode, while the flattened Gaussian beam has many advantages such as nearly constant energy distribution on the center of the cross-section. Following the theory of the flattened Gaussian beam and the waveform theory of the laser altimeter, some of the primary parameters of the received waveform were derived, and a laser altimetry waveform simulator and waveform processing software were programmed and improved under the circumstance of a flattened Gaussian beam. The result showed that the bias between theoretical and simulated waveforms was less than 3% for every order mode, the waveform width and range error would increase as target slope or order number rose. Under higher order mode, the shapes of the received waveforms were no longer Gaussian, and could be fitted more precisely as a generalized Gaussian function with power bigger than 2. The flattened beam got much better performance for a multi-surface target, especially when the small surface is far from the center of the laser footprint. This article provides the waveform theoretical basis for the use of a flattened Gaussian beam in a laser altimeter.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.46.2-46.2
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• 2019

We propose a deep learning model that can generate a waveform of coalescing binary black holes in merging and ring-down phases in less than one second with a graphics processing unit (GPU) as an approximant of gravitational waveforms. Up to date, numerical relativity has been accepted as the most adequate tool for the accurate prediction of merger phase of waveform, but it is known that it typically requires huge amount of computational costs. We present our method can generate the waveform with ~98% matching to that of the status-of-the-art waveform approximant, effective-one-body model calibrated to numerical relativity simulation and the time for the generation of ~1500 waveforms takes O(1) seconds. The validity of our model is also tested through the recovery of signal-to-noise ratio and the recovery of waveform parameters by injecting the generated waveforms into a public open noise data produced by LIGO. Our model is readily extendable to incorporate additional physics such as higher harmonics modes of the ring-down phase and eccentric encounters, since it only requires sufficient number of training data from numerical relativity simulations.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.191-196
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• 2007

The acoustic array waveforms are simulated in a simple borehole model for both monopole and dipole sources. The model is based on the parameters obtained by the semblance processing of field waveforms collected on the physical models whose physical parameters are known. Both the synthetic and field waveforms are compared to understand the sonic waveform as well as the source wavelet characteristics.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1709-1718
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• 2021

The waveform data of the Airborne Bathymetric LiDAR (ABL; LiDAR: Light Detection And Ranging) system provides data with improved accuracy, resolution, and reliability compared to the discrete-return data, and increases the user's control over data processing. Furthermore, we are able to extract additional information about the return signal. Waveform decomposition is a technique that separates each echo from the received waveform with a mixture of water surface and seabed reflections, waterbody backscattering, and various noises. In this study, a new waveform decomposition technique based on a Gaussian model was developed to improve the point extraction performance from the ABL waveform data. In the existing waveform decomposition techniques, the number of decomposed echoes and decomposition performance depend on the peak detection results because they use waveform peaks as initial values. However, in the study, we improved the approximation accuracy of the decomposition model by adding the estimated potential peak candidates to the initial peaks. As a result of an experiment using waveform data obtained from the East Coast from the Seahawk system, the precision of the decomposition model was improved by about 37% based on evaluating RMSE compared to the Gaussian decomposition method.

• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.22-25
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• 1999

A brushless DC motor has the high quality of torque output and silence, has been more widely used in industrial area. As the driver and controller of BLDC motor have been more complicated and precise, simulation method has been much used in motor design. And the output characteristics of BLDC motor is determined by the waveform of BACK-KMF in instinct. But because the conventional model of BLDC motor is obtained by approximation of real nonlinear waveform to ideal trapezoidal waveform, the error is occurred in simulation result. Thus in this paper, for the correction of this error in simulation, the model of real nonlinear waveform considered is proposed, and the simulation result is obtained in case of three-phase, four-poles Y-connected, surface mounted permanent magnet BLDC motor.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.12
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• pp.209-219
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• 1995

As a new algorithm for RC tree delay estimation, we propose a $\tau$-model of the driver and a moment propagation method. The $\tau$-model represents the driver as a Thevenin equivalent circuit which has a one-time-constant voltage source and a linear resistor. The new driver model estimates the input voltage waveform applied to the RC more accurately than the k-factor model or the 2-piece waveform model. Compared with Elmore method, which is a lst-order approximation, the moment propagation method, which uses $\pi$-model loads to calculate the moments of the voltage waveform on each node of RC trees, gives more accurate results by performing higher-order approximations with the same simple tree walking algorithm. In addition, for the instability problem which is common to all the approximation methods using the moment matching technique, we propose a heuristic method which guarantees a stable and accureate 2nd order approximation. The proposed driver model and the moment propagation method give an accureacy close to SPICE results and more than 1000 times speedup over circuit level simulations for RC trees and FPGA interconnects in which the interconnect delay is dominant.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.877-882
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• 1993

An adaptive EEG waveform detection is presented. The method is based on a layered process model. The model allows the bilateral information exchange across the layers. The criteria for the waveform detection and epoch-wise classification can be adapted according to the higher layer context information embedded in a wider range of adjacent signals. The designed system is experimentally tested to show the adaptive operation of the waveform detection.

• Journal of Ocean Engineering and Technology
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• v.7 no.1
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• pp.147-155
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• 1993

The effect of stress waveforms on corrosin fatigue and the role of dissolution mechanism in 3NilCr steel and 20Ni maraging steel have been investigated in aerated 3% NaCl solution and synthetic seawater under sinusoidal, triangular, square, positive sawtooth, negative sawtooth, and trapezoidal stress waveforms with open circuit at frequency of 1Hz and stress ratio of 0.1. The crack growth rates under square waveform were substantially lower than under sinusoidal and triangular waveforms, but the crack growth rates under sinusoidal waveform were slightly higher under triangular waveform. For a given frequency the growth rates under the positive sawtooth waveform are higher than those under the negative sawtooth waveform. The fatigue crack growth rates of most specimens were in good agreement with the values calculated by the model based on the dissoultion mechanism.

• Proceedings of the KSEEG Conference
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• 2002.04a
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• pp.159-162
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• 2002

We tried to obtain an initial velocity model for prestack depth migration via waveform inversion. For application of any field data we chose a smooth background layered velocity model (v=v0 + k x z) as an initial velocity model. Newton type waveform inversion needs to invert huge Hessian matrix. In order to compute full Hessian matrix arising from full aperture data and full illumination zone, we meet insurmountable difficulties of paying astronomical computing cost. For the layered media, approximate Hessian emerging from single shot aperture data can be used repeatedly for split spread source configuration. In our work of using this Hessian characteristic of layered media we attempted to obtain the approximate velocity model as close as possible to the true velocity model in first iteration.