• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.251-254
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• 2006

A precise real-time method of using the IGS ultra rapid products (IGU) and the GPS broadcast ephemeris to calculate the VRS orbit corrections was presented here which was suited for GPS/VRS reference station network based positioning. Test data acquired from both the SGRSN (Sichuan GPS Reference Station Network) and SCIGN (Southern California integrated GPS network) were used to evaluate the performance of the modeling techniques. The new method was proven to be more precise and reliable compared with the existing conventional network-based orbit error interpolation method. It was shown that 0.004ppm relative accuracy was reached, namely the influence from the orbit bias for the RTK positioning within 100km area can be of sub-millimeter level.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.283-287
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• 1996

This paper described the estimator and eliminator far three kinds of artifacts in electrocardiogram. The most efficient estimation of baseline drift could be obtain in the cubic spline interpolation method with the PQ and TP segment which are considered to be isoelectric, from the experimental results obtained from the applied 4 types of algorithms. The time loss and distortion could be avoided with the aid of detection criteria by checking if baseline drifts exist or not. The AIEF proposed in this paper was verified as having the best removal performance with less distortion in the QRS complex through the comparison of 5 proposed algorithms. furthermore, the AIEF are most suitable far the ECG analyzer which was only needed relatively short time data due to the fast conversion into the stable state. The proposed parabolic filter with 11 points width was identified as having the best performance for the elimination of muscle artifacts. Also we could obtain 99.7% detection accuracy of spike component and minimize the error identifying QRS complex as spike.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1725-1731
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• 2017

In hysteresis simulation, the Preisach model is most widely used as the reliability. However, since the first-order transition curves used in the conventional Preisach model are very inconvenient for actual measurement, many researches have been made to simplify them. In this study, the minor loops obtained along the initial magnetization curve are used to obtain the Everett function used in the Preisach model. In other words, The Everett table is constructed by using the minor loops, and are applied to the magnetization dependent Preisach model to reconstruct the Everett table. In order to minimize the error, the spline interpolation method is used to complete the final Everett table and the hysteresis loop simulation is performed with the Everett table. Furthermore, it is applied to the inductor analysis to perform not only sinusoidal wave and square wave drive but also PWM wave drive considering hysteresis. The validity of the proposed method is confirmed by comparison with simulation and experiment.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.220-224
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• 2009

The authors have investigated the acoustic field analysis using the Constrained Interpolation Profile(CIP) Method recently proposed by Yabe. The present study has examined the calculation accuracy of the three-dimensional (3-D) acoustic field analysis using the type-M CIP method. In this paper we show phase error of type-M CIP method and the dependence on the wave-propagation direction in the type-M CIP acoustic field analysis, and then demonstrate that it is effective for acoustic field analysis, compared with the FDTD and the exact solution. We show the dependency on the propagation angle in the CIP acoustic field analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.103-103
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• 2019

본 연구에서는 Terra MODIS 위성영상과 Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) 모형을 이용하여 2012년부터 2017년까지 한반도 전국의 증발산량을 산정하고 플럭스 타워 실측 증발산량과 비교하였다. METRIC은 전 세계에 널리 적용된 바 있는 에너지 수지 기반의 Surface Energy Balance Algorithm for Land (SEBAL) 모형의 개념과 기술을 기반으로 현열(Sensible Heat Flux) 추정 모듈을 개선한 모형이다. 본 연구에서 METRIC 모형은 기존 C#으로 개발되어 있던 SEBAL 코드에서 현열 추정 모듈을 수정하였고 연산 속도 개선을 위해 Python으로 재작성하였다. METRIC 모형의 위성 자료로 Terra MODIS 위성의 MOD13A2(16day, 1km) NDVI, MOD11A1(Daily, 1km) Land Surface Temperature (LST) 및 MCD43A3(Daily, 500m) Albedo를 구축하였으며 500m 공간해상도의 Albedo는 1000m 해상도로 resample하여 활용하였다. 기상자료는 기상청 기상관측소의 풍속, 풍속측정높이, 습도, 10분 간격 이슬점 온도, 일사량 자료를 위성 자료와 같은 공간해상도로 내삽(Interpolation)하여 구축하였다. 모형결과 검증을 위해 국내 플럭스 타워 (설마천, 청미천, 덕유산) 증발산량 관측 자료와의 결정계수(Coefficient of determination, $R^2$), RMSE(Root mean square error) relative RMSE (RMSE%), Nash-Sutcliffe efficiency (NSE) 및 IOA(Index of Agreement)를 산정하고, 기존 SEBAL 모형 결과와의 비교를 통해 본 모형의 개선점을 보이고자 한다.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.52.1-52.1
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• 2019

The Helioseismic and Magnetic Imager (HMI) is the instrument of Solar Dynamics Observatory (SDO) to study the magnetic field and oscillation at the solar surface. The HMI image is not enough to analyze very small magnetic features on solar surface since it has a spatial resolution of one arcsec. Super resolution is a technique that enhances the resolution of a low resolution image. In this study, we use a method for enhancing the solar image resolution using a Deep-learning model which generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained a model based on a very deep residual channel attention networks (RCAN) with HMI images in 2014 and test it with HMI images in 2015. We find that the model achieves high quality results in view of both visual and measures: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is much better than the conventional bi-cubic interpolation. We will apply this model to full-resolution SDO/HMI and GST magnetograms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.305-313
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• 2022

The evolution of the GNSS (Global Navigation Satellite System) technology has enhanced positioning performance in terms of positioning accuracy and time efficiency. The technology makes it possible to determine orthometric heights at a few centimeter accuracies by transforming accurate ellipsoid heights if an accurate geoid model has been employed. This study aims to generate a correction surface using GNSS/leveling co-points and a local geoid model, Thailand Geoid Model 2017 (TGM2017), through the Kriging interpolation method in a small local area. Combining the surface and TGM2017 significantly improves height transformation with the 1-cm RMSE (Root Mean Square Error) fit of 10 GNSS/leveling reference points and a mean offset of +0.1 cm. The evaluation of the correction surface at 5 GNSS/leveling checkpoints shows the RMSE of 1.0 cm, which is 82.6 percent of accuracy improvements. The GNSS leveling method can possibly be used to replace a conventional leveling technique at a few centimeter uncertainties in the case of small areas with clear-sky and high satellite visibility environments.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.2
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• pp.54-65
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• 1993

The paper describes and alternative method based on a new idea to measure the circular movement of machining centers. ISO has employed three testing methods for the acceptance tests of machine tools; the first is a rotating one-dimensional probe method, the second is a two-dimensional probe and a master circular ring, and the third is a kinematic ball bar. The last two methods were proposed and introduced by W. Knapp and J. B. Bryan, respectively. The newly developed method is superior to above two methods; the rotating angle can be detected and the rotating radius is variable. Circular movement errors of machining centers were investigated by the analysis of data measured by R- .THETA. method. Followint observations are obtained 1) The errors which depend on positions, i.e., periodical errors by the pitch of ball screws, errors by compensation of backlash and errors by perpendicularity of X and Y-axis, were analyzed. 2) The errors which depend on NC control system, i.e., errors by the unbalance of position-loop-gaians, errors by velocity-loop-gains and errors by feed speeds, were quantiatively analyzed. 3) The method of extracting error information, which uses moving technique of averaging angle and fourier's analysis data mesured by the R- .THETA. method, was proposed.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.70.4-70.4
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• 2019

Image super-resolution (SR) is a technique that enhances the resolution of a low resolution image. In this study, we use three SR models (RCAN, ProSRGAN and Bicubic) for enhancing solar SDO/HMI magnetograms using deep learning. Each model generates a high resolution HMI image from a low resolution HMI image (4 by 4 binning). The pixel resolution of HMI is about 0.504 arcsec. Deep learning networks try to find the hidden equation between low resolution image and high resolution image from given input and the corresponding output image. In this study, we trained three models with HMI images in 2014 and test them with HMI images in 2015. We find that the RCAN model achieves higher quality results than the other two methods in view of both visual aspects and metrics: 31.40 peak signal-to-noise ratio(PSNR), Correlation Coefficient (0.96), Root mean square error (RMSE) is 0.004. This result is also much better than the conventional bi-cubic interpolation. We apply this model to a full-resolution SDO/HMI image and compare the generated image with the corresponding Hinode NFI magnetogram. As a result, we get a very high correlation (0.92) between the generated SR magnetogram and the Hinode one.

• Wind and Structures
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• v.38 no.2
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• pp.147-160
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• 2024

The aerodynamic force is a significant component that influences the stability and safety of structures. It has unstable properties and depends on computer precision, making its long-term prediction challenging. Accurately estimating the aerodynamic traits of structures is critical for structural design and vibration control. This paper establishes an unsteady aerodynamic time series prediction model using Long Short-Term Memory (LSTM) network. The unsteady aerodynamic force under varied Reynolds number and angles of attack is predicted by the LSTM model. The input of the model is the aerodynamic coefficients of the 1 to n sample points and output is the aerodynamic coefficients of the n+1 sample point. The model is predicted by interpolation and extrapolation utilizing Unsteady Reynolds-average Navier-Stokes (URANS) simulation data of flow around a circular cylinder, square cylinder and airfoil. The results illustrate that the trajectories of the LSTM prediction results and URANS outcomes are largely consistent with time. The mean relative error between the forecast results and the original results is less than 6%. Therefore, our technique has a prospective application in unsteady aerodynamic force prediction of structures and can give technical assistance for engineering applications.