• The Journal of Industrial Distribution & Business
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• v.9 no.6
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• pp.15-24
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• 2018

Purpose - The adjustment of one country's monetary policy can cause the macroeconomic change of other countries. Due to this, this paper attempts to analyze the impact of China's monetary policy on South Korea's exchange rate. Research design, data, and methodology - Based on the flexible-price monetary model, sets of annual time series from 1980 to 2017 are employed to perform an empirical estimation. The vector error correction model is also used to exploit the short-run relationship between both of them. Of course, the South Korea's real GDP, the China's real GDP, South Korea's interest rate, the South Korea's interest rate and the South Korea's monetary supply are treated as independent variables in this paper. Result - The long-run findings reveal that the China's money supply has a negative effect on South Korea's exchange rate. Respectively, the short-run findings depicts that the China's money supply has negative a effect on South Korea's exchange rate. Of course, other variables selected in this paper also have an effect on South Korea's exchange rate whatever positive or negative. Conclusions - As the empirical evidence shows, the China's monetary policy has a negative effect on South Korea's exchange rate whenever in the long run or in the short run.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.197-207
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• 2013

Difficulties of emissivity determination and atmospheric correction degrade the estimation accuracy of land surface temperature (LST). That is, since the emissivity determination of land surface material and the correction of atmospheric effect are not perfect, it is very difficult to estimate the precise LST from a thermal infrared image such as Landsat TM and ETM+, ASTER, etc. In this study, we propose an efficient method to estimate land surface temperature difference (LSTD) rather than LST from Landsat thermal band images. This method is based on the assumptions that 1) atmospheric effects are same over a image and 2) the emissivity of vegetation region is 0.99. To validate the performance of the proposed method, error sensitive analysis according to error variations of reference land surface temperature and the water vapor is performed. The results show that the estimated LSTD have respectively the errors of ${\pm}0.06K$, ${\pm}0.15K$ and ${\pm}0.30K$ when the water vapor error of ${\pm}0.302g/cm^2$ and the radiance differences of 0.2, 0.5 and $1.0Wm^{-2}sr^{-1}{\mu}m$ are considered. And also the errors of the LSTD estimation are respectively ${\pm}0.037K$, ${\pm}0.089K$, ${\pm}0.168K$ in the reference land surface temperature error of ${\pm}2.41K$. Therefore, the proposed method enables to estimate the LSTD with the accuracy of less than 0.5K.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2246-2253
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• 2011

This paper presents the error correction method of magnetic position sensor using recursive least square method (RLSM) with forgetting factor. Magnetic position sensor is proposed for linear position detection of the linear motor which has tooth shape stator, consists of permanent magnet, iron core and linear hall sensor, and generates sine and cosine waveforms according to the movement of the mover of the linear motor. From the output of magnetic position sensor, the position of the linear motor can be detected using arc-tan function. But the variation of the air gap between magnetic position sensor and the stator and the error in manufacturing process can cause the variation in offset, phase and amplitude of the generated waveforms when the linear motor moves. These variations in sine and cosine waveforms are changed according to the current linear motor position, and it is very difficult to compensate the errors using constant value. In this paper, the generated sine and cosine waveforms from the magnetic position sensor are compensated on-line using the RLSM with forgetting factor. And the speed observer is introduced to reduce the effect of uncompensated harmonic component. The approaches are verified by some simulations and experiments.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.6
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• pp.354-360
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• 2002

Delay estimation must be simple and efficient, since millions or more delay calculations may be required during a timing-driven placement stage. We have developed a new Modified Elmore delay estimation method, which is significantly more accurate than the original Elmore delay by considering resistance shielding effects, but has the same order of complexity with that of Elmore delay. Experimental results show that the suggested technique can significantly reduce the error in estimated delay, from 31.6 ~ 145.2% to 2.5 ~ 22.7%.

• Journal of the Korean Solar Energy Society
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• v.31 no.3
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• pp.1-7
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• 2011

In the performance test for wind turbines of medium and large, The reference met-mast should be installed for measurement reference wind speed as IEC 61400-12-1 standards and design of booms for mounted an anemometer must be considered exactly. Boom-mounted cup anemometer are influenced by flow distortion of the mast and the boom. Therefore design of booms must be important so that flow distortion due to booms should be kept below 0.5%. But, in some cases at size of met-mast structure, the distance of boom from mast is longer then measurement of wind speed is impossible because of oscillation of boom-mounted anemometer. In this paper, We measured a wind speed at several point from mast and boom and we analyzed the error of wind speed at each point of measurement. Also, we will suggest a correction method using the data curve fitting about errors of wind speed between each point of mounted anemometer.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.4
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• pp.155-161
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• 2014

The purpose of this study is to develop precise point positioning (PPP) algorithms based on GLONASS code-pseudorange, verify their performance and present their utility. As the basic correction models of PPP, we applied Inter Frequency Bias (IFB), relativistic effect, satellite antenna phase center offset, and satellite orbit and satellite clock errors, ionospheric errors, and tropospheric errors that must be provided on a real-time basis. The satellite orbit and satellite clock errors provided by Information-Analytical Centre (IAC) are interpolated at each observation epoch by applying the Lagrange polynomial method and linear interpolation method. We applied Global Ionosphere Maps (GIM) provided by International GNSS Service (IGS) for ionospheric errors, and increased the positioning accuracy by applying the true value calculated with GIPSY for tropospheric errors. As a result of testing the developed GLONASS PPP algorithms for four days, the horizontal error was approximately 1.4 ~ 1.5 m and the vertical error was approximately 2.5 ~ 2.8 m, showing that the accuracy is similar to that of GPS PPP.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.405-421
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• 2019

Predicting how much energy to use is an important issue in society. However, it is more difficult to capture the usage characteristics of residential buildings than other buildings. This paper provides time series analysis methods for electricity consumption in a residential building. Temperature is closely related to electricity demand. An error correction model, which is a method of adjusting the error with time, is applied when a cointegration relation is established between variables. Therefore, we analyze data via ECMs with consideration of the temperature effect.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1295-1305
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• 2021

Satellite-derived ocean color products are required to effectively monitor clear open ocean and coastal water regions for various research fields. For this purpose, accurate correction of atmospheric effect is essential. Currently, the Geostationary Ocean Color Imager (GOCI)-II ground segment uses the reanalysis of meteorological fields such as European Centre for Medium-Range Weather Forecasts (ECMWF) or National Centers for Environmental Prediction (NCEP) to correct gas absorption by water vapor and ozone. In this process, uncertainties may occur due to the low spatiotemporal resolution of the meteorological data. In this study, we develop water vapor absorption correction model for the GK-2 combined GOCI-II atmospheric correction using Advanced Meteorological Imager (AMI) total precipitable water (TPW) information through radiative transfer model simulations. Also, we investigate the impact of the developed model on GOCI products. Overall, the errors with and without water vapor absorption correction in the top-of-atmosphere (TOA) reflectance at 620 nm and 680 nm are only 1.3% and 0.27%, indicating that there is no significant effect by the water vapor absorption model. However, the GK-2A combined water vapor absorption model has the large impacts at the 709 nm channel, as revealing error of 6 to 15% depending on the solar zenith angle and the TPW. We also found more significant impacts of the GK-2 combined water vapor absorption model on Rayleigh-corrected reflectance at all GOCI-II spectral bands. The errors generated from the TOA reflectance is greatly amplified, showing a large error of 1.46~4.98, 7.53~19.53, 0.25~0.64, 14.74~40.5, 8.2~18.56, 5.7~11.9% for from 620 nm to 865 nm, repectively, depending on the SZA. This study emphasizes the water vapor correction model can affect the accuracy and stability of ocean color products, and implies that the accuracy of GOCI-II ocean color products can be improved through fusion with GK-2A/AMI.

• Journal of Korea Port Economic Association
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• v.23 no.1
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• pp.1-18
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• 2007

The purpose of this study is to examine the effect of exchange rate volatility on Trading Volume of Container of Korea, and to induce policy implication in the contex of GARCH and regression model. In order to test whether time series data is stationary and the model is fitness or not, we put in operation unit root test, cointegration test. And we apply impulse response functions and variance decomposition to the structural model to estimate dynamic short run behavior of variables. The major empirical results of the study show that the increase in exchange rate volatility exerts a significant negative effect on Trading Volume of Container in long run. The results Granger causality based on an error correction model indicate that uni-directional causality between trading volume of container and exchange rate volatility is detected. This study applies impulse response function and variance decompositions to get additional information regarding the Trading Volume of Container to shocks in exchange rate volatility. The results indicate that the impact of exchange rate volatility on Trading Volume of Container is negative and converges on a stable negative equilibrium in short-run. Th exchange rate volatility have a large impact on variance of Trading Volume of Container, the effect of exchange rate volatility is small in very short run but become larger with time. We can infer policy suggestion as follows; we must make a stable policy of exchange rate to get more Trading Volume of Container

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.521-521
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• 2015

This study evaluated the gap filler radar as an implementation of the 1.5 km CAPPI data in Korea. The use of the 1.5 km CAPPI data was an inevitable choice, given the topography of the Korean Peninsula and the location of the radar. However, there still exists a significant portion of beam blockage, and thus there has been debate about the need to introduce the gap filler radar (or, the gap-filler). This study evaluated the possible benefits of introducing gap-fillers over the Korean Peninsula. As a first step, the error of the radar data was quantified by the G/R ratio and RMSE, and the radar data over the Korean Peninsula were evaluated. Then, the gap-fillers were located where the error was high, whose effect was then evaluated by the decrease in the G/R ratio and RMSE. The results show that the mean values of the G/R ratio and RMSE of the 1.5 m CAPPI data over the Korean Peninsula were estimated to be about 2.5 and 4.5 mm/hr, respectively. Even after the mean-field bias correction, the RMSE of the 1.5 km CAPPI data has not decreased much to be remained very high around 4.4 mm/hr. Unfortunately, the effect of the gap-filler on the 1.5 CAPPI data was also found very small, just 1 - 2%. However, the gap-filler could be beneficial, if the lowest elevation angle data were used instead of the 1.5 km CAPPI data. The effect of five gap-fillers could be up to 7% decrease in RMSE.