• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.77-84
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• 2010

In this study, we tried to predict tractor power output, fuel consumption rate and work performance indirectly in order to develop an eco driving system. Firstly, we developed equations which could predict tractor power output and fuel consumption rate using characteristic curves of tractor power output. Secondly, with actual engine rpm determined by initial engine rpm and work load, tractor power output and fuel consumption rate were forecasted. Thirdly, with speed signals of GPS sensor system, it was possible to foresee tractor work performance and fuel consumption rate. Lastly, precision of the eco driving system was evaluated through tractor PTO test, and effects of the eco driving system were investigated in the plowing and rotary tilling operations. Engine rpm, power output, fuel consumption rate, work performance and fuel consumption rate per plot area were displayed in the eco driving system. Predicted tractor power outputs in the full load curve were well coincided with the actual power output of prototype, but small differences, 1 to 6 ㎾, were found in the part load curve. Error of the fuel consumption rate was 0.5 L/h, 4.5%, the greatest, and 1 to 3 L/h at the part load curve. It was shown that 69% and 53% of fuel consumption rates could be reduced in plowing and rotary tilling operations, respectively, when the eco driving system was installed in tractor.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.15-27
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• 2012

We have studied the realized variance(RV) of intra-day returns and market microstructure noise based on high-frequency stock transaction data for the four largest companies in terms of market capitalization in the KOSPI. First, non-negligible biases are observed for the RV and for the bias-corrected realized variance($RV_{AC_1}$) which is constructed by adjusting RV for the first order autocorrelation in intra-day returns. Bias is more obvious for the RV and the $RV_{AC_1}$ when intra-day returns are sampled more frequently than every 2 minutes. Transaction Time Sampling(TTS) is shown to be better than Calendar Time Sampling(CTS) in terms of biases of the RV and the $RV_{AC_1}$ for the 4 companies. The analysis reveals that market microstructure noise is temporally dependent. Second, by using the Noise-to-Signal Ratio(NSR), we estimate sampling frequencies that are optimal in terms of the Mean Square Errors(MSE) of the RV and the $RV_{AC_1}$. The optimal sampling frequencies are around 200 for RV and is around 5000 for the $RV_{AC_1}$ for all the four stock prices. For the 6 hour transaction period of the Korean stock trading, these correspond to about 2 minutes and 6 seconds.

• Journal of Photoscience
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• v.4 no.3
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• pp.97-103
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• 1997

The effect of temperature on the fluorescence quenching of 2-(4-Methoxyphenyl)-5-(1-naphthyl)-1,3,4-oxadiazole (MPNO1), 2-(4-Methoxyphenyl)-5-(2-naphthyl)-1,3,4-oxadiazote(MPNO2), by aniline, and 2-Phenylindole (2-PI) by CCk, in toluene by steady state method and in benzene by time-resolved method have been carried out in the temperature range 30 - 70$\circ$C. The Stem-Volmer (S-V) plots, I$_0$/I against quencher concentration [Q] at different temperanares show positive deviations. The fluorescence lifetimes determined at different temperatures show no systematic variations and the variations being within the experimental error, the average values of lifetimes $ $\tau$ (t) are taken for further calculations. Rate constants such as Stem-Volmer quenching constants K$_sv}$, quenching rate parameters k$_q$ and k'$_q$, static quenching constant V and kinetic distance r are determined using the modified Stem-Volmer equation and sphere of action static quenching model. In order to see whether the reactions are diffusion limited, equations k$_q$ = e$^{-Eq/RT}$ and k'$_q$ = e$^{-Eq/RT}$ are used to determine the values of E$_q$ and E'$_q$, the activation energies for collisional quenching and the values of E$_q$ are 14.53. 17.28 and 16.20 kJ mole$^{-1}$ for MPNO1, MPNO2 and 2-PI respectively and the values of E'$_q$ are 14.62 and 17.73 for MPNO1 and MPNO2 respectively. From the magnitudes of various quantities it has been concluded that the reactions are diffusion limited and the observed positive deviations in the S-V plot are due to static and dynamic quenching.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.303-314
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• 2011

Surface albedo is an important parameter of the surface energy budget, and its accurate quantification is of major interest to the global climate modeling community. Therefore, in this paper, we consider the direct solution of kernel based bidirectional reflectance distribution function (BRDF) models for retrieval of normalized reflectance of high resolution satellite. The BRD effects can be seen in satellite data having a wide swath such as SPOT/VGT (VEGETATION) have sufficient angular sampling, but high resolution satellites are impossible to obtain sufficient angular sampling over a pixel during short period because of their narrow swath scanning when applying semi-empirical model. This gives a difficulty to run BRDF model inferring the reflectance normalization of high resolution satellites. The principal purpose of the study is to estimate normalized reflectance of high resolution satellite (RapidEye) through BRDF components from SPOT/VGT. We use semi-empirical BRDF model to estimated BRDF components from SPOT/VGT and reflectance normalization of RapidEye. This study used SPOT/VGT satellite data acquired in the S1 (daily) data, and within this study is the multispectral sensor RapidEye. Isotropic value such as the normalized reflectance was closely related to the BRDF parameters and the kernels. Also, we show scatter plot of the SPOT/VGT and RapidEye isotropic value relationship. The linear relationship between the two linear regression analysis is performed by using the parameters of SPOTNGT like as isotropic value, geometric value and volumetric scattering value, and the kernel values of RapidEye like as geometric and volumetric scattering kernel Because BRDF parameters are difficult to directly calculate from high resolution satellites, we use to BRDF parameter of SPOT/VGT. Also, we make a decision of weighting for geometric value, volumetric scattering value and error through regression models. As a result, the weighting through linear regression analysis produced good agreement. For all sites, the SPOT/VGT isotropic and RapidEye isotropic values had the high correlation (RMSE, bias), and generally are very consistent.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.420-428
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• 2016

For more than 50 years, satellite images have been used to monitor crop growth. Currently, unmanned aerial vehicle (UAV) imagery is being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study refers to the derivation of growth estimating equation for highland Kimchi cabbage using UAV derived normalized difference vegetation index (NDVI) and agro-meteorological factors. Anbandeok area in Gangneung, Gangwon-do, Korea is one of main districts producing highland Kimchi cabbage. UAV imagery was taken in the Anbandeok ten times from early June to early September. Meanwhile, three plant growth parameters, plant height (P.H.), leaf length (L.L.) and outer leaf number (L.N.), were measured for about 40 plants (ten plants per plot) for each ground survey. Six agro-meteorological factors include average temperature; maximum temperature; minimum temperature; accumulated temperature; rainfall and irradiation during growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 93% of the P.H. and L.L. with a root mean square error (RMSE) of 2.22, 1.90 cm. And $NDVI_{UAV}$ and accumulated temperature in the model explain 86% of the L.N. with a RMSE of 4.29. These lead to the result that the characteristics of variations in highland Kimchi cabbage growth according to $NDVI_{UAV}$ and other agro-meteorological factors were well reflected in the model.

• Knee surgery & related research
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• v.30 no.4
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• pp.326-333
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• 2018

Purpose: To evaluate the reliability and validity of the femorotibial mechanical axis angle from radiographs in the weight bearing (WB) and supine positions compared with navigation-measured values. Materials and Methods: Sixty-eight cases of navigation-assisted total knee arthroplasty (TKA) were included. The pre- and postoperative whole leg radiographs (WLRs) in WB and supine positions were compared with the initial and final navigation values. Results: The mean mechanical axis angle from the preoperative WBWLR and navigation were not statistically different (p=0.079) and were correlated strongly with each other (intraclass correlation [ICC], 0.818). However, on postoperative measurements, although the WBWLR and navigation values were not different (p=0.098), they were not correlated with each other (ICC, 0.093). The standard error of measurement was $1.8^{\circ}{\pm}3.6^{\circ}$ for the preoperative WBWLR and $2.5^{\circ}{\pm}4.8^{\circ}$ for the postoperative WBWLR. The validity that was determined by the Bland-Altman plot was not acceptable for both pre- and postoperative measurements. Conclusions: The preoperative WBWLR could provide accurate but not precise measurement value of the femorotibial mechanical axis angle for navigation-assisted TKA, and postoperative measurements in navigation were not comparable with radiographic measurements. The lack of agreement was found between the radiographic and navigation measurements of the coronal alignment regardless of pre- or postoperative evaluation although the accuracy was found acceptable. Level of Evidence : Level 4.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.103-114
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• 2023

This study collected various data of urban roadways to analyze the effect of travel speed change, and a GRU-based short-term travel speed prediction model was developed using such big data. The baseline model and the double exponential smoothing model were selected as comparison models, and prediction errors were evaluated using the RMSE index. The model evaluation results revealed that the average RMSE of the baseline model and the double exponential smoothing model were 7.46 and 5.94, respectively. The average RMSE predicted by the GRU model was 5.08. Although there are deviations for each of the 15 links, most cases showed minimal errors in the GRU model, and the additional scatter plot analysis presented the same result. These results indicate that the prediction error can be reduced, and the model application speed can be improved when applying the GRU-based model in the process of generating travel speed information on urban roadways.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.342-350
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• 2016

This study aims to make the stand density management diagram which is very useful for establishing systematic management plan and obtaining management goal in Pinus densiflora forest. To estimate 5 models mainly composed of stand density management diagram, we used total of 1,886 sample plots having more than 75% of the total basal area of the pine trees in each stand. To test the goodness of fit, $X^2$ was computed with a significance level of 5%, and the acceptable error range as 20%. Also standard deviation of the model was $34.59m^3{\cdot}ha^{-1}$, minimum acceptable error range was 16.59% and coefficient of variation was 22.11%. If we use the stand density management diagram, it would be useful to establish the timber yield and thinning plan understanding the pathway of stand density management.

• Journal of Korean Society of Forest Science
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• v.8 no.1
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• pp.11-16
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• 1968

1. A Study was to delineate the correlation relationship growth factors, a) height and clear-length, b) height and circle of breast height, c) height and circle of ground height, d) height and crown length, of phyllostachys reticulata kock and phyllostachys edulis riv, 2. The formula applied to arrive at correlation coefficient according to correlation table, was $e=\frac{1-{\mu}^2}{\sqrt{\Sigma}X^2y^2}$ the formula for average error was $e=0.6745\frac{1-{\mu}^2}{\sqrt{n}}$ 3. The correlation coefficient and average error by each species were as three tables. 4. Area of the sample plot were 0.5~1 acres. 5. Height, clear-length, circle of breast height, circle of ground height and crown-length of bamboos were measured by weise hypsometer and pole.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.422-433
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• 2017

Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we developed for estimating garlic growth at field scale model in major cultivation regions. We used the $NDVI_{UAV}$ that reflects the crop conditions, and seven meteorological elements for 3 major cultivation regions from 2015 to 2017. For this study, UAV imagery was taken at Taean, Changnyeong, and Hapcheon regions nine times from early February to late June during the garlic growing season. Four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.), and fresh weight (F.W.) were measured for twenty plants per plot for each field campaign. The multiple linear regression models were suggested by using backward elimination and stepwise selection in the extraction of independent variables. As a result, model of cold type explain 82.1%, 65.9%, 64.5%, and 61.7% of the P.H., F.W., L.N., P.D. with a root mean square error (RMSE) of 7.98 cm, 5.91 g, 1.05, and 3.43 cm. Especially, model of warm type explain 92.9%, 88.6%, 62.8%, 54.6% of the P.H., P.D., L.N., F.W. with a root mean square error (RMSE) of 16.41 cm, 9.08 cm, 1.12, 19.51 g. The spatial distribution map of garlic growth was in strong agreement with the field measurements in terms of field variation and relative numerical values when $NDVI_{UAV}$ was applied to multiple linear regression models. These results will also be useful for determining the UAV multi-spectral imagery necessary to estimate growth parameters of garlic.