• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.

• Environmental Analysis Health and Toxicology
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• v.29
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• pp.12.1-12.8
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• 2014

Objectives Cohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to $10{\mu}m$ in diameter ($PM_{10}$) concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability. Methods We obtained hourly $PM_{10}$ data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average $PM_{10}$ concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared ($R^2$) statistics were computed. Results Mean annual average $PM_{10}$ concentrations in the seven major cities ranged between 45.5 and $66.0{\mu}g/m^3$ (standard deviation=2.40 and $9.51{\mu}g/m^3$, respectively). Cross-validated $R^2$ values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had $R^2$ values of zero. The national model produced a higher cross-validated $R^2$ (0.36) than those for the city-specific models. Conclusions In general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate $PM_{10}$ source characteristics.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.2111-2111
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• 2001

A chemoinfometrical method for evaluating the quantitative determination of crystallinity one polymorphs based on fourie-transformed near-infrared (FT-NIR) spectroscopy was established. A direct comparison of the data with the ones collected from using the and compared with the conventional powder X-ray diffraction method was performed. [Method] The pPure a and g forms of indomethacin (IMC) were prepared by reportedusing published methods. Six kinds of standard samples obtained by physically mixing of a and g forms. After the powder X-ray diffraction profiles of samples have been measured, the intensity values were normalized to against the intensity of silicon powder as the as an external standard. The calibration curves for quantification of crystal content were based upon the total relative intensity of four diffraction peaks from of the form g crystal. FT-NIR spectra of six calibration sample sets were recorded 5 times with the NIR spectrometer (BRAN+LUEBBE). Chemoinfometric analysis was performed on the NIR spectral data sets by applying the principal component regression (PCR). [Results] The relation between the actual and predicted polymorphic contents of form g IMC measured using by the X-ray diffraction method shows a good straight linen linear relation., and it has slope of 0.023, an intercept of 0.131 and a correlation coefficient of 0.986. PCR analyses wereis was performed based on normalized NIR spectra sets offer standard samples of known content of IMC g form. IMC. A calibration equation was determined to minimize the root mean square error of the predictionthe prediction. Figure 1 shows a plot of the calibration data obtained by NIR method between the actual and predicted contents of form g IMC. The predicted values were reproducible and had a smaller standard deviation. Figure 2 shows that the plot for the predicted transformation rate (%) of form a IMC to form g as measured by X-ray diffractomeoy against to those as measured by NIR method. The plot has a slope of 1.296, an intercept of 1,109, and a correlation coefficient of 0.992. The line represents a satisfactory correlation between the two predicted values of form g IMC content. Thus NIR spectroscopy is an effective method for the evaluation to the pharmaceutical products of quantitative of polymorph.

• Journal of Navigation and Port Research
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• v.40 no.4
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• pp.207-212
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• 2016

The box-counting(BC) method is one of the most commonly used methods for fractal dimension calculation of binary images in the fields of Engineering, Science, Medical Science, Geology, etc due to its simplicity and reliability. It deals with only square images with each size equal to the power of 2 to prevent it from discarding unused pixels for images of arbitrary size. In this paper, we presents a more efficient BC method based on the original one, which is applicable to images of arbitrary size. The proposed approach allows the number of the counting boxes to be real to improve the estimation accuracy. The mean absolute error performance is computed on two deterministic fractal images whose theoretical dimensions are well known to compare with those of the existing BC method and triangular BC method. The experimental results show that the proposed method can outperform the two methods and assess the complexity of coastline images of Korea and Chodo island taken from the Google map.

• Journal of the Korean Geotechnical Society
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• v.24 no.9
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• pp.41-48
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• 2008

The aim of this study is to present a graphical method in order to evaluate stages in shrinkage cracking. Firstly, the distribution of crack openings is established by sorting the openings of individual cracks in the soil cracking system. Secondly, it is normalized in a range of 0 to 1 to obtain the normalized crack opening distribution. Thirdly, three S-shape curve models introduced by Brooks and Corey(1964), Fredlund and Xing(1994) and van Genuchten(1980) are chosen to fit the normalized crack opening distribution using a curve fitting method. The accuracy of fitting which is described through fitting parameters by the van Genuchten equation is much higher than that by the Brooks and Corey equation and slightly higher than that by the Fredlund and Xing equation; thus the van Genuchten model is used. Finally, the stages of shrinkage cracking are graphically evaluated by drawing three separate straight lines corresponding to three linear parts of the fitted normalized crack opening distribution. The proposed method is tested with different sample thicknesses. The measured data are fitted by the selected model with the fairly high regression coefficient and small root mean square error. The results show graphically that shrinkage cracking comprises three stages; namely, primary, secondary and residual stages. Subsequently, the ranges of evaluated crack opening for each of these stages are presented.

• Journal of Biosystems Engineering
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• v.36 no.2
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• pp.130-139
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• 2011

Three modes of VIS/NIR spectroscopic measurement (interactance and two modes of transmission) were compared for their ability to estimate soluble solids content (SSC) of 'Shingo' pear non-destructively. The two transmission modes are named as full- and semi-transmission, where full-transmission stands for passing of light through abdomen of pear and semi-transmission is for transit of light mainly through flesh of pear. For comparison of the modes, prediction models developed from the collected spectroscopic data by the three modes were developed and tested for comparison of their performance. Partial least square regression (PSLR) was used to develop the models and various pre-processing methods were applied to develop models of high accuracy. The experiment was repeated three times with pears produced in different regions. The experiments resulted that selection of pre-processing is very important to attain accurate models, and multiplicative scatter correction (MSC) was selected as a pre-processor of high accuracy for the three modes of spectroscopic measurement in every experiment. Except for MSC, different group of pre-processing methods were selected for the three modes of measurement in every experiment without any tendency to the tested modes of measurement and pears of different produced region. Root-mean-square error of prediction (RMSEP) of prediction models of the three modes of measurement using prepreocessor of MSC were compared for their ability to estimate SSC. The models resulted in ranges of $0.37{\sim}0.57^{\circ}Brix$, $0.65{\sim}0.72^{\circ}Brix$, $0.39{\sim}0.51^{\circ}Brix$ for interactance, full- and semi-transmission, respectively. As shown, modes of semi-transmission and interactance resulted about the same level of prediction accuracy and were noted as modes of high performance to predict SSC.

• Journal of Biosystems Engineering
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• v.42 no.4
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• pp.314-322
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• 2017

Purpose: This study was conducted to investigate the hot air drying characteristics of squash slices depending on the drying conditions (input air velocity, input air temperature, and sample thickness). Methods: The developed drying system was equipped with a controllable air blower and electric finned heater, drying chamber, and ventilation fan. Squash (summer squash called Korean zucchini) samples were cut into slices of two different thicknesses (5 and 10 mm). These were then dried at two different input air temperatures (60 and $70^{\circ}C$) and air velocities (5 and 7 m/s). Six well-known drying models were tested to describe the experimental drying data. A non-linear regression analysis was applied to determine model constants and statistical indices such as the coefficient of determination ($R^2$), reduced chi-square (${\chi}^2$), and root mean square error (RMSE). In addition, the effective moisture diffusivity ($D_{eff}$) was estimated based on the curve of ln(MR) versus drying time. Results: The results clearly showed that drying time decreased with an increase in input air temperature. Slice thickness also affected the drying time. Air velocity had a greater influence on drying time at $70^{\circ}C$ than at $60^{\circ}C$ for both thicknesses. All drying models accurately described the drying curve of squash slices regardless of slice thickness and drying conditions; the Modified Henderson and Pabis model had the best performance with the highest R2 and the lowest RMSE values. The effective moisture diffusivity ($D_{eff}$) changes, obtained from Fick's diffusion method, were between $1.67{\times}10^{-10}$ and $7.01{\times}10^{-10}m^2/s$. The moisture diffusivity was increased with an increase in input air temperature, velocity, and thickness. Conclusions: The drying time of squash slices varied depending on input temperature, velocity, and thickness of slices. The further study is necessary to figure out optimal drying condition for squash slices with retaining its original quality.

• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.271-280
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• 2017

This study presents the application of satellite laser ranging (SLR) to orbit determination (OD) of high-Earth-orbit (HEO) satellites. Two HEO satellites are considered: the Quasi-Zenith Satellite-1 (QZS-1), a Japanese elliptical-inclinedgeosynchronous-orbit (EIGSO) satellite, and the Compass-G1, a Chinese geostationary-orbit (GEO) satellite. One week of normal point (NP) data were collected for each satellite to perform the OD based on the batch least-square process. Five SLR tracking stations successfully obtained 374 NPs for QZS-1 in eight days, whereas only two ground tracking stations could track Compass-G1, yielding 68 NPs in ten days. Two types of station bias estimation and a station data weighting strategy were utilized for the OD of QZS-1. The post-fit root-mean-square (RMS) residuals of the two week-long arcs were 11.98 cm and 10.77 cm when estimating the biases once in an arc (MBIAS). These residuals were decreased significantly to 2.40 cm and 3.60 cm by estimating the biases every pass (PBIAS). Then, the resultant OD precision was evaluated by the orbit overlap method, yielding three-dimensional errors of 55.013 m with MBIAS and 1.962 m with PBIAS for the overlap period of six days. For the OD of Compass-G1, no station weighting strategy was applied, and only MBIAS was utilized due to the lack of NPs. The post-fit RMS residuals of OD were 8.81 cm and 12.00 cm with 49 NPs and 47 NPs, respectively, and the corresponding threedimensional orbit overlap error for four days was 160.564 m. These results indicate that the amount of SLR tracking data is critical for obtaining precise OD of HEO satellites using SLR because additional parameters, such as station bias, are available for estimation with sufficient tracking data. Furthermore, the stand-alone SLR-based orbit solution is consistently attainable for HEO satellites if a target satellite is continuously trackable for a specific period.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.257-264
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• 2020

Vectorization is currently the main method in feature collection (extraction) during digital mapping using UAV-Photogrammetry. However, this method is time consuming and prone to gross elevation errors when extracted from a DSM (Digital Surface Model), because three-dimensional feature coordinates are vectorized separately: plane information from an orthophoto and height from a DSM. Consequently, the demand for stereo plotting method capable of acquiring three- dimensional spatial information simultaneously is increasing. However, this method requires an expensive equipment, a Digital Photogrammetry Workstation (DPW), and the technology itself is still incomplete. In this paper, we evaluated the accuracy of low-cost stereo plotting system, Menci's StereoCAD, by analyzing its three-dimensional spatial information acquisition. Images were taken with a FC 6310 camera mounted on a Phantom4 pro at a 90 m altitude with a Ground Sample Distance (GSD) of 3 cm. The accuracy analysis was performed by comparing differences in coordinates between the results from the ground survey and the stereo plotting at check points, and also at the corner points by layers. The results showed that the Root Mean Square Error (RMSE) at check points was 0.048 m for horizontal and 0.078 m for vertical coordinates, respectively, and for different layers, it ranged from 0.104 m to 0.127 m for horizontal and 0.086 m to 0.092 m for vertical coordinates, respectively. In conclusion, the results showed 1: 1,000 digital topographic map can be generated using a stereo plotting system with UAV images.