• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.155-169
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• 2016

In this study, we developed a multi-sensor blending short-term rainfall forecasting technique using radar and satellite data during extreme rainfall occurrences in Busan and Gyeongnam region in August 2014. The Tropical Z-R relationship ($Z=32R^{1.65}$) has applied as a optimal radar Z-R relation, which is confirmed that the accuracy is improved during 20mm/h heavy rainfall. In addition, the multi-sensor blending technique has applied using radar and COMS (Communication, Ocean and Meteorological Satellite) data for quantitative precipitation estimation. The very-short-term rainfall forecasting performance was improved in 60 mm/h or more of the strong heavy rainfall events by multi-sensor blending. AWS (Automatic Weather System) and MAPLE data were used for verification of rainfall prediction accuracy. The results have ensured about 50% or more in accuracy of heavy rainfall prediction for 1-hour before rainfall prediction, which are correlations of 10-minute lead time have 0.80 to 0.53, and root mean square errors have 3.99 mm/h to 6.43 mm/h. Through this study, utilizing of multi-sensor blending techniques using radar and satellite data are possible to provide that would be more reliable very-short-term rainfall forecasting data. Further we need ongoing case studies and prediction and estimation of quantitative precipitation by multi-sensor blending is required as well as improving the satellite rainfall estimation algorithm.

• Geophysics and Geophysical Exploration
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• v.12 no.4
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• pp.328-337
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• 2009

To investigate the relation between pore fluid conductivity and bulk resistivity of a rock sample it is assumed that electrolyte solution perfectly substitute the pore fluid that occupied the pore space within the sample in general. In this study, it is investigated that how much can the electrolyte solution substitute the pore fluid by repeating the same saturation process. Four kinds of NaCl solutions of 8, 160, 3200, 64000 ${\mu}S$/cm are used. The saturation process has repeated four times for each electrolyte in increasing conductivity order first then four times each in decreasing order. The more the saturation process repeated with the same electrolyte, the more electrolyte solution substitute the pore fluid. Geometric mean of bulk resistivity in increasing and decreasing orders with the same electrolyte solution is assumed to be mostly close to the bulk resistivity with perfect substitution. Bulk resistivity measurements for both increasing and decreasing order differs within 10% to the geometric mean when repeating the saturation process 4 times while maximum 40% difference is observed when single saturation process for each electrolyte solution with increasing order. The modified parallel resistant model can generally represent the relations between pore fluid resistivity and bulk resistivity in the experiment, but more experimental data with various rock samples with different porosity is needed to generalize the model.

• Korean journal of applied entomology
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• v.22 no.4 s.57
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• pp.300-306
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• 1983

Effect on blast lesion development was investigated in rice cultivar Milyang 23 and Jinheung using two races of Pyricularia oryzae compatible or incompatible to each of two rice cultivars. Discase lesions were measured in rice when inoculated with inoculum mixed with compatible and incompatible races, inoculated with a compatible race following with an incompatible race and vice versa. Lesions were smaller when rice was incoulated with an incompatible race and then inoculated with a compatible race than those inoculated in the reverse way both at the inoculated site and at 3cm-upper part from inoculated spot. The results suggested that induced resistance might play a role in suppression of lesion development although such an effect appeared to be influenced by heavy application of nitrogen fertilizer.

• Journal of the Korean earth science society
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• v.38 no.4
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• pp.283-292
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• 2017

In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.21 no.1
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• pp.1-10
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• 2016

Currently available surface seawater partial pressure carbon dioxide ($pCO_2$) data sets in the East Sea are not enough to quantify statistically the carbon dioxide flux through the air-sea interface. To complement the scarcity of the $pCO_2$ measurements, we construct a neural network (NN) model based on satellite data to map $pCO_2$ for the areas, which were not observed. The NN model is constructed for the Ulleung Basin, where $pCO_2$ data are best available, to map and estimate the variability of $pCO_2$ based on in situ $pCO_2$ for the years from 2003 to 2012, and the sea surface temperature (SST) and chlorophyll data from the MODIS (Moderate-resolution Imaging Spectroradiometer) sensor of the Aqua satellite along with geographic information. The NN model was trained to achieve higher than 95% of a correlation between in situ and predicted $pCO_2$ values. The RMSE (root mean square error) of the NN model output was $19.2{\mu}atm$ and much less than the variability of in situ $pCO_2$. The variability of $pCO_2$ with respect to SST and chlorophyll shows a strong negative correlation with SST than chlorophyll. As SST decreases the variability of $pCO_2$ increases. When SST is lower than $15^{\circ}C$, $pCO_2$ variability is clearly affected by both SST and chlorophyll. In contrast when SST is higher than $15^{\circ}C$, the variability of $pCO_2$ is less sensitive to changes in SST and chlorophyll. The mean rate of the annual $pCO_2$ increase estimated by the NN model output in the Ulleung Basin is $0.8{\mu}atm\;yr^{-1}$ from 2003 to 2014. As NN model can successfully map $pCO_2$ data for the whole study area with a higher resolution and less RMSE compared to the previous studies, the NN model can be a potentially useful tool for the understanding of the carbon cycle in the East Sea, where accessibility is limited by the international affairs.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.2
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• pp.114-120
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• 2019

This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation($R^2$) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The $R^2$ and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.

• The Journal of Korean Society for Radiation Therapy
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• v.33
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• pp.25-33
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• 2021

Purpose : The purpose of this study is to evaluate the accuracy and usefulness of the Trigger mode for the Respiratory Gated Radiation Therapy (RGRT) Materials and methods : A QUASAR respiratory phantom that inserted a 3 mm fiducial marker (a gold marker) was used to estimate the accuracy of the Trigger mode. And the 20 bpm was used as reference respiration rate in this study. The marker that placed at the center of the phantom was contoured, and the lower threshold of a gating window was fixed at 2.0 mm using an OBI with Truebeam STx^TM. The upper threshold was measured every 0.5 mm from 1.0 mm to 3.0 mm. The respiration rates were changed every 10 bpm from 10 bpm to 60 bpm. We repeatedly measured five times to check the error rate of the trigger mode in the same condition. Result : The differences of a distance from a peak phase to upper threshold, 1.0 to 3.0 mm at a 20 bpm as a reference for 3 days in a row were 0.68±0.05 mm, 0.91±0.03 mm, 1.23±0.03 mm, 1.42±0.04 mm, and 1.66±0.06 mm, respectively. Measurement result of changes in respiratory rate compared to baseline respiratory rate in maximum absolute difference. The coefficient of determination (R2) to estimate the correlation between the respiration velocity and variation of absolute difference was on average 0.838, 0.887, 0.770, 0.850, and 0.906. The p-values of all the variables were below 0.05. Conclusion : Using Trigger mode during respiratory gated radiation therapy (RGRT), accuracy and usefulness of trigger mode at reference breathing rate were confirmed. However, inaccuracies depending on the rate of breathing it could be uncertain in case of respiration rate is faster than 20 bpm as a standard respiration rate compared to slower than 20 bpm. Consequently, when conducting a RGRT using the trigger mode, real time monitoring is required with well educated respiration.

• Journal of The Korean Association For Science Education
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• v.33 no.7
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• pp.1367-1384
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• 2013

The purpose of this study was to develop a Science Academic Emotion Scale for Elementary Students. To make a scale, authors extract a core of 14 emotions related to science learning situations from Kim & Kim (2013) and literature review. Items on the scale consisted of 14 emotions and science learning situations. The first preliminary scale had 174 items on it. The number of 174 items was reduced and elaborated on by three science educators. Authors verified the scale using exploratory factor analysis, confirmatory factor analysis, inter-item consistency and concurrent validity. The second preliminary scale consisted of 141 items. The preliminary scale was reduced to seven factors and 56 items by applying exploratory factor analysis twice. The seven factors include: enjoyment contentment interest, boredom, shame, discontent, anger, anxiety, and laziness. The 56 items were elaborated on by five science educators. The scale with 56 items was fixed with seven factors and 35 items to get the final scale by applying confirmatory factor analysis twice. Except for Chi-square and GFI (Goodness of Fit Index), other various goodness of fit characteristics of the seven factors and 35 items model showed good estimated figures. The Cronbach of the scale was 0.85. The Cronbach of seven factors are 0.95 in enjoyment contentment interest, 0.81 in boredom, 0.87 in shame, 0.82 in discontent, 0.87 in anger, 0.77 in anxiety, 0.81 in laziness. The correlation coefficient was 0.59 in enjoyment contentment interest, 0.54 in anxiety, 0.42 in shame, and 0.28 in boredom, which were estimated using the Science Academic Emotion Scale and National Assessment System of Science-Related Affective Domain (Kim et al., 1998). Based on the results, authors judged that the Science Academic Emotion Scale for Elementary Students achieved an acceptable validity and reliability.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.137-148
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• 2004

In this paper, we propose a new camera calibration method for rotating multi-view cameras to generate image-based panoramic 3D Virtual Environment. Since calibration accuracy worsens with an increase in distance between camera and calibration pattern, conventional camera calibration algorithms are not proper for panoramic 3D VE generation. To remedy the problem, a geometric relationship among all lenses of a multi-view camera is used for intra-camera calibration. Another geometric relationship among multiple cameras is used for inter-camera calibration. First camera parameters for all lenses of each multi-view camera we obtained by applying Tsai's algorithm. In intra-camera calibration, the extrinsic parameters are compensated by iteratively reducing discrepancy between estimated and actual distances. Estimated distances are calculated using extrinsic parameters for every lens. Inter-camera calibration arranges multiple cameras in a geometric relationship. It exploits Iterative Closet Point (ICP) algorithm using back-projected 3D point clouds. Finally, by repeatedly applying intra/inter-camera calibration to all lenses of rotating multi-view cameras, we can obtain improved extrinsic parameters at every rotated position for a middle-range distance. Consequently, the proposed method can be applied to stitching of 3D point cloud for panoramic 3D VE generation. Moreover, it may be adopted in various 3D AR applications.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.765-771
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• 2019

With the increase in the speed of ships and the size of ocean structures, the importance of flow noise has become increasingly critical in meeting regulatory standards. However, unlike active investigations in aeroacoustics fields for airplanes and trains, which are based on acoustic analogy methods for tonal and broadband frequency noise, only the discrete blade passing frequency noise from propellers is considered in marine fields. In this study, prediction methods for broadband noise in marine propellers and underwater appendages are investigated using FW-H Formulation1B, which can consider the mechanism of primary noise generation of trailing edge noise. The original FW-H Formulation 1B is based on the pressure correlation function tolackitsgeneralityandaccuracy. To overcome these limitations, wall-pressure spectrum models are adopted to improve the generality in fluid mediums. The comparison of the experimental results obtained in air reveals that the proposed model exhibits a higher accuracy within 5 dB. Furthermore, the prediction procedures for broadband noise for hydrofoils are established, and the estimation of broadband noise is conducted based on the results of the computational fluid dynamics.