• Journal of the Korean Chemical Society
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• v.17 no.6
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• pp.395-405
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• 1973

By use of an Integral Hellmann-Feynman formula, the cubic crystal field splitting 1O Dq in $KNiF_3$ is calculated from first principles. Numerical values of covalency parameters and necessary integrals are quoted from Sugano and Shulman. The result, 7100$cm^{-1}$, is in excellent agreement with the observed value, 7250$cm^{-1}$. It is found that higher order perturbation energy correction is of the same order of magnitude as 10 Dq itself and is, therefore, essential tin calculating 10 Dq from first principles. It is also found that the point charge potential is the dominant part of the crystal field potential.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.297-303
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• 2014

The effect of solar irradiance has been used to estimate daily maximum temperature, which make it possible to reduce the error inherent to lapse-rate based elevation difference correction in mountainous terrain. Still, recent observations indicated that the effect of solar radiation would need correction for estimation of daily maximum temperature. It was attempted to examine what would cause the variability of solar irradiance effect in determination of daily maximum temperature under natural field conditions and to suggest improved methods for estimation of the temperature distribution over mountainous regions. Temperature at 1500 and the wind speed for 1100 to 1500 were obtained at 10 validation sites with various topographical features including slope and aspect within a mountainous $50km^2$ catchment for 2012-2013. Lapse-rate corrected temperature estimates on clear days were compared with these observations, which would represent the differential irradiance effect among sloped surfaces. Results indicated a negative correlation between the mean wind speed and the estimation error. A simple scheme was derived from relationship between wind speed and estimation error for daily temperature to correct the effect of solar radiation. This scheme was incorporated into an existing model to estimate daily maximum temperature based on the effect of solar radiation. At 10 validation sites on clear days, estimates of 1500 LST temperature with and without the correction scheme were compared. It was found that a substantial improvement was achieved when the correction scheme was applied in terms of bias correction as well as error size reduction at all sites.

• Journal of the Korean Geosynthetics Society
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• v.17 no.1
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• pp.65-74
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• 2018

The degree of compaction of embankments is generally measured using the sand replacement method or a soil density gauge. However, these methods include coarse particles, which are relatively large. The degree of compaction is overestimated if the in-situ soil density is simply compared with the density obtained from a Proctor compaction test (KS F 2312, 2001), because the density of coarse particles is higher than that of soil. However, there is no recommended correction for the coarse particle ratio in Korea, thus intentionally increasing the degree of compaction for structures to which large loads are applied or for which compaction is critical. Here, a correction considering the Korean Proctor compaction test and the difference between the maximum allowable particle sizes was recommended after corrections for coarse particle ratios in other countries were collected and analyzed. The degree of compaction was re-estimated by applying the recommended correction to the results of both Proctor compaction and sand replacement tests. The degree of compaction without the correction of coarse particle ratio was overestimated, because the re-estimated degree of compaction decreased as the coarse particle ratio increased. The relatively accurate results obtained from the field application of the correction will offer long-term cost savings due to reduced maintenance fees during operation.

• The Journal of Korean Society for Radiation Therapy
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• v.18 no.2
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• pp.89-96
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• 2006

Purpose: To study effectiveness of heterogeneity correction of internal-body inhomogeneities and patient positioning immobilizers in dose calculation, using images obtained from CT-Simulator. Materials and Methods: A water phantom($250{\times}250{\times}250mm^3$) was fabricated and, to simulate various inhomogeneity, 1) bone 2) metal 3) contrast media 4) immobilization devices(Head holder/pillow/Vac-lok) were inserted in it. And then, CT scans were peformed. The CT-images were input to Radiation Treatment Planning System(RTPS) and the MUs, to give 100 cGy at 10 cm depth with isocentric standard setup(Field Size=$10{\times}10cm^2$, SAD=100 cm), were calculated for various energies(4, 6, 10 MV X-ray). The calculated MUs based on various CT-images of inhomogeneities were compared and analyzed. Results: Heterogeneity correction factors were compared for different materials. The correction factors were $2.7{\sim}5.3%$ for bone, $2.7{\sim}3.8%$ for metal materials, $0.9{\sim}2.3%$ for contrast media, $0.9{\sim}2.3%$ for Head-holder, $3.5{\sim}6.9%$ for Head holder+pillow, and $0.9{\sim}1.5%$ for Vac-lok. Conclusion: It is revealed that the heterogeneity correction factor calculated from internal-body inhomogeneities have various values and have no consistency. and with increasing number of beam ports, the differences can be reduced to under 1%, so, it can be disregarded. On the other hand, heterogeneity correction from immobilizers must be regarded enough to minimize inaccuracy of dose calculation.

• Geophysics and Geophysical Exploration
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• v.21 no.2
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• pp.103-111
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• 2018

The recent research aim of seismic trace interpolation is to effectively interpolate the data with spatial aliasing. Among various interpolation methods, the Matching Pursuit interpolation, that finds the proper combination of basis functions which can best recover traces, has been developed. However, this method cannot interpolate aliased data. Thus, the multi-component Matching Pursuit interpolation and moveout correction method have been proposed for interpolation of spatially aliased data. It is difficult to apply the multi-component Matching Pursuit interpolation to interpolating the OBC (Ocean Bottom Cable) data which is the multi-component data obtained at the ocean bottom because the isolation of P wave component is required in advance. Thus, in this study, we dealt with an effective single-component matching Pursuit interpolation method in OBC data where P-wave and S-wave are mixed and spatial aliasing is present. To do this, we proposed the Ricker wavelet based single-component Matching Pursuit interpolation workflow with moveoutcorrection and systematically investigated its effectiveness. In this workflow, the spatial aliasing problem is solved by applying constant value moveout correction to the data before the interpolation is performed. After finishing the interpolation, the inverse moveout correction is applied to the interpolated data using the same constant velocity. Through the application of our workflow to the synthetic OBC seismic data, we verified the effectiveness of the proposed workflow. In addition, we showed that the interpolation of field OBC data with severe spatial aliasing was successfully performed using our workflow.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.277-283
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• 2021

Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.83-87
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• 2008

The purpose of this study is to get the correction factor to correct the measured values of the absolute absorbed dose proportional to the water equivalent depth. The measurement conditions in white polystyrene and water phantoms for 10MV X-ray beam are that the distance of source to center of ionization chamber is fixed at SAD 100 cm, the field sizes are $10{\times}10\;cm^2$, $20{\times}20\;cm^2$ and the depths are 2.3 cm, 5 cm, 10 cm, and 15 cm, respectively. The mean value of ionization was obtained by three times measurements in each field size and depths after delivering 100 MU from linear accelerator with output of 400 MU per min to the two phantoms. The correction factor and the percentage deviation in TPR were obtained below 0.97% and 0.53%, respectively. Therefore, we can get high accuracy by using the correction factor and the percentage deviation in TPR in measuring the absolute absorbed dose with the solid water equivalent phantom.

• Atmosphere
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• v.24 no.3
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• Journal of Wetlands Research
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• v.14 no.2
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• pp.243-254
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• 2012

Recently, the use of radar rainfall data that can help tracking of the development and movement of rainfall's spatial distribution is drawing much attention in hydrology. The reliability of existing radar rainfall compared to gauge rainfall data on the ground has not yet been confirmed and so we have difficulties to apply the radar rainfall in hydrology. The radar rainfall for the applications in hydrology are adjusted merging method derived from gage. This study uses the Mean-Field Bias (MFB) and Statistical Objective Analysis (SOA) as correction methods to create adjusted grid-based radar rainfall data which can represent the temporal and spatial distribution of rainfall. This study used a storm event occurred in August 2010 for the adjustment of radar rainfall. In addition, the grid-based distributed rainfall-runoff model (Vflo), which enables more detailed examinations of spatial flux changes in the basin rather than the lumped hydrological models, has been applied to Gamcheon river basin which is a tributary of Nakdong River located in south-eastern part of the Korean peninsular and the basin area is $1005km^2$. The simulated runoff was compared with the observed runoff in an attempt to evaluate the usability of radar rainfall data and the reliability of the correction methods. The error range of peak discharge using each correction method was within 20 percent and the efficiency of the model was between 60 and 80 percent. In particular, the SOA method showed better results than MFB method. Therefore, the SOA method could be used for the adjustment of grid-based radar rainfall and the adjusted radar rainfall can be used as an input data of rainfall-runoff models.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1149-1160
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• 2019

In this study, two radiometric correction methods deriving reflectance from UAV multispectral image for monitoring forest vegetation were applied and evaluated. Multispectral images were obtained from a small multispectral camera having 5 spectral bands. Reflectance were derived by applying the two methods: (1) the direct method using downwelling irradiance measurement and (2) the empirical line correction method by linking a set of field reflectance measured simultaneous with the image capture. Field reflectance were obtained using a spectroradiometer during the flight and used for building the linear equation for the empirical method and for the validation of image reflectance derived. Although both methods provided the high correlations between field reflectance and image-derived reflectance, their distributions were somewhat different. While the direct method provided rather stable and consistent distribution of reflectance all over the entire image area, the empirical method showed very unstable and inconsistent reflectance distribution. The direct method would be more appropriate for relatively wide area that requires more time to acquire image and may vary in downwelling irradiance and atmospheric conditions.