• Journal of Soil and Groundwater Environment
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• v.13 no.5
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• pp.57-73
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• 2008

Nitrate concentrations were measured up to 49 mg/L (as $NO_3$-N) and 22% of the samples exceeded drinking water standard in shallow and bedrock groundwater of the northern Nonsan area. Nitrate concentrations showed a significant difference among land use groups. To predict nitrate concentration in groundwater, multiple regression analysis was carried out using hydrogeologic parameters of soil media, topography and land use which were categorized as several groups, well depth and altitude, and field parameters of temperature, pH, DO and EC. Hydrogeologic parameters were quantified as area proportions of each category within circular buffers centering at wells. Regression was performed to all the combination of variables and the most relevant model was selected based on adjusted coefficient of determination (Adj. $R^2$). Regression using hydrogelogic parameters with varying buffer radii show highest Adj. $R^2$ at 50m and 300m for shallow and bedrock groundwater, respectively. Shallow groundwater has higher Adj. $R^2$ than bedrock groundwater indicating higher susceptibility to hydrogeologic properties of surface environment near the well. Land use and soil media was major explanatory variables for shallow and bedrock groundwater, respectively and residential area was a major variable in both shallow and bedrock groundwater. Regression involving hydrogeologic parameters and field parameters showed that EC, paddy and pH were major variables in shallow groundwater whereas DO, EC and natural area were in bedrock groundwater. Field parameters have much higher explanatory power over the hydrogeologic parameters suggesting field parameters which are routinely measured can provide important information on each well in assessment of nitrate contamination. The most relevant buffer radii can be applied to estimation of travel time of contaminants in surface environment to wells.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.496-503
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• 2016

To analyze an infinite slope that is reinforced with stabilizing piles, the forces on the stabilizing pile were estimated by the theory of plastic deformation and the theory of plastic flow and the effects of diverse factors on the factor of safety of an infinite slope were investigated. According to the results of the analyses, the factor of the safety of the slope reinforced with stabilized piles were increased tremendously and the factor of safety decreased as the center to center distance of the stabilizing pile increased. The effect of the existence of seepage of the infinite slope with stabilizing piles on the factor of safety appears to be insignificant. Considering the formulated factor of safety of an infinite slope with stabilizing piles, the width and length of the element of the infinite slope and force on the stabilizing pile influence the factor of safety of the infinite slope with a stabilizing pile including the soil strength parameter, inclination of the slope and depth of the slope, which are important for calculating the factor of safety of a non-reinforced infinite slope. The factor of safety of an infinite slope with stabilizing piles derived from the theory of plastic deformation were increased significantly with the internal friction angle of the soil, and the minimum and the maximum factor of safety under the conditions considered in this study were 13.7 and 65.6, respectively. As the diameter of the stabilizing pile increased, the forces on the stabilizing pile also increased but the factor of safety of the infinite slope with stabilizing piles decreased due to the effects of the width and the length of the element of the infinite slope. The factor of safety of the infinite slope with stabilizing piles derived from plastic flow were much larger than that of the non-reinforced infinite slope and the factor safety of the infinite slope with a stabilizing pile increased with increasing product of the flow velocity and plastic viscosity ( ) and the factor of safety of the infinite slope with stabilizing piles decreased with increasing center to center distance of the pile.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.1
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• pp.26-34
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• 2009

Purpose: The purpose of this study was to find out what clinicopathologic or immunohistochemical parameter that may affect FDG uptake of primary tumor in PET/CT scan of the gastric carcinoma patient. Materials and Methods: Eighty-nine patients with stomach cancer who underwent pre-operative FDG PET/CT scans were included. In cases with perceptible FDG uptake in primary tumor, the maximum standardized uptake value (SUVmax) was calculated. The clinicopathologic results such as depth of invasion (T stage), tumor size, lymph node metastasis, tumor differentiation and Lauren's classification and immunohistochemical markers such as Ki-67 index, expression of p53, EGFR, Cathepsin D, c-erb-B2 and COX-2 were reviewed. Results: Nineteen out of 89 gastric carcinomas showed imperceptible FDG uptake on PET/CT images. In cases with perceptible FDG uptake in primary tumor, SUVmax was significantly higher in T2, T3 and T4 tumors than T1 tumors ($5.8{\pm}3.1$ vs. $3.7{\pm}2.1$, p=0.002). SUVmax of large tumors (above or equal to 3 cm) was also significantly higher than SUVmax of small ones (less than 3 cm) ($5.7{\pm}3.2$ vs. $3.7{\pm}2.0$, p=0.002). The intestinal types of gastric carcinomas according to Lauren showed higher FDG uptake compared to the non-intestinal types ($5.4{\pm}2.8$ vs. $3.7{\pm}1.3$, p=0.003). SUVmax between p53 positive group and negative group was significantly different ($6.0{\pm}2.8$ vs. $4.4{\pm}3.0$, p=0.035). No significant difference was found in presence of LN metastasis, tumor differentiation, Ki-67 index, and expression of EGFR, Cathepsin D, c-erb-B2 and COX-2. Conclusion: T stage of gastric carcinoma influenced the detectability of gastric cancer on FDG PET PET/CT scan. When gastric carcinoma was perceptible on PET/CT scan, T stage, size of primary tumor, Lauren's classification and p53 expression were related to degree of FDG uptake in primary tumor.

• Korean Journal of Environmental Agriculture
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• v.26 no.4
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• pp.343-350
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• 2007

Three different experiments were carried out to investigate the runoff and erosion losses of endosulfan from sloped-field by rainfall. The mobility of endosulfan and which phase it was transported by were examined in adsorption study, the influence of rainfall pattern and slope degree on the pesticide loss were evaluated in simulated rainfall study, and the pesticide losses from soybean-grown field comparing with bare soil were measured in field lysimeter study. Adsorption parameter (K) of endosulfan ranged from 77 to 131 by adsorption method and K values by the desorption method were higher than those by the adsorption method. By the SSLRC's classification for pesticide mobility endosulfan was classified as non-mobile class ($K_{oc}>4,000$). Runoff and erosion loss of endosulfan by three rainfall scenarios ranged from 3.4 to 5.6%and from 4.4 to 15.6%of the amount treated. Endosulfan residues were mainly remained at the top 5 cm of soil depth after the simulated rainfall study. Pesticide loss in case of 30%-slope degree ranged from 0.6 to 0.9 times higher than those in case of 10%-slope degree. The difference of pesticide runoff loss was related with its concentration in runoff water and the difference of pesticide erosion loss would related closely with the quantity of soil eroded. Endosulfan losses from a series of lysimeter plots in sloped land by rainfall ranged from 5 to 35% of the amount treated. The erosion rate of endosulfan from soybean-plots was 66% of that from bare soil plots. The effect of slope conditions was not great for runoff loss, but was great for erosion loss as increasing to maximum $4{\sim}12$ times with slope degree and slope length. The peak runoff concentration of endosulfan in soybean-plots and bare soil plots ranged from 8 to 10 and from 7 to $9{\mu}gL^{-1}$ on nine plots with different slope degree and slope length. Therefore the difference of the peak runoff concentrations between bare soil plots and soybean-plots were not great.

• Journal of radiological science and technology
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• v.29 no.1
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• pp.1-6
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• 2006

Purpose: Renal stones are common and typically arise within the collecting system. The renal sinus are contains the collection system, the renal vessels, lymphatcs, fat, and fibrous tissue. Because of the compression of all the large echoes in signal processing, the echo from the renal stone generally cannot be distinguished from large echoes emanating from normal structures of the renal sinus. Use of ultrasonography has been difficult for detecting small renal stone without posterior shadowing and chemical composition of stone. The aim of study was measuring for posterior acoustic shadowing to a stone for various scan parameter and it examines a help in renal stone diagnosis. Material & Methods: The stone was place on sponge examined in a water bath with a 3.5MHz or 7.5MHz transducer(LOGIQ 400, USA). First, tested a variety of gain. Second, tested a variety of dynamic range. Third, tested a variety of focal zone. Fourth, measuring of the echo level for low and high frequency for depth. Results: 1) Average echo level was 98 for low total gain(10 dB) and was 142 for high total gain(40 dB). Posterior acoustic shadowing of renal stone was clear for low gain. 2) Average echo level was 129 for low dynamic range(42 dB) and was 101 for high dynamic range(72 dB). Posterior acoustic shadowing of renal stone was clear for high dynamic range. 3) When stone is in focal zone of transducer, definite posterior acoustic shadow is identified. 4) Stone was clear appeared for high frequency(7.5 MHz) than low frequency(3.5 MHz) and it is not distorted. Conclusion: The demonstration of an posterior acoustic shadow of renal stone dependents on several technical factors such as gain, dynamic range, focus, and frequency. This various factors are a help in renal stone diagnosis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.77-89
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• 2004

The spatial and temporal variations of aerosol optical depth (AOD) over Northeast Asia regions have special importance in the aerosol research for estimation of aerosol radiative forcing parameters and climate change. Aerosol optical and physical properties (AOD and ${\AA}$ngstrom parameter) have been investigated by using Moderate Resolution Imaging Spectroradiometer (MODIS) and Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) to estimate aerosol characteristics over the study region during 2001. Additionally, aerosol characteristics over the Korean peninsular during Aerosol Characteristic Experiment in Asia (ACE-Asia) Intensive Observation Period (IOP) have been investigated by using satellite observations. The results showed that the daily-observed aerosol data indicate seasonal variations with relatively higher aerosol loading in the spring and very low during the winter. The typical Asian dust case showed higher AOD (>0.7) with lower Angstrom exponent (<0.5) and higher AI (>0.5) that is mainly due to the composition of coarse particles in the springtime. Mean AOD for 2001 at 4 different places showed 0.65$\pm$0.37 at Beijing, 0.31$\pm$0.19 at Gosan, 0.54$\pm$0.26 at Seoul, and 0.38$\pm$0.19 at Kwangju, respectively. An interesting result was found in the present study that polluted aerosol events with small size dominated-aerosol loading around the Korean peninsular are sometimes observed. The origin of these polluted aerosols was thought to East China. Aerosol distribution from satellite images and trajectory results shows the proof of aerosol transport. Therefore, aerosol monitoring using satellite data is very useful.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.105-119
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• 2023

Water supply is decreasing due to climate change, and coastal and island regions are highly dependent on groundwater, reducing the amount of available water. For sustainable water supply in coastal and island regions, it is necessary to accurately diagnose the current condition and efficiently distribute and manage water. For a precise analysis of the groundwater flow in the coastal island region, submarine fresh groundwater discharge was calculated for the Seongsan basin in the eastern part of Jeju Island. Two methods were used to estimate the thickness of the fresh groundwater. One method employed vertical interpolation of measured electrical conductivity in a multi depth monitoring well; the other used theoretical Ghyben-Herzberg ratio. The value using the Ghyben-Herzberg ratio makes it impossible to accurately estimate the changing salt-saltwater interface, and the value analyzed by electrical conductivity can represent the current state of the freshwater-saltwater interface. Observed parameter was distributed on a virtual grid. The average of submarine fresh groundwater discharge fluxes for the virtual grid was determined as the watershed's representative flux. The submarine fresh groundwater discharge and flux distribution by year were also calculated at the basin scale. The method using electrical conductivity estimated the submarine fresh groundwater discharge from 2018 to 2020 to be 6.27 × 10⁶ m³/year; the method using the Ghyben-Herzberg ratio estimated a discharge of 10.87 × 10⁶ m³/year. The results presented in this study can be used as basis data for policies that determine sustainable water supply by using precise water budget analysis in coastal and island areas.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.94-100
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• 2010

Purpose: We can evaluate function of kidney by Glomerular Filtration Rate (GFR) test using $^{99m}Tc$-DTPA which is simple. This test is influenced by several parameter such as net syringe count, kidney depth, corrected kidney count, acquisition time and characters of gamma camera. In this study, we evaluated predose count according to matrix size in the GFR test using $^{99m}Tc$-DTPA. Materials and Methods: Gamma camera of Infinia in GE was used, and LEGP collimator, three types of matrix size ($64{\times}64$, $128{\times}128$, $256{\times}256$) and 1.0 of zoom factor were applied. We increased radioactivity concentration from 222 (6), 296 (8), 370 (10), 444 (12) up to 518 MBq (14 mCi) respectively and acquired images according to matrix size at 30 cm distance from detector. Lastly, we evaluated these values and then substituted them for GFR formula. Results: In $64{\times}64$, $128{\times}128$ and $256{\times}256$ of matrix size, counts per second was 26.8, 34.5, 41.5, 49.1 and 55.3 kcps, 25.3, 33.4, 41.0, 48.4 and 54.3 kcps and 25.5, 33.7, 40.8, 48.1 and 54.7 kcps respectively. Total counts for 5 second were 134, 172, 208, 245 and 276 kcounts from $64{\times}64$, 127, 172, 205, 242, 271 kcounts from $128{\times}128$, and 137, 168, 204, 240 and 273 kcounts from $256{\times}256$, and total counts for 60 seconds were 1,503, 1,866, 2,093, 2,280, 2,321 kcounts, 1,511, 1,994, 2,453, 2,890 and 3,244 kcounts, and 1,524, 2,011, 2,439, 2,869 and 3,268 kcounts respectively. It is different from 0 to 30.02 % of percentage difference in $64{\times}64$ of matrix size. But in $128{\times}128$ and $256{\times}256$, it is showed 0.60 and 0.69 % of maximum value each. GFR of percentage difference in $64{\times}64$ represented 6.77% of 222 MBq (6 mCi), 42.89 % of 518 MBq (14 mCi) at 60 seconds respectively. However it is represented 0.60 and 0.63 % each in $128{\times}128$ and $256{\times}256$. Conclusion: There was no big difference in total counts of percentage difference and GFR values acquiring from $128{\times}128$ and $256{\times}256$ of matrix size. But in $64{\times}64$ of matrix size when the total count exceeded 1,500 kcounts, the overflow phenomenon was appeared differently according to predose radioactivity of concentration and acquisition time. Therefore, we must optimize matrix size and net syringe count considering the total count of predose to get accurate GFR results.