• Journal of the Korean Geophysical Society
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• v.4 no.4
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• pp.267-285
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• 2001

This study has tried to develop the modified DRASTIC Model by supplying the parameters,such as structural lineament density and landuse, into conventional DRASTIC medal, and to predict the potential of groundwater contamination using GIS in Whanam 2 Area, Gyeonggi Province, Korea. Since the aquifers in Korea is generally through the joints of rock-mass in hydrogeological environment, lineament denisity affects to the behavior of goundwater and contaminated plumes directly, and land-use reflect the effect of point or non-point source of contamination indirectly. For the statistical analysis, lattice layers of each parameter were generated, and then level of confidence was assessed by analyzing each correlation coefficient. Composite contamination map was achieved as a final result by comparing modified DRASTIC potential and the amount of generation load of several contaminant sources logically. The result could suggest the predictability of the area of contamination potrntial in the respects of hydrogeological aspect and water quality.

• Progress in Medical Physics
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• v.29 no.2
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• pp.66-72
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• 2018

The proper position of a multi-leaf collimator (MLC) is essential for the quality of intensity-modulated radiation therapy (IMRT) and volumetric modulated arc radiotherapy (VMAT) dose delivery. Task Group (TG) 142 provides a quality assurance (QA) procedure for MLC position. Our study investigated the QA validation of the mechanical leaf gap measurement and the maintenance procedure. Two $VitalBeam^{TM}$ systems were evaluated to validate the acceptance of an MLC position. The dosimetric leaf gaps (DLGs) were measured for 6 MV, 6 MVFFF, 10 MV, and 15 MV photon beams. A solid water phantom was irradiated using $10{\times}10cm^2$ field size at source-to-surface distance (SSD) of 90 cm and depth of 10 cm. The portal dose image prediction (PDIP) calculation was implemented on a treatment planning system (TPS) called $Eclipse^{TM}$. A total of 20 VMAT plans were used to confirm the accuracy of dose distribution measured by an electronic portal imaging device (EPID) and those predicted by VMAT plans. The measured leaf gaps were 0.30 mm and 0.35 mm for VitalBeam 1 and 2, respectively. The DLG values decreased by an average of 6.9% and 5.9% after mechanical MLC adjustment. Although the passing rates increased slightly, by 1.5% (relative) and 1.2% (absolute) in arc 1, the average passing rates were still within the good dose delivery level (>95%). Our study shows the existence of a mechanical leaf gap error caused by a degenerated MLC motor. This can be recovered by reinitialization of MLC position on the machine control panel. Consequently, the QA procedure should be performed regularly to protect the MLC system.

• Ocean Science Journal
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• v.42 no.3
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• pp.153-163
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• 2007

This study is based on a series of numerical modeling experiments to understand the tidal circulation in the Kangjin Bay (KB). The tidal circulation in the KB is mostly controlled by the inflow from two channels, Noryang and Daebang which introduce the open ocean water into the northern part of the KB with relatively strong tidal current, while in the southern part of the KB, shallowest region of the entire study area, weak tidal current prevails. The model prediction of the sea level agrees with observed records at skill scores exceeding 90 % in terms of the four major tidal constituents (M2, S2, K1, O1). However, the skill scores for the tidal current show relatively lower values of 87, 99, 59, 23 for the semi-major axes of the constituents, respectively. The tidal ellipse parameters in the KB are such that the semi-major axes of the ellipse for M2 range from 1.7 to 38.5 cm/s and those for S2 range from 0.5 to 14.4 cm/s. The orientations of the major-axes show parallel with the local isobath. The eccentricity values at various grid points of ellipses for M2 and S2 are very low with 0.2 and 0.06 on the average, respectively illustrating that the tidal current in the KB is strongly rectilinear. The magnitude of the tidal residual current speed in the KB is on the order of a few cm/s and its distribution pattern is very complex. One of the most prominent features is found to be the counter-clockwise eddy recirculation cell at the mouth of the Daebang Channel.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.3-12
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• 2007

The purpose of this paper is to analyze the relationship between meteorological factors and agricultural reservoir storage, and predict the reservoir storage by multiple regression equation selected by high correlated meteorological factors. Two agricultural reservoirs (Geumgwang and Gosam) located in the upsteam of Gongdo water level gauging station of Anseong-cheon watershed were selected. Monthly reservoir storage data and meteorological data in Suwon weather station of 21 years (1985-2005) were collected. Three cases of correlation (case 1: yearly mean, case 2: seasonal mean dividing a year into 3 periods, and case 3: lagging the reservoir storage from 1 month to 3 months under the condition of case 2) were examined using 8 meteorological factors (precipitation, mean/maximum/minimum temperature, relative humidity, sunshine hour, wind velocity and evaporation). From the correlation analysis, 4 high correlated meteorological factors were selected, and multiple regression was executed for each case. The determination coefficient ($R^{2}$) of predicted reservoir storage for case 1 showed 0.45 and 0.49 for Geumgwang and Gosam reservoir respectively. The predicted reservoir storage for case 2 showed the highest $R^{2}$ of 0.46 and 0.56 respectively in the period of April to June. The predicted reservoir storage for 1 month lag of case 3 showed the $R^{2}$ of 0.68 and 0.85 respectively for the period of April to June. The results showed that the status of agricultural reservoir storage could be expressed with couple of meteorological factors. The prediction enhanced when the storage data are divided into periods rather than yearly mean and especially from the beginning time of paddy irrigation (April) to high decrease of reservoir storage (June) before Jangma.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.17-28
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• 2004

This study has tried to develop the modified DRASTIC Model by supplying the parameters, such as structural lineament density and land-use, into conventional DRASTIC model, and to predict the potential of groundwater contamination using GIS in Hwanam 2 District, Gyeonggi Province, Korea. Since the aquifers in Korea is generally through the joints of rock-mass in hydrogeological environment, lineament density affects to the behavior of groundwater and contaminated plumes directly, and land-use reflect the effect of point or non-point source of contamination indirectly. For the statistical analysis, lattice-layers of each parameter were generated, and then level of confidence was assessed by analyzing each correlation coefficient. Groundwater contamination potential map was achieved as a final result by comparing modified DRASTIC potential and the amount of pollutant load logically. The result suggest the predictability of contamination potential in a specified area in the respects of hydrogeological aspect and water quality.

• Journal of Radiation Protection and Research
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• v.30 no.1
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• pp.45-54
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• 2005

A dynamic compartment model was developed to appraise the level of the contamination of agricultural plants by accidentally released tritium from nuclear facility. The model consists of a set of inter-connected compartments representing atmosphere, soil and plant. In the model three categories of plant are considered: leafy vegetables, grain plants and tuber plants, of which each is modeled separately to account for the different transport pathways of tritium. The predictive accuracy of the model was tested through the analysis of the tritium exposure experiments for rice-plants. The predicted TFWT(tissue free water tritium) concentration of the rice ear at harvest was greatly affected by the absolute humidity of air, the ratio of root uptake, and the rate of rainfall, while its OBT(organically bound tritium) concentration the stowing period of the ear, the absolute humidity of air and the content of hydrogen in the organic phase. There was a good agreement between the model prediction and the experimental results lot the OBT concentration of the ear.

• Nuclear Engineering and Technology
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• v.21 no.2
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• pp.73-88
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• 1989

Ten methods of the total two-phase pressure drop prediction based on five existing models and correlations have been examined for their accuracy and applicability to pressurized water reactor conditions. These methods were tested against 209 experimental data of local and bulk boiling conditions : Each correlations were evaluated for different ranges of pressure, mass velocity and Quality, and best performing models were identified for each data subsets. A computer code entitled 'K-TWOPD' has been developed to calculate the total two-phase pressure drop using the best performing existing correlations for a specific property range and a correction factor to compensate for the predicted error of the selected correlations. Assessment of this code shows that the present method fits all the available data within $\pm$11% at a 95% confidence level compared with $\pm$25%, for the existing correlations.

• The Journal of Engineering Research
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• v.5 no.1
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• pp.89-107
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• 2004

This study has tried to develop the modified DRASTIC Model by supplying the parameters, such as structural lineament density and landuse, into conventional DRASTIC model, and to predict the potential of groundwater contamination using GIS in Whanam 2 Area, Gyeonggi Province, Korea. Since the aquifers in Korea is generally through the joints of rock-mass in hydrogeological environment, lineament density affects to the behavior of groundwater and contaminated plumes directly, and land-use reflect the effect of point or non-point source of contamination indirectly. For the statistical analysis, lattice layers of each parameter were generated, and then level of confidence was assessed by analyzing each correlation coefficient. Composite contamination map was achieved as a final result by comparing modified DRASTIC potential and the amount of generation load of several contaminant sources logically. The result could suggest the predictability of the area of contamination potential on the respects of hydrogeological aspect and water quality.

• Membrane and Water Treatment
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• v.9 no.2
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• pp.115-121
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• 2018

Artificial neural network (ANN) simulation is used to predict the dynamic change of permeate flux during wheat starch industry wastewater microfiltration with and without static turbulence promoter. The experimental program spans range of a sedimentation times from 2 to 4 h, for feed flow rates 50 to 150 L/h, at transmembrane pressures covering the range of $1{\times}10^5$ to $3{\times}10^5Pa$. ANN predictions of the wastewater microfiltration are compared with experimental results obtained using two different set of microfiltration experiments, with and without static turbulence promoter. The effects of the training algorithm, neural network architectures on the ANN performance are discussed. For the most of the cases considered, the ANN proved to be an adequate interpolation tool, where an excellent prediction was obtained using automated Bayesian regularization as training algorithm. The optimal ANN architecture was determined as 4-10-1 with hyperbolic tangent sigmoid transfer function transfer function for hidden and output layers. The error distributions of data revealed that experimental results are in very good agreement with computed ones with only 2% data points had absolute relative error greater than 20% for the microfiltration without static turbulence promoter whereas for the microfiltration with static turbulence promoter it was 1%. The contribution of filtration time variable to flux values provided by ANNs was determined in an important level at the range of 52-66% due to increased membrane fouling by the time. In the case of microfiltration with static turbulence promoter, relative importance of transmembrane pressure and feed flow rate increased for about 30%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.341-346
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• 2022

Due to global warming and abnormal climate, the frequency and damage of floods are increasing, and the number of people exposed to flood-prone areas has increased by 25% compared to 2000. Floods cause huge financial and human losses, and in order to reduce the losses caused by floods, it is necessary to predict the flood in advance and decide to evacuate quickly. This paper proposes a flood risk determination model using a CNN-based classification model so that timely evacuation decisions can be made using rainfall and water level data, which are key data for flood prediction. By comparing the results of the CNN-based classification model proposed in this paper and the DNN-based classification model, it was confirmed that it showed better performance. Through this, it is considered that it can be used as an initial study to determine the risk of flooding, determine whether to evacuate, and make an evacuation decision at the optimal time.