• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1187-1198
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• 2008

Many reservoirs in Korea and their downstream environments are under increased pressure for water utilization and ecosystem management from longer discharge of turbid flood runoff compared to a natural river system. Turbidity($C_T$) is an indirect measurement of water 'cloudiness' and has been widely used as an important indicator of water quality and environmental "health". However, $C_T$ modeling studies have been rare due to lack of experimental data that are necessary for model validation. The objective of this study is to validate a coupled three-dimensional(3D) hydrodynamic and particle dynamics model (ELCOM-CAEDYM) for the simulation of turbid density flows in stratified Daecheong Reservoir using extensive field data. Three different groups of suspended solids (SS) classified by the particle size were used as model state variables, and their site-specific SS-$C_T$ relationships were used for the conversion between field measurements ($C_T$) and state variables (SS). The simulation results were validated by comparing vertical profiles of temperature and turbidity measured at monitoring stations of Haenam(R3) and Dam(R4) in 2004. The model showed good performance in reproducing the reservoir thermal structure and propagation of stream density flow, and the magnitude and distribution of turbidity in the reservoir were consistent with the field data. The 3D model and turbidity modeling framework suggested in this study can be used as a supportive tool for the best management of turbidity flow in other reservoirs that have similar turbidity problems.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1249-1263
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• 2013

In order to minimize the damages caused by long-term drought, appropriate drought management plans of the basin should be established with the drought forecasting technology. Further, in order to build reasonable adaptive measurement for future drought, the duration and severity of drought must be predicted quantitatively in advance. Thus, this study, attempts to forecast drought in Korea by using an Artificial Neural Network Model, and drought index, which are the representative statistical approach most frequently used for hydrological time series forecasting. SPI (Standardized Precipitation Index) for major weather stations in Korea, estimated using observed historical precipitation, was used as input variables to the MLP (Multi Layer Perceptron) Neural Network model. Data set from 1976 to 2000 was selected as the training period for the parameter calibration and data from 2001 to 2010 was set as the validation period for the drought forecast. The optimal model for drought forecast determined by training process was applied to drought forecast using SPI (3), SPI (6) and SPI (12) over different forecasting lead time (1 to 6 months). Drought forecast with SPI (3) shows good result only in case of 1 month forecast lead time, SPI (6) shows good accordance with observed data for 1-3 months forecast lead time and SPI (12) shows relatively good results in case of up to 1~5 months forecast lead time. The analysis of this study shows that SPI (3) can be used for only 1-month short-term drought forecast. SPI (6) and SPI (12) have advantage over long-term drought forecast for 3~5 months lead time.

• Journal of the Korean Geotechnical Society
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• v.40 no.2
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• pp.29-40
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• 2024

This study aimed to evaluate the swelling behavior characteristics of KJ-II buffer blocks by performing numerical analysis of swelling pressure measurement experiments using the nonlinear elasticity model of COMSOL Multiphysics. The analysis was conducted under boundary conditions that included isotropic constraints and water injection pressure, mirroring the experimental settings. Validation of the numerical model was achieved by comparing its outputs with experimental results. The validated model was then used to simulate swelling deformations under unconfined conditions and to analyze swelling pressure as influenced by dry density and the geometric shape of the buffer material. The results accurately represented the swelling deformation observed during the saturation process and demonstrated that swelling pressure increases with higher dry density. Moreover, simulations concerning the geometric shape of the buffer material indicated a markedly faster rate of pressure increase in U-shaped samples compared to cylindrical ones. Analysis suggested that stress manifested preemptively near the internal edges of U-shaped samples during saturation. To enhance the simulation's fidelity to actual buffer material behavior, further refinement of the analysis model using a nonlinear elasticity model is recommended.

• Food Science of Animal Resources
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• v.38 no.5
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• pp.1109-1119
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• 2018

In this paper, we report the development of a nondestructive prediction model for lean meat percentage (LMP) in Korean pig carcasses and in the major cuts using a machine vision technique. A popular vision system in the meat industry, the VCS2000 was installed in a modern Korean slaughterhouse, and the images of half carcasses were captured using three cameras from 175 selected pork carcasses (86 castrated males and 89 females). The imaged carcasses were divided into calibration (n=135) and validation (n=39) sets and a multilinear regression (MLR) analysis was utilized to develop the prediction equation from the calibration set. The efficiency of the prediction equation was then evaluated by an independent validation set. We found that the prediction equation - developed to estimate LMP in whole carcasses based on six variables - was characterized by a coefficient of determination ($R^2_v$) value of 0.77 (root-mean square error [RMSEV] of 2.12%). In addition, the predicted LMP values for the major cuts: ham, belly, and shoulder exhibited $R^2_v$ values${\geq}0.8$ (0.73 for loin parts) with low RMSEV values. However, lower accuracy ($R^2_v=0.67$) was achieved for tenderloin cuts. These results indicate that the LMP in Korean pig carcasses and major cuts can be predicted successfully using the VCS2000-based prediction equation developed here. The ultimate advantages of this technique are compatibility and speed, as the VCS2000 imaging system can be installed in any slaughterhouse with minor modifications to facilitate the on-line and real-time prediction of LMP in pig carcasses.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• Journal of radiological science and technology
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• v.40 no.3
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• pp.469-484
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• 2017

Radiological Technologists deals with the life of a person which means professional competency is essential for the job. Nevertheless, there have been no studies in Korea that identified the job competence of radiologists. In order to define the core job competencies of Korean radiologists and to present the factor models, 147 questionnaires on job competency of radiology were analyzed using 'PASW Statistics Version 18.0' and 'AMOS Version 18.0'. The valid model consisted of five core job competencies ('Patient management', 'Health and safety', 'Operation of equipment', 'Procedures and management') and 17 sub - competencies. As a result of the factor analysis, the RMSEA value was 0.1 and the CFI, and TLI values were close to 0.9 in the measurement model of the five core job competencies. The validity analysis showed that the mean variance extraction was 0.5 or more and the conceptual reliability value was 0.7 or more, And there was a high correlation between subordinate competencies included in each subordinate competencies. The results of this study are expected to provide specific information necessary for the training and management of human resources centered on competence by clearly showing the job competence required for radiologists in Korea's health environment.

• Journal of the Korean earth science society
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• v.44 no.4
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• pp.318-330
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• 2023

This study aimed to verify the validity of a measurement tool for Vietnamese high school students' systems thinking abilities. Two quantitative assessment tools, the Systems Thinking Measuring Instrument (Lee et al., 2013) and the Systems Thinking Scale (Dolansky et al., 2020), were used to measure students' systems thinking after translation into Vietnamese. As a result, it was revealed that Cronbach-α for each tool (i.e., STMI and STS) was .917 and .950, respectively, indicating high reliability for both. To validate the construct validity of the translated questionnaire, exploratory factor analysis was performed using SPSS 26.0, and confirmatory factor analysis was performed using AMOS 21.0. For concurrent validity, correlation analysis using structural equation modeling was performed to validate the translated questionnaire. Exploratory factor analysis revealed that 10 items from the STMI and 12 items from the STS loaded on the intended factors and appropriate factor loading values were obtained. For confirmatory factor analysis, a structural equation model organized with 10 items from the STMI and 12 items from the STS was used. The result of this showed that the convergent validity values of the model were all appropriate, and the model fit indices were analyzed to be χ²/df of 1.892, CFI of .928, TLI of .919, SRMR of .047, and RMSEA of .063, indicating that the model consisting of the 22 items of the two questionnaires was appropriate. Analysis of the concurrent validity of the two tools indicated a high correlation coefficient (.903) and high correlation (.571-.846) among the subfactors. In conclusion, both the STMI and STS are valid quantitative measures of systems thinking, and it can be inferred that the systems thinking of Vietnamese high-school students can be quantitatively measured using the 22 items identified in our analysis. Using the tool validated in this study with other tools (e.g., qualitative assessment) can help accurately measure Vietnamese high school students' systems thinking abilities. Furthermore, these tools can be used to collect evidence and support effective education in ODA projects and volunteer programs.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.11
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• pp.1529-1540
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• 2011

Silencing of a specific gene using RNAi (RNA interference) is a valuable tool for functional analysis of a target gene. However, information on RNAi for analysis of gene function in farm animals is relatively nil. In the present study, we have validated the interfering effects of siRNA (small interfering RNA) using both quantitative and qualitative gene silencing in buffalo granulosa cells. Qualitative gene knockdown was validated using a fluorescent vector, enhanced green fluorescence protein (EGFP) and fluorescently labeled siRNA (Cy3) duplex. While quantitatively, siRNA targeted against the luciferase and CYP19 mRNA was used to validate the technique. CYP19 gene, a candidate fertility gene, was selected as a model to demonstrate the technique optimization. However, to sustain the expression of CYP19 gene in culture conditions using serum is difficult because granulosa cells have the tendency to luteinize in presence of serum. Therefore, serum free culture conditions were optimized for transfection and were found to be more suitable for the maintenance of CYP19 gene transcripts in comparison to culture conditions with serum. Decline in fluorescence intensity of green fluorescent protein (EGFP) was observed following co-transfection with plasmid generating siRNA targeted against EGFP gene. Quantitative decrease in luminescence was seen when co-transfected with siRNA against the luciferase gene. A significant suppressive effect on the mRNA levels of CYP19 gene at 100 nM siRNA concentration was observed. Also, measurement of estradiol levels using ELISA (enzyme-linked immunosorbent assay) showed a significant decline in comparison to control. In conclusion, the present study validated gene silencing using RNAi in cultured buffalo granulosa cells which can be used as an effective tool for functional analysis of target genes.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.5
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• pp.499-509
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• 2000

Next to carbon dioxide, methane is the second largest contributor to global warming among anthropogenic greenhouse gases. Methane is emitted into the atmosphere from both natural and anthropogenic sources. Natural sources include wetlands, termites, wildries, ocean and freshwater. Anthropogenic sources include landfill, natural gas and oil production, and agriculture. These manmade sources account for about 70% of total global methane emissions; and among these, landfill accounts for approximately 10% of total manmade emissions. Solid waste landfills produce methane as bacteria decompose organic wastes under anaerobic conditions. Methane accounts for approximately 45 to 50 percent of landfill gas, while carbon dioxide and small quantities of other gases comprise the remaining to 50 to 55 percent. Using the closed enclosure technique, surface emission fluxes of methane from the selected landfill sites were measured. These data were used to estimate national methane emission rate from domestic landfills. During the three different periods, flux experiments were conducted at the sites from June 30 through December 26, 1999. The chamber technique employed for these experiments was validated in situ. Samples were collected directly by on-site flux chamber and analyzed for the variation of methane concentration by gas chromatography equipped with FID. Surface emission rates of methane were found out to vary with space and time. Significant seasonal variation was observed during the experimental period. Methane emission rates were estimated to be 64.5$\pm$54.5mgCH$_4$/$m^2$/hr from Kimpo landifll site. 357.4$\pm$68.9mgCH$_4$/$m^2$/hr and 8.1$\pm$12.4mgCH$_4$/$m^2$/hr at KwanJu(managed and unmanaged), 472.7$\pm$1056mgCH$_4$/$m^2$/hr at JonJu, and 482.4$\pm$1140 mgCH$_4$/$m^2$/hr at KunSan. These measurement data were used for the extrapolation of national methane emission rate based on 1997 national solid waste data. The results were compared to those derived by theoretical first decay model suggested by IPCC guidelines.

• Korean Journal of Social Welfare
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• v.67 no.3
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• pp.151-180
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• 2015

This study aimed to develop a scale to measure physical health behaviors among social work clients using general services. The scale items were constructed based on literature review and FGI of social workers. Exploratory factor analysis and confirmative factor analysis affirmed the factor structure of Physical Health Behavior Scale with two sub-scales: Health Promotion Behavior Scale and Health Hindrance Behavior Scale. Promotion Scale had 7 factors and Hindrance Scale had 5 factors. Both sub-scales showed acceptable ranged goodness-of-fit for the model, and internal consistency test proved that the scale was reliable. The analyses of discriminant validity, convergent validity, and concurrent validity resulted significant validation. Based on those results, the developed Physical Health Behavior Scale were proved well-constructed, reliable and valid. The Scale will be utilized for both clients in general to check their own health related behaviors and social workers to adopt as a tool for assessment in order to perform an evidence based practice.