• Journal of the Korean Geotechnical Society
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• v.23 no.9
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• pp.5-16
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• 2007

The simple linear elastic-perfectly plastic model with soil parameters $s_u,\;E_u$ and n of undrained condition is usually applied to predict the displacement of a constructed diaphragm wall(DW) on soft soils during excavation. However, the application of this soil model for finite element analysis could not interpret the continued increment of the lateral displacement of the DW for the large and deep excavation area both during the elapsed time without activity of excavation and after finishing excavation. To study the characteristic behaviors of soil behind the DW during the periods without excavation, a series of tests on soft Bangkok clay samples are simulated in the same manner as stress condition of soil elements happening behind diaphragm wall by triaxial tests. Three kinds of triaxial tests are carried out in this research: $K_0$ consolidated undrained compression($CK_0U_C$) and $K_0$ consolidated drained/undrained unloading compression with periodic decrement of horizontal pressure($CK_0DUC$ and $CK_0UUC$). The study shows that the shear strength of series $CK_0DUC$ tests is equal to the residual strength of $CK_0UC$ tests. The Young's modulus determined at each decrement step of the horizontal pressure of soil specimen on $CK_0DUC$ tests decreases with increase in the deviator stress. In addition, the slope of Critical State Line of both $CK_0UC$ and $CK_0DUC$ tests is equal. Moreover, the axial and radial strain rates of each decrement of horizontal pressure step of $CK_0DUC$ tests are established with the function of time, a slope of critical state line and a ratio of deviator and mean effective stress. This study shows that the results of the unloading compression triaxial tests can be used to predict the diaphragm wall deflection during excavation.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.83-94
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• 1998

To have a basic idea on the spectral reflectance signature in paddy rice canopy, we measured spectral reflectance from paddy rice canopy(Ilpumbyeo) using spectroradiometer (GER Inc. SFOV : 0.35~2.50 ${\mu}{\textrm}{m}$) in situ weekly or biweekly from transplanting to ripening stage. Spectral reflectance of the visible range (0.4~0.7 ${\mu}{\textrm}{m}$) was decreased to below 5% and then slightly increased again after heading stage in rice canopy. Meanwhile spectral reflectance of the near-infrared range (0.7~1.1 ${\mu}{\textrm}{m}$) was increased to 40~50% and then decreased a great deal after panicle initiation stage in rice canopy. Landsat TM equivalent band set ($\bar{p}$$_{TMi}$) was created by averaging spectral reflectance values to the real TM bands. Correlation analysis between the rice crop variables (LAI, total dry matter) and TM equivalent band set ($\bar{p}$$_{TMi}$) showed that LAI and total dry matter of rice were highly correlated with visible bands such as $\bar{p}$$_{TM1}$, $\bar{p}$$_{TM2}$, and $\bar{p}$$_{TM3}$. Ratio values ($\bar{p}$$_{TMi}$/$\bar{p}$$_{TMi}$) such as $\bar{p}$$_{TM4}$/$\bar{p}$$_{TM2}$ were also highly correlated with rice crop variables such as LAI and total dry matter.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.21-36
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• 2019

Dead fuel moisture content is a key variable in fire danger rating as it affects fire ignition and behavior. This study evaluates simple regression models estimating the moisture content of standardized 10-h fuel stick (10-h FMC) at three sites with different characteristics(urban and outside/inside the forest). Equilibrium moisture content (EMC) was used as an independent variable, and in-situ measured 10-h FMC was used as a dependent variable and validation data. 10-h FMC spatial distribution maps were created for dates with the most frequent fire occurrence during 2013-2018. Also, 10-h FMC values of the dates were analyzed to investigate under which 10-h FMC condition forest fire is likely to occur. As the results, fitted equations could explain considerable part of the variance in 10-h FMC (62~78%). Compared to the validation data, the models performed well with R2 ranged from 0.53 to 0.68, root mean squared error (RMSE) ranged from 2.52% to 3.43%, and bias ranged from -0.41% to 1.10%. When the 10-h FMC model fitted for one site was applied to the other sites, $R^2$ was maintained as the same while RMSE and bias increased up to 5.13% and 3.68%, respectively. The major deficiency of the 10-h FMC model was that it poorly caught the difference in the drying process after rainfall between 10-h FMC and EMC. From the analysis of 10-h FMC during the dates fire occurred, more than 70% of the fires occurred under a 10-h FMC condition of less than 10.5%. Overall, the present study suggested a simple model estimating 10-h FMC with acceptable performance. Applying the 10-h FMC model to the automatic mountain weather observation system was successfully tested to produce a national-scale 10-h FMC spatial distribution map. This data will be fundamental information for forest fire research, and will support the policy maker.

• The Korean Journal of Nuclear Medicine
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• v.37 no.2
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• pp.73-82
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• 2003

Objectives: A new software (Cardiac SPECT Analyzer: CSA) was developed for quantification of volumes and election fraction on gated myocardial SPECT. Volumes and ejection fraction by CSA were validated by comparing with those quantified by Quantitative Gated SPECT (QGS) software. Materials and Methods: Gated myocardial SPECT was peformed in 40 patients with ejection fraction from 15% to 85%. In 26 patients, gated myocardial SPECT was acquired again with the patients in situ. A cylinder model was used to eliminate noise semi-automatically and profile data was extracted using Gaussian fitting after smoothing. The boundary points of endo- and epicardium were found using an iterative learning algorithm. Enddiastolic (EDV) and endsystolic volumes (ESV) and election fraction (EF) were calculated. These values were compared with those calculated by QGS and the same gated SPECT data was repeatedly quantified by CSA and variation of the values on sequential measurements of the same patients on the repeated acquisition. Results: From the 40 patient data, EF, EDV and ESV by CSA were correlated with those by QGS with the correlation coefficients of 0.97, 0.92, 0.96. Two standard deviation (SD) of EF on Bland Altman plot was 10.1%. Repeated measurements of EF, EDV, and ESV by CSA were correlated with each other with the coefficients of 0.96, 0.99, and 0.99 for EF, EDV and ESV respectively. On repeated acquisition, reproducibility was also excellent with correlation coefficients of 0.89, 0.97, 0.98, and coefficient of variation of 8.2%, 5.4mL, 8.5mL and 2SD of 10.6%, 21.2mL, and 16.4mL on Bland Altman plot for EF, EDV and ESV. Conclusion: We developed the software of CSA for quantification of volumes and ejection fraction on gated myocardial SPECT. Volumes and ejection fraction quantified using this software was found valid for its correctness and precision.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Tuberculosis and Respiratory Diseases
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• v.44 no.4
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• pp.871-888
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• 1997

Background : It is now thought that the earliest manifestation of idiopathic pulmonary fibrosis is alveolitis, that is, an accumulation of inflammatory and immune effector cells within alveolar walls and spaces. Inflammatory cells including alveolar macrophages and resident normal pulmonary tissue cells participate through the release of many variable mediators such as inflammatory growth factors and cytokines, which contribute to tissue damage and finally cause chronic pulmonary inflammation and fibrosis. This study was performed to investigate the source and distribution pattern of transforming growth factor-${\beta}_1$(TGF-${\beta}_1$), platelet derived growth factor(PDGF), basic fibroblast growth factor(bFGF), interleukin 1(IL-1), interleukin 6(IL-6), tumor necrosis factor-$\alpha$ (TNF-$\alpha$) and the role of these mediators on bleomycin(BLM)-induced pulmonary injury and fibrosis in rats. Method : Wistar rats were divided into three groups(control group, BLM treated group, BLM and vitamine E treated group). Animals were sacrificed periodically at 1, 2, 3, 4, 5, 7, 14, 21, 28 days after saline or BLM administration. The effects were compared to the results of bronchoalveolar lavage fluid analysis, light microscopic findings, immunohistochemical stains for six different mediators(TGF-${\beta}_1$, PDGF, bFGF, IL-1, IL-6 and TNF-$\alpha$) and mRNA in situ hybridization for TGF-${\beta}_1$. Results : IL-1 and IL-6 are maximally expressed at postbleomycin 1~7th day which are mainly produced by neutrophils and bronchiolar epithelium. It is thought that they induce recruitment of inflammatory cells at the injury site. The expression of IL-1 and IL-6 at the bronchiolar epithelium within 7th day is an indirect evidence of contribution of bronchiolar epithelial cells to promote and maintain the inflammatory and immune responses adjacent to the airways. TNF-$\alpha$ is mainly produced by neutrophils and bronchiolar epithelial cells during 1~5th day, alveolar macrophages during 7~28th day. At the earlier period, TNF-$\alpha$ causes recruitment of inflammatory cells at the injury site and later stimulates pulmonary fibrosis. The main secreting cells of TGF-${\beta}_1$ are alveolar macrophages and bronchiolar epithelium and the target is pulmonary fibroblasts and extracellular matrix. TGF-${\beta}_1$ and PDGF stimulate proliferation of pulmonary fibroblasts and TGF-${\beta}_1$ and bFGF incite the fibroblasts to produce extracellular matrix. The vitamine E and BLM treated group shows few positive cells(p<0.05). Conclusion : After endothelial and epithelial injury, the neutrophils and bronchiolar epithelium secrete IL-1, IL-6, TNF-$\alpha$ which induce infiltration of many neutrophils. It is thought that variable enzymes and $O_2$ radicals released by these neutrophils cause destruction of normal lung architecture and progression of pulmonary fibrosis. At the 7~28th day, TGF-${\beta}_1$, PDGF, bFGF, TNF-$\alpha$ secreted by alveolar macrophages sting pulmonary fibroblasts into proliferating with increased production of extracellular matrix and finally, they make progression of pulmonary fibrosis. TNF-$\alpha$ compares quite important with TGF-${\beta}_1$ to cause pulmonary fibrosis. Vitamine E seems to decrease the extent of BLM induced pulmonary fibrosis.