• Journal of the Korean Institute of Landscape Architecture
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• v.14 no.1
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• pp.45-60
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• 1986

The purpose of the present studies is to establish more rational and practical planning theory for trails of gradient. The results drawn from this research work are as follow ; Mean angle according to topography of Jiga road is $3^{\circ}$33'in low part, $8^{\circ}$17'in middle park and $12^{\circ}$48'in high part. Here, we can find that the highest gradient of Jige roacl is $12^{\circ}$48, Which is showing the fact that jigs road is the most function road when we compare other roads. The regression coefficient between potential model pattern and calculuted model pattern is 0.8 withinTEX>$ 0~<5^{\circ}$, 0.5 within$ 6~10^{\circ}$, and 0.53 within $11~16^{\circ}$. The linear of these model pattern is lower in R & L value, and lager in S & A value according to be steeping gradient. It is thought that these fact are closely related with between human fatigue and R.S.A.L value. Accordingly, when we plan the trails of the gradient in city park, the from of trails is right to mix straight line with curve line within $0~5^{\circ}$, and sine wave close curve line within $6~10 ^{\circ}$, $l1~16^{\circ}$. But, in fact, It is absurd that potential model pattern is applied to the city park in park of corner, widely road and facilities. Therefore, It is thought that the study of this problems will be proceeded in the future. I can reduce the following equation in relation R & S by gradient ; 22 log (R-6.0)=47.96-$\delta$

• Archives of Pharmacal Research
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• v.25 no.4
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• pp.505-510
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• 2002

An improved kinetic assay for prekallikrein activator (PKA), a potential vasodilator, has been developed to be used as an indicator for quality control during production of human albumin preparations. It consists of two reaction stages. In the first stage, PKA and prekallikrein are incubated at $37^{\circ}C$ for 45 min to allow the transformation into kallikrein. Kallikrein, a serine protease, catalyzes the splitting of p-nitroaniline (pNA) from its substrate H-D-Pro-Phe-Arg-pNA(S-2302). The rate at which pNA is released was measured spectrophotometrically at 405 nm. Prekallikrein, a substrate of PKA was purified by DEAE ion-exchange chromatography and the major potential variations in the assay were optimized; pH 8.0 and 150 mM sodium chloride were chosen to give a proper ionic strength. Reaction times in the range of 10 to 360 min provided linear dose-response curves. The concentration of prekallikrein was adjusted to fall between 1:1 and 1:3 dilutions to generate a linear standard calibration curve. Under the optimized conditions, reproducibility was checked. In a precision test, the coefficient of variation (CV) stayed within ${\pm}4%$ and the dose-response curve showed a good correlation (${r^2}=0.999$). An accuracy test with an international standard of PKA afforded a mean recovery of 97.5%.

• Safety and Health at Work
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• v.1 no.1
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• pp.69-79
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• 2010

Objectives: Various cytokines induced by inhalation of coal dust may mediate inflammation and lead to tissue damage or fibrosis, such as coal workers' pneumoconiosis (CWP). Methods: To investigate the relevance of serum cytokines in CWP, the levels of serum interleukin-8 (IL-8) and tumor necrosis factor-alpha (TNF-${\alpha}$) as CWP biomarkers in 110 retired coal miners (22 controls and 88 CWP subjects) were related to cross sectional findings and 1-year progressive changes of the pneumoconiosis. Progressive changes of CWP were evaluated by paired comparison of chest radiographs. Analysis by a receiver operating characteristic curve assessed the biomarker potential of each cytokine. Results: The mean serum IL-8 level was significantly higher in CWP compared to controls and IL-8 levels correlated with the degree of CWP. The median serum TNF-${\alpha}$ level was significantly higher in subjects with progressive CWP compared to subjects without CWP progression. The area under the ROC curve for IL-8 (0.70) and TNF-${\alpha}$ (0.72) for CWP identification and progression, respectively, indicated the biomarker potential of the two cytokines. Serum cutoff values of IL-8 and TNF-${\alpha}$ were 11.63 pg/mL(sensitivity, 69%; specificity, 64%) and 4.52 pg/mL (sensitivity, 67%; specificity, 79%), respectively. Conclusion: The results suggest that high levels of serum IL-8 are associated with the presence of CWP and those of serum TNF-${\alpha}$ are associated with the progression of CWP.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2767-2773
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• 2021

We used the GEANT4 Monte Carlo MC Toolkit to simulate carbon ion beams incident on water, tissue, and bone, taking into account nuclear fragmentation reactions. Upon increasing the energy of the primary beam, the position of the Bragg-Peak transfers to a location deeper inside the phantom. For different materials, the peak is located at a shallower depth along the beam direction and becomes sharper with increasing electron density NZ. Subsequently, the generated depth dose of the Bragg curve is then benchmarked with experimental data from GSI in Germany. The results exhibit a reasonable correlation with GSI experimental data with an accuracy of between 0.02 and 0.08 cm, thus establishing the basis to adopt MC in heavy-ion treatment planning. The Kolmogorov-Smirnov K-S test further ascertained from a statistical point of view that the simulation data matched the experimentally measured data very well. The two-dimensional isodose contours at the entrance were compared to those around the peak position and in the tail region beyond the peak, showing that bone produces more dose, in comparison to both water and tissue, due to secondary doses. In the water, the results show that the maximum energy deposited per fragment is mainly attributed to secondary carbon ions, followed by secondary boron and beryllium. Furthermore, the number of protons produced is the highest, thus making the maximum contribution to the total dose deposition in the tail region. Finally, the associated spectra of neutrons and photons were analyzed. The mean neutron energy value was found to be 16.29 MeV, and 1.03 MeV for the secondary gamma. However, the neutron dose was found to be negligible as compared to the total dose due to their longer range.

• Clinical and Experimental Pediatrics
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• v.62 no.9
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• pp.353-359
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• 2019

Background: Researchers have shown that eosinophil peroxidase (EPO) is a relatively accurate marker of eosinophilia and eosinophil activity. However, its use as a marker of eosinophilic inflammation in nasal secretions is limited because the diagnostic cutoff values of EPO for use as a one-time test for allergic diseases such as allergic rhinitis have not been established. Purpose: To identify the correlation between nasal eosinophil count and EPO in children and adolescents with rhinitis. Methods: We recruited patients <18 years of age with rhinitis for more than 2 weeks or more than 2 episodes a year whose nasal eosinophil and EPO were measured at a single allergy clinic. The eosinophil percentage was calculated by dividing the eosinophil count by the number of total cells under light microscopy at ${\times}1,000$ magnification. EPO and protein were measured from nasal secretions. We retrospectively analyzed the correlation between nasal eosinophils and protein-corrected EPO (EPO/protein) value. Results: Of the 67 patients enrolled, 41 were male (61.2%); the mean age was $8.2{\pm}4.0years$. The median nasal eosinophil count was 1 and percentage was 1%. The median protein-corrected EPO value was $12.5ng/{\mu}g$ (range, $0-31ng/{\mu}g$). There was a statistically significant correlation between eosinophil count and percentage (P<0.001). However, the eosinophil percentage and EPO did not correlate. The eosinophil count and EPO had a statistically significant correlation (P=0.01). The EPO cutoff value examined for nasal eosinophil counts of 2, 5, 10, and 20 was $17.57ng/{\mu}g$ regardless of the reference count. The largest area under the curve value was obtained when the receiver operating characteristic curve was drawn using the eosinophil count of 2. Conclusion: Nasal eosinophil count was significantly associated with protein-corrected EPO.

• The Journal of Korean Institute of Information Technology
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• v.17 no.12
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• pp.21-28
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• 2019

Side effects of drugs mean harmful and unintended effects resulting from drugs used to prevent, diagnose, or treat diseases. These side effects can lead to patients' death and are the main causes of drug developmental failures. Thus, various methods have been tried to identify side effects. These can be divided into biological and systems biology approaches. In this study, we use systems biology approach and focus on using various phenotypic information in addition to the chemical structure and target proteins. First, we collect datasets that are used in this study, and calculate similarities individually. Second, we generate a set of features using the similarities for each drug-side effect pair. Finally, we confirm the results by AUC(Area Under the ROC Curve), and showed the significance of this study through a comparison experiment.

• Investigative Magnetic Resonance Imaging
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• v.25 no.1
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• pp.10-22
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• 2021

Purpose: To overcome the difficulty in building a large data set with a high-quality in medical imaging, a concept of 'blended-transfer learning' (BTL) using a combination of both source data and target data is proposed for the target task. Materials and Methods: Source and target tasks were defined as training of the source and target networks to reconstruct cardiac CINE images from undersampled data, respectively. In transfer learning (TL), the entire neural network (NN) or some parts of the NN after conducting a source task using an open data set was adopted in the target network as the initial network to improve the learning speed and the performance of the target task. Using BTL, an NN effectively learned the target data while preserving knowledge from the source data to the maximum extent possible. The ratio of the source data to the target data was reduced stepwise from 1 in the initial stage to 0 in the final stage. Results: NN that performed BTL showed an improved performance compared to those that performed TL or standalone learning (SL). Generalization of NN was also better achieved. The learning curve was evaluated using normalized mean square error (NMSE) of reconstructed images for both target data and source data. BTL reduced the learning time by 1.25 to 100 times and provided better image quality. Its NMSE was 3% to 8% lower than with SL. Conclusion: The NN that performed the proposed BTL showed the best performance in terms of learning speed and learning curve. It also showed the highest reconstructed-image quality with the lowest NMSE for the test data set. Thus, BTL is an effective way of learning for NNs in the medical-imaging domain where both quality and quantity of data are always limited.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2600-2609
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• 2021

Low cycle fatigue behaviors of SA508-3 low-alloy steel were investigated in room-temperature air, high-temperature air and in light water reactor (LWR) water environments. The fatigue mean curve and design curve for the low-alloy steel are developed based on the fatigue data in room-temperature and high-temperature air. The environmental fatigue model for low-alloy steel is developed by the environmental fatigue correction factor (F_en) methodology based on the fatigue data in LWR water environments with the consideration of effects of strain rate, temperature, and dissolved oxygen concentration on the fatigue life.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.85-85
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• 2020

South Korea experiences few large scale erosion and sedimentation problems, however, there are numerous local sedimentation problems. A reliable and consistent approach to modelling and management for sediment processes are desirable in the country. In this study, field measurements of sediment concentration from 34 alluvial river basins in South Korea were used with the Modified Einstein Procedure (MEP) to determine the total sediment load at the sampling locations. And then the Flow Duration-Sediment Rating Curve (FD-SRC) method was used to estimate the specific degradation for all gauging stations. The specific degradation of most rivers were found to be typically 50-300 tons/㎢·yr. A model tree data mining technique was applied to develop a model for the specific degradation based on various watershed characteristics of each watershed from GIS analysis. The meaningful parameters are: 1) elevation at the middle relative area of the hypsometric curve [m], 2) percentage of wetland and water [%], 3) percentage of urbanized area [%], and 4) Main stream length [km]. The Root Mean Square Error (RMSE) of existing models is in excess of 1,250 tons/㎢·yr and the RMSE of the proposed model with 6 additional validations decreased to 65 tons/㎢·yr. Erosion loss maps from the Revised Universal Soil Loss Equation (RUSLE), satellite images, and aerial photographs were used to delineate the geospatial features affecting erosion and sedimentation. The results of the geospatial analysis clearly shows that the high risk erosion area (hill slopes and construction sites at urbanized area) and sedimentation features (wetlands and agricultural reservoirs). The result of physiographical analysis also indicates that the watershed morphometric characteristic well explain the sediment transport. Sustainable management with the data mining methodologies and geospatial analysis could be helpful to solve various erosion and sedimentation problems under different conditions.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.297-307
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• 2021

Objective: To compare the performance of simulated abbreviated breast MRI (AB-MRI) and full diagnostic (FD)-MRI in distinguishing between benign and malignant lesions detected by MRI and investigate the features of discrepant lesions of the two protocols. Materials and Methods: An AB-MRI set with single first postcontrast images was retrospectively obtained from an FD-MRI cohort of 111 lesions (34 malignant, 77 benign) detected by contralateral breast MRI in 111 women (mean age, 49.8. ± 9.8; range, 28-75 years) with recently diagnosed breast cancer. Five blinded readers independently classified the likelihood of malignancy using Breast Imaging Reporting and Data System assessments. McNemar tests and area under the receiver operating characteristic curve (AUC) analyses were performed. The imaging and pathologic features of the discrepant lesions of the two protocols were analyzed. Results: The sensitivity of AB-MRI for lesion characterization tended to be lower than that of FD-MRI for all readers (58.8-82.4% vs. 79.4-100%), although the findings of only two readers were significantly different (p < 0.05). The specificity of AB-MRI for lesion characterization was higher than that of FD-MRI for 80% of readers (39.0-74.0% vs. 19.5-45.5%, p ≤ 0.001). The AUC of AB-MRI was comparable to that of FD-MRI for all readers (p > 0.05). Fifteen percent (5/34) of the cancers were false-negatives on AB-MRI. More suspicious margins or internal enhancement on the delayed phase images were related to the discrepancies. Conclusion: The overall performance of AB-MRI was similar to that of FD-MRI in distinguishing between benign and malignant lesions. AB-MRI showed lower sensitivity and higher specificity than FD-MRI, as 15% of the cancers were misclassified compared to FD-MRI.