• Journal of the Korean GEO-environmental Society
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• v.14 no.2
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• pp.19-29
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• 2013

The objective of this study is to develop a new GIS Model for calculating the hydrological geographic parameters efficiently using ArcGIS ModelBuilder. To evaluate the applicability of the new GIS Model, hydrological geographic parameters calculated by WMS and HEC-GeoHMS were compared with 5 geographic parameters from the new GIS Model. 18 reservoirs in Chungdo-gun were selected for this study. Hydrological geographic parameters used in this study are watershed area, stream length, watershed slope, stream slope and curve number. As the results of this study, the average relative error of 5 geographic parameters from all watersheds is shown more than 10.00%. In the results by the new GIS Model, hydrological geographic parameters are better efficiently and accurately to evaluate than those existing models.

• BMB Reports
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• v.34 no.4
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• pp.379-384
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• 2001

The cDNA encoding ribosomal protein was identified from a cDNA library of Schizosaccharomyces pombe. The nucleotide sequence of the 548 by cDNA clone reveals an open reading frame, which encodes a putative protein of 166 amino acids with a molecular mass of 18.3 kDa. The amino acid sequence of the S. pombe L11 protein is highly homologous with those of rat and fruit, while it is clearly less similar to those of prokaryotic counterparts. The 1,044 by upstream sequence, and the region encoding N-terminal 7 amino acids of the genomic DNA were fused into the promoterless $\beta$-galactosidase gene of the shuttle vector YEp357 in order to generate the fusion plasmid pHY L11. Synthesis of $\beta$-galactosidase from the fusion plasmid varied according to the growth curve. It decreased significantly in the growth-arrested yeast cells that were treated with aluminum chloride and mercuric chloride. However, it was enhanced by treatments with cadmium chloride ($2.5\;{\mu}M$), zinc chloride ($2.5\;{\mu}M$), and hydrogen peroxide (0.5 mM). This indicates that the expression of the L,11 gene could be induced by oxidative stress.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.4
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• pp.299-307
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• 2011

The offshore plants such as FPSO are subjected to combination loading of environmental conditions (swell, wave, wind and current). Therefore the fatigue damage is occurred in the operation time because the units encounter the environmental phenomena and the structural configurations are complicated. This paper is a research for frequency domain fatigue analysis of wide-band random loading focused on accuracy of fatigue damage estimation regarding the proposed methods. We selected ideal bi-modal spectrum. And comparison between time-domain fatigue analysis and frequency-domain fatigue analyses are conducted through the fatigue damage ratio. Fatigue damage ratios according to Vanmarcke's bandwidth parameter are founded for wide-band. Considering safety, we recommend that Jiao-Moan and Tovo-Benasciutti methods are optimal way at the fatigue design for wide-band response. But, it is important that these methods based on frequency-domain unstably change the accuracy according to the material parameter of S-N curve. This study will be background and guidance for the new frequency-domain fatigue analysis development in the future.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.2
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• pp.1-9
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• 2005

An end beam is one of the most important structural members supporting uncovered freight under in-service loading. In general, it needs to endure over 25 years. However fatigue fracture has occurred at dynamic stress concentration location of the end beam because user's specifications demanded high speed and vehicle manufacturer made the uncovered freight car with comparatively low strength and stiffness. For durability analysis, finite element analysis is performed to evaluate the problem of uncovered freight structure and local strain. The uncovered freight car was operated on actual problematic railroad line to measure dynamic stress versus time history on the critical part from which a crack is initiated often. Rainflow cycle counting method was used to estimate fatigue damage at dangerous area under operating condition. Therefore, this study shows that analytical fatigue life at the end beam can be predicted on the basis of S-N curve and structure analysis and has a fairly good correlation with experimental fatigue life.

• Structural Engineering and Mechanics
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• v.72 no.2
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• pp.245-256
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• 2019

The experimentally determined mechanical behavior of the material under the prescribed service conditions is the basis of advanced engineering optimum design. To allow experimental data on the behavior of the material considered, uniaxial stress tests were made. The aforementioned tests have enabled the determination of mechanical properties of material at different temperatures, then, the material's resistance to creep at various temperatures and stress levels, and finally, insight into the uniaxial high cyclic fatigue of the material under different applied stresses for prescribed stress ratio. Based on fatigue tests, using modified staircase method, fatigue limit was determined. All these data contributes the reliability of the use of material in mechanical structures. Data representing mechanical properties are shown in the form of engineering stress-strain diagrams; creep behavior is displayed in the form of creep curves while fatigue of the material is presented in the form of S-N (maximum applied stress versus number of the cycles to failure) curve. Material under consideration was 18CrNi8 (1.5920) steel. Ultimate tensile strength and yield strength at room temperature and at temperature of $600^{\circ}C$: [${\sigma}_{m,20/600}=(613/156)MPa$; ${\sigma}_{0.2,20/600}=(458/141)MPa$], as well as endurance (fatigue) limit at room temperature and stress ratio of R = -1 : (${\sigma}_{f,20,R=-1}=285.1MPa$).

• Biomedical Science Letters
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• v.25 no.1
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.

• Biomedical Science Letters
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• v.24 no.4
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• pp.418-425
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• 2018

Amyloid brain positron emission tomography (PET) images are visually and subjectively analyzed by the physician with a lot of time and effort to determine the ${\beta}$-Amyloid ($A{\beta}$) deposition. We designed a convolutional neural network (CNN) model that predicts the $A{\beta}$-positive and $A{\beta}$-negative status. We performed 18F-florbetaben (FBB) brain PET on controls and patients (n=176) with mild cognitive impairment and Alzheimer's Disease (AD). We classified brain PET images visually as per the on the brain amyloid plaque load score. We designed the visual geometry group (VGG16) model for the visual assessment of slice-based samples. To evaluate only the gray matter and not the white matter, gray matter masking (GMM) was applied to the slice-based standard samples. All the performance metrics were higher with GMM than without GMM (accuracy 92.39 vs. 89.60, sensitivity 87.93 vs. 85.76, and specificity 98.94 vs. 95.32). For the patient-based standard, all the performance metrics were almost the same (accuracy 89.78 vs. 89.21), lower (sensitivity 93.97 vs. 99.14), and higher (specificity 81.67 vs. 70.00). The area under curve with the VGG16 model that observed the gray matter region only was slightly higher than the model that observed the whole brain for both slice-based and patient-based decision processes. Amyloid brain PET images can be appropriately analyzed using the CNN model for predicting the $A{\beta}$-positive and $A{\beta}$-negative status.

• Journal of Ocean Engineering and Technology
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• v.33 no.5
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• pp.435-446
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• 2019

Because offshore structures are affected by various environmental loads, the risk of damage is high. As a result of ever-changing ocean environmental loads, damage to offshore structures is expected to differ from year to year. However, in previous studies, it was assumed that a relatively short period of load acts repeatedly during the design life of a structure. In this study, the residual life of an offshore wind turbine support structure was evaluated in consideration of the timing uncertainty of the ocean environmental load. Sampling points for the wind velocity, wave height, and wave period were generated using a central composites design, and a transfer function was constructed from the numerical analysis results. A simulation was performed using the joint probability model of ocean environmental loads. The stress time history was calculated by entering the load samples generated by the simulation into the transfer function. The damage to the structure was calculated using the rain-flow counting method, Goodman equation, Miner's rule, and S-N curve. The results confirmed that the wind speed generated at a specific time could not represent the wind speed that could occur during the design life of the structure.

• Research in Community and Public Health Nursing
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• v.33 no.3
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• pp.299-311
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• 2022

Purpose: Untreated depression in adolescents affects their entire life. It is important to detect and intervene early depression in adolescence considering the characteristics of adolescent's depressive symptoms accompanied by internalization and externalization. The aim of this study was to identify latent classes of depressive symptom trajectories of adolescents and determinants of classes in Korea. Methods: The three time-point (2018~2020) data derived from the Korean Children and Youth Panel Survey 2018 were used (N=2,325). Latent Growth Curve Modeling (LGCM) was conducted to explore the depressive symptom trajectories in all adolescents, and Latent Class Growth Modeling (LCGM) was conducted to identify each latent class. Multinomial logistic regression analysis was performed to confirm the determinants of each latent class. Results: The LGCM results showed that there was no statistically significant change in all adolescents' depressive symptoms for 3 years. However, the LCGM results showed that four latent classes showing different trajectories were distinguished: 1) Low-stable (intercept=14.39, non-significant slope), 2) moderate-increasing (intercept=19.62, significantly increasing slope), 3) high-stable (intercept=26.30, non-significant slope), and 4) high-rapidly decreasing (intercept=26.34, significantly rapidly decreasing slope). The multinomial logistic regression analysis showed that the significant determinants (i.e., gender, self-esteem, aggression, somatization, peer relationship) of each latent class were different. Conclusion: When screening adolescent's depression, it is necessary to monitor not only direct depression symptoms but also self-esteem, aggression, somatization symptoms, and peer relationships. The findings of this study may be valuable for nurses and policy makers to develop mental health programs for adolescents.

• Journal of dental hygiene science
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• v.12 no.3
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• pp.209-215
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• 2012

Somok, the heart wood of Caesalpinia sappan is used in traditional Chinese medicine. This study was performed to investigate the effect of growth and culture conditions of brazilin from C. sappan against S. mutans ATCC 25175. The bacteria were cultured in brain heart infusion (BHI) broth, and then incubated under 5% $CO_2$ at $37^{\circ}C$ for 18-24 hours. The effect of brazilin against S. mutans was confirmed under the changes of the culture conditions, such as growth curve and the change of pH, protein, and total carbohydrate. The growth of S. mutans in control medium was the highest at 24 hr, while brazilin-added medium (0.3 mg/ml) showed maximum growth at 32 hr. The pH values of the control medium was 5.25 at 16 hr, but the media supplemented with brazilin (0.3 mg/ml) was 7.0 at 16 hr. The amounts of total carbohydrate of the control medium was 11 mg/ml at 8 hr, but the brazilin-added media (0.3 mg/ml) was 18 mg/ml at 8 hr. In the protein change of the culture medium, the control culture broth and the brazilin supplemented-cultures was 2.4 mg/ml and 2.54 mg/ml at 24 hr, respectively. Polysaccharide contents of the control medium and test media were 3 mg/ml and 2 mg/ml at 8 hr, respectively. Thus, the application of C. sappan can be considered a useful and practical material for the prevention of dental caries.