• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.976-983
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• 2023

Purpose: The dynamic behavior of a bridge structure under seismic loading depends on many uncertainties, such as the nature of the seismic waves and the material and geometric properties. However, not all uncertainties have a significant impact on the dynamic behavior of a bridge structure. Since probabilistic seismic performance evaluation considering even low-impact uncertainties is computationally expensive, the uncertainties should be identified by considering their impact on the dynamic behavior of the bridge. Therefore, in this study, a global sensitivity analysis was performed to identify the main parameters affecting the dynamic behavior of bridges with I-curved girders. Method: Considering the uncertainty of the earthquake and the material and geometric uncertainty of the curved bridge, a finite element analysis was performed, and a surrogate model was developed based on the analysis results. The surrogate model was evaluated using performance metrics such as coefficient of determination, and finally, a global sensitivity analysis based on the surrogate model was performed. Result: The uncertainty factors that have the greatest influence on the stress response of the I-curved girder under seismic loading are the peak ground acceleration (PGA), the height of the bridge (h), and the yield stress of the steel (fy). The main effect sensitivity indices of PGA, h, and fy were found to be 0.7096, 0.0839, and 0.0352, respectively, and the total sensitivity indices were found to be 0.9459, 0.1297, and 0.0678, respectively. Conclusion: The stress response of the I-shaped curved girder is dominated by the uncertainty of the input motions and is strongly influenced by the interaction effect between each uncertainty factor. Therefore, additional sensitivity analysis of the uncertainty of the input motions, such as the number of input motions and the intensity measure(IM), and a global sensitivity analysis considering the structural uncertainty, such as the number and curvature of the curved girders, are required.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.93-109
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• 2020

Purpose: The radiochromic film (Gafchromic EBT3, Ashland Advanced Materials, USA) and 3-dimensional analysis system dosimetry checkTM (DC, MathResolutions, USA) were evaluated for patient-specific quality assurance (QA) of helical tomotherapy. Materials and Methods: Depending on the tumors' positions, three types of targets, which are the abdominal tumor (130.6㎤), retroperitoneal tumor (849.0㎤), and the whole abdominal metastasis tumor (3131.0㎤) applied to the humanoid phantom (Anderson Rando Phantom, USA). We established a total of 12 comparative treatment plans by the four geometric conditions of the beam irradiation, which are the different field widths (FW) of 2.5-cm, 5.0-cm, and pitches of 0.287, 0.43. Ionization measurements (1D) with EBT3 by inserting the cheese phantom (2D) were compared to DC measurements of the 3D dose reconstruction on CT images from beam fluence log information. For the clinical feasibility evaluation of the DC, dose reconstruction has been performed using the same cheese phantom with the EBT3 method. Recalculated dose distributions revealed the dose error information during the actual irradiation on the same CT images quantitatively compared to the treatment plan. The Thread effect, which might appear in the Helical Tomotherapy, was analyzed by ripple amplitude (%). We also performed gamma index analysis (DD: 3mm/ DTA: 3%, pass threshold limit: 95%) for pattern check of the dose distribution. Results: Ripple amplitude measurement resulted in the highest average of 23.1% in the peritoneum tumor. In the radiochromic film analysis, the absolute dose was on average 0.9±0.4%, and gamma index analysis was on average 96.4±2.2% (Passing rate: >95%), which could be limited to the large target sizes such as the whole abdominal metastasis tumor. In the DC analysis with the humanoid phantom for FW of 5.0-cm, the three regions' average was 91.8±6.4% in the 2D and 3D plan. The three planes (axial, coronal, and sagittal) and dose profile could be analyzed with the entire peritoneum tumor and the whole abdominal metastasis target, with planned dose distributions. The dose errors based on the dose-volume histogram in the DC evaluations increased depending on FW and pitch. Conclusion: The DC method could implement a dose error analysis on the 3D patient image data by the measured beam fluence log information only without any dosimetry tools for patient-specific quality assurance. Also, there may be no limit to apply for the tumor location and size; therefore, the DC could be useful in patient-specific QAl during the treatment of Helical Tomotherapy of large and irregular tumors.

• Journal of Food Hygiene and Safety
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• v.31 no.6
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• pp.439-444
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• 2016

In the present study, the performance of culture methods using two selective agars and real-time PCR were compared for selective isolation of Cronobacter in powdered infant formula and dried pumpkin. Two food samples were spiked with the pathogen and then preenriched in distilled water. A small portion of preenrichment (10 mL) was incubated in Enterobacteriaceae enrichment both, followed by inoculation onto Druggan-Forsythe-Iversen agar (DFI agar) and Cronobacter sakazakii chromogenic plating agar (R&F agar). The preenrichment and enrichment (1 mL each) was used in real-time PCR assay. In powdered infant formula (PIF), no statistical difference was observed between both culture methods and real-time PCR with preenrichemt (p > 0.05). However, the number of positives obtained by R&F agar and real-time PCR was much higher than that of culture method using DFI agar in dried pumpkin (p < 0.05). In particular, R&F agar yielded a significantly greater selectivity than DFI agar in dried pumpkin (p < 0.05). Real-time PCR and R&F agar, which are currently recommended by US FDA, could be used as an alternative detection tools for the isolation of Cronobacter in PIF and ingredient of child foods such as dried pumpkin that has high number of competing natural microflora.

• The Korean Journal of Blood Transfusion
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• v.23 no.2
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• pp.127-135
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• 2012

Background: Despite modern advances in laboratory automated medicine, work-process in the blood bank is still handled manually. Several automated immunohematological instruments have been developed and are available in the market. The IH-1000 (Bio-Rad Laboratories, Hercules, CA, USA), a fully automated instrument for immunohematology, was recently introduced. In this study, we evaluated the performance of the IH-1000 for ABO/Rh typing and irregular antibody screening. Methods: In October 2011, a total of 373 blood samples for ABO/Rh typing and 303 cases for unexpected antibody screening were collected. The IH-1000 was compared to the manual tube and slide methods for ABO/Rh typing and to the microcolumn agglutination method (DiaMed-ID system) for antibody screening. Results: For ABO/Rh typing, concordance rate was 100%. For unexpected antibody screening, positive results for both column agglutination and IH-1000 were observed in 10 cases (four cases of anti-E and c, three of anti-E, one of anti-D, one of anti-M, and one of anti-Xg) and negative results for both were observed in 289 cases. The concordance rate between IH-1000 and column agglutination was 98.7%. Sensitivity and specificity were 90.9% and 99.3%, respectively. Conclusion: The automated IH-1000 showed good correlation with the manual tube and slide methods and the microcolumn agglutination method for ABO-RhD typing and irregular antibody screening. The IH-1000 can be used for routine pre-transfusion testing in the blood bank.

• Annals of Clinical Microbiology
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• v.18 no.2
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• pp.37-43
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• 2015

Background: Tuberculosis is globally the most important cause of death from single pathogen. Rapid and accurate identification of mycobacteria is essential for the control of tuberculosis. We evaluated a fluorescence in situ hybridization (FISH) method using peptide nucleic acid (PNA) probes for the differentiation of Mycobacterium tuberculosis complex (MTB) and nontuberculous mycobacteria (NTM) in direct smears of sputum specimens. Methods: The cross-reactivity of MTB- and NTM-specific PNA probes was examined with reference strains of M. tuberculosis ATCC 13950, Mycobacterium kansasii ATCC 12479, Mycobacterium fortuitum ATCC 6841, several clinical isolates of mycobacteria (Mycobacterium abscessus, Mycobacterium avium, Mycobacterium intracellulare, Mycobacterium gordonae and Mycobacterium chelonae), and 11 frequently isolated respiratory bacterial species other than mycobacteria. A series of 128 sputa (89 MTB culture positive, 29 NTM culture positive, and 10 under treatment culture negative) with grades of trace to 4+ were used to evaluate the performance of the method. Results: The MTB- and NTM-specific PNA probes showed specific reactions with the reference strains of MTB and M. kansasii and clinical isolates of mycobacteria except M. fortuitum ATCC 6841, and no cross-reactivity with other tested bacteria. The PNA probe-based FISH assay for detection of MTB had a sensitivity and specificity of 100%, respectively. The sensitivity and specificity of the NTM-specific PNA probe was 100%. The smear grades of the PNA FISH test were same as with those of the fluorescence AFB stain in 2+ or higher grade. Conclusion: Detection and differentiation based on PNA FISH is sensitive and accurate for detecting mycobacteria and for differentiating MTB from NTM in clinical sputum smears.

• Korean Journal of Optics and Photonics
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• v.28 no.3
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• pp.108-115
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• 2017

We report the assembly procedure and performance evaluation of a visible and near-infrared spectrometer in the wavelength region of 400-900 nm, which is later to be combined with fore-optics (a telescope) to form a f/2.5 imaging spectrometer with a field of view of ${\pm}7.68^{\circ}$. The detector at the final image plane is a $640{\times}480$ charge-coupled device with a $24{\mu}m$ pixel size. The spectrometer is in an Offner relay configuration consisting of two concentric, spherical mirrors, the secondary of which is replaced by a convex grating mirror. A double-pass test method with an interferometer is often applied in the assembly process of precision optics, but was excluded from our study due to a large residual wavefront error (WFE) in optical design of 210 nm ($0.35{\lambda}$ at 600 nm) root-mean-square (RMS). This results in a single-path test method with a Shack-Hartmann sensor. The final assembly was tested to have a RMS WFE increase of less than 90 nm over the entire field of view, a keystone of 0.08 pixels, a smile of 1.13 pixels and a spectral resolution of 4.32 nm. During the procedure, we confirmed the validity of using a Shack-Hartmann wavefront sensor to monitor alignment in the assembly of an Offner-like spectrometer.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.6
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• pp.306-318
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• 2018

In order to evaluate the seismic capacity of massive vertical type breakwaters which have intensively been deployed along the coast of South Korea over the last two decades, we carry out the preliminary numerical simulation against the PoHang, GyeongJu, Hachinohe 1, Hachinohe 2, Ofunato, and artificial seismic waves based on the measured time series of ground acceleration. Numerical result shows that significant sliding can be resulted in once non-negligible portion of seismic energy is shifted toward the longer period during its propagation process toward the ground surface in a form of shear wave. It is well known that during these propagation process, shear waves due to the seismic activity would be amplified, and non-negligible portion of seismic energy be shifted toward the longer period. Among these, the shift of seismic energy toward the longer period is induced by the viscosity and internal friction intrinsic in the soil. On the other hand, the amplification of shear waves can be attributed to the fact that the shear modulus is getting smaller toward the ground surface following the descending effective stress toward the ground surface. And the weakened intensity of soil as the number of attacking shear waves are accumulated can also contribute these phenomenon (Das, 1993). In this rationale, we constitute the numerical model using the model by Hardin and Drnevich (1972) for the weakened shear modulus as shear waves go on, and shear wave equation, in the numerical integration of which $Newmark-{\beta}$ method and Modified Newton-Raphson method are evoked to take nonlinear stress-strain relationship into account. It is shown that the numerical model proposed in this study could duplicate the well known features of seismic shear waves such as that a great deal of probability mass is shifted toward the larger amplitude and longer period when shear waves propagate toward the ground surface.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.431-438
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• 2021

To prepare more stringent regulations for USCG Phase II ballast water management, this study investigated the staining efficiency of SYBR Green I(SGI) and SYBR Gold(SG) on the virus-like particle (VLP). A dye with high staining efficiency was applied to the treated water that was passed through the ballast water treatment system (BWTS). VLP staining was observed most clearly under the 100-fold and 200-fold dilution of the stock solution when the volume of filtered samples was 0.5 mL to 2 mL. The staining efficiency of SGI and SG did not show a significant difference. On the other hand, the green fluorescence of viruses in the sample stained with SGI was more pronounced than in the samples stained with SG (expressed yellow fluorescence), making it easier to observe. The abundance of VLP in the test water and control water treatments that did not pass through the two types of BWTS (electrolysis type, UV + electrolysis type) was approximately 109 - 1010 VLP 100 mL-1. In contrast, no stained VLP was observed in the treated water treatments. Moreover, SGI was confirmed to be effectively stained under various salinity conditions, including seawater, brackish water, and freshwater. Further verification tests and development of staining methods under various BWTS are required, but the SGI staining method is believed to be a good alternative to the VLP live/dead determination of the USCG Phase II type approval test.