• Korean Journal of Plant Resources
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• v.35 no.2
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• pp.169-182
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• 2022

This study was conducted to predict the distribution of rare·endemic plants (Sophora koreensis Nakai) in the border forests where wildfire damage occurred and to quantify the damage. For this purpose, we tried to derive more accurate results through forest area damage (NBR) according to the Burn severity of wildfires, damage by tree species type (Vegetation map), and MaxEnt model. For Burn severity analysis, satellite imagery (Landsat-8) was used to analyze Burn severity (ΔNBR2016-2015) and to derive the extent of damage. To prepare the Vegetation map, the land cover map prepared by the Ministry of Environment, the Vegetation map prepared by the Korea Forest Service, and the vegetation survey conducted by itself were conducted to prepare the clinical map before and after the forest fire. Lastly, for MaxEnt model analysis, the AUC value was derived by using the habitat coordinates of Sophora koreensis Nakai based on the related literature and self-report data. As a result of combining the Maxent model analysis data with the Burn severity data, it was confirmed that 45.9% of the 44,760 m² of habitat (predicted) area of Sophora koreensis Nakai in the wildfire damaged area or 20,552 m², was damaged.

• Ecology and Resilient Infrastructure
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• v.9 no.2
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• pp.100-106
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• 2022

The relationships between river length and weir density versus fish species observed were analyzed for 210 local rivers in the Seomjin River system (SJR). A nonlinear exponential relationship between river length and number of fish species were observed. Model coefficient was 0.03 and coefficient of determinant (R²) was 0.59, meaning that about 59.0% of total variance was explained by river length variable. Predicted value by model and observed number of species showed a difference. About 110 local rivers (about 52.4%) showed lower value than predictive value. The average index of weir's density (IWD) in the SJR was about 2.7/km, which was significantly higher than that of other river basins. As a result of nonparametric 2-Kimensional Kolmogorov-Smirnov (2-DKS) analysis based on the IWD, the threshold value affecting fish diversity was about 2.5/km (D_max=0.048, p<0.05). Above the threshold value, it means that the number of fish species would be decreased. In fact, the ratio of the expected species to the observed species was lowered to less than 70%, when the IWD is higher than the threshold value. To maintain aquatic ecological connectivity in future, it is necessary to manage IWD below the threshold value.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.2
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• pp.191-199
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• 2021

In this study, the correlation between the influencing factors on corrosion and Half Cell Potential(HCP) measurement was analyzed considering the three levels of W/C ratio, cover depth, and chloride concentration. The HCP increased with enlarged cover depth, so it was confirmed that the increment of cover depth was effective for control of corrosion. Based on the criteria, the case of 60mm cover depth showed excellent corrosion control with under -200mV, indicating increase of cover depth is an effective method for reducing intrusion of external deterioration factors. When fresh water was injected to the upper part of specimens, very low level of HCP was monitored, but in the case that concentrations of chloride were 3.5% and 7.0%, HCP dropped under -200mV. In addition, the case with high volume of unit binder showed lower HCP measurement like increasing cover depth. Multiple regression analysis was performed to evaluate the correlation between the corrosive influence factors and HCP results, showing high coefficient of determination of 0.97. However, there were limitations such as limited number of samples and measuring period. Through the additional corrosion monitoring and chloride content evaluation after dismantling the specimen, more reasonable prediction can be achieved for correlation analysis with relevant data.

• Journal of Chest Surgery
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• v.55 no.2
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• pp.143-150
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• 2022

Background: The effectiveness of extracorporeal membrane oxygenation (ECMO) for patients with refractory cardiogenic shock or cardiac arrest is being established, and serum lactate is well known as a biomarker of end-organ perfusion. We evaluated the efficacy of pre-ECMO lactate for predicting 6-month survival in patients with acute coronary syndrome (ACS) undergoing ECMO. Methods: We reviewed the medical records of 148 patients who underwent veno-arterial (VA) ECMO for ACS between January 2015 and June 2020. These patients were divided into survivors and non-survivors based on 6-month survival. All clinical data before and during ECMO were compared between the 2 groups. Results: Patients' mean age was 66.0±10.5 years, and 116 (78.4%) were men. The total survival rate was 45.9% (n=68). Cox regression analysis showed that the pre-ECMO lactate level was an independent predictor of 6-month mortality (hazard ratio, 1.210; 95% confidence interval [CI], 1.064-1.376; p=0.004). The area under the receiver operating characteristic curve of pre-ECMO lactate was 0.64 (95% CI, 0.56-0.72; p=0.002; cut-off value=9.8 mmol/L). Kaplan-Meier survival analysis showed that the cumulative survival rate at 6 months was significantly higher among patients with a pre-ECMO lactate level of 9.8 mmol/L or less than among those with a level exceeding 9.8 mmol/L (57.3% vs. 31.8%, p=0.0008). Conclusion: A pre-ECMO lactate of 9.8 mmol/L or less may predict a favorable outcome at 6 months in ACS patients undergoing VA-ECMO. Further research aiming to improve the accuracy of predictions of reversibility in patients with high pre-ECMO lactate levels is essential.

• Journal of Gastric Cancer
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• v.23 no.2
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• pp.355-364
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• 2023

Background: There are no clear guidelines to determine whether to perform D1 or D1+ lymph node dissection in early gastric cancer (EGC). This study aimed to develop a nomogram for estimating the risk of extraperigastric lymph node metastasis (LNM). Materials and Methods: Between 2009 and 2019, a total of 4,482 patients with pathologically confirmed T1 disease at 6 affiliated hospitals were included in this study. The basic clinicopathological characteristics of the positive and negative extraperigastric LNM groups were compared. The possible risk factors were evaluated using univariate and multivariate analyses. Based on these results, a risk prediction model was developed. A nomogram predicting extraperigastric LNM was used for internal validation. Results: Multivariate analyses showed that tumor size (cut-off value 3.0 cm, odds ratio [OR]=1.886, P=0.030), tumor depth (OR=1.853 for tumors with sm2 and sm3 invasion, P=0.010), cross-sectional location (OR=0.490 for tumors located on the greater curvature, P=0.0303), differentiation (OR=0.584 for differentiated tumors, P=0.0070), and lymphovascular invasion (OR=11.125, P<0.001) are possible risk factors for extraperigastric LNM. An equation for estimating the risk of extraperigastric LNM was derived from these risk factors. The equation was internally validated by comparing the actual metastatic rate with the predicted rate, which showed good agreement. Conclusions: A nomogram for estimating the risk of extraperigastric LNM in EGC was successfully developed. Although there are some limitations to applying this model because it was developed based on pathological data, it can be optimally adapted for patients who require curative gastrectomy after endoscopic submucosal dissection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.27-30
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• 2022

The plasma process, which has many advantages in terms of efficiency and environment compared to conventional process methods, is widely used in semiconductor manufacturing. Plasma Sheath is a dark region observed between the plasma bulk and the chamber wall surrounding it or the electrode. The Plasma Sheath Monitoring Sensor (PSMS) measures the difference in voltage between the plasma and the electrode and the RF power applied to the electrode in real time. The PSMS data, therefore, are expected to have a high correlation with the state of plasma in the plasma chamber. In this study, a model for predicting the state of nitrogen ions in the plasma chamber is training by a deep learning machine learning techniques using PSMS data. For the data used in the study, PSMS data measured in an experiment with different power and pressure settings were used as training data, and the ratio, flux, and density of nitrogen ions measured in plasma bulk and Si substrate were used as labels. The results of this study are expected to be the basis of artificial intelligence technology for the optimization of plasma processes and real-time precise control in the future.

• Korean Journal of Transplantation
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• v.28 no.3
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• pp.135-143
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• 2014

Background: Kidney injury molecule-1 (KIM-1) is known as a good ancillary marker of acute kidney injury (AKI) and its expression has also been observed in acute rejection and chronic graft dysfunction. We tested usefulness of KIM-1 as an indicator of acute and chronic renal graft injury by correlating KIM-1 expression with renal graft function and histology. Methods: A total of 133 zero-time biopsies and 42 follow-up biopsies obtained within 1 year posttransplantation were selected. Renal tubular KIM-1 staining was graded semiquantitatively from 0 to 3 and the extent of staining was expressed as the ratio of KIM-1 positive/CD10 positive proximal tubules using Image J program. Results: KIM-1 was positive in 39.8% of zero-time biopsies. KIM-1 positive cases were predominantly male and had received grafts from donors with older age, deceased donors, and poor renal function at the time of donation, compared with KIM-1 negative cases. KIM-1 expression showed correlation with delayed graft function and acute tubular necrosis. In comparison of KIM-1 expression between stable grafts (n=23) and grafts with dysfunction (n=19) at the time of repeated biopsy, the intensity/extent of KIM-1 staining and renal histology at zero-time did not differ significantly between the two groups. Histologically, KIM-1 expression was significantly increased with both acute and chronic changes of glomeruli, tubules and interstitium, peritubular capillaritis, and arteriolar hyalinosis. Conclusions: KIM-1 can be used as an ancillary marker of AKI and a nonspecific indicator of acute inflammation and tubulointerstitial fibrosis. However, KIM-1 expression at zero-time is not suitable for prediction of long-term graft dysfunction.

• Steel and Composite Structures
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• v.47 no.1
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• pp.91-102
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• 2023

To study the evaluation standard and control limit of mortar filling layer void length, in this paper, the train sub-model was developed by MATLAB and the track-bridge sub-model considering the mortar filling layer void was established by ANSYS. The two sub-models were assembled into a train-track-bridge coupling dynamic model through the wheel-rail contact relationship, and the validity was corroborated by the coupling dynamic model with the literature model. Considering the randomness of fastening stiffness, mortar elastic modulus, length of mortar filling layer void, and pier settlement, the test points were designed by the Box-Behnken method based on Design-Expert software. The coupled dynamic model was calculated, and the support vector regression (SVR) nonlinear mapping model of the wheel-rail system was established. The learning, prediction, and verification were carried out. Finally, the reliable probability of the amplification coefficient distribution of the response index of the train and structure in different ranges was obtained based on the SVR nonlinear mapping model and Latin hypercube sampling method. The limit of the length of the mortar filling layer void was, thus, obtained. The results show that the SVR nonlinear mapping model developed in this paper has a high fitting accuracy of 0.993, and the computational efficiency is significantly improved by 99.86%. It can be used to calculate the dynamic response of the wheel-rail system. The length of the mortar filling layer void significantly affects the wheel-rail vertical force, wheel weight load reduction ratio, rail vertical displacement, and track plate vertical displacement. The dynamic response of the track structure has a more significant effect on the limit value of the length of the mortar filling layer void than the dynamic response of the vehicle, and the rail vertical displacement is the most obvious. At 250 km/h - 350 km/h train running speed, the limit values of grade I, II, and III of the lengths of the mortar filling layer void are 3.932 m, 4.337 m, and 4.766 m, respectively. The results can provide some reference for the long-term service performance reliability of the ballastless track-bridge system of HRS.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.177-188
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• 2022

Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO₂ storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.173-191
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• 2022

In this study, the shear wave velocity of the ground was measured using Flat TDR, and the precision analysis of the measured value and the verification of field applicability were performed. The shear wave velocity measurement value was derived in the field using the piezo-stack combined in the Flat TDR. analyzed. As a result of the experiment, the average value of the change in shear wave speed at the time of grout material injection was 10.15 m/s at the beginning of age, and the average value of the change in shear wave speed after the 7th to 14th days was 65.99 m/s, showing a tendency to increase with age. Also, it was found that dry density and shear wave speed increased as the water content increased on the dry side, and that the dry density and shear wave rate decreased as the water content increased on the wet side as the water content increased. The shear modulus value derived from the field test was confirmed to be a minimum of 17.36 MPa and a maximum of 28.13 MPa, confirming a measurement value similar to the reference value. Through this, it can be seen that the measured value of the shear modulus using Flat TDR is reliable data, and it can be determined that the compaction management of the site can be effectively managed in the future.