• Korean Journal of Radiology
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• v.22 no.9
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• pp.1514-1524
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• 2021

Objective: To develop a radiomics risk score based on dynamic contrast-enhanced (DCE) MRI for prognosis prediction in patients with glioblastoma. Materials and Methods: One hundred and fifty patients (92 male [61.3%]; mean age ± standard deviation, 60.5 ± 13.5 years) with glioblastoma who underwent preoperative MRI were enrolled in the study. Six hundred and forty-two radiomic features were extracted from volume transfer constant (K^trans), fractional volume of vascular plasma space (V_p), and fractional volume of extravascular extracellular space (V_e) maps of DCE MRI, wherein the regions of interest were based on both T1-weighted contrast-enhancing areas and non-enhancing T2 hyperintense areas. Using feature selection algorithms, salient radiomic features were selected from the 642 features. Next, a radiomics risk score was developed using a weighted combination of the selected features in the discovery set (n = 105); the risk score was validated in the validation set (n = 45) by investigating the difference in prognosis between the "radiomics risk score" groups. Finally, multivariable Cox regression analysis for progression-free survival was performed using the radiomics risk score and clinical variables as covariates. Results: 16 radiomic features obtained from non-enhancing T2 hyperintense areas were selected among the 642 features identified. The radiomics risk score was used to stratify high- and low-risk groups in both the discovery and validation sets (both p < 0.001 by the log-rank test). The radiomics risk score and presence of isocitrate dehydrogenase (IDH) mutation showed independent associations with progression-free survival in opposite directions (hazard ratio, 3.56; p = 0.004 and hazard ratio, 0.34; p = 0.022, respectively). Conclusion: We developed and validated the "radiomics risk score" from the features of DCE MRI based on non-enhancing T2 hyperintense areas for risk stratification of patients with glioblastoma. It was associated with progression-free survival independently of IDH mutation status.

• Korean Journal of Radiology
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• v.21 no.8
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• pp.1007-1017
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• 2020

Objective: The purpose of our study was to investigate the predictive abilities of clinical and computed tomography (CT) features for outcome prediction in patients with coronavirus disease (COVID-19). Materials and Methods: The clinical and CT data of 238 patients with laboratory-confirmed COVID-19 in our two hospitals were retrospectively analyzed. One hundred sixty-six patients (103 males; age 43.8 ± 12.3 years) were allocated in the training cohort and 72 patients (38 males; age 45.1 ± 15.8 years) from another independent hospital were assigned in the validation cohort. The primary composite endpoint was admission to an intensive care unit, use of mechanical ventilation, or death. Univariate and multivariate Cox proportional hazard analyses were performed to identify independent predictors. A nomogram was constructed based on the combination of clinical and CT features, and its prognostic performance was externally tested in the validation group. The predictive value of the combined model was compared with models built on the clinical and radiological attributes alone. Results: Overall, 35 infected patients (21.1%) in the training cohort and 10 patients (13.9%) in the validation cohort experienced adverse outcomes. Underlying comorbidity (hazard ratio [HR], 3.35; 95% confidence interval [CI], 1.67-6.71; p < 0.001), lymphocyte count (HR, 0.12; 95% CI, 0.04-0.38; p < 0.001) and crazy-paving sign (HR, 2.15; 95% CI, 1.03-4.48; p = 0.042) were the independent factors. The nomogram displayed a concordance index (C-index) of 0.82 (95% CI, 0.76-0.88), and its prognostic value was confirmed in the validation cohort with a C-index of 0.89 (95% CI, 0.82-0.96). The combined model provided the best performance over the clinical or radiological model (p < 0.050). Conclusion: Underlying comorbidity, lymphocyte count and crazy-paving sign were independent predictors of adverse outcomes. The prognostic nomogram based on the combination of clinical and CT features could be a useful tool for predicting adverse outcomes of patients with COVID-19.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.203-222
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• 2011

The characteristics of flood damages have been increasingly strengthened and take the form of unpredictable and unusual weather phenomena caused by climate change and climate anomalies. To prevent inundation damage caused by breach of hydraulic structure such as dam or levee, and trouble of drainage of inner basin, the prediction necessity of flood inundation area, flood risk analysis, and drawing flood risk maps have been on the rise, and the national flood risk maps have been produced. In this study, the quantitative flood vulnerability analysis was performed, which represents population living within flood-affected areas, types of economic activities, facilities affected by flood, in order to extend flood risk mapping from simple hazard concept into risk based idea. By applying it to Nakdong River basin, the flood vulnerability indices were estimated to draw flood risk maps subdivided into administrative districts. The result of this study can be applied to establish the disaster prevention measures and priority decision of disaster prevention project.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.25-38
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• 2021

Purpose: To reduce the damage caused by continuously occurring typhoons, we proposed a standardized grid so that it could be actively utilized in the prevention and preparation stage of typhoon response. We established grid-based convergence information on the typhoon risk area so that we showed the effectiveness of information used in disaster response. Method: To generate convergent information on typhoon hazard areas that can be useful in responding to typhoon situation, we used various types of data such as vector and raster to establish typhoon hazard area small grid-based information. A standardized grid model was applied for compatibility with already produced information and for compatibility of grid information generated by each local government. Result: By applying the grid system of National branch license plates, a grid of typhoon risk areas in Seoul was constructed that can be usefully used when responding to typhoon situations. The grid system of National branch license plates defines the grid size of a multi-dimensional hierarchical structure. And a grid of typhoon risk areas in Seoul was constructed using grids of 100m and 1,000m. Conclusion: Using real-time 5km resolution grid based weather information provided by Korea Meteorological Administration, in the future, it is possible to derive near-future typhoon hazard areas according to typhoon travel route prediction. In addition, the national branch number grid system can be expanded to global grid systems for global response to various disasters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• Journal of the Korean Geotechnical Society
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• v.38 no.4
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• pp.59-70
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• 2022

There is a growing interest in evaluating earthquake damage and determining disaster prevention measures due to the magnitude 5.8 earthquake in Pohang, Korea. Since the liquefaction phenomena occurred extensively in the residential area as a result of the earthquake, there was a demand for research on liquefaction phenomenon evaluation and liquefaction disaster prediction. Liquefaction is defined as a phenomenon where the strength of the ground is completely lost due to a sudden increase in excess pore water pressure caused due to large dynamic stress, such as an earthquake, acting on loose sand particles in a short period of time. The liquefaction potential index, which can identify the occurrence of liquefaction and predict the risk of liquefaction in a targeted area, can be used to create a liquefaction hazard map. However, since liquefaction assessment using existing field testing is predicated on a single borehole liquefaction assessment, there has been a representative issue for the whole targeted area. Spatial interpolation and geographic information systems can help to solve this issue to some extent. Therefore, in order to solve the representative problem of geotechnical information, this research uses the kriging method, one of the geostatistical spatial interpolation techniques, and constructs a geotechnical information database for liquefaction and spatial interpolation. Additionally, the liquefaction hazard map was created for each return period using the constructed geotechnical information database. Cross validation was used to confirm the accuracy of this liquefaction hazard map.

• Journal of the Korean Geosynthetics Society
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• v.16 no.3
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• pp.51-62
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• 2017

For the purpose of the study, of the 76 areas subject to preliminary concentrated management on sediment disaster in the downtown area, 9 areas were selected as research areas. They were classified into three stratified rock areas (Gyeongsan City, Goheung-gun and Daegu Metropolitan City), three igneous rock areas (Daejeon City, Sejong Special Self-Governing City and Wonju City) and three metamorphic rock areas (Namyangju City, Uiwang City and Inje District) according to the characteristics of the bedrock in the research areas. As for the 9 areas, analyses were conducted based on tests required to calculate soil characteristics, a predictive model for root adhesive power, loading of trees and on-the-spot research. As for a rainfall scenario (rainfall intensity), the probability of rainfall was applied as offered by APEC Climate Center (APCC) in Busan. As for the prediction of landslide risks in the 9 areas, TRIGRS and LSMAP were applied. As a result of TRIGRIS prediction, the risk rate was recorded 30.45% in stratified rock areas, 41.03% in igneous rock areas and 45.04% in metamorphic rock areas on average. As a result of LSMAP prediction based on root cohesion and the weight of trees according to crown density, it turned out to a 1.34% risk rate in the stratified rock areas, 2.76% in the igneous rock areas and 1.64% in the metamorphic rock areas. Analysis through LSMAP was considered to be relatively local predictive rather than analysis using TRIGRS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.603-610
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• 2018

The development of industry and the increase in the use of fossil fuels have accelerated the process of global warming and climate change, resulting in more frequent and intense natural disasters than ever before. Since electricity facilities are often installed outdoors, they are heavily influenced by natural disasters and the number of related accidents is increasing. In this paper, we analyzed the statistical status of domestic electrical fires, electric shock accidents, and electrical equipment accidents and hence analyzed the risk associated with climate change. Through the analysis of the electrical accidental data in connection with the various regional (metropolitan) climatic conditions (temperature, humidity), the risk rating and charts for each region and each equipment were produced. Based on this analysis, a basic electric risk prediction model is presented and a method of displaying an electric hazard prediction map for each region and each type of electric facilities through a website or smart phone app was developed using the proposed analysis data. In addition, efforts should be made to increase the durability of the electrical equipment and improve the resistance standards to prevent future disasters.

• Earthquakes and Structures
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• v.12 no.3
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• pp.321-332
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• 2017

The reverse fault is a dangerous geological hazard faced by buried steel pipelines. Permanent ground deformation along the fault trace will induce large compressive strain leading to buckling failure of the pipe. A hybrid pipe-shell element based numerical model programed by INP code supported by ABAQUS solver was proposed in this study to explore the strain performance of buried X80 steel pipeline under reverse fault displacement. Accuracy of the numerical model was validated by previous full scale experimental results. Based on this model, parametric analysis was conducted to study the effects of four main kinds of parameters, e.g., pipe parameters, fault parameters, load parameter and soil property parameters, on the strain demand. Based on 2340 peak strain results of various combinations of design parameters, a semi-empirical model for strain demand prediction of X80 pipeline at reverse fault crossings was proposed. In general, reverse faults encountered by pipelines are involved in 3D oblique reverse faults, which can be considered as a combination of reverse fault and strike-slip fault. So a compressive strain demand estimation procedure for X80 pipeline crossing oblique-reverse faults was proposed by combining the presented semi-empirical model and the previous one for compression strike-slip fault (Liu 2016). Accuracy and efficiency of this proposed method was validated by fifteen design cases faced by the Second West to East Gas pipeline. The proposed method can be directly applied to the strain based design of X80 steel pipeline crossing oblique-reverse faults, with much higher efficiency than common numerical models.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.185-190
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• 2014

Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high-lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness-associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.