• Journal of Conservation Science
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• v.37 no.5
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• pp.505-515
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• 2021

In this study, we evaluated the slope stability of the Pohang Daljeon-ri columnar joint (Natural Monuments # 415) and calculated the maximum energy, jumping height and moving distance of rockfalls using a simulation. Based on the results, we established the range of rockfall risk. The slopes of the Pohang Daljeon-ri columnar joint have dip directions of 93.79°, 131.99°, 165.54° and 259.84° from left (SW) to right (NE). Furthermore, they have a fan-like shape. The Pohang Daljeon-ri columnar joints are divided into four sections depending on the dip direction. The measurement results of the discontinuous face show that zone 1 is 125, zone 2 is 261, zone 3 is 262, zone 4 is 43. The results of slope stability analyses for each section using a stereographic projection method correspond to the range of planar and toppling failure. Although it is difficult to diagnose the type of failure, risk evaluation of currently falling rocks requires further focus. The maximum movement distance of a rockfall in the simulation was approximately 66 m and the rockfall risk range was the entire area under slope. In addition, it is difficult to forecast where a rock will fall as it rolls in various directions due to topographic factors. Thus, the installation of measures to prevent falling is suggested to secure the stability based on the results of the rockfall simulations and its probabilistic analysis.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.370-382
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• 2018

The purpose of this study is to quantitatively and effectively evaluate the factors affecting flood damage by watershed. National Water Resource Plan(MOCT, 2001) has been developed Potential Flood Damage(PFD) which indicates flood vulnerability. But, it is only a simple grouping and it does not provide guidelines for flood control planning based on detailed evaluation of sub-components. In this study, we used PFD in the Han River basin according to the method applied in the National Water Resource Plan (existing method) and improvement based on actual flood hazard area and data. As an application method, after analyzing by yearly change(2009~2014), we compared and analyzed the tendency of the sub - components that constitute the potential and risk rather than the current grouping. As the result, it was possible to accurately evaluate the existing and improved methods, and it was possible to derive the vulnerability rankings, but the existing methods have different results from the actual watershed tendency. Therefore, the PFD of the improvement method that correctly reflects past history and watershed characteristics is more appropriate for the evaluation of flood vulnerability in the watershed. In addition, it is reasonable to establish a flood control plan referring to this and prevent flood damage in advance.

• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.37-43
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• 2018

The storm surge is caused by an typhoons and it is not easy to predict the location, strength, route of the storm. Therefore, research using a scenario for storms occurrence has been conducted. In Korea, hazard maps for various scenarios were produced using the storm surge numerical simulation. Such a method has a disadvantage in that it is difficult to predict when other scenario occurs, and it is difficult to cope with in real time because the simulation time is long. In order to compensate for this, we developed a method to predict the storm surge damage by using research database. The risk grade prediction for the storm surge was performed predominantly in the study area of the East coast. In order to estimate the equation, COMSOL developed by COMSOL AB Corporation was utilized. Using some assumptions and limitations, the form of the basic equation was derived. the constants and coefficients in the equation were estimated by the trial and error method. Compared with the results, the spatial distribution of risk grade was similar except for the upper part of the map. In the case of the upper part of the map, it was shown that the resistance coefficient, k was calculated due to absence of elevation data. The SIND model is a method for real-time disaster prediction model and it is expected that it will be able to respond quickly to disasters caused by abnormal weather.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.755-758
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• 2014

In this paper, we propose effective Deblocking Filter hardware architecture for High Efficiency Video Coding encoder. we propose Deblocking Filter hardware architecture with less processing time, filter ordering for low area design, effective memory architecture and four-pipeline for a high performance HEVC(High Efficiency Video Coding) encoder. Proposed filter ordering can be used to reduce delay according to preprocessing. It can be used for realtime single-port SRAM read and write. it can be used in parallel processing by using two filters. Using 10 memory is effective for solving the hazard caused by a single-port SRAM. Also the proposed filter can be used in low-voltage design by using clock gating architecture in 4-pipeline. The proposed Deblocking Filter encoder architecture is designed by Verilog HDL, and implemented by 100k logic gates in TSMC $0.18{\mu}m$ process. At 150MHz, the proposed Deblocking Filter encoder can support 4K Ultra HD video encoding at 30fps, and can be operated at a maximum speed of 200MHz.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.272-282
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• 2019

Although the knowledge of current seismicity is a critical information for making and implementing effective earthquake-related policy, the detailed seismicity information of the metropolitan areas with high-population density has been largely underestimated due to the high-level of cultural noise and small earthquake magnitude. This study presents 12 earthquakes including 2 earthquakes previously known and 10 additional earthquakes occurred from 2010 to 2017 in Busan, but they were unreported by the Korea Meteorological Administration. Matched filter technique is used to detect micro-earthquakes. Although the epicenters of micro-earthquakes though present a distinguished linearity, a correlation with faults in the area is unknown. A repeated micro-seismicity suggests that there are subsurface structures responsible for observed events. If large earthquakes occur along the fault in Busan, they may cause catastrophic natural disasters. Given the fact that the recent earthquakes did not accompany any surface signatures, it is highly recommended that the current micro-seismicity be investigated, and updated seismicity information be incorporated into establishing active fault maps in Korea.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.442-449
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• 2019

Objective : Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT. Methods : We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation. Results : The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900). Conclusion : This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.299-311
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• 2020

This paper analyzes the distribution of water vapor pressure and relative humidity in complex terrains by collecting weather observation data at 6 locations in the valley in Jungdae-ri, Ganjeon-myeon, Gurye-gun, Jeolla South Province and 14 locations in Akyang-myeon, Hadong-gun, Gyeongsang South Province, which form a single drainage basin in rural and mountainous regions. Previously estimated water vapor pressure used in the early warning system for agrometeorological hazard and actual water vapor pressure arrived at using the temperature and humidity that were measured at the highest density (1.5 m above ground) at every hour in the valley of Jungdae-ri between 19 December 2014 and 23 November 2015 and in the valley of Akyang between 15 August 2012 and 18 August 2013 were compared. The altitude-specific gradient of the observed water vapor pressure varied with different hours of the day and the difference in water vapor pressure between high and low altitudes increased in the night. The hourly variations in the water vapor pressure in the weather stations of the valley of Akyang with various topographic and ground conditions were caused by factors other than altitude. From the observed data of the study area, a coefficient that adj usts the variation in the water vapor pressure according to the specific difference in altitude and estimates it closer to the actual measured level was derived. Relative humidity was simulated as water vapor pressure estimated against the saturated water vapor pressure, thus, confirming that errors were further reduced using the derived coefficient than with the previous method that was used in the early warning system.

• Tuberculosis and Respiratory Diseases
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• v.84 no.2
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• pp.125-133
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• 2021

Background: The coronavirus disease (COVID-19) can manifest in a range of symptoms, including both asymptomatic systems which appear nearly non-existent to the patient, all the way to the development of acute respiratory distress syndrome (ARDS). Specifically, COVID-19-associated pneumonia develops into ARDS due to the rapid progression of hypoxia, and although arterial blood gas analysis can assist in halting this deterioration, the current environment provided by the COVID-19 pandemic, which has led to an overall lack of medical resources or equipment, has made it difficult to administer such tests in a widespread manner. As a result, this study was conducted in order to determine whether the levels of oxygen saturation (SpO₂) and the fraction of inhaled oxygen (FiO₂) (SF ratio) can also serve as predictors of ARDS and the patient's risk of mortality. Methods: This was a retrospective cohort study conducted from February 2020 to Mary 2020, with the study's subjects consisting of COVID-19 pneumonia patients who had reached a state of deterioration that required the use of oxygen therapy. Of the 100 COVID-19 pneumonia cases, we compared 59 pneumonia patients who required oxygen therapy, divided into ARDS and non-ARDS pneumonia patients who required oxygen, and then investigated the different factors which affected their mortality. Results: At the time of admission, the ratios of SpO₂, FiO₂, and SF for the ARDS group differed significantly from those of the non-ARDS pneumonia support group who required oxygen (p<0.001). With respect to the predicting of the occurrence of ARDS, the SF ratio on admission and the SF ratio at exacerbation had an area under the curve which measured to be around 85.7% and 88.8% (p<0.001). Multivariate Cox regression analysis identified that the SF ratio at exacerbation (hazard ratio [HR], 0.916; 95% confidence interval [CI], 0.846-0.991; p=0.029) and National Early Warning Score (NEWS) (HR, 1.277; 95% CI, 1.010-1.615; p=0.041) were significant predictors of mortality. Conclusion: The SF ratio on admission and the SF ratio at exacerbation were strong predictors of the occurrence of ARDS, and the SF ratio at exacerbation and NEWS held a significant effect on mortality.

• The Journal of Engineering Geology
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• v.31 no.2
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• pp.165-178
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• 2021

The influence of Soil-Water Characteristic Curve (SWCC) fitting parameters for an unsaturated natural slope was evaluated through seepage and slope stability analysis as a function of rainfall. Soil samples were collected from the study area in Jirisan National Park and the physical and mechanical characteristics of unsaturated soil layers were measured in laboratory tests. The saturation depth was calculated via seepage analysis by changing fitting parameters α, the parameter related to the Air Entry Value (AEV) and n, the parameter related to the slope of the SWCC in the range of natural conditions. Slope stability analysis using the limit equilibrium method considered the calculated depth of saturation. Results from seepage analysis for various rainfall conditions indicate the saturation depth in the soil layer suddenly increased as the fitting parameter α decreased; the saturation time for the entire soil layer also decreased. Slope stability analysis considering the calculated depth of saturation shows that the slope safety factor rapidly decreased as the fitting parameter α decreased, whereas the variation in slope safety factor was very small when n increased. Hence, fitting parameter α has a large effect on saturation depth during rainfall and therefore on slope stability, whereas slope stability is relatively unaffected by the fitting parameter n.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.226-237
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• 2021

Coastal safety accidents are characterized by a high proportion of human negligence and repeated occurrences of accidents caused by the same factors. The Korea Coast Guard prepares and implements various countermeasures to prevent accidents at coastal safety accident sites. However, there is a shortage of safety facilities and safety management personnel according to the limited budget. In addition, the ability to be proactively and proactively respond is low due to the limitations of the coastal safety accident risk forecasting system, which relies on the meteorological warning of the Korea Meteorological Administration. In this study, as part of preparing the foundation for establishing a preemptive and active coastal safety management system that can manage accident-causing factors, predict and evaluate risk, and implement response and mitigation measures after an accident occurs before coastal safety accidents occur. The establishment of a risk assessment system was proposed. The main evaluation factors and indicators for risk assessment were established through the analysis of the status of coastal safety accidents. The risk assessment methodology was applied to 40 major hazardous areas designated and managed by the Korea Coast Guard.