• Journal of the Korean Institute of Gas
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• v.25 no.6
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• pp.7-13
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• 2021

Various research has been done on fires and explosions at gas stations at home and abroad. However, only studies of off-site damage in the event of fire at the gas station were conducted, and research on fire at the auxiliary facilities in the gas station was insufficient. The gas station is a place where anyone can easily access dangerous goods. As the risk of fire increases due to the recent increase of auxiliary facilities such as convenience stores and car repair shops in gas stations, it is important to detect the effects of fire on the main oil refinery in case of fire and to verify the validity of existing regulations. In this thesis, we conducted a study to find out the effect of radiation heat on the separation between fixed and fixed oil reactors in the event of fire at an auxiliary facility. Simulation was modelled using FDS 5.5.3 Version, and the size of the fire source was configured with 13 fire assessment devices and the heat emission rate per unit area was entered. Simulation shows that the separation distance of 2 m does not secure the safety of the gas pump in the event of fire at the auxiliary facilities, and radiation heat does not damage at the separation distance of at least 4 m. Accordingly, facilities that can block radiant heat in the event of fire at auxiliary facilities, and measures to limit the use of auxiliary facilities or to re-impose the separation between buildings and fixtures will be needed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.159-165
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• 2023

While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.

• Journal of the Korean Geotechnical Society
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• v.23 no.4
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• pp.161-167
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• 2007

In this study, ultimate lateral load capacity of piles is analyzed with consideration of lateral stress effect. Based on results obtained in this study, a method for the estimation of ultimate lateral load capacity is proposed. This makes it possible to more realistically estimate the ultimate lateral load capacity under various stress states caused by in-situ soil condition and pile installation process. Calibration chamber test results with various soil conditions were used in the analysis. From the test results, it was found that effect of the lateral stress was greater than that of the vertical stress on the ultimate lateral load capacity of piles. It was also found that, as the relative density increases, displacements required to reach the ultimate state increases, showing relative displacements of around 14% and 18-25% for $D_R$ : 55% and 86%, respectively. Based on results obtained in this study, a methodology for the estimation of ultimate lateral load capacity of piles using correction factors was proposed. Results from proposed method matched well measured results.

• Journal of Industrial Convergence
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• v.21 no.7
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• pp.29-39
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• 2023

In the recent period, there have been numerous earthquakes both domestically and internationally, and buildings in South Korea are particularly vulnerable to seismic design and earthquake damage. Therefore, the objective of this study is to discover an effective method for assessing the seismic vulnerability of buildings and conducting a density analysis of high-risk structures. The aim is to model this approach and validate it using data from pilot area(Seoul). To achieve this, two modeling techniques were employed, of which the predictive accuracy of the statistical analysis technique was 87%. Among the machine learning techniques, Random Forest Model exhibited the highest predictive accuracy, and the accuracy of the model on the Test Set was determined to be 97.1%. As a result of the analysis, the district rating revealed that Gwangjin-gu and Songpa-gu were relatively at higher risk, and the density analysis of at-risk buildings predicted that Seocho-gu, Gwanak-gu, and Gangseo-gu were relatively at higher risk. Finally, the result of the statistical analysis technique was predicted as more dangerous than those of the machine learning technique. However, considering that about 18.9% of the buildings in Seoul are designed to withstand the Seismic intensity of 6.5 (MMI), which is the standard for seismic-resistant design in South Korea, the result of the machine learning technique was predicted to be more accurate. The current research is limited in that it only considers buildings without taking into account factors such as population density, police stations, and fire stations. Considering these limitations in future studies would lead to more comprehensive and valuable research.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.4
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• pp.20-36
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• 2022

This study aims to provide basic data for high-quality street tree management by setting reasonable management items and appropriate unit prices by reviewing the adequacy of current street tree management. Currently, street tree management items, except for street tree pruning, use general landscape tree quantity per unit for the street tree management quantity per unit. KEPCO (Korea Electric Power Corporation) applied pruning items from standard electric production infrastructure and carried out the activities at an average unit price of 51% lower for heavy pruning and 39% lower for light pruning than the standard estimate. This was judged to be a level that could not maintain or increase the quality of street tree management. It was determined that an appropriate standard unit price for street tree management was necessary. To improve the quantity per unit for the proper management of street trees, it was necessary to review costs in the field. However, due to the absence of data on actual construction costs in the domestic landscape field, detailed items of the US RSMeans Building Construction Cost Data (RSMeans) were reviewed, and the actual construction costs were calculated by applying personal domestic expenses. As a result, the standard of the estimated unit showed a good ratio of 107% for heavy pruning of street tree pruning compared to the actual construction cost, but light pruning was underestimated with a 59% ratio. Shrub pruning was 82%, weeding was 92%, tree fertilization was 87%, and windbreak wall installation was 91% under-engineered. In addition, it was also confirmed that the watering by sprinkler trucks and chemical spraying were over-designed compared to the actual construction cost at the rates of 118% and 124%, respectively. Due to the specificity of the street trees, the increase in personal expenses and the input cost of equipment, such as road safety controls, were judged to be the main cause of the underestimation of items. Therefore, it is necessary to add items related to street trees and general landscape trees to the landscape maintenance items of the standard of the estimated unit.

• Korean Journal of Soil Science and Fertilizer
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• v.27 no.2
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• pp.65-71
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• 1994

This study was conducted to investigate the influence of treatment of fly ash on heavy metal contents in the arable soils. Rice was cultivated on the two types of paddy field(clay loam and sandy loam soil) with 0, 4, 8, 12t/10a of anthracite fly ash and bituminous coal fly ash, respectively. And soybean was cultivated on the same types of upland field with those of 0, 3, 6, 9t/10a, respectively. At the harvest time, the heavy metal contents in surface and subsoil were investigated. The results were summarized as follows : 1. Anthracite fly ash. 1) In the paddy field of clay loam, the contents of Cu and Zn in the surface soil and Cd and Ni in the subsoil were increased with the increase of the amount of fly ash applied, but the others didn't show that tendency. 2) In the paddy field of sandy loam, only the content of Fe was increased in the surface and subsoils. 3) In the case of upland soil, the concentration of Ni and Cr in the surface soil and Cd in the subsoil were increased in the clay loam soil, and those of Cr in the surface soil and Pb in the subsoil were increased in the sandy loam soil. 2. Bituminous coal fly ash 1) In the paddy field of clay loam, the contents of Cu and Zn in the subsoil were increased with increase of the amount of fly ash applied, but in the case of sandy loam, those of Pb and Ni in the surface soil were increased. 2) In the upland soil of clay loam, the concentration of Ni in the surface soil and Pb in the subsoil were increased. 3) In case of upland soil of sandy loam, the contents of Cr and Fe were increased in the surface and subsoil, respectively, but those of Cu and Mn were increased in the both of the surface and subsoil.

• Journal of Hospice and Palliative Care
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• v.17 no.3
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• pp.179-184
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• 2014

Purpose: We investigated the safety and efficacy of peripherally inserted central catheters (PICCs) in terminally ill cancer patients. Methods: A retrospective review was conducted on patients who underwent PICC at the hospice-palliative division of KEPCO (Korea Electric Power Corporation) Medical Center between January 2013 and December 2013. All PICCs were inserted by an interventional radiologist. Results: A total of 30 terminally ill cancer patients received the PICC procedure during the study period. Including one patient who had had two PICC insertions during the period, we analyzed a total of 31 episodes of catheterization and 571 PICC days. The median catheter life span was 14.0 days (range, 1~90 days). In 25 cases, catheters were maintained until the intended time (discharge, transfer, or death), while they were removed prematurely in six other cases (19%; 10.5/1000 PICC days). Thus, the catheter maintenance success rate was 81%. Of those six premature PICC removal cases, self-removal due to delirium occurred in four cases (13%; 7.0/1000 PICC days), and catheter-related blood stream infection and thrombosis were reported in one case, each (3%; 1.8/1000 PICC days). Complication cases totaled eight (26%; 14.1/1000 PICC days). The time to complication development ranged from two to 14 days and the median was seven days. There was no PICC complication-related death. Conclusion: Considering characteristics of terminally ill cancer patients, such as a poor general condition, vulnerability to trivial damage, and a limited period of survival, PICC could be a safe intravenous procedure.

• Korean Journal of Soil Science and Fertilizer
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• v.27 no.3
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• pp.220-225
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• 1994

This study was conducted to investigate the influence of treatment of fly ash on heavy metal contents in the grain. Rice was cultivated on the two types of paddy field, clay loam and sandy loam soil, with 0, 4, 8, 12t/10a of anthracite fly ash and bituminous coal fly ash, respectively. And soybean was cultivated on the same types of upland field with those of 0, 3, 6, 9t/10a, respectively. Also. rice and soybean were cultivated the same types of paddy and upland field with those ashes of 0, 12ton/10a and 0, 9ton/10a, yearly for three years. At the harvest time, the heavy metal contents in rice and soybean were Investigated. The results were summarized as follows : 1. Amount of application. 1) The contents of Cd in brown rice increased in the clay loam soil. Cr and Ni increased sandy loam soil with the application of anthracite fly ash. 2) The contents of Zn in rice increased in the sandy loam soil with the application of bituminous coal fly ash. 3) The contents of Cu in soybean increased with the application of anthracite and bituminous coal fly ash, but Zn, Pb, Cr and Ni increased only with the bituminous. 2. Successive application. 1) The contents of Cd in brown rice increased in the clay and sandy loam soil, however Cu, Zn, Ni, Cr and Fe increased only in sandy loam soil with the anthracite fly ash. 2) The contents of Cr in soybean were increased in the clay and sandy loam soil, but Cu, Fe increased only sandy loam soil with anthracite fly ash. 3) The contents of Cd, Zn, and Cr in brown rice increased in the clay and sandy loam soil, but those of Cu, Mn increased only in the sandy loam soil with application of bituminous. 4) The contents of Cd, Pb, and Cr in soybean increased in the sandy loam soil with the application of bituminous coal fly ash.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.1 no.1
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• pp.127-156
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• 2006

This paper introduced successful case studies of the EIP (Entrepreneurship Intensive Programs) programs that are planed by 5MBA (Small and Medium Business Administration) and executed by Hoseo University and Jinju National University in 2004. Therefore, the illustrations and examples used in this paper are based on the EIP programs of those schools. Currently there are five graduate schools for Entrepreneurship educations that are originated from the EIP program models and those graduateschools are actively and successfully working. The purpose of this paper is to find out the diffusing strategies of the Entrepreneurship spirits and Entrepreneurship Education programs after careful analysis and review of the EIP programs. The main factors of the Success of the EIP are as follows. First, there were excellent modules of the education process. Second, there were firm and clear goals of the education. Three, there were differentiated contents of the entrepreneurship education programs. Four. each and every education performance was monitored. Five, during the programs, real start-up cases were actually handled and students had many opportunities to present their cases. However, there were some shortcomings to improve and change of the entrepreneurship education. First of all, it was very difficult to make proper education formation that is fit in the purpose of the program. Second, motivating students to find out their own business opportunities so as to turn them into real business was not satisfactory or easy. Third, there were some limitations in distributing and executing the EIP budgets. Therefore, to improve the efficiency of the Entrepreneurship education, following expanding strategies should be complemented. First, continuous redesigning of the entrepreneurship education programs is very important. Second, the specialization of the contents of the entrepreneurship education programs is essential. Third, there should be some discretionary room for the management of the entrepreneurship programs. Fourth, it is also important activating the entrepreneurship networks among schools of the entrepreneurship education. Finally, it is necessary to give some incentives and motivations based on the proper performance evaluation system.