• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.1
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• pp.13-26
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• 2023

Recently, as the development of underground spaces has become active due to rapid urbanization and population density, interest in the ground behavior according to the construction of underground spaces is increasing. In large cities with high population density and many buildings, ground subsidence has a great impact on structures and there may be a risk of collapse, so the analysis of ground behavior due to underground construction is essential. Previous studies have been conducted on the subsidence pattern of the surface and the deformation of the tunnel when constructing the tunnel, but analysis has rarely been conducted by using actual topographic information. Therefore, this study analyzed the difference in ground behavior between the actual topography and the flat topography. As a result, it was confirmed that ground settlement occurs at higher elevations, such as in mountainous topography, and when the numerical analysis is performed considering topographical information, the crown settlement of the tunnel is up to about approx. It showed a difference of 10 mm, and it was found that the sensitivity was less in the case of displacement of tunnel wall compared to the crown settlement and ground settlement. The numerical analysis considering the actual GIS-based topographic information presented in this study can be used to obtain more accurate surface subsidence data to understand the behavior of the upper structure due to tunnel excavation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.182-192
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• 2023

In this study, the efficacy of Engineered Cementitious Composite(ECC) jacket for masonry fences subjected to lateral dynamic load was experimentally verified through a shaking table test, comparing it with the performance of an unreinforced masonry(URM) fence. Firstly, dominant frequencies, modal damping ratios and deformed shapes were identified through an impact hammer test. URM and ECC-strengthened fences with heights of 940mm and 970mm had natural frequencies of 6.4 and 35.3Hz, and first modal damping ratios of 7.0 and 5.3%, respectively. Secondly, a shaking table test was conducted in the out-of-plane direction, applying a historical earthquake, El Centro(1940) scaled from 25 to 300%. For the URM fence, flexural cracking occurred at the interface of brick and mortar joint(i.e., bed joint) at the ground motion scaled to 50%, and out-of-plane overturning failure followed during the subsequent test conducted at the ground motion scaled to 30%. On the other hand, the ECC-jacketed fence showed a robust performance without any crack or damage until the ground motion scaled to 300%. Finally, the base shear forces exerted upon the URM and ECC-jacketed fences by the ground motions scaled to 25~300% were evaluated and compared with the ones calculated according to the design code. In contrast to the collapse risk of the URM fence at the ground motion of 1,000-year return period, the ECC-jacketed fence was estimated to remain safe up to the 4,800-year return period ground motion.

• Atmosphere
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• v.34 no.2
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• pp.139-151
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• 2024

The Yeongdong region has suffered from severe snowstorms and the relevant damage such as traffic accidents on slippery roads, and the collapse of greenhouses and temporary buildings. While a lot of research on snowfall has been conducted, the detailed study of snow crystals' phase and habit through intensive observations and the relevant microphysical analysis is still lacking. Therefore, a snowflake camera, PARSIVEL, and intensive radiosonde soundings were utilized to investigate phase and habit changes in solid precipitation. Two remarkable episodes of phase and habit changes were selected such as 19 March 2022 and 15 February 2023. Both events occurred in the synoptic condition of the High in the north and the Low passing by the south, which was accompanied by rapid temperature cooling below 2.5 km. During the events of a short period between 3 to 6 hours, the temperature at 850 hPa decreased by about 4 to 6℃. This cooling led to a change in the main habit of snow particles from riming to aggregate, identified with both MASC and PARSIVEL. Meanwhile, the LDAPS model analyses do not successively represent the rapid cooling and short-term variations of solid precipitation, probably by virtue of overestimating low-level equivalent potential temperature during these periods. The underlying causes of these the low-level temperature variations within 6 hours, still remain unclear. It might be associated with mesoscale orographic phenomenon due to the mountains and East Sea effects, which certainly needs an intensive and comprehensive observation campaign.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.3
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• pp.543-560
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• 2018

With the increased development in downtown underground space facilities that vertically cross under a railway at a shallow depth, the demand for non-open cut method is increasing. However, most construction sites still adopt the pipe roof method, where medium and large diameter steel pipes are pressed in to form a roof, enabling excavation of the inside space. Among the many factors that influence the loosening region and loads that occur while pressing in steel pipes, the size of the pipe has the largest impact, and this factor may correspond to the magnitude of load applied to the underground structure inside the steel pipe roof. The super equilibrium method (SEM) has been developed to minimize ground disturbance and loosening load, and uses small diameter pipes of approximately 114 mm instead of conventional medium and large diameter pipes. This small diameter steel pipe is called an SEM pile. After SEM piles are pressed in and the grouting reinforcement is constructed, a crossing structure is pressed in by using a hydraulic jack without ground subsidence or heaving. The SEM pile, which plays the role of timbering, is a fore-poling pile of approximately 5 m length that prevents ground collapse and supports surface load during excavation of toe part. The loosening region should be adequately calculated to estimate the spacing and construction length of the piles and stiffness of members. In this paper, we conducted a comparative analysis of calculations of loosening load that occurs during the press-in of SEM pile to obtain an optimal design of SEM. We analyzed the influence of factors in main theoretical and empirical formulas applied for calculating loosening regions, and carried out FEM analysis to see an appropriate loosening load to the SEM pile. In order to estimate the soil loosening caused by actual SEM-pile indentation and excavation, a steel pipe indentation reduction model test was conducted. Soil subsidence and soil loosening were investigated quantitatively according to soil/steel pipe (H/D).

• Horticultural Science & Technology
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• v.30 no.5
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• pp.509-518
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• 2012

The objective of this study was to determine the effect of heat shock treatments on the phytochemicals including antioxidants and anticancer materials in kale (Brassica oleracea L. var. acephala) sprouts. In study I, kale sprouts grown under the growing system for four days were soaked at 40, 50, or $60^{\circ}C$ distilled water for 10, 30, or 60 seconds, and in study II, kale sprouts were soaked at $50^{\circ}C$ distilled water for 10, 20, 30, 45, or 60 seconds. After the heat shock treatments, the sprouts were transferred into normal growing conditions and recovered there for two days. Fresh and dry weights, electrolyte leakage, total phenolic concentration, antioxidant capacity, total flavonoid concentration, phenylalanine ammonia-lyase (PAL) activity, and glucosinolates content of the sprouts were measured before and after the heat shock treatments. As a result, there was a significant decrease in the fresh and dry weight of kale sprouts treated with heat shock compared with control at harvest in study I. Especially, heat shock at $60^{\circ}C$ lead to more pronounced growth inhibition compared with heat treatments at 40 and $50^{\circ}C$. Electrolyte leakage by cell collapse was the highest in the sprouts exposed to $60^{\circ}C$ distilled water, which agreed with the growth results. Heat shock at $50^{\circ}C$ significantly induced the accumulation of phenolic compounds. In study II, fresh weight of kale sprouts at $50^{\circ}C$ heat shock showed a significant decrease compared with the control at one and two days after the treatment. However, the decrease was minimal and dry weight of kale sprouts was not significantly different from that in control. In contrast, the heat shock-treated kale sprouts had higher level of total phenolic concentration than control at harvest. Heat shock treatments at $50^{\circ}C$ for 20 seconds or more showed at least 1.5 and 1.2 times higher total phenolic concentration and antioxidants capacity than control, respectively. The change of the total flavonoid concentration was similar with that of antioxidants. PAL activity after 24 hours of heat shock was higher in all the heat shock-treated sprouts than that in control suggesting heat shock may stimulate secondary metabolic pathway in kale sprouts. Seven glucosinolates were identified in kale sprouts and soaking the sprouts with $50^{\circ}C$ water for 20 seconds had a pronounced impact on the accumulation of total glucosinolates as well as two major glucosinolates, progoitrin and sinigrin, at harvest. In conclusion, this study suggests that heat shock using hot water would be a potential strategy to improve nutritional quality of kale sprouts by inducing the accumulation of phytochemicals with antioxidant and anticancer properties.

• International Commerce and Information Review
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• v.15 no.4
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• pp.457-479
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• 2013

Through a Chinese rise, Chinese dream is actualizing as the world's great power. According to outlook of World Bank and IMF, Around 2030 China will be a great power bigger than America's economic power. The rise of China will give a huge impact to the whole world. China expands her influence through a global manufacturing base and a global market. To actualize 'Peaceful Rise' Strategy, China has many constraints. Chinese society is facing many difficult social problem due to side effects of a rapid development. Such as the spread of corruption, the severity of wealth gap, environmental degradation and energy shortage. Internationally there are containment from hegemon so-called 'China threat' dispute, Taiwan issue and territorial disputes. Western countries are hostile to China for two reasons. Based on expectations, one is China's socialist system and the other is the rising China which will compete for supremacy with Europe and America. Recent emergence of Chinese nationalism and the containment of the neighboring countries are also serious limiting factors. Domestically they have the rampant corruption in the bureaucracy, weakened capacity of Communist rule, wealth disparity due to the discriminatory economic development strategy, seriousness of rural problem, social instability, lack of social security systems and the development gap between the eastern coastal areas and western inland areas, ethnic minorities problems, the constraint of sustainable development issues due to lack of resources, environmental pollution and energy constraints. Like the former Soviet Union, China may face a dismantlement. After the rise, China may encounter possibilities of a war between great powers or a collapse of Chinese society caused by deepening internal conflict. Serious economic polarization would make peasants and urban workers, who are social vulnerable people, to turn their back to communist party and threaten the justification and the appropriateness of the ruling communist party. Chinese government will think internal system security threat is more formidable risk factor than a system security threat from the hegemon. The decline of great country comes from internal reasons rather than external reasons. To achieve peaceful rise, unification with Taiwan is an essential prerequisite. Taiwan issues are complex problems which equipped with international and domestic factors. Lack of energy resources, environmental pollution in China will bring economic crisis to Korean enterprises. Important influence to Korean economy will be a changeover of the method in economic development. It will turn the balance of investment and consumption, GDP-centered growth to consumption and environment-centered growth. Services industries including finance, environment, culture, education, health care and social welfare will grow. Change in China's growth model will give a great challenge upon the intermediate goods industry in Korea. Korea should reduce the portion of machinery, automotive, semiconductor, steel and chemical-centered export industry to China, and should increase the proportion of the service industry.

• Journal of the Korean Society of Radiology
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• v.8 no.4
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• pp.211-216
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• 2014

Radium is rock or soil of crust or uranium of building materials after radioactivity collapse process are created colorless and odorless inert gas that accrue well in sealed space like basement. It inflow to lung circulate respiratory organ and caused lung cancer because of deposition of lung or bronchial tubes. In this study, the air in the elementary school classroom nongdoeul tonkatsu place of measured values were compared using the calculated annual internal radiation exposure. La tonkatsu exposure measured in primary school classroom at least five schools when you close the windows in the average floor 0.56mSv 2 floors ground floor windows when opened 0.384mSv 048mSv 3 floors, 2 floor levels of the same three layers 0.31mSv 0.296mSv the human exposure to radon and radiation on the first floor of 3 floors above ground in a lot of exposure was moderate. When you close the window from the first floor up 0.384mSv 056mSv 3 floors with a minimum annual radiation exposure due to natural radiation in the 16 to 23.3 percent minimum 2.4mSv accounted for. When I opened the window to the maximum annual radiation exposure 2.4mSv 0.296mSv 0.31mSv least a minimum of 12.3 to 12.91% accounted for Results suggest that more than five chodeunghakgyoeun La tonkatsu domestic radon measurements conducted below regulatory requirements and internal exposure has also fall within the normal range. People The less the radiation exposure to the human body because it reduces the impact in the classroom in elementary school vent windows often reduced to the maximum radon concentration in the air, if called tonkatsu be able to reduce radiation exposure for the immune system is weak and elementary will be helpful to experiment more in the future for the school authorities called tonkatsu investigation is done to him if the action to establish a more secure school building facilities is thought would be helpful.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.161-173
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• 2021

The shipping industry plummeted and was depressed due to the global economic crisis caused by the bankruptcy of Lehman Brothers in the US in 2008. In 2020, the shipping market also suffered from a collapse in the unstable global economic situation due to the COVID-19 pandemic, but unexpectedly, it changed to an upward trend from the end of 2020, and in 2021, it exceeded the market of the boom period of 2008. According to the Clarksons report published in May 2021, the decrease in cargo volume due to the COVID-19 pandemic in 2020 has returned to the pre-corona level by the end of 2020, and the tramper bulk carrier capacity of 103~104% of the Panamax has been in the ports due to congestion. Earnings across the bulker segments have risen to ten-year highs in recent months. In this study, as factors affecting BDI, the capacity and congestion ratio of Cape and Panamax ships on the supply side, iron ore and coal seaborne tonnge on the demand side and Granger causality test, IRF(Impulse Response Function) and FEVD(Forecast Error Variance Decomposition) were performed using VAR model to analyze the impact on BDI by congestion caused by strengthen quarantine at the port due to the COVID-19 pandemic and the loading and discharging operation delay due to the infection of the stevedore, etc and to predict the shipping market after the pandemic. As a result of the Granger causality test of variables and BDI using time series data from January 2016 to July 2021, causality was found in the Fleet and Congestion variables, and as a result of the Impulse Response Function, Congestion variable was found to have significant at both upper and lower limit of the confidence interval. As a result of the Forecast Error Variance Decomposition, Congestion variable showed an explanatory power upto 25% for the change in BDI. If the congestion in ports decreases after With Corona, it is expected that there is down-risk in the shipping market. The COVID-19 pandemic occurred not from economic factors but from an ecological factor by the pandemic is different from the past economic crisis. It is necessary to analyze from a different point of view than the past economic crisis. This study has meaningful to analyze the causality and explanatory power of Congestion factor by pandemic.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.