• Journal of Korea Trade
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• v.26 no.3
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• pp.45-62
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• 2022

Purpose - Using unexpected changes in geopolitical tensions on the Korean peninsula as a quasi-natural experimental setting, we examine whether and how geopolitical risks travel across borders through firm-level imports and exports linkages. We also test whether the effects are driven by either imports or exports and assess whether firms can effectively hedge themselves against geopolitical risks. Design/methodology - We focus on a series of unanticipated geopolitical events taken place in Korea in 2018. Making use of the shocks to geopolitical climate, we identify five milestone events toward peace talks. We employ the event studies methodology. We examine heterogenous firm-level stock price reactions around key event dates depending on firms' exposure to geopolitical risks. As a measure of firms' exposure to geopolitical risks in Korea, we utilize a text-based measure of firm-level trade links. When a firm announces and discusses its purchase of inputs from Korea or sales of outputs to Korea in their annual disclosure filings, we define a firm to have a trade relationship with Korea and have exposure to Korean geopolitical risks. Similarly, we use a measure of a firm's hedging policies based on a firm's textual mention of the use of foreign exchange derivatives in their annual disclosure. Findings - We find that U.S. firms that have direct trade links to Korea gained significantly more value when the intensity of geopolitical risks drops compared to firms without such trade links to Korea. The effects are pronounced for firms purchasing inputs from or selling outputs to Korea. We find that the effectiveness of foreign exchange hedging against geopolitical risks is limited. Originality/value - We document the international transmission of geopolitical uncertainty through trade linkages. Export links as well as import links serve as important nexus of transmission of geopolitical risks across borders. Hedging strategies involving foreign-exchanges derivatives do not seem to insulate firms again geopolitical risks. With the recent movements of localization and reshuffling of the global value chain, our results suggest a significant impact of geopolitical risks in Korea on the construction of the global value chain.

• Korea Journal of Hospital Management
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• v.28 no.1
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• pp.24-36
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• 2023

Purposes: The purpose of this study was to analyze the factors associated with current smoking status in Wonju-si and Chuncheon-si, and to study the cause of difference in smoking rates between these two regions. Methodology: Data was from the National Health Insurance Service database from 2019 to 2020. Current smoking status was based on the response to the health examination questionnaire. Logistic regression analysis was conducted to identify factors associated with current smoking status. The study included 207,307 individuals from Wonju-si and 173,698 individuals from Chuncheon-si. Findings: The smoking rate of Wonju-si was 19.83%, and Chuncheon-si was 18.20%, showing a difference in the smoking rates between the two regions. Logistic regression analysis found that men, those aged 40-49, being a self-employed insured, a medical-aid beneficiary, having a lower income, working in construction, transport, storage, communication, or manufacturing industries, having a high-risk drinking level and being underweight were significantly associated with a higher likelihood of smoking(p<0.05). Additionally, having a chronic disease was associated with a lower likelihood of smoking in the case of Chuncheon-si(p<0.05). Practical Implication: This study found the differences of factors associated with smoking rates between the two regions and could provide implications for establishing intervention programs or policies that could contribute to lowering the smoking rate in areas with high smoking rates.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.85-85
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• 2020

South Korea experiences few large scale erosion and sedimentation problems, however, there are numerous local sedimentation problems. A reliable and consistent approach to modelling and management for sediment processes are desirable in the country. In this study, field measurements of sediment concentration from 34 alluvial river basins in South Korea were used with the Modified Einstein Procedure (MEP) to determine the total sediment load at the sampling locations. And then the Flow Duration-Sediment Rating Curve (FD-SRC) method was used to estimate the specific degradation for all gauging stations. The specific degradation of most rivers were found to be typically 50-300 tons/㎢·yr. A model tree data mining technique was applied to develop a model for the specific degradation based on various watershed characteristics of each watershed from GIS analysis. The meaningful parameters are: 1) elevation at the middle relative area of the hypsometric curve [m], 2) percentage of wetland and water [%], 3) percentage of urbanized area [%], and 4) Main stream length [km]. The Root Mean Square Error (RMSE) of existing models is in excess of 1,250 tons/㎢·yr and the RMSE of the proposed model with 6 additional validations decreased to 65 tons/㎢·yr. Erosion loss maps from the Revised Universal Soil Loss Equation (RUSLE), satellite images, and aerial photographs were used to delineate the geospatial features affecting erosion and sedimentation. The results of the geospatial analysis clearly shows that the high risk erosion area (hill slopes and construction sites at urbanized area) and sedimentation features (wetlands and agricultural reservoirs). The result of physiographical analysis also indicates that the watershed morphometric characteristic well explain the sediment transport. Sustainable management with the data mining methodologies and geospatial analysis could be helpful to solve various erosion and sedimentation problems under different conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.99-106
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• 2006

Due to both global warming and constructions of seadike/seawalls, continuously or abruptly rising tendencies of extreme high water levels have been detected at Kunsan and Mokpo harbors. This paper deals firstly with the separation of each effect, namely global warming effect and construction effect, on increases of water level quantitatively by a linear regression method. And then, it can be explained why and how the extreme high water levels had been risen just after constructions at both harbors. A numerical simulation of $M_2$ tidal constituent at Mokpo coastal zone shows that the tidal amplification by constructions is mainly due to the extinguishment of TCE at Mokpogu. The tidal flat effect makes the amplification more deepen at spring tide or extreme high tide, which results in the increase of inundation risk at Mokpo harbor. A frequency analysis method is applied, which is shown to be effective at such a site of having non-homogeneous tidal data due to constructions as Mokpo harbor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.81-89
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• 2009

CM(Configuration Management) is a field of management that focuses on establishing and maintaining consistency of a product's performance and its functional and physical attributes with its requirements, design, and operational information throughout its life. Recently upcoming concept of CM, regardless of various definitions, consists of the organization and the process for value creation through project change management, value preservation by Risk, Project Management implementation by Change management. The CM provide a basis for, and a record of, the project's performance in meeting the scope, time, cost. Overseas international companies have already adopted the CM system and enjoyed the benefits arising from such systems. And the CM provides perspectives and insights applicable to all types of projects. This study presents the review on the current systems now in use at jobsites and known to be efficient, and the introduction and application of configuration systems now at big issue. Hereby indicates the connective system consisted of work process, change control and knowledge referring to the methods and actual cases as an effective promotion of CM.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.551-555
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• 2009

This study is performed to apply a standard to evaluate fire protection assessment for tunnel structures when a fire breaks out in the road tunnel. Recently, a number of road tunnels have been rapidly increased and fire risk also multiplyed according to extend tunnel length, due to natural features and environmentally-friendly road construction in Korea. But we have not yet been prescribed appropriate time-temperature curve for tunnel fire. Therefore, we presented fire design model and investigated time-temperature curve proposed by a foreign country considering traffic, a kinds of vehicles which are a basis of heat rate. At the end, Hydrocarbon modified curve applied as design fire model by using numerical analysis and presented design fire model and examined the effects of tunnel structures.

• Journal of the Korean Geotechnical Society
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• v.39 no.10
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• pp.27-39
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• 2023

To effectively manage flood risk, it is crucial to assess the stability of flood defense structures like levees under extreme flood conditions. This study focuses on the time-dependent probabilistic assessment of embankment slope stability when subjected to rapid water level drops. We integrate seepage analysis results from finite element analysis with slope stability analysis and employ Monte Carlo simulations to investigate the time-dependent behavior of the slope during rapid drawdown. The resulting probability of failure is used to develop fragility curves for the levee slope. Notably, the probability of slope failure remains low up to a specific water level, sharply increasing beyond that threshold. Furthermore, the fragility curves are strongly influenced by the rate of drawdown, which is determined through hydraulic analysis based on flood scenarios. Climate change has a significant impact on the stability of the water-side slope of the embankment due to water level fluctuations.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.135-146
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• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.195-206
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• 2024

Shenzhen Innovation Light source Facility (SILF) is a 3.0 GeV fourth generation diffraction limited synchrotron light source currently under construction in Shenzhen. The SILF storage ring is proposed to use two 500 MHz single cell superconducting radio frequency (SRF) cavities to provide 2.4 MV RF voltage. In this study, we examined the geometric structure of mature CESR superconducting cavities and adopted a beam-pipe-type extraction scheme for high-order modes (HOM). One of the objectives of SRF cavity design and optimization in this study is to reduce E_p/E_acc and B_p/E_acc as much as possible to reduce power loss and ensure stable operation of the cavity. To reduce the risk of beam instability and thermal breakdown, the HOM and Multipacting (MP) are simulated. Moreover, the mechanical properties of the cavity are analyzed, including frequency sensitivity from pressure of liquid helium (LHe), stress, tuning, Lorentz force detuning (LFD), the microphone effect, and buckling. By comprehensive design and optimization of 500 MHz single-cell SRF cavities, a superconducting cavity for SILF storage ring was developed. This paper will detailed present the design and simulation.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.107-115
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• 2024

This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.