• Atmosphere
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• v.31 no.4
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• pp.405-420
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• 2021

Forest fire happens every year at Yeongdong, Gangwon-do, due to the strong local wind during the spring time and it causes a huge damage. This wind is named "Yangganjipung" or "Yanggangjipung" that blows along Yeongdong. However, the occurrence conditions of the wind have been still unclear. To identify the occurrence mechanism of local strong wind through three-dimensional observation data, Gangwon Regional Meteorological Administration performed Joint Gangwon-Yeongdong 3D Observation Project in 2020. The special observation was carried out for 6 times from March to April. The observation data was analyzed by focusing on the structure of synoptic pressure distribution and inversion layer. The result showed that the strength of wind is different depending on the latitude of low pressure, intensity of inversion layer, and changes on height in the south-high and north-low pressure distribution. As the interval of the upper and lower parts of the inversion layer was narrow, the strength of the wind became stronger, which is one of the observational characteristics of the springtime wind pattern at Yeongdong, Gangwon-do. In future, the clear mechanism of the local wind in the Yeongdong during the spring time is expected to be verified based on the accumulative observation data and close analysis.

• Journal of Veterinary Science
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• v.22 no.5
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• pp.72.1-72.15
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• 2021

It has been speculated that bats serve as reservoirs of a huge variety of emerging coronaviruses (CoVs) that have been responsible for severe havoc in human health systems as well as negatively affecting human economic and social systems. A prime example is the currently active severe acute respiratory syndrome (SARS)-CoV2, which presumably originated from bats, demonstrating that the risk of a new outbreak of bat coronavirus is always latent. Therefore, an in-depth investigation to better comprehend bat CoVs has become an important issue within the international community, a group that aims to attenuate the consequences of future outbreaks. In this review, we present a concise introduction to CoVs found in bats and discuss their distribution in Southeast Asia. We also discuss the unique adaptation features in bats that confer the ability to be a potential coronavirus reservoir. In addition, we review the bat coronavirus-linked diseases that have emerged in the last two decades. Finally, we propose key factors helpful in the prediction of a novel coronavirus outbreak and present the most recent methods used to forecast an evolving outbreak.

• Environmental Engineering Research
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• v.23 no.4
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• pp.406-419
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• 2018

In planning public service systems such as waterworks, the design population is very important factor. Owing to the limitations of the indirect method, two new models, which take into consideration urban characteristics, were developed to accurately predict external migration rate (EMR), which is an essential component in estimating reliably the design population. The root mean square error (RMSE) between the model values and observed values were 10.12 and 15.58 for the metropolitan cities and counties respectively and were lower compared to RMSE values of 27.31 and 28.79 obtained by the indirect method. Thus, the developed models provide a more accurate estimate of EMR than the indirect method. In addition, the major influencing factors for external migration in counties were development type, ageing index, number of businesses. On the other hand, the major influencing migration factors for cities were project scale, distance to city center, manufacturing size, population growth rate and residential environment. Future medium and long-term studies would be done to identify emerging trends to appropriately inform policy making.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.912-928
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• 2019

Crowd behavior analysis research has revealed a central role in helping people to find safety hazards or crime optimistic forecast. Thus, it is significant in the future video surveillance systems. Recently, the growing demand for safety monitoring has changed the awareness of video surveillance studies from analysis of individuals behavior to group behavior. Group detection is the process before crowd behavior analysis, which separates scene of individuals in a crowd into respective groups by understanding their complex relations. Most existing studies on group detection are scene-specific. Crowds with various densities, structures, and occlusion of each other are the challenges for group detection in diverse crowded scenes. Therefore, we propose a group detection approach called Collective Interaction Filtering to discover people motion interaction from trajectories. This approach is able to deduce people interaction with the Expectation-Maximization algorithm. The Collective Interaction Filtering approach accurately identifies groups by clustering trajectories in crowds with various densities, structures and occlusion of each other. It also tackles grouping consistency between frames. Experiments on the CUHK Crowd Dataset demonstrate that approach used in this study achieves better than previous methods which leads to latest results.

• Earthquakes and Structures
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• v.17 no.4
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• pp.387-398
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• 2019

On the basis that ground motions may arrive at a structure from any horizontal direction and that different directions of seismic incidence would result in different structural dynamic responses, this paper focuses on orienting the crucial seismic incidence of transmission tower-line systems based on the wavelet energy method. A typical transmission tower-line system is chosen as the case study, and two finite element (FE) models are established in ABAQUS, with and without consideration of the interaction between the transmission towers and the transmission lines. The mode combination frequency is defined by considering the influence of the higher-order modes of the structure. Subsequently, wavelet transformation is performed to obtain the total effective energy input and the effective energy input rate corresponding to the mode combination frequency to further judge the critical angle of seismic incidence by comparing these two performance indexes under different seismic incidence angles. To validate this approach, finite element history analysis (FEHA) is imposed on both FE models to generate comparative data, and good agreement is found. The results demonstrate that the wavelet energy method can forecast the critical angle of seismic incidence of a transmission tower-line system with adequate accuracy, avoiding time-consuming and cumbersome computer analysis. The proposed approach can be used in future seismic design of transmission tower-line systems.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.785-790
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• 2019

Convergence and advancement between technologies such as Artificial Intelligence, Big Data, and the Internet of Things have a significant impact on the regional flagship industry. All technical fields are used as a converged technology by connecting between technology and industry. In order to understanding the recent technical trend, it is possible to easily realized the technical trend research and analysis through keyword search using patent information. The purpose of this study is to identify patent trends applied to convergence technology in the 4th Industrial Revolution age in radiation technology development and to present patent trends and analysis for strengthening and utilizing radiation-related industrial technology competitiveness and to apply them to demand technology and forecast future promising technologies.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.1
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• pp.37-48
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• 2020

Logistics centers, distribution centers, or warehouse facilities increasingly dominate urban and suburban landscapes, their enormous but blank, repetitive facades completely overshadowing adjacent buildings. Mostly ignored by architects, this new building type symbolically represents the arrival of post-anthropocene, or post-urbicene era of architecture, in which an increasing portion of our built environment will not be intended for human occupancy, but rather for use by machines and artificial intelligence. As a new wave of logistics centers are becoming more automated, and more supersized, it is important to deepen architects' understanding of the organizational logic and programming factors that inform the overall design decisions for these facilities. With a particular focus on three case studies--Coupang, E-Mart, and Amazon Fulfillment Centers, this research examines the current trends in automation and expansion of logistics centers, and offers an analysis and forecast for future facilities in South Korea.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.91-101
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• 2021

The paper examines the impact of the COVID-19 pandemic on the stock market prices. The vector autoregression model (VAR) has been used in this analysis to survey 341 stocks on the Ho Chi Minh City Stock Exchange (HOSE) for the period from January 23, 2020 to December 31, 2020. The empirical results obtained from the analysis of 11 economic sectors suggest that there is a statistically significant impact relationship between COVID-19 and the healthcare and utility industries. Additional findings show a statistically significant negative impact of COVID-19 on the utility share price at lag 1. Analysis of impulse response function (IRF) and forecast error variance decomposition (FEVD) show an inverse reaction of utility stock prices to the impact of COVID-19 and a gradual disappearing shock after two steps. Major findings show that there is a clear negative effect of the COVID-19 pandemic on share prices, and the daily increase in the number of confirmed cases, indicate that, in future disease outbreaks, early containment measures and positive responses are necessary conditions for governments and nations to protect stock markets from excessive depreciation. Utility stocks are among the most severely impacted shares on financial exchanges during a pandemic due to the high risk of immediate or irreversible closure of manufacturing lines and poor demand for basic amenities.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.311-331
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• 2021

Climate change with extreme hydrological events has become a significant concern for agricultural water systems. Climate change affects not only irrigation availability but also agricultural water requirement. In response, adaptation strategies with soft and hard options have been considered to mitigate the impacts from climate change. However, their implementation has become progressively challenging and complex due to the interconnected impacts of climate change with socio-economic change in agricultural circumstances, and this can generate more uncertainty and complexity in the adaptive management of the agricultural water systems. This study was carried out for the agricultural water supply system in Seongju dam watershed in Seonju-gun, Gyeongbuk in South Korea. The first step is to identify system disturbances. Climate variation and socio-economic components with historical and forecast data were investigated Then, as the second step, problematic trends of the critical performance were identified for the historical and future climate scenarios. As the third step, a system structure was built with a dynamic hypothesis (causal loop diagram) to understand Seongju water system features and interactions with multiple feedbacks across system components in water, agriculture, and socio-economic sectors related to the case study water system. Then, as the fourth step, a mathematical SD (system dynamics) model was developed based on the dynamic hypothesis, including sub-models related to dam reservoir, irrigation channel, irrigation demand, farming income, and labor force, and the fidelity of the SD model to the Seongju water system was checked.

• Geomechanics and Engineering
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• v.24 no.3
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• pp.281-293
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• 2021

Uncertainties in geomechanical input parameters which mainly related to inappropriate data acquisition and estimation due to lack of sufficient calibration information, have led wellbore instability not yet to be fully understood or addressed. This paper demonstrates a workflow of employing Quantitative Risk Assessment technique, considering these uncertainties in terms of rock properties, pore pressure and in-situ stresses to makes it possible to survey not just the likelihood of accomplishing a desired level of wellbore stability at a specific mud pressure, but also the influence of the uncertainty in each input parameter on the wellbore stability. This probabilistic methodology in conjunction with Monte Carlo numerical modeling techniques was applied to a case study of a well. The response surfaces analysis provides a measure of the effects of uncertainties in each input parameter on the predicted mud pressure from three widely used failure criteria, thereby provides a key measurement for data acquisition in the future wells to reduce the uncertainty. The results pointed out that the mud pressure is tremendously sensitive to UCS and SHmax which emphasize the significance of reliable determinations of these two parameters for safe drilling. On the other hand, the predicted safe mud window from Mogi-Coulomb is the widest while the Hoek-Brown is the narrowest and comparing the anticipated collapse failures from the failure criteria and breakouts observations from caliper data, indicates that Hoek-Brown overestimate the minimum mud weight to avoid breakouts while Mogi-Coulomb criterion give better forecast according to real observations.