• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.2161-2166
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• 2009

It is important for 0-6 hour nowcasting to provide for a high-quality initial condition in a meso-scale atmospheric model by a data assimilation of several observation data. The polarimetric radar data is expected to be assimilated into the forecast model, because the radar has a possibility of measurements of the types, the shapes, and the size distributions of hydrometeors. In this paper, an impact on rainfall prediction of the data assimilation of hydrometeor types (i.e. raindrop, graupel, snowflake, etc.) is evaluated. The observed information of hydrometeor types is estimated using the fuzzy logic algorism. As an implementation, the cloud-resolving nonhydrostatic atmospheric model, CReSS, which has detail microphysical processes, is employed as a forecast model. The local ensemble transform Kalman filter, LETKF, is used as a data assimilation method, which uses an ensemble of short-term forecasts to estimate the flowdependent background error covariance required in data assimilation. A heavy rainfall event occurred in Okinawa in 2008 is chosen as an application. As a result, the rainfall prediction accuracy in the assimilation case of both hydrometeor types and the Doppler velocity and the radar echo is improved by a comparison of the no assimilation case. The effects on rainfall prediction of the assimilation of hydrometeor types appear in longer prediction lead time compared with the effects of the assimilation of radar echo only.

• 한국시스템다이내믹스연구
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• 제15권3호
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• pp.5-36
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• 2014

The purpose of this paper is to develop a System Dynamics model for estimating the volume of forest resources in the future and simulating the volume of function of public benefit linked to forest resources in dynamic manner. Also it is to analyze the impact when the volume of forest land conversion is controlled by policy using the SD model. The analysis was done at nation-wide for the simulation period 2000 to 2040. Estimated forest area was 6.2 million ha and estimated growing stock was $4.7\;billion\;m^3$ in 2040 from the future forecast without policies. Changing of forest resources, 13.9 billion tons of forest-ground-water storage was estimated, $1.8\;million\;m^3$ of erosion control of forest was estimated and 377 million tons of $CO_2$ absorption was estimated. As a result of simulation with two alternatives, forest area was less reduced and growing stock was bigger than do nothing policy. Also, function of public benefit reflected by changes of forest resources was enhanced. This study contributes to estimate the quantitatively measured volume of forest resources and function of public benefit over the 30 years in Korean forest land in scientific way. Using this SD model, decision maker would develop forest land policies more delicately for deserving forest resources and increasing the volume of function of public.

• 유통과학연구
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• 제20권10호
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• pp.61-66
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• 2022

Purpose: Predicting the financial distress distribution of an enterprise is important to warn enterprises about their future. Predicting the possibility of financial distress helps companies have action plans to avoid the possibility of bankruptcy. In this study, the author conducted a forecast of the financial distress distribution of enterprises. Research design, data and methodology: The forecasting method is based on Logit and Discriminant analysis models. The data was collected from companies listed on Vietnam Stock Exchange from 2012 to 2020. In which there are both companies suffer from financial distress and non-financial distress. Results: The forecast analysis results show that the Logistic model has better predictability than the Discriminant analysis model. At the same time, the results also indicate three main factors affecting the financial distress of enterprises at all three research stages: (1) Liquidity, (2) Interest payment, and (3) firm size. In addition, at each stage, the impact of factors on financial distress differs. Conclusions: From the results of this study, the author also made several recommendations to help companies better control company operations to avoid falling into financial distress. Adjustments to current assets, debt, and company expansion considerations are the most important factors for companies.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.952-955
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• 2005

In the early 90's, we had serious shortage of construction engineers in Korea. The shortage was acute especially in construction quality control and supervision area, which were gaining social attention due to the road bridge and the department store collapse that took the hundreds of lives in the early 90's in Seoul, Korea. In order to meet the high demand of construction engineers, the engineering license regulations were changed in 1995. Engineers who did not pass the written exam but have equivalent working experience are given engineering license to practice engineering legally. Since year 2000, while the severe engineer-shortage has been resolved, the opposite situation has occurred: there is serious over-supply of construction engineers. Policy makers and engineering practitioners are agreed to bring back the old-fashioned written exam engineer licensing system like before 1995, i.e., no more written exam exemption. However, the engineers who obtained license without taking written exam may not want to go back to old policy which would take their license. It is required to provide appropriate grace period before the new policy takes effect to minimize the impact of the changes. This paper forecasts the supply-demand of construction engineers providing the basis for the most appropriate policy changes.

• 한국건설관리학회논문집
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• 제24권6호
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• pp.81-90
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• 2023

Climate change has resulted in increased frequency and intensity of heat waves, which poses a significant threat to the health and safety of construction workers, particularly those engaged in labor-intensive and heat-stress vulnerable working environments. To address this challenge, this study aimed to propose an interpretable machine learning approach for forecasting personal heat strain by considering the cumulative effect of heat exposure as a situational variable, which has not been taken into account in the existing approach. As a result, the proposed model, which incorporated the cumulative working time along with environmental and personal variables, was found to have superior forecast performance and explanatory power. Specifically, the proposed Multi-Layer Perceptron (MLP) model achieved a Mean Absolute Error (MAE) of 0.034 (℃) and an R-squared of 99.3% (0.933). Feature importance analysis revealed that the cumulative working time, as a situational variable, had the most significant impact on personal heat strain. These findings highlight the importance of systematic management of personal heat strain at construction sites by comprehensively considering the cumulative working time as a situational variable as well as environmental and personal variables. This study provided a valuable contribution to the construction industry by offering a reliable and accurate heat strain forecasting model, enhancing the health and safety of construction workers.

• 화약ㆍ발파
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• 제22권3호
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• pp.43-55
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• 2004

최근 들어 타워형 구조물의 사용 연한이 초과함에 따라 구조물 안전 진단 결과에 따라 철거 작업 혹은 국부적인 성능개선 공사론 수행하고 있다. 그러나 철거 작업시 가능한 한 휴지기간(Shut down)을 단축하여야 한다는 측면 및 경제성 측면에서 발파해체공법은 매우 매력적인 철거수단으로 관심이 증대되고 있으나, 철거시 발생되는 진동으로 인해 인접한 정밀 기기류에 대한 영향을 우려하여 철거 기간과 비용측면에서 상대적으로 불리한 기계식 철거공법을 선호하고 있다. 따라서, 본 연구는 연돌과 같은 타워형 구조물의 발파해체시 붕괴된 부재가 지면과 충돌시 발생되는 지반진동 수준을 예측하는 기법과 진동을 저감할 수 있는 각종 방법에 대한 효과를 축소모형시험을 통해 도출하였다.

• 한국군사과학기술학회지
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• 제27권1호
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• pp.24-30
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• 2024

The gas-gun test is a experimental approach employed to validate the operational or structural stability when subjected to the impact energy encountered during launch or target collision. Predicting the outcomes of the gas-gun test has traditionally relied on empirical knowledge, due to numerous factors such as the bird assembly's shape, weight, material, and flight velocity. However, due to the nonlinearity and complex interactions between these variables, numerous tests are necessary to identify the necessary requirements, resulting in significant expense and time consumption during the process. The objective of this study is to forecast the variations in impact energy in future tests by developing a numerical model and analysis that aligns with the test outcomes, utilizing the ABAQUS Explicit. The outcome of the numerical analysis produced a framework that anticipates the peak g and the duration of the actual gas-sun test results, throughout post-processing techniques using FFT and LPF filters.

• 대기
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• 제30권2호
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• pp.169-181
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• 2020

We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

• 대기
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• 제30권2호
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• pp.195-207
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• 2020

This study aims to introduce the structure of the impact-based heat health warning system on 165 counties in South Korea developed by the National Institute of Meteorological Sciences. This system was developed using the daily maximum perceived temperature (PTmax), which is a human physiology-based thermal comfort index, and the Local ENSemble prediction system for the probability forecasts. Also, A risk matrix proposed by the World Meteorological Organization was employed for the impact-based forecasts of this system. The threshold value of the risk matrix was separately set depending on regions. In this system, the risk level was issued as four levels (GREEN, YELLOW, ORANGE, RED) for first, second, and third forecast lead-day (LD1, LD2, and LD3). The daily risk level issued by the system was evaluated using emergency heat-related patients obtained at six cities, including Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan, for LD1 to LD3. The high-risks level occurred more consistently in the shorter lead time (LD3 → LD1) and the performance (r_s) was increased from 0.42 (LD3) to 0.45 (LD1) in all cities. Especially, it showed good performance (r_s = 0.51) in July and August, when heat stress is highest in South Korea. From an impact-based forecasting perspective, PTmax is one of the most suitable temperature indicators for issuing the health risk warnings by heat in South Korea.

• The Journal of Asian Finance, Economics and Business
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• 제7권6호
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• pp.551-560
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• 2020

This research investigates the impact of vocational training on wages of ethnic minority labors in emerging countries; Vietnam is the case study. The study uses secondary data from 2014 to 2018 collected through Vietnam Household Living Standards Surveys (VHLSS) conducted by the General Statistics Office. In order to analyze the impact of vocational training on wages of ethnic minority areas in Vietnam, this research creates ethnic area variables. According to Vietnamese regulations, ethnic areas are communes of 51 different provinces, inhabited by ethnic minority people. The statistics from VHLSS in 2018, show that the proportion of labors of working age with a certificate was 22.5%. The research employs Heckman Sample Selection Model to estimate the impact of vocation training on wage of labors in ethnic minority areas. The results show that vocational training plays a crucial role in improving the wages of ethnic minorities and has a positive impact. However, apart from the achieved outcomes, vocational training and job creation for ethnic minorities are not without limitations and shortcomings. Based on the findings, some recommendations to ethnic minority labors, enterprises and the Government are proposed to encourage participation in vocational training for the purpose of promoting the efficiency of the labor market.