• Title/Summary/Keyword: 강건모형

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위성자료를 이용한 미계측 유역의 장기유출모의 평가 -임진강 유역을 중심으로

  • Kang, Keon Kuk;Jeung, Se Jin;Lee, Suk Ho;Kim, Byung Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.453-453
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    • 2015
  • 미계측 유역에서의 수문 예측은 유역의 다차원 시공간에서 일어나고 있는 수문학적 기능에 대한 깊은 이해와 성찰을 요구한다. 유역면적의 2/3가 미계측 지역인 임진강 유역은 북한지역과 중첩하고 있어 관측자료가 불충분 하고 소량의 관측자료가 존재하더라도 기후변화로 인해 환경이 변화하기 때문에 미계측 지역 연구에 적당하다. 이에 따라 수문학적 반응을 예측할 수 있도록 비접촉 비파괴적인 도구를 이용하여 수집된 자료를 통해 미계측 유역에 대한 정확한 신뢰성 구축을 마련할 필요가 있다고 판단된다. 신뢰성 구축을 위한 방법으로는 현장답사 및 항공사진에 비하여 넓은 지역을 한번에 관측할 수 있는 Landsat TM 영상을 이용하여 북한의 지형과 토지피복특성 등을 구축하고, 준분포형 모형인 SLURP를 이용하여 소유역으로 구분 된 ASA의 하도 추적을 통해 전체유역의 출구지점 유출량을 산정하였다. 또한 예측 불확실성을 감소시키기 위해 wamis에서 제공하는 GIS Data와 위성영상의 Data를 비교하여 분석하였다. 그 결과 미계측 지역의 불확실성을 최소화 시킬 수 있는 비교 분석이 가능하였다.

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The Efficiency Analysis of National R&D Programs for Drug Development Using Range Adjusted Measure (영역조절모형(RAM)을 활용한 신약개발 국가연구개발사업의 효율성 분석)

  • Um, Ik-Cheon;Baek, Chulwoo;Hong, Seho
    • Journal of Korea Technology Innovation Society
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    • v.19 no.4
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    • pp.711-735
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    • 2016
  • Drug Development is very important for promoting public health and pharmaceutical industry. There has been many studies on the efficiency of drug development, but there are few studies on the drug development R&D performed by government. Since CCR model assumes unidirectional influence of input and output, it is not appropriate to analyze the efficiency of R&D due to the time-lag and spill-over effect. Also, BBC model which assumes variable returns to scale has difficulty in deriving priorities between decision making units. Recently, Range Adjusted Measure (RAM) model has been suggested in R&D efficiency analysis. RAM model measures the efficincy by eliminating inefficiencies under variable returns to scale assumption, and its strong monotonicity enables to provide clear priorities between decision making units. In this study, we analyzed the efficiency of national R&D programs for drug development using the two-step approach, including RAM model and Tobit regression analysis, and discussed major policy implications.

Does the Real Estate Market affect the Unemployment Rate in Korea? (한국에서 부동산시장은 실업률에 영향을 미치는가?)

  • Myunghoon Han;Heonyong Jung
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.119-124
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    • 2023
  • This study analyzed the impact of the real estate changes on the unemployment rate in Korea. Using monthly data from January 2013 to February 2023, the study employed a multiple regression analysis model. The key findings are as follows: First, there was a significant causal relationship between the real estate changes and the unemployment rate. Specifically, an increase in the real estate market led to a significant decrease in the unemployment rate, while a decrease in the real estate market resulted in a significant increase in the unemployment rate. Second, an increase in the loan interest rate was found to significantly reduce the unemployment rate, while a rise in interest rates had positive effects on the employment. Furthermore, an increase in inflation was associated with a significant rise in the unemployment rate. Moreover, an increase in the number of permits issued for housing construction significantly reduced the unemployment rate. Lastly, conducting robustness tests by substituting variables did not significantly alter the analysis results, indicating the robustness of the impact of the real estate changes on the unemployment rate. Based on the above analysis, it can be inferred that the fluctuations in real estate prices in South Korea are linked to fluctuations in the unemployment rate, and stable management of the real estate market may contribute to the stability of the unemployment rate.

Estimation of Energy Price Elasticity of per Capita CO2 Emissions under Environmental Kuznets Hypothesis (환경 쿠즈네츠 가설하의 일인당 이산화탄소 배출량의 에너지 가격 탄력성 추정)

  • Lee, Gwanghoon
    • Journal of Environmental Policy
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    • v.11 no.2
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    • pp.55-71
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    • 2012
  • This paper attempts to estimate the energy price elasticity of per capita $CO_2$ emissions, which helps to understand the influence of recent energy price increase on the natural reduction of $CO_2$ emissions. For this purpose, this study researched panel data of twenty-nine OECD countries from 1978 to 2009 and adopted estimation models for testing the environmental Kuznets hypothesis. Estimation results show that the 1% increase of energy price index will cause a statistically significant decrease of per capita $CO_2$ emissions by 0.26 ~ 0.31%, which is substantial enough for policy consideration. Also Kuznet curves in estimation models were identifed, the turning points of income lie between 22.2~48.5 thousand US dollars, depending on model specifications.

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Asymmetric Price Responses of Industrial Energy Demand in Korea (산업부문 에너지 수요의 비대칭 가격반응)

  • Sukha Shin
    • Environmental and Resource Economics Review
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    • v.32 no.4
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    • pp.267-292
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    • 2023
  • In this paper, we estimate a time series model of energy demand in the industrial sector with an asymmetric response to energy prices. Including the asymmetric response to energy prices in the model strengthens robustness of the cointegration relationship and reduces the variation of the estimated coefficients across the estimating methods. We find that rising energy prices have a larger impact on energy demand than falling energy prices, with the largest impact occurring when energy prices rise to new highs. The estimation results are partially improved when using gross output rather than value added as a measure of production. Using single equation methods to estimate the asymmetric response model, the elasticity of gross output ranged from 1.05 to 1.09 and the elasticity of price-rise ranged from -0.48 to -0.56, which is similar to the results of international studies.

Characteristics of Tsunami Propagation through the Korean Straits and Statistical Description of Tsunami Wave Height (대한해협에서의 지진해일 전파특성과 지진해일고의 확률적 기술)

  • Cho, Yong-Jun;Lee, Jae-Il
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.18 no.4
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    • pp.269-282
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    • 2006
  • We numerically studied tsunami propagation characteristics through Korean Straits based on nonlinear shallow water equation, a robust wave driver of the near field tsunamis. Tsunamis are presumed to be generated by the earthquake in Tsuhima-Koto fault line. The magnitude of earthquake is chosen to be 7.5 on Richter scale, which corresponds to most plausible one around Korean peninsula. It turns out that it takes only 60 minutes for leading waves to cross Korean straits, which supports recently raised concerns at warning system might be malfunctioned due to the lack of evacuation time. We also numerically obtained the probability of tsunami inundation of various levels, usually referred as tsunami hazard, along southern coastal area of Korean Peninsula based on simple seismological and Kajiura (1963)'s hydrodynamic model due to tsunami-generative earthquake in Tsuhima-Koto fault line. Using observed data at Akita and Fukaura during Okushiri tsunami in 1993, we verified probabilistic model of tsunami height proposed in this study. We believe this inundation probability of various levels to give valuable information for the amendment of current building code of coastal disaster prevention system to tame tsunami attack.

Financial Factors Influencing Corporate Cash Reserves of Firms in Chungcheong Province in the Korean Capital Markets (충청권 소재 제조업체들의 현금 유동성 수준에 대한 재무적 분석)

  • Kim, Hanjoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.1
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    • pp.679-687
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    • 2017
  • This study examines financial factors affecting cash holdings of firms in the domestic capital markets. Specifically, this study focuses on regional firms with headquarters in Chungcheong province, the Republic of Korea, which features little previous research concentrating on the firms in the particular region. Three primary hypotheses were empirically tested utilizing robust econometric models, including static panel data, Tobit regression, and logistic models.Results reveal only five explanatory variables, including DSO, LIQUID, LEVERAGE, PMARGIN, and SIZE, showed statistically significant effects on the level of cash holdings among the nine variables studied. In addition two IDVs, LEVERAGE and FOS, showed significant differentiated effects between firms with headquarters in North and South Chungcheong regions. With continued debate among interested parties on the optimal level of cash reserves, the study provides a new vision for the optimal cash reserves for firms with headquarters in Chungcheong Province, where unprecedented socio-economic factors are driven.

Numerical Analysis of Nonlinear Shoaling Characteristics over Surf Zone Using SPH and Lagrangian Dynamic Smagronsky Model (Lagrangian Dynamic Smagronsky 난류모형과 SPH를 이용한 쇄파역에서의 비선형 천수거동에 관한 연구)

  • Cho, Yong-Jun;Lee, Heon
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.19 no.1
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    • pp.81-96
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    • 2007
  • Nonlinear shoaling characteristics over surf zone are numerically investigated based on spatially averaged NavierStokes equation. We also test the validity of gradient model for turbulent stresses due to wave breaking using the data acquainted during SUPERTANK LABORATORY DATA COLLECTION PROJECT(Krauss et al., 1992). It turns out that the characteristics length scale of breaking induced current is not negligible, which firmly stands against ever popular gradient model, ${\kappa}-{\varepsilon}$ model, but favors Large Eddy Simulation with finer grid. Based on these observations, we model the residual stress of spatially averaged NavierStokes equation after Lagrangian Dynamic Smagorinsky(Meneveau et al., 1996). We numerically integrate newly proposed wave equations using SPH with Gaussian kernel function. Severely deformed water surface profile, free falling water particle, queuing splash after landing of water particle on the free surface and wave finger due to structured vortex on rear side of wave crest(Narayanaswamy and Dalrymple, 2002) are successfully duplicated in the numerical simulation of wave propagation over uniform slope beach, which so far have been regarded very difficult features to mimic in the computational fluid mechanics.

Empirical Analyses on the Financial Profile of Korean Chaebols in Corporate Research & Development Intensity (국내 자본시장에서의 재벌 계열사들의 연구개발비 비중에 대한 재무적 실증분석)

  • Kim, Hanjoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.4
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    • pp.232-241
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    • 2019
  • This study examines one of the conventional and controversial issues in modern finance. Specifically, this study identifies financial determinants of corporate R&D intensity for firms belonging to Korean Chaebols. Empirical estimation procedures are applied to derive more robust results of each hypothesis test. Static panel data, Tobit regression and stepwise regression models are employed to obtain significant financial factors of R&D expenditures, while logit, probit and complementary log-log regression models are used to detect financial differences between Chaebol firms and their counterparts not classified as Chaebols. Study results found the level of R&D intensity in the prior fiscal year, market-value based leverage ratio and firm size empirically showed their significance to account for corporate R&D intensity in the first hypothesis test, whereas the majority of explanatory variables had important power on a relative basis. Assuming that the current circumstances in the domestic capital market may necessitate gradual changes of Korean Chaebols in terms of their socio-economic function, the results of this study are expected to contribute to identifying financial antecedents that can be beneficial to attain optimal level of corporate R&D expenditures for Chaebol firms on a virtuous cycle.

Convergence Implementing Emotion Prediction Neural Network Based on Heart Rate Variability (HRV) (심박변이도를 이용한 인공신경망 기반 감정예측 모형에 관한 융복합 연구)

  • Park, Sung Soo;Lee, Kun Chang
    • Journal of the Korea Convergence Society
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    • v.9 no.5
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    • pp.33-41
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    • 2018
  • The purpose of this study is to develop more accurate and robust emotion prediction neural network (EPNN) model by combining heart rate variability (HRV) and neural network. For the sake of improving the prediction performance more reliably, the proposed EPNN model is based on various types of activation functions like hyperbolic tangent, linear, and Gaussian functions, all of which are embedded in hidden nodes to improve its performance. In order to verify the validity of the proposed EPNN model, a number of HRV metrics were calculated from 20 valid and qualified participants whose emotions were induced by using money game. To add more rigor to the experiment, the participants' valence and arousal were checked and used as output node of the EPNN. The experiment results reveal that the F-Measure for Valence and Arousal is 80% and 95%, respectively, proving that the EPNN yields very robust and well-balanced performance. The EPNN performance was compared with competing models like neural network, logistic regression, support vector machine, and random forest. The EPNN was more accurate and reliable than those of the competing models. The results of this study can be effectively applied to many types of wearable computing devices when ubiquitous digital health environment becomes feasible and permeating into our everyday lives.