• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.1
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• pp.44-49
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• 2003

Masan Bay is one of the most heavily polluted bay in Korea owing to the large industrial complex and urban area. Water transparency, Secchi depth in meter, was observed 33 times totally at four sites during 1995 through 2002 and analysed statistically. The range was 0.2∼7.2m, mean 204m, and variation coefficient 60% in totally. Roughly speaking, monthly mean showed lower value April or July than other months. Seasonal mean showed lower in spring or summer than other seasons. Yearly mean was lowest in '95 and '98 during 7 years. Each sampling site showed a different patterns by the monthly, seasonal or yearly transparencies. Inner bay area, S1 site, showed lowest transparency and highest variation coefficient owing to the streamlets and urban area. And it was supposed that one of the important factor affecting different transparency distribution of most seaward site, S4 site, among four sites in the Masan Bay may be the underwater effluents of urban sewage water treated.

• Nuclear industry
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• v.8 no.7 s.65
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• pp.93-95
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• 1988

소련 체르노빌원전에서 사고가 발생한지 2년이 넘었다. 우리나라에서는 방사성물질 강하 등의 영향이 거의 없었으나, 지리적으로 가까운 유럽에서는 사고 당시 심각한 영향을 받은 국가가 있었다고 한다. 경제협력개발기구/원자력기관(OECD/NEA)이 금년 1월 사고영향에 관한 보고서를 발표하였다. 다음은 방사선에 의한 영향을 중심으로 한 동 보고서의 개요이다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.463-464
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• 2007

본 논문은 경제성 및 안정성을 유지하는 최적의 전압유지범위 설정을 위해 다양한 목적함수를 최적조류계산에 이용하였다. 경제성을 위해 융통전력 최대화와 유효전력 손실최소화를 목적함수로 하였고 안정성을 위해 무효전력예비력 최대화를 목적함수로 하였다. 또한 경제성과 안정성을 모두 반영하기 위해 다목적 함수를 구성하였다. 최적화기법을 실계통에 적용하였을 때 목적함수를 얼마나 잘 만족시킬 수 있는지 각종 지표를 통해 살펴보았다. 그리고 모니터링 모선의 전압 변동 추이를 살펴보고 이를 통해 경제성 및 안정성을 유지하는 최적의 전압유지 범위설정을 하는데 활용할 수 있도록 하였다.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.1-12
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• 2023

Oceanic wind waves have been recognized as one of the important indicators of global warming and climate change. It is necessary to study the spatial and temporal variability of significant wave height (SWH) and wave direction in the Yellow Sea and a part of the East China Sea, which is directly affected by the East Asian monsoon and climate change. In this study, the spatial and temporal variability including seasonal and interannual variability of SWH and wave direction in the Yellow Sea and East China Sea were analyzed using European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) data. Prior to analyzing the variability of SWH and wave direction using the model reanalysis, the accuracy was verified through comparison with SWH and wave direction measurements from Ieodo Ocean Science Station (I-ORS). The mean SWH ranged from 0.3 to 1.6 m, and was higher in the south than in the north and higher in the center of the Yellow Sea than in the coast. The standard deviation of the SWH also showed a pattern similar to the mean. In the Yellow Sea, SWH and wave direction showed clear seasonal variability. SWH was generally highest in winter and lowest in late spring or early summer. Due to the influence of the monsoon, the wave direction propagated mainly to the south in winter and to the north in summer. The seasonal variability of SWH showed predominant interannual variability with strong variability of annual amplitudes due to the influence of typhoons in summer.

• Proceedings of the Korean Fiber Society Conference
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• 2003.04a
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• pp.157-160
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• 2003

드래프트 공정을 거친 슬라이버의 선밀도 불균제는 제품의 품질과 공정의 효율 면에서 많은 문제를 일으킨다. 이러한 불균제의 특성을 해석하고 균제성을 제고하기 위해서는 실제 불균제가 발생하는 드래프트 존 내에서 섬유집속체의 동적거동을 정확하게 묘사해 줄 이론적 모델 연구가 필요하다. 본 연구에서는 이미 제시한 드래프트 존 내에서의 섬유의 동적거동을 묘사하는 fundamental equation을 바탕으로 force-deformation의 관계를 나타내는 constitutive model의 주요 model parameter 변동이 출력 슬라이버의 두께 flucturation에 미치는 영향으르 찾아보기 위하여 model simulation을 하고, fiber openness와 직접적인 관련이 있는 model parameter u의 변동범위를 실험을 통해 살펴보았다. (중략)

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.15-31
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• 2009

The next generation IT environment is expected to be an open computing environment based on Grid computing technologies, which allow users to access to any type of computing resources through networks. The open computing environment has benefits in aspects of resource utilization, collaboration, flexibility and cost reduction. Due to the variation in performance of open computing resources, however, resource allocation simply based on users' budget and time constraints often fails to meet the Service Level Agreement(SLA). This paper proposes the Mean-Absolute Deviation(MAD) portfolio optimization approach, in which service brokers consider the uncertainty of performance of resources, and compose resource portfolios that minimize the uncertainty. In order to investigate the effect of this approach, we simulate an open computing environment with varying uncertainty levels, users' constraints, and brokers' optimization strategies. The simulation result concludes threefolds. First, the MAD portfolio optimization improves the success ratio of delivering the required performance to users. Second, the success ratio depends on the accuracy in predicting the variability of performance. Thirdly, the measured variability can also help service brokers expand their service to cost-critical users by discounting the access cost of open computing resources.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.608-613
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• 2017

In this paper, we consider the stability bound for uncertainty of delayed state variables in the linear discrete interval time-varying systems with time-varying delay time. The considered system has an interval time-varying system matrix for non-delayed states and is perturbed by the unstructured time-varying uncertainty in delayed states with time-varying delay time within fixed interval. Compared to the previous results which are derived for time-invariant cases and can not be extended to time-varying cases, the new stability bound in this paper is applicable to time-varying systems in which every factors are considered as time-varying variables. The proposed result has no limitation in applicable systems and is very powerful in the aspects of feasibility compared to the previous. Furthermore. the new bound needs no complex numerical algorithms such as LMI(Linear Matrix Inequality) equation or upper solution bound of Lyapunov equation. By numerical examples, it is shown that the proposed bound is able to include the many existing results in the previous literatures and has better performances in the aspects of expandability and effectiveness.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.408-409
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• 2015

한국전력공사에서는 2015년 4월말 기준 808개의 변전소를 운전 중에 있다. 변압기 용량으로 보면 299,734MVA에 달하고 있으며, 매년 증가하는 전력수요에 맞추어 신규 변전소 건설과 더불어 변전설비가 계속하여 확충되고 있다. 또한, 계절별 및 시간대별 부하변동에 따른 변전소 모선의 전압변동에 대응하기 위하여 Sh.C(Shunt Condenser), Sh.R(Shunt Reactor), SVC(Static Var Compensator) 등 다양한 무효전력보상 및 조절 설비들이 지속적으로 설치되고 있다. 이들 무효전력보상 설비들은 주로 변전소 모선에 전용 차단기를 통하여 연결되어 운전되고 있으며, 전용 차단기는 매일 시간대별 부하변동에 대응하여 개폐빈도가 많은 다빈도 차단기로서 잦은 개폐조작에 따른 내구성이 필요하며 변전소 모선전압을 기준전압 범위 이내로 안정적으로 유지하기 위한 신뢰성이 요구되고 있다. 본 논문에서는 345kV Sh.R 개폐용 동일유형의 345kV 50kA 1점절 다빈도 차단기에서 차단조작시 발생한 차단부 절연파괴 고장의 원인을 분석하고 재발방지를 위한 대책에 대하여 논하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1099-1108
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• 2017

Data points obtained by conducting repetitive experiments under identical environmental conditions are, theoretically, required to correspond. However, experimental data often display variations due to generated errors or noise resulting from various factors and inherent uncertainties. In this study, an algorithm aiming to determine valid bounds of input variables, representing uncertainties, was developed using probabilistic and statistical methods. Furthermore, a reliability assessment was performed to verify and validate applications of this algorithm using bolt-fastening friction coefficient data in a sample application.