• 한국반도체및디스플레이장비학회:학술대회논문집
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• 한국반도체및디스플레이장비학회 2007년도 춘계학술대회
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• pp.253-253
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• 2007

• 한국임상수의학회:학술대회논문집
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• 한국임상수의학회 2006년도 춘계학술대회
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• pp.117-117
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• 2006

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.728-732
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• 2008

일반적으로 유역의 유출량을 모의하는 경우 강우-유출모형을 구축한 후 해당 모형에서 제공하는 유출결과를 활용하고 있다. 그러나 모형에 의한 유출결과는 단편적인 유출총량에 대해서만 검증된 결과이기 때문에 기저 및 직접유출성분 각각의 적정에 대한 신뢰성 문제가 야기될 수 있다. 본 연구에서는 금강유역을 대상으로 SSARR모형을 적용하고 단순 유출결과 뿐만 아니라 유출성분별로 결과값을 도출하고, 이를 검증하기 위해 분리주파수 기법을 활용하여 관측값의 유출성분을 분리하고, 모의결과와 서로 비교하였다. 이와같이 적용 검증된 모형을 토대로 유출성분 뿐만 아니라 소유역별 습윤상황과 용수이용정보 등 유출지표를 산정하여 효율적 유출관리 지원을 위한 기초 수문정보를 제공하고자 하였다.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.951-959
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• 2011

The proposed method is based on a penalized censored regression model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log likelihood function of censored regression model. It provide the efficient computation of regression parameters including variable selection and leads to the generalized cross validation function for the model selection. Numerical results are then presented to indicate the performance of the proposed method.

• Journal of the Korean Data and Information Science Society
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• 제21권4호
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• pp.765-775
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• 2010

For the accelerated failure time (AFT) model a lot of effort has been devoted to develop effective estimation methods. AFT model assumes a linear relationship between the logarithm of event time and covariates. In this paper we propose a semiparametric support vector machine to consider situations where the functional form of the effect of one or more covariates is unknown. The proposed estimating equation can be computed by a quadratic programming and a linear equation. We study the effect of several covariates on a censored response variable with an unknown probability distribution. We also provide a generalized approximate cross-validation method for choosing the hyper-parameters which affect the performance of the proposed approach. The proposed method is evaluated through simulations using the artificial example.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2004년도 하계학술대회
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• pp.3-5
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• 2004

Balanced input 단을 갖는 IC chip과의 interface를 위하여 2.4GHz 대역의 Balun BPF를 설계하였다. $2.4{\times}2.0 (mm)$ 크기의 LTCC chip 형태로 제작하기위하여 LPF-HPF 형태를 응용한 집중소자형 Balun을 설계하고 Comb-line 형태의 BPF를 접합하여 설계 및 시뮬레이션을 하였다. 시뮬레이션 결과 Balun BPF의 삽입손실은 3.03dB, 위상차는 $170^{\circ}$, Amplitude balance는 0.09dB이다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
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• pp.294-297
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• 2006

Using a single LC panel and two lighting systems, we have developed an advanced LCD system called "Double-Sided LCD." It has only one LC panel and two lighting systems, but it can display images of the same size and resolution on both the front and the rear side. Furthermore, utilizing a simple and thin lighting system we have reduced dramatically its module thickness up to 3.0mm, much thinner than that of conventional dual-type LCD, which is quite appropriate for the use of mobile applications.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 C
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• pp.1616-1618
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• 2001

In recent the on-line partial discharge (PD) measurement using sensors, such as EMC, SSC, RTD and RFCT, as an indicator of stator winding insulation condition has been developed. RFCT sensor was placed arounding a grounding lead of surge capacitor to detecting PD. Trend of PD magnitude/phase angle/pulse number over time are useful parameter to diagnosis aging state. We have developed Radio Frequency Current Transformer(RFCT) sensor which is suitable for PD diagnostic measurement in 6.6kV rotating machines. In this paper, we describe the characteristics of RFCT sensor, such as frequency and PD magnitude using 6.6 kV model stator winding in Lab.

• Journal of the Korean Data and Information Science Society
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• 제22권3호
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• pp.589-596
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• 2011

The conditional autoregressive value at risk (CAViaR) model is useful for risk management, which does not require the assumption that the conditional distribution does not vary over time but the volatility does. But it does not provide volatility forecasts, which are needed for several important applications such as option pricing and portfolio management. For a variety of probability distributions, it is known that there is a constant relationship between the standard deviation and the distance between symmetric quantiles in the tails of the distribution. This inspires us to use a support vector quantile regression (SVQR) for volatility forecasts with the distance between CAViaR forecasts of symmetric quantiles. Simulated example and real example are provided to indicate the usefulness of proposed forecasting method for volatility.

• Journal of the Korean Data and Information Science Society
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• 제20권5호
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• pp.905-912
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• 2009

We propose a doubly penalized kernel machine (DPKM) which uses heteroscedastic location-scale model as basic model and estimates both mean and volatility functions simultaneously by kernel machines. We also present the model selection method which employs the generalized approximate cross validation techniques for choosing the hyperparameters which affect the performance of DPKM. Artificial examples are provided to indicate the usefulness of DPKM for the mean and volatility functions estimation.