• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1007-1015
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• 2017

This paper proposes a new control technique of energy storage system (ESS) for smoothing the active power of renewable energy sources (RES) such as photovoltaic and wind turbine generation. As the penetration of RES into grid increases, it is difficult to maintain the permissible level of power quality, that is, voltage and frequency fluctuation in power systems. To solve this problem, ESS control methods using low pass filter (LPF) have been proposed for mitigating the fluctuation of RES output. However, those have a lot of drawbacks which need to be supplemented. Hence, this paper presents the improved active power control with additional reactive power control for maintaining power quality properly. The proposed method minimizes the capacity of ESS to be required for smoothing RES output fluctuation through mitigation of phase delay problem in LPF. In addition, the voltage regulation improves by using additional reactive power control. The proposed method was verified through simulation analysis using PSCAD/EMTDC.

• 전기학회논문지
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• 제62권2호
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• pp.149-154
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• 2013

Short term load forecasting for electric power demand is essential for stable power system operation and efficient power market operation. High accuracy of the short term load forecasting can keep the power system more stable and save the power market operation cost. We propose an optimal coefficient selection method for exponential smoothing model in short term load forecasting on weekdays. In order to find the optimal coefficient of exponential smoothing model, load forecasting errors are minimized for actual electric load demand data of last three years. The proposed method are verified by case studies for last three years from 2009 to 2011. The results of case studies show that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.

• Journal of Computational Design and Engineering
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• 제3권3호
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• pp.191-197
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• 2016

Since 3D measurement technologies have been widely used in manufacturing industries edge detection in a depth image plays an important role in computer vision applications. In this paper, we have proposed an edge detection process in a depth image based on the image based smoothing and morphological operations. In this method we have used the principle of Median filtering, which has a renowned feature for edge preservation properties. The edge detection was done based on Canny Edge detection principle and was improvised with morphological operations, which are represented as combinations of erosion and dilation. Later, we compared our results with some existing methods and exhibited that this method produced better results. However, this method works in multiframe applications with effective framerates. Thus this technique will aid to detect edges robustly from depth images and contribute to promote applications in depth images such as object detection, object segmentation, etc.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.279-282
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• 1997

Bayesian reconstruction methods for emission computed tomography have been a topic of interest in recent years, partly because they allow for the introduction of prior information into the reconstruction problem. Early formulations incorporated priors that imposed simple spatial smoothness constraints on the underlying object using Gibbs priors in the form of four-nearest or eight-nearest neighbors. While these types of priors, known as "membrane" priors, are useful as stabilizers in otherwise unstable ML-EM reconstructions, more sophisticated prior models are needed to model underlying source distributions more accurately. In this work, we investigate whether the "thin plate" model has advantages over the simple Gibbs smoothing priors mentioned above. To test and compare quantitative performance of the reconstruction algorithms, we use Monte Carlo noise trials and calculate bias and variance images of reconstruction estimates. The conclusion is that the thin plate prior outperforms the membrane prior in terms of bias and variance.

• Communications for Statistical Applications and Methods
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• 제16권3호
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• pp.519-528
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• 2009

This paper deals with nonparametric estimation of discontinuous regression curve. Quite number of researches about this topic have been done. These researches are classified into two categories, the indirect approach and direct approach. The major goal of the indirect approach is to obtain good estimates of jump locations, whereas the major goal of the direct approach is to obtain overall good estimate of the regression curve. Thus it seems that two approaches are quite different in nature, so people say that the comparison of two approaches does not make much sense. Therefore, a thorough comparison of them is lacking. However, even though the main issue of the indirect approach is the estimation of jump locations, it is too obvious that we have an estimate of regression curve as the subsidiary result. The point is whether the subsidiary result of the indirect approach is as good as the main result of the direct approach. The performance of two approaches is compared through a simulation study and it turns out that the indirect approach is a very competitive tool for estimating discontinuous regression curve itself.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.815-816
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• 2008

In this paper, we evaluate depth image preprocessing for 3D data service based on DIBR over T-DMB. We evaluate two preprocessing methods of depth images. These are gaussian smoothing and adaptive smoothing. The results show that adaptive smoothing is more suitable for images with sharp transition of depth.

• Journal of Advanced Marine Engineering and Technology
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• 제34권7호
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• pp.943-950
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• 2010

An efficient meshfree method based on a stabilized conforming nodal integration method is developed for elastoplastic contact analysis of metal forming processes. In this approach, strain smoothing stabilization is introduced to eliminate spatial instability in Galerkin meshfree methods when the weak form is integrated by a nodal integration. The gradient matrix associated with strain smoothing satisfies the integration constraint for linear exactness in the Galerkin approximation. Strain smoothing formulation and numerical procedures for path-dependent problems are introduced. Applications of metal forming analysis are presented, from which the computational efficiency has been improved significantly without loss of accuracy.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2005년도 춘계 학술대회 발표논문집
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• pp.91-94
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• 2005

The performance of speech recognition is degraded by the mismatch between training and test environments. Many methods have been presented to compensate for additive noise and channel effect in the cepstral domain, and Cepstral Mean Subtraction (CMS) is the representative method among them. Recently, high order cepstral moment normalization method has introduced to improve recognition accuracy. In this paper, we apply high order moment normalization method and smoothing filter for real-time processing. In experiments using Aurora2 DB, we obtained error rate reduction of 49.7% with the proposed algorithm in comparison with baseline system.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.809-817
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• 2012

We propose a semiparametric inference for a generalized varying coefficient partially linear model(VCPLM) for negative binomial data. The VCPLM is useful to model real data in that varying coefficients are a special type of interaction between explanatory variables and partially linear models fit both parametric and nonparametric terms. The negative binomial distribution often arise in modelling count data which usually are overdispersed. The varying coefficient function estimators and regression parameters in generalized VCPLM are obtained by formulating a penalized likelihood through smoothing splines for negative binomial data when the shape parameter is known. The performance of the proposed method is then evaluated by simulations.

• 한국정밀공학회지
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• 제20권4호
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• pp.174-182
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• 2003

Recently, medical imaging has taken interest on CAD based solution for anatomical part fabrication or finite element analysis of human body. In principle, contours representing object boundary are obtained through image processing techniques. Surface models are then approximated by a skinning method. For this, various methods should be applied to medical images and contours. The major bottleneck of the reconstruction is to remove shape inconsistency between contours and to generate the branching surface. In order to solve these problems, bi-directional smoothing and the composite contour generation method are proposed. Bi-directional smoothing has advantage of removing the shape inconsistency between contours and minimizing shrinkage effect with a large number of iterations. The composite contour by the proposed method ensures smooth transition in branching region.