• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.57-58
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• 2009

임베디드 시스템이 복잡해질수록, 성능 병목을 파악할 수 있는 성능 분석도구가 요구되고 있다. 현존하는 리눅스 기반의 소프트웨어 성능 분석 도구는 전체 시스템 관점에서 소프트웨어 계층에 따라 응용 소프트웨어의 실행 흐름을 파악하기에는 한계가 있다. 본 논문에서는 모든 소프트웨어 계층에서의 실행 흐름을 일관적으로 파악할 수 있는 문맥 분석 기법을 제안한다. 이 도구를 통해서 사용자 영역의 사용자 정의 함수와 라이브러리 함수, 커널 영역에서의 시스템 호출과 커널 이벤트에 대한 호출자와 피호출자에 대한 관계를 모두 파악할 수 있다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.337-343
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• 2014

This paper presents a continuum-based shape design sensitivity analysis(DSA) method for crack propagation problems using a reproducing kernel method(RKM), which facilitates the remeshing problem required for finite element analysis(FEA) and provides the higher order shape functions by increasing the continuity of the kernel functions. A linear elasticity is considered to obtain the required stress field around the crack tip for the evaluation of J-integral. The sensitivity of displacement field and stress intensity factor(SIF) with respect to shape design variables are derived using a material derivative approach. For efficient computation of design sensitivity, an adjoint variable method is employed tather than the direct differentiation method. Through numerical examples, The mesh-free and the DSA methods show excellent agreement with finite difference results. The DSA results are further extended to a shape optimization of crack propagation problems to control the propagation path.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.124-132
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• 2011

In a modern electronic warfare, radar signal environments become more denser and complex. Therefor the capability of reliable signal analysis techniques is required for ES(Electronic warfare Support) system to identify and analysis individual emitter signals from received signals. In this paper, we propose the new signal grouping algorithm to ensure the reliable signal analysis and to reduce the cost of the signal processing steps in the ES. The proposed grouping algorithm uses KDE(Kernel Density Estimator) and its CDF(Cumulative Distribution Function) to compose windows considering the statistical distribution characteristics based on the radar frequency modulation type. Simulation results show the good performance of the proposed technique in the signal grouping.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.127-136
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• 2013

This paper proposes a video deblurring algorithm which maintains uniform sharpness between frames. Unlike the previous algorithms using fixed parameters, the proposed algorithm keeps uniform sharpness by adjusting parameters for each frame. First, we estimate the initial blur kernel and perform deconvolution, then measure the sharpness of the deblurred image. In order to maintain uniform sharpness, we adjust the regularization parameter and kernel according to the examined sharpness, and perform deconvolution again. The experimental results show that the proposed algorithm achieves outstanding deblurring results while providing consistent sharpness.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.211-222
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• 2013

We consider the problem of nonparametrically estimating the conditional quantile function from censored data and propose new estimators here. They are based on local logistic regression technique of Lee et al. (2006) and "double-kernel" technique of Yu and Jones (1998) respectively, which are modified versions under random censoring. We compare those with two existing estimators based on a local linear fits using the check function approach. The comparison is done by a simulation study.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.443-446
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• 2003

프로세스 복구 기법은 장시간 실행을 요하는 프로세스에서 시스템 결함으로 인하여 발생하는 심각한 피해를 최소화하기 위하여 절대적으로 요구된다. 프로세스의 무결성을 지원하기 위한 예방 및 회피책은 결함 발생의 원인 규명과 예측에 의한 오버헤드가 있다. 본 논문에서는 이러한 오버헤드를 최소화하기 위한 결함 허용 프로세스 복구 기법을 제시한다. 제시한 기법은 프로세스의 실행 상태 저장 및 복구 기능을 위한 두 개의 시스템 호출을 설계하고, 리눅스 커널 2.4.18 내부에 구현하여 그 타당성을 검토하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.75-88
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• 2008

This paper presents a spatial-level nonparametric multi-focus image fusion technique based on kernel estimates of input image blocks' underlying class-conditional probability density functions. Image fusion is approached as a classification task whose posterior class probabilities, P($wi{\mid}Bikl$), are calculated with likelihood density functions that are estimated from the training patterns. For each of the C input images Ii, the proposed method defines i classes wi and forms the fused image Z(k,l) from a decision map represented by a set of $P{\times}Q$ blocks Bikl whose features maximize the discriminant function based on the Bayesian decision principle. Performance of the proposed technique is evaluated in terms of RMSE and Mutual Information (MI) as the output quality measures. The width of the kernel functions, ${\sigma}$, were made to vary, and different kernels and block sizes were applied in performance evaluation. The proposed scheme is tested with C=2 and C=3 input images and results exhibited good performance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.7-12
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• 2011

In this papwer, we propose a new feature extraction method, named as Class-augmented Kernel Principal Component Analysis (CA-KPCA), which can extract nonlinear features for classification. Among the subspace method that was being widely used for feature extraction, Class-augmented Principal Component Analysis (CA-PCA) is a recently one that can extract features for a accurate classification without computational difficulties of other methods such as Linear Discriminant Analysis (LDA). However, the features extracted by CA-PCA is still restricted to be in a linear subspace of the original data space, which limites the use of this method for various problems requiring nonlinear features. To resolve this limitation, we apply a kernel trick to develop a new version of CA-PCA to extract nonlinear features, and evaluate its performance by experiments using data sets in the UCI Machine Learning Repository.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1353-1366
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• 2015

These days Shewhart control chart for evaluating stability of the process is widely used in various field. But it must follow strict assumption of distribution. In real-life problems, this assumption is often violated when many quality characteristics follow non-normal distribution. Moreover, it is more serious in multivariate quality characteristics. To overcome this problem, many researchers have studied the non-parametric control charts. Recently, SVDD (Support Vector Data Description) control chart based on RBF (Radial Basis Function) Kernel, which is called K-chart, determines description of data region on in-control process and is used in various field. But it is important to select kernel parameter or etc. in order to apply the K-chart and they must be predetermined. For this, many researchers use grid search for optimizing parameters. But it has some problems such as selecting search range, calculating cost and time, etc. In this paper, we research the efficiency of selecting parameter regions as data structure vary via simulation study and propose a new method for determining parameters so that it can be easily used and discuss a robust choice of parameters for various data structures. In addition, we apply it on the real example and evaluate its performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4B
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• pp.397-402
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• 2004

In this paper, we have designed and simulated a new file transmission method. This method restricts memory copy and context switching happened in traditional file transmission. This method shows an improved performance than traditional method in network environment. When the UNIX/LINUX system that uses the existing file transfer technique transmits a packet to the remote system, a memory copy between the user and kernel space occurs over twice at least. Memory copy between the user and kernel space increase a file transmission time and the number of context switching. As a result, the existing file transfer technique has a problem of deteriorating the performance of file transmission. We propose a new algorithm for solving these problems. It doesn't perform memory copy between the user and kernel space. Hence, the number of memory copy and context switching is limited to the minimum. We have modified the network related source code of LINUX kernel 2.6.0 to analyzing the performance of proposed algorithm and implement new network system calls.