• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.305-317
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• 2006

Outliers adversely affect model identification, parameter estimation, and forecast in time series data. In particular, when outliers consist of a patch of additive outliers, the current outlier detection procedures suffer from the masking and swamping effects which make them inefficient. In this paper, we propose new outlier detection procedure based on high breakdown estimators, called as the dual robust filtering. Empirical and simulation studies in the autoregressive model with orders p show that the proposed procedure is effective.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.907-920
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• 2016

This study suggests an outlier detection algorithm that uses quantile autoregressive model in time series data, eventually applying it to actual stock manipulation cases by comparing its performance to existing methods. Studies on outlier detection have traditionally been conducted mostly in general data and those in time series data are insufficient. They have also been limited to a parametric model, which is not convenient as it is complicated with an analysis that takes a long time. Thus, we suggest a new algorithm of outlier detection in time series data and through various simulations, compare it to existing algorithms. Especially, the outlier detection algorithm in time series data can be useful in finding stock manipulation. If stock price which had a certain pattern goes out of flow and generates an outlier, it can be due to intentional intervention and manipulation. We examined how fast the model can detect stock manipulations by applying it to actual stock manipulation cases.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.21-31
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• 2014

Singular value decomposition (SVD) has been widely used to identify unique features from a data set in various fields. However, a complex matrix calculation of SVD requires tremendous computation time. This paper improves the performance of a representative one-sided block Jacoby algorithm using a two-dimensional (2D) multi-core system. In addition, this paper explores an optimal multi-core system by varying the number of processing elements in the 2D multi-core system with the same 400MHz clock frequency and TSMC 28nm technology for each matrix-based one-sided block Jacoby algorithm ($128{\times}128$, $64{\times}64$, $32{\times}32$, $16{\times}16$). Moreover, this paper demonstrates the potential of the 2D multi-core system for the one-sided block Jacoby algorithm by comparing the performance of the multi-core system with a commercial high-performance graphics processing unit (GPU).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.267-271
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• 2007

본 논문은 원본이미지와 은닉이미지의 좋은 압축률과 만족할만한 이미지의 질, 그리고 외부공격에 강인한 이미지은닉의 한 방법으로 특이치 분해와 퍼지 군집화를 이용한 벡터양자화를 이용한 워터마킹 방법을 소개하였다. 실험에서는 은닉된 이미지의 비가시성과 외부공격에 대한 강인성을 증명하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.10a
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• pp.160-164
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• 1994

본 논문에서는 구조물의 진동으로 야기되는 소음원을 규명하기 위해 구조물 동작중의 응답신호를 측정한다. 먼저 응답 신호벡터에서 스펙트럼행렬을 구성하여 특이치 분리법을 수행한다. 특이치의 정보로 구조물의 응답에 영향을 미치는, 서로 독립적으로 작용하는 주 가진원을 파악한다. 간단한 구조물에 대해, 본 논문에서 적용된 기법의 유용성 및 물리적 성질을 검토한 후, 자동차 파워트레인이 구조 진동이 실내 소음에 미치는 구조적 소음을 실험을 통해 규명한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1118-1122
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• 2003

In this paper, we propose a new invisible digital watermarking scheme based on wavelet transform using singular value decomposition. Embedding process is started by decomposing the lowest frequency band image with 3${\times}$3 block among which we define the watermark block chosen by a key set; entropy and condition number of the block. A watermark is embedded in the singular values of each watermark blocks. This provides a robust watermarking in lowest possible time-frequency domain. To detect the watermark, we are locally modeling an attack as 3${\times}$3 matrices on the watermark blocks. Combining with the SVD and the attack matrices, we estimate watermark set corresponding to the watermark blocks. In each watermark block, we determine an optimal watermark which is justified by the T-testing. A numerical experiment shows that the proposed watermarking scheme efficiently detects the watermarks from several JPEG attacks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.602-609
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• 2002

In this paper, we propose an robust invisible watermarking method using wavelet transform and singular value decomposition for the ownership protection. of images. For this method, after we decompose the original image in three level using wavelet transform, we use singular value decomposition based key depended watermark insertion method in the lowest band $LL_3.$ And we also watermark using DCT for extraction of watermark and verification of robustness. In the experiments, we found that it had a good quality and robustness in attack such as compression, image processing, geometric transformation and noises. Especially, we know that this method have very high extraction ratio against nose and JPEG compression. And Digimarc's method can not extract watermark in 80 percent compression ratio of JPEG, but the proposed method can extract well.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.2
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• pp.48-55
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• 1999

To cope actively with the changes of external environments, it is necessary that a robot should have visual feedback control (VFC) using image informations. A VFC system consists of a manipulator and camera(s). For the fixed visual system, when feature value are located at the same line, we have a problem of singular value unable to be controlled by VFC. As a solution, we may define state values of the image Jacobians, then, by making comparisons and evaluations of feature values, select available ones. This method, however, has a demerit increasing numbers of feature values. To solve the problem, moving cameras of VFC system actively, we suggest an algorithm which dose not cause singular value, and prove its availability through simulations.

• Geophysics and Geophysical Exploration
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• v.16 no.1
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• pp.1-5
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• 2013

Stacking in seismic processing plays an important role in improving signal-to-noise ratio and imaging quality of seismic data. However, the conventional stacking method doesn't remove random noises with various distributions and outliers up to a satisfactory level. This paper introduces a robust and optimum weighted stack method which shows both robustness to outlier noises and optimum in removing random noises. This was achieved by combining the robust median stacking with the optimum weighted stacking using local correlation. Application of the method to synthetic data showed that the proposed method is very effective in suppressing random noises with various distributions including outliers.

• Journal of the Korean Magnetics Society
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• v.17 no.6
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• pp.259-264
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• 2007

This paper describes the mathematical modeling method for the static magnetic field signature generated by a magnetic scale model. we proposed the equivalent dipole modeling method utilizing a singular value decomposition technique from magnetic field signatures by magnetic sensors are located special depths below the scale model. The proposed dipole modeling method was successfully verified through comparisons with the real measured values in our non-magnetic laboratory. Using the proposed method, it is possible to predict and analyze static magnetic field distributions at any difference depths generated from the real ships as well as a scale model ship.