• 대한의용생체공학회:의공학회지
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• 제17권1호
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• pp.93-98
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• 1996

The purpose of this paper is to propose a new localized imaging method of reduced imaging time luting a locally-linear gradient. Since most fast MR(Magnetic Resonance) imaging methods need the whole $\kappa$-space(Spatial frequency space) data corresponding to the whole imaging area, there are limitstions in reducing the minimum imaging time. The imaging method proposed in this paper uses a specially-made gradient coil generating a local ramp-shape field and uniform field outside of the imaging areal Conventional imaging sequences can be used without any RF/gradient pulse sequence modifiestions except the change in the number of encoding steps and the field of view.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.607-617
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• 2003

This paper offers a practical comparison of efficiency between local likelihood approach and conventional kernel approach in density estimation. The local likelihood estimation procedure maximizes a kernel smoothed log-likelihood function with respect to a polynomial approximation of the log likelihood function. We use two types of data driven bandwidths for each method and compare the mean integrated squares for several densities. Numerical results reveal that local log-linear approach with simple plug-in bandwidth shows better performance comparing to the standard kernel approach in heavy tailed distribution. For normal mixture density cases, standard kernel estimator with the bandwidth in Sheather and Jones(1991) dominates the others in moderately large sample size.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.979-980
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• 2008

In this paper we use the Isometric Projection, a linear subspace method, for manifold representation of the pose-varying-faces. Isometric Projection method for pose identification is evaluated on view varying faces and is compared with other global and local linear subspace methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4502-4518
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• 2015

Fisher linear discriminant analysis (LDA) is one of the most popular projection techniques for feature extraction and has been widely applied in face recognition. However, it cannot be used when encountering the single sample per person problem (SSPP) because the intra-class variations cannot be evaluated. In this paper, we propose a novel method called local similarity based linear discriminant analysis (LS_LDA) to solve this problem. Motivated by the "divide-conquer" strategy, we first divide the face into local blocks, and classify each local block, and then integrate all the classification results to make final decision. To make LDA feasible for SSPP problem, we further divide each block into overlapped patches and assume that these patches are from the same class. To improve the robustness of LS_LDA to outliers, we further propose local similarity based median discriminant analysis (LS_MDA), which uses class median vector to estimate the class population mean in LDA modeling. Experimental results on three popular databases show that our methods not only generalize well SSPP problem but also have strong robustness to expression, illumination, occlusion and time variation.

• 한국지능시스템학회논문지
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• 제23권1호
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• pp.18-23
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• 2013

In this paper we propose an image enhancement technique based on histogram specification method over local overlapping regions referred as Local Histogram Specification. First, both reference and original images are splitted into local regions that each overlaps half of its adjacent regions and general histogram specification method is used between corresponding local regions of reference and original image. However it produces noticeable boundary effects. Linear weighted image blending method is used to reduce this effect in order to make seamless image and we also proposed new technique dealing with over-enhanced contrast areas. We satisfied with our experimental results that showed better enhancement accuracy and less noise amplifications compared to other well-known image enhancement methods. We conclude that the proposed method is well suited for motion detection systems as a responsible part to overcome sudden illumination changes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.840-855
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• 2011

In the context of additive noise steganography model, we propose a method to detect least significant bit (LSB) matching steganography in grayscale images. Images are decomposed into detail sub-bands with local linear transform (LLT) masks which are sensitive to embedding. Novel normalized characteristic function features weighted by a bank of band-pass filters are extracted from the detail sub-bands. A suboptimal feature set is searched by using a threshold selection algorithm. Extensive experiments are performed on four diverse uncompressed image databases. In comparison with other well-known feature sets, the proposed feature set performs the best under most circumstances.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 춘계학술대회
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• pp.193-199
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• 2005

A simple method is proposed to detect the number of change points with jump discontinuities in nonparamteric regression functions. The proposed estimators are based on a local linear regression fit by the comparison of left and right one-side kernel smoother. Also, the proposed methodology is suggested as the test statistic for detecting of change points and the direction of jump discontinuities.

• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.31-38
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• 2003

A simple method is proposed to detect the number of change points and test the location and size of multiple change points with jump discontinuities in an otherwise smooth regression model. The proposed estimators are based on a local linear regression fit by the comparison of left and right one-side kernel smoother. Our proposed methodology is explained and applied to real data and simulated data.

• 대한수학회지
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• 제59권6호
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• pp.1171-1184
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• 2022

We study the real-analytic continuation of local real-analytic solutions to the Cauchy problems of quasi-linear partial differential equations of first order for a scalar function. By making use of the first integrals of the characteristic vector field and the implicit function theorem we determine the maximal domain of the analytic extension of a local solution as a single-valued function. We present some examples including the scalar conservation laws that admit global first integrals so that our method is applicable.

• 지역연구
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• 제14권2호
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• pp.107-126
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• 1998

Since the election of governors and mayors by vote, many local governments in Korea establish long-range plans for their regional development. The major purposes of the plans are to set up development path for their communities and to devise economic development strategies. But most of the plans established thus formulated by the same method utilized in centralized political regime. This method is considered no longer appropriate to devise the long-range development plans for local government especially in the era of globalization and localization, where local governments behave independently, where local governments behave independently competition. We suggest an alternative way to establish such plans, based on the method employed in business sector. The plans, formulated in this way, are called strategy oriented long-range development plans. The underlying logic for the plans is non-linear one. The plans are issue oriented and focus more on process than outcome. Given that these features are properly incorporated in the plans, we expect that the strategy oriented long-range development plans can be genuine guidelines for local economic development in the years to come.