• 충청수학회지
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• 제9권1호
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• pp.115-121
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• 1996

Let $\{X(t);\;t{\in}R^n\}$ be a measurable, separable and H-sssis random fields. Here, we suppose that the increments are invariant under all Euclidean rigid body motions. We investigate some properties of H-sssis random fields and monotonicity of projection process $\{X_e(t);\;t{\in}R^1\}$ in any direction $e{\in}R^n$.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.81-88
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• 2023

In the present scenario, enormous amounts of data are produced every second. These data also contain private information from sources including media platforms, the banking sector, finance, healthcare, and criminal histories. Data mining is a method for looking through and analyzing massive volumes of data to find usable information. Preserving personal data during data mining has become difficult, thus privacy-preserving data mining (PPDM) is used to do so. Data perturbation is one of the several tactics used by the PPDM data privacy protection mechanism. In Perturbation, datasets are perturbed in order to preserve personal information. Both data accuracy and data privacy are addressed by it. This paper will explore and compare several perturbation strategies that may be used to protect data privacy. For this experiment, two perturbation techniques based on random projection and principal component analysis were used. These techniques include Improved Random Projection Perturbation (IRPP) and Enhanced Principal Component Analysis based Technique (EPCAT). The Naive Bayes classification algorithm is used for data mining approaches. These methods are employed to assess the precision, run time, and accuracy of the experimental results. The best perturbation method in the Nave-Bayes classification is determined to be a random projection-based technique (IRPP) for both the cardiovascular and hypothyroid datasets.

• Communications for Statistical Applications and Methods
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• 제27권5호
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• pp.523-533
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• 2020

This paper suggests three available methods for finding nonnegative estimates of variance components of the random effects in mixed models. The three proposed methods based on the concepts of projections are called projection method I, II, and III. Each method derives sums of squares uniquely based on its own method of projections. All the sums of squares in quadratic forms are calculated as the squared lengths of projections of an observation vector; therefore, there is discussion on the decomposition of the observation vector into the sum of orthogonal projections for establishing a projection model. The projection model in matrix form is constructed by ascertaining the orthogonal projections defined on vector subspaces. Nonnegative estimates are then obtained by the projection model where all the coefficient matrices of the effects in the model are orthogonal to each other. Each method provides its own system of linear equations in a different way for the estimation of variance components; however, the estimates are given as the same regardless of the methods, whichever is used. Hartley's synthesis is used as a method for finding the coefficients of variance components.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.848-853
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• 2005

3D geometric modeling of an object of interest has been intensively investigated in many fields including CAD/CAM and computer graphics. Traditionally, CAD and geometric modeling tools are widely used to create geometric models that have nearly the same shape of 3D real objects or satisfy designers intent. Recently, with the help of the reverse engineering (RE) technology, we can easily acquire 3D point data from the objects and create 3D geometric models that perfectly fit the scanned data more easily and fast. In this paper, we present 3D geometric model generation based on a stereo vision system (SVS) using random pattern projection. A triangular mesh is considered as the resulting geometric model. In order to obtain reasonable results with the SVS-based geometric model generation, we deal with many steps including camera calibration, stereo matching, scanning from multiple views, noise handling, registration, and triangular mesh generation. To acquire reliable stere matching, we project random patterns onto the object. With experiments using various random patterns, we propose several tips helpful for the quality of the results. Some examples are given to show their usefulness.

• Communications for Statistical Applications and Methods
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• 제25권3호
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• pp.275-282
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• 2018

This paper discusses the use of projections for the sums of squares in the analyses of variance for two-way nested design data. The model for this data is assumed to only have random effects. Two different sizes of experimental units are required for a given experimental situation, since nesting is assumed to occur both in the treatment structure and in the design structure. So, variance components are coming from the sources of random effects of treatment factors and error terms in different sizes of experimental units. The model for this type of experimental situation is a random effects model with more than one error terms and therefore estimation of variance components are concerned. A projection method is used for the calculation of sums of squares due to random components. Squared distances of projections instead of using the usual reductions in sums of squares that show how to use projections to estimate the variance components associated with the random components in the assumed model. Expectations of quadratic forms are obtained by the Hartley's synthesis as a means of calculation.

• 응용통계연구
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• 제34권3호
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• pp.401-410
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• 2021

판별분류분석에서 널리 이용되는 k-최근접 이웃 분류 방법은 고정된 이웃의 수만을 고려하여 자료의 국소적 특징을 반영하지 못하는 한계가 있다. 이에 자료의 국소적 구조를 고려하여 이웃의 개수를 선택하는 적응 최근접이웃방법이 개발된 바 있다. 고차원 자료의 분석에 있어서는 k-최근접 이웃 분류를 사용하기 전에 랜덤 투영 기법 등을 활용하여 차원 축소를 수행하는 것이 일반적이다. 이렇게 랜덤 투영시킨 다수의 분류 결과들을 면밀히 조합하여 투표를 통해 최종 할당을 하는 기법이 최근 개발된 바 있다. 본 연구에서는 고차원 자료에서의 분석을 위해 적응 최근접이웃방법과 랜덤 투영 앙상블 기법을 조합한 새로운 판별분류 기법을 제안하였다. 제안된 방법은 기존에 개발된 방법에 비해 분류 정확성 측면에서 더 뛰어남을 모의실험 및 실제 사례 분석을 통해 확인하였다.

• 응용통계연구
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• 제30권3호
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• pp.335-344
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• 2017

본 논문은 분할구실험으로 부터 주어진 자료분석을 위해 사영을 이용하는 방법을 다루고 있다. 분할구 실험의 특성으로 서로 다른 크기의 실험단위를 나타내는 오차항과 처리에 포함된 확률효과가 존재할 때 이들 분산성분의 추정에 사영을 이용하여 구하는 방법을 제시하고 있다. 분산성분 추정을 위해 잔차벡터에 대한 확률모형의 구축을 다루고 있다. 고정효과를 제외한 확률효과에 따른 제곱합의 계산을 위해 상수적합법이 적용되고 있다. 적률법에 의한 분산성분 추정을 위해 변동량의 기댓값 계산에 합성법을 이용한다. 고정효과들의 선형함수로 주어지는 추정가능함수에 관한 추정을 다루고 있다.

• 응용통계연구
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• 제27권5호
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• pp.717-729
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• 2014

본 연구에서는 나무구조의 분류분석에서 자료의 크기가 방대해짐에 따라 중요한 문제로 대두되고 있는 변수의 중요도에 대하여 사영추적분류나무를 중심으로 고찰하였다. 사영추적분류나무(projection pursuit classification tree)는 각 마디에서 사영추적을 이용하여 그룹을 잘 분리하는 변수들의 선형결합을 이용하는 방법으로 이때 사용되는 사영계수들은 각 마디에서의 분류에 대한 정보를 가지고 있다. 이를 종합하여 각 변수의 분류에 대한 중요도를 계산할 수 있다. 먼저 사영추적분류나무의 분류과정에서 계산되는 사영추적계수를 이용하여 분류를 위한 변수선택의 중요도를 계산하고 이들의 특성을 살펴보고 이를 같은 형태의 나무모형방법인 CART와 랜덤 포레스트의 결과와 비교 분석하여 사영추적분류나무의 특성을 살펴보고 비교, 분석하였다. 대부분의 자료에서 사영추적분류나무가 훨씬 좋은 성능을 보이고 있었으며 특히 상관계수가 높은 변수들이 포함되어 있는 경우에는 상대적으로 적은 수의 변수로도 잘 분류를 할 수 있음을 확인하였다. 랜덤 포레스트에서 제공하는 변수 중요도는 변수들 간의 상관관계가 높은 경우에는 사영추적분류나무의 변수중요도와 매우 다르게 나타나며 사영추적분류나무의 변수 중요도가 조금 더 나은 성능을 보이고 있음을 알 수 있다.

• Communications for Statistical Applications and Methods
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• 제26권4호
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• pp.337-346
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• 2019

This paper discusses a method for obtaining nonnegative estimates for variance components in a random effects model. A variance component should be positive by definition. Nevertheless, estimates of variance components are sometimes given as negative values, which is not desirable. The proposed method is based on two basic ideas. One is the identification of the orthogonal vector subspaces according to factors and the other is to ascertain the projection in each orthogonal vector subspace. Hence, an observation vector can be denoted by the sum of projections. The method suggested here always produces nonnegative estimates using projections. Hartley's synthesis is used for the calculation of expected values of quadratic forms. It also discusses how to set up a residual model for each projection.

• 비파괴검사학회지
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• 제30권3호
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• pp.181-193
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• 2010

The paper presents an alternative way to classical stereocorrelation. First, 2D image processing of random patterns is described. Sub-pixel displacements are determined using phase analysis. Then distortion evaluation is presented. The distortion is identified without any assumption on the lens model because of the use of a grid technique approach. Last, shape measurement and shape variation is caught by fringe projection. Analysis is based on two pin-hole assumptions for the video-projector and the camera. Then, fringe projection is coupled to in-plane displacement to give rise to 3D measurement set-up. Metrological characterization shows a resolution comparable to classical (stereo) correlation technique ($1/100^{th}$ pixel). Spatial resolution seems to be an advantage of the method, because of the use of temporal phase stepping (shape measurement, 1 pixel) and windowed Fourier transform (in plane displacements measurement, 9 pixels). Two examples are given. First one is the study of skin properties; second one is a study on leather fabric. In both cases, results are convincing, and have been exploited to give mechanical interpretation.