• 한국정보과학회논문지:시스템및이론
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• 제33권10호
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• pp.768-776
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• 2006

연결 정보가 없는 포인트 데이타가 주어졌을 때, 본 논문은 MLS(moving least-squares) 근사화 기법을 이용하여 포인트 데이타에 대해 근사화된 표면을 생성한다. 근사화된 표면에서의 각 포인트에 대해 지역적인 곡률과 곡률 미분 값을 측정 한 후, 딜러니 삼각화(Delaunay tessellation)를 통해 이웃간의 정보를 생성하게 되고, 연결된 포인트들 간의 제로-클로싱(zero-crossing)을 측정하여 특징 포인트들을 추출하고, 곡률 방향으로 추출 된 포인트들을 연결한다. 본 방법은 기존의 메쉬 데이타에서 특징 선을 찾는 방법과 비슷한 복잡도를 갖는다. 몇 개의 포인트-샘플 된 모델에 대해 특징 선 추출을 수행하며, 곡률의 크기에 따라 특징선의 두께를 조절하고 포인트-스플릿팅 방법에 의해 렌더링 한다.

• Wind and Structures
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• 제19권4호
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• pp.371-387
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• 2014

Probability plotting positions are popular and used as the basis for distribution fitting and for inspecting the quality of the fit because of its simplicity. The plotting positions that lead to excellent approximation to the mean of the order statistics should be used if the objective of the fitting is to estimate quantiles. Since the mean depends on the sample size and is not amenable for simple to use closed form solution, many plotting positions have been presented in the literature, including a new plotting position that is derived based on the weighted least-squares method. In this study, the accuracy of using the new plotting position to fit the Gumbel distribution for estimating quantiles is assessed. Also, plotting positions derived by fitting the mean of the order statistics for all ranks is proposed, and an approximation to the covariance of the order statistics for the Gumbel (and Weibull) variate is given. Relative bias and root-mean-square-error of the estimated quantiles by using the proposed plotting position are shown. The use of the proposed plotting position to estimate the quantiles of annual maximum wind speed is illustrated.

• Wind and Structures
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• 제34권6호
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• pp.469-482
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• 2022

The generalized extreme value distribution (GEVD) is frequently used to fit the block maximum of environmental parameters such as the annual maximum wind speed. There are several methods for estimating the parameters of the GEV distribution, including the least-squares method (LSM). However, the application of the LSM with the expected order statistics has not been reported. This study fills this gap by proposing a fitting method based on the expected order statistics. The study also proposes a plotting position to approximate the expected order statistics; the proposed plotting position depends on the distribution shape parameter. The use of this approximation for distribution fitting is carried out. Simulation analysis results indicate that the developed fitting procedure based on the expected order statistics or its approximation for GEVD is effective for estimating the distribution parameters and quantiles. The values of the probability plotting correlation coefficient that may be used to test the distributional hypothesis are calculated and presented. The developed fitting method is applied to extreme thunderstorm and non-thunderstorm winds for several major cities in Canada. Also, the implication of using the GEVD and Gumbel distribution to model the extreme wind speed on the structural reliability is presented and elaborated.

• 한국컴퓨터그래픽스학회논문지
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• 제2권2호
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• pp.11-20
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• 1996

산포된 자료 보간을 응용하는 분야에는 모델링, 자연현상 가시화 등을 비롯하여 여러 가지를 들 수 있다. 사면체 분할은 사차원적 공간 형성을 위한 전 처리 단계 중의 하나이다. 본 논문은 다양한 사면체 분할법인, Delaunay, least squares fitting, gradient difference, 와 jump in normal direction derivatives 들을 논의하였다. 본 논문은 사면체 영역을 가시화 함으로써, 사면체 분할법들을 구별시키고, 사면체 영역을 바탕으로 보간된 공간상의 등사치를 수치적 뿐만 아니라 시각적으로 가시화 하여 그 정확도를 비교 분석할 수 있는 방법을 제시하였다.

• Journal of the Korean Data and Information Science Society
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• 제27권6호
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• pp.1653-1660
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• 2016

Smoothly clipped absolute deviation (SCAD) penalty is known to satisfy the desirable properties for penalty functions like as unbiasedness, sparsity and continuity. In this paper, we deal with the regression function estimation and variable selection based on SCAD penalized censored regression model. We use the local linear approximation and the iteratively reweighted least squares algorithm to solve SCAD penalized log likelihood function. The proposed method provides an efficient method for variable selection and regression function estimation. The generalized cross validation function is presented for the model selection. Applications of the proposed method are illustrated through the simulated and a real example.

• Communications for Statistical Applications and Methods
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• 제24권3호
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• pp.193-209
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• 2017

The power Lindley distribution with some of its properties is considered in this article. Maximum likelihood, least squares, maximum product spacings, and Bayes estimators are proposed to estimate all the unknown parameters of the power Lindley distribution. Lindley's approximation and Markov chain Monte Carlo techniques are utilized for Bayesian calculations since posterior distribution cannot be reduced to standard distribution. The performances of the proposed estimators are compared based on simulated samples. The waiting times of research articles to be accepted in statistical journals are fitted to the power Lindley distribution with other competing distributions. Chi-square statistic, Kolmogorov-Smirnov statistic, Akaike information criterion and Bayesian information criterion are used to access goodness-of-fit. It was found that the power Lindley distribution gives a better fit for the data than other distributions.

• Journal of information and communication convergence engineering
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• 제6권3호
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• pp.310-314
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• 2008

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. This novel method uses the support vector machines (SVM) with its function approximation property. It works together with RLS (Recursive least-squares) algorithm. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems.

• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1223-1232
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• 2011

Tong and Wang's estimator (2005) is a new approach to estimate the error variance using least squares method such that a simple linear regression is asymptotically derived from Rice's lag- estimator (1984). Their estimator highly depends on the setting of a regressor and weights in small sample sizes. In this article, we propose a new approach via a local quadratic approximation to set regressors in a small sample case. We estimate the error variance as the intercept using a ridge regression because the regressors have the problem of multicollinearity. From the small simulation study, the performance of our approach with some existing methods is better in small sample cases and comparable in large cases. More research is required on unequally spaced points.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제49권6호
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• pp.354-359
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• 2000

A new method of measuring residual stress in micromachined film is proposed. An estimation of residual stress is performed by using least squares fit with an appropriate deflection modeling. an exact value of residual stress is obtained without any of the ambiguities that exist in conventional buckling method, and a good approximation is also obtained by using a few data points. Therefore, the test structures area could be greatly decreased by using this method. The measurement can be done more easily and simply without any actuation or any specific measuring equipment. The structure and fabrication processes described in this paper are simple and widely used in surface micromachining. In addition, in-situ measurement is available by using the proposed method when the test structure and the measurement structure are fabricated on a wafer simultaneously.

• 대한의용생체공학회:의공학회지
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• 제28권5호
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• pp.665-675
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• 2007

The morphological change of ECG is the important diagnostic parameter to finding the malfunction of a heart. Generally ST segment deviation is concerned with myocardial abnormality. The aim of this study is to detect the change of ST in shape using a polynomial approximation method and the reference ST type. The developed algorithm consists of feature point detection, ST level detection and ST shape classification. The detection of QRS complex is accomplished using it's the morphological characteristics such as the steep slope and high amplitude. The developed algorithm detects the ST level change, and then classifies the ST shape type using the polynomial approximation. The algorithm finds the least squares curve for the data between S wave and T wave in ECG. This curve is used for the classification of the ST shapes. ST type is classified by comparing the slopes of the specified points between the reference ST set and the least square curve. Through the result from the developed algorithm, we can know when the ST level change occurs and what the ST shape type is.