• The Korean Journal of Applied Statistics
• /
• v.7 no.2
• /
• pp.239-248
• /
• 1994

The Yule-Walker estimator and the approximate conditional least squares estimator of the parameter of the EARMA(1, 1) model are obtained. These two estimators are compared by simulation study. It is shown that the approximate conditional least squares estimator is better in the sense of the mean square error than the Yul-Walker estimator.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2011.04a
• /
• pp.752-755
• /
• 2011

이종재료의 열전달문제 수치해석시 추가적으로 만족시켜야 하는 계면경계조건들의 존재와 계면경계로 인한 불연속면의 처리는 근사함수의 구성 뿐만 아니라 수치기법의 개발 자체를 어렵게 만든다. 본 논문에서는 계면경계의 불연속성을 모델링하는 특수한 함수를 포함하고 계면경계조건을 항상 만족시킬 수 있는 근사함수를 구성하고, 계면경계문제의 강형식을 직접 이산화하며 고속으로 해를 계산할 수 있는 이동최소제곱 차분법을 제시한다. 계면경계조건이 매입된 이동최소제곱 차분법으로 이종재료의 열전달문제를 해석한 결과, 높은 정확성과 효율성을 갖는 것을 확인할 수 있었다.

• Journal of KIISE:Computer Systems and Theory
• /
• v.28 no.6
• /
• pp.289-300
• /
• 2001

본 논문에서는 유한 필드 GF(2$_{m}$ ) 상에서 모듈러 곱셈 A($\chi$)B($\chi$) mod P($\chi$)을 수행하는 새로운 선형 문제-크기(full-size) 시스톨릭 어레이 구조인 LSB-first 곱셈기를 제안한다. 피연산자 B($\chi$)의 LSB(least significant bit)를 먼저 사용하는 LSB-first 모듈러 곱셈 알고리즘으로부터 새로운 비트별 순환 방정식을 구한다. 데이터의 흐름이 규칙적인 순환 방정식을 공간-시간 변환으로 새로운 시스톨릭 곱셈기를 설계하고 분석한다. 기존의 곱셈기와 비교할 때 제안한 곱셈기의 면적-시간 성능이 각각 10%와 18% 향상됨을 보여준다. 또한 같은 설계방법으로 곱셈과 제곱연산을 동시에 수행하는 새로운 시스톨릭 곱셈/제곱기를 제안한다. 유한 필드상의 지수연산을 위해서 제안한 시스톨릭 곱셈/제곱기를 사용할 때 곱셈기만을 사용 할 때보다 면적-시간 성능이 약 26% 향상됨을 보여준다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.577-580
• /
• 2023

물리 기반 시뮬레이션과 같이 연속적인 움직임을 표현하기 위해서 고차 보간(High-order interpolation)을 설계하는 것을 중요한 문제이다. 본 논문에서는 제약적인 벡터와 밀도 형태를 몬테카를로법을 사용하여 이동최소제곱(MLS, Moving least squares)을 제곱하여 이를 통해 속도 필드를 표현할 수 있는 방법을 제안한다. 결과적으로 밀도의 형태를 고려하여 MLS의 가중치가 적용된 결과를 보여주며, 그 결과가 벡터 보간에 얼마나 큰 영향을 끼치는지를 다양한 실험을 통해 보여준다.

• Journal of Cadastre & Land InformatiX
• /
• v.45 no.2
• /
• pp.117-130
• /
• 2015

A least squares method for adjusting the horizontal network satisfies the conditions which is minimizing the sum of the squares of errors based on probability theory. This research compared accuracy of 3rd cadastral control points adjusted by traditional and least square method with respect to the result of Network-RTK. Test results showed the least square method more evenly distribute closure error than traditional method. Mean errors of least square and traditional adjusting method are 2.7cm, 2.2cm respectively. In addition, blunder in angle observations can be detected by comparing position errors which calculated by forward and backward initial coordinates. However, distance blunder cannot offer specific observation line occurred mistake because distance error propagates several observation lines which have similar directions.

• The KIPS Transactions:PartB
• /
• v.13B no.4 s.107
• /
• pp.393-400
• /
• 2006

There are many feature extraction methods for face recognition. We need a new method to overcome the small sample problem that the number of feature variables is larger than the sample size for face image data. The paper considers partial least squares(PLS) as a new dimension reduction technique for feature vector. Principal Component Analysis(PCA), a conventional dimension reduction method, selects the components with maximum variability, irrespective of the class information. So, PCA does not necessarily extract features that are important for the discrimination of classes. PLS, on the other hand, constructs the components so that the correlation between the class variable and themselves is maximized. Therefore PLS components are more predictive than PCA components in classification. The experimental results on Manchester and ORL databases shows that PLS is to be preferred over PCA when classification is the goal and dimension reduction is needed.

• The Korean Journal of Applied Statistics
• /
• v.15 no.2
• /
• pp.395-403
• /
• 2002

In the third phase of the response surface methods, the first-order model is assumed and the curvature of the response surface is checked with a fractional factorial design augmented by centre runs. We further assume that a true model is a quadratic polynomial. To choose an optimal design, Box and Draper(1959) suggested the use of an average mean squared error (AMSE), an average of MSE of y(x) over the region of interest R. The AMSE can be partitioned into the average prediction variance (APV) and average squared bias (ASB). Since AMSE is a function of design moments, region moments and a standardized vector of parameters, it is not possible to select the design that minimizes AMSE. As a practical alternative, Box and Draper(1959) proposed minimum bias design which minimize ASB and showed that factorial design points are shrunk toward the origin for a minimum bias design. In this paper we propose a robust AMSE design which maximizes the minimum efficiency of the design with respect to a standardized vector of parameters.

• The Journal of the Korea Contents Association
• /
• v.9 no.5
• /
• pp.332-336
• /
• 2009

Functional prediction of unannotated proteins is one of the most important tasks in yeast genomics. Analysis of a protein-protein interaction network leads to a better understanding of the functions of unannotated proteins. A number of researches have been performed for the functional prediction of unannotated proteins from a protein-protein interaction network. A chi-square method is one of the existing methods for the functional prediction of unannotated proteins from a protein-protein interaction network. But, the method does not consider the topology of network. In this paper, we propose a novel method that is able to predict specific molecular functions for unannotated proteins from a protein-protein interaction network. To do this, we investigated all protein interaction DBs of yeast in the public sites such as MIPS, DIP, and SGD. For the prediction of unannotated proteins, we employed a modified chi-square measure based on neighborhood counting and we assess the prediction accuracy of protein function from a protein-protein interaction network.

• The Korean Journal of Applied Statistics
• /
• v.30 no.2
• /
• pp.259-269
• /
• 2017

Due to the nonnegativity of variance, most of nonparametric estimations of discontinuous variance function have used the Nadaraya-Watson estimation with residuals. By the modification of Chen et al. (2009) and Yu and Jones (2004), Huh (2014, 2016a) proposed the estimators of the log-variance function instead of the variance function using the local linear estimator which has no boundary effect. Huh (2016b) estimated the variance function using the adjusted squared residuals by the estimated jump size in the discontinuous variance function. In this paper, we propose an estimator of the discontinuous log-variance function using the local linear estimator with the adjusted log-squared residuals by the estimated jump size of log-variance function like Huh (2016b). The numerical work demonstrates the performance of the proposed method with simulated and real examples.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.1 s.39
• /
• pp.45-53
• /
• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the $x^2$ reliability model, which can capture the increasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing shape parameter of the $x^2$ distribution using the degree of freedom, was employed. This analysis of failure data compared with the $x^2$ model and the existing model using arithmetic and Laplace trend tests, Kolmogorov test is presented.