• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.1-8
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• 2004

We address the problem of parameter estimation in multivariate distributions under ignorable non-monotone missing data. The factoring likelihood method for monotone missing data, termed by Robin (1974), is extended to a more general case of non-monotone missing data. The proposed method is algebraically equivalent to the Newton-Raphson method for the observed likelihood, but avoids the burden of computing the first and the second partial derivatives of the observed likelihood Instead, the maximum likelihood estimates and their information matrices for each partition of the data set are computed separately and combined naturally using the generalized least squares method. A numerical example is also presented to illustrate the method.

• Steel and Composite Structures
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• v.35 no.6
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• pp.717-727
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• 2020

The homotopy perturbation method (HPM) to predict the pre- and post-buckling behaviour of simply supported steel beams with rectangular hollow section (RHS) is presented in this paper. The non-linear differential equations solved by HPM derive from a kinematics where large twist and cross-sections distortions are considered. The results (linear and non-linear paths) given by the present HPM are compared to those provided by the Newton-Raphson algorithm with arc length and by the commercial FEM code Abaqus. To investigate the effect of cross-sectional distortion of beams, some numerical examples are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1016-1026
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• 1994

In this paper, we have studied load balancing problems in distributed systems. The nodes of distributed systems exchange periodically system state information each other. The information is stored in history. Based on the information, we compute an expected load index(ELI) using a five-degree interpolation polynomial in Newton`s backward difference interpolation formula. A new location policy of dynamic load balancing systems makes use of the ELI. We show that its performance is better than that of the existing load balancing algorithm through a simulation study.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.173-178
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• 1989

Optimal Power Flow (OPF) solution by the Newton's method provides a reliable and robust method to classical OPF problems. The major challenge in algorithm development is to identify the binding inequalities efficiently. This paper propose a simple strategy to identify the binding set. From the mechanism of penalty shifting with soft penalty in trial iteration, a active binding sit is identified automatically. This paper also suggests a technique to solve the linear system whore coefficients are presented by the matrix. This implementation is highly efficient for sparsity programming. Case study for 3,5,14,118,190 bus and practrical KEPCO 305 bus system are performed as well.

• Journal of KSNVE
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• v.8 no.5
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• pp.879-886
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• 1998

An automated calibration system of sound level meters was developed and tested. As a standard sound source, the speaker unit(Forstex FE208) cabineted by 440$\times$390$\times$490 $\textrm{mm}^3$(LHW) volume wood box was adopted. Including this source, the driving part was found out to have a good linearity of sound pressure output vs AC voltage input. The Hybrid-Bisect/Newton-Raphson method modified by the linearity was adopted as a searching algorithm. Uisng GPIB interface, the console PC make the control, measurements, and calculations and finally make the accumulation of useful data and results automatically by the instructon in the program coded by C languate. Several trials of automatic calibration using this developed system give the reliable results.

• Journal of the Korean Mathematical Society
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• v.57 no.4
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• pp.915-933
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• 2020

A two-level finite element method based on the Newton iterative method is proposed for solving the Navier-Stokes/Darcy model. The algorithm solves a nonlinear system on a coarse mesh H and two linearized problems of different loads on a fine mesh h = O(H^4-𝜖). Compared with the common two-grid finite element methods for the considered problem, the presented two-level method allows for larger scaling between the coarse and fine meshes. Moreover, we prove the stability and convergence of the considered two-level method. Finally, we provide numerical experiment to exhibit the effectiveness of the presented method.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.225-232
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• 2003

The support vector machine (SVM) is becoming increasingly popular in classification. The import vector machine (IVM) has been introduced for its advantages over SMV. This paper tries to improve the IVM. The proposed method, which is referred to as the polychotomous machine (PM), uses the Newton-Raphson method to find estimates of coefficients, and the Rao and Wald tests, respectively, for addition and deletion of import points. Because the PM basically follows the same addition step and adopts the deletion step, it uses, typically, less import vectors than the IVM without loosing accuracy. Simulated and real data sets are used to illustrate the performance of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.3
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• pp.223-231
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• 1990

Optimal Power Flow (OPF) solution by the Newton's method provides a reliable and robust method to classical OPF problems. The major challenge in algorithm development is to identify the binding inequalities efficiently. This paper proposes a simple strategy to identify the binding set. From the mechanism of penalty shifting with soft penalty in trial iteration, an active binding set is identidied automatically. This paper also suggests a technique to solve the linear system whose coefficients are presented in the matrix from. This implementation is highly efficient for sparsity programming. Case studies for 3, 5, 14, 118 bus and practical TPC-190, KEPCO-306 bus systems are performed as well.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.485-489
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• 2006

In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and closed-form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a self-tuning weighted least square AOA algorithm that is a modified version of the conventional closed-form solution. In order to estimate the error covariance matrix as a weight, two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1033-1036
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• 2002

본 연구에서는 Newton 기법과 모멘트에 기초를 둔 fixed point 알고리즘의 신경망 기반 독립성분분석기법을 제안하였다. 여기서 Newton 기법은 함수의 접선에 기초를 둔 해를 구하는 방법으로 역혼합행렬의 빠른 경신을 위함이고, 모멘트는 접선을 구하는 과정에서 함수의 기울기변화 계산으로 발생하는 발진을 줄여 좀 더 빠른 학습을 위함이다. 제안된 기법을 $256{\times}256$ 픽셀(pixel)의 12개 지문영상으로부터 임의의 혼합행렬에 따라 발생되는 영상들을 각각 대상으로 시뮬레이션 한 결과, 기존의 Fixed point 알고리즘에 의한 결과보다 우수한 분리성능과 빠른 학습속도가 있음을 확인하였다.