• Genomics & Informatics
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• v.2 no.2
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• pp.92-98
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• 2004

A cDNA microarray experiment is one of the most useful high-throughput experiments in medical informatics for monitoring gene expression levels. Statistical analysis with a cDNA microarray medical data requires a normalization procedure to reduce the systematic errors that are impossible to control by the experimental conditions. Despite the variety of normalization methods, this. paper suggests a more general and synthetic normalization algorithm with a control gene set based on previous studies of normalization. Iterative normalization method was used to select and include a new control gene set among the whole genes iteratively at every step of the normalization calculation initiated with the housekeeping genes. The objective of this iterative normalization was to maintain the pattern of the original data and to keep the gene expression levels stable. Spatial plots, M&A (ratio and average values of the intensity) plots and box plots showed a convergence to zero of the mean across all genes graphically after applying our iterative normalization. The practicability of the algorithm was demonstrated by applying our method to the data for the human photo aging study.

• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.13-20
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• 2016

Microsimulation model has aimed to simulate the impact of policy at the level of individual and household. Recently, microsimulation model has been widely accepted in OECD countries for evaluating their economic and social policies. For improving the availability of microsimulation model, the population data which shows good accordance with the official statistics should be required. In this paper, we generate Korean synthetic populations by using the iterative proportional updating method. For the validation of Korean synthetic populations, we compute the difference between the generated synthetic populations and the summary table of Korean census. Then, we confirm that it shows good accordance with the summary table.

• Structural Engineering and Mechanics
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• v.14 no.1
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• pp.57-70
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• 2002

This work presents an iterative mesh partitioning approach to improve the efficiency of parallel substructure finite element computations. The proposed approach employs an iterative strategy with a set of empirical rules derived from the results of numerical experiments on a number of different finite element meshes. The proposed approach also utilizes state-of-the-art partitioning techniques in its iterative partitioning kernel, a cost function to estimate the computational cost of each submesh, and a mechanism that adjusts element weights to redistribute elements among submeshes during iterative partitioning to partition a mesh into submeshes (or substructures) with balanced computational workloads. In addition, actual parallel finite element structural analyses on several test examples are presented to demonstrate the effectiveness of the approach proposed herein. The results show that the proposed approach can effectively improve the efficiency of parallel substructure finite element computations.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.6-22
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• 1991

This thesis presents a parallel implementation of an iterative method for large scale, sparse linear system and gives result of computational experiments performed on both single transputer and multi transputer parallel computers. To solve linear system, we use conjugate gradient method and develope data storage techinique, data communication scheme. In addition to the explanation of conjugate gradient method, the result of computational experiment is summarized.

• Communications of the Korean Mathematical Society
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• v.9 no.2
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• pp.449-465
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• 1994

The two common numerical methods to approximate the solution of partial differential equations are the finite element method and the finite difference method. They both lead to solving large sparse linear systems. For many applications, it is not unusal that the order of matrix is greater than 10, 000. For this kind of problem, a direct method such as Gaussian elimination can not be used because of the prohibitive cost. To this end, many iterative methods with modest cost have been studied and proposed by numerical analysts.(omitted)

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.10
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• pp.360-366
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• 1983

In this paper, operation cost of the system is calculated by the probabilistic simulation method. And it is proved that only 20 iterative simulations are enough to get the result obtain by the Monte Carlo simulation method which requires more than 1000 iterative simulations. In the probabilistic simulation method we use the ranking of line contingency which is derived from the line countingency selection algorithm proposed in (2). In using this method the nature of the sparsity of the power system is used.

• Journal of the Optical Society of Korea
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• v.15 no.3
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• pp.209-215
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• 2011

A new iterative algorithm is developed to estimate LIDAR ratio for a thin cirrus cloud over an aerosol layer. First, the thin cirrus cloud is screened out and replaced by a modeled LIDAR signal and the extinction coefficients of the aerosol layer are derived using the Fernald backward method. These aerosol coefficients are referred as the "actual values". Second, the original LIDAR signal which includes the thin cirrus cloud is also inverted by the Fernald backward method down to the aerosol layer but using different LIDAR ratio for the thin cirrus cloud. Depending on the different assumptions about the LIDAR ratio of the thin cirrus cloud, different sets of aerosol extinction can be derived. The "actual values" which are found in the first step can be used to constrain this iterative progress and the correct LIDAR ratio of the thin cirrus cloud can be found. The detailed description of this method and retrieval examples are given in the paper. The cases compared with other methods are presented and the statistical result is also shown and agrees well with other studies.

• Journal of the Korean Mathematical Society
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• v.54 no.2
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• pp.461-477
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• 2017

A dual substructuring method with a penalty term was introduced in the previous works by the authors, which is a variant of the FETI-DP method. The proposed method imposes the continuity not only by using Lagrange multipliers but also by adding a penalty term which consists of a positive penalty parameter ${\eta}$ and a measure of the jump across the interface. Due to the penalty term, the proposed iterative method has a better convergence property than the standard FETI-DP method in the sense that the condition number of the resulting dual problem is bounded by a constant independent of the subdomain size and the mesh size. In this paper, a further study for a dual iterative substructuring method with a penalty term is discussed in terms of its convergence analysis. We provide an improved estimate of the condition number which shows the relationship between the condition number and ${\eta}$ as well as a close spectral connection of the proposed method with the FETI-DP method. As a result, a choice of a moderately small penalty parameter is guaranteed.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.303-306
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• 1996

We propose a robust tuning method of the quadratic criterion based iterative learning control(Q-ILC) algorithm for discrete-time linear batch system. First, we establish the frequency domain representation for batch systems. Next, a robust convergence condition is derived in the frequency domain. Based on this condition, we propose to optimize the weighting matrices such that the upper bound of the robustness measure is minimized. Through numerical simulation, it is shown that the designed learning filter restores robustness under significant model uncertainty.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.161-173
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• 2009

In this paper, we introduce an iterative scheme for finding a common element of the set of fixed points of a nonexpansive mapping, the set of solutions of the variational inequality for an inverse-strongly monotone mapping and the set of solutions of an equilibrium problem in a Hilbert space. We show that the iterative sequence converges strongly to a common element of the three sets. The results of this paper extend and improve the corresponding results announced by many others.