• Proceedings of the KSME Conference
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• 2000.04a
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• pp.345-350
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• 2000

Adaptive finite element analysis, which its solution error meets with the user defined allowable error, is recently used far improving reliability of finite element analysis results. This adaptive analysis is composed of two procedures; one is the error estimation of an analysis result and another is the reconstruction of finite elements. In the rp-method, an element size is controlled by relocating of nodal positions(r-method) and the order of an element shape function is determined by the hierarchical polynomial(p-method) corresponding to the element solution error. In order to show the effectiveness and accuracy of the suggested rp-method, various numerical examples were analyzed and these analysis results were examined by comparing with those obtained by the existed methods. As a result of this study, following conclusions are obtained. (1) rp-method is more accurate and effective than the r- and p-method. (2) The solution convergency of the rp-method is controlled by means of the iterative calculation numbers of the r- and p- method each other.

• Korean Journal of Mathematics
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• v.13 no.2
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• pp.127-137
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• 2005

The objective of numerical analysis is to devise and analyze efficient algorithms or numerical methods for equations arising in mathematical modeling for science and engineering. In this article, we present some recent topics in computational mathematics, specially in the finite element method and overview the development of the mixed finite element method in the context of second order elliptic and parabolic problems. Multiscale methods such as MsFEM, HMM, and VMsM are included.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.327-329
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• 1998

Up-Propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden variables using top-down connections. The inversion process is iterative, utilizing a negative feedback loop that depends on an error signal propagated by bottom-up connections. The error signal is also used to learn the generative model from examples. the algorithm is benchmarked against principal component analysis in experiments on images of handwritten digits.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.53-60
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• 2002

It has been recognized that damage control must become a more explicit design consideration. In an effort to develop design methods based on performance it is clear that the evaluation of the inelastic response is required. The methods available to the design engineer today are nonlinear time history analyses, or monotonic static nonlinear analyses, or equivalent static analyses with simulated inelastic influences. Some codes proposed the capacity spectrum method based on the nonlinear static(pushover) analysis to determine earthquake-induced demand given the structure pushover curve. This procedure is conceptually simple but iterative and time consuming with some errors. This paper presents a nonlinear direct spectrum method to evaluate seismic Performance of structure, without iterative computations, given the structural initial elastic period and yield strength from the pushover analysis, especially for multi degree of freedom structures. The purpose of this paper is to investigate accuracy and confidence of this method from a point of view of various earthquakes and unloading stiffness degradation parameters.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.365-375
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• 2014

This paper proposes an abnormal V-shaped-error-free non-blind deconvolution technique featuring an adaptively segmented forward-problem based iterative deconvolution (ASDCN) process. Unlike the algebraic based inverse operations, this eliminates any operations of differential and division by zero to successfully circumvent the issue on the abnormal V-shaped error. This effectiveness has been demonstrated for the first time with applying to a real analysis for the effects of the Random Telegraph Noise (RTN) and/or Random Dopant Fluctuation (RDF) on the overall SRAM margin variations. It has been shown that the proposed ASDCN technique can reduce its relative errors of RTN deconvolution by $10^{13}$ to $10^{15}$ fold, which are good enough for avoiding the abnormal ringing errors in the RTN deconvolution process. This enables to suppress the cdf error of the convolution of the RTN with the RDF (i.e., fail-bit-count error) to $1/10^{10}$ error for the conventional algorithm.

• Information and Communications Magazine
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• v.24 no.12
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• pp.14-21
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• 2007

This paper aims to improve the design of iterative detection and decoding(IDD) based on the soft interference cancellation with minimum mean squared error(SC-MMSE) detector, which shows low performance compared to the maximum a posteriori(MAP) detector. By means of extrinsic information transfer(EXIT) chart analysis, such low performance may be attributed to that the "pure"(original) turbo principle is not always best for IDD. Thus, we propose a new IDD architecture based on the SC-MMSE detector which uses new a priori information. Simulation results show that the performance of the proposed IDD is very close to that of IDD based on the MAP detector.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.3
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• pp.144-154
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• 1994

An efficient tidal model, TIDE which is an iterative type, nonlinear finite element model has developed for the analysis of the tidal movement in the coastal area which is characterized by irregular boundaries and bottom topography. Traditional time domain finite element models have been in difficulties with requirement for high eddy viscosity coefficients and small time steps to insure numerical instability. These problems are overcome by operating in the frequency domain with an elaborate grid system by combining the triangular and quadrilateral shape grids. Furthermore, in order to handle non-linearity which will be more significant in the shallow region, an iterative scheme with least square error minimization algorithm has been implemented in the model. The results of TIDE model are agreed with the analytical solutions in a rectangular channel under the condition of tidal waves entering the channel closed at one end.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.59-62
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• 2004

The performance of turbo code is improved by updating extrinsic information. The bit patterns are categorized by the transition characteristics of extrinsic information in this paper. And the distribution of these patterns is surveyed according to signal-to-noise ratio. Based on the results, the dominant error pattern is determined at high signal-to-noise ratio range. Thus, it is expected to improve the error performance in the error floor region by correcting the dominant error pattern which is found in this paper.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.2
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• pp.121-127
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• 2008

Micro end-milling has been becoming an important machining process to manufacture a number of small products such as micro-devices, bio-chips, micro-patterns and so on. Despite the importance of micro end-milling, many related researches have given grand efforts to micro end-milling phenomenon, for example, micro end-milling mechanism, cutting force modeling and machinability. This paper strongly concerned actual problem, micro tool deflection, which causes excessive machining errors on the workpiece. To solve this problem, machining error prediction method was proposed through a series of test micro cutting and analysis of their SEM images. An iterative algorithm was applied in order to obtain corrected tool path which allows reducing machining errors in spite of tool deflection. Experiments are carried out to validate the proposed approaches. In result, remarkable error reduction could be obtained.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.1
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• pp.83-88
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• 2019

Structural analysis remains as an essential part of any integrated civil engineering system in today's rapidly changing computing environment. Even with enormous advancements in capabilities of computers and mobile tools, enhancing computational efficiency of algorithms is necessary to meet the changing demands for quick real time response systems. The finite element method is still the most widely used method of computational structural analysis; a robust, reliable and automated finite element structural analysis module is essential in a modern integrated structural engineering system. To be a part of an automated finite element structural analysis, an efficient adaptive mesh generation scheme based on R-H refinement for the mesh and error estimates from representative strain values at Gauss points is described. A coefficient that depends on the shape of element is used to correct overly distorted elements. Two simple case studies show the validity and computational efficiency. The scheme is appropriate for nonlinear and dynamic problems in earthquake engineering which generally require a huge number of iterative computations.