• Journal of the Computational Structural Engineering Institute of Korea
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• v.12 no.3
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• pp.397-406
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• 1999

A new solution procedure for approximate reanalysis, using the staged hybrid methods with substructuring, is proposed in this study. Displacements are calculated with two step mixed procedures. First step is to introduce the conservative approximation, which is a hybrid form of the linear and reciprocal approximation, as local approximation. In the next step, it is combined with the global approximation by reduced basis approach. Stresses are evaluated from the displacements by matrix transformation. The quality of reanalyzed quantities can be greatly improved through these staged hybrid approximations, specially for large changes in the design. Overall procedures are based on substructuring scheme. Several numerical examples illustrate the validity and effectiveness of the proposed methods.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.11
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• pp.7-14
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• 2005

A subdomain-interface finite element method is suggested to solve a class of fully- coupled thermomechanical problems with contact boundaries. The penalty method is used for connecting subdomains that satisfy interface compatibility conditions. As a result, effective stiffness matrices are always positive definite, and computational efficiency can be improved to a considerable degree. Moreover, any complex-shaped domain can be divided into independently modeled subdomains without considering the conformity of meshes on interfaces. Using a computer code based on the present method, these advantageous features are shown through a set of numerical studies.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.301-308
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• 2007

This paper proposes high performance coprocessor architecture for real time dense disparity computation based on a phase-based binocular stereo matching technique called local weighted phase-correlation(LWPC). The algorithm combines the robustness of wavelet based phase difference methods and the basic control strategy of phase correlation methods, which consists of 4 stages. For parallel and efficient hardware implementation, the proposed architecture employs SIMD(Single Instruction Multiple Data Stream) architecture for each functional stage and all stages work on pipelined mode. Such that the newly devised pipelined linear array processor is optimized for the case of row-column image processing eliminating the need for transposed memory while preserving generality and high throughput. The proposed architecture is implemented with Xilinx HDL tool and the required hardware resources are calculated in terms of look up tables, flip flops, slices, and the amount of memory. The result shows the possibility that the proposed architecture can be integrated into one chip while maintaining the processing speed at video rate.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.25-36
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• 2004

This paper proposes and measures the performance of a distributed EIT (Electrical Impedance Tomography) image reconstruction algorithm which has a master-slave structure. The image construction is a computation based application of which the execute time is proportional to the cube of the unknowns. After receiving a specific frame from the master, each computing node extracts the basic elements by executing the first iteration of Kalman Filter in parallel. Then the master merges the basic element lists into one group and then performs the sequential iterations with the reduced number of unknowns. Every computing node has MATLAB functions as well as extended library implemented for the exchange of MATLAB data structure. The master implements another libraries such as threaded multiplication, partitioned inverse, and fast Jacobian to improve the speed of the serial execution part. The parallel library reduces the reconstruction time of image visualization about by half, while the distributed grouping scheme further reduces by about 12 times for the given target object when there are 4 computing nodes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1297-1308
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• 2006

Multiplications in finite fields are one of the most important arithmetic operations for implementations of elliptic curve cryptographic systems. In this paper, we propose a new multiplication algorithm and VLSI architecture over $GF(2^m)$ using Gaussian normal basis. The proposed algorithm is designed by using a symmetric property of normal elements multiplication and transforming coefficients of normal elements. The proposed multiplication algorithm is applicable to all the five recommended fields $GF(2^m)$ for elliptic curve cryptosystems by NIST and IEEE 1363, where $m\in${163, 233, 283, 409, 571}. A new VLSI architecture based on the proposed multiplication algorithm is faster or requires less hardware resources compared with previously proposed normal basis multipliers over $GF(2^m)$. In addition, we gives an easy method finding a basic multiplication matrix of normal elements.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.13-18
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• 2017

With the advancement of internet technology, the importance of data protection is gaining more attention. As a possible data protection solution, we propose a novel video encryption method using complemented maximum-length cellular automata (C-MLCA). The first step for encryption is to use 90/150 CA rule to generate a transition matrix T of a C-MLCA state followed by a 2D C-MLCA basis image. Then, we divide the video into multiple frames. Once, we perform exclusive-OR operation with the split frames and the 2D basis image, the final encrypted video can be obtained. By altering values of pixel, the fundamental information in visualizing image data, the proposed method provides improved security. Moreover, we carry out some computational experiments to further evaluate our method where the results confirm its feasibility.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.191-197
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• 2021

To calculate the induced charge of atoms in molecular dynamics, linear equations for the induced charges need to be solved. As induced charges are determined at each time step, the process involves considerable computational costs. Hence, an efficient method for calculating the induced charge distribution is required when analyzing large systems. This paper introduces the Uzawa method for solving saddle point problems, which occur in linear systems, for the solution of the Lagrange equation with constraints. We apply the accelerated Uzawa algorithm, which reduces computational costs noticeably using the Schur complement and preconditioned conjugate gradient methods, in order to overcome the drawback of the Uzawa parameter, which affects the convergence speed, and increase the efficiency of the matrix operation. Numerical models of molecular dynamics in which two gold nanoparticles are placed under external electric fields reveal that the proposed method provides improved results in terms of both convergence and efficiency. The computational cost was reduced by approximately 1/10 compared to that for the Gaussian elimination method, and fast convergence of the conjugate gradient, as compared to the basic Uzawa method, was verified.