• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.631-636
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• 2007

Eigenvalue reduction schemes approximate the lower eigenmodes that represent the global behavior of the structures. In the, we proposed a two-level condensation scheme(TLCS) for the construction of a reduced system. In first step, the of candidate elements by energy estimation, Rayleigh quotient, through Ritz vector calculation, and next, the primary degrees of freedom is selected by sequential elimination from the degrees of freedom connected the candidate elements in the first step. In the present study, we propose TLCS combined with iterative improved reduced system(IIRS) to increase accuracy of higher modes intermediate range. Also, it possible to control the accuracy of the eigenvalues and eigenmodes of the reduced system. Numerical examples demonstrate performance of proposed method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.1
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• pp.65-73
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• 2007

In the inverse perturbation method, enormous computational resource was required to obtain reliable results, because all unspecified DOFs were considered as unknown variables. Thus, in the present study, a reduced system method is used to condense the unspecified DOFs by using the specified DOFs, and to improve the computational efficiency as well as the solution accuracy. In most of the conventional reduction methods, transformation errors occur in the transformation matrix between the unspecified DOFs and the specified DOFs. Thus it is hard to obtain reliable and accurate solution of inverse perturbation problems by reduction methods due to the error in the transformation matrix. This numerical trouble is resolved in the present study by adopting iterative improved reduced system(IIRS) as well as by updating the transformation matrix at every step. In this reduction method, system accuracy is related to the selection of the primary DOFs and Iteration time. And both are dependent to each other So, the two level condensation method (TLCS) is selected as Selection method of primary DOFs for increasing accuracy and reducing iteration time. Finally, numerical verification results of the present iterative inverse perturbation method (IIPM) are presented.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.231-234
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• 1997

This paper presents improved direct method for calculating the closest saddle node bifurcation (CSNB) point, which is also applicable to the selection of appropriate load shedding, reactive power compensation point detection. The proposed method reduced dimension of nonlinear equation compared with that of Dobson's direct method. The improved direct method, utilizing Newton Iterative method converges very quickly. But it diverges if the initial guess is not very close to CSNB. So the direct method is performed with the initial values obtained by carrying out the iterative method twice, which is considered most efficient at this time. Since sparsity techniques can be employed, this method is a good choice to a large scale system on-line application. Proposed method has been tested for 5-bus, New England 30-bus system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.347-352
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• 2007

Eigenvalue reduction schemes approximate the lower eigenmodes that represent the global behavior of the structures. In the previous study, we proposed a two-level condensation scheme (TLCS) for the construction of a reduced system. In the first step, the selection of candidate elements by energy estimation, Rayleigh quotient, through Ritz vector calculation. In the second step, the primary degrees of freedom are selected by the sequential elimination method from the degrees of freedom connected to the candidate elements in the first step. In the present study, we propose TLCS combined with iterative improved reduced system (IIRS) to increase accuracy of the higher modes in the intermediate range. Also, it is possible to control the accuracy of the eigenvalues and eigenmodes of the reduced system. Finally, numerical examples demonstrate the performance of the proposed method.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.491-496
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• 2003

In sensitivity analysis, semi-analytical method(SAM) reveals severe inaccuracy problem when relatively large rigid body motions are identified for individual elements. Recently such errors of SAM resulted by the finite difference scheme have been improved by the separation of rigid body mode. But the eigenvalue should be obtained first before the sensitivity analysis is performed and it takes much time in the case that large system is considered. In the present study, by constructing a reduced one from the original system, iterative method combined with mode decomposition technique is proposed to compute reliable semi-analytical design sensitivities. The sensitivity analysis is performed by the eigenvector acquired from the reduced system. The error of SAM caused by difference scheme is alleviated by Von Neumann series approximation.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.303-315
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• 2007

This paper proposes a 3D structure recovery and registration method that uses four or more common points. For each frame of a given video, a partial structure is recovered using tracked points. The 3D coordinates, camera positions and camera directions are computed at once by our improved scaled orthographic factorization method. The partially recovered point sets are parts of a whole model. A registration of point sets makes the complete shape. The recovered subsets are integrated by transforming each coordinate system of the local point subset into a common basis coordinate system. The process of shape recovery and integration is performed uniformly and linearly without any nonlinear iterative process and without loss of accuracy. The execution time for the integration is significantly reduced relative to the conventional ICP method. Due to the fast recovery and registration framework, our shape recovery scheme is applicable to various interactive video applications. The processing time per frame is under 0.01 seconds in most cases and the integration error is under 0.1mm on average.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2012-2018
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• 2001

This paper proposes the adaptive suboptimal iterative algorithm using threshold to reduce system complexity in the PTS\`s. Performance of the proposed adaptive suboptimal iteration algorithm is represented in terms of iteration number and CDF. In the case of the number of sub-block is 4, the 10-3 PAPR of the proposed method and P S improved this by 0.4dB compared to Cimini\`s. And the complexity of the proposed method was reduced to nearly 22% for the PTS\`s and 44% for the Cimini\`s for 8dB threshold. For the 8 sub-blocks, the 10$\^$-3/ PAPR of the proposed method reduced by 0.7dB compared to PTS\`s, but improved by 0.4dB compared to Cimini\`s. And the complexity of the proposed method was reduced to nearly 2.4% for the PTS\`s and 39% for the Cimini\`s.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.188-210
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• 2022

As a promising technique to support tremendous numbers of Internet of Things devices and a variety of applications efficiently, mobile edge computing (MEC) has attracted extensive studies recently. In this paper, we consider a MEC-assisted peer-to-peer (P2P) mobile communication system where MEC servers are deployed at access points to accelerate the communication process between mobile terminals. To capture the tradeoff between the time delay and the energy consumption of the system, a cost function is introduced to facilitate the optimization of the computation and communication resources. The formulated optimization problem is non-convex and is tackled by an iterative block coordinate descent algorithm that decouples the original optimization problem into two subproblems and alternately optimizes the computation and communication resources. Moreover, the MEC-assisted P2P communication system is compared with the conventional P2P communication system, then a condition is provided in closed-form expression when the MEC-assisted P2P communication system performs better. Simulation results show that the advantage of this system is enhanced when the computing capability of the receiver increases whereas it is reduced when the computing capability of the transmitter increases. In addition, the performance of this system is significantly improved when the signal-to-noise ratio of hop-1 exceeds that of hop-2.

• Journal of IKEEE
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• v.18 no.2
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• pp.272-281
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• 2014

In electrical impedance tomography (EIT), modified Newton Raphson (mNR) method is widely used inverse algorithm for static image reconstruction due to its convergence speed and estimation accuracy. The unknown conductivity distribution is estimated iteratively by minimizing a cost functional such that the residual error namely the difference in measured and calculated voltages is reduced. Although, mNR method has good estimation performance, EIT inverse problem still suffers from ill-conditioned and ill-posedness nature. To mitigate the ill-posedness, generally, regularization methods are adopted. The inverse solution is highly dependent on the choice of regularization parameter. In most cases, the regularization parameter has a constant value and is chosen based on experience or trail and error approach. In situations, when the internal distribution changes or with high measurement noise, the solution does not get converged with the use of constant regularization parameter. Therefore, in this paper, in order to improve the image reconstruction performance, we propose a new scheme to determine the regularization parameter. The regularization parameter is computed based on residual error and updated every iteration. The proposed scheme is tested with numerical simulations and laboratory phantom experiments. The results show an improved reconstruction performance when using the proposed regularization scheme as compared to constant regularization scheme.