• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.13-19
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• 2001

The conventional fractal decoding was required a vast amount computational complexity, since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested that each range block was classified to iterated and non-iterated regions. Non-iterated regions is called data dependency region, and if data dependency region extended, IFS regions are contractive. In this paper, a searched region of the domain is limited to the range regions that is similar with the domain blocks, and the domain region is more overlapped. As a result, data dependency region has maximum region, that is IFS regions can be minimum region. The minimizing method of domain region is defined to minimum domain(MD) which is minimum IFS region. Using the minimizing method of domain region, there is not influence PSNR(peak signal-to-noise ratio). And it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• Journal of Korea Multimedia Society
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• v.2 no.1
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• pp.38-46
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• 1999

In this paper, the fractal image compression using the minimizing method of domain region is proposed. It is minimize to domain regions in the process of decoding. Since the conventional fractal decoding applies to IFS(iterative function system) for the total range blocks of the decoded image, its computational complexity is a vast amount. In order to improve this using the number of the referenced times to the domain blocks for the each range blocks, a classification method which divides necessary and unnecessary regions for IFS is suggested. If necessary regions for IFS are reduced, the computational complexity is reduced. The proposed method is to define the minimum domain region that a necessary region for IFS is minimized in the encoding algorithms. That is, a searched region of the domain is limited to the range regions that is similar with the domain regions. So, the domain region is more overlapped. Therefore, there is not influence on image quality or PSNR(peak signal-to-noise ratio). And it can be a fast decoding by reduce the computational complexity for IFS in fractal image decoding.

• 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.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.237-247
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• 1997

A geometrical inverse heat conduction problem is solved for the infrared scanning cavity detection by the boundary element method using minimal energy technique. By minimizing the kinetic energy of temperature field, boundary element equations are converted to the quadratic programming problem. A hypothetical inner boundary is defined such that the actual cavity is located interior to the domain. Temperatures at hypothetical inner boundary are determined to meet the constraints of mea- surement error of surface temperature obtained by infrared scanning, and then boundary element analysis is peformed for the position of an unknown boundary (cavity). Cavity detection algorithm is provided, and the effects of minimal energy technique on the inverse solution method are investigated by means of numerical analysis.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.364-366
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• 2004

소프트웨어 개발 과정의 여러 산출물 간의 일관성 유지는 최종 소프트웨어의 품질을 결정하는 중요한 요소가 되며, 운영단계의 유지보수 효율성에도 큰 영향을 미친다. 특히 구현 등 개발 후반부 활동을 진행시 발견된 하나의 오류는 그 이전 단계의 다수의 산출물의 오류로 인한 파급 결과이므로, 발견된 오류의 원인(Cause)가 되는 이전 단계의 오류를 효과적으로 추적할 수 있는 체계가 요구된다. 본 논문에서는 한 산출물의 오류가 다른 어떤 산출물의 어떤 세부항목들의 어떤 오류로 인한 파급 결과인지를 정의한 역추적(Backtracking) 그래프를 제안하여, 개발자가 오류를 발견 시 관련 산출물과 항목을 신속히 파악할 수 있도록 한다. 이를 이용하여 산출물간의 일관성 유지 노력과 시간을 최소화하고 일관성 유지의 정확성을 높일 수 있다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.7
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• pp.761-768
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• 2010

This paper presents an effective method to achieve the wideband waveform for high resolution SAR(Synthetic Aperture Radar) using the frequency multiplication technique. And also this paper analyzes the root causes for the spectral regrowth due to 3rd-order intermodulation in chirp bandwidth expansion scheme using quadrature modulator and frequency multipliers. The amplitude and phase imbalance requirement are defined based on the simulation results in terms of quadrature channel imbalance. This minimizes the degradation of range resolution, peak sidelobe ratio and integrated sidelobe ratio. The wideband chirp generator using the frequency multiplier and memory map scheme was manufactured and the compensation technique was presented to reduce the spectral regrowth of SAR waveform by minimizing the amplitude and phase imbalance. After I and Q channel imbalance adjustment, the carrier level reduces －28.7 dBm to －53.4 dBm. Chirp signal with 150 MHz bandwidth at S-band expands to 600 MHz bandwidth at X-band. The sidelobe levels are reduced by about 8 to 9 dB by compensating the amplitude balance between I and Q channels.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.227-233
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• 2004

Complex scheduling problems are related to planning, scheduling, constraint satisfaction problems, object-oriented concepts, and agent systems. Human preference-driven scheduling technique was to solve complex scheduling problems using constraint satisfaction problems and object-oriented concepts. We have tried to apply human preference-driven scheduling technique to reservation problems. For customer's satisfaction, we have considered customer's preferences in the reservation scheduling. The technique of reservation scheduling proposed in this thesis is based on object-oriented concepts. 1'o consider the over all satisfaction, the events of every object are alloted to the board along its priority. Constraints to reservation scheduling are classified to global and local. The definition of board and information of every event are global constraints and the preferences to object's board slots are local constraints. We have applied look-ahead technology to reservation scheduling in order to minimize backtracking not to fail the allotment of events.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.203-211
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• 2023

A Markov chain Monte Carlo (MCMC) simulation is proposed for probabilistic full waveform inversion (FWI) in a layered half-space. Dynamic responses on the half-space surface are estimated using the thin-layer method when a harmonic vertical force is applied. Subsequently, a posterior probability distribution function and the corresponding objective function are formulated to minimize the difference between estimations and observed data as well as that of model parameters from prior information. Based on the gradient of the objective function, a proposal distribution and an acceptance probability for MCMC samples are proposed. The proposed MCMC simulation is applied to several layered half-space examples. It is demonstrated that the proposed MCMC simulation for probabilistic FWI can estimate probabilistic material properties such as the shear-wave velocities of a layered half-space.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.145-150
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• 2019

We develop the system realization of whale sound reconstruction by inverse MFCC algorithm with the weighted L2-norm minimization techniques. The output products from this research will contribute to the whale tourism and multimedia content industry by combining whale sound contents with the prototype of 3D printing. First of all, we develop the softwares for generating whale sounds and install them into Raspberry Pi hardware and fasten them inside a 3D printed whale. The languages used in the development of this system are the C++ for whale-sounding classification, MATLAB and Python for whale-sounding playback algorithm, and Rhino 6 for 3D printing.