• Journal of applied mathematics & informatics
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• v.35 no.3_4
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• pp.399-411
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• 2017

We first provide the linear operator equations corresponding to the Tikhonov regularization image denoising problems with different regularization terms, and then we propose how to choose Kronecker product preconditioners which are required for accelerating the $G{\ell}$-PCG method. Next, we provide how to apply the $G{\ell}$-PCG method with Kronecker product preconditioner to the linear operator equations. Lastly, we provide numerical experiments for image denoisng problems to evaluate the effectiveness of the $G{\ell}$-PCG with Kronecker product preconditioner.

• Journal of applied mathematics & informatics
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• v.36 no.5_6
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• pp.531-540
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• 2018

We first show how to construct the linear operator equations corresponding to Tikhonov regularization problems for solving image deblurring problems with nearly separable point spread functions. We next propose a Kronecker product preconditioner which is suitable for the global PCG method. Lastly, we provide numerical experiments of the global PCG method with the Kronecker product preconditioner for several image deblurring problems to evaluate its effectiveness.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.905-907
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• 1991

One of the general methods to diagnose abnormalities of heart is stethoscopy. This method needs special skill and experiment of doctors and it lacks for objectivity. Electrocardiography(ECG) is another biomedical method which is commonly used to diagnoss abnormalities of heart. The development of PCG is required in recent years to improve objectivity of stethoscopy method. In this paper, PCG is implemented on personal computer and ECG is also included to help the analysis of PCG waveform. Time analysis is used so far, but in this paper the frequency analysis is also considered to improve the accuracy of disgonosis. As future research, recognition of PCG and ECG signal and the Expert System is required to improve the accuracy of diagnosis.

• Journal of applied mathematics & informatics
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• v.36 no.3_4
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• pp.317-330
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• 2018

We first provide how to apply the global preconditioned conjugate gradient ($G{\ell}-PCG$) method with Kronecker product preconditioners to image deblurring problems with nearly separable point spread functions. We next provide a coarse-grained parallel image deblurring algorithm using the $G{\ell}-PCG$. Lastly, we provide numerical experiments for image deblurring problems to evaluate the effectiveness of the $G{\ell}-PCG$ with Kronecker product preconditioner by comparing its performance with those of the $G{\ell}-CG$, CGLS and preconditioned CGLS (PCGLS) methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.237-240
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• 2009

We suggested the portable measurement system that estimate heart-condition for heart disease patients and healthy. We used informations of ECG and PCG in this system. The informations of ECG and PCG obtained by using electrodes and microphone, respectively.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.331-339
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• 2002

A preconditioned conjugate gradient(PCG) scheme with the aid of deflation for computing a few of the smallest eigenvalues arid their corresponding eigenvectors of the large generalized eigenproblems is considered. Topically there are two types of deflation techniques, the deflation with partial shifts and an arthogonal deflation. The efficient way of determining partial shifts is suggested and the deflation-PCG schemes with various partial shifts are investigated. Comparisons of theme schemes are made with orthogonal deflation-PCG, and their asymptotic behaviors with restart operation are also discussed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8C
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• pp.786-794
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• 2006

We proposed a novel preconditioner based PCG(Preconditioned Conjugate Gradient) method for super resolution image reconstruction. Compared with the conventional block circulant type preconditioner, the proposed preconditioner can be more effectively applied for objective functions that include roughness penalty functions. The effectiveness of the proposed method was shown by simulations and experiments.

• Applied Science and Convergence Technology
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• v.24 no.6
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• pp.268-272
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• 2015

We report the systematic study to reduce extrinsic doping in graphene grown by chemical vapor deposition (CVD). To investigate the effect of crystallinity of graphene on the extent of the extrinsic doping, graphene samples with different levels of crystal quality: poly-crystalline and single-crystalline graphene (PCG and SCG), are employed. The graphene suspended in air is almost undoped regardless of its crystallinity, whereas graphene placed on an $SiO_2/Si$ substrate is spontaneously p-doped. The extent of p-doping from the $SiO_2$ substrate in SCG is slightly lower than that in PCG, implying that the defects in graphene play roles in charge transfer. However, after annealing treatment, both PCG and SCG are heavily p-doped due to increased interaction with the underlying substrate. Extrinsic doping dramatically decreases after annealing treatment when PCG and SCG are placed on the top of hexagonal boron nitride (h-BN) substrate, confirming that h-BN is the ideal substrate for reducing extrinsic doping in CVD graphene.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.362-369
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• 1998

The computational environment in which engineers perform their designs has been rapidly evolved from coarse serial machines to massively parallel machines. Although the recent development of high-performance computers are available for a number of years, only limited successful applications of the new computational environments in computational structural engineering field has been reported due to its limited availability and large cost associated with high-performance computing. As a new computational model for high-performance engineering computing without cost and availability problems, parallel structural analysis models for large scale structures on a network of personal computers (PCs) are presented in this paper. In structural analysis solving routine for the linear system of equations is the most time consuming part. Thus, the focus is on the development of efficient preconditioned conjugate gradient (PCG) solvers on the proposed computational model. Two parallel PCG solvers, PPCG-I and PPCG-II, are developed and applied to analysis of large scale space truss structures.

• Transactions of Materials Processing
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• v.30 no.5
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• pp.219-225
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• 2021

When extruding Al6061 alloys, deformation energy is deposited inside the extruded alloy depending on the deformation and the temperature of extrusion. This creates a Peripheral Coarse Grain (PCG) on the surface, where relatively more deformation energy. of the extruded alloy has been accumulated. Furthermore, since the deformation of materials continues while the materials recrystallize, it is important to examine the effect of deformation energy on dynamic recrystallization in the process of extruding Al alloys along with their microstructure. Prior studies explain the theory behind PCG growth though quantitative analysis on PCG growth of Al alloys during extrusion processes has not yet been addressed. This study aims to measure the generated PCG thickness which determines the correlation between extrusion outlet temperature and its effect on mechanical properties. Surface structure observations were performed using Optical Microscope (OM) and mechanical properties were evaluated through tensile strength and hardness measurement. Throughout this study, we endevoured to find the optimum condition of extrusion exit temperature of Al6061 and confirmed improved d reliability. This study describes the effect of the complex process variables such as exit temperature on the thickness of PCG layer for the Al6061 alloy using the 200 tons extrusion press. We therefore, discovered that the PCG layer thickness was 117 ㎛ at temperatures between 460 ℃ to 520 ℃.