• The KSFM Journal of Fluid Machinery
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• v.18 no.6
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• pp.37-44
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• 2015

Conjugate heat analysis on a high pressure turbine stage including secondary flow paths has been carried out. The secondary flow paths were designed to be located in front of the nozzle and between the nozzle and rotor domains. Thermal boundary conditions such as empirical based temperature or heat transfer coefficient were specified at nozzle and rotor solid domains. To create heat transfer interface between the nozzle solid domain and the rotor fluid domain, frozen rotor with automatic pitch control was used assuming that there is little temperature variation along the circumferential direction at the nozzle solid and rotor fluid domain interface. The simulation results showed that secondary flow injected from the secondary flow path not only prevents main flow from penetrating into the secondary flow path, but also effectively cools down the nozzle and rotor surfaces. Also thermal barrier coating with different thickness was numerically implemented on the nozzle surface. The thermal barrier coating further reduces temperature gradient over the entire nozzle surface as well as the overall temperature level.

• Journal of Ocean Engineering and Technology
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• v.12 no.1
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• pp.120-127
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• 1998

An Elliptic model for calculating the combined refraction/diffraction of monochromatic linear waves is developed, including a term which allows for the dissipation of wave energy. Conjugate gradient method is employed as a solution technique. Wave height variations are calculated for localized circular and rectangular dissipation areas. It is shown that the numerical results agree very well with analytical solution in the case of circular damping region. The localized dissipation area creates a shadow region of low wave energy and the recovery of wave height by diffraction occurs very slowly with distance behind the damping region.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.7 no.4
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• pp.321-328
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• 1995

The FIT(fully implicit tidal) model which adopts PCGCS (preconditioned conjugate gradient squared) method is developed and is applied to near Mokpo Harbor. Comparing computational results with observed velocities and elevations for the M$_2$ tidal constituent, agreeable correspondence is detected. The validity of the model is also proven by applying it to such areas which have narrow width (therefore showing rapid velocity), irregular topography and complex geometry. Tidal amplification phenomenon according to the constructions of seadike and sea-walls is considered by analyzing the 'filter effect' of Mokpo-ku using the model.

• BMB Reports
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• v.31 no.1
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• pp.95-100
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• 1998

Two innovative methods to prepare target-sensitive immunoliposomes containing doxorubicin by coupling monoclonal antibodies (mAb DH2, SH1) specific to cancer cell surface antigens ($G_{M3}$, $Le^X$) have been developed and are described here. Firstly, liposomes containing N-glutaryl phosphatidylethanolamine (NGPE) were prepared, followed by the encapsulation of doxorubicin, DH2 or SH1 antibodies were conjugated to NGPE in the liposomes (direct coupling). Secondly, liposomes were prepared with NGPE/mAb conjugates by the detergent dialysis method (conjugate insertion), and then doxorubicin was encapsulated by proton gradient. The immunoliposomes prepared by both methods were able to specifically bind to the surface of the tumor cells - B16BL6 mouse melanoma cells. The efficiencies of doxorubicin-entrapping into liposomes prepared by direct coupling and conjugate insertion was about 98% and 25%, respectively. These types of liposomal formulation are sensitive to target cells, which can be useful for various clinical applications.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.298-301
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• 2000

We discuss the iterative methods for linear systems on a single processing node of the HITACHI SR8000. Each processing node of the SR8000 is a shared memory parallel computer which is composed of eight RISC processors with a pseudo-vector facility. We implement highly optimized codes for basic linear operations including a matrix-vector product and apply them to the conjugate gradient (CG) and the conjugate residual (CR) methods for linear systems. Our tuned codes for both method score nearly 50% of the theoretical peak performance, which is the best in the sense that it corresponds to an asymptotic performance of the inner product.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.4
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• pp.134-138
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• 2015

Heart sound is used for a basic clinical examination to check for abnormalities in the lungs and heart that can be heard with a stethoscope or phonocardiography. In this paper, we try to find an easier and non-invasive method to diagnose heart diseases using neural network classifier. The classifier has been developed for one normal heart sound and five murmurs by using Shannon entropy and conjugate scaled back propagation algorithm. The experimental results showed that the classification is possible with 1.63185e-6 of classification error.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.2
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• pp.169-176
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• 2012

This paper uses loop-star basis functions to overcome the low frequency breakdown problem in method of moments (MoM) based on electric field integral equation(EFIE). In addition, p-Type Multiplicative Schwarz preconditioner (p-MUS) technique is employed to reduce the number of iterations required for the conjugate gradient method(CGM). Low frequency instability with Rao Wilton Glisson(RWG) basis functions in EFIE can be resolved using loop-start basis functions and frequency normalized techniques. However, loop-star basis functions, consisting of irrotational and solenoidal components of RWG basis functions, require a large number of iterations to calculate a solution through iterative methods, such as conjugate gradient method(CGM), due to high condition number. To circumvent this problem, in this paper, the pMUS preconditioner technique is proposed to reduce the number of iterations in CGM. Simulation results show that pMUS preconditioner is much faster than block diagonal preconditioner(BDP) when the sparsity of pMUS is the same as that of BDP.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.90-100
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• 2011

We present a parallel bi-conjugate gradient (Bi-CG) matrix solver for large scale Bio-FET simulations based on recent graphics processing units (GPUs) which can realize a large-scale parallel processing with very low cost. The proposed method is focused on solving the Poisson equation in a parallel way, which requires massive computational resources in not only semiconductor simulation, but also other various fields including computational fluid dynamics and heat transfer simulations. As a result, our solver is around 30 times faster than those with traditional methods based on single core CPU systems in solving the Possion equation in a 3D FDM (Finite Difference Method) scheme. The proposed method is implemented and tested based on NVIDIA's CUDA (Compute Unified Device Architecture) environment which enables general purpose parallel processing in GPUs. Unlike other similar GPU-based approaches which apply usually 32-bit single-precision floating point arithmetics, we use 64-bit double-precision operations for better convergence. Applications on the CUDA platform are rather easy to implement but very hard to get optimized performances. In this regard, we also discuss the optimization strategy of the proposed method.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.692-704
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• 2005

With the improvement of computer hardware, GPUs(Graphics Processor Units) have tremendous memory bandwidth and computation power. This leads GPUs to use in general purpose computation. Especially, GPU implementation of compute-intensive physics based simulations is actively studied. In the solution of differential equations which are base of physics simulations, tridiagonal matrix systems occur repeatedly by finite-difference approximation. From the point of view of physics based simulations, fast solution of tridiagonal matrix system is important research field. We propose a fast GPU implementation for the solution of tridiagonal matrix systems. In this paper, we implement the cyclic reduction(also known as odd-even reduction) algorithm which is a popular choice for vector processors. We obtained a considerable performance improvement for solving tridiagonal matrix systems over Thomas method and conjugate gradient method. Thomas method is well known as a method for solving tridiagonal matrix systems on CPU and conjugate gradient method has shown good results on GPU. We experimented our proposed method by applying it to heat conduction, advection-diffusion, and shallow water simulations. The results of these simulations have shown a remarkable performance of over 35 frame-per-second on the 1024x1024 grid.

• Journal of applied mathematics & informatics
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• v.32 no.5_6
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• pp.761-781
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• 2014

An exponentially accurate nonconforming spectral element method for elasticity systems with discontinuities in the coefficients and the flux across the interface is proposed in this paper. The method is least-squares spectral element method. The jump in the flux across the interface is incorporated (in appropriate Sobolev norm) in the functional to be minimized. The interface is resolved exactly using blending elements. The solution is obtained by the preconditioned conjugate gradient method. The numerical solution for different examples with discontinuous coefficients and non-homogeneous jump in the flux across the interface are presented to show the efficiency of the proposed method.