• The Korean Journal of Physiology and Pharmacology
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• v.19 no.4
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• pp.319-325
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• 2015

Among solute carrier proteins, the organic anion transporters (OATs) play an important role for the elimination or reabsorption of endogenous and exogenous negatively charged anionic compounds. Among OATs, SLC22A9 (hOAT7) transports estrone sulfate with high affinity. The net decrease of estrogen, especially in post-menopausal women induces rapid bone loss. The present study was performed to search the SNP within exon regions of SLC22A9 in Korean females with osteoporosis. Fifty healthy controls and 50 osteoporosis patients were screened for the genetic polymorphism in the coding region of SLC22A9 using GC-clamped PCR and denaturing gradient gel electrophoresis (DGGE). Six SNPs were found on the SLC22A9 gene from Korean women with/without osteoporosis. The SNPs were located as follows: two SNPs in the osteoporosis group (A645G and T1277C), three SNPs in the control group (G1449T, C1467T and C1487T) and one SNP in both the osteoporosis and control groups (G767A). The G767A, T1277C and C1487T SNPs result in an amino acid substitution, from synonymous vs nonsynonymous substitution arginine to glutamine (R256Q), phenylalanine to serine (F426S) and proline to leucine (P496L), respectively. The Km values and Vmax of the wild type, R256Q, P496L and F426S were 8.84, 8.87, 9.83 and $12.74{\mu}M$, and 1.97, 1.96, 2.06 and 1.55 pmol/oocyte/h, respectively. The present study demonstrates that the SLC22A9 variant F426S is causing inter-individual variation that is leading to the differences in transport of the steroid sulfate conjugate (estrone sulfate) and, therefore this could be used as a marker for certain disease including osteoporosis.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.435-443
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• 2007

Computing the interior spectrum of large sparse generalized eigenvalue problems $Ax\;=\;{\lambda}Bx$, where A and b are large sparse and SPD(Symmetric Positive Definite), is often required in areas such as structural mechanics and quantum chemistry, to name a few. Recently, CG-type methods have been found useful and hence, very amenable to parallel computation for very large problems. Also, as in the case of linear systems proper choice of preconditioning is known to accelerate the rate of convergence. After the smallest eigenpair is found we use the orthogonal deflation technique to find the next m-1 eigenvalues, which is also suitable for parallelization. This offers advantages over Jacobi-Davidson methods with partial shifts, which requires re-computation of preconditioner matrx with new shifts. We consider as preconditioners Incomplete LU(ILU)(0) in two variants, ever-relaxation(SOR), and Point-symmetric SOR(SSOR). We set m to be 5. We conducted our experiments on matrices from discretizations of partial differential equations by finite difference method. The generated matrices has dimensions up to 4 million and total number of processors are 32. MPI(Message Passing Interface) library was used for interprocessor communications. Our results show that in general the Multi-Color ILU(0) gives the best performance.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1042-1047
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• 2004

Voltage control is an essential part of the electric energy transmission and distribution system to maintain proper voltage limit at the consumer's terminal. Besides the generating units that provide the basic voltage control, there are many additional voltage-controlling agents e.g., shunt capacitors, shunt reactors, static VAr compensators, regulating transformers mentioned in [1], [2]. The most popular one, among all those agents for controlling voltage levels at the distribution and transmission system, is the on-load tap changer transformer. It serves two functions-energy transformation in different voltage levels and the voltage control. Artificial Neural Network (ANN) has been realized as a convenient tool that can be used in controlling the on load tap changer in the distribution transformers. Usage of the ANN in this area needs suitable training and testing data for performance analysis before the practical application. This paper briefly describes a procedure of processing the data to train an Artificial Neural Network (ANN) to control the tap changer operating decision of parallel transformers for a closed primary bus. The data set are used to train a two layer ANN using three different neural net learning algorithms, namely, Standard Backpropagation [3], Bayesian Regularization [4] and Scaled Conjugate Gradient [5]. The experimental results are presented including performance analysis.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.3
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• pp.436-444
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• 1997

Three-dimensional conjugate heat transfer and particle deposition on a circular cylinder in the OVD process are numerically investigated. Flow and temperature fields are obtained by an iterative method, and thermophoretic particle deposition is simulated. Effects of the heat conduction in the cylinder, the rotation speed of the cylinder, and the traversing speed of torch on the deposition are studied. Effects of variable properties are also included. As the conductivity of the cylinder decreases, particle deposition rate and deposition efficiency greatly decrease due to the reduced temperature gradient. The rotation of the cylinder has no significant effect on the deposition due to the small diameter of the cylinder and low speed of rotation. Since the increase of the torch speed keeps the surface low temperature, the particle deposition increases with the traversing speed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.2
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• pp.1-4
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• 1999

The Helmholtz equation is very important in physics and engineering. However, solution of the Helmholtz equation is in general known as a very difficult phenomenon. For if the ${\omega}$ is negative, the FDM discretized linear system becomes indefinite, whose solution by iterative method requires a very clever preconditioner. In this paper we assume that ${\omega}$ is nonnegative, and determine the optimal ${\rho}$ parameter for the three dimensional ADI iteration for the Helmholtz equation. The ADI(Alternating Direction Implicit) method is also getting new attentions due to the fact that it is very suitable to the vector/parallel computers, for example, as a preconditioner to the Krylov subspace methods. However, classical ADI was developed for two dimensions, and for three dimensions it is known that its convergence behaviour is quite different from that in two dimensions. So far, in three dimensions the so-called Douglas-Rachford form of ADI was developed. It is known to converge for a relatively wide range of ${\rho}$ values but its convergence is very slow. In this paper we determine the necessary conditions of the ${\rho}$ parameter for the convergence and optimal ${\rho}$ for the three dimensional ADI iteration of the Peaceman-Rachford form for the real Helmholtz equation with nonnegative ${\omega}$. Also, we conducted some experiments which is in close agreement with our theory. This straightforward extension of Peaceman-rachford ADI into three dimensions will be useful as an iterative solver itself or as a preconditioner to the the Krylov subspace methods, such as CG(Conjugate Gradient) method or GMRES(m).

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.9 s.240
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• pp.1049-1056
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• 2005

A conservative pressure-based finite-volume numerical method has been developed for computing flow and heat transfer by using an unstructured grid system. The method admits arbitrary convex polyhedra. Care is taken in the discretization and solution procedures to avoid formulations that are cell-shape-specific. A collocated variable arrangement formulation is developed, i.e. all dependent variables such as pressure and velocity are stored at cell centers. Gradients required for the evaluation of diffusion fluxes and for second-order-accurate convective operators are found by a novel second-order accurate spatial discretization. Momentum interpolation is used to prevent pressure checkerboarding and the SIMPLE algorithm is used for pressure-velocity coupling. The resulting set of coupled nonlinear algebraic equations is solved by employing a segregated approach, leading to a decoupled set of linear algebraic equations fer each dependent variable, with a sparse diagonally dominant coefficient matrix. These equations are solved by an iterative preconditioned conjugate gradient solver which retains the sparsity of the coefficient matrix, thus achieving a very efficient use of computer resources.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.27 no.6
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• pp.787-793
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• 1994

It has been demonstrated for the finite-difference ocean circulation model that the problem of uncertain forcing and input data can be tackled with an optimization techniques. The uncertainty problem in interesting flow properties is exploring a finite difference ocean circulation model due to the uncertainty in the driving boundary conditions. The mathematical procedure is based upon optimization method by the conjugate gradient method using the simulated data and a simple barotropic model. An example for the ocean circulation model is discussed in which wind forcing and the steady-state circulation are determined from a simulated stream function.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1899-1909
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• 2015

Glaucoma is one of the most common causes of blindness which is caused by increase of fluid pressure in the eye which damages the optic nerve and eventually causing vision loss. An automated technique to diagnose glaucoma disease can reduce the physicians’ effort in screening of Glaucoma in a person through the fundal retinal images. In this paper, optimal hyper analytic wavelet transform for Glaucoma detection technique from fundal retinal images is proposed. The optimal coefficients for transformation process are found out using the hybrid GSO-Cuckoo search algorithm. This technique consists of pre-processing module, optimal transformation module, feature extraction module and classification module. The implementation is carried out with MATLAB and the evaluation metrics employed are accuracy, sensitivity and specificity. Comparative analysis is carried out by comparing the hybrid GSO with the conventional GSO. The results reported in our paper show that the proposed technique has performed well and has achieved good evaluation metric values. Two 10- fold cross validated test runs are performed, yielding an average fitness of 91.13% and 96.2% accuracy with CGD-BPN (Conjugate Gradient Descent- Back Propagation Network) and Support Vector Machines (SVM) respectively. The techniques also gives high sensitivity and specificity values. The attained high evaluation metric values show the efficiency of detecting Glaucoma by the proposed technique.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.11 no.3
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• pp.135-140
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• 1999

To simulate the wave transformation by an energy dissipation region, a numerical model is suggested by discretizing the elliptic mild-slope equation. Generalized conjugate gradient method is used as solution algorithm to apply parabolic approximation to open boundary condition. To demonstrate the applicabil-ity of the numerical procedure suggested, the wave scattering by a circular damping region is examined. The feature of reflection in front of the damping region is captured clearly by the numerical solution. The effect of the size of dissipation coefficient is examined for a rectangular damping region. The recovery of wave height by diffraction occurs very slowly with distance behind the damping region.

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.485-498
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• 2020

A diffusion synthetic acceleration (DSA) technique for the S_N transport equation discretized with the linear discontinuous expansion method with subcell balance (LDEM-SCB) on unstructured tetrahedral meshes is presented. The LDEM-SCB scheme solves the transport equation with the discrete ordinates method by using the subcell balances and linear discontinuous expansion of the flux. Discretized DSA equations are derived by consistently discretizing the continuous diffusion equation with the LDEM-SCB method, however, the discretized diffusion equations are not fully consistent with the discretized transport equations. In addition, a fine mesh rebalance (FMR) method is devised to accelerate the discretized diffusion equation coupled with the preconditioned conjugate gradient (CG) method. The DSA method is applied to various test problems to show its effectiveness in speeding up the iterative convergence of the transport equation. The results show that the DSA method gives small spectral radii for the tetrahedral meshes having various minimum aspect ratios even in highly scattering dominant mediums for the homogeneous test problems. The numerical tests for the homogeneous and heterogeneous problems show that DSA with FMR (with preconditioned CG) gives significantly higher speedups and robustness than the one with the Gauss-Seidel-like iteration.