• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.3
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• pp.215-222
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• 2006

The Lowry method was used in this study to measure protein in Haemophilus influenzae type b (Hib) conjugate vaccines (polyribosylibitol phosphate-tetanus toxoid; PRP-TT) using deoxycholic acid (DOC) to induce protein precipitation. Trichloroacetic acid (TCA) did not induce precipitation adequately from the Hib conjugate bulk and the freeze-dried Hib conjugate product. Its yield was approximately 50%. The matrix structure of Hib conjugate inhibits precipitation by TCA. Although the Lowry method can be carried out without precipitation in Hib conjugate bulk when no residual impurities (adipic acid dihydrazide [ADH], 1-ethyl-3-(3-dimethylamino-propyl) carbodiimide-HCI [EDAC], phenol and cyanogens bromide [CNBr], etc.) are present, it cannot be used for Hib conjugate products that contain sucrose 8.5%, because 8.5% concentration of sucrose enhanced the protein concentration. DOC- and HCl-induced precipitation is an alternative method for evaluating the protein content of the Hib conjugate bulk and the Hib conjugate product. The precipitation was optimal with a final concentrate of 0.1% for DOC at $4^{\circ}C$ and pH 2. This Lowry method, using DOC/HCI precipitation to induce protein precipitation, was confirmed a consistent, reproducible, and valid test for proteins in Hib conjugate bulk and its freeze-dried product.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1303-1309
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• 2011

Based on the PRP method, a new spectral PRP conjugate gradient method has been proposed to solve general unconstrained optimization problems which produce sufficient descent search direction at every iteration without any line search. Under the Wolfe line search, we prove the global convergence of the new method for general nonconvex functions. The numerical results show that the new method is efficient for the given test problems.

• Journal of the Chungcheong Mathematical Society
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• v.11 no.1
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• pp.129-142
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• 1998

In this paper, we propose a blocked variant of the Conjugate Gradient method which performs as well as and has coarser parallelism than the classical Conjugate Gradient method.

• Journal of the military operations research society of Korea
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• v.24 no.1
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• pp.146-156
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• 1998

Cholesky factorization is known to be inefficient to problems with dense column and network problems in interior point methods. We use the conjugate gradient method and preconditioners to improve the convergence rate of the conjugate gradient method. Several preconditioners were applied to LPABO 5.1 and the results were compared with those of CPLEX 3.0. The conjugate gradient method shows to be more efficient than Cholesky factorization to problems with dense columns and network problems. The incomplete Cholesky factorization preconditioner shows to be the most efficient among the preconditioners.

• Journal of Mechanical Science and Technology
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• v.20 no.10
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• pp.1741-1752
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• 2006

A combined Streamline Upwind Petrov-Galerkin method (SUPG) and segregated finite element algorithm for solving conjugate heat transfer problems where heat conduction in a solid is coupled with heat convection in viscous fluid flow is presented. The Streamline Upwind Petrov-Galerkin method is used for the analysis of viscous thermal flow in the fluid region, while the analysis of heat conduction in solid region is performed by the Galerkin method. The method uses the three-node triangular element with equal-order interpolation functions for all the variables of the velocity components, the pressure and the temperature. The main advantage of the presented method is to consistently couple heat transfer along the fluid-solid interface. Four test cases, which are the conjugate Couette flow problem in parallel plate channel, the counter-flow in heat exchanger, the conjugate natural convection in a square cavity with a conducting wall, and the conjugate natural convection and conduction from heated cylinder in square cavity, are selected to evaluate efficiency of the presented method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.740-749
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• 1998

This paper proposes compression of image data using neural networks based on conjugate gradient method and dynamic tunneling system. The conjugate gradient method is applied for high speed optimization .The dynamic tunneling algorithms, which is the deterministic method with tunneling phenomenon, is applied for global optimization. Converging to the local minima by using the conjugate gradient method, the new initial point for escaping the local minima is estimated by dynamic tunneling system. The proposed method has been applied the image data compression of 12 ${\times}$12 pixels. The simulation results shows the proposed networks has better learning performance , in comparison with that using the conventional BP as learning algorithm.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.461-466
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• 2006

In this paper, an algorithm with a new Armijo-type line search is proposed that ensure global convergence of a correlative Polak-Ribiere conjugate method for the unconstrained minimization of non-convex differentiable function.

• Structural Engineering and Mechanics
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• v.65 no.4
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• pp.415-422
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• 2018

The Conjugate Finite-Step Length" (CFSL) algorithm is proposed to improve the efficiency and robustness of first order reliability method (FORM) for reliability analysis of highly nonlinear problems. The conjugate FORM-based CFSL is formulated using the adaptive conjugate search direction based on the finite-step size with simple adjusting condition, gradient vector of performance function and previous iterative results including the conjugate gradient vector and converged point. The efficiency and robustness of the CFSL algorithm are compared through several nonlinear mathematical and structural/mechanical examples with the HL-RF and "Finite-Step-Length" (FSL) algorithms. Numerical results illustrated that the CFSL algorithm performs better than the HL-RF for both robust and efficient results while the CFLS is as robust as the FSL for structural reliability analysis but is more efficient.

• Journal of applied mathematics & informatics
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• v.34 no.1_2
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• pp.157-165
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• 2016

In this paper, we develop a new hybridization conjugate gradient method for solving the unconstrained optimization problem. Under mild assumptions, we get the sufficient descent property of the given method. The global convergence of the given method is also presented under the Wolfe-type line search and the general Wolfe line search. The numerical results show that the method is also efficient.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.103-106
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• 2002

This paper presents an effective numerical method for analyzing three-dimensional unsteady conjugate heat transfer problems of a curved pipe subjected to infernally thermal stratification. In the present numerical analyses, the thermally stratified flows in the pipe are simulated using the standard $k-{\varepsilon}$turbulent model and the unsteady conjugate heat transfer is treated numerically with a simple and convenient numerical technique. The unsteady conjugate heat transfer analysis method is implemented in a finite volume thermal-hydraulic computer code based on a non-staggered grid arrangement, SIMPLEC algorithm and higher-order bounded convection scheme. Numerical calculations have been performed far the two cases of thermally stratified pipe flows where the surging directions are opposite each other i.e. In-surge and out-surge. The results show that the present numerical analysis method is effective to solve the unsteady flow and conjugate heat transfer in a curved pipe subjected to infernally thermal stratification.