• Food Science of Animal Resources
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• v.36 no.2
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• pp.145-151
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• 2016

The relationship between chemical compositions, meat quality traits, and palatability attributes in 10 primal cuts from Hanwoo steer carcasses were assessed. Sensory palatability attributes of Hanwoo beef were more closely related with fat content than to moisture or protein content. Among the chemical compositions, only fat had a significant correlation with juiciness (0.67, p<0.001), tenderness (0.32, p<0.05), and overall palatability (0.56, p<0.001). Oleic acid (%) was not significantly related with overall palatability (p>0.05). Overall palatability was negatively correlated with drip loss (−0.32, p<0.05), cooking loss (−0.36, p<0.05), and shear force (−0.54, p<0.01). The correlation between fat content and overall palatability was increased when higher fat cuts (Ansim, Dungsim, Chaekeut, Yangjee, and Kalbi) were analyzed, compared to lower fat cuts (Moksim, Abdari, Udun, Suldo, and Satae). Also, the correlation between shear force and overall palatability was decreased in lower fat cuts compared to higher fat cuts. Our results suggest that the palatability of Hanwoo beef can be improved by increasing fat content in muscles, as increased fat content leads to an increase in sensory tenderness, flavor, and juiciness.

• The Journal of Information Technology
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• v.3 no.2
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• pp.73-85
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• 2000

The efficient algorithms are suggested in this study for solving the multicommodity network flow problems applied to Communications Systems. These problems are typical NP-complete optimization problems that require integer solution and in which the computational complexity increases numerically in appropriate with the problem size. Although the suggested algorithms are not absolutely optimal, they are developed for computationally efficient and produce near-optimal and primal integral solutions. We supplement the traditional Lagrangian method with a price-directive decomposition. It proceeded as follows. First, A primal heuristic from which good initial feasible solutions can be obtained is developed. Second, the dual is initialized using marginal values from the primal heuristic. Generally, the Lagrangian optimization is conducted from a naive dual solution which is set as ${\lambda}=0$. The dual optimization converged very slowly because these values have sort of gaps from the optimum. Better dual solutions improve the primal solution, and better primal bounds improve the step size used by the dual optimization. Third, a limitation that the Lagrangian decomposition approach has Is dealt with. Because this method is dual based, the solution need not converge to the optimal solution in the multicommodity network problem. So as to adjust relaxed solution to a feasible one, we made efficient re-allocation heuristic. In addition, the computational performances of various versions of the developed algorithms are compared and evaluated. First, commercial LP software, LINGO 4.0 extended version for LINDO system is utilized for the purpose of implementation that is robust and efficient. Tested problem sets are generated randomly Numerical results on randomly generated examples demonstrate that our algorithm is near-optimal (< 2% from the optimum) and has a quite computational efficiency.

• East Asian mathematical journal
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• v.26 no.1
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• pp.9-23
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• 2010

In this paper we generalize large-update primal-dual interior point methods for linear optimization problems in [2] to the $P_*(\kappa)$ linear complementarity problems based on a new kernel function which includes the kernel function in [2] as a special case. The kernel function is neither self-regular nor eligible. Furthermore, we improve the complexity result in [2] from $O(\sqrt[]{n}(\log\;n)^2\;\log\;\frac{n{\mu}o}{\epsilon})$ to $O\sqrt[]{n}(\log\;n)\log(\log\;n)\log\;\frac{m{\mu}o}{\epsilon}$.

• Journal of applied mathematics & informatics
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• v.34 no.1_2
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• pp.19-34
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• 2016

In this paper, we present a split least-squares characteristic mixed finite element method(MFEM) to get the approximate solutions of the convection dominated Sobolev equations. First, to manage both convection term and time derivative term efficiently, we apply a least-squares characteristic MFEM to get the system of equations in the primal unknown and the flux unknown. Then, we obtain a split least-squares characteristic MFEM to convert the coupled system in two unknowns derived from the least-squares characteristic MFEM into two uncoupled systems in the unknowns. We theoretically prove that the approximations constructed by the split least-squares characteristic MFEM converge with the optimal order in L² and H¹ normed spaces for the primal unknown and with the optimal order in L² normed space for the flux unknown. And we provide some numerical results to confirm the validity of our theoretical results.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.13 no.3
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• pp.189-202
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• 2009

In this paper we propose new primal-dual interior point algorithms for $P_*(\kappa)$ linear complementarity problems based on a new class of kernel functions which contains the kernel function in [8] as a special case. We show that the iteration bounds are $O((1+2\kappa)n^{\frac{9}{14}}\;log\;\frac{n{\mu}^0}{\epsilon}$) for large-update and $O((1+2\kappa)\sqrt{n}log\frac{n{\mu}^0}{\epsilon}$) for small-update methods, respectively. This iteration complexity for large-update methods improves the iteration complexity with a factor $n^{\frac{5}{14}}$ when compared with the method based on the classical logarithmic kernel function. For small-update, the iteration complexity is the best known bound for such methods.

• East Asian mathematical journal
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• v.35 no.5
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• pp.569-587
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• 2019

In this paper, we consider a split least-squares characteristic mixed element method for Sobolev equations with a convection term. First, to manipulate both convection term and time derivative term efficiently, we apply a characteristic mixed element method to get the system of equations in the primal unknown and the flux unknown and then get a least-squares minimization problem and a least-squares characteristic mixed element scheme. Finally, we obtain a split least-squares characteristic mixed element scheme for the given problem whose system is uncoupled in the unknowns. We prove the optimal order in $L^2$ and $H^1$ normed spaces for the primal unknown and the suboptimal order in $L^2$ normed space for the flux unknown.

• East Asian mathematical journal
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• v.25 no.1
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• pp.55-68
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• 2009

In this paper we propose new large-update primal-dual inte-rior point algorithms for $P_*(\kappa)$ linear complementarity problems(LCPs). New search directions and proximity measures are proposed based on the kernel function$\psi(t)=\frac{t^{p+1}-1}{p+1}+\frac{e^{\frac{1}{t}}-e}{e}$,$p{\in}$[0,1]. We showed that if a strictly feasible starting point is available, then the algorithm has $O((1+2\kappa)(logn)^{2}n^{\frac{1}{p+1}}log\frac{n}{\varepsilon}$ complexity bound.

• Journal of the Korean Operations Research and Management Science Society
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• v.9 no.2
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• pp.3-8
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• 1984

This paper considers the intermediate warehouse location problem in a two stage distribution system where commodities are delivered from the given set of capacitated factories to customers via uncapacitated intermediate warehouses. In order to determine the subset of warehouses to open which minimizes the total distribution costs including the fixed costs associated with opening warehouses, the cross decomposition method for mixed integer programming recently developed by T.J. Van Roy is used. The cross decomposition unifies Benders decomposition and Lagrangean relaxation into a single framework that involves successive solutions to a primal subproblem and a dual subproblem. In our problem model, primal subproblem turns out to be a transshipment problem and dual subproblem turns out to be an intermediate warehouse location problem with uncapacitated factories.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.1
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• pp.59-70
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• 1992

Quadratic programming problems(QP) have been widely used as a direction-finding subproblem in the engineering and structural design optimization. To develop an efficient solution algorithm for the QP subproblems, theoretical aspects and numerical behavior of mathematical programming methods that can be used as QP solver are studied and compared. For the solution of both primal and dual QP, Simplex, gradient projection(GRP), and augmented Lagrange multiplier algorithms are investigated and coded. From the numerical study, it is found that the primal GRP algorithm with potential constraint strategy and the dual Simplex algorithm are more attractive and effective than the others. They have theoretical robustness as well. Moreover, primal GRP algorithm is preferable in case the number of constraints is larger than the number of design variables. Favorable features of GRP and Simplex algorithm are merged into a combined algorithm, which is useful in the structural design optimization.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.4
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• pp.531-540
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• 2012

Pigs from four sire lines were allocated to a series of low energy (LE, 3.15 to 3.21 Mcal ME/kg) corn-soybean meal-based diets with 16% wheat midds or high energy diets (HE, 3.41 to 3.45 Mcal ME/kg) with 4.5 to 4.95% choice white grease. All diets contained 6% DDGS. The HE and LE diets of each of the four phases were formulated to have equal lysine:Mcal ME ratios. Barrows (N = 2,178) and gilts (N = 2,274) were fed either high energy (HE) or low energy (LE) diets from 27 kg BW to target BWs of 118, 127, 131.5 and 140.6 kg. Carcass primal and subprimal cut weights were collected. The cut weights and carcass measurements were fitted to allometric functions (Y = A $CW^B$) of carcass weight. The significance of diet, sex or sire line with A and B was evaluated by linearizing the equations by log to log transformation. The effect of diet on A and B did not interact with sex or sire line. Thus, the final model was cut weight = (1+$b_D$(Diet)) A($CW^B$) where Diet = -0.5 for the LE and 0.5 for HE diets and A and B are sire line-sex specific parameters. Diet had no affect on loin, Boston butt, picnic, baby back rib, or sparerib weights (p>0.10, $b_D$ = -0.003, -0.0029, 0.0002, 0.0047, -0.0025, respectively). Diet affected ham weight (bD = -0.0046, p = 0.01), belly weight (bD = 0.0188, p = 0.001) three-muscle ham weight ($b_D$ = -0.014, p = 0.001), boneless loin weight (bD = -0.010, p = 0.001), tenderloin weight ($b_D$ = -0.023, p = 0.001), sirloin weight ($b_D$ = -0.009, p = 0.034), and fat-free lean mass ($b_D$ = -0.0145, p = 0.001). Overall, feeding the LE diets had little impact on primal cut weight except to decrease belly weight. Feeding LE diets increased the weight of lean trimmed cuts by 1 to 2 percent at the same carcass weight.