• Animal Bioscience
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• 제36권3호
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• pp.498-505
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• 2023

Objective: This study was conducted to determine the optimal dose of novel iron amino acid complexes (Fe-Lys-Glu) by measuring laying performance, egg quality, egg iron (Fe) concentrations, and blood biochemical parameters in laying hens. Methods: A total of 1,260 18-week-old healthy Beijing White laying hens were randomly divided into 7 groups with 12 replicates of 15 birds each. After a 2-wk acclimation to the basal diet, hens were fed diets supplemented with 0 (negative control, the analyzed innate iron content was 75.06 mg/kg), 15, 30, 45, 60, and 75 mg Fe/kg as Fe-Lys-Glu or 45 mg Fe/kg from FeSO₄ (positive control) for 24 wk. Results: Results showed that compared with the negative and positive control groups, dietary supplementation with 30 to 75 mg Fe/kg from Fe-Lys-Glu significantly (linear and quadratic, p<0.05) increased the laying rate (LR) and average daily egg weight (ADEW); hens administered 45 to 75 mg Fe/kg as Fe-Lys-Glu showed a remarkable (linear, p<0.05) decrease in feed conversion ratio. There were no significant differences among all groups in egg quality. The iron concentrations in egg yolk and serum were elevated by increasing Fe-Lys-Glu levels, and the highest iron content was found in 75 mg Fe/kg group. In addition, hens fed 45 mg Fe/kg from Fe-Lys-Glu had (linear and quadratic, p<0.05) higher yolk Fe contents than that with the same dosage of FeSO₄ supplementation. The red blood cell (RBC) count and hemoglobin content (linear and quadratic, p<0.05) increased obviously in the groups fed with 30 to 75 mg Fe/kg as Fe-Lys-Glu in comparison with the control group. Fe-Lys-Glu supplementation also (linear and quadratic, p<0.05) enhanced the activity of copper/zinc-superoxide dismutase (Cu/Zn-SOD) in serum, as a result, the serum malonaldehyde content (linear and quadratic, p<0.05) decreased in hens received 60 to 75 mg Fe/kg as Fe-Lys-Glu. Conclusion: Supplementation Fe-Lys-Glu in laying hens could substitute for FeSO₄ and the optimal additive levels of Fe-Lys-Glu are 45 mg Fe/kg in layers diets based on the quadratic regression analysis of LR, ADEW, RBC, and Cu/Zn-SOD.

• 응용통계연구
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• 제10권2호
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• pp.293-308
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• 1997

일변량 분할 역회귀 방법은 일반화 회귀모형에서 효과적인 차원축약방향과 공간을 추정하는 방법이다. 본 논문에서는 두 일반화 회귀모형을 동시에 고려하여 효과적인 차원축약방향과 공간을 추정하는 방법으로 이변량 분할 역회귀를 제안한다. 이러한 이변량 분할 역회귀 방법은 모형식이 선형, 이차형, 삼차형, 비선형 등의 여러 모형식에서 효과적인 차원축약방향을 추정하며, 일변량 분할 역회귀에 비하여 모형에 존재하는 오차에 크게 영향을 받지 않고 효과적인 차원축약방향을 추정한다. 특히 모형식이 대칭의 이차형인 경우에 일변량 분할 역회귀 방법이 효과적인 차원축약방향을 추정하지 못하는 문제를 해결할 수 있다.

• Communications for Statistical Applications and Methods
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• 제15권1호
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• pp.95-104
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• 2008

This paper addresses issues of robustness in Bayesian optimal design. We may have difficulty applying Bayesian optimal design principles because of the uncertainty of prior distribution. When there are several plausible prior distributions and the efficiency of a design depends on the unknown prior distribution, robustness with respect to misspecification of prior distribution is required. We suggest a new optimal design criterion which has relatively high efficiencies across the class of plausible prior distributions. The criterion is applied to the problem of estimating the turning point of a quadratic regression, and both analytic and numerical results are shown to demonstrate its robustness.

• 품질경영학회지
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• 제34권1호
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• pp.48-53
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• 2006

Applying Bayesian optimal design principles is not easy when a prior distribution is not certain. We present a optimal design criterion which possibly yield a reasonably good design and also robust with respect to misspecification of the prior distributions. The criterion is applied to the problem of estimating the turning point of a quadratic regression. Exact mathematical results are presented under certain conditions on prior distributions. Computational results are given for some cases not satisfying our conditions.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(3)
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• pp.135-138
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• 2002

This paper addresses incremental learning method for regression. SVM(support vector machine) is a recently proposed learning method. In general training a support vector machine requires solving a QP (quadratic programing) problem. For very large dataset or incremental dataset, solving QP problems may be inconvenient. So this paper presents an incremental support vector learning method for function approximation problems.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 추계 학술발표회 논문집
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• pp.179-182
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• 2003

This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

• 한국연초학회지
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• 제3권2호
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• pp.115-122
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• 1981

Data for this study were obtained from Burley 21 (Nicotiana tabacum L.) grown under various densities on the field in 1978 and 1979 at the Jeonju Experiment Station, Korea Ginseng & Tobacco Research Institute. Interrelations between yield and its components were statistically studied by correlation, regression, and pathway analysis. Correlation of yield with plant population was significant and positive. Quadratic functions for yield vs. plant population and the length of the largest leaf were fitted to the data. Multiple recession equation between yield and its components (leaf number ($X_1$), a leaf area ($X_5$), weight per unit leaf area ($X_9$), plant population ($X_14$)), was significant at the 5% level. Measuring the relative importance of its components on yield, plant population was 49.5%, weight per unit leaf area 25.3%, a leaf 15.6%, and leaf number 9.8%.

• 약학회지
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• 제20권1호
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• pp.63-69
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• 1976

Prednisolone tablet product design problem was structured as constrained optimization problem and subsequently solved by multiple regression analysis and Lagrangian method of optimixation. Prednisolone was the drug chosen and anhydrous lactose and corn starch were the adjuvants. The effect of anhydrous lactose and corn starch concentrations on tablet hardness, volume, disintegration time and in vitro release rate was studied. The concentrations of anhydrous lactose and corn starch used in this experiment were 30-60 percent and 5-30 percent, respectively. A full second-order (quadratic) model with all possible two-factor interactions was employed. To obtain the values of anhydrous lactose and corn starch which miniumize the in vitro : release time (t$_{60%}$) subject to the constraint on tablet hardness, disintegration time and volume, we solved the Lagrange function. Multiple correlation coefficients for the regression models were correlated at less than 0.05 level and it was found that the optimum concentrations of anhydrous lactose and corn starch were 45 percent and 21 percent, respectively.

• Computers and Concrete
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• 제27권2호
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• pp.143-152
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• 2021

Large dams are a part of the infrastructure of any society, and a huge amount of resources are consumed to build them. Among the various types of dams, the optimum design of concrete gravity dams requires special attention because these types of dams require a huge amount of concrete for their construction. On the other hand, concrete gravity dams are among the structures whose design, regarding the acting forces, geometric parameters, and resistance and stability criteria, has some complexities. In the present study, an optimization methodology is proposed based on Sequential Quadratic Programming (SQP), and a computer program is developed to perform optimization of concrete gravity dams. The optimum results for 45 concrete gravity dams are studied and regression analyses are performed to obtain some explicit formulas for optimization of the gravity dams. The optimization of concrete gravity dams can be provided easily using the developed formulas, without the need to perform any more optimization process.

• Asian-Australasian Journal of Animal Sciences
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• 제24권1호
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• pp.17-27
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• 2011

A selection experiment for reduced residual feed intake (RFI) in Yorkshire pigs consisted of a line selected for lower RFI (LRFI) and a random control line (CTRL). Longitudinal measurements of daily feed intake (DFI) and body weight (BW) from generation 5 of this experiment were used. The objectives of this study were to evaluate the use of random regression (RR) and nonlinear mixed models to predict DFI and BW for individual pigs, accounting for the substantial missing information that characterizes these data, and to evaluate the effect of selection for RFI on BW and DFI curves. Forty RR models with different-order polynomials of age as fixed and random effects, and with homogeneous or heterogeneous residual variance by month of age, were fitted for both DFI and BW. Based on predicted residual sum of squares (PRESS) and residual diagnostics, the quadratic polynomial RR model was identified to be best, but with heterogeneous residual variance for DFI and homogeneous residual variance for BW. Compared to the simple quadratic and linear regression models for individual pigs, these RR models decreased PRESS by 1% and 2% for DFI and by 42% and 36% for BW on boars and gilts, respectively. Given the same number of random effects as the polynomial RR models, i.e., two for BW and one for DFI, the non-linear Gompertz model predicted better than the polynomial RR models but not as good as higher order polynomial RR models. After five generations of selection for reduced RFI, the LRFI line had a lower population curve for DFI and BW than the CTRL line, especially towards the end of the growth period.