• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.05a
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• pp.270-273
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• 2009

This work describes a method of determining material parameters included in recrystallization and grain growth models. Focus is on the recrystallization and grain growth models of Ni-Fe base superalloy, Alloy 718. High temperature compression tests at different strain, strain rate and temperature conditions were chosen to determine the material parameters of dynamic recrystallization model. The critical strain and dynamically recrystallized grain size and fraction at various process variables were quantitated with the microstructual analysis and strain-stress relationships of the compression tests. Besides, isothermal heat treatments were utilized to fit the material constants included in the grain growth model. Verification of the determined material parameters is carried out by comparing the measured data obtained from other compression tests.

• Journal of People, Plants, and Environment
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• v.24 no.6
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• pp.629-638
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• 2021

Background and objective: This study was conducted to develop diameter growth models for thinned Quercus glauca Thunb. (QGT) stands to inform production goals for treatment and provide the information necessary for the systematic management of this stands. Methods: This study was conducted on QGT stands, of which initial thinning was completed in 2013 to develop a treatment system. To analyze the tree growth and trait response for each thinning treatment, forestry surveys were conducted in 2014 and 2021, and a one-way analysis of variance (ANOVA) was executed. In addition, non-linear least squares regression of the PROC NLIN procedure was used to develop an optimal diameter growth model. Results: Based on growth and trait analyses, the height and height-to-diameter (H/D) ratio were not different according to treatment plot (p > .05). For the diameter of basal height (DBH), the heavy thinning (HT) treatment plot was significantly larger than the control plot (p < .05). As a result of the development of diameter growth models by treatment plot, the mean squared error (MSE) of the Gompertz polymorphic equation (control: 2.2381, light thinning: 0.8478, and heavy thinning: 0.8679) was the lowest in all treatment plots, and the Shapiro-Wilk statistic was found to follow a normal distribution (p > .95), so it was selected as an equation fit for the diameter growth model. Conclusion: The findings of this study provide basic data for the systematic management of Quercus glauca Thunb. stands. It is necessary to construct permanent sample plots (PSP) that consider stand status, location conditions, and climatic environments.

• Animal Bioscience
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• v.37 no.5
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• pp.817-825
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• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

• Korean Journal of Environmental Agriculture
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• v.39 no.3
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• pp.204-213
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• 2020

BACKGROUND: Since the number of crops cultivated in reclaimed land is huge, it is very difficult to quantify the total crop production. Therefore, a non-destructive method for predicting crop production is needed. Salt tolerant root vegetables such as red beets and sugar beet are suitable for cultivation in reclaimed land. If their underground biomass can be predicted, it helps to estimate crop productivity. Objectives of this study are to investigate maximum leaf length and weight of red beet, sugar beet, and turnips grown in reclaimed land, and to determine optimal model with regression analysis for linear and allometric growth models. METHODS AND RESULTS: Maximum leaf length, width, and root fresh weight of red beets, sugar beets, and turnips were measured. Ten linear models and six allometric growth models were selected for estimation of root fresh weight and non-linear regression analysis was conducted. The allometric growth model, which have a variable multiplied by square of maximum leaf length and maximum leaf width, showed highest R² values of 0.67, 0.70, and 0.49 for red beets, sugar beets, and turnips, respectively. Validation results of the models for red beets and sugar beets showed the R² values of 0.63 and 0.65, respectively. However, the model for turnips showed the R² value of 0.48. The allometric growth model was suitable for estimating the root fresh weight of red beets and sugar beets, but the accuracy for turnips was relatively low. CONCLUSION: The regression models established in this study may be useful to estimate the total production of root vegetables cultivated in reclaimed land, and it will be used as a non-destructive method for prediction of crop information.

• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.103-118
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• 2015

The purpose of this paper is to discuss possibilities of applying growth curve models, such as Logistic, Log-Logistic, Log-Normal, Gompertz and Weibull, to three specific technology areas of Fishery Science and Technology in the process of measuring their technology level between Korea and countries with the state-of-the art level. Technology areas of hazard control of organism, environment restoration, and fish cluster detect were selected for this study. Expert panel survey was conducted to construct relevant panel data for years of 2013, 2016, and a future time of approaching the theoretical maximum technology level. The size of data was 70, 70 and 40 respectively. First finding is that estimation of shape and location parameters of each model was statistically significant, and lack-of-fit test using estimated parameters was statistically rejected for each model, meaning all models were good enough to apply for measuring technology levels. Second, three models other than Pearl and Gompertz seemed very appropriate to apply despite the fact that previous case studies have used only Gompertz and Pearl. This study suggests that Weibull model would be a very valid candidate for the purpose. Third, fish cluster detect technology level is relatively higher for both Korea and a country with the state-of-the-art among three areas as of 2013. However, all three areas seem to be approaching their limits(highest technology level point) until 2020 for countries with the state-of-the-art. This implies that Korea might have to speed up her research activities in order to catch up them prior to 2020. Final suggestion is that future study may better apply various and more appropriate models respectively considering each technology characteristics and other factors.

• Asian-Australasian Journal of Animal Sciences
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• v.2 no.4
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• pp.599-605
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• 1989

A comparison of the ARC metabolizable energy system and the NRC net energy system was made with special reference to growing steers. Two simulation models, one based on the ARC and other on the NRC system, were constructed to examine differences between the energy systems. The average daily live-weight gains predicted from both models for growing steers were compared under various conditions in which equal feeding levels and metabolizabilities were assumed. The two simulation models yielded similar results with very high energy intake with high quality feed. Difference between the two systems became larger as feeding conditions deviated from the above. The ARC system generally predicted higher daily live-weight gains than the NRC system. This appeared to be due to the higher efficiency of utilization of metabolizable energy ($k_m$ and $k_f$) and basal metabolism (F), and lower energy value of growth (EVG) in the ARC system.

• Journal of the Korean Regional Science Association
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• v.15 no.1
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• pp.63-73
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• 1999

It is generally believed that there is a trade-off between economic growth and environmental quality since pollutants are generated in the process of production and consumption of commodities. Several researchers have shown this prevailing belief using the short-term input-output models. The literature, however, shows that there have been few attempts to investigate the relationship using long-term forecasting models. This motivates the current paper. This paper attempts to build a reginal growth model in a partial equilibrium framework taking into consideration the requirements of capital invested for pollutant abatement. Model is largely neoclassical. Labor is assumed to move a region with high utility specified in regional per capita average was income and pollution level while capital is partially mobile to a region with high returns. The regional growth is explored in a phase diagram. The paper shows that there are two stable growth equilibria which a region can converge over time and that the equilibria are distinguished by the initial threshold capital stock that a region holds. If the initial capital stock of a region is over(under) than the threshold size, the region converges to the higher (lower) growth equilibrium over time. Moreover, based on this result an environmental quality enhancing policy is analyzed in the phase diagram. It has revealed that the policy calls for the relocation of growth equilibrium points, specifically speaking, it stimulates an increase in labor stock and a decrease in capital stock. Hence the paper has suggested that the prevailing belief which the environmental policy negatively impacts on a regional economic growth is not always true.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.276-283
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• 2024

Currently, the overall tendency for green and sustainable economic development is creating a circular economy. In actuality, agricultural output is currently benefiting greatly from the growth of the circular economy. The creation of a circular economy helps address resource scarcity, save the environment, combat climate change, and increase economic efficiency. Vietnam's economy can grow quickly and sustainably by shifting to a circular economy production model. Comparing prior growth techniques to the digital age and implementing circular economic development connected with high technology will be a fantastic opportunity to boost growth efficiency. In actuality, Vietnam currently has a large number of agricultural circular economy models. These are models: Creating and using gas from waste and wastewater in livestock and farming; model combining cultivation, livestock, and aquaculture; agro-forestry model; garden-forest model; Circular model using agricultural by-products as a catalyst or creating other valuable products; model of moderation, linked to reducing the use of growth hormones, veterinary medications, pesticides, and artificial fertilizers in agriculture and animal husbandry. Unfortunately, there have been few studies and applications of the aforementioned models, which has made it difficult to build the agricultural sector sustainably. In this paper, we outline the current situation and propose solutions to develop a circular economy model in agriculture in Vietnam for sustainable development.

• Journal of Bio-Environment Control
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• v.25 no.3
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• pp.146-152
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• 2016

Due to complicate canopy structures of Irwin mangoes grown in greenhouses, it is difficult to determine their growth parameters accurately. Leaf area, leaf fresh weight, and leaf dry weight are widely used as indicators to diagnose the tree growth. Therefore, it is necessary to establish models that can non-destructively estimate these growth indicators. The objective of this study was to establish regression models to estimate leaf area, leaf fresh weight, and leaf dry weight of Irwin mangoes (Mangifera indica L. cv. Irwin) by using leaf length, leaf width, petiole length, and SPAD value. The input values of leaf length, leaf width, petiole length, and SPAD value of 6-year old Irwin mangoes were measured, and the corresponding output values of leaf area, leaf fresh weight, and leaf dry weight were also measured. After 14 models were selected among the existing models, coefficients of the models were estimated by regression analysis. Three models with higher $R^2$ and lower RMSE values selected. In validation the $R^2$ values for the selected models were 0.967, 0.743, and 0.567 in the leaf area, leaf fresh weight, and leaf dry weight models, respectively. It is concluded that this models will be helpful to conveniently diagnose the growth of the Irwin mango.

• Korean Management Science Review
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• v.31 no.3
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• pp.1-12
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• 2014

This study suggests the two types DEA models such as DEA CCR model and Super Efficiency model to evaluate the value of a company and to apply them for the investments. 14 kinds of real data of companies such as EV/EBITDA, EPS growth rate, PCR, PER, dividend yield, PBR, stock price/net current asset, debt ratio, current ratio, ROE, operating margin, inventory turnover, accounts receivable turnover, and sales growth ratio were used as input variables of DEA models. 12 year data from December 30, 2000 up to December 30, 2012 were collected, and the data with negative, missing and 0 values were removed reflecting the characteristics of the DEA. In order to verify the effectiveness of the models, we compared the historical variability and rate of return of both models those of the market. Study results are as follows. First, two DEA models are more stable than market in terms of rate of return because the historical variability of both models are less than that of market. Second, Super Efficiency model is more stable than CCR model. Lastly, the cumulative rate of return of Super Efficiency model (434%) is greater than that of the CCR model (420%) and that of the market (269%).