• Korean Journal of Ichthyology
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• v.12 no.3
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• pp.166-172
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• 2000

Growth of Ammodytes personatus was investigated based on the specimens collected in the costal waters of Shinsudo, Sacheon from March 20 to December 14, 1988. Age determination based on otolith. The rings in the otolith were used as the basis for age annulus. The time of ring formation was estimated to one time per year in May far 1st ring group and March for 2nd ring group. The spawning season peaked in December. It takes approximately 16 months for the first ring and 11 months for the second ring to form in the otolith. The opaque zone was formed and marked over summer at 1st ring group and spawning mark at 2nd ring group. The relationship between the total length(TL) and otolith radius(R), and body weight(BW) were represented respectively as follows: TL=29.17+182.9R, BW=$4.9{\times}10^{-8}TL^{3.9587}$. Von Bertalanffy growth model is $TL_t$ = 177.273 ($1_e^{-0.040(t+7.332)}$), Robertson growth model is $TL_t=\frac{150.275}{1+2.085e^{-0.099t}}$ and Gompertz growth model is $TL_t=157.551e^{-1.214exp(-0.069t)}$.

• Food Science of Animal Resources
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• v.33 no.2
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• pp.155-161
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• 2013

This study developed predictive models to evaluate the kinetic behaviors of Bacillus cereus and Staphylococcus aureus in milk during storage at various temperatures. B. cereus and S. aureus (3 Log CFU/mL) were inoculated into milk and stored at $10^{\circ}C$, $15^{\circ}C$, $20^{\circ}C$, and $30^{\circ}C$, as well as $5^{\circ}C$, $15^{\circ}C$, $25^{\circ}C$, and $35^{\circ}C$, respectively, while bacterial populations were enumerated. The growth data were fitted to the modified Gompertz model to estimate kinetic parameters, including the maximum specific growth rate (${\mu}_{max}$; Log CFU/[$mL{\cdot}h$]), lag phase duration (LPD; h), lower asymptote ($N_0$; Log CFU/mL), and upper asymptote ($N_{max}$; Log CFU/mL). To describe the kinetic behavior of B. cereus and S. aureus, the parameters were fitted to the square root model as a function of storage temperature. Finally, the developed models were validated with the observed data, and Bias (B) and Accuracy (A) factors were calculated. Cell counts of both bacteria increased with storage time. Primary modeling yielded the following parameters; ${\mu}_{max}$: 0.14-0.75 and 0.06-0.51 Log CFU/mL/h; LPD: 1.78-14.03 and 0.00-1.44 h, $N_0$: 3.10-3.37 and 2.09-3.07 Log CFU/mL, and $N_{max}$: 7.59-8.87 and 8.60-9.32 Log CFU/mL for B. cereus and S. aureus, respectively. Secondary modeling yielded a determination of coefficient ($R^2$) of 0.926.0.996. B factors were 1.20 and 0.94, and A factors were 1.16 and 1.08 for B. cereus and S. aureus, respectively. Thus, the mathematical models developed here should be useful in describing the kinetic behaviors of B. cereus and S. aureus in milk during storage.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.8
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• pp.1296-1303
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• 2014

This study was conducted to develop predictive models for the growth of Bacillus cereus on carrot treated with slightly acidic electrolyzed water (SAcEW) and ultrasonication (US) at different storage temperatures. In addition, the inactivation of B. cereus by US with SAcEW was investigated. US treatment with a frequency of 40 kHz and an acoustic energy density of 400 W/L at $40^{\circ}C$ for 3 min showed the maximum reduction of 2.87 log CFU/g B. cereus on carrot, while combined treatment of US (400 W/L, $40^{\circ}C$, 3 min) with SAcEW reached to 3.1 log CFU/g reduction. Growth data of B. cereus on carrot treated with SAcEW and US at different temperatures (4, 10, 15, 20, 25, 30, and $35^{\circ}C$) were collected and used to develop predictive models. The modified Gompertz model was found to be more suitable to describe the growth data. The specific growth rate (SGR) and lag time (LT) obtained from the modified Gompertz model were employed to establish the secondary models. The newly developed secondary models were validated using the root mean square error, bias factor, and accuracy factor. All results of these factors were in the acceptable range of values. After compared SGR and LT of B. cereus on carrot, the results showed that the growth of B. cereus on carrot treated with SAcEW and US was slower than that of single treatment. This result indicates that shelf life of carrot treated with SAcEW and US could be extended. The developed predictive models might also be used to assess the microbiological risk of B. cereus infection in carrot treated with SAcEW and US.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.23-43
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• 2014

We study the dependence between the insureds in multiple-life insurance contracts. With the future lifetimes of the insureds modeled as correlated random variables, both premium and reserve are different from those under independence. In this paper, Gaussian copula is used to impose the dependence between the insureds with Gompertz marginals. We analyze the change of the reserves of standard multiple-life insurance contracts at various dependence levels. We find that the reserves based on the assumption of dependent lifetimes are quite different for some contracts from those under independence as its correlation increase, which elucidate the importance of the dependence model in multiple-life contingencies in both theory and practice.

• Journal of Korean Society for Quality Management
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• v.22 no.2
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• pp.51-68
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• 1994

Various growth models were each fitted onto the data sets in an attempt to determine which growth models achieved the best forecasts for differing types of growth data. Of six such models studied, some models do significantly better than others in predicting future levels of growth. It is recommened that Weibull and the Gompertz growth curve be considered along with Pearl model by those industries presently considering the implementation of substitution analysis in their life analysis. In the early stage of growth, linear estimation should suffice to give reasonable forecasts. In the latter stage, however, as more data become availavle, nonlinear estimation should be used.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.105-107
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• 2012

This study was conducted to investigate the strength development of fly ash concrete using the strength development estimation for the ready mixed concrete for construction of nuclear reactors. The findings are as follows. First, the higher the curing temperature becomes, the shorter the setting time becomes. In addition, the compressive strength also increased as the curing temperature gets higher. The apparent activation energy derived from ASTM C 1074 showed 34.75 KJ/mol. The results of concrete strength estimation confirmed that Gompertz model formula has good accuracy.

• Food Science and Biotechnology
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• v.15 no.5
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• pp.715-720
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• 2006

This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of $R^2{\geq}0.9192$. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ($R^2\;=\;0.97$ for SGR and $R^2\;=\;0.86$ for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor ($B_f$ was 0.6 for SGR and 0.97 for LT).

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.349-371
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• 2022

Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

• Journal of Korean Society of Forest Science
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• v.94 no.2 s.159
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• pp.121-126
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• 2005

This study was carried out to construct a single diameter and a single height model that could localize Chamaecyparis obtusa stand grown in 3 Southern regions of Korea. Dummy variables, which convert qualitative information such as geographical regions into quantitative information by means of a coding scheme (0 or 1), were used to localize growth models. In results, modified form of Gompertz equation, $Y_2={\exp}({\ln}(Y_1){\exp}(-{\beta}(T_2-T_1)+{\gamma}({T_2}^2-{T_1}^2))+({\alpha}+{\alpha}_1Al+{\beta}_1k_1+{\beta}_2k_2)(1-{\exp}(-{\beta}(T_2-T_1)+{\gamma}({T_2}^2-{T_1}^2))$, for diameter and height was successfully disaggregated to provide different projection equation for each of the 3 regions individually. The use of dummy variables on a single equation, therefore, provides potential capabilities for testing the justification of having different models for different sub-populations, where a number of site variables such as altitude, annual rainfall and soil type can be considered as possible variables to explain growth variation across regions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.2
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• pp.111-118
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• 2020

Recently, bioenergy research using microalgae, one of the most promising biofuel sources, has attracted much attention. Cell disruption, which can be classified as physical or chemical, is essential to extract functional ingredients from microalgae. In this study, we investigated the cell disruption efficiency of Chlorella sp. using low-frequency non-focused ultrasound (LFNFU). This is a continuously physical method that is superior to chemical methods with respect to environmental friendliness and low processing cost. A flat panel photobioreactor was employed to cultivate Chlorella sp. and its growth curve was fitted both with Logistic and Gompertz models. The temporal change in cell reduction by cell disruption using LFNFU was fitted with a Logistic model. The experimental conditions that were investigated were the initial concentration of microalgal cells, relative amplitude of output ultrasound waves, processing volume of microalgal cells, and initial pH value. The optimal conditions for the most efficient cell disruption were determined through the various tests.