• Journal of Food Hygiene and Safety
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• v.26 no.1
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• pp.25-30
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• 2011

In this study, predictive mathematical models were developed to predict the kinetics of Listeria monocytogenes growth in the mixed fresh-cut vegetables, which is the most popular ready-to-eat food in the world, as a function of temperature (4, 10, 20 and $30^{\circ}C$). At the specified storage temperatures, the primary growth curve fit well ($r^2$=0.916~0.981) with a Gompertz and Baranyi equation to determine the specific growth rate (SGR). The Polynomial model for natural logarithm transformation of the SGR as a function of temperature was obtained by nonlinear regression (Prism, version 4.0, GraphPad Software). As the storage temperature decreased from $30^{\circ}C$ to $4^{\circ}C$, the SGR decreased, respectively. Polynomial model was identified as appropriate secondary model for SGR on the basis of most statistical indices such as mean square error (MSE=0.002718 by Gompertz, 0.055186 by Baranyi), bias factor (Bf=1.050084 by Gompertz, 1.931472 by Baranyi) and accuracy factor (Af=1.160767 by Gompertz, 2.137181 by Baranyi). Results indicate L. monocytogenes growth was affected by temperature mainly, and equation was developed by Gompertz model (-0.1606+$0.0574^*Temp$+$0.0009^*Temp^*Temp$) was more effective than equation was developed by Baranyi model (0.3502-$0.0496^*Temp$+$0.0022^*Temp^*Temp$) for specific growth rate prediction of L.monocytogenes in the mixed fresh-cut vegetables.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.111-120
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• 2010

The policy which encourages people to use cars on the road has been based on the growth of economy in Korea. It has also caused the concentration and overcrowding in Seoul. That's because the increasing number of people possessing cars interconnects with the urban development. The transportation is a derived demand; so many scholars have recognized the importance of understanding the relationship between urban land use and transport. Considering such importance, this study theoretically compared the developed urban land use-transportation models each other and outlined the particular models briefly. Models were categorized by 2 types; optimizing model and predictive mode. Predictive model is also defined by static model, entropy based model, spatial-economic model, and activity model. After studying models, we investigated other major cities in America. This process is the pre-step for transport policy assessment. Through careful literature review, we can finally develop the integrated land-use transportation model in Seoul metropolitan area. In addition, we will be able to deal the changes of traffic demand pattern under U-Society. Consequently, the results of this study can be applied to ITS projects in the future.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.11
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• pp.1618-1624
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• 2009

This study was conducted to estimate the shelf-life of cooked mung bean sprouts contaminated with Staphylococcus aureus according to storage temperatures after cooking in school foodservice operations. A predictive growth model of S. aureus in cooked mung bean sprouts prepared using a standard recipe was developed at 4 storage temperatures (5, 15, 25, and 35${^{\circ}C}$). To determine the effect of vinegar on the shelf-life of cooked mung bean sprouts, the growth of S. aureus in sprouts prepared using vinegar and the standard recipe were compared. The $R^2$ values of the specific growth rate (SGR) and lag time (LT) determined using the Gompertz model were greater than 0.90 at all temperatures except 5${^{\circ}C}$, which confirmed that it would be appropriate to use these parameters for a secondary model. The secondary model, which indicates changes in LT and SGR values according to storage temperatures, was calculated using response surface models. The compatibility of the developed model was confirmed by calculating $R^2$, Bf, Af and MSE values as statistic parameters. The $R^2$ values of LT and SGR were 0.94 or higher, and the MSE, Bf and Af values were 0.02 and 0.002, 0.97 and 1.03, and 1.31 and 1.10, respectively, with high statistical compatibility. The growth rate of S. aureus was higher when the standard recipe was used than when vinegar was used at all temperatures. Indeed, no growth of S. aureus was observed in mung bean sprouts prepared using vinegar. Based on the model developed, cooked mung bean sprouts prepared using the standard recipe for school foodservice should be stored at 10${^{\circ}C}$ or less. Additionally, sprouts stored at 25 or 35${^{\circ}C}$ should be consumed within 6 or 12 hours after cooking. Finally, the addition of vinegar will prevent the growth of S. aureus in cooked mung bean sprouts.

• 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.

• Korean Journal of Agricultural Science
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• v.49 no.1
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• pp.61-75
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• 2022

The first purpose of this study is to evaluate the usefulness of pork traceability data, which is monthly time-series data, and to draw implications with regard to its usefulness. The second purpose is to construct a dynamic ecological equation model (DEEM) that reflects the biological characteristics at each growth stage, such as pregnancy, birth and growth, and the slaughter of pigs, using traceability data. With the monthly pig model devised in this study, it is expected that the number of slaughtered animals (supply) that can be shipped in the future is predictable and that policy simulations are possible. However, this study was limited to traceability data and focused only on building a supply-side model. As a result of verifying the traceability data, it was found that approximately 6% of farms produce by mixing great grand parent (GGP), grand parent (GP), parent stock (PS), and artificial insemination (AI), meaning that it is necessary to separate them by business type. However, the analysis also showed that the coefficient values estimated by constructing an equation for each growth stage were consistent with the pig growth outcomes. Also, the model predictive power test was excellent. For this reason, it is judged that the model design and traceability data constructed with the cohort and the dynamic ecological equation model system considering biological growth and shipment times are excellent. Finally, the model constructed in this study is expected to be used as basic data to inform producers in their decision-making activities and to help with governmental policy directions with regard to supply and demand. Research on the demand side is left for future researchers.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.7
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• pp.1013-1018
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• 2014

In this study, we developed kinetic models to predict the growth of pathogenic Escherichia coli on cheeses during storage at constant and changing temperatures. A five-strain mixture of pathogenic E. coli was inoculated onto natural cheeses (Brie and Camembert) and processed cheeses (sliced Mozzarella and sliced Cheddar) at 3 to 4 log CFU/g. The inoculated cheeses were stored at 4, 10, 15, 25, and $30^{\circ}C$ for 1 to 320 h, with a different storage time being used for each temperature. Total bacteria and E. coli cells were enumerated on tryptic soy agar and MacConkey sorbitol agar, respectively. E. coli growth data were fitted to the Baranyi model to calculate the maximum specific growth rate (${\mu}_{max}$; log CFU/g/h), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The kinetic parameters were then analyzed as a function of storage temperature, using the square root model, polynomial equation, and linear equation. A dynamic model was also developed for varying temperature. The model performance was evaluated against observed data, and the root mean square error (RMSE) was calculated. At $4^{\circ}C$, E. coli cell growth was not observed on any cheese. However, E. coli growth was observed at $10{\circ}C$ to $30^{\circ}C$C with a ${\mu}_{max}$ of 0.01 to 1.03 log CFU/g/h, depending on the cheese. The ${\mu}_{max}$ values increased as temperature increased, while LPD values decreased, and ${\mu}_{max}$ and LPD values were different among the four types of cheese. The developed models showed adequate performance (RMSE = 0.176-0.337), indicating that these models should be useful for describing the growth kinetics of E. coli on various cheeses.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.39-43
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• 2010

The main objective of this research is to develop a mechanistic performance predictive model for fatigue cracking of asphalt-aggregate mixtures. Controlled-stress diametral fatigue tests were performed to characterize fatigue cracking of asphalt-aggregate mixtures. Performance prediction model for fatigue cracking was developed using the internal damage ratio (IDR) growth method. In the IDR growth method, the general concepts of the dissipated energy, the reference tensile strain, the threshold tensile strain, and the strain shift factor were introduced. The source of the dissipated energy in the fatigue test is from the intrinsic viscoelastic material property of an asphalt concrete mixture and the damage growth within the asphalt concrete specimen. In controlled-stress mode test, the dissipated energy is gradually increased with an increasing number of load applications.

• 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.

• Journal of Food Hygiene and Safety
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• v.35 no.5
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• pp.495-502
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• 2020

Processing fresh produce into fresh-cut products increases the risk of bacterial growth and contamination by breaking the exterior barrier of produce. Our objective in this study was to develop predictive models of Listeria monocytogenes in the fresh-cut salad, fresh-cut pineapple, and frozen mango. Predictive growth and survival models were developed to predict the change of L. monocytogenes populations in the fresh-cut salad (4, 10, 12, 13, 17, 25, and 36℃), fresh-cut pineapple (4, 10, 17, 25, 30, and 36℃), and frozen mango (-2, -10 and -18℃) as a function of temperature. The growth of L. monocytogenes in fresh-cut salad and pineapple was observed at above 13℃ and 10℃, respectively. The growth of L. monocytogenes in pineapple was faster than in salad. The delta value of L. monocytogenes in frozen mango increased as the storage temperature decreased. The results indicate that L. monocytogenes behave differently according to the physicochemical properties of fresh-cut fruits and vegetables. Since L. monocytogenes grow and survive well in refrigerated and frozen conditions, management programs and preventive controls for the processing of fresh-cut produce should be effectively implemented to enhance the safety of fresh-cut fruits and vegetables at retail markets.

• Women's Health Nursing
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• v.28 no.2
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• pp.123-133
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• 2022

Purpose: This study investigated the trajectory of subjective health status in married postmenopausal women and aimed to identify predictive factors affecting subjective health status. Methods: Data were obtained from women who participated in wave 4 (2012) of the Korean Longitudinal Survey of Women & Families Longitudinal Study and continued to the latest phase (wave 7, 2018). A latent growth model (LGM) was used to analyze data from 1,719 married postmenopausal women in the framework of the ecological system theory. Results: The mean age of the participants at wave 4 was 56.39±4.71 years, and the average subjective health status was around the midpoint (3.19±0.84). LGM analysis confirmed that subjective health status decreased over time (initial B=3.21, slope B=-0.03). The factors affecting initial subjective health were age, body mass index, frequency of vigorous physical activity (microsystem level), marital satisfaction (mesosystem level), and medical service utilization (macrosystem level). Medical service utilization and the frequency of vigorous physical activity were identified as predictive factors affecting the slope in subjective health status. The model fit was satisfactory (TLI=.92, CFI=.95, and RMSEA=.04). Conclusion: This analysis of the trajectory of subjective health status of married postmenopausal women over time confirmed that subjective health is influenced by overall ecological system factors, including the microsystem, mesosystem, exosystem, macrosystem, and chronosystem. Therefore, it is necessary to assess physical activity and support policies promoting access to medical services in order to improve the subjective health status of married postmenopausal women.