• Food Science and Biotechnology
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• v.14 no.1
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• pp.42-45
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• 2005

The present study was carried out to envisage the aerobic growth of Listeria monocytogenes and Yersinia enterocolitica on pork, which is one of the major meat sources in Korea. The results were compared with the previously developed predictive model systems for the verification of microbial growth in a real situation during pork processing. Pork loin samples (8.0 g, 5 mm thick) were aseptically prepared and inoculated with each pathogen by immersing into the respective inoculums for one min. Each of the samples were then wrapped with PE film and stored at 5, 10, and $15^{\circ}C$ up to 36 days to measure the growth profile of the respective pathogens. The growth parameters were calculated by using Gompertz equation and were compared with the previously reported data. The predicted generation time (GT) of L. monocytogenes at 5, 10 and $15^{\circ}C$ was 28.74, 7.85 and 4.02 hr, respectively, and for Y. enterocolitica was 10.29, 4.74 and 2.50 hr, at the same temperatures respectively. In this study, the GT values predicted on pork were slightly higher than the values predicted in other studies using liquid model systems. Unlike previous reports, both the pathogens were found to grow at $5^{\circ}C$ on pork. This finding recommends the necessity of controlling the growth of both the pathogens during the slaughtering process and distribution.

• Parasites, Hosts and Diseases
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• v.45 no.4
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• pp.273-282
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• 2007

In acute uncomplicated falciparum malaria, there is a continuum from mild to severe malaria. However, no mathematical system is available to predict uncomplicated falciparum malaria patients turning to severe malaria. This study aimed to devise a simple and reliable model of Malaria Severity Prognostic Score (MSPS). The study was performed in adult patients with acute uncomplicated falciparum malaria admitted to the Bangkok Hospital for Tropical Diseases between 2000 and 2005. Total 38 initial clinical parameters were identified to predict the usual recovery or deterioration to severe malaria. The stepwise multiple discriminant analysis was performed to get a linear discriminant equation. The results showed that 4.3% of study patients turned to severe malaria. The MSPS = 4.38 (schizontemia) + 1.62 (gametocytemia) + 1.17 (dehydration) + 0.14 (overweight by body mass index; BMI) + 0.05 (initial pulse rate) + 0.04 (duration of fever before admission)-0.50 (past history of malaria in last 1 year). 0.48 (initial serum albumin)-5.66. Based on the validation study in other malaria patients, the sensitivity and specificity were 88.8% and 88.4%, respectively. We conclude that the MSPS is a simple screening tool for predicting uncomplicated falciparum malaria patients turning to severe malaria. However, the MSPS may need revalidation indifferent geographical areas before utilized at specific places.

• Nutrition Research and Practice
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• v.15 no.1
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• pp.95-105
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• 2021

BACKGROUND/OBJECTIVES: The measurement of body composition, including muscle and fat mass, remains challenging in large epidemiological studies due to time constraint and cost when using accurate modalities. Therefore, this study aimed to develop and validate prediction equations according to sex to measure lean body mass (LBM), appendicular skeletal muscle mass (ASM), and body fat mass (BFM) using anthropometric measurement, serum creatinine level, and lifestyle factors as independent variables and dual-energy X-ray absorptiometry as the reference method. SUBJECTS/METHODS: A sample of the Korean general adult population (men: 7,599; women: 10,009) from the Korean National Health and Nutrition Examination Survey 2008-2011 was included in this study. The participants were divided into the derivation and validation groups via a random number generator (with a ratio of 70:30). The prediction equations were developed using a series of multivariable linear regressions and validated using the Bland-Altman plot and intraclass correlation coefficient (ICC). RESULTS: The initial and practical equations that included age, height, weight, and waist circumference had a different predictive ability for LBM (men: R2 = 0.85, standard error of estimate [SEE] = 2.7 kg; women: R2 = 0.78, SEE = 2.2 kg), ASM (men: R2 = 0.81, SEE = 1.6 kg; women: R2 = 0.71, SEE = 1.2 kg), and BFM (men: R2 = 0.74, SEE = 2.7 kg; women: R2 = 0.83, SEE = 2.2 kg) according to sex. Compared with the first prediction equation, the addition of other factors, including serum creatinine level, physical activity, smoking status, and alcohol use, resulted in an R2 that is higher by 0.01 and SEE that is lower by 0.1. CONCLUSIONS: All equations had low bias, moderate agreement based on the Bland-Altman plot, and high ICC, and this result showed that these equations can be further applied to other epidemiologic studies.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.205-219
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• 2021

The present study identified determinants to user acceptance of artificial intelligence(AI)-based news anchor. Our conceptual model included three constructs of ability, benevolence, and integrity to determine whether these three constructs are predictive of trust perceived from AI news anchor. This work further examined the influences of social presence, anthropomorphism, perceived usefulness, understanding as well as trust as immediate determinants to user acceptance. The conceptual model was validated on survey data collected from 513 respondents. A series of scale refinement process was conducted by the examination of data normality, common method bias, structure of latent variables as well as internal consistency. In addition, a confirmatory factor analysis was performed to assess the extent to which the sample data collected from survey study measures the constructs adequately. The results from the analysis of structural equation model indicated that, (1) two constructs of ability and integrity were found to be significantly predictive of perceived trust, and (2) anthropomorphism, perceived usefulness, and trust emerged as significant and positive predictors of user acceptance of AI-based news anchor.

• Journal of Korean Academy of Nursing
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• v.52 no.2
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• pp.157-172
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• 2022

Purpose: This study aimed to construct and test a hypothetical model to explain the predictive factors and causal pathways for exercise levels in patients with ankylosing spondylitis based on the self-determination theory. A conceptual framework was constructed assuming that autonomy support by health care providers would satisfy the three basic psychological needs of patients, which would increase their autonomous motivation for exercise, resulting in its initiation and continuation. Methods: This cross-sectional study included 221 patients with ankylosing spondylitis who were visiting rheumatology clinics in two tertiary hospitals. Health Care Climate Questionnaire-exercise regularly, Basic Psychological Needs Satisfaction scale, Behavior Regulation in Exercise Questionnaire-2, and exercise level were used to collect data. Results: The fitness of the hypothetical model met the recommended level (𝛘²/df ≤ 3, SRMR ≤ .08, RMSEA ≤ .08, GFI ≥ .90, AGFI ≥ .85, NFI ≥ .90, TLI ≥ .90, CFI ≥ .90). The model effect analysis revealed that autonomy support by health care providers had a positive effect on patients' autonomy, competence, relatedness, autonomous motivation, and exercise level. Competence and relatedness had positive effects on autonomous motivation and exercise level, respectively. Autonomous motivation had a positive effect on exercise level. Conclusion: The predictive factors of exercise level in patients with ankylosing spondylitis were autonomous motivation, health care providers' autonomy support, competence, and relatedness. Considering these factors, we recommend the development of an effective program for improving exercise levels in these patients.

• Journal of Korean Academy of Nursing
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• v.52 no.3
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• pp.308-323
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• 2022

Purpose: This study aimed to construct and test a predictive model for the quality of life (QOL) in mothers of children with developmental disabilities (DB). The hypothesized model included severity of illness, distress, uncertainty, self-help, and parenting efficacy as influencing factors, QOL as a consequence based on the Braden's Self-Help Model. Methods: The data were collected through a direct and online surveys from 206 mothers in 8 locations, including welfare or daycare centers, developmental treatment centers, and The Parents' Coalition for the Disabled located in two provinces of Korea. Data were analysed using SPSS/WIN 23.0 and AMOS 21.0 program. Results: The fit indices of the predictive model satisfied recommended levels; 𝛘² = 165.79 (p < .001), normed 𝛘² (𝛘²/df) = 2.44, RMR = .04, RMSEA = .08, GFI = .90, AGFI = .85, NFI = .91, TLI = .93, CFI = .95. Among the variables, distress (β = - .46, p < .001), parenting efficacy (β = .22, p < .001), and self-help (β = .17, p = .018) had direct effects on QOL. Severity of illness (β = - .61, p = .010) and uncertainty (β = - .08, p = .014) showed indirect effects. The explanatory power of variables was 61.0%. Conclusion: The study results confirm the utility of Braden's Self-Help Model. They provide a theoretical basis for improving QOL in mothers of children with DB. Nursing intervention strategies that can relieve mothers' distress and uncertainty related to disease and enhance parenting efficacy and self-help behavior should be considered.

• Explosives and Blasting
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• v.18 no.2
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• pp.7-13
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• 2000

Abstract The characteristics of bed rock in the study area was classified by means of the crack coefficient estimated from the seismic velocities of in-situ and intact rocks. Various statistical methods were investigated in order to minimize the possible errors in estimating the predictive equation of blasting vibration and to enhance the determination coefficient $R^2$, for more reliable estimation. The determination coefficient showed the highest in the analysis for those groups using weighting function with the number of samples. The analysis for the weighting function employed with standard coefficient and variance also enhanced the determination coefficients significantly compared to the others, but the reliability was slightly lower than results obtained former method. Therefore the most reliable predictive equation of blasting vibration was found to be obtained from a regression analysis of the mean vibration level using the weighting of same distance groups within 15m with the same explosive charge weight per delay. The coefficients, K and n 317.4 and -1.66, respectively, when using the square root scaling, and 209.9 and -1.66, respectively, when using the cube root scaling. The analysis also showed that the square root scaling may be used in the distance less than 31m form the blast source, and the cube root scaling in the distance more than 31m for safe design.

• 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 for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.445-455
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• 2010

In order to effectively predict thermo-acoustic instability within real combustors of rocket engines and gas turbines, in the present study, the Helmholtz equation in conjunction with the time lag hypothesis is discretized by the finite element method on three-dimensional hybrid unstructured mesh. Numerical nonlinearity caused by the combustion response term is linearized by an iterative method, and the large-scale eigenvalue problem is solved by the Arnoldi method available in the ARPACK. As a consequence, the final solution of complex valued eigenfrequency and acoustic pressure field can be interpreted as resonant frequency, growth rate, and modal shape for acoustic modes of interest. The predictive capabilities of the present method have been validated against two academic problems with complex impedance boundary and premixed flame, as well as an ambient acoustic test for liquid rocket combustion chamber with/without baffle.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.3
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• pp.118-123
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• 2017

This study investigated the feasibility of a statistical approach for the prediction of BaP and total PAHs as pyrogenic sources. As results of regression, excellent linear and multiple correlations ($r^2$ > 0.94) were observed between BaP (or ${\Sigma}PAH$) and Pyr concentrations. When a developed prediction equation was applied to other investigations as validation and application studies, outstanding prediction results were obtained. The predictive model showed very good correlation between the measured and calculated ${\Sigma}PAH$. From this equation, Pyr was an apparently important hydrocarbon for the prediction of PAH. This model might provide a potentially useful tool for the calculation of average BaP and ${\Sigma}PAH$ in a certain region without additional tests.