• Journal of Information Science Theory and Practice
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• v.3 no.3
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• pp.45-63
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• 2015

The word ‘growth’ represents an increase in actual size, implying a change of state. In science and technology, growth may imply an increase in number of institutions, scientists, or publications, etc. The present study demonstrates the growth of neurology literature for the period 1961-2010. A total of 291,702 records were extracted from the Science Direct Database for fifty years. The Relative Growth Rate (RGR) and Doubling Time (Dt.) of neurology literature have been calculated, supplementing with different growth patterns to check whether neurology literature fits exponential, linear, or logistic models. The results of the study indicate that the growth of literature in neurology does not follow the linear, or logistic growth model. However, it follows closely the exponential growth model. The study concludes that there has been a consistent trend towards increased growth of literature in the field of neurology.

• Korean Journal of Food Science and Technology
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• v.36 no.2
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• pp.349-354
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• 2004

Predictive growth model of Vibrio parahaemolyticus in modified surimi-based imitation crab broth was investigated. Growth curves of V. parahaemolyticus were obtained by measuring cell concentration in culture broth under different conditions ($Initial\;cell\;level,\;1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}\;colony\;forming\;unit\;(CFU)/mL$; temperature, 15, 25 37, and $40^{\circ}C$; pH 6, 7, and 8) and applying them to Gompertz model. Microbial growth indicators, maximum specific growth rate (k), lag time (LT), and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of V. parahaemolyticus increased with increasing temperature, reaching maximum rate at $37^{\circ}C$. LT and GT were also the shortest at $37^{\circ}C$. pH and initial cell number did not influence k, LT, and GT values significantly (p>0.05). Polynomial model, $k=a{\cdot}\exp(-0.5{\cdot}((T-T_{max}/b)^{2}+((pH-pH_{max)/c^{2}))$, and square root model, ${\sqrt{k}\;0.06(T-9.55)[1-\exp(0.07(T-49.98))]$, were developed to express combination effects of temperature and pH under each initial cell number using Gauss-Newton Algorism of Sigma plot 7.0 (SPSS Inc.). Relative coefficients between experimental k and k Predicted by polynomial model were 0.966, 0.979, and 0.965, respectively, at initial cell numbers of $1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}CFU/mL$, while that between experimental k and k Predicted by square root model was 0.977. Results revealed growth of V. parahaemolyticus was mainly affected by temperature, and square root model showing effect of temperature was more credible than polynomial model for prediction of V. parahaemolyticus growth.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.4
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• pp.67-77
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• 2002

This paper introduces the calibration results of the fatigue crack growth models for damage tolerance analysis of the aircraft structures. Generalized Willenborg model and Wheeler model are calibrated with experimental data tested under the load spectrum of a trainer. The retardation factors such as, shut-off ratio in Generalized Willenborg model and shaping exponent in Wheeler model, are evaluated for aluminum alloys AL2024-T3511, AL7050-T7451 and AL7075-T73511. It is shown that the retardation effect of the crack growth rate depends on the yield strength of material and the maximum stress in the load spectrum. Generalized Willenborg model and Wheeler model give satisfactory prediction of crack growth life but the calibration of the experimental parameters with test is required.

• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1012-1017
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• 2005

Predictive growth model of putrefactive bacteria of surimi-based imitation crab in the modified surimi-based imitation crab (MIC) broth was investigated. The growth curves of putrefactive bacteria were obtained by measuring cell number in MIC broth under different conditions (Initial cell number, $1.0{\times}10^2,\;1.0{\times}10^3$ and $1.0{\times}10^4$ colony forming unit (CFU)/mL; temperature, $15^{\circ}C,\;20^{\circ}C\;and\;25^{\circ}C$) and applied them to Gompertz model. The microbial growth indicators, maximum specific growth rate constant (k), lag time (LT) and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of putrefactive bacteria was become fast with rising temperature and fastest at $25^{\circ}C$. LT and GT were become short with rising temperature and shortest at $25^{\circ}C$. There were not significant differences in k, LT and GT by initial cell number (p>0.05). Polynomial model, $k=-0.2160+0.0241T-0.0199A_0$, and square root model, $\sqrt{k}=0.02669$ (T-3.5689), were developed to express the combination effects of temperature and initial cell number, The relative coefficient of experimental k and predicted k of polynomial model was 0.87 from response surface model. The relative coefficient of experimental k and predicted k of square root model was 0.88. From above results, we found that the growth of putrefactive bacteria was mainly affected by temperature and the square root model was more credible than the polynomial model for the prediction of the growth of putrefactive bacteria.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.4
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• pp.17-23
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• 1984

A model analysis of pattern shift in the epitaxial growth of silicon on (111) substrates was performed. The growth rate anisotropy was considered as the most important affecting factor of pattern shift, and for the model establishment the off angle of the substrate and the process temperature were taken as the variables. We derived a theoretical equation of pattern shift by assuming the growth rate anisotropy as the trigonometric sine function of the off angle of the substrate and defining the growth rate anisotropy factor related to the process temperature. The pattern shift ratio calculated by this model had the same tendency with the experimental ones, which, however, were about twice greater than those. It was supposed that this discrepailcy was due to the second order affecting factor such as facetting and step broadening which had been exluded in model establishment.

• Journal of Korean Society for Quality Management
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• v.44 no.3
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• pp.565-574
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• 2016

Purpose: In this study, A reliability assurance model (or reliability program) is proposed to evaluate the reliability of an armed vehicle. The reliability assurance is performed through the reliability-centered activities in the K-000(armed vehicle) of D-Company Methods: By reflecting the current situations of korea defense industry, a reliability assurance model is built up based on the benchmarking results of world leading companies' best practices in same fields. So The reliability growth model is applied the Crow-AMSAA model Results: This research analysis the K-000(armed vehicle) of D-Company using the DT and OT failure data. and application case study by growth model of armed vehicles Conclusion: This research is result of application case study by growth model of armed vehicles.

• Biotechnology and Bioprocess Engineering:BBE
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• v.5 no.5
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• pp.382-385
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• 2000

A mathematical model was developed, based on the time dependent changes of the specific growth rate, for prediction of the typical microbial cell growth in batch cultures. This model could predict both the lag growth phase and the stationary growth phase of batch cultures, and it was tested with the batch growth of Trichoderma reesei and Lactobacillus delbrueckii.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.566-574
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• 2021

The process of cavitation involves generation, growth, coalescence, and collapse of small bubbles and is tremendously influenced by bubble-bubble interactions. To understand these interactions, a new cavitation model based on the transport equation is proposed herein. The modified Rayleigh-Plesset equation is analyzed to determine the bubble growth rate by assuming equal-sized spherical bubble clouds. The source term in the transport equation is then derived according to the bubble growth rate with the bubble-bubble interaction. The proposed model is validated by various test simulations, including microscopic bubble cloud evolution as well as macroscopical two- and three-dimensional cavitating flows. Compared with previous models, namely the Kunz and Zwart cavitation models, the newly proposed model does not require adjustable parameters and generally results in better predictions both microscopic and macroscopical cases. This model is more physical.

• Korean System Dynamics Review
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• v.10 no.1
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• pp.5-32
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• 2009

This paper revisited the key advances on System Dynamics modeling about traditional macro-economic models and economic growth structures, and then tries to elaborate a new model based on the endogenous growth theory that incorporates new growth factors, relevant to knowledge/technology as well as the Environment, into traditional growth models. Accordingly, the new model augments the acceleration and multiplier loops and the balancing ones representing market clearing mechanism with a simple numerical example. The authors thus provides macroeconomic System Dynamics analysts with a milestone to model macro-economic structures reflecting on traditional and cutting-edge theories on sustainable economic growth and general equilibrium modeling.

• Korean Journal of Food Science and Technology
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• v.37 no.2
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• pp.194-198
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• 2005

Growth curves of Listeria monocytogenes in modified surimi-based imitation crab (MIC) broth were obtained by measuring cell concentration in MIC broth at different culture conditions [initial cell numbers, $1.0{\times}10^{2},\;1.0{\times}10^{3}\;and\;1.0{\times}10^{4}$, colony forming unit (CFU)/mL; temperature, 15, 20, 25, 37, and $40^{\circ}C$] and applied to Gompertz model to determine microbial growth indicators, maximum specific growth rate constant (k), lag time (LT), and generation time (GT). Maximum specific growth rate of L. monocytogenes increased rapidly with increasing temperature and reached maximum at $37^{\circ}C$, whereas LT and GT decreased with increasing temperature and reached minimum at $37^{\circ}C$. Initial cell number had no effect on k, LT, and GT (p > 0.05). Polynomial and square root models were developed to express combined effects of temperature and initial cell number using Gauss-Newton Algorism. Relative coefficients of experimental k and predicted k of polynomial and square root models were 0.92 and 0.95, respectively, based on response surface model. Results indicate L. monocytogenes growth was mainly affected by temperature and square root model was more effective than polynomial model for growth prediction.