• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.3
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• pp.202-208
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• 2001

Under the constant daylength of 13 hours and growth temperatures of 15$^{\circ}C$ to 27$^{\circ}C$, the final number of loaves (FNL) on the main culm was constant as 15 regardless of temperature in rice variety 'Kwanganbyeo'. Leaf appearance rate (LAR) increased with rising temperature and decreased with phenological development. Threshold temperature (T$_{o}$) was not constant across growth stages, but increased with phenological development. Effective accumulated temperature (EAT), which is calculated by the summation of values subtracting T0 from daily mean temperature, is closely related with number of leaves appeared (LA). LA was fitted to bilinear, quadratic, power and logistic function of EAT. Among the functions, logistic function had the best fitness of which coefficient of determination was $R^2$=0.995. Therefore, LAR prediction model was established by differentiating this function in terms of time: (equation omitted). where dL/dt is LAR, T$_1$ is daily mean temperature, L is the number of leaves appeared, and a, b, and c are constants that were estimated as 41.8, 1098.38, and -0.9273, respectively. When predictions of LA were made by LAR prediction model using data independent of model establishment, the observed and predicted LA showed good agreement of $R^2$$\geq$0.99.

• Journal of Environmental Health Sciences
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• v.42 no.1
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• pp.41-52
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• 2016

Objectives: Scrub typhus is one of the most prevalent vector-borne diseases. It is caused by Orientia tsutsugamushi, which is transmitted when people are bitten by infected chigger mites. This study aims at quantifying the association between the incidence of scrub typhus and meteorological factors in Jeollabuk-do Province over the period 2001-2015. Methods: Reported cases of scrub typhus were collected from the website of the Disease Web Statistical System supported by the Korea Centers for Disease Control and Prevention (KCDC). Simultaneous meteorological data, including temperature, rainfall, relative humidity, and sunshine duration were collected from the website of the National Climate Data Service System by the Korea Meteorological Administration. Correlation and regression analyses were applied to identify the association between the incidence of scrub typhus and meteorological factors. Results: The general epidemiological characteristics of scrub typhus in Jeollabuk-do Province were similar to those nationwide for sex, age, and geographical distribution. However, the annual incidence rate (i.e., cases per 100,000) of scrub typhus in Jeollabuk-do Province was approximately four times higher than all Korea's 0.9. The number of total cases was the highest proportion at 13.3% in Jeonbuk compared to other regions in Korea. The results of correlation analysis showed that there were significant correlations between annual cases of scrub typhus and monthly data for meteorological factors such as temperature and relative humidity in late spring and summer, especially in the case of temperature in May and June. The results of regression analysis showed that determining factors in the regression equation explaining the incidence of scrub typhus reached 46.2% and 43.5% in May and June. Using the regression equation, each 1oC rise in the monthly mean temperature in May or June may lead to an increase of 38 patients with scrub typhus compared to the annual mean of incidence cases in Jeollabuk-do Province. Conclusion: The result of our novel attempts provided rational evidence that meteorological factors are associated with the occurrence of scrub typhus in Jeollabuk-do. It should therefore be necessary to observe the trends and predict patterns of scrub typhus transmission in relation to global-scale climate change. Also, action is urgently needed in all areas, especially critical regions, toward taking steps to come up with preventive measures against scrub typhus transmission.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.6 no.1
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• pp.40-50
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• 1994

For an accurate prediction of the temperature field induced by heated water discharged into a shallow crossflow, a two-dimensional near-field numerical model is developed. It is based on a 4-equation turbulence model in which the transport equations for mean of the temperature fluctuation squared and its dissipation rate are added to those of a 2-equation turbulence model which cannot give the information of the thermal time scale ratio. Vertical diffusion is also considered by including buoyancy production and turbulence heat flux terms. The developed model is applied to a steady flow in an open channel with simple geometry and the results are compared with existing experimental data and those of the already established 2-equation turbulence model. Numerical results of the model agree with the experimental data better than those of the 2-equation model. The present model also simulates quite adequately the physical characteristics of thermal discharge in the jet entrainment and stable regions.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1376-1381
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• 2004

Understanding the thermal conductivity and heat transfer processes in superlattice structures is critical for the development of thermoelectric materials and optoelectronic devices based on quantum structures. $Chen^{(1)}$ developed ballistic diffusive equation(BDE) for alternatives of the Boltzmann equation that can be applied to the complex geometrical situation. In this study, a simulation code based on BDE is developed and applied to the 1-dimensional transient heat conduction across a thin film and transient 2-dimensional heat conduction across the film with heater. The obtained results are compared to the results of the $Chen^{(1)}$ and Yang and $Chen^{(1)}$. Finally, steady 2-dimensional heat conduction in the quantum dot superlattice are solved to obtain the equivalent thermal conductivity of the lattice and also compared with the experimental data from $Borca-Tasciuc^{(2)}$.

• 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.

• Food Science and Biotechnology
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• v.16 no.2
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• pp.238-242
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• 2007

Square root models were developed for predicting the kinetics of growth of Listeria monocytogenes in sesame leaves as a function of temperature (4, 10, or $25^{\circ}C$). At these storage temperatures, the primary growth curves fit well ($R^2=0.898$ to 0.980) to a Gompertz equation to obtain lag time (LT) and specific growth rate (SGR). The square root models for natural logarithm transformations of the LT and SGR as a function of temperature were obtained by SAS's regression analysis. As storage temperature ($4-25^{\circ}C$) decreased, LT increased and SGR decreased, respectively. Square root models were identified as appropriate secondary models for LT and SGR on the basis of most statistical indices such as coefficient determination ($R^2=0.961$ for LT, 0.988 for SGR), mean square error (MSE=0.l97 for LT, 0.005 for SGR), and accuracy factor ($A_f=1.356$ for LT, 1.251 for SGR) although the model for LT was partially not appropriate as a secondary model due to the high value of bias factor ($B_f=1.572$). In general, our secondary model supported predictions of the effects of temperature on both LT and SGR for L. monocytogenes in sesame leaves.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.420-428
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• 2016

For more than 50 years, satellite images have been used to monitor crop growth. Currently, unmanned aerial vehicle (UAV) imagery is being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study refers to the derivation of growth estimating equation for highland Kimchi cabbage using UAV derived normalized difference vegetation index (NDVI) and agro-meteorological factors. Anbandeok area in Gangneung, Gangwon-do, Korea is one of main districts producing highland Kimchi cabbage. UAV imagery was taken in the Anbandeok ten times from early June to early September. Meanwhile, three plant growth parameters, plant height (P.H.), leaf length (L.L.) and outer leaf number (L.N.), were measured for about 40 plants (ten plants per plot) for each ground survey. Six agro-meteorological factors include average temperature; maximum temperature; minimum temperature; accumulated temperature; rainfall and irradiation during growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 93% of the P.H. and L.L. with a root mean square error (RMSE) of 2.22, 1.90 cm. And $NDVI_{UAV}$ and accumulated temperature in the model explain 86% of the L.N. with a RMSE of 4.29. These lead to the result that the characteristics of variations in highland Kimchi cabbage growth according to $NDVI_{UAV}$ and other agro-meteorological factors were well reflected in the model.

• International Journal of Industrial Entomology and Biomaterials
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• v.6 no.1
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• pp.21-25
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• 2003

The implications of temperature $(25, 30 and 35{\times}1^{\circ}C)$ and relative humidity $(60, 70 and 80{\times}2%)$ on the moulting pattern, moulting duration and moulting survival were studied in the silkworm, Bombyx mori L. Larvae of two pure silkworm breeds, Pure Mysore (PM) and NB$_4$D$_2$and their hybrid, $PM{\times}NB_{4} D_{2}$ were reared under experimental conditions under natural day photoperiodic (LD 12:12) condition. Two developmental marker events in the fourth moulting, settling for moult (SM) and completion of moult (CM) occurred at or around the middle of the photophase. The computed mean vector (equation omitted), based on the circular statistics also confirmed the above. Temperature and humidity did not alter the moulting rhythmicity much. However, extreme temperature and humidity conditions reduced moulting survival in PM and $PM {\times}NB_{4} D_{2}$. Further, moulting survival reduced below the economic level in $NB_{4} D_{2}$. The temperature and humidity together seem to exert synergic impact on the moulting survival of the silkworm Bombyx mori, at least in $NB_{4} D_{2}$.

• Journal of Magnetics
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• v.19 no.4
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• pp.315-322
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• 2014

In this work, Artificial Neural Network (ANN) was used to model the dynamic behavior of ferromagnetic hysteresis derived from performing the mean-field analysis on the Ising model. The effect of field parameters and system structure (via coordination number) on dynamic critical points was elucidated. The Ising magnetization equation was drawn from mean-field picture where the steady hysteresis loops were extracted, and series of the dynamic critical points for constructing dynamic phase-diagram were depicted. From the dynamic critical points, the field parameters and the coordination number were treated as inputs whereas the dynamic critical temperature was considered as the output of the ANN. The input-output datasets were divided into training, validating and testing datasets. The number of neurons in hidden layer was varied in structuring ANN network with highest accuracy. The network was then used to predict dynamic critical points of the untrained input. The predicted and the targeted outputs were found to match well over an extensive range even for systems with different structures and field parameters. This therefore confirms the ANN capabilities and indicates the ANN ability in modeling the ferromagnetic dynamic hysteresis behavior for establishing the dynamic-phase-diagram.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.2
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• pp.207-216
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• 1995

Flow and heat transfer characteristics of mixed convection heat transfer in a rectangular en-closure with various outlets are numerically investigated. The parameters considered here include Reynolds number, Grashof number and the position of outlet. The results show streamlines, isotherms, Nusselt numbers, velocity and temperature distributions. It has been shown that as Reynolds number increases, the size of cell decreases at Re$\leq$100 and increases at Re>100 for $Gr=10^4$. There is a minimum size of cells at Re=100, $Gr=10^4$. The maximum mean Nusselt number occurs at Re=400, $Gr=10^4$ and one right outlet. The mean Nusselt numbers can be formulated by the correlation equation $Nu=C{\cdot}Gr^a{\cdot}Re^b$.