• Journal of Biomedical Engineering Research
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• v.23 no.4
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• pp.269-279
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• 2002

When we inject a current into an electrically conducting subject such as a human body, voltage and current density distributions are formed inside the subject. The current density within the subject and injection current in the lead wires generate a magnetic field. This magnetic flux density within the subject distorts phase of spin-echo magnetic resonance images. In Magnetic Resonance Current Density Imaging (MRCDI) technique, we obtain internal magnetic flux density images and produce current density images from $\bigtriangledown{\times}B/\mu_\theta$. This internal information is used in Magnetic Resonance Electrical Impedance Tomography (MREIT) where we try to reconstruct a cross-sectional resistivity image of a subject. This paper describes numerical techniques of computing voltage. current density, and magnetic flux density within a subject due to an injection current. We use the Finite Element Method (FEM) and Biot-Savart law to calculate these variables from three-dimensional models with different internal resistivity distributions. The numerical analysis techniques described in this paper are used in the design of MRCDI experiments and also image reconstruction a1gorithms for MREIT.

• Food Engineering Progress
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• v.23 no.1
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• pp.7-15
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• 2019

The impregnation of solid foods into the surrounding hypotonic or hypertonic solution was explored as a method to infuse NaCl in pork loin cube without altering its matrix. Mass transfer kinetics using a diffusive model as the mathematical model for moisture gain/loss and salt gain and the resulting textural properties were studied for the surrounding solutions of NaCl 2.5, 5.0, 10.0 and 15% (w/w). It was possible to access the effects of brine concentration on the direction of the resulting water flow, quantify water and salt transfer, and confirm tenderization effect by salt infusion. For brine concentrations up to 10% it was verified that meat samples gained water, while for processes with 15% concentration, pork loin cubes lost water. The effective diffusion coefficients of salt ranged from 2.43×10^-9 to 3.53×10^-9 m²/s, while for the values of water ranged from 1.22×10^-9 to 1.88×10^-9 m²/s. The diffusive model was able to represent well salt gain rates using a single parameter, i.e. an effective diffusion coefficient of salt through the meat. However, it was not possible to find a characteristic effective diffusion coefficient for water transfer. Within the range of experimental conditions studied, salt-impregnated samples by 5% (w/w) brine were shown with minimum hardness, chewiness and shear force.

• Korean Journal of Weed Science
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• v.14 no.3
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• pp.163-170
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• 1994

The experiment was conducted in 1993 to find out a simple prediction method of weeds and to make the prediction models of weeds in paddy fields. The annuals producing fine seeds were apt to emerge at sampling soil only, on the contrary the perennials and the annuals producing large seeds tended not to emerge at sampling soil due to the miss of seeds at sampling. There was no appropriate regression between a total number of weeds emerged at sampling soil and that of weeds occurred in fields. The important annual weeds occurring in fields were able to predict by the number of weeds emerged at sampling soil, but it was difficult to predict the important perennial weeds. In case of Bidens tripartita producing large seeds and Eleocharis kuroguwai producing large tubers, the prediction coefficients were high as above 1.0, and that of Echinochloa crus-galli and Sagittaria pygmaea were comparatively high as 0.175 and 0.172, respectively. However the coefficients of the other weeds were much low as below 0.08. The prediction models for 9 species were made. The model of six species including E. crus-galli, M. vaginalis, R. indica, B. tripartita, E. triandra and S. pygmaea were linear regression with high significance, however that of 3 species including C. difformis, S. juncoides and E. kuroguwai were curve regression with high significance.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).