• Journal of the Korean Geotechnical Society
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• v.34 no.1
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• pp.17-24
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• 2018

A buffer in a geological disposal system minimizes groundwater inflow from the surrounding rock and protects the disposed high-level waste (HLW) against any mechanical impact. As decay heat of a spent fuel causes temperature variation in the buffer that affects the mechanical performance of the system, an accurate estimation of the temperature variation is substantial. The temperature variation is affected by thermal and material properties of the system such as thermal conductivity, density and specific heat capacity of the buffer, and thus these factors should be properly included in the design of the system. In particular, as the thermal properties are variable depending on the density and water content of the buffer, consideration of the effects should be included in the analysis. Hence, in this study, a numerical model based on finite element method (FEM) which is able to consider the change of density and water content of the buffer was established. In addition, using the numerical model, a parametric study was conducted to investigate the effect of each thermal property on the temperature variation of the buffer.

• Journal of IKEEE
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• v.17 no.1
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• pp.63-70
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• 2013

In this paper, we have implemented the performance evaluation system of the unified fuel heater for CRDI diesel engine. If the diesel engine be cold by low temperature in winter, then that makes the waxing materials like a paraffin and is the source of poor engine starting. The unified fuel heater is the barrow meter that estimate the start performance of diesel engine, and be tested by test chamber. The chamber perform the normal temperature, an extremely low temperature, an operating performance in an extremely high temperature, the resistance operation delay time and current operation delay time in setting up test resistance, the bimetal delay time test in temperature variation, the current and resistor test of the composited heater, a heating operation test.

• 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.

• Journal of Environmental Health Sciences
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• v.34 no.4
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• pp.316-326
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• 2008

The Earth's temperature has risen $0.76^{\circ}C$ (degree) during last 100 years which Implies a sudden rise, compare with the 4oC (degrees) rise through out the past 20,000 years. If the volume of GHG (Greenhouse Gas) emission continues at the current level, the average temperature of the Earth will rise by $1^{\circ}C$ (degree) by 2030 with the further implication that the temperature of Earth will rise by $2{\sim}5^{\circ}C$ (degrees) every 100 years. Therefore, as we are aware that the temperature of the glacial epoch was $8{\sim}9^{\circ}C$ (degrees) lower than the present time, we can easily predict that the above temperature rises can be potentially disastrous for human life. Every country in the world recognizes theseriousness of the current climate change and adopted a convention on climate change in June 1992 in Rio. The COP1 was held in March 1995 in Berlin and the COP3 in Dec. 1997 in Kyotowhere the target (2008-2012) was determined and the advanced nations' reduction target (5.2%, average)was also agreed at this conference. Korea participated in the GHG reduction plan which required the world's nations to ratify the Kyoto Protocol. Ratification of the Kyotoprotocol and the followup requirement to introduce an international emissions trading scheme will require severe reductions in GHGs and considerable economic consequences. USA are still refusing to fully ratify the treaty as the emission reductions could severely damage the economies of these countries. In order to estimate the exact $CO_2$ emission, this study statistically analyzed $CO_2$ emission of each country based on the following variables : level of economic power and scientific development, the industrial system, productivity and energy efficiency.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.475-482
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• 2011

In this research, we have attempted to estimate the water quality of fish farms in terms of parameters such as water temperature, dissolved oxygen, pH, and salinity by employing observational data obtained from a coastal ocean observatory of a national institution located close to the fish farm. We requested and received marine data comprising nine factors including water temperature from Korea Hydrographic and Oceanographic Administration. For verifying our results, we also established an experimental fish farm in which we directly placed the sensor module of an optical mode, YSI-6920V2, used for self-cleaning inside fish tanks and used the data measured and recorded by a environment monitoring system that was communicating serially with the sensor module. We investigated the differences in water temperature and salinity among three areas - Goheung Balpo, Yeosu Odongdo, and the experimental fish farm, Keumho. Water temperature did not exhibit significant differences but there was a difference in salinity (significance <5%). Further, multiple regression analysis was performed to estimate the water quality of the fish farm at Keumho based on the data of Goheung Balpo. The water temperature and dissolved-oxygen estimations had multiple regression linear relationships with coefficients of determination of 98% and 89%, respectively. However, in the case of the pH and salinity estimated using the oceanic environment with nine factors, the adjusted coefficient of determination was very low at less than 10%, and it was therefore difficult to predict the values. We plotted the predicted and measured values by employing the estimated regression equation and found them to fit very well; the values were close to the regression line. We have demonstrated that if statistical model equations that fit well are used, the expense of fish-farm sensor and system installations, maintenances, and repairs, which is a major issue with existing environmental information monitoring systems of marine farming areas, can be reduced, thereby making it easier for fish farmers to monitor aquaculture and mariculture environments.

• Food Science of Animal Resources
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• v.29 no.3
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• pp.289-295
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• 2009

The aim of this research was to develop predictive models for the growth of spoilage bacteria (total viable cells, Pseudomonas spp., and lactic acid bacteria) on frankfurters and to estimate the shelf-life of frankfurters under aerobic conditions at various storage temperatures (5, 15, and $25^{\circ}C$). The primary models were determined using the Baranyi model equation. The secondary models for maximum specific growth rate and lag time as functions of temperature were developed by the polynomial model equation. During 21 d of storage under various temperature conditions, lactic acid bacteria showed the longest lag time and the slowest growth rate among spoilage bacteria. The growth patterns of total viable cells and Pseudomonas spp. were similar each other. These data suggest that Pseudomonas spp. might be the dominant spoilage bacteria on frankfurters. As storage temperature increased, the growth rate of spoilage bacteria also increased and the lag time decreased. Furthermore, the shelf-life of frankfurters decreased from 7.0 to 4.3 and 1.9 (d) under increased temperature conditions. These results indicate that the most significant factor for spoilage bacteria growth is storage temperature. The values of $B_f$, $A_f$, RMSE, and $R^2$ indicate that these models were reliable for identifying the point of microbiological hazard for spoilage bacteria in frankfurters.

• Korean Journal of Remote Sensing
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• v.3 no.1
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• pp.41-54
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• 1987

Accurate determination of Sea Surface Temperature (SST) is essential for ocean and climate studies. This paper estimated SST in the sea region around the Korea from the Advenced Very High Resolution Radiometer(AVHRR) channel 4 data on board NOAA-9 satellite. The processing procedure used to derive SSTs utilized: 1) Ascending node prediction of satellite orbit 2) Geometric correction 3) Radiometric calibration and radiance to temperature conversion look up table 4) Removing cloudy area. SST product results are displayed as colored video and hardcopy. In this processing, geometric correction is derived from equator crossing time, ascending time and subpoint coordinate information. Also, normalized response function of infrared 10.5-11.5$\mu\textrm{m}$ wavelength is used for temperature conversion. The SST derived from this processing is relatively similar to the measurements made by ship data, but because of water vapor attenuation SST from satellite are in general 2$^{\circ}$- $^{\circ}C$ lower than the ship data.

• Atmosphere
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• v.31 no.5
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• pp.525-537
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• 2021

Black ices on road surfaces in winter tend to cause severe and terrible accidents. It is very difficult to detect black ice events in advance due to their localities as well as sensitivities to surface and upper meteorological variables. This study develops a methodology to detect the road sections vulnerable to black ice with the use of road surface temperature data obtained from a mobile road weather observation vehicle. The 7 experiments were conducted on the route from Nam-Wonju IC to Nam-Andong IC (132.5 km) on the Jungang Expressway during the period from December 2020 to February 2021. Firstly, temporal road surface temperature data were converted to the spatial data with a 50 m resolution. Then, the spatial road surface temperature was normalized with zero mean and one standard deviation using a simple normalization, a linear de-trend and normalization, and a low-pass filter and normalization. The resulting road thermal map was calculated in terms of road surface temperature differences. A road ice index was suggested using the normalized road temperatures and their horizontal differences. Road sections vulnerable to black ice were derived from road ice indices and verified with respect to road geometry and sky view, etc. It was found that black ice could occur not only over bridges, but also roads with a low sky view factor. These results are expected to be applicable to the alarm service for black ice to drivers.

• ALGAE
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• v.39 no.1
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• pp.1-16
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• 2024

Many dinoflagellates produce bioluminescence. To estimate the intensity of bioluminescence produced by populations of the heterotrophic dinoflagellates Noctiluca scintillans and Polykrikos kofoidii and autotrophic dinoflagellate Alexandrium mediterraneum in Korean waters, we measured cellular bioluminescence intensity as a function of water temperature and calculated population bioluminescence intensity with cell abundances and water temperature. The mean 200-second-integrated bioluminescence intensity per cell (BL_cell) of N. scintillans satiated with the chlorophyte Dunaliella salina decreased continuously with increasing water temperature from 5 to 25℃. However, the BL_cell of P. kofoidii satiated with the mixotrophic dinoflagellate Alexandrium minutum continuously increased from 5 to 15℃ but decreased at temperatures exceeding this (to 30℃). Similarly, the BL_cell of A. mediterraneum continuously increased from 10 to 20℃ but decreased between 20 and 30℃. The difference between highest and lowest BL_cell of N. scintillans, P. kofoidii, and A. mediterraneum at the tested water temperatures was 3.5, 11.8, and 21.0 times, respectively, indicating that water temperature clearly affected BL_cell. The highest estimated population bioluminescence intensity (BL_popul) of N. scintillans in Korean waters in 1998-2022 was 4.22 × 10¹³ relative light unit per liter (RLU L^-1), which was 1,850 and 554,000 times greater than that of P. kofoidii and A. mediterraneum, respectively. This indicates that N. scintillans populations produced much brighter bioluminescence in Korean waters than the populations of P. kofoidii or A. mediterraneum.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.221-228
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• 2019

The effects of wind speed on the temperature change during day time could be insignificant in a region with a complex terrain. The objective of this study was to derive empirical relationship between solar radiation and hourly temperature under a windy condition for the period from sunrise to sunset in order to improve hourly air temperature at a site-specific scale. The deviation of the temperature measurements was analyzed along with the changes of the hourly sunlight at weather observation sites located on the east and west slopes under given wind speed. An empirical model where wind speed use used as an independent variable was obtained to quantify the solar effects on the temperature change (MJ/㎡). This model was verified estimating the hourly temperature during the daytime (0600-1900 h) at 25 weather observation sites located in the study area that has complex topography for the period from January to December 2018. The mean error (ME) and root mean square error (RMSE)of the estimated and measured values ranged from -0.98 to 0.67 ℃, and from 0.95 to 2.04 ℃, respectively. The daytime temperature at 1500 h were estimated using new and previous models. It was found that to the model proposed in the present study reduced the measurement errors of the hourly temperature in the afternoon in comparison with the previous model. For example, the ME and RMSE of the previous model were (ME -0.91 ℃ and 1.47 ℃, respectively. In contrast, the values of ME and RMSE were -0.45 ℃ and 1.22 ℃ for the new model, respectively. Our results suggested that the reliability of hourly temperature estimates at a specific site could be improved taking into account the effect of wind as well as solar radiation.