• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1197-1208
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• 2019

Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to improve TVDI performance over the study region. In-situ measured air temperature was employed to increase accuracy, regression line was generated using monthly data to include seasonal effect, and TVDI was calculated at each province level to consider vegetation type and local climate. The modified TVDI calculation method was evaluated in wildfire cases and showed significant improvement in wildfire danger estimation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.96-104
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• 2001

Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.277-282
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• 2012

When wind speed exceeds a certain threshold, daily minimum temperature does not drop as predicted by the geospatial model in a cold pooling catchment. A linear regression equation was derived to explain the warming effect of wind speed on daily minimum temperature by analyzing observations at a low lying location within an enclosed catchment. The equation, Y=2X+0.4 ($R^2$=0.76) where Y stands for the warming ($^{\circ}C$) and X for the mean horizontal wind speed (m/s) at 2m height, was combined to an existing model to predict daily minimum temperature across an enclosed catchment on cold pooling days. The adjusted model was applied to 3 locations submerged in a cold air pool to predict daily minimum temperature on 25 cold pooling days with the input of simulated wind speed at each location. Results showed that bias (mean error) was reduced from -1.33 to -0.37 and estimation error (RMSE) from 1.72 to 1.20, respectively, in comparison with those from the unadjusted model.

• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.3
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• pp.149-158
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• 2005

This paper describes design, fabrication, and application of the silicon based temperature controllable micro reactor. In order to achieve fast temperature variation and low energy consumption, reaction chamber of the micro reactor was thermally isolated by etching the highly conductive silicon around the reaction chamber. Compared with the model not having thermally isolated structure, the thermally isolated micro reactor showed enhanced thermal performances such as fast temperature variation and low energy consumption. The performance enhancements of the micro reactor due to etched holes were verified by thermal experiment and numerical analysis. Regarding to 42 percents reduction of the thermal mass achieved by the etched holes, approximately 4 times faster thermal variation and 5 times smaller energy consumption were acquired. The total size of the fabricated micro reactor was $37{\times}30{\times}1mm^{3}$. Microchannel and reaction chamber were formed on the silicon substrate. The openings of channel and chamber were covered by the glass substrate. The Pt electrodes for heater and sensor are fabricated on the backside of silicon substrate below the reaction chamber. The dimension of channel cross section was $200{\times}100{\mu}m^{2}$. The volume of reaction chamber was $4{\mu}l$. The temperature of the micro reactor was controlled and measured simultaneously with NI DAQ PCI-MIO-16E-l board and LabVIEW program. Finally, the fabricated micro reactor and the temperature control system were applied to the thermal denaturation and the trypsin digestion of protein. BSA(bovine serum albumin) was chosen for the test sample. It was successfully shown that BSA was successfully denatured at $75^{\circ}C$ for 1 min and digested by trypsin at $37^{\circ}C$ for 10 min.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.405-414
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• 2021

This study predicted waxy corn harvest date in South Korea using 30-year (1991-2020) hindcasts (1-6 month lead) produced by the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. To estimate corn harvest date, the cumulative temperature is used, which accumulated the daily observed and predicted temperatures from the seeding date (5 April) to the reference temperature (1,650~2,200℃) for harvest. In terms of the mean air temperature, the hindcasts with a bias correction (20.2℃) tends to have a cold bias of about 0.1℃ for the 6 months (April to September) compared to the observation (20.3℃). The harvest date derived from bias-corrected hindcasts (DOY 187~210) well simulates one from observation (DOY 188~211), despite a slight margin of 1.1~1.3 days. The study shows the possibility of obtaining the gridded (5 km) daily temperature and corn harvest date information based on the cumulative temperature in advance for all regions of South Korea.

• Journal of Animal Science and Technology
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• v.64 no.4
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• pp.770-781
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• 2022

Meteorological disasters caused by climate change like heat, cold waves, and unusually long rainy seasons affect the milk productivity of cows. Studies have been conducted on how milk productivity and milk compositions change due to heat stress (HS). However, the estimation of losses in milk production due to HS and hereby environmental impacts of greenhouse gas (GHG) emissions are yet to be evaluated in Korean dairy farms. Dairy milk production and milk compositions data from March to October 2018, provided by the Korea Dairy Committee (KDC), were used to compare regional milk production with the temperature-humidity index (THI). Raw data for the daily temperature and relative humidity in 2018 were obtained from the Korea Meteorological Administration (KMA). This data was used to calculate the THI and the difference between the maximum and minimum temperature changing rate, as the average daily temperature range, to show the extent to which the temperature gap can affect milk productivity. The amount of milk was calculated based on the price of 926 won/kg from KDC. The results showed that the average milk production rate was the highest within the THI range 60-73 in three regions in May: Chulwon (northern region), Hwasung (central region), and Gunwi (southern region). The average milk production decreased by 4.96 ± 1.48% in northern region, 7.12 ± 2.36% in central region, and 7.94 ± 2.57% in southern region from June to August, which had a THI range of 73 or more, when compared to May. Based on the results, the level of THI should be maintained like May. If so, the farmers can earn a profit of 9,128,730 won/farm in northern region, 9,967,880 won/farm in central region, and 12,245,300 won/farm in southern region. Additionally, the average number of cows raised can be reduced by 2.41 ± 0.35 heads/farm, thereby reducing GHG emissions by 29.61 ± 4.36 kg CO₂eq/day on average. Overall, the conclusion suggests that maintaining environmental conditions in the summer that are similar to those in May is necessary. This knowledge can be used for basic research to persuade farmers to change farm facilities to increase the economic benefits and improve animal welfare.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.685-691
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• 2022

This study was based on the steel composite concrete box structure (Transfer girder) which was installed to support the skyscrapers directly above the subway line. In this study, it was analytically proved that the cause of cracks on the steel composite concrete box structure were the shrinkage cracks by comparing the results of crack investigation and numerical analysis. As the results, it was found that the internal temperature difference between concrete and steel members occurred according to the shape of the steel frame embedded in concrete, the location of vertical stiffener, and the closed section area. The narrower spacing of vertical stiffener was occurred the internal temperature concentration of the structure and the temperature difference increased. And the location of higher thermal strain and temperature were similar to the location of actual cracks by the visual inspection. Therefore, the internal temperature concentration parts were formed according to the presence and spacing of the vertical stiffeners and the inspection passage in the central part of the structure. The shrinkage cracks were occurred by the restrained of temperature expansion and contraction of the concrete. As the results of this study, it was important to separate and manage the non-structural cracks caused by shrinkage and the structural cracks in the maintenance of serviced steel-composite concrete structures.

• Journal of Practical Agriculture & Fisheries Research
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• v.18 no.1
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• pp.71-78
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• 2016

The present study was performed to examine the high temperature adaptability with CO₂ treatment for tomato under the condition of greenhouse cultivation during summer season. The plants with the CO₂ concentration of 1000 ppm recorded higher scores in Fm/Fo and Fv/Fm but lower score in Fo than others through the measurement of chlorophyll fluorescence, which implicated that the plants with the CO₂ concentration of 1000 ppm had more adaptability to high temperature than the others. At the condition of the same air temperature as 30℃ and 40℃, the photosynthetic rate was increased with the increase of CO₂ concentration. When in the high air temperature state of 40℃, although the photosynthic rate was low in comparison with 30℃, its value was about 18.5umolm^-2s^-1 in case of 1000ppm. The higher concentration of CO₂ made the more activated anti-oxidation enzyme (superoxide dismutase and peroxidase) for the both cultivars as 'momotaro' and 'minichal'. The cultivar of 'minichal' performed the high temperature limit as 41℃ at the CO₂ condition of 500 ppm and 43℃ at the CO₂ condition of 1000 ppm through the estimation on the variation of chlorophyll fluorescence Fo by CO₂ concentrations.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.4
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• pp.395-403
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• 2005

It is very important to forecast water supply for reasonal operation and management of water utilities. In this paper, water supply forecasting models using artificial intelligence are developed. Artificial intelligence models shows better results by using Temperature(t), water supply discharge (t-1) and water supply discharge (t-2), which are expressed by neural network(LMNNWS; Levenberg-Marquardt Neural Network for Water Supply, MDNNWS; MoDular Neural Network for Water Supply) and neuro fuzzy(ANASWS; Adaptive Neuro-Fuzzy Inference Systems for Water Supply). ANFISWS model which is applied for water supply forecasting shows stable application to the variable water supply data. As results, MDNNWS model shows the highest overall accuracy among proposed water supply forecasting models and the lowest estimation error with the order of ANFISWS, LMNNWS model.

• Journal of the Korean Solar Energy Society
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• v.25 no.1
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• pp.97-104
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• 2005

A one-dimensional heat transfer model for the vertical borehole system is derived in this study to predict the thermal behavior of the system and surrounding soil. In this model the U-tube is replaced with one effective tube of effective diameter which is surrounded by concentric grout region. All thermal resistances of borehole are counted in the grout region with effective thermal conductivity of grout. Effective thermal conductivity of grout and sand are calculated through parameter estimation. The validity of this model is accomplished through comparison of the predicted temperature profiles of the model with experimental data.