• Economic and Environmental Geology
• /
• v.26 no.1
• /
• pp.21-27
• /
• 1993

Fluid inclusion has been widely used to study the origin and physiochemical conditions of ore deposits. However, it is difficult to get the accurate physiochemical data from fluid inclusion study due to the error of microthermometric data and the complexity of calculation of density and isochore of fluid inclusion. The computer programs HALWAT, $CO_2$, and CHNACL written by Nicholls and Crowford (1985) partly contributed to improve the accuracy of physiochemical data by using complicated equations. These programs are applied to determine the densities and isochores of fluid inclusions for the Cretaceous Keumhak mine using Choi and So's data (1992) and for the Jurassic Samhwanghak mine using Yun's data (1990). The estimated PoT for Keumhak mine from calculated isochores of coexisting fluid inclusions are $230^{\circ}{\sim}290^{\circ}C$ and 500~800 bar which matche well to the poT estimated by Choi and So ($280^{\circ}{\sim}360^{\circ}C$ and 500~800 bar, 1992). However, the poT for Samwhanghak mine estimated in this study by combining the calculated isochores and sulfur isotope geothermometer data by Yun (1990) are about 4~7 kb at $329{\pm}50^{\circ}{\sim}344{\pm}55^{\circ}C$ which are quite different form the P-T estimates by Yun ($255^{\circ}{\sim}294^{\circ}C$ and 1.2~1.9kb, 1990). This discrepancy caused by misinterpretation of homogenization temperature (Th) of fluid inclusion and by application of inappropriate isochores. The application of homogenization temperature and/or inappropriately selected isochore to determine the trapping PoT condition of ore-deposits should be avoided, particularly for ore-deposits formed at pressures higher than 1~2 kb.

• Journal of Climate Change Research
• /
• v.6 no.3
• /
• pp.209-221
• /
• 2015

Temperature is one of the most important factors affecting crop growth. The diurnal cycle of the scale factor [Tsc] for air temperature and the surface temperature of crop leaf and soil could be estimated by the following equation : $[Tsc]=0.5{\times}sin(X+C)+0.5$. The daily air temperature (E[Ti]) according to the E&E time [X] can be estimated by following equation using average (Tavg), maximum (Tm) and minimum (Tn) temperature : $E[Ti]=Tn+(Tm-Tn){\times}[0.5{\times}sin\;\{X+(9.646Tavg+703.65)\}+0.5]$. The crop leaf temperature in 24th June 2014 was high as the order of red pepper without mulching > red pepper with mulching > soybean under drought > soybean with irrigation > Chinese cabbage. The case in estimating crop leaf surface temperature using air temperature and soil surface temperature was lower in the deviation compared to the case using air temperature for Chinese cabbage and red pepper. These results can be utilized for the crop models as input data with estimation.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.405-414
• /
• 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 the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.16 no.5
• /
• pp.104-111
• /
• 2002

This paper presents a fuzzy rule extraction method using EM(Expectation-Maximization) algorithm and a design method of adaptive neuro-fuzzy control. EM algorithm is used to estimate a maximum likelihood of a GMM(Gaussian Mixture Model) and cluster centers. The estimated clusters is used to automatically construct the fuzzy rules and membership functions for ANFIS(Adaptive Neuro-Fuzzy Inference System). Finally, we applied the proposed method to the water temperature control system and obtained better results with respect to the number of rules and SAE(Sum of Absolute Error) than previous techniques such as conventional fuzzy controller.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.1
• /
• pp.46-56
• /
• 2018

This paper aimed to identify main factors of community characters, which have an effect on the land surface temperature(LST) change and estimate the impacting coefficient(ratio) of factors in a significant level of statistics. Chungcheongbuk-do province was selected and then partitioned into city and county areas for the sake of convenience of modeling. LST time series data and the community character data were developed based on Terra Satellite MODIS data and collected from the National Statistical Office, respectively. By the cause and effect relationship between community characters and LST, regression coefficients were estimated using a penal model. In a panel modeling, LST and community characters were used as a dependent variable and explanatory variables, respectively. Panel modeling analysis was carried out using statistical package STATA14 and one-way fixed effect model was selected as the most suitable model to evaluate the regression coefficients in the study area. The impacting ratio of LST change by any explanatory variable derived from the regression coefficients of the panel model fixed. Impacting ratios for industrial areas, elevation ${\times}$ building, energy usage, average window speed, non-urban management area, agricultural, nature and environmental conservation, average precipitation were 3.746, 2.856, 2.742, 0.553, 0.102, 0.071 and 0.003, respectively.

• Korean Journal of Environmental Biology
• /
• v.27 no.3
• /
• pp.292-296
• /
• 2009

This study was conducted to estimate relationship between temperature and egg development of Nannophya pygmaea, an endangerd dragonfly species in Korea, using eight different temperature conditions (17, 20, 22, 25, 28, 30, 33, and $36^{\circ}C$). Eggs of N. pygmaea were collected from female adults inhabited a small wetland in Mungyeong-si, Gyeongsangbuk-do, Korea, in June 2007. As a result, hatching rates were 2.86, 17.09, 24.32, 39.67, 34.43, 40.57, 44.79, and 1.75% at 17, 20, 22, 25, 28, 30, 33, and $36^{\circ}C$, respectively. The nonlinear model of the temperature related to egg development was well fit to the modified Sharpe and DeMichele model. The derived lower developmental threshold temperature for egg hatching was $14.02^{\circ}C$(y=0.005988x-0.084, $r^2$=0.99), and the derived optimal development temperature was $30{\sim}35^{\circ}C$.

• Proceedings of the KIPE Conference
• /
• 2018.07a
• /
• pp.249-251
• /
• 2018

본 논문에서는 모델 기반 적응제어 방식중 하나인 확장 칼만 필터(EKF: Extended Kalman Filter)를 사용하여 전기자전거용 배터리팩의 충전량(SOC: State of Charge)을 상온과 저온에서 추정하였다. 온도에 따라 배터리의 특성은 매우 가변적이며, 모델의 특성이 달라짐에 따라 적응제어를 위한 내부 파라미터 또한 상이하게 나타난다. 본 논문에서는 Matlab/Simulink를 이용하여 배터리와 확장 칼만 필터를 설계하고 시뮬레이션하였다. 온도에 따른 최적의 SOC 추정 성능을 얻기 위해, 오차 원인을 분석하고 이에 따른 개선된 SOC 추정 결과를 나타냈다.

• Proceedings of the KIPE Conference
• /
• 2019.07a
• /
• pp.420-421
• /
• 2019

리튬 이온 배터리는 전압, 전류, 온도 등의 측정 정보를 기반으로 용량, 수명 등 배터리의 상태를 추정해야 하며 이를 위해 다양한 방법들이 활용되고 있다. 이러한 추정 정보들은 결국 배터리 관리 시스템에서 수행하는 핵심 기능이며 효율적이고 안전한 제어를 수행하기 위해 필수적인 정보이다. 본 연구에서는 배터리 팩의 실험 데이터를 이용하여 근사 모델을 개발하고 이를 이용하여 배터리 팩의 용량을 추정하는 방법에 대한 연구를 수행하였다. 기존 수학적 모델 기반의 알고리즘을 활용하는 방법과 통계적인 기법을 활용하는 방법으로 구현하는 것과 달리, 충분한 데이터 확보가 가능한 경우, 데이터를 표현하는 근사 모델을 생성하고 이에 대한 활용 가능성을 확인하였다.

• Journal of Biomedical Engineering Research
• /
• v.10 no.2
• /
• pp.165-172
• /
• 1989

In this paper, the temperature dependence of tissue is estimated by measuring the attenuation coefficient and the propagation velocity of ultrasonic reflection signal. And, on the basis of expeiments, the possibility of non- invasive temperature estimation is considered. Specimens in the experiment are acryl 1)late. muscle, fat and liver of pig. The temperature of specimen is controlled by water bath which is able to adjust temperature a quarter of a degree. Through the series of experiments, we conformed that the ultrasonic parameters have lin earity to a certain extents with the change of tissue's temperature. And we expect that noninvasive temperature estimation of tissue can be realized after several preconditions be satisfied with the standard experiment conditions and a great number of base data.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.1 no.2
• /
• pp.119-126
• /
• 1999

A numerical model using soil surface energy balance and soil heat flow equations to estimate mulched soil temperature was developed. The required inputs data include weather data, such as global solar radiation, air temperature, wind speed, atmospheric water vapor pressure, the optical properties of mulching material, and soil physical properties. The observed average soil temperature at 50 cm depth was used as the initial value of soil temperature at each depth. Soil temperature was simulated starting at 0 hour at an interval of 10 minutes. The model reliably described the variation of soil temperature with time progress and soil depth. The correlation between the estimated and measured temperature yielded coefficient values of 0.961, 0.966 for 5cm and 10cm depth of the bare soil, respectively, 0.969, 0.965 for the paper mulched soil, and 0.915, 0.938 for the black polyethylene film mulched soil. The percentages of absolute differences less than 2$^{\circ}$C between soil temperatures measured and simulated at 10 minute interval were 97.4% and 98.5% for 5 cm and 10cm for the bare soil, respectively, and 95.8% and 97.4% for the paper mulched soil, and 70.1% and 92.5% for the polyethylene film mulched soil. The results indicated that the model was able to predict the soil temperature fairly well under mulched condition. However, in the night time, the model performance was a little poor as compared with day time due to the difficulty of accurate determination of the atmospheric long wave radiation.