• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.1-10
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• 2003

A computer simulation was carried out to determinate the optimum capacity of bulk type trailer which is used as a tractor attachment. Soil physical properties. such as soil moisture content. bulk density, soil hardness and soil texture were measured in the 10 major rice production area for computer simulation. Mathematical model which include soil physical properties and vehicle factor was used for computer simulation. Most of the soil texture of the investigated area was silty loam. Soil moisture content ranged between 30 and 40% mostly. Soil bulk density was in the range of 1.500 to 1.700 kg/㎥. Soil hardness ranged between 1 to 18 kg/$\textrm{cm}^2$. Soil hardness incorporate the effects of many soil physical properties such as moisture content texture and bulk density, and so the range of soil hardness was greater than any other physical properties. The capacity of bulk type trailer was above 3000 kg$_{f}$ fer the most of the investigated area. and mostly in the range of 4000 to 6000 kg$_{f}$ depending upon the slip. But for the soft soil area such as Andong and Namyang. tractor itself had mobility problem and showed minus trailer capacity for some places. For this area. the capacity of bulk type trailer ranged between 1000 and 2000 kg$_{f}$ mostly so bulk type trailer should be designed as a small capacity compared to the other area.ared to the other area. area.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.8-13
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• 2021

The study for soil has been conducted separately by several areas such as soil mechanics and soil chemistry. Soil is important in terms of prediction of how the plant grow with nutrient requirement. Also, soil is important for machines to work on to solve labor shortage and save farmers from harsh environment during farm work. To meet diverse needs related to soil in agriculture, the soil related study needs to be conducted synthetically. Thus, we tried to obtain the data related to soil chemistry including pH and Electrical Conductivity (EC) with data related to soil mechanics including Cone Index (CI), moisture content, soil classification. Specifically, the condition of the field was set to be cultivated at least for five years continuously at a first step. The soil was taken from 30 sites. CI was obtained using the soil penetrometer and soil classification was conducted using sieve analysis with eight kinds of sieve. The soil was taken on December when is during winter in Korea. There was variation of data including moisture content and CI.

• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.181-191
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• 2020

In order to produce accurate initial condition of soil moisture for global Numerical Weather Prediction (NWP), spin-up experiment is carried out using Noah Land Surface Model (LSM). The model is run repeatedly through 10 years, under the atmospheric forcing condition of 2008-2017 until climatological land surface state is achieved. Spin-up time for the equilibrium condition of soil moisture exhibited large variability across Koppen-Geiger climate classification zone and soil layer. Top soil layer took the longgest time to equilibrate in polar region. From the second layer to the fourth layer, arid region equilibrated slower (7 years) than other regions. This result means that LSM reached to equilibrium condition within 10 year loop. Also, spin-up time indicated inverse correlation with near surface temperature and precipitation amount. Initialized from the equilibrium state, LSM was spun up to obtain land surface state in 2018. After 6 months from restarted run, LSM simulates soil moisture, skin temperature and evaportranspiration being similar land surface state in 2018. Based on the results, proposed LSM spin-up system could be used to produce proper initial soil moisture condition despite updates of physics or ancillaries for LSM coupled with NWP.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.75-81
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• 2021

Since plant growth is greatly influenced by moisture, it is important to control the soil to have optimal moisture for the plant being grown. Recently, researches on automatically analyzing plant growth information including soil moisture using spectral images are being conducted. However, hyperspectral images are difficult to use due to huge amount of data appearing in spectral bands. In this paper, we propose a method to solve the complexity of hyperspectral images using a CNN. Since the proposed method automatically analyzes the entire band of the target hyperspectral using deep learning, there is no need to make an effort to find a specific band for analysis of each image. In order to show the effectiveness of the proposed system, we conduct an experiment to analyze moistures using hyperspectral images obtained from soil.

• Near Infrared Analysis
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• v.1 no.1
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• pp.37-41
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• 2000

The purpose of this research was to develop a the reflection technique with near infrared (NIR) radiation for estimating soil components. NIR reflectance was scanned at 2nm intervals from 1100 to 2500nm with an InfraAlyzer 500 (Bran & Luebbe Co.). Over 400 soil sample from fields of different crops and land-use over Youngnam and Honam regions were used to obtain mean diffuse reflection of the soil for the calibration and validation of the calibration set in estimating moisture, organic matter (OM) and total nitrogen (T-N) of the soils. Multiple linear regression (MLR) was used to evaluate the correlation of NIR spectroscopy method. Reflection pattern of NIR spectra for finely sized sample (<0.5mm) and coarsely sized soil(<2mm) did not show much difference. The results showed that NIR spectroscopy and coarsely sized soil (<2mm) did not show much difference. The results showed that NIR spectroscopy could be used as a routine soil testing method in estimating OM, moisture, T-N in soil samples simultaneously.

• Atmosphere
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• v.23 no.1
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• pp.113-121
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• 2013

The objective of this study is to develop and evaluate the system to produce the real-time ensemble drought prediction data. Ensemble drought prediction consists of 3 processes (meteorological outlook using the multi-initial conditions, hydrological analysis and drought index calculation) therefore, more processing time and data is required than that of single member. For ensemble drought prediction, data process time is optimized and hardware of existing system is upgraded. Ensemble drought data is estimated for year 2012 and to evaluate the accuracy of drought prediction data by using ROC (Relative Operating Characteristics) analysis. We obtained 5 ensembles as optimal number and predicted drought condition for every tenth day i.e. 5th, 15th and 25th of each month. The drought indices used are SPI (Standard Precipitation Index), SRI (Standard Runoff Index), SSI (Standard Soil moisture Index). Drought conditions were determined based on results obtained for each ensemble member. Overall the results showed higher accuracy using ensemble members as compared to single. The ROC score of SRI and SSI showed significant improvement in drought period however SPI was higher in the demise period. The proposed ensemble drought prediction system can be contributed to drought forecasting techniques in Korea.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.19-19
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• 2019

It is necessary to maintain stable crop productions under the unsuitable environments, because the drought and flood may be frequently caused by the global warming. Therefore, it is agent to improve the crop growth model corresponded to soil moisture status. Chili pepper (Capsicum annuum) is one of the useful crop in Asia, and then it is affected by change of precipitation in consequence drought and flood occur however crop model to evaluate water stresses on chili pepper is not enough yet. In this study, development of crop model under different soil moisture status was attempted. The experiment was conducted on the slope fields in the greenhouse. The water level was kept at 20cm above the bottom of the container. Habanero (C. chinense) was used as material for crop model. Sap bleeding rate, SPAD value, chlorophyll content, stomatal conductance, leaf water potential, plant height, leaf area and shoot dry weight were measured at 10 days after treatment (DAT) and 13 DAT. Moreover, temperature and RH in the greenhouse, soil volume water contents (VWC) and soil water potential were measured. As a result, VWC showed 4.0% at the driest plot and 31.4% at the wettest plot at 13 DAT. The growth model was calculated using WVC and the growth analysis parameters. It was considered available, because its coefficient of determination showed 0.84 and there are significant relationship based on plants physiology among the parameters and the changes over time. Furthermore, we analyzed the important factors for higher accuracy prediction using multiple regression analysis.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.28-33
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• 2003

Achievements in the real-time soil spectro-photometer are: an improved soil penetrator to ensure a uniform soil surface under high speed conditions, real-time collecting of underground soil reflectance, getting underground soil color images, use of a RTK-GPS, and all units are arranged for compactness. With the soil spectrophotometer, field experiments were conducted in a 0.5 ha paddy field. With the original reflectance, averaging and multiple scatter correction, Kubelka-Munk (KM) transformation as soil absorption, its 1st and 2nd derivatives were calculated. When the spectra was highly correlated with the soil parameters, stepwise regression analysis was conducted. Results include the best prediction models for moisture, soil organic matter (SOM), nitrate nitrogen (NO$_3$-N), pH and electric conductivity (EC), and soil maps obtained by block kriging analysis.

• Journal of the Korean Institute of Landscape Architecture
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• v.22 no.4
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• pp.75-80
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• 1995

It is important to estimate the possibility of recovery in physiologically damaged woody plant. It is suggested that C.E.R(cambial electrical resistance) might be a useful method to predict the permanent wilting point. D/A and A/D converter can be used to measure the C.E.R and it took only 10-20 msec for a measurement and the values were stable during this study. A computer could be used for the continual measurement of C.E.R. There were very big daily changes of C.E.R. was changed according to the changes of indoor temperature, but the phase was slightly different. It is reasoned that daily changes in C.E.R. is induced by the changes of water potential and cambial thickness. It was difficult to detect the changes of C.E.R. caused by changes in soil moisture under high soil water potential. Under low soil water potential, the changes in soil moisture under high soil water potential. Under low soil water potential, the changes of C.E.R. can be detected. After wilting, C.E.R. is increased very rapidly. When C.E.R. is not decreased by watering, it will be permanent wilting point. But it takes several days to confirm the permanent wilting point. To predict the possibility of recovery from wilting, the values of C.E.R. have no meaning. But the changes of C.E.R. are significant. Therefore we can predict the permant wilting point in woody plant by monitoring the change of C.E.R. by the computer.

• Agricultural and Biosystems Engineering
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• v.4 no.2
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• pp.45-49
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• 2003

Achievements in the real-time soil spectro-photometer are: an improved soil penetrator to ensure a uniform soil surface under high speed conditions, real-time collecting of underground soil reflectance, getting underground soil color images, use of a RTK-GPS, and all units are arranged for compactness. With the soil spectrophotometer, field experiments were conducted in a 0.5 ha paddy field. With the original reflectance, averaging and multiple scatter correction, Kubelka-Munk (KM) transformation as soil absorption, its 1st and 2nd derivatives were calculated. When the spectra was highly correlated with the soil parameters, stepwise regression analysis was conducted. Results include the best prediction models for moisture, soil organic matter (SOM), nitrate nitrogen ($NO_3-N$), pH and electric conductivity (EC), and soil maps obtained by block kriging analysis.