• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.83-93
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• 2020

East Asia, which includes China, Japan, Korea, and Mongolia, is highly impacted by hydroclimate extremes such drought, flood, and typhoon recent year. In 2017, more than 18.5 million hectares of crops have been damaged in China, and Korea has suffered economic losses as a result of severe drought. Satellite-derived rainfall products are becoming more accurate as space and time resolution become increasingly higher, and provide an alternative means of estimating ground-based rainfall. In this study, we verified the availability of rainfall products by comparing widely used satellite images such as Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with ground stations in East Asia. Also, the satellite-based rainfall products were used to calculate the Standardized Precipitation Index (SPI). The temporal resolution is based on monthly images and compared with the past 30 years data from 1989 to 2018. The comparison between rainfall data based on each satellite image products and the data from weather station-based weather data was shown by the coefficient of determination and showed more than 0.9. Each satellite-based rainfall data was used for each grid and applied to East Asia and South Korea. As a result of SPI analysis, the RMSE values of CHIRPS were 0.57, 0.53 and 0.47, and the MAE values of 0.46, 0.43 and 0.37 were better than other satellite products. This satellite-derived rainfall estimates offers important advantages in terms of spatial coverage, timeliness and cost efficiency compared to analysis for drought assessment with ground stations.

• Journal of Climate Change Research
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• v.7 no.1
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• pp.9-17
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• 2016

Climate change affects plant responses on physiological characteristics and growth, and Pinus densiflora, one of the major tree species in Korea, are expected to be particularly vulnerable to rising temperature and increased precipitation. This study was conducted to investigate the effects of an open-field warming and precipitation manipulation on physiological characteristics and growth of P. densiflora seedlings. Seedlings of 2-year-old P. densiflora were planted in April, 2013, in open-field nursery located at Korea University. The air temperature of warmed plots had been set to be $3^{\circ}C$ higher than the control plots using infrared lamps. Precipitation was manipulated to be 30% lower or higher than the control, using transparent panels and drip irrigation. Net photosynthetic rate, total chlorophyll content, seedling height, root collar diameter and biomass were measured from April, 2014 to April, 2015. The increase in new shoot biomass from warming was statistically significant, with the biomass in warmed plots about 2-fold higher than in the control plots in 2014 and 2015. This result might be related to advanced bud burst and increased occurrence of abnormal new shoots in warmed plots. Meanwhile, the results of net photosynthetic rate, total chlorophyll content, seedling height, root collar diameter and total biomass from warming and precipitation manipulation were not statistically significant, but tendencies of lower net photosynthetic rate and higher seedling height and biomass in warmed plots compared to the control were shown. Such might be speculated as results of the extended growth period. When root to shoot (R/S) ratio was calculated from the biomass data obtained in April 2014 and April 2015, increased R/S ratio was observed regardless of the treatments applied. Drought tolerance of P. densiflora and particularly low annual precipitation observed in 2014 were suggested as the possible reasons.

• Journal of Pharmaceutical Investigation
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• v.24 no.4
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• pp.233-243
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• 1994

Precipitation was formed during the preparation of decoction from a mixture of Scutellariae Radix and Coptidis Rhizoma or Phellodendri Cortex according to the prescription of Hwang-ryean-hae-dog-tang. Baicalin and berberine were identified in coprecipitated product and these components were the active ingredients of two herbal medicine. The coprecipitated product was very slightly soluble in water and sparingly soluble in ethanol. The stoichiometric ratio of baicalin and berberine was found to be 1:1. The lipid-water partition coefficients of coprecipitated product were increased more than baicalin and berberine in chloroform, but were decreased in other organic solvents. The content of baicalin and berberine in coprecipitated product, determined by HPLC, were 23.08% and 26.75%, but the content of active ingredients in supernatant were 0.66% and 0.26%, respectively. The dissolution profile of baicalin of coprecipitated product was increased more than extract of Scutellariae Radix in artificial gastric juice, but was decreased in artificial intestinal juice. The dissolution rate of berberine of coprecipitated product was lower than extract of Coptidis Rhizoma in artificial gastric juice and intestinal juice commonly.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.65-71
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• 2012

The objective of this study was to estimate surface runoff from rice paddy plots using an artificial neural network (ANN). A field experiment with three treatment levels was conducted in the NICS saemangum experimental field located in Iksan, Korea. The ANN model with the optimal network architectures, named Paddy1901 with 19 input nodes, 1 hidden layer with 16 neurons nodes, and 1 output node, was adopted to predict surface runoff from the plots. The model consisted of 7 parameters of precipitation, irrigation rate, ponding depth, average temperature, relative humidity, wind speed, and solar radiation on the daily basis. Daily runoff, as the target simulation value, was computed using a water balance equation. The field data collected in 2011 were used for training and validation of the model. The model was trained based on the error back propagation algorithm with sigmoid activation function. Simulation results for the independent training and testing data series showed that the model can perform well in simulating surface runoff from the study plots. The developed model has a main advantage that there is no requirement for any prior assumptions regarding the processes involved. ANN model thus can be a good tool to predict surface runoff from rice paddy fields.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.1
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• pp.27-35
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• 2016

Black-box classifiers, such as artificial neural network and support vector machine, are a popular classifier because of its remarkable performance. They are applied in various fields such as inductive inferences, classifications, or regressions. However, by its characteristics, they cannot provide appropriate explanations how the classification results are derived. Therefore, there are plenty of actively discussed researches about interpreting trained black-box classifiers. In this paper, we propose a method to make a fuzzy logic-based classifier using extracted rules from the artificial neural network and support vector machine in order to interpret internal structures. As an object of classification, an anomalous propagation echo is selected which occurs frequently in radar data and becomes the problem in a precipitation estimation process. After applying a clustering method, learning dataset is generated from clusters. Using the learning dataset, artificial neural network and support vector machine are implemented. After that, decision trees for each classifier are generated. And they are used to implement simplified fuzzy logic-based classifiers by rule extraction and input selection. Finally, we can verify and compare performances. With actual occurrence cased of the anomalous propagation echo, we can determine the inner structures of the black-box classifiers.

• Journal of Pharmaceutical Investigation
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• v.25 no.3
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• pp.185-192
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• 1995

Precipitation reaction occured between berberine in Coptidis Rhizoma and glycyrrhizin in Glycyrrhizae Radix when they were boiled together in aqueous solution and the supernatant solution thus obtained did not show any antibacterial activity which was derived from berberine. The content of berberine in BG and CGP by HPLC analysis were 41.1%, 8.3% respectively. BG was occured mostly at pH 5.0. The solubility of berberine was 0.15%, while that of BG and CGP was 0.07%, 0.12%, respectively. CGP shown more increased antibacterial activity to gram positive bacteria, S. dysenteriae and K. pneumoniae than berberine. The absorption rates of CGP in stomach, duodenum and jejunum of rats were compared with those of Coptidis Rhizoma water extracts (CR), which were increased more than CR. The time required for the maximum serum concentration of berberine from CGP in mice was 90 minutes after oral administration. The maximum serum concentration of berberine from CGP was higher than that from CR. The dissolution of CGP was increased more than berberine and BG in both artificial gastric and intestinal fluids. The dissolution of CGP pill made from gelatin was 63.4% in artificial gastric fluids and that made from CMC was 76.0% in artificial intestinal fluids.

• Journal of the Korean Ceramic Society
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• v.53 no.6
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• pp.670-675
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• 2016

Calcium phosphate crystallites were prepared by wet chemical method for use in artificial bone. In order to obtain ${\beta}$-tricalcium phosphate (TCP), nano-crystalline calcium phosphate (CaP) was precipitated at $37^{\circ}C$ and at $pH5.0{\pm}0.1$ under stirring using highly active $Ca(OH)_2$ in DI water and an aqueous solution of $H_3PO_4$. The precipitated nano-crystalline CaP solution was kept at $90^{\circ}C$ for the growth of CaP crystallites. Through the growing process of CaP crystallites, we were able to obtain various sizes of rectangular CaP crystallites according to the crystal growing times. Dry nano-crystalline CaP powders at $37^{\circ}C$ were mixed with dry macro-crystalline CaP crystallites and the shaped mixture sample was fired at $1150^{\circ}C$ to make a ${\beta}-TCP$ block. Several tens of nm powders were uniformly coated on the surface, which was comprised of powders of several tens of ${\mu}m$, using a vibrator. The mixing ratio between the nanometer powders and the micrometer powders greatly affected the mechanical strength of the mixture block; the most appropriate ratio of these two materials was 50 wt% to 50 wt%. The sintered block showed improved mechanical strength, which was caused by the solid state interaction between the nano-crystalline ${\beta}-TCP$ and the macro-crystalline ${\beta}-TCP$.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1235-1240
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• 2019

It is well known that the ground water level changes rapidly before and after the earthquake, and the variation of ground water level prediction is used to predict the earthquake. In this paper, we predict the ground water level in Miryang City using ANFIS algorithm for earthquake prediction. For this purpose, this paper used precipitation and temperature acquired from National Weather Service and data of underground water level from Rural Groundwater Observation Network of Korea Rural Community Corporation which is installed in Miryang city, Gyeongsangnam-do. We measure the prediction accuracy using RMSE and MAPE calculation methods. As a result of the prediction, the periodic pattern was predicted by natural factors, but the change value of ground water level was changed by other variables such as artificial factors that was not detected. To solve this problem, it is necessary to digitize the ground water level by numerically quantifying artificial variables, and to measure the precipitation and pressure according to the exact location of the observation ball measuring the ground water level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1732-1739
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• 2004

In this paper, we proposed a visualization system with ANN algorithm that traits the motion of particles that move colliding in the water, where we got a great deal of variable information and predicts the distribution of particles according to the flowing of water and the pattern of their precipitation. We adopted ART2 to detect sensitively the collision between particles in this visualzation. Various particles and their mutual collision influencing the force such as buoyancy force, gravitational force, and the pattern of precipitation are considered in this system. Flowing particles whose motion is changed with the environment can be visualized in the system presented here as they are in real water.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.1-11
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• 2019

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.