• Korean Journal of Soil Science and Fertilizer
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• v.38 no.4
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• pp.222-229
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• 2005

A simplified one-dimensional model STELLA was used to predict soil water movement in lllinois corn fields using soil water balance sheets. It offered the potential to increase understanding of soil nitrate and agrochemical leaching process. The model accounted for aU possible annual inputs and outputs of water from a closed ecosystem as represented by corn fields. Water inputs included precipitation, while outputs included runoff, transpiration, evaporation and drainage. To run the model required daily inputs of two climatic data measurements such as daily precipitation and pan evaporation. Vertical water flow through the soil profile was calculated with first order equation including the difference in hydraulic conductivity and matric potential at the various soil types. The output results included daily changes of water content in the soil layers and daily amount of water losses including run-off, percolation, transpiration. This model was verified using Illinois corn field data for the soil water content measured by neutron scattering methods through 1992 to 1994 growing seasons. Approximately 22 to 78% of simulated water contents agreed with the measured values and their standard deviation, depending on soil types, whereas 30 to 70% of simulated water values agreed with the measured values and their standard deviations depending on soil layers.

• Korean Journal of Soil Science and Fertilizer
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• v.28 no.2
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• pp.160-164
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• 1995

This study was conducted to obtain quantitative data on the behavior of surface-applied urea to a paddy field which would help to protect against environmental pollution as well as to increase the efficiency of nitrogen fertilizer. The percolating water samples were collected with porous ceramic cups installed at 25, 50 and 75cm depths in a paddy field during the rice growing season(June 1992-September 1992) and analyzed for urea-N. NHAN and $NO_3-N$. In the paddy field to which urea fertilizer was applied at the rates of 12 and 24kg N/10a, the surface-applied urea was detected even at 75cm depth as the form of urea-N upto 12days after application. The maximum concentrations of urea-N in the percolating water sampled at 25, 50 and 75cm depths were the same irrespective of soil depth and the values were 0.06 and $0.12{\mu}g/m{\ell}$ for the application rates of 12 and 24kg N/10a respectively. The concentrations of $NH_4-N$ gradually decreased with time during the vegetative growth period : thereafter. the concentrations remained nearly constant. The maximum concentrations of $NH_4-N$ at 25cm depth were 1.2 and $5.6{\mu}g/m{\ell}$ for 12 and 24kg N/10a rate respectively. The $NO_3-N$ concentrations of percolating water ranged 0.1~0.5 and $0.2{\sim}0.5{\mu}g/m{\ell}$ for urea application rates of 12 and 24kg N/10a respectively. The nitrate concentration data suggest that nitrification process occurred continuously in paddy field during the rice growing season.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.129-136
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• 2006

Engineered mixtures, which consist of rigid sand particles and soft fine-grained rubber particles, are tested to characterize their small and large-strain responses. Engineered soils are prepared with different volumetric sand fraction, sf, to identify the transition from a rigid to a soft granular skeleton using wave propagation, $K_{o}-loading$, and triaxial testing. Deformation moduli at small, middle and large-strain do not change linearly with the volume fraction of rigid particles; instead, deformation moduli increase dramatically when the sand fraction exceeds a threshold value between sf=0.6 to 0.8 that marks the formation of a percolating network of stiff particles. The friction angle increases with the volume fraction of rigid particles. Conversely, the axial strain at peak strength increases with the content of soft particles, and no apparent peak strength is observed in specimens when sand fraction is less than 60%. The presence of soft particles alters the formation of force chains. While soft particles are not part of high-load carrying chains, they play the important role of preventing the buckling of stiff particle chains.

• Korean Journal of Soil Science and Fertilizer
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• v.7 no.2
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• pp.71-97
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• 1974

Many studies on the changes of the materials in the water-logged paddy soil have been reported, but there will be several problems to apply them on the field soil. The main differences between the method of soil packed in beaker or column tube to that of natural field furrow slice are with or without of the rice root and the effect of water percolation. On the other hand, the mechanism of the water percolation on the changes of material in the natural field furrow slice are gradually understood. The purpose of this experiment is to know the effect of the rice cultivation on the chemical and physical changes of material in the water-logged paddy soil. Obtained results are as follows. 1. The physical and chemical changes on the water-logged paddy soil in the non-planted control-plot were nearly the same as the beaker or column tube experiment, while in the planted plot, slightly altered patterns were observed. 2. The relation between the number of tillers and total cation, $Ca^{{+}{+}}$, $Mg^{{+}{+}}$, Fe and Mn in the leachate showed very high significance. T hisresult showed that the leaching of those cation was promoted by growing of the rice r- of the rice root. 3. On the other hand, the concentration of the potassium, silica and phosphorus in leachates was gradually decreased and that of $NH_4$-N could not detect after the stage of active tillering. These facts revealed that such components were absorbed by rice plant. 4. The highly significant correlation between the number of tillers and the concentration of the total cation, $Ca^{{+}{+}}$, $Mg^{{+}{+}}$, $Fe^{{+}{+}}$, Fe and Mn in the percolated water was observed except that of $Mg^{{+}{+}}$. It was also showed that the rice root promoted the leaching of those cation. 5. The very high significance in the correlation between $HCO_3{^-}$ and the number of tillers indicated that the higher activity of the rice root was, the more $HCO_3{^-}$ concentration in the leachate was increased. 6. The relationship between the $HCO_3{^-}$ and the total cation, $Ca^{{+}{+}}$, $Mg^{{+}{+}}$, $Fe^{{+}{+}}$, Fe and Mn was appeared very highly significant. $HCO_3{^-}$, the metabolite of the rice root, promoted the leaching of $Ca^{{+}{+}}$, $Mg^{{+}{+}}$, $Fe^{{+}{+}}$ and Mn. This fact might be a result that these cations were leached as the form of bicarbonate. 7. The iron in the leachate was the form of $Fe^{{+}{+}}$ and the correlation between $Fe^{{+}{+}}$ and $HCO_3{^-}$ was very highly significant. This result indicated that it seemed to be ferrous bicarbonate when it is leached out. 8. In the rhizosphere, ferrous iron was decreased gradually and the concentration of glucose was as high as 2 to 3 times in comparison with the other parts of the soil. These facts were the same as the previous reports in which rhizosphere was oxidized by the oxigen excreted from the root, and was enriched by the organic matter which was also excreted from the root and accumulated residues of the root. 9. ${\beta}$-Glucosidase and phosphatase activity in the rhizosphere was higher than that of the other parts of the soil. This facts might be attributed to the vigorous activity of microorganism in the rhizosphere where glucose concentration was high. 10. The pH in the leachate of the planted plot was lower than that of control, and the Eh on the planted soil was elevated in the last stage.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.1
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• pp.31-38
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• 1999

Rainfall factor. R, and soil factor, K were estimated to use the Revised Universal Soil Loss Equation (RUSLE) to predict the amount of soil erosion from a land on slope in Kangwon-do, Korea. The average of R factor was 405 with a range from 251 to 601. The R factor differed among regions. The R factor at Taegwalryung, in the highland region, was 409 and those at Inje and Hongchon, in the mid mountainous regions, ranged from 310 to 493. The R factors at Wonju and Chuncheon, in the plain regions, ranged from 505 to 601. The R factors at Sokcho, Kangnung and Samchok, in the east coastal region, which ranged from 251 to 368, were lowee than those in the western part of the Taebaeg Mountains. The R factor during the winter including the effect of winter freezing and thawing was 12 to 30% of the annual average value in the east coastal and highland regions, while that in the western part of Taebaeg Mountains was lower than 7%. The average of K factor in the surface soil was 0.21 with a range from 0.06 to 0.42. The K factors of Odae and Weoljeong serieses were the lowest, while that of Imog was the highest. The average of K factor in the subsoil was 0.28 with a range from 0.07 to 0.45. The K factor of the subsoil was 1.3 times higher than that of top soil. The average of K factor in he soil including the effect of the gravel covering and percolation was 0.18 with a range from 0.03 to 0.33. In contrast. the K factor excluding the effect of the gravel covering was lower than this. The average of K factor in the frozen subsoil was 0.33, which was 1.6 times higher than that of the non frozen subsoil.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.2
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• pp.157-166
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• 1995

The fate and use efficiency of applied nitrogen were evaluated in a pot experiment with different fertilizers and water management practices during 30days after fertilizer application. N-P-K compound fertilizers, 13-10-1l(F-l) for upland Crop use and 15-10-10(F-3) for rice Crop use, and mixed fertilizer, 21-17-17(F-2) for basal dressing in rice were used. Fertilizers corresponding to 1.8g N were mixed thoroughly with the whole volume of sandy loam soil in a pot. The pots were flooded upto 3cm above soil surface for O(0dF), 10(10dF), 20(20dF), and 30(30dF) days after fertilizer application and all the treatments were flooded continuously from 30 days after fertilizer application. During the flooding period water percolation rate was adjusted to 2.5mm/day. Rice seedlings were transplanted 40 days after fertilizer application. The pH of infiltrated water increased with increasing duration of flooding. The pH of F-2 was higher than those of F-1 and F-3 between which there were no differences. The applied nitrogen remained 23% in F-1, 29% in F-2, and 29.1 % in F-3, and 45.0% in 0dF, 26.6% in 10dF, 24.8% in 20dF, and 20.3% in 30dF as inorganic nitrogen at 63 days after fertilizer application. Nitrogen losses by leaching amounted to 51.3%, 32.1% and 48.1% of applied nitrogen in F-1, F-2 and F-3, respectively. Nitrogen leaching losses increased with increasing duration of flood- ing, amounting to 25.7%, 29.8%, 32.7%, and 35.8% in 0dF, 10dF, 20dF and 30dF, respectively. Gaseous loss of applied nitrogen was greatest in F-2, followed by F-1 and F-3. Total loss of nitrogen due to gaseous volatilization and leaching was greatest in F -1, followed by F -2 and F-3, and were greater in the treatments with longer flooding after fertilizer application. Nitrogen recovery by rice shoot until 72 days after transplanting were 23.2%, 24.7% and 27.4% of applied nitrogen in F-1, F-2 and F-3, respectively and 34.1%, 25.5%, 21.1%, and 21.2% in 0dF, 10dF, 20dF and 30dF, respectively.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Korean Journal of Environmental Agriculture
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• v.27 no.3
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• pp.225-230
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• 2008

Objective of this study was to access the environmental impacts of the use of discharge water from municipal waste water treatment plant as alternative irrigation resources during drought season for rice cultivation. For the field experiments, it was observed that plant growth and yield characteristics at 20 days of alternative irrigation period with application of FAST (fertilizer application based on soil test) 50% were relatively the same as the control. For the surface water quality, it appeared that $EC_i$ (electrical conductivity of irrigation water) and SAR (sodium adsorption ratio) values of DMWT (discharge waters from municipal wastewater treatment plant) irrigation were twofold higher than those of ground water irrigation as the control regardless of fertilization levels. For the irrigation periods, there were not significantly difference between 10 and 20 days of treatments, but $EC_i$ and SAR values of surface water were highest at 30 days of irrigation periods at initial rice growing stages. Generally, $EC_i$ values of percolation water in all the treatments were gradually increasing until 30days after irrigation, and then decreasing to harvest stage. Overall, it might be considered that there was possibility to irrigate DMWT with application of FAST 50% for 20 days of drought periods at rice transplanting season. Furthermore, efficiency rate of alternative irrigation water for 20 days of drought period was 32.7% relative to the total annual irrigation water for rice cultivation.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.1203-1210
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• 2012

As the area of upland crops increase, it is become more important for farmers to understand status of soil water at their own fields due to key role of proper irrigation. In order to estimate daily water balance and soil water content with simple weather data and irrigation records, we have developed the model for estimating water balance and soil water content, called AFKAE0.5, and verified its simulated results comparing with daily change of soil water content observed by soil profile moisture sensors. AFKAE0.5 has two hypothesis before establishing its system. The first is the soil in the model has 300 mm in depth with soil texture. And the second is to simplify water movement between the subjected soil and beneath soil dividing 3 categories which is defined by soil water potential. AFKAE0.5 characterized with determining the amount of upward and downward water between the subjected soil and beneath soil. As a result of simulation of AFKAE0.5 at Gongju region with red pepper cultivation in 2005, the water balance with input minus output is recorded as - 88 mm. the amount of input water as precipitation, irrigation, and upward water is annually 1,043, 0, and 207 mm, on the other, output as evapotranspiration, run-off, and percolation is 831, 309, and 161 mm, respectively.

• Applied Biological Chemistry
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• v.44 no.2
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• pp.97-102
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• 2001

Cheju island depends on a hydrogeologically vulnerable aquifer system as its principle source of drinking water. Most of golf courses are located in the area which is important for the ground water recharge, and pesticides are applied to golf courses often at relatively high rates. Therefore, turf pesticides in golf course should be applied without adversely impacting ground water. In this experiment, downward movement of pesticides was monitored in model greens of golf course, where different adsorbents were layered in 3-cm thickness at 35-cm depth, and effect of the adsorption layer on the leaching loss of pesticides was investigated. Major leachings were observed in the periods of heavy rain and very limited leaching was observed under artificial irrigation. Fenitrothion and triadimefon, which have relatively short persistence and high adsorption coefficient, were found in the leachate in low concentrations only at the first rainfall event, around 20 days after the pesticide application. However, diniconazole, which has a relatively long half-life (97 days), was detected in the leachate during the whole period of experiment and concentration was much higher than those of the other pesticides. Maximum leachate concentrations were 1.9, 10.3, and 84.5 ${\mu}l^{-1}$ for fenitrothion, triadimefon, and diniconazole, respectively. Therefore, in golf course green which allows rapid water percolation and has extremely low adsorption capacity, persistence in soil could be more important factor in determination of leaching potential of pesticides. Total quantity of pesticides leached from the model green was <0.2% for fenitrothion and triadimefon and 1.8% for diniconazole. Adsorption layers significantly reduced pesticide leaching, and active carbon and Orpar were more effective than zeolite. In the model green having adsorption layer of active carbon or Orpar, leaching loss of pesticides was reduced below 0.01% of the initial application.