• Tunnel and Underground Space
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• v.34 no.4
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• pp.393-412
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• 2024

In selecting a disposal site for high-level radioactive waste, the hydrogeological research of the site is very important, and the hydraulic conductivity and the storage coefficient are key parameters. In this study, the hydraulic conductivity obtained by two different types of field hydraulic test equipment and methods was compared and analyzed for the deep granite rockmass in the Wonju area to understand the hydraulic characteristics of the deep granite rockmass. One was to perform the lugeon test, constant pressure injection test, and slug test at a maximum depth of 602.0 m by using the auto pressure/flow injection system, and the calculated hydraulic conductivity ranged from 1.26E-9 to 4.16E-8 m/s. In the overall depth, the maximum and minimum differences of the hydraulic conductivity were found to be about 33 times, and in the same test section, the difference by test method or analysis method was 1.13 to 8.25 times. In the other, the hydraulic conductivity calculated by performing a constant pressure injection test and a pulse test at a maximum depth of 705.1 m using the deep borehole hydraulic testing system was found to be 1.60E-10 to 2.05E-8 m/s, and the maximum and minimum differences were found to be about 130 times. In the constant pressure injection test, the difference depending on the analysis method was found to be 1.02 to 2.8 times. The hydraulic conductivity calculated by the two test equipment and methods generally showed similar ranges as E-9 and E-8 m/s, and no clear trend was observed according to depth. It was found that the granite rockmass in the Wonju area where the field hydraulic test was conducted showed low or very low rockmass permeability, and although there are differences in the range of hydraulic conductivity and the depth of application that can be measured depending on the applied test equipment and test method, it is generally believed that reliable results were presented.

• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.3
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• pp.25-37
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• 1988

The purpose of this study is to fmd out the bask data for irrigation plans of tomato and chinese cabbage during the growing period, such as total amount of evapotranspiration, coefficients of evapotranspiration at each growth stage, the peak stage of evapotranspiration, the maximum evapotranspiration, optimum irrigation point, total readily available moisture and intervals of irrigation date. The plots of experiment were arranged with split plot design which were composed of two factors, irrigation point for main plot and soji texture for split plot, and three levels, irrigation points with PF 1.8, PF 2.2, PF 2.6 for tomato and those with PF 1.9, PF 2.3, PF 2.7, for Chinese cabbage, soil textures of silty clay, sandy loam and sandy soil for both tomato and Chinese cabbage, with two replications. The results obtained are summarized as follows 1. There was the highest significant correlation between the evapotranspiration and the pan evaporation, beyond all other meteoralogical factors considered. Therefore, the pan evaporation is enough to be used as a meteorological index measuring the quantity of evapotranspiration. 2. 1/10 probability values of maximum total pan evaporation during growing period for tomato and Chinese cabbage were shown as 355.8 mm and 233.0 mm, respectively, and those of maximum ten day pan evaporation for tomato and Chinese cabbage, 68.0 mm and 43.8 mm, respectively. 3. The time that annual maximum of ten day pan evaporation can be occurred, exists at any stage of growing period for tomato, and at any growth stage till the late of Septemberfor Chinese cabbage. 4. The magnitude of evapotranspiration and of its coefficient for tomato and Chinese cabbage was occurred in the order of pF 1.8>pF 2.2>pF 2.6 and of pF 1.9>pF 2.3>pF 2.7 respectively in aspect of irrigation point and of silty clay>sandy loam>sandy soil in aspect of soil texture. 5. 1/10 probability value of evapotranspiration and its coefficient during the growing period of tomato were shown as 327.3 mm and 0.92 respectively, while those of Chinese cabbage, 261.0 mm and 1.12 respectively. 6. The time that maximum evapotranspiration of tomato can be occurred is at the date of fortieth to fiftieth after transplanting and the time for Chinese cabbage is presumed to he in the late of septemben At that time, 1/10 probability value of ten day evapotranspiration and its coefficient for tomato is presumed to be 74.8 mm and 1.10 respectively, while those of Chinese cabbage, 43.8 mm and 1.00. 7. In aspect of only irrigaton point, the weight of raw tomato and Chinese cabbage were mcreased in the order of pF 2.2>pF 1.8>pF 2.6 and of pF 1.9>pF 2.3>pF 2.7, respectively but optimum irrigation point for tomato and Chinese cabbage, is presumed to be pF 2.6 - 2.7 if nonsignificance of the yield between the different irrigation treatments, economy of water, and reduction in labour of irrigaion are synthetically considered. 8. The soil moisture extraction patterns of tomato and Chinese cabbage have shown that maximum extraction rate exists at 7 cm deep layer at the beginning stage of growth m any soil texture and that extraction rates of 21 cm to 35 cm deep layer are increased as getting closer to the late stage of growth. And especially the extraction rates of 21 cm deep layer and 35 cm deep layer have shown tendency to be more increased in silty clay than in any other soils. 9. As optimum irrigation point is presumed to be pF Z6-2.7, total readily available moisture of tomato in silty clay, sandy loam and sandy sofl becomes to be 19.06 mm, 21.37 mm and 20.91 mm respectively while that of Chinese cabbage, 18.51 mm, 20.27 mm, 21.11 mm respectively. 10. On the basis of optimum irrigation point with pF 2.6 - 2.7 the intervals of irrigation date of tomato and Chinese cabbage at the growth stage of maximum consumptive use become to be three days and five days respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.21-30
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• 2014

Lately, new influentials have secured a large number of volunteers on social networks due to vitalization of various social media. There has been considerable research on these influential people in social networks but the research has limitations on location information of Location Based Social Network Service(LBSNS). Therefore, the purpose of this study is to propose a spatial detection methodology and application plan for influentials who make comments about diverse social and cultural issues in LBSNS using spatial statistical analysis methods. Twitter was used to collect analysis object data and 168,040 Twitter messages were collected in Seoul over a month-long period. In addition, 'politics,' 'economy,' and 'IT' were set as categories and hot issue keywords as given categories. Therefore, it was possible to come up with an exposure index for searching influentials in respect to hot issue keywords, and exposure index by administrative units of Seoul was calculated through a spatial joint operation. Moreover, an influential index that considers the spatial dependence of the exposure index was drawn to extract information on the influential areas at the top 5% of the influential index and analyze the spatial distribution characteristics and spatial correlation. The experimental results demonstrated that spatial correlation coefficient was relatively high at more than 0.3 in same categories, and correlation coefficient between politics category and economy category was also more than 0.3. On the other hand, correlation coefficient between politics category and IT category was very low at 0.18, and between economy category and IT category was also very weak at 0.15. This study has a significance for materialization of influentials from spatial information perspective, and can be usefully utilized in the field of gCRM in the future.

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.3
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• pp.41-56
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• 1989

The purpose of this study is to find out the basic data for irrigation plans of garlic and cucumber during the growing period, such as total amount of evapotranspiration, coefficients of evapotranspiration at each growth stage, the peak stage of evapotranspiration and the maximum evapotranspiraton, optimum irrigation point, total readily available moisture, and intervals of irrigation date. The plots of experiment were arranged with split plot design which were composed of two factors, irrigation point for main plot and soil texture for split plot, and three levels ; irrigation points with pP 1.7-2.1, pP 2.2-2.5, pP 2.6-2.8, for garlic and those with pP 1.9, pF 2.3, pP 2.7, for cucumber, soil textures of silty clay, sandy loam and sandy soil for both garlic and cucumber, with two replications. The results obtained are summarized as follows 1.There was the highest significant correlation between the avapotranspiration of garlic and cucumber and the pan evaporation, beyond all other meteorological factors considered, as mentioned in the previous paper. Therefore, the pan evaporation is enough to be used as a meteorological index measuring the quantity of evapotranspiration. 2.1/10 probability values of maximum total pan evaporation during growing period for garlic and cucumber were shown as 495.8mm and 406.8mm, respectively, and those of maximum ten day pan evaporation for garlic and cucumber, 63.8mm and 69.7mm, respectively. 3.The time that annual maximum of ten day pan evaporation can be occurred, exists at any stage between the middle of May and the late of June(harvest period) for garlic, and at any stage of growing period for cucumber. 4.The magnitude of evapotranspiration and of its coefficient for garlic and cucumber was occurred in the order of pF 1.7-2.1>pF 2.2-2.5>pF 2.6-2.8 and of pF 1.9>pF 2.3>pF2.7 respectively in aspect of irrigation point and of sandy loam>silty clay>sandy soil in aspect of soil texture for both garlic and cucumber. 5.The magnitude of leaf area index was shown in the order of pF 2.2-2.5>pF 1.7-2.1>pF 2.6-2.8 for garlic and of pF 1.9>pF 2.3>pF 2.7 for cucumber in aspect of irrigation point, and of sandy loam>sandy soil>silty clay in aspect of soil texture for both garlic and cucumber. 6.1/10 probability value of evapotranspiration and its coefficient during the growing period for garlic were shown as 391.7mm and 0.79 respectively, while those of cucumber, 423.lmm and 1.04 respectively. 7.The time the maximum evapotranspiration of garlic can be occurred is at the date of thirtieth before harvest period and the time for cucumber is presumed to be at the date of sixtieth to seventieth after transplanting, At that time, 1/10 probability value of ten day evapotranspiration and its coefficient for garlic is presumed to be 65.lmm and 1.02 respectively, while those of cucumber, 94.8mm and 1.36 respectively. 8.In aspect of irrigation point, the weight of raw garlic and cucumber were increased in the order of pF 2.2-2.5>pF 1.7-2.1>pF 2.6-2.8 and of pF 1.9>pF 2.3>pF 2.7 respectively. Therefore, optimum irrigation point for garlic and cucumber is presumed to be pF 2.2-2.5 and pF 1.9 respectively, when the significance of yield between the different irrigation treatments is considered. 9.Except the mulching period of garlic that soil moisture extraction patterns were about the same, those of garlic and cucumber have shown that maximum extraction rate exists at 7cm deep layer at the beginning stage after removing mulching for garlic and at the beginning stage of growth for cucumber and that extraction rates of 21cm to 35cm deep layer are increased as getting closer to the late stage of growth. 10.Total readily available moisture of garlic in silty clay, sandy loam, sandy soil become to be 18.71-24.96mm, 19.08-25.43mm, 10.35- 13.80mm respctively on the basis of the optimum irrigation point with pF 2.2-2.5, while that of cucumber, 11.8lmm, 12.03mm, 6.39mm respectively on the basis of the optimum irrigation point with pF 1.9. 11.The intervals of irrigation date of garlic and cucumber at the growth stage of maximum consumptive use become to be about three and a half days and one and a half days respectively, on the basis of each optimum irrgation point.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.17-24
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• 2011

Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.255-264
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• 2019

In this study, we conducted the hot box tests to compare the changes in thermal insulation for the four types of multi-layer thermal screens by the used period after collecting them from the greenhouses in the field when they were replaced at the end of their usage. The main materials for these four types of multi-layer thermal screens were matt georgette, non-woven fabrics, polyethylene (PE) foam, chemical cotton, etc. These materials were differently combined for each multi-layer thermal screen. We built specimens ($70{\times}70cm$) for each of these multi-layer thermal screens and measured the temperature descending rate, heat transmission coefficient, and thermal resistance for each specimen through the hot box tests. With regard to the material combinations of multi-layer thermal screens, thermal insulation can be increased by applying a multi-layered PE foam. However, it is considered that the multi-layered PE foam significantly less contributes to heat-retaining than chemical wool that forms an air-insulating layer inside multi-layer thermal screens. For the suitable heat-retaining performance of multi-layer thermal screens, basically, materials with the function of forming an air-insulating layer such as chemical cotton should be contained in multi-layer thermal screens. The temperature descending rate, heat transmission coefficient, and thermal resistance of multi-layer thermal screens were appropriately measured through the hot box tests designed in this study. However, in this study, we took into consideration only the four kinds of multi-layer thermal screens due to difficulties in collecting used multi-layer thermal screens. This is the results obtained with relatively few examples and it is the limit of this study. In the future, more cases should be investigated and supplemented through related research.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.366-376
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• 2023

This study was conducted to develop a model for predicting the growth of kimchi cabbage using image data and environmental data. Kimchi cabbages of the 'Cheongmyeong Gaual' variety were planted three times on July 11th, July 19th, and July 27th at a test field located at Pyeongchang-gun, Gangwon-do (37°37' N 128°32' E, 510 elevation), and data on growth, images, and environmental conditions were collected until September 12th. To select key factors for the kimchi cabbage growth prediction model, a correlation analysis was conducted using the collected growth data and meteorological data. The correlation coefficient between fresh weight and growth degree days (GDD) and between fresh weight and integrated solar radiation showed a high correlation coefficient of 0.88. Additionally, fresh weight had significant correlations with height and leaf area of kimchi cabbages, with correlation coefficients of 0.78 and 0.79, respectively. Canopy coverage was selected from the image data and GDD was selected from the environmental data based on references from previous researches. A prediction model for kimchi cabbage of biomass, leaf count, and leaf area was developed by combining GDD, canopy coverage and growth data. Single-factor models, including quadratic, sigmoid, and logistic models, were created and the sigmoid prediction model showed the best explanatory power according to the evaluation results. Developing a multi-factor growth prediction model by combining GDD and canopy coverage resulted in improved determination coefficients of 0.9, 0.95, and 0.89 for biomass, leaf count, and leaf area, respectively, compared to single-factor prediction models. To validate the developed model, validation was conducted and the determination coefficient between measured and predicted fresh weight was 0.91, with an RMSE of 134.2 g, indicating high prediction accuracy. In the past, kimchi cabbage growth prediction was often based on meteorological or image data, which resulted in low predictive accuracy due to the inability to reflect on-site conditions or the heading up of kimchi cabbage. Combining these two prediction methods is expected to enhance the accuracy of crop yield predictions by compensating for the weaknesses of each observation method.

• Korean Journal of Soil Science and Fertilizer
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• v.8 no.1
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• pp.1-17
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• 1975

Laboratory experiments on the phosphorus adsorption by soil were conducted to evaluate the parameters for determination of phosphorus adsorption capacity of soil, which serve as a basis for establishing the amount of phosphorus required to improve newly reclaimed soil and volcanic ash soil. The calculated Langmuir adsorption maxima varied from 6.2-32.9, 74.7-90.4 and 720-915mg p/100g soil for cultivated soils, non-cultivated soils, and volcanic ash soils respectively. The phosphorus absorption coefficient ranged from 116-179, 161-259 and 1,098-1,205mg p/100g soil for cultivated soils, non-cultivated soils, and volcanic ash soils respectively. The ratio of the phosphorus absorption coefficient to Langmuir adsorption maximum was low in soils of high phosphorus adsorption capacity (1.3-1.5) and high in soils of low phosphorus adsorption capacity (2.2-18.7). Changes in the amount of phosphurus adsorption induced by liming and preaddition of phosphorus were hadly detected by the phosphorus absorption coefficient, which is measured using a test solution with a relatively high phosphorus concentration. The Langmuir adsorption maximum was a more sensitive index of the phosphorus adsorption capacity. The Langmuir adsorption maxima of the non-cultivated soils, which were treated with an amount of calcium hydroxide equivalent to the exchangeable Al and incubated ($25-30^{\circ}C$) for 40 days at field capacity, were lower than the original soils. The change in the adorption maximum on incubation following the liming of soils was insignificant for other soils. The secondary adsorption maximum of soils, which received phosphorus equivalent to the Langmuir adsorption maximum of the limed soils incubated ($25-30^{\circ}C$) for 50 days at held capacity, was 74.5, 5.6 and 23.8% of the primary adsorption maximum for volcanic ash soils, non-cultivated soils, and cultivated soils respectively. The amount of phosphorus adsorbed by soils increased quadratically with the concentration of phosphorus solution added to the soils. The amount of phosphorus adsorbed by 5-g soil samples from 100ml of 100- and 1,000mg p/l solution for the mineral soils and volcanic ash soils respectively was found to be close to the Langmuir adsorption maximum. The amount of the phosphorus adsorbed at these concentrations is defined as a saturation adsorption maximum and proposed as a new parameter for the phosphorus adsorption capacity of the soil. The evaluation of the phosphorus adsorption capacity by the saturation adsorption maximum is regarded as a more practical method in that it obviates the need for the various concentrations used for the determination of the Langmuir adsorption maximum.