• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.183-198
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• 2011

With the recent development of IT technology, the existing contents have been digitalized through various distribution channels. Accordingly, a lot of studies have been done in order to figure out the distribution and features of digital contents, In these studies, however, categorical characteristics of digital contents were not considered ; most of the previous researchers saw digital contents as only a single item or focused on some contents within particular part such as movie, music, etc. So, this study divides digital contents into movies, music and texts. I was going to study which factors affect Customer Satisfaction in relation with the kind of contents. With SERVQUAL as independent variables, which affect the Customer satisfaction, I used five factors :Design Quality, Information Quality, Security Quality, Communication Quality and Transaction Quality. As for the detailed items, I corrected them with Open-End Question and Pre Survey Research, which are more fit into the features of digital contents. This research conducted Principle Component Analysis, Reliability Test, Correlation Analysis and Regression Analysis. I verified that each factor of Service Qualities has a positive effect on Customer Satisfaction. Moreover, the factors of the effect are different according to the kind of digital contents. This paper was added Exploratory Study to find the best distribute channel. For the study, I search the possible distribute channel in each digital contents and their characteristic.