• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.107-117
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• 2010

The feature models representing the common and variable concepts among the software products and the feature configurations generated by selecting the features to be included in the target product are the essential components in the software product lines methodology. Although the researches on the formal semantics and reasoning of the feature models and feature configurations are in progress, the researches on feature model ontologies and feature configuration validation using the semantic web technologies are yet insufficient. This paper defines the formal semantics of the feature models and proposes a feature configuration validation technique based on ontology and semantic web technologies. OWL(Web Ontology Language), a semantic web standard language, is used to represent the knowledge in the feature models and the feature configurations. SWRL(Semantic Web Rule Language), a semantic web rule languages, is used to define the rules to validate the feature configurations. The approach in this paper provides the formal semantic of the feature models, automates the validation of feature configurations, and enables the application of various semantic web technologies, such as SQWRL.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.3
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• pp.209-216
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• 2001

A numerical study is peformed to investigate the effect of circumferential velocity generated by the guide vane on the nozzle flow of a jet fan, s a way of increasing the penetration force of jet fan with nozzle of 175mm diameter. For the validation of numerical results. the velocity is measured by a 5-hole pitot tube and flow visualization is conducted by the tuft method. Under the inlet condition that the maximum circumferential velocity in the stator outlet of the present jet fan is 1.8m/s, the axial velocity in the nozzle outlet has the feature that the velocity at the axis is low and the velocity near the wall high. Therefore, to increase the throw length of the jet fan, the configuration of the fairing and nozzle needs to be developed and the precise revise of the stator angle is required, In addition, the bigger the circumferential velocity, the smaller the axial velocity at the axis and the bigger non-uniformity of the flow distribution.

• Journal of The Geomorphological Association of Korea
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• v.23 no.3
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• pp.67-78
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• 2016

Soil carbon(C) is an essential property for characterizing soil quality. Understanding spatial patterns of soil C is particularly limited for mountain areas. This study aims to predict the spatial pattern of soil C using terrain analysis in a steep mountainous area. Specifically, model performances and prediction uncertainties were investigated based on the number of resampling repetitions. Further, important predictors for soil C were also identified. Finally, the spatial distribution of uncertainty was analyzed. A total of 91 soil samples were collected via conditioned latin hypercube sampling and a digital soil C map was developed using support vector regression which is one of the powerful machine learning methods. Results showed that there were no distinct differences of model performances depending on the number of repetitions except for 10-fold cross validation. For soil C, elevation and surface curvature were selected as important predictors by recursive feature elimination. Soil C showed higher values in higher elevation and concave slopes. The spatial pattern of soil C might possibly reflect lateral movement of water and materials along the surface configuration of the study area. The higher values of uncertainty in higher elevation and concave slopes might be related to geomorphological characteristics of the research area and the sampling design. This study is believed to provide a better understanding of the relationship between geomorphology and soil C in the mountainous ecosystem.