Browsing by Author "Yang, KS"

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Characteristics of air-water two-phase flow in a 3-mm smooth tube
(2000-10-01)
Wang, CC
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Yang, KS
;
Chang, YJ
;
Lu, DC
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機械工程學系
Two-phase flow pattern and friction characteristics for an air-water system in a 3.17 mm smooth tube are reported in this study. The range of mass flux is between 50 and 700 kg/m(2)s. The experimental data show that the two-phase friction multipliers are strongly related to the flow pattern. For a stratified-wavy flow pattern, a mass-flux dependence of the two-phase multipliers is seen. For a non-stratified flow pattern, the two-phase frictional multipliers are comparatively independent of mass flux. Correlations of the frictional multipliers are developed for stratified and non-stratified flow. To use the appropriate correlation in different regime, a simple criterion is proposed.
K-support system: Knowledge support for disseminating and sharing task-relevant knowledge
(2004)
Wu, IC
;
Liu, DR
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Yang, KS
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
In task-based business environments, an important issue in deploying Knowledge Management Systems (KMS) is providing task-relevant information to fuflll the information needs of knowledge workers. This work develops a Knowledge Support (K-Support) system providing a collaborative task-based workplace to facilitate knowledge retrieval and sharing among peer-groups. In the developed system, an adaptive task-based profiling approach is proposed to model worker's information needs (profiles), while a fuzzy analytical method is proposed to identify peer-groups with similar task-interests based on workers' profiles. The K-Support system is grounded in a research institute to effectively stimulate task-based knowledge retrieval and sharing.
Task-based K-Support system: disseminating and sharing task-relevant knowledge
(2005-08-01)
Liu, DR
;
Wu, IC
;
Yang, KS
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
In task-based business environments, effective knowledge management relies on providing task-relevant information to fulfill the information needs of knowledge workers. This work proposes an adaptive task-based profiling approach to model workers' task needs, namely information needs (profiles) on tasks. Meanwhile, a fuzzy analytical method is proposed to identify peer-groups with similar task needs based on workers' profiles. Accordingly, a Knowledge Support (X-Support) system is developed to provide a collaborative task-based workplace facilitating knowledge retrieval and sharing among peer-groups. The proposed X-Support system is grounded in a research institute to stimulate task-based knowledge retrieval and sharing. Experimental results show that the proposed system can support task-relevant knowledge effectively. (C) 2005 Elsevier Ltd. All rights reserved.