Cloud computing technology created a brand new approach for further information resources management and utilization. Based on exploring characteristics and applications of cloud computing technology, the study in this paper is focused on cloud service with information resources. The aim of this study is to construct a cloud service model, namely Information Resource as a Service (IRaaS). Our model depicts the components of IRaaS and relationships among those components, which builds up a prime foundation for further studying on both information resource management and service.
Discovering service-on-demand for large numbers of functionality-similar web services is one of the key issues in service discovery study. To find out the proper service among the functionality-similar web services, a merging cluster algorithm regarding QoS-oriented supply and demand is proposed in this paper. To meet the target, FCM clustering is adopted for agglomerative clustering between the user’s QoS requirement information and the QoS information from Web Service resources. Then, the sequence could be determined by similarity computation with the same clustering. Lastly, the numerical example is presented to illustrate that the service-on-demand can be discovered efficiently and effectively.
The selection mode for technology transfer plays a significant role along with whole process of technology transfer because its methods and approaches could impact the progress and effect of technology transfer, which also fundamentally influence on regional sustainable development. To construct a selection model for monitoring technology transfer, we firstly examined influential factors related with technology transfer from four perspectives, such as regional development, supplies and recipient of technology, transferred technology and transfer modes. Then we drafted a roadmap for technology transfer, and built up the selection model of technology transfer mode with multivariate conditional LOGIT theory. The research contribution in this paper could be used for monitoring on mode selection for technology transfer, which could influence on regional sustainable development both directly and indirectly.
Based on literature review from both perspectives between emerging technology transfer and sustainable development, this paper conducts a study on identifying some fundamental components and approaches. The research results are significantly important for further modeling on suitability monitoring related with emerging technology transfer, as well as extending research scope on suitability monitoring modeling.
Based on literature study, three principles of identifying benchmark were formulated, and four general approaches of benchmark recognition were summarized. We adopted Beijing sustainable development indicators as a sample to test each approach, with which we could compare the results and analyze the characteristics, advantages, disadvantages as well as suitability. The research results showed that indicators with different characters should be treated with different approaches for benchmark identification.
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