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Data warehousing and Data mining find enormous applications; RFID technology is one among them. A RFID data warehousing system with novel data cleaning, transformation and loading technique has been proposed in the previous work. The system has been dedicatedly implemented in one of the significant RFID applications tracking of goods in warehouses. The warehoused RFID data is in specific format and so an effective mining system is required to mine the needed information from the database. The existing mining algorithms are inefficient in extracting the information from the warehoused RFID data. In this paper, a novel data mining system is proposed, which effectively extracts the information regarding the nature of movement of the RFID tags. The proposed mining system generates an intermediate dataset (I-dataset) from the warehoused dataset. From the I-dataset, sequential patterns are mined with different pattern length combinations. From the mined sequential patterns, fuzzy rules are generated, which depicts the nature of movement of the RFID tags. The implementation results show that the proposed mining system performs well by extracting the significant RFID tags and its combinations and the nature of movement of the tags.

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Cloud computing is one of the Information Communication Technology (ICT) trends. It is amalgamation of network of computers connected by centralized physical server. These servers are located on remote computers so that we can access applications directly from distant computer by sitting at our place. The paper makes readers aware of concepts of cloud computing along with its architecture. Few distinctive features among different cloud models have been described.It is believed that existing model must be improved time to time to ensure efficient computing of tasks. Keeping this in mind, an improved architecture of cloud computing has been proposed in following paper. The proposed model consists of ontology module into cloud information architecture and retrieves terms related to user query using Query Retrieval Mechanism.

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