37 research outputs found

    Security protocol based on random key generation for an Rfid system

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    Radio Frequency Identification (RFID) is a technology, which describes the transmission of unique information by a wireless device, over Radio waves, when prompted or read by a compatible reader; The basic components in implementing RFID are RFID tags which are small microchips attached to a radio antenna, mounted on a substrate, and a wireless transceiver/reader that queries the RFID tags; This thesis deals with research issues related to security aspects in the communication between an RFID tag and its reader. More precisely, it deals with a new, simple and efficient security protocol based on an encryption that uses the concept of regular public key regeneration, which can be effortlessly adopted in an RFID application

    A guide to learning modules in a dynamic network

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    A guide to learning modules in a dynamic network

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    RNA sequencing-based identification of candidate hypersensitive transcripts in Perna viridis

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    The Asian Green Lipped mussel, Perna viridis one of the widely distributed bivalves act as a source of low cost protein providing nutritious meal to the coastal population in the form of well balanced amino acids and micronutrients. The immune system produces antibodies to certain class of proteins present in shellfish meat thereby causing hypersensitive reactions in the body. The next generation integrated transcriptome sequencing approach identifies all the potential allergenic proteins expressed in an animal very effectively. The present study describes the transcriptome of P. viridis based on the sequence data generated using five tissues. Transcriptome level candidate allergens and epitopes were observed and identified that might play a role in hypersensitive reaction to shellfish proteins including certain novel candidate allergens like Ran protein and a filamin A like protein. The existence of epitope hotspots in an important protein, arginine kinase was also observed and the unigenes identified would be a valuable resource for conduct of functional studies

    A Hybrid Approach for Data Warehouse View Selection ABSTRACT

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    Materialized view selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. Static selection of views may materialize certain views that are not beneficial as the data and usage trends change overtime. On the contrary, dynamic selection of views works better only for queries demanding a high degree of aggregation. These facts point to the need for a technique that combines the improved response time of the static approach and the automated tuning capability of the dynamic approach. In this paper, we propose a hybrid approach for the selection of materialized views. The idea is to partition the collection of all views into a static and a dynamic set such that views selected for materialization from the static set are persistent over multiple query (and maintenance) windows, whereas views selected from the dynamic set can be queried and/or replaced on the fly. Highly aggregated views are selected on the fly based on the query access patterns of users, whereas the more detailed static set of views play a significant role in the efficient maintenance of the dynamic set of views and in answering certain detailed view queries. We prove that our proposed strategy satisfies the monotonicity requirements, which is essential for the greedy heuristic to deliver competitive solutions. 1 Experimental results show that our approach outperforms Dynamat; a well-known dynamic view management system that is known to outperform optimal static view selection
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