We

No abstract

Abstract. After the introduction of Bitcoin, blockchain has made its way through numerous applications and been adopted by various communities. A number of implementations exist today providing a platform to carry on business with ease. However, it is observed the scalability of blockchain still remains an issue. Also, none of the framework can claim the ability to handle Big Data and support to perform analytics, which is an important and integral facet of current world of business. We propose HBasechainDB, a scalable blockchain-based tamperproofed Big Data store for distributed computing. HBasechainDB adds the blockchain characteristics of immutability and decentralization to the HBase database in the Hadoop ecosystem. Linear scaling is achieved by pushing computation to the data nodes. HBasechainDB comes with inherent property of efficient big data processing as it is built on Hadoop ecosystem. HBasechainDB also makes adaptation of blockchain very easy for those organizations whose business logic are already existing on Hadoop ecosystem. HBasechainDB can be used as a tamper-proof, decentralized, distributed Big Data store.

Agriculture is one of the major sources of income in developing countries like India. Pests are one of the main sources for the degradation of quality and quantity of the major crops such as Rice and Wheat. The lack of knowledge about technical & scientific methods to prevent pest diseases is the main reason for less production of these commodities. This paper presents an architectural framework of an agriculture Expert System and describes the design and development of the rule based expert system for rice and wheat crop pest management. The designed system is intended for the diagnosis of diseases caused by pests in the rice & wheat plants respectively and it also facilitates different components including decision support module with interactive console base user interface for diagnosis on the basis of response(s) of the user made against the queries related to particular disease symp-toms. This paper provides a new approach for knowledge representation in expert systems for agricultural domain. The Explanation block (EB) of the system provides the explanation for a particular decision taken by the system. Explanation block gives the clear view of logic followed by kernel of the expert system.

The Cell is a heterogeneous multicore processor that has attracted much attention in the HPC community.

No abstract

No abstract

No abstract