International Journal of Modern Computer Science and Engineering
ISSN: 2325-0798 (online)Search Article(s) by:
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Current Issue: Vol. 5 No. 1or Keyword in Title:
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Table of Content for Vol. 5 No. 1, 2016

Pattern Association Using New Maximally Entangled States in a Two-qubit System
Manu Pratap Singh and B.S. Rajput
 PP. 1 - 20
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ABSTRACT: New set of maximally entangled states (Singh-Rajput MES), constituting orthonormal eigen bases, has been revisited and its superiority and suitability in the processes of quantum associative memory (QuAM) have been demonstrated. Using these MES as memory states in the evolutionary process of pattern storage, the suitability and superiority of these MES over Bell’s MES have been demonstrated and it has been shown that, under the operations of all the possible memorization operators for a two-qubit system, the first two states of Singh-Rajput MES are useful for storing the pattern ǀ11> and the last two of these MES are useful in storing the pattern ǀ10> while Bell’s MES are not much suitable as memory states in a valid memorization process. Recall operations of quantum associate memory (QuAM) have been conducted through evolutionary process in terms of unitary operators by separately choosing Singh-Rajput MES and Bell’s MES as memory states for various queries and it has been shown that in each case the choices of Singh-Rajput MES as valid memory states are much more suitable than those of Bell’s MES.

A Comprehensive Survey on Machine Learning of Artificial Intelligence
Shireesh Pyreddy
 PP. 21 - 28
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ABSTRACT: Machine Learning of Artificial Intelligence explains the definition, concept, significance and main strategy of machine learning as well as the basic structure of machine learning system. By combining several basic ideas of main strategies, great effort is laid on introducing several machine learning methods, such as Rote learning, Explanation-based learning, Learning from instruction, Learning by deduction, Learning by analogy and Inductive learning, etc. Machine learning is a fundamental way that enable the computer to have the intelligence; its application which had been used mainly the method of induction and the synthesis rather than the deduction has already reached many fields of Artificial Intelligence.

Big Data: A Study of Its Issues and Challenges
Mudasir Manzoor Kirman, Syed Mohsin Saif, Ahmad Talha Siddiqui
 PP. 29 - 36
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ABSTRACT: Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. Big data is not merely data, rather it has become a complete subject, which involves various tools, techniques and frameworks. Big Data refers to the data volumes in the range of 10-10,000 tera bytes and beyond. Such volumes exceed the capacity of current storage systems and processing system. One cannot claim that technology is 100 percent good, beneficial and effective to support the mammoth size of data. Every emerging technology has both advantages and disadvantages associated with it and as time passes it gets reframed to get better out of best. It was observed that all the developmental prospects have environmental, social, and human consequences that go far beyond the immediate purposes of the technical devices and practices themselves. The era of Big Data has begun. Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists, and many others are demanding for access to the massive quantities of information produced by “internet of things”. In this paper a review study is made to analyze the issues and challenges are inline with adopting this technology and benefits that are end product of using big data in special reference to Social media.

A Compendious Research on Big Data and Hadoop
Shireesh Pyreddy
 PP. 37 - 46
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ABSTRACT: Big data is a term that describes the large volume of both structured and unstructured data that inundates a business on a day-to-day basis. Due to the fact that the database systems like RDBMS can process the unstructured data but RDBMS finds it challenging to handle such huge data volumes. To deal with the challenges Hadoop is used. It is software framework for distributed storage and distributed processing of very large data sets. MapReduce is a back-end processing engine which is used to perform operations like map and reduce and makes the data simple and stores it into HDFS.