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There have been three approaches to find the measures of fuzzy sets, which extend the count function for crisp sets. The first one is due to Deluca and Termini; second one a measure theoretic approach due to Zadeh and a bag theoretic approach due to Tripathy et al. Intuitionistic fuzzy sets are generalizations of fuzzy sets. So, efforts have been made recently to extend the above three approaches to find measures for cardinalities of intuitionistic fuzzy sets. The extension of the approach due to Deluca and Termini to the context of intuitionistic fuzzy sets by Tripathy et al [9]. In this paper, we define measures of intuitionistic fuzzy sets to define the count of an intuitionistic fuzzy set in the direction of Zadeh. Also, we establish several properties of these measures.

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Graph theory has found its applications in various fields of computation involved in day to day life. A problem solving approach that incorporates graph theory has an added advantage of being simple and visually more comprehensible [9]. Data mining, image processing, astrology and astronomy, theoretical computer science, artificial intelligence and compiler optimization et al., every evolving field utilizes efficient algorithms involving graphs and their properties. Graph coloring has major applications in the field of compiler optimization. This paper proposes a heuristic approach of graph coloring for code optimization and hence, improvement in compiler performance and accuracy. Color-based merging of colored graphs reduces the use of temporary variables, increasing efficiency in memory utilization. A comparative analysis has been carried out in order to present the advantages of the proposed algorithm [5] [6].