Articles written in Sadhana

    • Modified fuzzy c-mean for custom-sized clusters


      More Details Abstract Fulltext PDF

      Fuzzy c-mean (FCM) is one of the widely used data clustering methods. FCM method not only divides a data set into several clusters but also determines the potential belongingness of each data in different clusters. The size of clusters generated by FCM cannot be controlled by the inherent mechanism. However,sometimes real life situations demand that the clusters should have some pre-specified size. In this study, the FCM method is further extended to obtain clusters with specified size. In the first step of the proposed method, FCM algorithm is executed; later the potential belongingness matrix passes through an optimization model to yield clusters with specified sizes. In the proposed technique, the centres of the clusters obtained from FCM are considered but the boundary elements are redistributed to achieve equal or custom-sized clusters. The methodology has been explained further with examples.

    • An approach of refining RC4 with performance analysis on new variants


      More Details Abstract Fulltext PDF

      Many years of research on the RC4 stream cipher proves it to be strong enough, but there are claims that its swap function is responsible for essential biases in the output. There are suggestions to discard some initial bytes from the key-stream, to get rid of this, before the actual encryption starts, though no optimum valuehas been defined. In this paper, by analysing different variants of RC4, the authors have attempted to find out whether this cipher becomes more secure by discarding initial bytes and, if so, what is its optimum limit. Also, multiple S-boxes generated by different logics and a unique key-mixing procedure have been implemented,which made k RC4 more robust.

    • Graphical method to solve fuzzy linear programming


      More Details Abstract Fulltext PDF

      In this paper, the graphical method for solving linear programming is extended in fuzzy environment. Here, we dealt with the fully fuzzy linear programming (FFLP) which involves fuzzy constraints and fuzzy objective. Determining and visualizing the fuzzy feasible space in the geometrical space is one of the novel contributions of this study. Defining fuzzy constraints as fuzzy lines and finding the nature of the point of intersection between fuzzy lines are also studied. The fuzzy constraints divide the geometrical into fuzzy half planes. Intersection of such fuzzy half planes yields a fuzzy convex hull. The optimal solution of fuzzy linear programming problem is obtained at an extreme point of this fuzzy convex hull. The results obtained from the proposed method are compared with existing methodologies.

  • Sadhana | News

    • Editorial Note on Continuous Article Publication

      Posted on July 25, 2019

      Click here for Editorial Note on CAP Mode

© 2022-2023 Indian Academy of Sciences, Bengaluru.