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.

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.