Showing papers by "Kamala Krithivasan published in 2007"

Returning and non-returning parallel communicating finite automata are equivalent

Abstract: A parallel communicating automata system consists of several automata working independently in parallel and communicating with each other by request with the aim of recognizing a word. Rather surprisingly, returning parallel communicating finite automata systems are equivalent to the non-returning variants. We show this result by proving the equivalence of both with multihead finite automata. Some open problems are finally formulated.

Network of evolutionary processors with splicing rules and permitting context

Abstract: In this paper we consider networks of evolutionary processors with splicing rules and permitting context (NEPPS) as language generating and computational devices. Such a network consists of several processors placed on the nodes of a virtual graph and are able to perform splicing (which is a biologically motivated operation) on the words present in that node, according to the splicing rules present there. Before applying the splicing operation on words, we check for the presence of certain symbols (permitting context) in the strings on which the rule is applied. Each node is associated with an input and output filter. When the filters are based on random context conditions, one gets the computational power of Turing machines with networks of size two. We also show how these networks can be used to solve NP-complete problems in linear time.

Self-assembly of graphs

Abstract: Self-assembly is a process in which simple objects autonomously combine themselves into larger objects. It is considered as a promising technique in nano-technology. In this paper, we propose a graph-based self-assembly model. Two simple graphs G 1 and G 2 with a vertex of common degree overlap and a new self-assembled graph is formed. Besides studying the properties of these self assembled graphs, we answer the question: can a given set of graphs be generated through the process of self-assembly? If so, how to find the generator that could generate the given set of graphs by the process of self-assembly. The question of the existence of the minimal generator is also discussed. The necessary and sufficient condition for a graph H to be obtained by the iterated self-assembly of the graph G is also answered. We also conclude that the problem of finding the generator is decidable.

On the Reduction of Side Effects in Tomography

Abstract: As the Computed Tomography(CT) requires normally hundreds of projections to reconstruct the image, patients are exposed to more X-ray energy, which may cause side effects such as cancer. Even when the variability of the particles in the object is very less, Computed Tomography requires many projections for good quality reconstruction. In this paper, less variability of the particles in an object has been exploited to obtain good quality reconstruction. Though the reconstructed image and the original image have same projections, in general, they need not be the same. In addition to projections, if a priori information about the image is known, it is possible to obtain good quality reconstructed image. In this paper, it has been shown by experimental results why conventional algorithms fail to reconstruct from a few projections, and an efficient polynomial time algorithm has been given to reconstruct a bi-level image from its projections along row and column, and a known sub image of unknown image with smoothness constraints by reducing the reconstruction problem to integral max flow problem. This paper also discusses the necessary and sufficient conditions for uniqueness and extension of 2D-bi-level image reconstruction to 3D-bi-level image reconstruction. Keywords— Discrete Tomography, Image Reconstruction, Projection, Computed Tomography, Integral Max Flow Problem, Smooth Binary Image.