Theoretical Computer Science

DNA computing, or, more generally, molecular computing, is an exciting fast developing interdisciplinary area. Research in this area concerns theory, experiments, and applications of DNA computing. In this paper, we demonstrate the theoretical developments by discussing a number of selected topics. We also give an introduction to the basic structure of DNA and the basic DNA processing tools.

Data exchange is the problem of taking data structured under a source schema and creating an instance of a target schema that reflects the source data as accurately as possible. In this paper, we address foundational and algorithmic issues related to the semantics of data exchange and to the query answering problem in the context of data exchange. These issues arise because, given a source instance, there may be many target instances that satisfy the constraints of the data exchange problem.

This paper is aimed at exploring the hidden fundamental computational property of natural language that has been so elusive that it has made all attempts to characterize its real computational property ultimately fail. Earlier natural language was thought to be context-free. However, it was gradually realized that this does not hold much water given that a range of natural language phenomena have been found as being of non-context-free character that they have almost scuttled plans to brand natural language contextfree. So it has been suggested that natural language is mildly context-sensitive and to some extent context-free. In all, it seems that the issue over the exact computational property has not yet been solved. Against this background it will be proposed that this exact computational property of natural language is perhaps the N-th dimension of language, if what we mean by dimension is nothing but universal (computational) property of natural language.

In this work, we address the problem of locally estimating the size of a Peerto-Peer (P2P) network using local information. We present a novel approach for estimating the size of a peer-to-peer (P2P) network, fitting the sum of new neighbors discovered at each iteration of a breadth-first search (BFS) with a logarithmic function, and then using Lambert’s W function to solve a root of a ln(n)+b−n = 0, where n is the network size. With rather little computation, we reach an estimation error of at most 10 percent, only allowing the BFS to iterate to the third level.

Benchmarking graph-oriented database workloads and graph-oriented database systems are increasingly becoming relevant in analytical Big Data tasks, such as social network analysis. In graph data, structure is not mainly found inside the nodes, but especially in the way nodes happen to be connected, i.e. structural correlations. Because such structural correlations determine join fan-outs experienced by graph analysis algorithms and graph

We study the dynamical behavior of D-dimensional linear cellular automata over Zm. We provide an easy-to-check necessary and sufficient condition for a D-dimensional linear cellular automata over Zm to be ergodic and topologically transitive. As a byproduct, we get that for linear cellular automata ergodicity is equivalent to topological transitivity. Finally, we prove that for 1-dimensional linear cellular automata over

This chapter is devoted to introducing the theories of interval algebra to people who are interested in applying the interval methods to uncertainty analysis in science and engineering. In view of this purpose, we shall introduce the key concepts of the algebraic theories of intervals that form the foundations of the interval techniques as they are now practised, provide a historical and epistemological background of interval mathematics and uncertainty in science and technology, and finally describe some typical applications that clarify the need for interval computations to cope with uncertainty in a wide variety of scientific disciplines.

Keywords. Interval mathematics, Uncertainty, Quantitative Knowledge, Reliability, Complex interval arithmetic, Machine interval arithmetic, Interval automatic differentiation, Computer graphics, Ray tracing, Interval root isolation.

Recommended Citation:

Hend Dawood. Interval Mathematics as a Potential Weapon against Uncertainty. In S. Chakraverty, editor, Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems. chapter 1, pages 1-38. IGI Global, Hershey, PA, 2014. ISBN 978-1-4666-4991-0.

The final publication is available at IGI Global via http://dx.doi.org/10.4018/978-1-4666-4991-0.ch001

Recently, it has been recognizedthat phase transitions play an important role in the proba- bilistic analysis of combinatorial optimization problems. However, there are in fact many other relations that leadto close ties between computer science andstatistical physics. This review aims at presenting the tools andconcepts d esignedby physicists to d eal with optimization or decision problems in a language accessible

The use of social networking websites has increased since last few decades. The social networking sites such as Twitter, Facebook, LinkedIn and YouTube are sources of human interaction, where the users are allowed to create and share their activities, thoughts and opinions pertaining to different subjects. These sites have not only connected large user populations but have also captured massive information associated with their daily interactions in the form of Big Data. This data provides unprecedented information about human behavior and social interactions. It makes it possible to understand who the users are, what their interests are and what they need. This information is vital for businesses to target potential consumers or seek customer opinions in the event of diversification as a business strategy. Thus, this work analyzes social media data to predict significant personality traits, i.e. qualities or characteristics specific to an individual, using the Big Five Model. The predictions can be applied to various domains like business intelligence, marketing, sociology and psychology. A parallelism between an individual’s personality traits and his/her linguistic information is explored for analytics.

The author of this article is a theoretical physicist and computer scientist, who has no background in literature or creative writing. Nor did he intend to write a book on poetry. This book entitled: “About Love” came as Divine Inspiration. The writing was so captivating, majestic, fascinating and effortlessly magical. The poems came to him during the draft of his book Digital Physics: The Meaning of the Holographic Universe and Its Implications beyond Theoretical Physics. During the writing, he started asking himself many questions, particularly about where do our ideas come from? Is there a universe of ideas out there that we have access to it? Indeed, he is aware that some of our thoughts originate from the books we read, from school, society and the environment surrounding us, but that perhaps does not answer the question. The facts before his eyes say that not all our ideas come from society or learning.

Keywords: computes, digital, discrimination, divine, happiness, injustice, inspiration, love, multiverse, physics, Platonism, struggle, togetherness, universe.

In this paper the problem of the number of fixed points for an RSA algorithm is considered. This is an important question from the point of view of any cryptosystem. We have estimated the expected value of this number for randomly chosen RSA parameters. It turned out that it is O(ln2n), and the probability of finding such a point is O(ln2n/n). Thus, these values are really negligible, which had been intuitively expected.

In this paper we consider several types of equations on words, motivated by the attempt of characterizing the class of polyominoes that tile the plane by translation in two distinct ways. Words coding the boundary of these polyominoes satisfy an equation whose solutions are in bijection with a subset of the solutions of equations of the form ABA˜B˜≡XYX˜Y˜. It turns