Transition state theory (TST) 1 is the most widely used theory for calculating rates of bimolecular eactions occurring in the gas phase and in condensed phases. TST is also incorporated into the widely used RRKM theory for unimolecular reactions. The popularity of TST is largely due to its simplicity and its usefulness for correlating trends in reaction rates in terms of easily interpreted quan...

In this study the most probable reaction paths of ATnm, OATnm, MATnm, PATnm, NMATo and NMATm transition states with OH radicals have been analyzed. The optimized geometry was calculated via Gauss View 5. Subsequently, the lowest energy level was found by geometric optimization via the Gaussian 09 programme. The geometrical structure analysis and bond lengths were also calculated. This study aim...

For effective smart media service, a reliable and confidential context recognition is required to prepare and react properly. However, it is difficult to achieve a higher confidence level for several reasons. First, raw data from multiple sensors have different degrees of uncertainty. Second, generated contexts can indicate conflicting results, even though they are acquired by simultaneous oper...

A major aspect of describing transport in heterogeneous media has been that of relating effective diffusivities to the topological properties of the medium. While such effective transport coefficients may be useful for mass fractals or under steady state conditions, they are not adequate under transient conditions for self-similar pore fractal media. In porous formations without scale, diffusio...

Social media and social networking sites have become a global pinboard for exposition and discussion of news, topics, and ideas, where social media users often update their opinions about a particular topic by learning from the opinions shared by their friends. In this context, can we learn a data-driven model of opinion dynamics that is able to accurately forecast users’ opinions? In this pape...

Most speech parameter estimation techniques are easily innuenced by the frequency response of the communication channel. We have developed a technique that is more robust to such steady-state spectral factors in speech. The approach is conceptually simple and computationally eecient. The new method is described, and experimental results are reported, showing a signiicant advantage for the propo...

This paper is a short summary of the main results in the thesis [1]. Based on the P2P paradigm we construct a stochastic model for a live media streaming content delivery network. Starting from the behavior of the out degree process of each node we analyze the evolution of the resulting random graph. For the out degree process we provide an iterative formula for the distribution probabilities a...

Fast and accurate tracking of moving objects in video streams is a critical process in computer vision. This problem can be formulated as exploration problems and thus can be expressed as a search into a state space based representation approach. However, these search problems are hard to solve because they involve search through a high dimensional space. In this paper, we describe an A* heuris...

5 Regular expressions with capture groups offer a concise and natural way to define parse trees over the text that they are parsing, however classical algorithms only return a single match for each capture group, not the full parse tree. We describe an algorithm based on finite-state automata that extracts full parse trees from text in Θ(nm) time and Θ(dn+m) space (where n is the size of the te...

PageRank is one of the most popular measures for ranking the nodes of a network according to their importance. However, PageRank is defined as a steady state of a random walk, which implies that the underlying network needs to be fixed and static. Thus, to extend PageRank to networks with a temporal dimension, the available temporal information has to be judiciously incorporated into the model....