A distributed system is commonly modelled by a graph where nodes represent processors and there is an edge between two processors if and only if they can communicate directly. In ...
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
—Recently, Bayesian probabilistic models have been used for predicting software development effort. One of the reasons for the interest in the use of Bayesian probabilistic model...
Parag C. Pendharkar, Girish H. Subramanian, James ...
This paper presents a real-time database modeling complex networks of intersecting roads and walkways in urban virtual environments. The database represents information about the ...