Background: Covariance models (CMs) are probabilistic models of RNA secondary structure, analogous to profile hidden Markov models of linear sequence. The dynamic programming algo...
Many systems such as Tukwila and YFilter combine automaton and algebra techniques to process queries over tokenized XML streams. Typically in this architecture, an automaton is fi...
When we try to implement a multi-objective genetic algorithm (MOGA) with variable weights for finding a set of Pareto optimal solutions, one difficulty lies in determining appropri...
The goal of testing is to distinguish between a number of hypotheses about a systemfor example, dierent diagnoses of faults by applying input patterns and verifying or falsifying t...
In this article, a hybrid optimization method has been proposed consisting of modified ant colony systems (ACSs) and constrained nonlinear programming (NLP) to solve the problems ...