Context plays an important role in various analysis and design methods in software engineering, and is typically exemplified within data flow diagrams and (sometimes) design patterns. However, we believe that context within software engineering has been largely limited to identifying system boundaries for the scoping of work. In this paper we introduce an approach where the notion of context pl...

This paper develops an evolutionary method that learns inductively to recognize the makeup and the position of very short consensus sequences, cis-acting sites, which are a typical feature of promoters in genomes. The method combines a Finite State Automata (FSA) and Genetic Programming (GP) to discover candidate promoter sequences in primary sequence data. An experiment measures the success of...

Most of the sophisticated methods to estimate evolutionary divergence between DNA sequences assume that the two sequences have evolved with the same pattern of nucleotide substitution after their divergence from their most recent common ancestor (homogeneity assumption). If this assumption is violated, the evolutionary distance estimated will be biased, which may result in biased estimates of d...

Since the birth of molecular evolutionary analysis, primates have been a central focus of study and mitochondrial DNA is well suited to these endeavors because of its unique features. Surprisingly, to date no comprehensive evaluation of the nucleotide substitution patterns has been conducted on the mitochondrial genome of primates. Here, we analyzed the evolutionary patterns and evaluated selec...

This paper presents an agent-based approach to pattern classification that intensively uses evolutionary techniques to support supervised learning of classifiers. The paper first provides a formalization of the peculiar sort of agents and multi-agent systems that we consider. Then, a brief description of the adopted evolutionary technique is provided together with a justification for its use. F...

Since a particular arrangement of filaments, which has come to be known as the 9 + 2 pattern, is found with one exception (9) in all motile cilia and flagella that have heretofore been examined with the electron microscope, some interest (2, 3, 5) has arisen in the remarkable stability of this pattern and its universal occurrence. Bradfield (3) has summarized three possibilities. First, the con...

Echo State Networks are a special class of recurrent neural networks, that are well suited for attractor-based learning of motor patterns. Using structural multi-objective optimization, the trade-off between network size and accuracy can be identified. This allows to choose a feasible model capacity for a follow-up full-weight optimization. Both optimization steps can be combined into a nested,...

In this paper, a Differential Evolution (DE) algorithm for solving multiobjective optimization problems to solve the problem of tuning Artificial Neural Network (ANN) parameters is presented. The multiobjective evolutionary used in this study is a Differential Evolution algorithm while ANN used is Three-Term Backpropagation network (TBP). The proposed algorithm, named (MODETBP) utilizes the adv...

This paper discusses a class of 2-dimensional asynchronous cellular automata with conservation of mass, for the formation of patterns in groups. The previous study reported a methodology of searching, automatically, for pattern-forming cellular automata using a genetic algorithm; this approach successfully found a few types of pattern-forming rules. The current study is a series of statistical ...

A method of finding pattern similarities between two sequences is given. Two portions, one from each sequence, are similar if they are close in the metric space of evolutionary distances. The method allows a complete list to be made of all pairs of intervals, one from each of two given sequences, such that each pair displays a maximum local degree of similarity, an& if the lengths of the given ...