Vital areas in Bioinformatics research is one of the Protein sequence analysis. Protein sequence motifs are determining the structure, function, and activities of the particular protein. The main objective of this paper is to obtain protein sequence motifs which are universally conserved across protein family boundaries. In this research, the input dataset is extremely large. Hence, an efficien...

We outline a rough–neuro computing model as a basis for granular computing. Our approach is based on rough sets, rough mereology and information granule calculus.

In this study, we pursue fundamental ideas of granular computing by concentrating on further conceptual developments of metastructures which are inherently associated with computing involving a large number of distributed datasets. We show that such processing leads to the representatives of information granules and granular models in the form of metastructures and metamodels. The formulation o...

The field of granular computing deals with representing, organizing, and processing information based on different levels of abstraction or aggregation. In the domain of image search, an increasingly common approach is to organize and aggregate the retrieved images within multi-level structures. In this paper, we will explore some of the core principles of granular computing within the context ...

1.1. Digital communities and a fundamental quest for human-centric systems. 1.2. A historical overview: towards a non-Aristotelian perspective of the world. 1.3. Granular Computing. 1.3.1. Sets and interval analysis. 1.3.2. The role of fuzzy sets: a perspective of information granules. 1.3.3. Rough sets. 1.3.4. Shadowed sets. 1.4. Quantifying information granularity: generality versus specifici...

This chapter provides a general introduction to interval computations, especially to interval computations as an important part of granular computing. This introduction is aimed at researchers who would like to learn more – and eventually to use – the main ideas and techniques of granular computing. We explain how intervals naturally appear in data processing, which techniques exist for process...

We look at the problem of adverarial decision making. Our objectivel here is to try to replace the infinite regress inherent in adversarial making decisions problems with the use of knowledge about the adversary. We use granular computing and particularly the Dempster-Shafer belief structure to represent this knowledge. This allows us to turn the problem of adverarial decision making into a pro...

What is granular computing(GrC)? It is a shifting paradigm. Let us start with a few words about how the term was coined. In the academic year 1996-97, when Lin (this section editor) took his sabbatical leave at UC-Berkeley, Zadeh suggested granular mathematics (GrM) to be his research area. To limit the scope, Lin proposed the term granular computing [14]. What was GrC then? Zadeh had outlined ...