Formal concept analysis (FCA) is a solid mathematical framework to manage information based on logic and lattice theory. It defines two explicit representations of the knowledge present in dataset as concepts implications. This paper describes an R package called [fcaR](https://CRAN.R-project.org/package=fcaR) that implements FCA's core notions techniques. Additionally, it extension FCA fuzzy d...

Usually, datasets contain imprecise data (noise), which can produce unsuspected results on the considered mappings. For instance, this happen with infimum and supremum operators, since both operators are straightforwardly associated universal existencial quantifiers, respectively. An interesting possibility, of decreasing impact possible noise in final results, is consideration generalized quan...

It is known that a (concept) lattice contains an n-dimensional Boolean suborder if and only the context contra-nominal scale as subcontext. In this work, we investigate more closely interplay between subcontexts of given finite suborders its concept lattice. To end, define mappings from set to vice versa study their structural properties. addition, introduce closed-subcontexts extension closed ...

logic analysis and attack construction methods are two major approaches in verification of cryptographic protocols. however, it is almost preferable to use both of them for a complete analysis. in this paper, a generic framework for the integration of the two verification approaches is presented. using the framework we can propose analysis methods in which security properties and breach scenari...