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Rough set-based rule generation in tables with uncertainties, especially non-deterministic information and missing values, is investigated. The possible world semantics is employed, and both certain rules and possible rules are defined. Even though these definitions cause the computational problem, it is solved by using rough set-based concepts, and(More)
Follicular helper T (Tfh) cells are recognized as a distinct CD4helper T cell subset, and mainly dysregulated in the autoimmune disease, whether it plays a role in the infectious mononucleosis (IM) diseases is unknown. In this study, we found that the CD4CXCR5 Tfh cells were not significantly changed, but the CD4CXCR5ICOS and CD4CXCR5ICOSPD1 Tfh subsets(More)
This paper reports the definability of a set of objects and rough set-based rule generation. In a standard table, we at first obtain equivalence classes with respect to an attribute set, and we solve the definability of a set X of objects. As the side effect, we obtain conditions for specifying the set X. We have extended this algorithm to tables with(More)
This paper briefly surveys rough set-based framework RNIA (Rough Non-deterministic Information Analysis), which can handle tables with non-deterministic data. Each rough set-based concept in the standard tables is redefined based on the possible world semantics. Especially, in rule generation, we reconsider the definition of rules, because the standard(More)