Trust is a fundamental concept that is critical in human decision processes in almost all domains, but of particular relevance in the domain of computer security. In many computer systems deployed today, trust is only modeled indirectly through a serious of formal rules and regulations describing when privileges are to be granted or revoked. Recently, research has been conducted into the area o...

In the classical image processing paradigm, the fundamental idea of image enhancement is to produce a new image such that it exposes information for analysis more than the original image. Fuzzy Logic methods are one of valuable and frequently used techniques among many other image enhancement approaches. In this work we demonstrate that a type-2 fuzzy logic system is able to perform image contr...

We introduce a type-2 fuzzy logic system (FLS), which can handle rule uncertainties. The implementation of this type-2 FLS involves the operations of fuzzification, inference, and output processing. We focus on “output processing,” which consists of type reduction and defuzzification. Type-reduction methods are extended versions of type-1 defuzzification methods. Type reduction captures more in...

In this paper we study two important concepts, i.e. the direct andthe inverse limit of hyperstructures associated with fuzzy sets of type 2, andshow that the direct and the inverse limit of hyperstructures associated withfuzzy sets of type 2 are also hyperstructures associated with fuzzy sets of type 2.

Type-2 fuzzy sets are growing in popularity as, for certain applications they model uncertainty and imprecision better than type1 fuzzy sets. However, type-2 fuzzy sets can be difficult to understand and explain. Recent work has introduced embedded type-2 fuzzy sets and the Representation Theorem which enable us to discuss type-2 fuzzy sets in a different way. In particular they allow for alter...

Type-2 (T2) fuzzy variable is an extension of an ordinary fuzzy variable. In fuzzy possibility theory, T2 fuzzy variable is defined as a measurable map from the universe to the set of real numbers, and the possibility of a T2 fuzzy variable takes on a real number is a regular fuzzy variable (RFV). T2 fuzziness, which is usually used to handle linguistic uncertainties, can be described as T2 fuz...

about to represent. Once the membership function has been established (estimated or defined), the concept is described very precisely as the membership values are exact numerical quantities. This seems to raise a certain dilemma of excessive precision in describing imprecise phenomena. In fact, this concern has already sparked a lot of debates starting from the very inception of fuzzy sets.” Co...

Image segmentation is an essential issue in image description and classification. Currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. Moreover, there are many uncertainties and vagueness in images, which crisp clustering and even Type-1 fuzzy clustering could not handle. Hence, Type-...

The single input rule modules (SIRMs) based type-1 fuzzy inference systems (SIRM-T1FISs), which assign each input item with a rule module, can greatly reduce the number of fuzzy rules and have found lots of applications. This paper extends SIRMT1FISs to the interval type-2 case to achieve better performance. Furthermore, the properties of the SIRMs based interval type-2 fuzzy inference systems ...