Aggregating measure scores is an important step in multiple criteria decision-making, determining the overall effectiveness from dissimilar measures. One of the most popular aggregating methods is Simple Additive Weighting (SAW), which assigns weights to measures based on subjective preference information, and sum weighted scores up. The quality of overall score is highly dependent on the quali...

In this paper, the authors extend concept of a t-intuitionistic fuzzy set to PMS-subalgebras PMS-algebras. The define PMS-subalgebra PMS-algebra and show that any intuitionistic is PMS-subalgebra. provide condition for an in be use their (α,β) level cuts characterize PMS-algebra. investigate whether homomorphic images inverse are also PMS-subalgebras. Furthermore, nonempty again Finally, Cartes...

In this paper, a new Fuzzy Morphology (FM) based on the GeneralizedDempster-Shafer Theory (GDST) is proposed. At first, in order to clarify the similarity ofdefinitions between Mathematical Morphology (MM) and Dempster-Shafer Theory (DST),dilation and erosion morphological operations are studied from a different viewpoint. Then,based on this similarity, a FM based on the GDST is proposed. Unlik...

Image conversion of malicious binaries, or binary visualisation, is a relevant approach in the security community. Recently, it has exceeded role single-file malware analysis tool and become part Intrusion Detection Systems (IDSs) thanks to adoption Convolutional Neural Networks (CNNs). However, there been little effort toward image segmentation for converted images. In this study, we propose n...

This paper deals with the problem of testing hypothesis when both the hypotheses and the available data are fuzzy. First, four different kinds of fuzzy hypotheses are defined. Then, a procedure is developed for constructing the fuzzy point estimation based on fuzzy data. Also, the concept of fuzzy test statistic is defined based on the α-cuts of the fuzzy null hypothesis and the α-cuts of the c...

The paper aims to present a cost evaluation for multi-project environment, taking into account imprecision in activity duration and cost. Data specification in the form of discrete α-cuts enables the connection of distinct and imprecise data, and the implementation of a constraints satisfaction problem with the use of constraint programming. Moreover, using α-cuts, optimistic, pessimistic, and ...

Problem of impulse noise reduction is a very well studied problem in image processing community and many different approaches have been proposed to tackle this problem. In the current work, the problem of fixed value impulse noise (salt and pepper) removal from images is investigated by use of a Markov Random Field (MRF) models with smoothness priors. After the formulation of the problem as an ...

This paper deals with the problem of testing hypothesis when both the hypotheses and the available data are fuzzy. First, four different kinds of fuzzy hypotheses are defined. Then, a procedure is developed for constructing the fuzzy point estimation based on fuzzy data. Also, the concept of fuzzy test statistic is defined based on the α-cuts of the fuzzy null hypothesis and the α-cuts of the c...

We present a framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in α − β swap Graph-cuts algorithm. Moreover, depth values of...

It is known that the standard intersection and union of type-1 fuzzy sets (i.e., the intersection and union under the minimum t-norm and maximum tconorm) are the only cutworthy operations for type1 fuzzy sets. The aim of this paper is to show that similar property holds also for type-2 fuzzy sets, with respect to some special cutting. As was already demonstrated, the intersection and union of t...