In this paper, the Cartesian products on fuzzy soft set are defined, and the fuzzy soft relations can be presented based on the Cartesian products, including uni-int decision relation and level fuzzy soft relation. By using these new concepts an unt-int decision making method based on fuzzy soft set is constructed to selects a fuzzy set of optimum elements from the alternatives. Finally, an exa...

In this paper, we shall study the algebraic structure of the set of all soft sets defined on a fixed universe. We shall show that the set of all soft sets on a fixed set of parameters is actually a Boolean algebra. Properties of the set of all soft sets on a fixed set of parameters are studied. 2010 AMS Classification: 03B52, 03G05

Molodtsov's soft set theory provides a general mathematical framework for dealing with uncertainty. The concepts of (M, N)-SI implicative (Boolean) filters of BL-algebras are introduced. Some good examples are explored. The relationships between (M, N)-SI filters and (M, N)-SI implicative filters are discussed. Some properties of (M, N)-SI implicative (Boolean) filters are investigated. In part...

For certain weak versions of the Axiom of Choice (most notably, the Boolean Prime Ideal theorem), we obtain equivalent formulations in terms of partial orders, and filter-like objects within them intersecting certain dense sets or antichains. This allows us to prove some consequences of the Boolean Prime Ideal theorem using arguments in the style of those that use Zorn’s Lemma, or Martin’s Axiom.

Our goal is to provide a kernel to allow interactive and accurate modelling of volume objects. As a first step, we present a data structure for three-dimensional fields C continuous in the modelling space. Regular grids storing the field values discretely are combined with a triquadratic approximation filter to define volume objects. This association of a grid and an approximation/interpolation...

Diffusion magnetic resonance imaging (dMRI) is a medical imaging method that can be used to acquire local information about the structure of white matter pathways within the human brain. By applying computational methods termed fiber tractography on dMRI data, it is possible to estimate the location and extent of respective nerve bundles (white matter pathways). Visualizing these complex white ...

Abstract –Wavelet packets have been found to be effective in denoising of biological signals. Wavelet based denoising methods widely employ hard and soft thresholding filters for denoising the signals. This paper introduces a New thresholding filter for the purpose of thresholding in denoisng of EEG signals using wavelet packets. The functioning of the filter is examined and compared with that ...

Methods based on thresholding of wavelet coefficients have been found to be popular in the estimation of biological signals from noisy environment. Hard and soft filters are most commonly used in these methods. In this paper a novel thresholding filter for wavelet shrinkage estimation of biological signals is proposed. The proposed novel filter is applied using Visu Shrink rule and top rule to ...

We consider the problem of automatically discovering the solution preferred by a decision maker (DM). Recent work in the field of constraint programming [8] formalizes the user preferences in terms of soft constraints, whose weights are assumed to be partially unknown. An elicitation strategy is introduced based on the DM queries for constraint weights. In this paper, soft constraints are cast ...