Some new lacunary ff-statistical AA-convergent sequence spaces of order α\alpha

We study the concept of density for sets of natural numbers in some lacunary $A$-convergent sequence spaces. Also we are trying to investigate some relation between the ordinary convergence and module statistical convergence for evey unbounded modulus function. Morever we also study some results on the newly defined lacunary $f$-statistically $A$-convergent sequence spaces with respect to some Musielak-Orlicz function.Comment: Conference paper. arXiv admin note: text overlap with arXiv:1506.0545

On fuzzy real-valued double A-sequence spaces defined by Orlicz function

The purpose of this paper is to introduce and study a new concept of strong fuzzy real-valued double A- convergence sequences with respect to an Orlicz function. Also, some properties of the resulting fuzzy real-valued sequence spaces are examined. In addition, we define the double A-statistical convergence and establish some connections between the spaces of strong double A-convergence sequence and double $A$-statistical convergence sequence

On some properties of ideal convergent double sequences in fuzzy normed spaces

Recently, Rashid et al. [Rashid, Mohammad HM and Kočinac, Ljubiša DR. Ideal convergence in 2–fuzzy 2–normed spaces, Hacettepe Journal of Mathematics and Statistics, 46(1):149–162, 2017] defined the notion of ideal convergence of single sequences in 2–fuzzy 2–normed linear spaces. The aim of this paper is to generalize this notion to the double sequences in such spaces. For the sake of generalizing we define some concepts that contribute basically to outcomes that we came up with and study some basic properties of these new definitions.Publisher's Versio

Near-Optimal Scheduling for LTL with Future Discounting

We study the search problem for optimal schedulers for the linear temporal logic (LTL) with future discounting. The logic, introduced by Almagor, Boker and Kupferman, is a quantitative variant of LTL in which an event in the far future has only discounted contribution to a truth value (that is a real number in the unit interval [0, 1]). The precise problem we study---it naturally arises e.g. in search for a scheduler that recovers from an internal error state as soon as possible---is the following: given a Kripke frame, a formula and a number in [0, 1] called a margin, find a path of the Kripke frame that is optimal with respect to the formula up to the prescribed margin (a truly optimal path may not exist). We present an algorithm for the problem; it works even in the extended setting with propositional quality operators, a setting where (threshold) model-checking is known to be undecidable