The design of efficient communication protocols for wireless sensor networks has aroused great interest in the research community, especially face limited energy nodes and frequent change network topology. Routing remains a challenging problem communications, as deploying or replacing hazardous environments is difficult. Many studies have been devoted to alleviate certain limitations, such clus...

In this paper, we provide an energy efficient selfhealing mechanism for Wireless Sensor Networks. The proposed solution is based on our probabilistic sentinel scheme. To reduce energy consumption while maintaining good connectivity between sentinel nodes, we compose our solution on two main concepts, node adaptation and link adaptation. The first algorithm uses node adaptation technique and per...

Coverage and connectivity both are important in wireless sensor network (WSN). Coverage means how well an area of interest is being monitored by the deployed network. It depends on sensing model that has been used to design the network model. Connectivity ensures the establishment of a wireless link between two nodes. A link model studies the connectivity between two nodes. The probability of e...

The work presented here is the first attempt at creating a probabilistic constituency parser for Polish. The described algorithm disambiguates parse forests obtained from the Świgra parser in a manner close to Probabilistic Context Free Grammars. The experiment was carried out and evaluated on the Składnica treebank. The idea behind the experiment was to check what can be achieved with this wel...

In this paper, we formalize the Menger probabilistic normed space as a category in which its objects are the Menger probabilistic normed spaces and its morphisms are fuzzy continuous operators. Then, we show that the category of probabilistic normed spaces is isomorphicly a subcategory of the category of topological vector spaces. So, we can easily apply the results of topological vector spaces...

in this paper, we formalize the menger probabilistic normed space as a category in which its objects are the menger probabilistic normed spaces and its morphisms are fuzzy continuous operators. then, we show that the category of probabilistic normed spaces is isomorphicly a subcategory of the category of topological vector spaces. so, we can easily apply the results of topological vector spaces...

in this paper, we introduce the  probabilistic normed groups. among other results, we investigate the continuityof inner automorphisms of a group and the continuity of left and right shifts in probabilistic group-norm. we also study midconvex functions defined  on probabilistic normed groups and  give  some results about locally boundedness of such  functions.

Abstract. Predicting potential links between nodes in a network is a problem of great practical interest. Link prediction is mostly based on graph-based features and, recently, on approaches that consider the semantics of the domain. However, there is uncertainty in these predictions; by modeling it, one can improve prediction results. In this paper, we propose an algorithm for link prediction ...

In this paper, we define the concepts of modified intuitionistic probabilistic metric spaces, the property (E.A.) and  the common property (E.A.) in   modified  intuitionistic probabilistic metric spaces.Then, by the commonproperty (E.A.), we prove some common fixed point theorems in modified intuitionistic Menger probabilistic metric spaces satisfying an implicit relation.