Soft robots are made of compliant materials that perform their tasks by deriving motion from elastic deformations. They used in various applications, e.g., for handling fragile objects, navigating sensitive/complex environments, etc., and typically actuated Pneumatic/hydraulic loads. Though demands soft continuously increasing engineering sectors, due to the lack systematic approaches, they pri...

In this paper the problem of creating a wireless infrastructure to control a vertical transportation system is addressed. The work assumes the use of the standard IEEE 802.15.4 as wireless control field bus. Throughout the paper different network topologies are analyzed together with the network management algorithms. As a result of this analysis the tree topology is selected and experimentally...

Uncertainty is an inherent property of all living systems. Curiously enough, computational models inspired by biological systems do not take, in general, under consideration this essential aspect of living systems. In this paper, after introducing the notion of a multi-fuzzy set (i.e. an orthogonal approach to the fuzzification of multisets), we introduce two variants of P systems with fuzzy co...

We study the fuzzy soft proximity spaces in Katsaras's sense. First, we show how a fuzzy soft topology is derived from a fuzzy soft proximity. Also, we define the notion of fuzzy soft δ-neighborhood in the fuzzy soft proximity space which offers an alternative approach to the study of fuzzy soft proximity spaces. Later, we obtain the initial fuzzy soft proximity determined by a family of fuzzy ...

Neural network is one of the new soft computing methods commonly used for prediction of the thermodynamic properties of pure fluids and mixtures. In this study, we have used this soft computing method to predict the coefficients of the Antoine vapor pressure equation. Three transfer functions of tan-sigmoid (tansig), log-sigmoid (logsig), and linear were used to evaluate the performance of diff...

For dealing with uncertainties researchers introduced the concept of soft sets. Georgiou et al. [10] defined several basic notions on soft θ-topology and they studied many properties of them. This paper continues the study of the theory of soft θ-topological spaces and presents for this theory new definitions, characterizations, and results concerning soft θ-boundary, soft θ-exterior, soft θ-ge...

Molodstov introduced soft sets to deal with uncertainties and not clear objects. Researchers developed the relationship between soft sets and information systems. Fuzzification of the notions of soft sets and soft topology have been discussed in the literature. In this paper, we define and establish the topological structures of fuzzy soft semi-open sets and fuzzy soft semi-closed sets. We intr...

Since the PCS needs to handle high power high voltage, the soft-switching topologies utilized in the design should have both ZVT and ZCT functions. A novel soft-switching topology that has both ZVT and ZCT functions is suggested. The new topology has both ZVT and ZCT functions by using two additional components, a switch and a diode. The auxiliary inductor for soft-switching is implemented insi...

In that paper, the fuzzy nonlinear programming problem is discussed. In order to obtain more accurate solution, the properties of fuzzy set and fuzzy number with linear membership function and fuzzy maximum decision maker is utilized to fuzzifying the crisp problem. In the illustration, we have given a refinement to obtain this solution.