In this paper we define the Smarandache hoop-algebras and Q-Smarandache filters, we obtain some related results. After that, by considering the notions of these filters we determine relationships between filters in hoop-algebras and Q-Smarandache filters in hoop-algebras. Finally, we introduce the concept of Smarandache 2-structure and Smarandache 2-filter on hoop-algebras.

In this paper, Generalized Aggregated Uncertainty measure 2 (GAU2), as a new uncertainty measure, is considered to evaluate uncertainty in a localization problem in which cameras’ images are used. The theory that is applied to a hierarchical structure for a decision making to combine cameras’ images is Dezert-Smarandache theory. To evaluate decisions, an analysis of uncertainty is executed at every level of the decision-making system. The second generalization of Aggregated Uncertainty measure (GAU2) which is applicable for DSmT results is used as a supervisor. The GAU2 measure in spite of the GAU1 measure can be applied to the problems with vague borders or continuous events. This measure may help to make decisions based on better preference combinations of sensors or methods of fusion. GAU2 is used to evaluate uncertainty after applying classic DSmT and hybrid DSmT with extra knowledge. Therefore by using the decision making system, results with less uncertainty are generated in spite of high conflict sensory data.

Today due to the importance and necessity of implementing security systems in homes and other buildings, systems with higher certainty, lower cost and with sensor fusion methods are more attractive, as an applicable and high performance methods for the researchers. In this paper, the application of Dempster-Shafer evidential theory and also the newer, more general one Dezert-Smarandache theory for implementing as a home security system and also using sensor data fusion have been considered. The benefits of multisensor fusion with direct connection to the control unit, in comparison with the traditional single sensor systems, have been shown.

Today due to the importance and necessity of implementing security systems in homes and other buildings, systems with higher certainty, lower cost and with sensor fusion methods are more attractive, as an applicable and high performance methods for the researchers. In this paper, the application of Dempster-Shafer evidential theory and also the newer, more general one Dezert-Smarandache theory for implementing as a home security system and also using sensor data fusion have been considered. The benefits of multisensor fusion with direct connection to the control unit, in comparison with the traditional single sensor systems, have been shown.

In this paper, target differentiation based on the pattern of data which are obtained by a set of two ultrasonic sensors is considered. A neural network based target classifier is applied to these data to categorize the data of each sensor. Then the results are fused together by Dempster–Shafer theory (DST) and Dezert–Smarandache theory (DSmT) to make a final decision. The Generalized Aggregated Uncertainty measure named GAU1, as an extension to the Aggregated Uncertainty (AU), is used to evaluate DSmT. Then the GAU1 and AU as the uncertainty measures are applied to the obtained results of the decision makers to evaluate DSmT and DST accordingly. The introduced configuration for decision making has enough flexibility and robustness to use as a distributed sensor network.

Zadeh conceptualized the theory of fuzzy set to provide a tool for the basis of the theory of possibility. Atanassov extended this theory with the introduction of intuitionistic fuzzy set. Smarandache introduced the concept of refined intuitionistic fuzzy set by further subdivision of membership and non-membership value. The meagerness regarding the allocation of a single membership and non-membership value to any object under consideration is addressed with this novel refinement. In this study, this novel idea is utilized to characterize the essential elements e. g. subset, equal set, null set, and complement set, for refined intuitionistic fuzzy set. Moreover, their basic set theoretic operations like union, intersection, extended intersection, restricted union, restricted intersection, and restricted difference, are conceptualized. Furthermore, some basic laws are also discussed with the help of an illustrative example in each case for vivid understanding.

In order to solve the complex decision-making problems, there are many approaches and systems based on the fuzzy theory were proposed. In 1998, Smarandache introduced the concept of single-valued neutrosophic set as a complete development of fuzzy theory. In this paper, we research on the distance measure between single-valued neutrosophic sets based on the H-max measure of Ngan et al. [8]. The proposed measure is also a distance measure between picture fuzzy sets which was introduced by Cuong in 2013 [15]. Based on the proposed measure, an Adaptive Neuro Picture Fuzzy Inference System (ANPFIS) is built and applied to the decision making for the link states in interconnection networks. In experimental evaluation on the real datasets taken from the UPV (Universitat Politè cnica de Valè ncia) university, the performance of the proposed model is better than that of the related fuzzy methods.