Turiyam Graphs and its Applications

The single valued neutrosophic set (SVNS) was developed to handle uncertainty in information depending on independent states called truth, indeterminacy and false. Recently, the Turiyam set was introduced for dealing with the uncertainty in data sets when those states are in silent mode based on human quantum cognition or awareness. In this way, this set gives a way to explore the uncertainty in data sets beyond the existing true, false, and indeterminacy regions. The precise analysis of data with the Turiyam set and its graphical representation is indeed a requirement for knowledge processing tasks. To achieve this goal, the current paper introduces Turiyam graphs with illustrations. In addition, we define a complete Turiyam graph, a strong Turiyam graph, and a constant Turiyam graph. Further, we apply a constant Turiyam graph to the Wi-Fi system

Fuzziness, Indeterminacy and Soft Sets: Frontiers and Perspectives

The present paper comes across the main steps that laid from Zadeh's fuzziness ana Atanassov's intuitionistic fuzzy sets to Smarandache's indeterminacy and to Molodstov's soft sets. Two hybrid methods for assessment and decision making respectively under fuzzy conditions are also presented through suitable examples that use soft sets and real intervals as tools. The decision making method improves an earlier method of Maji et al. Further, it is described how the concept of topological space, the most general category of mathematical spaces, can be extended to fuzzy structures and how to generalize the fundamental mathematical concepts of limit, continuity compactness and Hausdorff space within such kind of structures. In particular, fuzzy and soft topological spaces are defined and examples are given to illustrate these generalizations.Comment: 15 pages, 2 figures, 3 Tables, 30n reference

Quantify resilience enhancement of UTS through exploiting connect community and internet of everything emerging technologies

This work aims at investigating and quantifying the Urban Transport System (UTS) resilience enhancement enabled by the adoption of emerging technology such as Internet of Everything (IoE) and the new trend of the Connected Community (CC). A conceptual extension of Functional Resonance Analysis Method (FRAM) and its formalization have been proposed and used to model UTS complexity. The scope is to identify the system functions and their interdependencies with a particular focus on those that have a relation and impact on people and communities. Network analysis techniques have been applied to the FRAM model to identify and estimate the most critical community-related functions. The notion of Variability Rate (VR) has been defined as the amount of output variability generated by an upstream function that can be tolerated/absorbed by a downstream function, without significantly increasing of its subsequent output variability. A fuzzy based quantification of the VR on expert judgment has been developed when quantitative data are not available. Our approach has been applied to a critical scenario (water bomb/flash flooding) considering two cases: when UTS has CC and IoE implemented or not. The results show a remarkable VR enhancement if CC and IoE are deploye