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As a summary, Table 1 demonstrates the differences between all the mentioned graphs in terms of different behaviors and definitions.
In this paper, we present some new bounds for the scattering number, integrity, tenacity of regular graphs in terms of the spectrum.
To avoid computational complications, it is important to express the formulas for the product of F-sum of graphs in terms of their factor graphs.
Open image in new window Figure 1 Inventory graphs in terms of time: (a) raw material, (b) perfect products, (c) scrap items, and (d) product in the warehouse.
The implicit material selection knowledge is represented as a set of labeled instances and RDF instance graphs in terms of the concept model, which provides a formal approach to organizing the captured material selection knowledge.
We determine the lower and upper bounds for the F-index and the Narumi-Katayama index of the Cartesian product of F-sum of graphs in terms of their factor graphs for (F=R).
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We characterise quasidiagonality of the C⁎-algebra of a cofinal k-graph in terms of an algebraic condition involving the coordinate matrices of the graph.
We also measured the running time of MUSE at each iteration against different size of the graph in terms of the number of edges.
The degree diameter problem involves finding the largest graph (in terms of the number of vertices) subject to constraints on the degree and the diameter of the graph.
It is shown via a mixture of analytic and computer techniques that there exist realisations of this graph in terms of two circular DNA molecules.
If we think of a graph in terms of bars and joints, a rigid graph means "not deformable" or "not flexible" [12].
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