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  • 1
    ISSN: 0020-7608
    Keywords: Computational Chemistry and Molecular Modeling ; Atomic, Molecular and Optical Physics
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A formula of the coefficient aN-K of the eigenpolynomials connected with the zero-order term's coefficient of the eigenpolynomials corresponding the k-order-induced subgraph's molecular fragments has been induced. From this formula, aN-K can be calculated and the contributions of the induced subgraph's molecular fragments to the stability and reactivity of the molecules are revealed. © 1994 John Wiley & Sons, Inc.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 0020-7608
    Keywords: Computational Chemistry and Molecular Modeling ; Atomic, Molecular and Optical Physics
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The characteristic polynomial associated with π-electrons of conjugated molecules are discussed by using subgraphs derived from molecular graphs as a basis for their construction. A practical method has been developed for evaluating the coefficient aK of conjugated molecules. Applying this method, the general formulas of evaluating the coefficient aK for homologous conjugated molecules have been obtained. The approach is illustrated on a few simple conjugated systems, including also a few polymeric systems. © 1996 John Wiley & Sons, Inc.
    Type of Medium: Electronic Resource
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  • 3
    Publication Date: 2018-04-26
    Description: Entropy, Vol. 20, Pages 315: Virtual Network Embedding Based on Graph Entropy Entropy doi: 10.3390/e20050315 Authors: Jingjing Zhang Chenggui Zhao Honggang Wu Minghui Lin Ren Duan For embedding virtual networks into a large scale substrate network, a massive amount of time is needed to search the resource space even if the scale of the virtual network is small. The complexity of searching the candidate resource will be reduced if candidates in substrate network can be located in a group of particularly matched areas, in which the resource distribution and communication structure of the substrate network exhibit a maximal similarity with the objective virtual network. This work proposes to discover the optimally suitable resource in a substrate network corresponding to the objective virtual network through comparison of their graph entropies. Aiming for this, the substrate network is divided into substructures referring to the importance of nodes in it, and the entropies of these substructures are calculated. The virtual network will be embedded preferentially into the substructure with the closest entropy if the substrate resource satisfies the demand of the virtual network. The experimental results validate that the efficiency of virtual network embedding can be improved through our proposal. Simultaneously, the quality of embedding has been guaranteed without significant degradation.
    Electronic ISSN: 1099-4300
    Topics: Chemistry and Pharmacology , Physics
    Published by MDPI Publishing
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