205 research outputs found
Discrete Mathematics and Symmetry
Some of the most beautiful studies in Mathematics are related to Symmetry and Geometry. For this reason, we select here some contributions about such aspects and Discrete Geometry. As we know, Symmetry in a system means invariance of its elements under conditions of transformations. When we consider network structures, symmetry means invariance of adjacency of nodes under the permutations of node set. The graph isomorphism is an equivalence relation on the set of graphs. Therefore, it partitions the class of all graphs into equivalence classes. The underlying idea of isomorphism is that some objects have the same structure if we omit the individual character of their components. A set of graphs isomorphic to each other is denominated as an isomorphism class of graphs. The automorphism of a graph will be an isomorphism from G onto itself. The family of all automorphisms of a graph G is a permutation group
LIPIcs, Volume 274, ESA 2023, Complete Volume
LIPIcs, Volume 274, ESA 2023, Complete Volum
Computer science: the hardware software and heart of IT
1st edition, 201
Data Mining
The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics. This book presents basic concepts, ideas, and research in data mining
A Survey on Centrality Metrics and Their Implications in Network Resilience
Centrality metrics have been used in various networks, such as communication,
social, biological, geographic, or contact networks. In particular, they have
been used in order to study and analyze targeted attack behaviors and
investigated their effect on network resilience. Although a rich volume of
centrality metrics has been developed for decades, a limited set of centrality
metrics have been commonly in use. This paper aims to introduce various
existing centrality metrics and discuss their applicabilities and performance
based on the results obtained from extensive simulation experiments to
encourage their use in solving various computing and engineering problems in
networks.Comment: Main paper: 36 pages, 2 figures. Appendix 23 pages,45 figure
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