Complex Networks: Advances in Research and Applications


Sébastien Faubert (Editor)

Series: Physics Research and Technology
BISAC: SCI055000

Chapter One focuses on investigational data on the fluorescence of DNA complexes inside neutrophils in flow cytometry with nanometer spatial resolution. Fluorescence visualizes oxidative activity of all coding and non-coding DNA parts in the full set of chromosomes. Chapter Two studies real-world networks based on a centrality metric called the Leverage Centrality metric which has been recommended as a means of identifying neighborhood hubs. The LevC of a node is a comparative measure of the connectivity of a node vis-a-vis its neighbors. In Chapter Three, the author goes on to examine neighborhood overlap, bipartivity index, and algebraic connectivity as edge centrality metrics to measure the consistency of links for mobile sensor networks. For several instances of node density and mobility, the author observes the stability of the network-wide data gathering trees determined using the proposed three edge centrality metrics to be significantly larger than the stability of the LET-based data gathering trees. Finally, Chapter Four proposes a fusion condition with the goal of preventing wrong fusions and alleviating the effect of the resolution limit. The suggested condition can also be used in other algorithms that make community fusions.

Table of Contents

Table of Contents


Chapter 1. Super Dense Fractal Networks for Multi Scale Activity of DNA Inside Cells (pp. 1-54)
N. E. Galich

Chapter 2. Leverage Centrality-Based Assortativity Analysis of Real-World Network Graphs (pp. 55-90)
Natarajan Meghanathan

Chapter 3. Location and Mobility Independent Theoretic Graph Metrics to Quantify the Stability of Links for Mobile Sensor Networks (pp. 91-104)
Natarajan Meghanathan

Chapter 4. A Fusion Condition for Community Detection with Modularity (pp. 105-136)
Olivier Gach and Jin-Kao Hao

Index (pp. 137)


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