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We address these issues by adopting a social media approach to studying network formation.
The CND concept has developed into a theoretical framework that is composed of many network properties, models, and theories, and is of great use for studying network structure.
Studying network companies in the energy sector, as well as in other network-based sectors, we have come across many dilemmas.
This chapter explains the importance of studying network traffic patterns to look for any scope for energy saving in a virtualized environment.
In this example, CND-based network theories can hardly distinguish the two systems, but if expertise similarity in a sub-team will lead to good performance, then we know that team 1 is better than team 2. Despite the theoretical success of the CND in studying network structure, most realistic case studies of network systems have to consider both topology and node activities simultaneously.
The question being asked here is therefore whether steady-state mRNA abundance or any of two factors is a more informative measurement target for studying network dynamics.
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Demonstrator for Intelligent Vehicular Environments [36] is a modular, flexible (i.e., easily adapted and updated), reconfigurable testbed demonstrator that allows studying network-layer aspects of vehicular communications (e.g., intra-vehicular, inter-vehicular, and vehicle to infrastructure communication), and advanced services for vehicular users.
Computer scientists also have a venerable history of studying networks.
Statistical physicists studying networks focus on advanced mathematics, modeling, and computer programming.
Our approach for studying network-level activity focuses on artificially constructed isolated micro-circuits.
Thus, we proceeded by studying networks with modified connectivities.
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