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The correlation between network behavior and structure was investigated using simulations.
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In the context of SDN, faults are any root causes that trigger the mismatch between underlying network behavior and high-level network policies.
PeerSharkPeerShark clusters flows based on statistical features obtained from their network behavior and then creates conversations between the flows in the same cluster.
Visualization of the network behavior and its changes over time.
The microRNA hsa-miR-9 correlated with network behavior and presents binding affinities with network members in a manner that suggests control over network behavior.
Acknowledging the expanding role of complex networks in numerous scientific contexts, we examine significant functional and topological differences between bridge and brick motifs for predicting network behaviors and functions.
Figures 2 a-1 and a-2 show the correlation between two typical network behaviors, SBA and hyper-excitable activity (HEA), and the total number of 2, 3, and 4-node APFL motifs in 12-node pulsed neural networks (see Figure 2 a-1, a-2).
In MPI, two types of symptoms are used to identify and reason about network faults: mismatched states (i.e., high-level specification or low-level configuration of network behavior) between layers, and system logs of different hardware components (e.g., virtual or physical interfaces, links, disks).
To map out the connection between original personality and online social network behavior, they have presented two studies and examined how real personality traits are expressed in Facebook.
Network kinetics is widely studied, and so is the connection between network structure and behavior.
Simulations were performed to assess network behavior before adaptation (basal conditions) and after adaptation (trained network).
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CEO of Professional Science Editing for Scientists @ prosciediting.com