The rationale behind SDN is twofold: it separates the data plane from the control plane and it introduces novel network control functionality based on abstract network representation.
The proposed method is based on a network representation enabling to match each network configuration with a Hopfield neural network in order to find the best path between any node pair by minimizing an energy function.
Based on this network representation, we can derive numeric scores for each country to describe their roles within the network; e.g., the total weight of outgoing edges adjacent to a given node may denote how actively that country participates in the detection of hazardous foodstuff.
We also review the use of novel statistical approaches based on a network representation of the functional connectivity and their application to the study of the rat brain functional architecture.
Besides the vector space model, there are text representations based on networks (or graphs), which can make use of some text semantic features.
Moreover, other representations than the FOL, for instance those based on networks [ 18- 21, 41, 43, 44], can be used to address distinct evolutionary questions, at different biological scales.
The average path length in our reconstructions is close to 3, which is the same as observed in many other metabolic networks based on the same network representation [ 37].
Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency.
The proposed model is based on a hierarchical network representation of the Gene Regulatory Network - the so-called Developmental Gene Execution Network (DGEN) - and evolution proceeds through a series of stochastic perturbations involving gene duplication, re-wiring and deletion.
The developed MILP scheduling models are based on state sequence network representation that has proven to inherently result in smaller problems in terms of binary variables.
