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It consists of a line graph template, on which users can enter data, labels for the axes, and a title.
Fig. 4 SDN reference model and component causality graph template.
As an example, we describe how to construct a causality graph template for NF as shown in Fig. 4. Please note that a causality graph template for a SDN switch is constructed differently due to the additional involved logical layers.
A causality graph template represents a local perspective of symptom-fault causality related a specific network entity.
A causality graph template represents the causal correlation between symptoms and faults for a specific network entity.
The final De Bruijn Graph, the concatenated Euler circuit and the corresponding graph template are shown in Figure 16 e).
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MPI uses component dependency graph templates to automatically model end-to-end services into a symptom-fault bipartite belief network.
Referring to the component causality graph templates derived from SDN reference model, the implementation view of the current running network services can be modeled as a belief network.
Referring to the component causality graph templates derived from SDN reference model, each Implementation View of a provisioned network service can be modeled to a Service Belief Network.
Using component causality graph templates derived from the SDN reference model, the Belief Construction module models each service provisioning policy to the corresponding Service Belief Network (Fig. 3 d).
the deployment of a pre-image algorithm to map the descriptor image points in the feature space back to the input space of the descriptors, and. the design of a probabilistic strategy to convert new descriptors into meaningful chemical graph templates.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com