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In the constructed nuclear model, if the Gaussian component number M (such as M=N) is large, it needs to calculate the fitting degrees (probability) of a test TRIOD to all constructed Gaussian models, and thus, the computational cost will be increased linearly to the component number.
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We report Figure 5, that shows the complementary cumulative degree probability distribution (ccdf) as a function of the degree in the cases discussed above.
Now the routing overhead model (5) contains three unknown parameters: expected forward degree, probability of no collision, and the probability of no channel error loss.
To test the proposed approaches and the derived formulas, we use a synthetically generated configuration type random graph with a given joint degree-degree probability distribution, which takes into account correlation in degrees between neighbor nodes.
For this reason, hubs were classified as being those nodes having a within module degree probability less than 0.01.
Nodes that had within-module degree probabilities (pki) less than 0.01 were delineated as hubs.
The roles of hubs were identified as provincial or connector based on participation coefficients and within module degree probabilities.
The number of edges attached to a node is called the node degree and probability distribution of these degrees over the whole network is called degree distribution.
Note the varying degrees of probability.
Propositions assert and deny information and are related to degrees of probability and degrees of usuality, which are referred to as modalization.
These subtypes of epistemic modality correspond to the degrees of probability in the SFG notion of modalization.
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