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reachability home agent.
Stochastic reachability analysis is a key factor in the verification and deployment of stochastic hybrid systems.
It operates with local densities of objects in the dataset by using the definition of local reachability density and calculates value of "local outlier factor" that indicates the degree of object's dissimilarity to other compounds in the data set.
The reachability and antecedent sets for each element are found out from the final reachability matrix.
Basically, local outlier factor is the average of the ratio of local reachability densities of objects in k-distance neighborhood of x to the local reachability density of x itself and given as LO F_{k(x) = frac{{sumlimits_{{z in N_{k} (x)}} {frac{{R_{{text{lrd}},k}(z)}}{{R_{{text{lrd}},k}(x)}}} }}{{|N_{k} (x)|}} (5).
Section 3.4 evaluates gene centrality based on the reachability profiles.
The local outlier factor is an average of the ratios of the local reachability densities of objects to those of object's k nearest neighbors (Eq. 15).
The reachability profile describes the ability of regulator genes to affect the transcription factors.
The local outlier factor LOF MinPts (p) for object p is computed based on the reachability distance as defined in Eq. 12. MinPts is the number of neighbours which are considered to belong to the local neighbourhood of the object, N MinPts (p) is the set of these neigbours.
However, typical constraints of energy conservation from battery-driven design, local spectrum availability, reachability with other sensor nodes, and large-scale network architecture with complex topology are factors that maintain an acceptable network performance in the design of CWSN.
Thus, for each gene, we compute its centrality by comparing the reachability profile for the original network with the reachability profile obtained when the gene is missing.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com