The first step is to develop a conceptual data model diagram and a set of functional dependencies (FDs) to correspond to each of the assertions given.
Then, for a given test order t and a set of d dependencies to be broken, the attribute complexity A is calculated according to Equation 1, where n is the total number of modules and k is any module included before the module i, in test order t.
Then, for a given test order t and a set of d dependencies to be broken, the operation complexity O is computed as defined by Equation 2. O ( t ) = ∑ i = 1 n ∑ j = 1 n OM ( i, j ) ; j ≠ k (2).
A compilation of experimentally verified interactions between HIV-1 and human proteins and a set of HIV-dependency factors (HDF) allowed insights into the topology and intricate interplay between viral and host proteins on a large scale.
Here, we pooled experimentally verified interactions between HIV-1 and human proteins, along with a set of HIV-dependency factor proteins (HDF), to investigate the topology of interactions between viral and host proteins on a large scale.
The conditional independence (Markov) properties permit a rich set of dependencies among the nodes and hence, the connectivity of a Markov network can reveal complex relationships between its nodes (Allen and Liu, 2013; Jalali et al., 2011).
Windows has blown it for a while, and although their mobile and embedded solutions are potentially powerful, they are part of a labyrinthine set of dependencies and legacy requirements, caught in the enormous web of the Microsoft software ecosystem.
This screen, carried out in colon cancer cells and followed up in a panel of lung cancer cell lines, revealed a more complex set of dependencies, with KRAS mutant cells being particularly reliant on genes in pathways related to mitotic functions, such as the Polo-like kinase PLK1, components of the anaphase-promoting complex (APC) and the proteasome.
Application of a refactoring operation creates a new set of dependency in the revised design as well as a new set of further refactoring candidates.
We encode a sparse and changing set of dependencies between the channels using a Markov-switching Gaussian graphical model for the innovations process driving the channel dynamics and demonstrate the importance of this model in parsing and out-of-sample predictions of iEEG data.
