Table 2 lists the values for the following fundamental properties for each of these networks: average degree ((k_mathrm{avg})), algebraic connectivity ((G_{c})) [11], diameter (D), average path length (PL _mathrm{avg})), assortativity ((G_mathrm{a})) [12], modularity ((G_mathrm{m})) [13], average clustering coefficient (CC _mathrm{avg})) [1], and number of components (#comps).
The validity of each of these explanations and the degree to which each contributes to the energy-efficiency gap are relevant for crafting sensible policies, so Gerarden, Newell, and I hope that our new monograph can help inform both future research and policy.
Each of these techniques pose varying degrees of damage to the periosteum and bone marrow.
Using this model, we focus on the recovery of second order shape under different generic motions, each of these motions presenting different degrees of error sensitivity.
Each of these barriers had varying degrees of perceived importance (Table 3).
The number of genes with significantly altered expression in each of these processes and their degrees of over-representation is noted in Table 4.
Answering each of these questions requires some degree of hermeneutics, especially when it comes to inferring the meaning of words such as "incompatible" and "publicity".
Each of these probabilities indicates the degree of confidence, denoted by h i j f, with which class e j is associated with shot s i. Dynamic Bayesian Networks (DBNs), and in particular HMMs, have been widely used in semantic video analysis tasks due to their suitability for modeling pattern recognition problems that exhibit an inherent temporality (Section 2.1).
Self-confidence has been my own downfall as a CrossFit Games competitor in the past, and I can attribute its lacking to each of these reasons to some degree.
