Exact(5)
Each pattern is denoted by a set of system characteristics.
The points to visit are denoted by a set of S which has number of p elements as (S = left{ {1, ldots,, p} right}).
As a result, a Flickr group can be denoted by a set of terms including comments and tags on photos of the pool, discussions, group name and description and by a set of social actions such as exchange of messages in a discussion board, comments and favorites on photos, and so on.
{text{t}}.,sumlimits_{a in A} {varPi_{ar} cdot mu_{a} } ge lambda_{r} quad r in R, (2) sumlimits_{a in A} {mu_{a} } = bar{n}, (3) lambda_{r} in left{ {0,1} right},quad mu_{a} in left{ {0,1} right},quad r in R,quad a in A, (4 where the road network is denoted by a set of links, A, and a set of OD pairs, R. The travel demand of OD pair r ∊ R is represented by q r.
This common subgraph can be represented by matching A to a and B to b, and it is denoted by a set of vertex correspondences as { A : a, B : b}.
Similar(55)
A graph (G) with N elements is able to define into a set (G= V,E)), where (V) is denoted by a finite set of vertices.
A functional atlas (or atlas for brevity) of G, denoted by A, is a set of facets that represents distinctive functional landscapes of G. Figure 1 depicts an atlas of three facets, with each facet decomposing the network into three functional modules.
We denote by E a set of finite linear measure in R +, not necessarily the same at each occurrence.
The cardinality of a set J will be denoted by J. T ϵ n X denotes a set of strongly ϵ-typical sequences x n ∈ X n, while A ϵ n X denotes a set of weakly ε-typical sequences x n ∈ X n, where ϵ > 0.
In this section, a cooperative network comprising a source terminal (S), N half-duplex AF fixed-gain relays (as denoted by the set of Ω={i=1,2,…,N}) and a destination terminal (D), is considered.
If we denote by A the sets of the candidates obtained with the first faulty cipher text except the correct value of S-box input and by B the sets of the candidates obtained with the second faulty cipher text except the correct value of S-box input, we can identify the correct value with probability: P = P ( A ∩ B = ∅ ) = P ( A ∩ B = 0 ) = 16 7 × 16 − 7 3 16 7 × 16 3 ≃ 15%%.
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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