Following the notation, the ordered probit model was expressed as (1) Prob y i = y 0 | x i = Ф p 1 − x i * b (2) Prob y i = y j | x i = Ф p j + 1 − x i * b − Ф p j − x i * b j = 1, 2, …, k − 1 (3) Prob y i = y k | x i = 1 − Ф p k − x i * b here yj (j=0,1,…k) were the discrete values of yi and Ф was the standard normal cumulative distribution function [ 3, 39].
A Well just put two crosses then I think B Here?
For each investigated host component h j, to associate a link to all its related botnets with the weight I(b i |h j ) (here, I(b i |h j )=C F(b i )).
For each investigated host component h j, to associate a link to all its related botnets with the weight I(b i |h j ) (here, I(b i |h j )=C F(b i )). Figure 3 Plausible Bot graph.
The Hausdorff distance between the sets A and B is then defined by: d H (A, B) = max {min j d a1, b j ),..., min j d(a m, b j ), min i d(a i, b1),..., min i d(a i, b n )} (1) Here the terms d(a i, b j ) denote the usual Euclidean distance between the points.
Here P i : B ¯ → ( a, b ), i = 1, …, p, are continuous functionals from Corollary 9.
Here, a i, b i, and c i ; i = 1, 2 are called consequent or linear parameters of ANFIS.
Here, b i ( b i † ) is the annihilation (creation) operator at the fermion site i, and a i ( a i † ) is the phonon annihilation (creation) operator at site i.
Here, ϕ i (b −i,g 1,g 2) is the threshold to queue i when the other user's queue state is b −i and channel states are g 1 and g 2. Let ϕ i be constructed by stacking ϕ i for all ((b_{-i},g_{1},g_{2})in mathcal {B}_{-i}times {mathcal {G}_{1}}times {mathcal {G}_{2}}).
Here S(a i, b i )=1 if a i = b i and a i ≠0.
