From (2.12) we can easily prove that (G(I)) is decreasing and (H(I)) is increasing.
Then, ω ′ i is decreasing (non-increasing) with δ i (see Fig. 3).
Specifically, if h i is an increasing function of i, it is easier for the greedy policy to be optimal than the case that h i is decreasing.
Thus, it is easy to see that (f (I)) is decreasing when (I>I_{1}) and increasing when (I< I_{1}).
We assume that k i + is constant or decreasing with index i, with k N + ≥ 0 ; the probability that a tumour cell of the i-th class is killed: p i. We assume that p i is decreasing with index i, with p N ≥0; the probability of transition T i → T i + 1to the state i: θ i.
Intuitively, as the frame size is increased, F T b, i) is decreased.
After the remote execution, ( varLambda i ) is decreased by ( {b}_j^i ), i.e., ( {varLambda}_i={varLambda}_i-{b}_j^i ).
For AP (a count vector), the bits of an atom i are straightforward to determine, the count for each pair involving atom i is decreased by one.
Then, during the small period Δt, slip with the amount of U i = V i + Δt is induced, and both shear stress and strength on the sub-fault i are decreased; the strength about ~B i U i /L i is decreased by the slip weakening.
If V i is provided with q i MIPS rate for the period t p, then, the value w i is decreased by q i × t p. In such case, V i finishes its service when w i becomes zero.
