More important for the purposes of this article is the nature of the problem: from among a class of curves, select the one that minimizes some quantity.
We show that, under this model, the original coloring problem gives rise to a new coloring version (called Probabilistic Min Coloring) where the objective becomes to determine a partition of V into independent sets S1,S2,…,Sk, that minimizes the quantity ∑i= 1kf(Si), where, for any independent set Si,i= 1,…,k, f(Si)= 1-∏vj∈Si 1-pj).
The test sample is a stack of layers, and we can look for the set of d x that minimizes the quantity Δ2 defined as follows: Δ 2 = ∑ a x ∑ a x − I x ∑ I x 2, (2).
The optimization problem can now be defined as finding the vector x that minimizes the quantity ||Σ x−b||2+λ2 ||x||2, where b is a column vector, ||x|| indicates the norm of x, and λ is a positively defined regularization parameter.
In this way, the FBSF minimizes the quantity of fentanyl that is swallowed in the saliva and that is consequently lost during first-pass metabolism.[ 56] The size of each FBSF is directly proportional to the strength of the administered fentanyl dose.
Although minimizing this quantity is not equivalent to minimizing the global cost function (28), such a simplified minimization scheme is commonly adopted in many algorithms, such as [20, 31].
Both cost functions minimized a quantity that reduced the external knee adduction torque.
Minimizing this quantity gives us the optimal measurements in different scenarios.
While larger paper tests (like those for pregnancy) are common, shrinking the paper and minimizing the quantity of the required chemical reagents reduces manufacturing costs.
By optimizing the distribution of the reinforcement, the aim is to minimize the quantity of material, thereby reducing costs.
