Sentence examples for optimal because it from inspiring English sources

Moreover, if there is a V Y such that all components in diag{I−G} are minimized simultaneously, then this V Y must be optimal because it provides the largest possible freedom to optimize over the rest variables, i.e., U X, U Y, Λ X, and Λ Y. Applying (9.H.2 in [12]) on G, we obtain λ { G } ≺ w diag { G ̂ }, (28).

There would be no national defense, even though such defense is arguably socially optimal because it deters armed invasion.

For example, reducing the extent of exposed invasion edge, through spread, removal, or strategically employing landscape features, can be optimal because it reduces long-term containment costs.

This option is not optimal because it turns the program into a black box, but it may be acceptable if the operations performed by the software are sufficiently clear.

The current standard of monitoring transplant patients by drug levels is not optimal because it does not take into account the different and individual effects of immunosuppressive drugs on each patient.

However, a water:ethanol ratio of 0.5 0.5 (wt/wt) was deemed optimal because it is comprised of green solvents and yielded results that were greater than 90% of the multi-response maximum values.

In the past I feared inconveniencing my narrators, often settling for a less optimal video shot because it was easier for them.

"There is nothing inherently wrong or unethical with this traditional onboarding approach, but we believe it is sub-optimal because it keeps employees emotionally detached from their jobs and fails to generate the most productive, innovative work environment," Dr. Gino told me.

They've been banished by an ad hoc coalition of lobbyists loaded with money, loud-mouth talk-show hosts who will flame anyone who crosses them, political consultants who warn that asking Americans to do anything important but hard makes one unelectable and a citizenry that doesn't even ask for optimal anymore because it believes that optimal is impossible.

For both steps, we identified 0.05 as an optimal value because it achieves the optimal combination of performance and model parsimony.

The effects of drift limit the ability of the population to stay close to the optimal combination because it is harder to optimize more independent traits simultaneously.