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The phrase "subject to penalization" is correct and usable in written English.
It can be used in contexts where actions or behaviors may lead to penalties or punishments, often in legal, academic, or organizational settings.
Example: "Failure to comply with the regulations will result in being subject to penalization by the governing body."
Alternatives: "liable to punishment" or "subject to penalties".
Exact(1)
Traditionally, errors are "sharp-end-wise" attributed to individual mistakes, and blamed professionals may be subject to penalization.
Similar(58)
PLR maximizes β m subject to a ridge penalization | β m |2 controlled by λ ∈ [0, 2], (8) The size of λ directly affects the size of the estimates for β m.
The method is based on a penalization technique where the system is considered as a single flow, subject to the Navier Stokes equation with a penalization term that enforces continuity at the solid fluid interface and rigid motion inside the solid.
The similarity between these two binding cores by GS would be very low due to penalization even if they are identical.
Here the authors propose to study, in the case of a simple mechanical problem, that of a metal cube subjected to a given pressure, three procedures, which differed in terms of the code and type of topology optimization calculations performed and the level of penalization applied.
With this connection to least squares regression it is straightforward to use penalization terms to impose sparsity on v ˜. (4) (u, v ˜ ^ ) = arg min u, v ˜ ‖ X − u v ˜ ^ T ‖ F 2 + λ P (v ˜ ), where P (v ˜ ) is a penalization term that induces sparsity on v ˜ and λ is a tuning parameter that determines the strength of the penalization.
IPA has a parameter, λ, which controls the relative weights given to the optimization of the PLF matrix and to the penalization of close-to-singular solutions.
A proper continuation scheme is proposed to all penalization coefficients in order to achieve black-and-white solutions.
The aim of this work is to combine penalization and level-set methods to solve inverse or shape optimization problems on uniform cartesian meshes.
It also introduced changes to the penalization coefficient linked with age of retirement.
Violating constraints types 2, 3 and 10 would lead to a penalization in the objective function value as indicated by Eqs.
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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