The phrase "a penalisation" is correct and usable in written English.
It can be used in contexts discussing punishment or consequences for a violation of rules or laws.
Example: "The committee decided to impose a penalisation on the team for their unsportsmanlike conduct during the match."
Alternatives: "a penalty" or "a sanction".
The Bayesian model class selection approach imposes a penalisation against overly complex model candidates and admits a selection of the most plausible HST-model according to the maximum value of model evidence provided by the data or relative plausibility within a set of model class candidates.
The sinograms generated at the time of scanning were retrospectively processed using the new ToF BPL reconstruction algorithm (Q.Clear, GE Healthcare, Milwaukee, USA) using a penalisation factor (beta) of 400, the only user-input variable for this algorithm.
However, unlike the SSA, the functional to be minimised involves a new penalisation term for the interlayer jumps of the velocity, which represents the vertical shear stresses induced by interlayer sliding.
These studies demonstrate that the proposed diffuse interface immersed boundary method, which could be related to a class of penalisation approaches, is a robust and promising alternative to computationally expensive conformal moving mesh algorithms as well as the class of sharp interface immersed boundary methods for multibody problems in multi-phase flows.
Notice also that a "softened" inequality restriction is nothing but an equality one with no penalisation on one of the slack variables above.
It also shows that the pilot-data-based estimation method can significantly overcome such penalisation and provides a performance better than the DL for all N f considered.
We are strong advocates that judgment and penalisation is not an appropriate form of behaviour change and other more efficient behaviour change models should be applied in the healthcare sector.
The exertion of control and imposition of fines on behalf of buyers impel farmers to implement a QMS so as to avoid penalisation.
The exertion of control and the imposition of fines by public authorities compel farmers to implement a QMS in order to avoid penalisation.
This permissive p-value was used to assure that the multivariate linear model did not contain artificially stringent associations, as the penalisation procedure also functions as a stringency filter, reducing the false discovery rate.
However, shortage of data, caused by too many variables compared with the number of events, may lead to higher penalisation, and reduce ability of a model to predict the outcome in the extremes.
