Sentence examples for loss decision making from inspiring English sources
fMRI: Functional magnetic resonance imaging; RT: Response time; BOLD: Blood oxygen level dependence; FWE: Family-wise-error; GLM: General linear model; MNI Monteal Neurological Institute WININ: Decision making after 3 consecutive winning trials; LOSS: Decision making after 3 consecutive losing trials; CONTROL: Control condition; ACC: Anterior cingulate cortex.
In fact, experimental evidence suggests that losses influence human decision making more than the simple payoff.
We then discuss scope for further research to develop and apply the implicit loss function to help decision making by policy makers and regulators.
The framework is a linear methodology which is based upon obtaining in turn output from each of the following analyses: hazard analysis; structural analysis; loss analysis, and finally decision making based on variables of interest, such as downtime or cost to repair.
It was a familiar tale for England at this World T20: a simple run chase complicated by a loss of nerve and poor decision making.
The following are the steps involved in implementing the proposed loss function approach (LFA) of decision making.
This critical step may correspond to the "loss of inhibitory control in decision making" against addiction suggested by some investigators [ 118].
One essential factor in successful implementation is physicians' faith in the guidelines, particularly reflected in the common physician concerns about the relevance of guideline for patients and the loss of autonomy in treatment decision making.
They also proposed that another controlling factor, namely, gain-loss frequency, can predict the decision making behavior in SGT and elucidate some inconsistent phenomenon in IGT [ 24, 25].
When cornerback Nnamdi Asomugha questioned the defensive decision making after the loss to the Lions, it was surely not the first time Reid grew concerned.
To achieve improved outcomes in an increasingly hazardous world, it is critical that we understand the appropriate role and type of models that can best inform effective decision making to reduce loss from unexpected environmental and societal shocks.
