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On each test set randomly generated, a performance statistic based on AUC test statistics described by DeLong et al. [ 20, 21] was computed for the paired comparison between the new score and the benchmark score.
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The cost of generating a performance model can be decomposed into different contributions: model setup, model generation, and model retargeting.
Additionally, ATLAS simulation platform can generate a performance analysis of the particular characterized environments.
Because of the large amount of signaling load, the GIA is not very practical but can be employed for generating a performance benchmark.
A case study is presented to show how the system works to generate a performance measurement tool for evaluating the disassemblability of a mechanical product design with multiple users.
Essentially, the developed methodology is based on Process Approach (Cambridge Approach) technique that systematizes procedures for generating a performance measures set coherent to operations strategy objectives and also produces a consistent strategy implementation process.
That a TMS double-pulse can generate a performance decrement for stimuli presented far outside of the retinotopic region directly affected by the TMS, is most certainly an indication of a non-specific bias, e.g. due to the auditory or somato-sensory distractions accompanying the pulses.
The system is able to automatically generate a performance report for a set of CT images with annotated lytic and blastic metastases.
However, it should be noted that scoring of the CCFT may also include a measurement of endurance, that is, the number of 10 seconds holds that the subject can do at their achieved pressure level to generate a performance index.
Regardless of whether distribution of individuals on a thermal gradient is due to underlying variation in preferred temperature or the transient occupation of different temperatures within a range of preferred or non-lethal temperatures, deviations from the optimal fitness temperature should lower population mean fitness, generating a "performance load" on the population (sensu [ 28, 29]).
This set of sub-images was used as a standard to generate a user performance score (UPS) for each Citizen Scientist according to their performance in identifying cancer cells in the sub-images as follows: (1) All of the Citizen Scientists are assigned a preliminary UPS of 0.5 and the experts are assigned a UPS of 1 on initializing the algorithm.
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