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These classifications are determined based on population size and the distance of a location from the nearest urban centre in relation to access to goods and services [ 27].> Data were collected from students across the spectrum of location classifications with the majority classified as ASGC-RA 3 5 (Table 2).
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This source enabled location, classification, and measurement of failures.
Thus, the time-course of target location classification accuracy did not differ between human and non-human faces.
Indexed by author, title, subject, series, publisher, place of publication, country, date, language, location, classification and reference number.
Effective fault location classification and especially performance degradation assessment of a roller bearing have been the subject extensive research, which can reduce costs and the nonscheduled down time.
Linear mixed effects models were fitted to estimate the effect of target type (exemplar versus category) and face species (human versus non-human) on peak and latency to peak target location classification accuracy.
Target type (exemplar or category) could be classified from approximately 100 ms, with higher accuracy for human than non-human faces at a latency (approximately 175 200 ms) that preceded target selection (based on latencies to peak target location classification, Table 2).
In this paper, however, we consider a machine-learning approach of logistic regression for location classification.
We also implement a simple location classification algorithm based on logistic regression on a cluster scale.
Note that CFFR-LR suffers from more interference than its ideal counterpart due to sub-optimal location classification and the distributed architecture.
For CFFR-LR, on the other hand, we are only interested in the running time of performing the location classification, scheduling and bandwidth partitioning.
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