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Fig. 8 The best Pareto fronts produced by each algorithm for datatset-3 and HighPrefs scenario on 30 runs, considering only HV metric.

Fig. 4 The total power needed by each algorithm for satisfying different interference powers under the condition that transmitter rate is fixed.

Fig. 3 The total power needed by each algorithm for satisfying different transmitter rates under the condition that interference power is fixed.

Table 5 illustrates the best biclusters provided by each algorithm for the second dataset.

Table 4 shows the best biclusters provided by each algorithm for the first dataset.

The primary measure of accuracy was the positive predictive value (PPV), the proportion of people identified by each algorithm for whom COPD was confirmed.

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Using the numbers of communities generated by each algorithm ( N = 322 for the map equation versus N = 413 for modularity maximisation), we calculated the Z-score for these prediction scores.

As a test, we measured the average absolute difference between the heat index values calculated by each algorithm and air temperature for cool and cold days (air temperature < 20°C/68°F, the cutoff for Steadman's original tables) in the U.S. state capitals in 2011.

As suggested in the "Evaluation of the amount of computational resources used by each algorithm" subsection, the configuration adopted for the TW parameter of the CARTE is capable to create direct impacts on the hit ratio, as well as on the number of substitutions performed by this algorithm.

Sensitivity, representing the proportion of correct diagnoses made by each algorithm, was 95.7%, 88% and 70% for CHUK, MSF and WHO, respectively.

It is found from Table 1 that the solution produced by the algorithm for each of the considered problems is the same as its optimal solutions [29].

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