Within the framework designed for obfuscating Android applications, we implement the "Naïve Bayesian Classifier" algorithm for the optimized obfuscation of the software complexity and the performance, and show that it outperforms the algorithm whose predictions rely on mean values.
In parallel, these algorithms rely on mean and standard deviation of resource utilization that gives an indication of future load of a VM which also can be an approach independently for overload detection [15].
Since the amount of food taken over 4 hrs by single animals was close to the limit of detection, we decided to rely on mean food amounts taken per cage (i.e., per 3 mice), whereby each treatment group consisted of n = 6 cages.
When information is available from individual patients in a trial we do not have to rely on mean values.
Lidar-based biomass estimates that rely on mean canopy height may be particularly sensitive to height biases from sampling issues that influence the accuracy of the DTM.
These findings illustrate how approaches that rely on mean canopy height to estimate aboveground biomass are sensitive to DTM errors that arise from variability in lidar sampling density.
