The RMS (root-mean-square) quality of fit (dipolarity) was defined by {1 − Σ Vobs − Vcal)/Σ Vobs)}1/2 × 100, where Vobs and Vcal were the observed and calculated potentials at each electrode.
Only positions where the root mean square mapping quality was greater than 20 were considered.
These locations in the nuclear genome were filtered to maintain variants for which the total coverage in the samples was between 4 and 500 reads (to limit the erroneous calling of variant positions in repetitive or duplicated regions), and the RMS (root mean square) mapping quality was greater than or equal to 10.
Positions with root mean squared mapping qualities less than 15 and insertion/deletion polymorphisms were ignored.
Mean Square Deviations of the quality characteristics are used as DEA inputs.
As the value of root mean square error decreases the quality of image increase.
This comparison examined through computer simulation for 64 carriers and 16-QAM OFDM system, with a Saleh's TWT amplifier, is based on some quality measure (mean square error), the required training time to reach a particular quality level, and computation complexity.
For each species, we obtained a diploid consensus genome sequence and filtered it by excluding sites at which the root-mean-square mapping quality of reads covering the site was below 25, the inferred consensus quality was below 20, and read depth was either more than twice or less than one-third of the average read depth across the genome.
To evaluate these images quantitatively, we use Root mean square (RMS), structural similarity, and perceptual quality metric (PQM) metrics which are discussed in the following sub-sections.
These are mathematical-based metrics, ranging, for video quality assessment, from mean square error (MSE) [6] and peak signal-to-noise ratio (PSNR) [6] to structural similarity (SSIM) [7] and more complex metrics possibly better estimating the perceived quality [8].
First, for the histogram-based schemes, it has the advantage of guaranteed output image quality because the mean square error (MSE) between the marked and original image is limited to be below 1, leading to the result of at least 48.13 dB in PSNR value [3].
