In architecture design, the proposed algorithm with data reordering scheme is adopted.
In order to reduce the hardware cost, we use the concept of data reordering to change the data computation flow.
The algorithms for data reordering are given.
Based on this data reordering within each bit-plane, spectral bands of lower frequency or higher rate-distortion properties are transmitted with priorities.
The data reordering scheme reduces the arithmetic operations in saving of one subtractor hardware cost, as illustrated in Figure 5. Figure 5 Data reordering scheme.
In addition, to reduce the arithmetic operations in saving of one subtractor, a modified scheme of data reordering is constructed.
A program, BrowseTMA Reorder XSLT script [see BrowseTMAReorder.xsl in Additional file 1], was added to BrowseTMA that can convert unimproved TMA DES XML data to improved data by reordering elements and, if needed, adding consecutively numbered identifiers.
In order to compare growth trajectories between twins and singletons, the singleton data were reordered as a function of chronological age instead of survey year.
In Figure 3, we see that eight nodes 7,9,10,15,14,11,6,13 form a cluster in A, but not in B, when the synthetic data is reordered with the final column of X - T. Applying the procedure above, using permutation to randomize the networks M = 1000 times as described below, we obtained a p-value of 0.007.
For a single species, one can (i) generate a genome-wide contact map but also (ii) use the genomic contact data to reorder the contact matrix of a poorly assembled genome (top) in order to scaffold its contigs into a more likely structure (bottom left).
Applying the same procedure, we also obtained a p-value of 0.029 for the first 6 nodes 18, 20, 16, 15, 19, 17 when the synthetic data is reordered with the first column of X - T, which visually form a cluster in B, but not in A. These p-values (< 0.05) both indicate that the results are statistically significant.
