  In this report, a new fuzzy 2bit-AND parallel-to-OR, or simply, a fuzzy
binary AND/OR (FBAR) text data compression model as an algorithm is suggested
for bettering spatial locality limits on nodes during database transactions.
The current model incorporates a four-layer application technique:
string-to-AND/OR pairwise binary bit + fuzzy quantum with noise conversions.
This technique promotes a lossless data compression ratio of 2:1 up to values
approximately = 3:1, generating a spatially-efficient compressed data file
compared to nowadays data compressors. Data decompression/specific data
reconstruction initiates an AND/OR pattern match technique in respect of fuzzy
quantum indicators in the binary function field. The reconstruction of data
occurs in the 4th layer using encryption methods. It is hypothesized that
significant data compression ratio of 2n:1 for n>3:1 ratios, e.g., 32~64:1 are
achievable via fuzzy qubit indexing over classical byte blocks for every bit
position fragmented into a (1/2 upper +1/2 lower)-bit noise frequency parallel
to its counterpart signal comprised of AND/ORed-bit polarity orientation, ready
for an identical data decompression.
