The results for the split databases are automatically joined before generating the output for the web-based version of DeconSeq.
This split-database design eliminates the problem of how to collate the data off each tablet into a unified database.
This approach uses a split-database design in which data-entry forms are dispersed as file copies residing on each touch-table PC and all data, organized in several tables, reside in a single back-end Access database file.
When previously developing search strategies for some categories of articles (e.g., therapy, prognosis) for MEDLINE, we split the database into 60%and40%0% components to provide a development and validation database.
The threshold depth of 50 cm most successfully split the database between upward and downward models.
We split the database into reference set R BP and test set T BP.
In order to use neural networks we had to split the database into a test and trainings set.
For CPG search strategy development for EMBASE, it was not feasible to split the database, as there were too few "pass" articles (e.g., 69 pass CPG articles in EMBASE).
At a later stage, recognition system has been experimented splitting the database into a population of 90 authorized users and 27 impostors with the intent to reduce False Acceptances and False Identifications with a measurement threshold.
The techniques proposed herein are: (i) an algorithm for splitting the database of snapshots generated by the full-order model; (ii) a method for solving quasi-symmetrical matrices; (iii) a strategy for reducing the frequency of the projection.
In our experiments we splitted the database in ten different nonoverlapped subsets.
