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Exact(17)
In the second and new approach, we only draw samples of the carrier phase.
Since the key findings were the same with either approach we only report the results using the midpoints.
In our approach, we only use Haar-like features, which are randomly generated, to represent each image patch (or samples), similar to[1].
Each block is encrypted by the same approach; we only need to prove that the n shares v1,j,j=1,2,…,n on block B1 satisfy the (k,n) threshold property.
For the abstract approach, we only consider a general scenario where a generic data receiving decision maker (mathfrak {M}) (e.g., the doctor) sends data to a generic data store (mathfrak {S}) (e.g., the knowledge base).
In our approach, we only need to define a group of meta-models, mapping rules and model-level programs, so the workload of hand coding can be greatly reduced.
Similar(43)
Due to the fact that we compare our approach to 20 other approaches, we only mention the name of the method and the applied type of information.
For both clustering approaches, we only use clusters consisting of 4 30 nodes and randomly choose one node from the first cluster as the starting point.
For hybrid approaches, we only study the combination of discs with halfplanes since it has not been studied previously and for other two methods introduced in Section 4.1.2, we refer the reader to [18, 19, 29].
For the other two approaches, we only used the data for subjects having complete genotype data for all SNPs.
However, in order to eliminate bias due to bad gene prediction obtained using ab initio approaches, we only focused our attention on genes coding for proteins with defined function (additional file 2).
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