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In order to overcome this problem, we have used the Discretization method as data pre-processing.
On the receiver side, legal receiver can extract the modified histogram in encrypted domain with the same method as data hiding procedure.
Our goal is to make the method as data driven as possible; i.e., minimize manual tuning and parameterization.
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Indeed, the proteins identified in the in gel samples were to > 95% covered by filter aided and in solution methods as well (data not shown).
The design challenges of the structures and the test method as well as the data assessment are described in detail.
Further estimates of the secondary economic value from direct impacts of Puget Sound shellfisheries: processing, distribution, and labour values, were made using benefit transfer methods as data on secondary value were not available for shellfish species in Puget Sound.
These research analyses used traditional statistical methods as well as data mining methods.
This comparison acts as a first validation of the method, as far as the experimental data that allow us the direct validation are available.
Detailed methods as well as information on data processing are included in the Supplemental Experimental Procedures.
MI-GRAAL's NCF is superior to GHOST's NCF, while the performance of the methods' ASs is data-dependent.
In general, we find that MI-GRAAL's NCF is superior to GHOST's NCF, while the superiority of the methods' ASs is data-dependent.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com