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The engine is fully designed by the authors, using Verilog Hardware Description language and tested by applying various programming codes.
These simulations are implemented in MATLAB language and tested on a PC with an Intel Core i5-3470 CPU of 3.20 GHz and DDR3 SDRAM of 8 GB.
In order to prove that our proposed clustering algorithm has a stronger performance so as to balance the utility of data and the efficiency of anonymization, we have implemented the algorithm using JAVA language and tested on several data sets obtained from the UCI Machine Learning Repository which were used in previous clustering works [12].
The simulation algorithms were implemented in the C++ language and tested on a laptop with an Intel(R) Core (TM) i5-2520M CPU, 2.50 GHz processor, 2 cores, Intel HD Graphics 3000 graphic card, and 8 GB RAM (Windows 7 64-bit).
The original items were developed in German language and tested in a German sample.
The survey was then piloted in each language and tested for reliability (see [ 53] for an overview of the validity and reliability testing in Australia).
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This relationship varies according to several moderators including context (second vs. foreign language) and testing conditions (timed vs. untimed, aural vs. written).
The implementation was written in OpenGL and Cg shading languages and tested in the convolution application.
Functionally identical implementations of a prototype proof-of-concept software design were constructed in two different languages and tested using a unit-under-test model.
The WHOQOL-BREF has been translated to various languages and tested internationally [ 4, 5].
It has been translated into various languages and tested in diverse cultures [ 59].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com