We decided for a new Speller implementation because, apparently, there is no available tool with these characteristicse.
We call this implementation naïve because it is easy to understand but performs poorly.
There might be a solution for this implementation problem because in more recent health behaviour literature, the large potential of the use of new media sources, such as computers and internet, has become clear [ 24, 25].
This example shows that it is then possible to relax constraints on the implementation because the phase variation induces a possible variation of the branches length, leading to a reduction of the chip area.
Regretfully, there is a problem in the implementation because the rounding-off operation is not deeply considered for the spread spectrum watermarking algorithm.
In the implementation, because people at different locations may have different-sized silhouettes, a few different-sized templates are applied simultaneously to locate head-shoulder contours.
This implementation was chosen because the Altera VGA module we are using provides information as a continuous stream as opposed to a framebuffer that the controller accesses.
This implementation was chosen because information about these assets and their connections were available at once, and contained in files.
The approximations outlined above do not harm the robustness as shown by a comparison between the rows 6 and 7 of Tables 2 and 3, but this implementation is faster because GD imputation is more efficient than MAP and the computation of the posterior probabilities are simplified.
