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The need for configuration of such methods is increasing accordingly.
For this reason the interest in the use of biological methods is increasing (Lika and Papadakis 2009).
At present, DNA- and protein-based assays support both activities but the demand for fast, inexpensive, sensitive methods is increasing.
Recently, with the development of high dimensional large-scale medical imaging devices, the need of fast, robust and accurate segmentation methods is increasing.
Incidentally, we note that the interest of computational astrophysics towards DG methods is increasing (Radice and Rezzolla 2011; Teukolsky 2015), and, especially in the relativistic context, they are expected to play a crucial role in the years to come.
Adoption of Internet based trial methods is increasing despite associated problems of high rates of attrition [14], [15].
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The interest in these methods is increased significantly during the last ten years in the networking and signal processing communities.
However, by increasing the size of the problem (3.3), difference between the solution values in two different methods is increased at a low rate (~ 1.7%).
In such routine situations, resources are limited in terms of time and expertise, and the risk of misuse of conventional statistical methods is increased.
In the case of the MINLP problem at hand, the need to use GO methods is increased by the additional non-linearities coming from the binary and integer variables and the augmented size of the problem.
Innovative designs, technologies, policies and marketing methods are increasing that potential faster than we are using it up.
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