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Various backbone extraction algorithms have been proposed in different scientific fields.
In the latest years, the use of zinc oxide (ZnO) nanostructures has been proposed in different biomedical applications, however, to date, only a few contrasting results concerning their biocompatibility can be found in the literature.
Split phase approach has been proposed in different contexts.
Recently, the ZigBee network has been proposed in different research areas in power systems.
Up to date, various plasmonic metamaterial absorbers have been proposed in different wavebands, which are mainly divided into two main categories: broadband absorbers and narrowband absorbers.
This problem is exacerbated because many methods have been proposed in different research communities (e.g. NLP, Information Science, Information Retrieval, Machine Learning), exploiting different techniques, with low knowledge about related efforts in other communities.
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In this paper, an integrated PRNET (PCA-Radial basis functional neural NET) model is proposed in different versions to select the relevant parameters for preparing composite preforms and to predict the deformation and strain hardening properties of Al Fe composites.
In Section 3, two three-party key exchanged protocols are proposed in different application scenarios, namely normal situation and critical or special situation.
The 2 methods were proposed in different contexts, but their underlying approaches are consistent and complementary.
Exercises were proposed in different combinations and intensities on the basis of the clinical evaluation preliminarily carried out by the physical therapist.
Accordingly, different PD targets have been proposed in the different studies addressing ICU patients, which sometimes make their comparison difficult.
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