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It is practical to collect a huge amount of movement data and environmental context information along with the health signals of individuals because there is the emergence of new generations of positioning and tracking technologies and rapid advancements of health sensors. The study of the relations between these datasets and their sequence similarity analysis is of interest to many applications such as health monitoring and recommender systems. However, entering all movement parameters and health signals can lead to the complexity of the problem and an increase in its computational load. In this situation, dimension reduction techniques can be used to avoid consideration of simultaneous dependent parameters in the process of similarity measurement of the trajectories. The present study provides a framework, named CaDRAW, to use spatial–temporal data and movement parameters along with independent context information in the process of measuring the similarity of trajectories. In this regard, the omission of dependent movement characteristic signals is conducted by using an unsupervised feature selection dimension reduction technique. To evaluate the effectiveness of the proposed framework, it was applied to a real contextualized movement and related health signal datasets of individuals. The results indicated the capability of the proposed framework in measuring the similarity and in decreasing the characteristic signals in such a way that the similarity results -before and after reduction of dependent characteristic signals- have small differences. The mean differences between the obtained results before and after reducing the dimension were 0.029 and 0.023 for the round path, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we reported the optical constants and dissipation electrical energy of MWCNTs synthesized on Cu-Ni nanoparticles in hydrogenated amorphous carbon with different Ni layer thicknesses using capacitance coupled radio frequency plasma enhanced chemical vapor deposition (RF-PECVD) system. It can be seen that the Multi-Walled Carbon Nanotubes, MWCNTs, synthesized have maximum value of the average diameters in films deposited with 15 nm Ni layer thickness. With increase of Ni layer thickness, the dielectric relaxation time peaks nearly obtain a blue shift. The RBS spectra results shown that Ni nanoparticles successfully was presented in thin films. Due to the maximum value of the trapping incident photons on films surface, films deposited with 5 nm Ni layer thickness have maximum value of the absorption edge. The values of the free carriers electric susceptibility, χc, in thin films with 15 nm Ni layers thickness, for all range wavelengths, have maximum values and they were increased with increasing wavelength. Films deposited with 10 nm Ni layer thickness have the maximum value of dissipation factor. [ABSTRACT FROM AUTHOR]