Supervised Kernel Principal Component Analysis by Most Expressive Feature Reordering, Journal of Telecommunications and Information Technology, 2015, nr 2

The presented paper is concerned with feature space derivation through feature selection. The selection is performed on results of kernel Principal Component Analysis (kPCA) of input data samples. Several criteria that drive feature selection process are introduced and their performance is assessed and compared against the reference approach, which is a combination of kPCA and most expressive feature reordering based on the Fisher linear discriminant criterion. It has been shown that some of the proposed modifications result in generating feature spaces with noticeably better (at the level of approximately 4%) class discrimination properties

Hand skin regions extraction using combination of different color spaces

In this paper a comparison procedure of existing color spaces and a new combination of color spaces used for skin extraction for gesture recognition is presented. Proposed color space is based on known color spaces YUV, CIELab, and YCrCb. The method of skin extraction is based on face detection by Haar-Like feature classification, and current face color model calculations, for better skin pixel extraction

Characteristics of the Structure, Mechanical, and Tribological Properties of a Mo-Mo2N Nanocomposite Coating Deposited on the Ti6Al4V Alloy by Magnetron Sputtering

Mo-Mo2N nanocomposite coating was produced by reactive magnetron sputtering of a molybdenum target, in the atmosphere, of Ar and N2 gases. Coating was deposited on Ti6Al4V titanium alloy. Presented are the results of analysis of the XRD crystal structure, microscopic SEM, TEM and AFM analysis, measurements of hardness, Young’s modulus, and adhesion. Coating consisted of a-Mo phase, constituting the matrix, and g-Mo2N reinforcing phase, which had columnar structure. The size of crystallite phases averaged 20.4 nm for the Mo phase and 14.1 nm for the Mo2N phase. Increasing nitrogen flow rate leads to the fragmentation of the columnar grains and increased hardness from 22.3 GPa to 27.5 GPa. The resulting coating has a low Young’s modulus of 230 GPa to 240 GPa. Measurements of hardness and Young’s modulus were carried out using the nanoindentation method. Friction coefficient and tribological wear of the coatings were determined with a tribometer, using the multi-cycle oscillation method. Among tested coatings, the lowest friction coefficient was 0.3 and wear coefficient was 10 × 10−16 m3/N∙m. In addition, this coating has an average surface roughness of RMS < 2.4 nm, determined using AFM tests, as well as a good adhesion to the substrate. The dominant wear mechanism of the Mo-Mo2N coatings was abrasive wear and wear by oxidation. The Mo-Mo2N coating produced in this work is a prospective material for the elements of machines and devices operating in dry friction conditions

Wenancjusz Fortunat, Wiersze opisowo-laudacyjne (Carmina I 19; I 20; III 12, CPL 1033)

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