2D SiC/Si Structure: Electron States and Adsorbability

Semiconductors - A model of a heterostructure consisting of a silicon-carbide single layer formed on a massive silicon substrate is proposed. The problem of the adsorption of alkali metal atoms and...     

Structural and Photoluminescence Properties of Graphite-Like Carbon Nitride

Semiconductors - Interrelationship between the structure and optical properties of graphite-like semiconductor carbon nitride produced by the heat treatment of thiocarbamide in an oxygen-containing...     

Investigation into the Influence of Sodium Lignosulfonate,Anionic Surfactants,and Their Mixtures on the Copper Cementation Rate by Zinc

Russian Journal of Non-Ferrous Metals - This article is devoted to the influence of sodium lignosulfonate (SL), anionic surfactants (sodium dodecylsulfate (SDS), sodium dodecylbenzene sulfonate...     

Strength Assessment of Welded Joints of High-Strength Alloy Steels by Indentation Method

Strength of Materials - The paper presents the indentation method for strength assessment of the welded joints in high-strength alloy steels, including base metal, heat-affected zone, and welded...     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.     

Synthesis of Nb2AlC MAX Phase by SHS Metallurgy

Russian Journal of Non-Ferrous Metals - A cast material based on the Nb2AlC MAX phase is formed by SHS metallurgy. The synthesis is performed using the Nb2O5–Al–C mixture with the...     

Influence of Sodium Microalloying on Rolling Contact Endurance and Mechanical Properties of Hot-Deformed Powder Steels

Russian Journal of Non-Ferrous Metals - Rolling bearing rings comprise a large reserve for expanding powder metallurgy production. This reserve is being incompletely implemented. The hot forging of...     

Related Oscillations of Plasmons in Two Similar Nanocylinders from Silver

Journal of Communications Technology and Electronics - Abstract—The two-dimensional diffraction problem of a plane polarized TM-wave on two identical solid silver nanocylinders is considered....     

The Possibility of Dense Materials Based on Obtaining an AlN–SiC Solid Solution by Self-Propagating High-Temperature Synthesis Gasostating

Russian Journal of Non-Ferrous Metals - The synthesis and sintering of the (AlN)x(SiC)1 – x solid solution have been studied under conditions of self-propagating high-temperature synthesis...     

Spanish doctoral theses in physical activity and sports sciences and authors’ scientific publications (LUSTRUM 2013–2017)

Scientometrics - The purpose of a doctorate is educating new researchers to later produce scientific articles derived from their doctoral thesis. The objective of this study is to verify if...