USING OPTOELECTRONIC NONCONTACT VOLTAGE RELAY IN ELECTRICAL SUPPLY SYSTEMS

In the article based on the results of the analysis of the existing opto-thyristor resistive circuits, a new scheme of the optoelectronic contactless voltage relay has been developed and its application in the power supply system has been considered. The possibility of controlling the operating modes of various installations amplifying electrical signals using optothyristors is presented and the ways of their inclusion in electrical circuits are presented. The optoelectronic contactless voltage relays were tested in laboratory conditions to obtain an input-output characteristic and a form of capacitance voltage. Based on the improvement of the proposed circuit, a circuit of an optoelectronic contactless voltage relay is developed and provide a high degree of reliability. The simulation of the proposed voltage relay circuits is performed using the MATLAB R2014a program, the results of which show that changes in the shape of the output voltage curve are close to a sinusoid and coincide with the results obtained analytically. As a result the obtained conditions of use make it possible to obtain a voltage with a sinusoidal shape on the load and achieve a relay return coefficient close to unity

Reconstruction and restoration of monuments of white stone architecture on the example of the church of the Image of Edessa in Abramtsevo

The article deals with the topic of preserving the historical appearance of objects during the reconstruction and restoration of architectural masterpieces. The analysis of the historical experience of recreating samples of ancient Russian architecture with elements of sculptural white stone reliefs is carried out on the example of the group method of work of members of the Abramtsevo art circle, imitating the activities of the national art collective. Based on the analysis of historical experience in the framework of the Abramtsevo Art Circle and their own research, the authors have established the basic principles of reconstruction and restoration of architectural monuments. When conveying of white stone works as masterpieces of ancient Russian architecture, technological techniques must be based on the ideological basis of creating an emotional and artistic atmosphere of collective creativity of folk masters. During the reconstruction and restoration of white stone architecture, it is also necessary to reproduce the natural irregularities of the walls themselves as a stylistic and functional feature of the historical time, designed to give originality to ancient buildings, taking into account the specifics of the perception of the relief of the walls of the monument as a similarity to the terrain

Intelligent system for diagnosing the welded joints quality on the basis of the radiographic method

The paper discusses the issue of creating an intelligent diagnostic system for welded joints based on the radiographic method. This will speed up the process of decoding radiographic images and reduce the number of errors associated with human factors, since at this time most of the work on decoding images is done manually. The goal of the work is to develop an intelligent system for finding defects in a welded joint in a radiographic image using neural networks. The obtained results are the algorithm of operation of the intelligent diagnostic system for welded joints based on the radiographic method, a trained neural network for detecting defects of welded joints.This work was supported by the Russian Foundation for Basic Research, research No 17-08-01569

Application of a deep convolutional neural network in the images colorization problem

Object of the research are modern structures and architectures of neural networks for image processing. Goal of the work is improving the existing image processing algorithms based on the extraction and compression of features using neural networks using the colorization of black and white images as an example. The subject of the work is the algorithms of neural network image processing using heterogeneous convolutional networks in the colorization problem. The analysis of image processing algorithms with the help of neural networks is carried out, the structure of the neural network processing system for image colorization is developed, colorization algorithms are developed and implemented. To analyze the proposed algorithms, a computational experiment was conducted and conclusions were drawn about the advantages and disadvantages of each of the algorithms.This work was supported by the Russian Foundation for Basic Research, research No 17-08-01569

System for in-depth analysis of network traffic based on artificial intelligence technologies

The relevance of research is explained by the need to improve the network traffic analysis systems, including deep analysis systems, taking into account existing threats and vulnerabilities of network equipment and software of computer networks based on methods and algorithms of machine learning: • traffic analysis systems are widely used in monitoring network activity of some users or a specific user and restricting the client's access to certain types of services – VPN, HTTPS, which makes content analysis impossible; • such decisions may limit the access to prohibited resources in order to comply with legal requirements for methods of restricting access to information resources applied in accordance with the Federal Law “On Information, Information Technologies and Information Protection”. Network traffic analysis methods with the goal of defining an application layer protocol without traditional means of deep package inspection (DPI) are considered under conditions when the payload is encrypted (for example, TLS / SSL protocol). The novelty lies in the development of algorithms for analyzing network traffic on the basis of a neural network. This method differs in the way of features generation and selection, which allows classifying the existing traffic of protected connections of selected users according to a predefined set of categories. Keywords: Deep network traffic analysis, computer network, traffic encryption, VPN, neural network traffic analysis model, random trees committeeThis work is partially supported by the Russian Science Foundation under grants No 17-07-00351

Simple model of adsorption on external surface of carbon nanotubes: a new analytical approach basing on molecular simulation data

Nitrogen adsorption on carbon nanotubes is wide- ly studied because nitrogen adsorption isotherm measurement is a standard method applied for porosity characterization. A further reason is that carbon nanotubes are potential adsorbents for separation of nitrogen from oxygen in air. The study presented here describes the results of GCMC simulations of nitrogen (three site model) adsorption on single and multi walled closed nanotubes. The results obtained are described by a new adsorption isotherm model proposed in this study. The model can be treated as the tube analogue of the GAB isotherm taking into account the lateral adsorbate-adsorbate interactions. We show that the model describes the simulated data satisfactorily. Next this new approach is applied for a description of experimental data measured on different commercially available (and characterized using HRTEM) carbon nanotubes. We show that generally a quite good fit is observed and therefore it is suggested that the observed mechanism of adsorption in the studied materials is mainly determined by adsorption on tubes separated at large distances, so the tubes behave almost independently

Komposisi dan Struktur Pohon Di Kasawasan Perladangan Ulu Gadut Padang.

ix, 39 Hal