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The article deals with the application of new methods and approaches for machining of carbon plastics on the basis of the analysis of foreign information sources with a search depth of five years. The complex problems of composite materials processing, in particular, carbon plastics, the solutions of which have not yet been found in full, are noted. Applying of new methods of hole formation, part milling, hydro-abrasive and laser processing allows to obtain new output quality indicators is pointed out. The implementation of considered methods, developed by foreign scientists, may supplement the tools arsenal and technologies of composite materials processing at domestic enterprise. The importance of quality assurance of composites` complex surfaces processing and formation in aircraft and aerospace engineering, where utilization level of this material is constantly increasing, is indicated.

The possibility of applying the method of ultrajet diagnostics for estimation of the stress–strain state (SSS) of carbon-fiber samples is considered. It was shown as a result of a series of experiments and numeric computations that informative parameters of the cavern do not contain objective information about the state of material in the current load state. This may be useful for the construction of a general method for diagnosing samples made of carbon fiber for estimation of their operational life, including the conditions of the effect of a set of external factors: static loading, temperature, various types of electromagnetic radiation, et al. Experiments showed there to be high indicators of correlation between computed values of stresses and depths of caverns formed as a result of ultrajet impact on the surface of carbon-fiber samples.

Searching for buried ancient objects that have no traces on the surface as a result of plowing of the topsoil for centuries is a challenge for archaeology. In this paper, the use of geophysical methods for mapping necropolises is illustrated by a geophysical survey of the Shekshovo-9 burial site (Suzdal Opolie). The main idea is to detect archaeological objects using geophysical data, regarding them as heterogeneities against the background.

The problem of modern archeology is the study of monuments that are not expressed on the surface due to centuries of plowing. Using the example of a geophysical study of the Shekshovo 9 monument (Suzdal Opolie region), we consider the use of geophysical methods for mapping the structure of the necropolis. The main idea is to search and interpret archaeological objects in geophysical data as heterogeneities towards background geological and soil structures.

The article is deal with the questions of assessing the applicability of the method of ultra-jet diagnostics of carbon plastics. In the work, phenomenological ideas about the process of destruction of carbon plastics under the action of a high-speed-jet of liquid are considered. The experimental part of the work is related to the implementation of the diagnostic effect of the ultra-jet on the surface of the carbon fiber reinforced plastic, the assessment of the geometric parameters of the hydraulic caverns and the qualitative assessment of the state of the fibers and the adhesion in the binder-fiber structure. In this experiment, carbon fiber samples were used both in the initial state and after the inhibitory effect of x-ray radiation. Such a technique made it possible to carry out a comparative analysis of the samples and evaluate the information content of the ultra-jet diagnostics method as applied to the materials under consideration.

In the development of life support systems for long-term space missions, the most important tasks are the absorption of carbon dioxide from the air, the production of carbon dioxide with a concentration above 98 %, and the production of oxygen from carbon dioxide by the Bosch – Sabatier process. To solve these problems, a regenerative carbon dioxide absorber adapted to space flight conditions is required. The article proposes a new method for the production of chemosorbents based on hydrated zirconium oxide using polyacrylates as a binder and polymer matrix. The regenerated absorber of carbon dioxide for its application in space flights must meet the regulatory requirements of sanitary-chemical and toxicological safety of materials intended for the equipment of inhabited sealed rooms, be resistant to radiation and to the effects of mold. In the study of the processes of “sorption – desorption” of carbon dioxide, we have established the relationship between the technological parameters of the synthesis of chemosorbents and the kinetic parameters of the processes of mass-sorption of sorbate in the “sorption – regeneration” cycles. It is found that the optimal weight ratio of the “adsorbent – filler/polymer matrix” 89÷94/11÷6 is optimal in terms of the performance characteristics of the developed absorbers. It is shown experimentally that the main operational characteristics of the developed materials do not change under experimental conditions during 2000 “sorption – regeneration” cycles. The resulting chemosorbents are investigated by physicochemical analysis. Employing methods of gas chromatography and chromatomass spectrometry, we have conducted sanitary and chemical studies and toxicological assessment of the quantitative and qualitative composition of the components of gas release of the developed regenerated carbon dioxide absorber and air-gas mixture formed during the regeneration of the regenerated carbon dioxide absorber. Also we have carried out microbiological tests of samples of the regenerated absorber of carbon dioxide for resistance of material to influence of mold mushrooms. The results obtained confirm the possibility of using the developed materials in life support systems of manned spacecraft for deep space exploration.

Predictive psychodiagnostics is the process of forming a predictive assessment of any metric based on the data of psychodiagnostic testing. The formation of a predictive estimate is a classification problem and a variety of algorithmic approaches can be used to solve it – logistic regression, support vector machines, decision trees, neural networks, and many others. The article describes the practice of using algorithms based on decision trees to create models used in solving predictive psychodiagnostics problems, as well as cases in which their application is most relevant. The results obtained using the models built on the basis of the decision tree algorithm using gradient boosting show sufficient predictability and statistical significance in comparison with the methods of traditional psychodiagnostics used to solve personnel assessment problems

The article deals with the architecture and structure of the most effective artificial neural networks (ANNs) in the tasks of network traffic classification: multilayer perceptron and LSTM (long short-term memory) network. Using one of the actual datasets CSE-CIC-IDS2018 trained ANNs and tested the effectiveness of detection of various attacks in the network traffic. An analysis of existing work has been performed. A multiclass classification was performed and the detection effectiveness of separate computer attacks was reported. The effectiveness evaluation focused on three metrics: completeness, correct response rate, and false positive rate. The test classification results were considered both in terms of comparison of numerical characteristics of recognition quality and in terms of class analysis in order to identify which computer attacks (CA) are better identified using multilayer perceptron and which are better identified using LSTM. On the basis of these results, an ANN, which is a hybrid network, is proposed as a promising Intrusion Detection System (IDS).

Currently, unmanned vehicles cannot yet be introduced on public roads, and the person behind the wheel is not predictable and behavior is a multi-parameter task. The article describes a methodology for calculating and evaluating various characteristics of a respondent's psychodiagnostic test using the integrated use of typical driver behavior uncertainty and assessing his condition through machine learning (ML) algorithms. The application of machine learning allows you to reduce the number of test questions and increase the processing speed, since the developed algorithm finds hidden patterns well. A large number of factors affect the driver's condition, and this article is devoted to determining the driver's condition in real time, which reduces the likelihood of an emergency. Based on the developed algorithm, it is possible to conduct an interview and pre-trip control. On the one hand, this makes it possible to improve the quality of the recruited personnel, and on the other, to improve the quality of logistics and, most importantly, to increase road safety.

The article describes an approach to reducing the number of questions in the Keys to Personal Mastery Inventory (KPMI) psychological testing questionnaire with the further addition of missing data and their use in a machine learning model to predict respondent satisfaction with their job. Since the 30s of the 20th century, mathematicians, physicists and engineers have been working on the description of traffic flows. But theoretical models do not work well because a person is driving a car, and a person is unpredictable. In the same situation, it behaves differently. This work aims to reduce driver uncertainty using machine learning methods.

The article discusses the task of assessing the damage of carbon plastics that arose as a result of the destructive effect of x-ray radiation using the diagnostic capabilities of ultra-jet technology. A technique is proposed for determining the thickness of a carbon fiber package that can protect an imaginary interior from the negative effects of x-ray waves. As informative diagnostic parameters in the method, the geometrical dimensions of the cavern arising on the surface of the sample as a result of exposure to a high-speed jet of liquid (water) are used. Based on the results of the experiments, it was found that a decrease in the depth value indicates a decrease in the penetrating effect of x-ray radiation and the destruction of the binder in the structure of the composite material. The studies were carried out under the grants of the Russian Foundation for Basic Research 18-29-18081, a grant from the President of the Russian Federation for state support of leading scientific schools of the Russian Federation NSh-3778.2018.8

Information security systems that use machine learning algorithms and are based on real datasets are among the most effective. The format and content of datasets used in artificial intelligence and machine learning methods directly affect the quality of information security system implementation. The article presents a classification of datasets in the field of information security of communication networks. The structure and features of several characteristic data sets related to the use of machine learning algorithms in information security systems are shown.

Ensembles of neural networks are used to improve the performance of the model and show themselves well in the case of using deep recurrent and convolutional networks on serial [1] and graphic data [2]. The article discusses the advisability of using a snapshot ensemble of not deep feedforward neural networks on a synthetic dataset.

Developed offers to choice frequency resource for radio engineering systems at FHSS. Justified efficiency indicator for assessment quantitative preliminarily mode testing frequency works. Results of analytic modeling shown. Proposals for practical implementation are formulated.

The article provides a description of the main legal acts in the field of creating objects of Critical Information Infrastructure (CII). Various methods of information security threats modeling for objects CII are considered. It is proposed to use technique Security Development Lifecycle (SDL) for threat modeling CII.

An approach for adaptive selection of frequencies, suitable for video transmission is proposed. Analytical tools to calculate the time delay of transmission of video in presence of damaged frequencies are developed. The results of computer modelling are shown.

As part of the study of mobile device traffic, the formation of an experimental database of network traffic of selected mobile applications, which can be used for training and testing classifiers using machine learning methods, occupies an important place.To automate the process of studying mobile application traffic classification algorithms, a software package has been developed that allows you to automatically collect network traffic packets from mobile devices and save them to a database; group network traffic packets into streams; upon user request, generate data sets with specified characteristics (number of specific application flows: background traffic; generate a data set based on the already created set with the addition of new flows, excluding repetitions).To collect traffic from mobile devices running the Android operating system, an application was developed that uses the application programming interface to create virtual private networks, collects network traffic packets, identifies the source application and sends them via HTTP to server software.Using the client and server software, the database created was filled with traffic from 18 main applications. During the data collection, 71,667 streams and 6,989,991 packets were received.

The article deals with the questions of assessing the applicability of the method of ultra-jet diagnostics of carbon plastics. In the work, phenomenological ideas about the process of destruction of carbon plastics under the action of a high-speed-jet of liquid are considered. The experimental part of the work is related to the implementation of the diagnostic effect of the ultra-jet on the surface of the carbon fiber reinforced plastic, the assessment of the geometric parameters of the hydraulic caverns and the qualitative assessment of the state of the fibers and the adhesion in the binder-fiber structure. In this experiment, carbon fiber samples were used both in the initial state and after the inhibitory effect of x-ray radiation. Such a technique made it possible to carry out a comparative analysis of the samples and evaluate the information content of the ultra-jet diagnostics method as applied to the materials under consideration.

Summary Сomplex geophysical studies were conducted with approbation of various methods for measuring and processing data in the search for single burials of the Shekshovo necropolis. The effectiveness of the research was evaluated during the subsequent excavations. The comparison allowed us to draw the following conclusions. Single burials of the studied necropolis are characterized by increased electrical resistivity. At the same time, the contrast of resistance in comparison with the enclosing rocks for single burials is noticeably lower than that of the fillings of the graves and economic holes. This makes the identification of single graves according to geophysics much more difficult than the detection of hidden kurgan rovikov and their remnants and pits of different origin. To single out single burials, a step of 1 m with 2D inversion is insufficient for all observation conditions. Measurements in two polarizations and 3D data inversion allows to increase the resolution of the research. The task of searching for individual graves should be considered as complex, requiring an analysis of the landscape of the monument as a whole, including geological, geomorphological, soil features and a system of agricultural development.

political reality is characterized by nonlinearity of processes and significant influence not only of formal, but also shadow mechanisms of interaction of the actors taking decisions - political elites and leaders. One of the most promising areas, which opens up new opportunities for studying political problems, is the synthesis of the “traditional” methodology of political analysis and methods of artificial intelligence. The paper substantiates the adequacy of the use of a decision tree for analyzing and forecasting political decisions by the example of the personnel policy of federal structures in relation to the regions of the Russian Federation.

One of the tasks of system identification within the modern signal processing system is the task of identification of unknown error-correction code (ECC). System identification can be done using various methods. Anyway, the more knowledge one has about the possible system structure provides better solution for system identification. Here we take a look into digital communication systems uses ECC, which are the major part of modern communication systems are. We create a new practical approach for identification of a priori unknown ECC being used over the transmission channel of the communication system which is examined for identification purposes. The approach is based as Big Data application which can provide new source for the study. Shown that usage of new approach provides better speed for system identification making the process of identification faster, more reliable, with better quality for solution found and with lower requirements for quality of the transmission channel.

Global climate warming causes an intensive melting and retreat of glaciers in the Tien Shan mountains. Melting water of glaciers causes overfilling of high mountain lakes. The increase of the surface and volume of the Petrov Lake accompanied with the decrease of stability of the dam represents an extremely dangerous situation that can produce a natural disaster. Failure can happen due to erosion, a buildup of water pressure, an earthquake or if a large enough portion of a glacier breaks off and massively displaces the waters in a glacial lake at its base. In case of the lake dam rupture, flooding of a disposal site of highly toxic tailing from the gold mine Kumtor is a threat. If this happens, the toxic waste containing cyanides would contaminate a large area in the Naryn (Syrdarya) river basin. Even if the flooding of the disposal site does not occur, the damage after lake dam fracture will be immense due to the glacial lake outburst flood may be a devastating mudslide. In order to prevent or reduce the risk of this event we recommend performing engineering surveys for the development and implementation of the project for the controlled reduction of water level in the Blue Bay of the Petrov Lake to a safe volume.

Creep and relaxation models based on fractional derivatives are submitted. Models of parameter determination are described. It allows predicting system behavior.

Viscoelastical deformation model based on fractional derivatives submitted. Model parameter determination is described. It allows to predict system behavior under different loading.

A model is proposed which describes the electrostriction temporal shift of laser pulses in their high-frequency train propagating in an optical fibre. The validity of the model is confirmed by good agreement of its predictions with the results of studies of relative temporal shifts in the high-frequency train of optical solitons known from the literature. The model predicts the possibility of a substantial reduction of temporal shifts in the data pulse train in fibreoptic links composed of fibres with different signs of dispersion. For comparatively low pulse repetition rates (less than 500 MHz), the oscillating dependence of the relative temporal shift of pulses on the data transmission rate is found.

Pentasil and Y-type hydrophobic zeolites are synthesized. The adsorption properties of the prepared powders of hydrophobic zeolites and granules on their basis with respect to toluene, benzene, and water under static and dynamic conditions are studied. The possibility of multiple reuses of hydrophobic sorbents is assessed and the conditions of their regeneration are selected.

Zubarev's nonequilibrium statistical operator method is applied to problems of relativistic kinetic theory. In the framework of this method, a generalized quantum kinetic equation with collision integrals of first and second order in the interaction is obtained. It is shown that the results also remain valid for gauge theories. The possibilities of the method are illustrated by models of relativistic nuclear matter.