Subject of Research. The paper considers the application of low-coherence reflectometry to the study of laser-pumped dyedoped random medium. The densely packed layers of titanium dioxide nanoparticles doped by rhodamine 6G are used as a laser-pumped dye-doped random medium. Method. The method of low-coherence reflectometry is based on analysis of the second and the third-order moments of intensity fluctuations of stochastic interference fields. Fluorescence radiation induced by the continuous laser pumping in fluorophor absorption band forms a stochastic interference pattern. The intensity distribution instochastic interference fields is described by the ratio of the coherence length of fluorescent radiation and the optical path length difference of the interfering field components. A confocal detection scheme is used for the stochastic interference analysis in the recorded signal. Main Results. The second and third-order moments of multiple scattered fluorescence intensity are calculated by experimentally obtained spatial fluctuations of fluorescent radiation limited by spectral range from 560 nm to 700 nm and spectral dependencies of moments are shown.The relationship is shown between the second and third-order statistical moments of the multiple scattered fluorescence radiation components and the coherence function and the probability density distribution of optical path lengths Practical Relevance. The considered method can be interpreted as an approach to the reconstruction of media optical transport characteristics based on comparison of the experimentally obtained statistical moments of fluorescence intensity fluctuations and theoretically-derived optical transport characteristics recovered by reverse Monte Carlo method. The study of radiation interaction with randomly inhomogeneous scattering media with high fluorescence quantum yield should be taken into account when analyzing functional and morphological states of complexly structured media, such as layers of biotissues, based on probing in the absorption bands of chromophores in spectroscopic methods.

Subject of Research. The paper presents a quantum search algorithm model, suitable for integration into a linear optical chip. Error impact caused by two-qubit operator implementation and directional coupler manufacture imperfection on the algorithm output is studied. Method. Analytical calculation of the algorithm scheme was performed to assess error impact caused by two-qubit operator optical implementation. Numerical simulation of the algorithm was executed for taking into account distortions caused by directional coupler imperfections. The simulation was completed using Qutip library on Python programming language. Main Results. Two well-known implementations of the algorithm scheme main component, a two-qubit CZ gate, are compared in order to select the most optimal chip architecture. It was shown that one of two-qubit gate implementations introduces an error critical for the algorithm work. Another implementation based on projection measurements does not introduce an error, but has a lower efficiency. We have performed simulation of the proposed scheme, taking into account the imperfections of its components in the framework of unitary dynamics. We have shown that the algorithm error probability does not exceed 0.011. Two-qubit Grover’s algorithm оptical implementation with regard to directional coupler imperfections has a low error rate, but it is limited by the low two-qubit operator efficiency. Practical Relevance. The study carried out can be useful for the physical implementation of the algorithm. Creation of an integrated optical scheme that implements Grover’s algorithm will make it possible to build a quantum router for the optimal route search in quantum networks with complex topology.

Epilepsy is a group of chronic neurological diseases that manifest themselves in the body’s susceptibility to the sudden onset of convulsive seizures. The pathogenesis of this disease is based on paroxysmal discharges in the brain neurons. Epilepsy is characterized by a difference in the level of peripheral blood autoantibodies (aAT) to the level of the glutamate receptor GluR1, which is a subunit of AMPA receptors (GluR1) and an increased level of IgG and IgM immunoglobulins between the group of patients with epilepsy and the group of healthy ones. We analyzed the serum of 30 healthy donors and 70 patients with epilepsy. The method of IR-spectroscopy in combination with multivariate analysis is proposed as a diagnostic method. In the course of the work, the following types of multivariate analysis were used to assess the correct probability of diagnosis: the principal component method (PCA) and the projection onto latent structures (PLS) method. Each of the presented methods gives the best results when using the first derivative of the spectra in the whole spectrum range. When analyzing this sample by regression procedures, the sensitivity was 100 % and the specificity of analysis was 76.9%.

Subject of Research. We study the approach to the underlying surface interpretation automation for satellite images obtained by the onboard optical-electronic equipment of the Earth remote sensing systems. The topicality of research is determined by the necessity of introduction of computer vision methods aimed at solving the search problem of the earth’s surface state changes through multi-temporal satellite monitoring data. The goal of research is reducing of the time spent on processing of large area satellite images. Method. The method is based on the idea of comparing the contrast of different-time satellite images. For method implementation, a mathematical apparatus is formed for calculating the contrast values of the analyzed images in the normalized interval from 0 to 1. The effectiveness of automated processing of satellite images is ensured by their pre- segmentation and zoning. Segmentation parameters are selected taking into account the size of the objects to be detected. The efficiency of the proposed method is confirmed by the high correlation of the automated processing results with the results of visual analysis of test satellite images. Main Results. The results of calculating the contrast of test images using the formulated mathematical apparatus are presented. The necessity of image segmentation is proved to solve the problem of detecting changes in the terrain on the example of processing images consisting of different number of fragments. An approach is developed for reducing the redundancy of data on terrain changes by performing a preliminary zoning procedure. The essence of this procedure is to determine the researched area boundaries in order to limit the zones for search of changes. Practical Relevance. The proposed method of data processing on the Earth remote sensing provides interpretation of the underlying surface images in an automated mode without operator participation. At that, the interpretation of images, when observing large areas, can be accelerated.

Subject of Research. The paper evaluates the possibility of periodic microstructures formation on the silicon surface by single-exposure double femtosecond laser pulse. Method. We used experimental method of double femtosecond laser pulses based on the Michelson interferometer and theoretical numerical simulation method of semiconductor photoexcitation process in the dielectric constant approximation. Main Results. Experimental results are presented on the monocrystalline silicon surface irradiation with one double femtosecond laser pulse near the ablation threshold at various time delays. Obtained optical images of the laser-irradiated silicon surface are analyzed and the results are compared with the results of photoexcitation process theoretical simulation in semiconductor based on the polariton theory concepts. The problematic nature of the periodic surface microstructures formation on silicon by a single femtosecond laser pulse is demonstrated. Practical Relevance. This study is useful when choosing industrially advantageous high-frequency modes of semiconductor surface femtosecond microstructuring.

The paper deals with an output control approach for structural uncertain MIMO systems under parametrical uncertainties, cross- reactions and external disturbances. The proposed technique ensures high quality of transients and high robustness in the steady state toward the disturbances without using high-gain components in the controller. A model transformation with one linear filter for control signal is used to obtain a structural determined form of the plant (“straight-feedback form”). The dynamical order of the filer is equal to the relative degree of MIMO plant. The procedure of relative dynamic degree estimation for nonlinear MIMO plant with cross-couplings is considered. The control algorithm combines an auxiliary loop method and backstepping method. The first one is a robust approach to unknown bounded disturbances evaluation and compensation. Backstepping is a well-known iterative procedure of control law synthesis by consecutive analysis of the plant state equations. The considered combination allows estimating undesired dynamics in each state equation and compensates it by creation of virtual control laws with equal magnitude toward disturbances and reverse sign. Experimental verification of the considered control algorithm is given with the use of a laboratory platform called “Twin Rotor MIMO System”. The platform can be controlled in two angle positions and represents the simplified helicopter dynamics.

Subject of Research. The paper deals with identification of the regression model unknown parameters by two estimation algorithms: the classical least square method and a new method of dynamic regressor extension and mixing. To compare the quality of the obtained estimates, the non-stationary parameters of the regression model were considered, and various noise of limited power was added to the input signal of the model. Method. The problem was solved by the dynamic regressor extension and mixing method followed by the gradient algorithm and the least squares method in real time mode ignoring the older values of the measured input signal. Main Results. The numerical simulation was presented illustrating the qualitative comparison of the two used methods. A noisy shifted sinusoidal signal with time-varying and unknown parameters of displacement, amplitude and phase shift was applied to the input of the estimation algorithms. Comparison has shown that with the application of dynamic regressor extension and mixing method, the estimation of the input signal parameters had an aperiodic form, while the least squares method gave unwanted oscillations. Numerical simulation has shown that the method of dynamic regressor extension and mixing qualitatively exceeds the method of least squares. Practical Relevance. The results can be used when solving practical problems in the areas of processing and evaluating for both harmonic signals and also signals with a more complex form.

Subject of Research. The paper presents the study of ammonium sulfate concentration effect on the content of impurities and the morphology of oxyhydrate powders and ceramic powders. Method. The synthesis of precursor powders was carried out by the method of reverse heterophase precipitation from chlorides. The method of energy dispersive analysis of the elemental composition was used to analyze the dynamics of changes in the concentration of chlorine and sulfur impurities in oxyhydrate powders and ceramic powders. The morphology of the experimental samples was evaluated according to scanning electron microscopy. Analysis of the agglomeration degree was performed using X-ray phase analysis methods and the BET gas adsorption method. Main Results. It was found that the usage of ammonium sulfate not only reduces the degree of agglomeration of ceramic powders by two orders of magnitude but also reduces the chlorine impurity concentration from 0.2 at. % to less than 0.01 at. %. In addition, the possibility of controlling the value of the specific surface area in the range of 1.5–15 m2/g by changing the concentration of ammonium sulfate was revealed. Practical Relevance. Applying an improved technique for the synthesis of ceramic powders, samples of optical ceramics were obtained with light transmission in the visible and near-IR range of more than 70% without taking into account the absorption bands of ytterbium.

Subject of Research. The paper considers the interaction of silver molecular clusters with trivalent europium ions in ion- exchanged layers of sodium-aluminosilicate glasses. Method. Glasses based on Na2O–ZnO–Al2O3–SiO2–F system anddoped with Sb2O3 and Eu2О3 were synthesized for the study. Silver ions were introduced into the synthesized glasses by low-temperature Na+–Ag+ ion exchange method; glass samples were immersed in a bath containing a melt of nitrate mixture 5AgNO3/95NaNO3 (mol%) at 320 °C for 15 minutes. To promote the growth of silver molecular clusters in ion-exchanged samples they were heat-treated at 350–450 °С for 20 hours. Heat treatment temperature was 500 °С for obtaining silver nanoparticles in the samples. Main Results. We have studied the spectral-luminescent properties of sodium-aluminosilicate glasses doped with silver molecular clusters and trivalent europium ions in ion-exchanged layers. Luminescence intensity of Eu3+ ions in the ion-exchanged glass with silver molecular clusters was found out to exceed considerably the intensity in the as-synthesized glass. Glass samples heat-treated at 450 °С are characterized by maximal emission intensity of silver molecular clusters and europium ions. Quenching of the luminescence was observed for the samples containing silver nanoparticles. Practical Relevance. Obtained results can be applied for developing phosphors in glass for LEDs and down-converters of ultraviolet radiation for solar cells

Subject of Research. We have studied the electronic structure of wurzite zinc oxide (ZnO) by quantum mechanical modeling using density functional theory (DFT) approach with different exchange-correlation energy functionals. Methods. The calculations were performed by means of generalized gradient approximation (GGA), Hubbard corrected generalized gradient approximation (DFT+U method) and hybrid functional PBE0. Main Results. The calculations have demonstrated that the basic GGA approach renders ZnO electronic structure with essential disadvantages demonstrating overestimated hybridization of zinc 3d and oxygen 2p shells and significantly underestimated bandgap. The inaccuracy for the latter has been eliminated by using the PBE0 approach, which is highly computationally demanding and increases the complexity of the calculations. We have shown that the best results complying with the experiment are obtained by applying Hubbard correction to all atoms of unit cell. Practical Relevance. The study shows the necessity of Hubbard correction usage when calculating zinc oxide electronic structure with the parameter of on-site repulsion “U” applied to both Zn and O atoms. The physical aspects and details of all used approaches and their computational demands are discussed.

Subject of Research. The paper presents the analysis of basic methods for generation of landscape maps taken as a basis for software module development intended for creation and study of models of environmental objects. Method. To achieve the synergistic effect, we proposed hybrid approach representing a mixture of two methods for construction of landscape mesh and textures: Voronoi diagrams and the algorithm of diamond-square. Main Results. The stages are defined; the conditions and requirements for the construction and visualization of landscape maps are formulated; a mathematical model of the surrounding space visualization is developed. The procedure of objects recognition from real photographs of the Buzuluk pine forest surroundings is presented; the result of the corresponding three-dimensional scene visualization is given. The analysis of CPU and RAM resource consumption showed the advantages of the hybrid approach compared to the application of Voronoi diagram or diamond-square algorithm separately. The hybrid approach implementation for adaptive landscape generation has reduced the requirements for productive capacity and computer resources. It is concluded that the developed mathematical model and algorithm can carry out high-quality modeling of realistic three-dimensional images of various objects based on two-dimensional images. Practical Relevance. The software module is integrated into a digital educational platform and enables any student to explore the possibilities of a real and key for the industry area of the landscape in the context of an online course, effectively preparing for the implementation of professional tasks in the future.

Subject of Research. The existing approaches to the automatic scaling of non-stationary operating cloud systems are analyzed. The drawbacks of the existing approaches to workload prediction are revealed due to the insufficient performance of the algorithms being used. The analysis of the properties of periodic non-stationary processes and automatic length estimation of their period are performed on the basis of measured data. The accuracy of the developed analytical models was confirmed in the course of numerous simulation experiments in the AnyLogic Professional modeling environment. Method. The basis of the developed method of automatic length estimation of the non-stationary processes period is the consistent approximation of the intermediate result to the desired value. The proposed method ranks the expected results in accordance with the probability of their compliance with the determined period of the non-stationary process. Main Results. The possibility is provided toestimate the period length for an adequate time. The testing was carried out on a system with an AMD FX 8120 CPU with a clock frequency of 3.1 GHz in one thread. The original signal was generated with amplitude 1. The waveform, the period value, the amplitude multiplier and the magnitude of the superimposed random noise were varied. According to the data from the largest transport network hub of Russia, Joint-Stock Company Center for Interaction of Computer Networks MSK-IX, the period of total transit traffic has been successfully determined, and also the periods of non-stationary processes for the cloud system model have been successfully determined. Practical Relevance. The developed method can be used as part of the services of cloud systems automatic scaling and provides more efficient management of the infrastructure resources of cloud computing systems.

Subject of Research. The paper presents encoding and decoding method for video information obtained from video surveillance cameras in transport. The method is based on the usage of adaptive three-dimensional discrete cosine transform. Video compression typically has two goals: to reduce spatial redundancy between image elements and temporal redundancy between successive frames. The basic principle of spatial encoding is the consideration of the correlation of the adjacent pixel brightnesses, and the basic principle of interframe encoding is prognosis and motion compensation for the interpolated sample positions in the reference frame in all known standard video codecs such as H. 26х and MPEG-x. Method. The method is characterized by applying an adaptive cosine transform in the signal space and with respect to time, and the sizes of the cubes are unspecified depending on spartial and time statistical characteristics of the image signal. Main Results. The results show that the proposed algorithm can improve the encoding and decoding efficiency of images taking into account the specifics of the transport images. The best performance is achieved at low and medium traffic intensity. At the same time, the algorithm computational complexity is reduced by 4-5 times while maintaining the quality of the restored video streams in comparison with codec standards. Practical Relevance. The proposed algorithms based on adaptive cosine transform give the possibility: firstly, to decrease the transmission rate of the transport sequences by 2–2.5 times compared to the classical cosine transform with the size of cubes equal to (8 × 8 × 8); secondly, to reduce significantly computational costs in the implementation of transport video surveillance systems in real time compared to standard codecs. The results of the work can be recommended to specialists in the field of video information encoding and decoding to provide the necessary transmission speed at a given distortion level.

Subject of Research. We consider problematic issues of ensuring the information security of autonomous unmanned objects. Prerequisites are revealed that determine the need for external monitoring systems. The type and statistical characteristics are shown used for the analysis and classification of sound signals. Method. The proposed approach to analysis of information security state of an autonomous object is based on classification methods and allows identifying the current state based on the processing of digitized acoustic information. An experiment is described aimed at obtaining statistical information on various types of maneuvers of an unmanned object with a different location of the audio recorder. The obtained data were processed using two-layer feed-forward neural networks with sigmoid hidden neurons. Main Results. We have solved the problem of identifying the state of information security of autonomous unmanned objects based on processing of signal information obtained through side channels. Digitized information from acoustic sensor (microphone) located statically in the experiment area has been classified more accurately than from a microphone located directly on an autonomous object. With minimal accumulation of statistical information using the proposed approach, it has become possible to identify differences in maneuvers performed by unmanned objects, and, consequently, the state of information security of an object with a probability close to 0.7. Practical Relevance. The proposed approach for processing of signal information can be used as an additional independent element for information security state determination of autonomous objects of unmanned systems. The approach can be quickly adapted using various mathematical methods and machine learning to achieve probabilistic assessment with a given quality.

Subject of Research. The paper presents research of the tourism support systems performed with modern information technologies. The subject of research is the intelligent tourist assistance system. The analysis of the existing tourist support systems is carried out and their advantages and disadvantages are given. The system architecture and implementation details are developed. A generation method for tourist attraction ratings is developed and experiments are carried out. Method. The method of description and comparative analysis of relevant systems was used for tourist support systems analysis. Machine learning methods were used to create recommendations for sightseeing. The methods of graph theory were used to build routes for places of interest visiting. Main Results. The advantages and disadvantages of the existing tourist support systems have been highlighted. The service-oriented architecture of the proposed intelligent tourist assistance system has been formulated. An attraction information generation method for the specific region based on the open specialized sources has been described. Experiments have been performed aimed at the work evaluation of the tourist assistance system. Practical Relevance. Application of the research results provides for the development of an intelligent tourist assistance system that meets modern requirements and surpasses the existing analogues.

Subject of Research. The paper deals with research of clustering algorithms for hyperparameters optimization used in machine learning. Model selection problem is comprehensively studied, and the need of the tradeoff between exploration and exploitation is identified. Thus, the problem is reduced to multi-armed bandit problem. Method. The paper presented the approach for simultaneous algorithm selection and hyperparameters optimization. We used solution of the Multiarmed Bandit problem and considered Softmax- and UCB1-based algorithm variants in combination with different reward functions. Main Results. Experiments on various datasets from UCI repository were carried out. The results of experiments confirmed that proposed algorithms in general achieve significantly better results than exhaustive search method. It also helped to determine the most promising version of the algorithm we propose. Practical Relevance. The suggested algorithm can be successfully used for model selection and configuration for clustering algorithms, and can be applied in a wide range of clustering tasks in various areas, including biology, psychology, and image analysis.

 Subject of Research. The task of energy consumption reducing and energy efficiency improvement is one of the key ones when designing systems on a chip. The main parameters affecting power consumption are the clock frequency and supply voltage. Determination of these parameters values under given technological and time constraints is the main goal of optimization. The paper discusses the ways of energy efficiency assessment for digital integrated circuits. An optimization criterion for one of the architectures of digital blocks is derived. Method. A method for parametric optimization of digital integrated circuits for micromechanical sensors is proposed. The method gives the possibility to optimize the parameters of computing devices according to the criterion of minimum energy consumption. Main Results. The methodology approbation results are presented on the example of sequential and pipelined architectures of digital blocks. Practical Relevance. The proposed technique can be used in the development of digital integrated circuits for any manufacturing technology and provides the evaluation of the parameters for digital integrated circuits with their optimization in the given constraints.

Subject of Research. High-resolution successive approximation analog-to-digital converters include a digital-to-analog converter with multiple capacitor arrays and have significant nonlinearity. Existing methods for nonlinearity reducing are aimed primarilyat nonlinearity lowering that arises in the digital-to-analog converter, which is a part of successive approximation analog-to- digital converter. These methods are not complex and are aimed only at reducing the impact of one or several factors that cause the nonlinearity of the digital-to-analog converter. In addition, the known approaches are applied only at the stage of topology development, that leads to significant time costs in the case of redesign when it is impossible to achieve the required accuracy of the analog-to-digital converter. Based on the above, we can assert the relevance of the development of process-oriented synthesis method for analog-to-digital converters reducing the transformation nonlinearity by taking into account the manufacturing technology at the early design stages. Method. A method of process-oriented synthesis for analog-to-digital converters is proposed providing analog-to-digital converter nonlinearity reducing. Main Results. As compared with the known methods, the method takes into account the peculiarities of the technological process at the early stage of device design. The method was used to design 18-bit analog-to-digital converter on 350 nm CMOS technology. Practical Relevance. The proposed method can be used for high-resolution analog-to-digital converter design on different CMOS technologies.

Subject of Research. The paper considers physical processes occurring in sensory elements of angular rate and apparent acceleration measuring devices, such as hemispherical resonator gyro and pendulum accelerometer. Inertial masses of the studied sensory elements are made of KU-1 quartz glass. Method. Actual engineering drawings of the sensory elements are converted into a specialized 3D environment to simulate the performance of devices under different input effects, that is impossible with real devices. Moreover, traditional mathematical modeling approach, that involves such software packages as Matlab, does not provide a complete picture. Main Results. Visual information on the nature of motion of inertial masses was obtained using the results of 3D modeling, making it possible to improve and correct the known mathematical models of devices for subsequent Matlab analysis with closed control loop, since the studied gyro and accelerometer are compensation type devices with positive and negative feedback, respectively. Resonant frequencies of the considered devices were calculated as well. Practical Relevance. Considering the accelerometer, the obtained information on resonant frequencies made it possible to calculate band pass filters in order to suppress reactions to disturbances at these frequencies in the device pass band, and for the hemispherical resonator gyro it provides the possibility to define more precisely the resonator working frequency of oscillations.

The paper presents the results on creation of a source of ultracold neutrons in the National Research Center “Kurchatov Institute” — PNPI. The source has three temperature zones: a helium chamber with superfluid helium at the temperature of 1.3 K, a deuterium chamber with liquid deuterium at the temperature of 20 K, a vacuum case with a lead screen and graphite blocks at room temperature. All these parts are exposed to cooling under the conditions of the reactor heat load. Calculations associated with the design of cooling circuits are presented. Analytically, a mass flow rate of 0.56 kg/s was obtained for cooling of the lead screen with a volumetric heat flow of 27 kW. A pump and a heat exchanger were selected for an autonomous cooling circuit on the basis of this flow. At this thermal mode, the radiant heat gain from the nose part of the vacuum module to the deuterium capsule was 24 watts. The total heat flux to the deuterium capsule and liquid deuterium, taking into account the reactor radiation, was 0.3 kW. To maintain the phase state of deuterium, temperature control is required in the temperature range 18.73–24.122. The finite-square method proved the possibility of safely maintaining the phase state of liquid deuterium in a 60-liter capsule with a flow of helium gas of 50 g/s.

The paper presents the study of an effective classification method for traffic signs on the basis of a convolutional neural network with various dimension filters. Every model of convolutional neural network has the same architecture but different dimension of filters for convolutional layer. The studied dimensions of the convolution layer filters are: 3 × 3, 5 × 5, 9 × 9, 13 × 13, 15 × 15, 19 × 19, 23 × 23, 25 × 25 and 31 ×31. In each experiment, the input image is convolved with the filters of certain dimension and with certain processing depth of image borders, which depends directly on the dimension of the filters and varies from 1 to 15 pixels. Performances of the proposed methods are evaluated with German Traffic Sign Benchmarks (GTSRB). Images from this dataset were reduced to 32 × 32 pixels in dimension. The whole dataset was divided into three subsets: training, validation and testing. The effect of the dimension of the convolutional layer filters on the extracted feature maps is analyzed in accordance with the classification accuracy and the average processing time. The testing dataset contains 12000 images that do not participate in convolutional neural network training. The experiment results have demonstrated that every model shows high testing accuracy of more than 82%. The models with filter dimensions of 9 × 9, 15 × 15 and 19 × 19 achieve top three with the best results on classification accuracy equal to 86.4 %, 86 % and 86.8 %, respectively. The models with filter dimensions of 5 × 5, 3 × 3 and 13 × 13 achieve top three with the best results on the average processing time equal to 0.001879, 0.002046 and 0.002364 seconds, respectively. The usage of convolutional layer filter with middle dimension has shown not only the high classification accuracy of more than 86 %, but also the fast classification rate, that enables these models to be used in real-time applications.

The paper proposes a modified form and procedure for automated processing of information about failures based on the analysis of the existing forms for recording statistical data on operating results and laboratory tests (developed on the basis of state standards). The procedure is intended for informational support of decision-making in the development of measures aimed at eliminating the causes of failures. The proposed form with fault categories and repeatability will provide not only information support in making decisions about the development of the missing measures, but also the effectiveness evaluation of previously completed improvements. The proposed procedure for automated processing of information about failures speeds up the decision-making process, based on automated calculation of the repeatability index. The implementation of statistical data processing in computer-aided design systems makes it possible to reduce the time taken to develop corrective measures and take into account the effect of operating factors when creating new projects.

Subject of Research. The paper considers a method of music noise reduction in a multichannel speech signal based on noise mask estimation. The method is applied for automatic speech recognition in presence of music noise. Method. The study is performed using an acoustic model implemented in artificial neural networks and real life recordings performed in reverberant conditions. Main Results. It is shown that the acoustic model is capable of estimating the noise mask on a multichannel mixture for different music genres. The application of such mask to covariance matrix estimation for MVDR (Minimum Variance Distortionless Response) beamforming algorithm results in increasing the recognition accuracy by at least 4.9 % at signal-noise ratio levels of 10–30 dB. Practical Relevance. The method of MVDR coefficient estimation based on noise mask estimation by an acoustic model serves to suppress non-stationary noise, such as music, thus increasing the robustness of automatic speech recognition systems.

The paper considers the issues of applying the additive technologies in the design process of the ship intercommunication facilities at a modern instrument-making enterprise. It is shown that the use of 3D printing technologies on Ultimaker 3 printer provides for creation of prototypes of finished products within the shortest time period and the appropriate option selection. Application of the additive technologies gives the possibility to reduce the complexity of the design work phase by 5–6 times

                                                                                                                                                                               About autor of publication   Vladimir Yu. Tertychny (Tertychny-Dauri) was born in 1954. He graduated from Leningrad State University (LSU) in 1977, the Faculty of Mathematics and Mechanics, and employer-sponsored graduate program of the same faculty in 1980. From 1980 to 1983 he was working at the Faculty of Mathematics and Mechanics of LSU, from 1983 to the present time he is working at ITMO University. Defense of the candidate and doctoral dissertations took place at the Faculty of Mathematics and Mechanics of LSU (in 1980) and Saint Petersburg State University (in 1994). He is a Professor at the Department of Higher Mathematics of ITMO University. He has published more than 130 academic papers including 24 monographs published in leading national and foreign journals and publishing houses. His scientific interests are: qualitative theory of differential equations, integral and integro-differential equations, classical mechanics, variational methods, nonholonomic and gyro systems, canonical transformations, normal forms, stability theory, synthesized vibrations, hyperdynamics, mechanics of space flight, chaos, stochastic instability and turbulence, adaptive, stochastic controlled systems, optimal control theory, signal filtering, systems with delay, neutron and charge kinetics, nuclear electrodynamics, cosmology, general and special theory of relativity, field relativistic quantum and gravitational interactions, mathematical economics, biomechanics, robotics and artificial intelligence. He was awarded four government awards. Twice he became the winner of international awards in mathematics.