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The paper proposes a method of infrared spectroscopy for objective control of the adhesive composition in the production of paper. For sizing paper, in order to increase mechanical strength and reduce water absorption, water-repellent materials are used. One of the most effective and used water-repellent material is ordinary pine resin rosin which is in short supply for the Republic of Uzbekistan. The paper investigates the properties of a new adhesive based on rosin from cherry resin for use in mass sizing in order to expand the range of sizing agents and reduce the share of imported components in the structure of local paper production. Infrared spectroscopy was used to identify the rosin-based glue from the resin of the cherry tree. The built-in device with a diamond crystal of the universal and compact Thermo Scientific Nicolet iS50 IR Fourier spectrometer made it possible to register spectra in the mid and far IR ranges up to 100 cm–1. The efficiency of sizing paper samples was studied by standard methods and evaluated by the following properties: density, tensile strength at stretching on a tensile machine, surface absorbency with one-sided wetting. Infrared spectra revealed the identity of the sizing agent from the resin of the cherry tree to the glue from the pine resin, taken for comparison, because their chemical composition is the same. A comparative analysis of the mechanical and surface properties of paper samples confirmed the possibility of using the studied sizing agent, since the obtained values are close to each other, while it is advisable to add in the range from 1 to 1.5 g per 100 g of dry cellulose raw materials. The use of infrared spectroscopy for express analysis of the composition of the sizing agent is promising, since it becomes possible to control the technological process and create glued types of paper products with desired properties that ensure print quality without loss of fine image details.

The paper considers the issues of high-precision parameter control of the produced paper products with secondary raw materials as a component. A method of atomic force microscopy is proposed for paper roughness study. Visualization of the obtained topographic images of each type of paper surface under study was performed with the use of a Solver HV scanning probe microscope; the average roughness of the height differences for each type of paper was determined. The results were compared with the state standard requirements and international recommendations. It is shown that applying of scanning probe microscopy makes it possible to carry out parameter express control of the cellulose paper products during their production. With the roughness express analysis by atomic force microscopy it might become possible to control purposefully the technological process and create the new types of paper products with specified properties that provide graphic printing accuracy without loss of small image details.

The paper deals with the precision control for the parameters of manufactured paper production, such as various kinds of paper and photo paper for printing. Research of untreated, matte, glossy and laminated paper is conducted by atomic force microscopy by means of educational and scientific scanning probe microscope NanoEducator LE in the framework of this paper. Visualization of characteristic structure for each type of studied paper was conducted, histogram of roughness was obtained, and average roughness of height differences was defined. A laminated paper has got the lowest roughness (Ra of about 70 nm) and glossy paper has got Ra of about 170 nm; roughness of untreated paper with cellulose fibers is about 530- 540 nm, and matte paper has got the highest roughness parameters (Ra about 670-680 nm). Scanning probe microscopy application for parameters monitoring of cellulosic paper production is shown to give the possibility of such microscopy type application in the production of paper products and high-precision control of its parameters.

An analytical review of the digital facial anthropometry application in the scientific and practical problems of the contemporary human world is presented. The research includes a brief history of anthropometry emergence (as a descriptive and comparative science, the subject of which is human) and its transformation into contemporary computer methods of digital anthropometry. We have considered the application features of digital facial anthropometry. They are: the concepts of the morphotype and phenotype of the face, problems of morphology and morphometry, as the basic means of digital facial anthropometry, methods of quantitative and qualitative assessment of the characteristics and parameters of individuals, the task of finding associations between gene sets in the genome and human facial features, the task of assessing the attractiveness and beauty of individuals, the relationship of facial anthropometry with "Chernoff Faces" and cognitive computer graphics used in practical medicine, the phenomenon of the human face and the problem of determining the emotions, sex and psycho-type of a person, special cases of face image recognition tasks, methods for solving them within the framework of digital facial anthropometry and examples of their solution. We have determined the prognosis for the close connection of digital facial anthropometry and the “Internet of things” in the contemporary world.

Problem statement ill-posedness in the paper by L.S. Konev et al. devoted to formation of backward wave at short laser pulse propagation in nonlinear media or fibers is specified. It is inconceivable in the correct problem statement to consider the radiation field at the medium entrance as a given function of time due to generation of backward wave in the medium, when the backward wave characteristics are target values. The proper evolution variable is time, and it is convenient to use the adopted finite-difference time-domain (FDTD) method for backward wave calculation.

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 examines the xanthene fluorescent dyes questions available to a wide laboratories range in order to detect microplastics with an average particle length of 157 ± 59 μm in soil samples and conduct phytotests using fluorescently labeled microplastics. For the research, soils with a humus content of 1.59 ± 0.15 % (P1) and 6.74 ± 0.11 % (P2) as well as suspension polyvinyl chloride (RusVinyl LLC, 157 ± 59 μm, white) were used. In order to study the possibility of selective staining of microplastics in the presence of soil particles, polyvinyl chloride microparticles, soil P1 and P2, as well as a mixture of soil P1 and polyvinyl chloride (5 % by weight) were stained with rhodamine B, rhodamine G, fluorescein and eosin Y in isopropyl alcohol (dye concentration — 200 mg/L, temperature — 100 °C, staining time — 2 hours with constant stirring on a magnetic stirrer) and washed with distilled water on a paper filter. To study the chemical polyvinyl chloride microparticles structure before and after staining attenuated total reflectance-Fourier transform infrared spectroscopy was used (spectrometer Tensor 37 (Bruker, Germany), attenuated total internal reflection MIRacle Pike attachment with a diamond-coated ZnSe crystal). Spectrophotometry and microphotograph analysis using ImageJ software were used to determine whether dye could be leached from polyvinyl chloride microparticles after repeated washing with water. To conduct the laboratory experiment to detect microplastics in soil a mixture of P1 soil and polyvinyl chloride microparticles (0.1 % by weight) was prepared and stained with rhodamine G. In order to reduce the amount of mineral particles and concentrate polyvinyl chloride microparticles, a separation technique was used due to the difference in density using binary solution of NaCl and Ca(NO3)2. Microphotographs were obtained using an optical microscope with an additional ultraviolet source (λ = 365 nm). Image areas measurements of detected microparticles projections, that are necessary for calculating the approximate mass of the pollutant, were carried out using ImageJ software. The possibility of using fluorescently labeled polyvinyl chloride microparticles for phytotests was established using the seed germination test in contaminated soil and studying seedlings using an optical microscope with an additional ultraviolet source. It was shown that after staining with rhodamine B and rhodamine G, fluorescence is observed in polyvinyl chloride microparticles both separately and in a mixture, since soil particles P1 and P2 do not acquire similar properties. When fluorescein and eosin were used, polyvinyl chloride microparticles and soil practically did not fluoresce. It has been established that coloring does not affect the polyvinyl chloride chemical structure. Dyes are not washed out of polyvinyl chloride microparticles after repeated washing with water. The laboratory experiment showed that it is possible to detect and quantitation polyvinyl chloride microparticles in soil at the 0.1 % concentration by weight with a relative error of about 30 %. It is possible to use fluorescently labeled polyvinyl chloride microparticles with rhodamine B and rhodamine G when conducting phytotests. This research demonstrates for the first time the possibility of selective staining of polyvinyl chloride microparticles with rhodamine B and rhodamine G in a mixture with soil due to the observed fluorescence and their detection in a concentration of 0.1 % by weight. The results obtained expand knowledge in the field of monitoring microplastics in soil and, since today there are no standardized methods for detecting this pollutant, it can be used in their development. Fluorescently labeled polyvinyl chloride microparticles with rhodamine B and rhodamine G are planned to be used in phytotests as part of experiments on the hygienic justification of the maximum permissible concentration of the pollutant in the soil.

Personalization is one of the keyways to improve the performance of conversational agents. It improves the quality of user interaction with a conversational agent and increases user satisfaction by increasing the consistency and specificity of responses. The dialogue with the agent becomes more consistent, the inconsistency of responses is reduced, and the responses become more specific and interesting. Training and testing personalized conversational agents requires specific datasets containing facts about a persona and texts of persona’s dialogues where replicas use those facts. There are several datasets in English and Chinese containing an average of five facts about a persona where the dialogues are composed by crowdsourcing users who repeatedly imitate different personas. This paper proposes a methodology for collecting an original dataset containing an extended set of facts about a persona and natural dialogues between personas. The new RuPersonaChat dataset is based on three different recording scenarios: an interview, a short conversation, and a long conversation. This is the first dataset for dialogue agent personalization collected which includes both natural dialogues and extended persona’s descriptions. Additionally, in the dataset, the persona’s replicas are annotated with the facts about the persona from which they are generated. The methodology for collecting an original corpus of test data proposed in this paper allows for testing language models for various tasks within the framework of personalized dialogue agent development. The collected dataset includes 139 dialogues and 2608 replicas. This dataset was used to test answer and question generation models and the best results were obtained using the Gpt3-large model (perplexity is equal to 15.7). The dataset can be used to test the personalized dialogue agents’ ability to talk about themselves to the interlocutor, to communicate with the interlocutor utilizing phatic speech and taking into account the extended context when communicating with the user.

In this paper, we study the trajectory tracking problem of a three-wheeled omnidirectional mobile robot with full state constraints and actuator saturation. Firstly, we analyze a three-wheeled omnidirectional mobile robot and give control model with actuator saturation. By using tan-type Barrier Lyapunov Function and backstepping method, kinematic and dynamic controllers are built, which can ensure that the system full states will not violate the given constraints when the robot is performing trajectory tracking. Then, considering the differential explosion problem which occurs when solving the derivatives of the virtual control law, we use a second-order differential sliding mode surface to calculate it, so as to reduce the complexity of the operation. In addition, due to the output saturation problem of the robot drive motor, an auxiliary compensation system is adopted to compensate for the error generated by the saturation function. Finally, an experimental simulation is performed in MATLAB and the simulation results illustrate the effectiveness of the control algorithm proposed in this paper.

The paper analyzes the features of representing artificial neural networks in Simulink and SimInTech. Examples of visual schemes (models) built in these modeling environments using neural network blocks are given. The following shortcomings of such representations are the lack of mechanisms: for carrying out structural optimization of neural networks, for combining them into ensembles, for training them synchronously with the simulation of the object model. It was noted that there are difficulties in using other tools, such as specialized Python libraries (Keras, PyTorch, etc.), the NeuroGenetic Optimizer (BioCompSystems) for building neural network control models. A method is shown to implement the representation of neural networks in the formalism of the method of multilevel component circuits, according to which the construction of models of an object and a control system is carried out in a visual language from ready-made blocks (components) with directional and non-directional connections. A technique has been developed for multilevel representation of neural network control models, which allows them to be combined with other tools of the component circuit method. Two options for representing neural networks are proposed: with an encapsulated structure and with a component structure. The first version of the representation is characterized by the compactness of the representation of the control model, the possibility of automated variation and optimization of the structure of the neural network, and the possibility of changing the structure of the network during the executing of the model within a computational experiment (scenario). The second option has the ability to perform detailed debugging and research of the network learning process, and the ability to construct a network of any structural complexity. The paper describes the main developed components with their connections: a neural network, a training block, an ensemble unit (bagging), a block for reading data from a file, a sampling block, a neural network layer (input, hidden, output). A multilevel computer model of the uncontrolled flight of a body (target) and the controlled flight of a projectile is presented as an example to illustrate the operation of the developed components to solve the problem of controlling a projectile to hit the target. The developed component libraries can be used as part of the MARS modeling environment to build multilevel control systems for objects of a multiphysics nature.

The paper proposes a modified method for measuring the refractive index of a triangular prism using an autocollimation angle measuring system designed to measure angles formed by flat surfaces of objects. The method involves using a fixed mirror to reflect the refracted beam, measurement of the angles of incidence of the beam on the face of the prism corresponding to the autocollimation positions and calculating the refractive index of the prism material using the solution of a system of equations. The paper presents the experimental study results for a triangular prism made of K8 optical glass using the proposed method, and a comparison of the results with the readings obtained using the State Primary Standard of the Refractive Index Unit GET 138-2021. The proposed method makes it possible to simplify the process of measuring the refractive index since there is no need to measure the angle of deviation of the beam.

A wide class of smooth continuous dynamic nonlinear systems (control objects) with a measurable state vector is considered. The problem of finding a special function (Lyapunov function), which guarantees asymptotic stability for the presented class of nonlinear systems in the framework of the second Lyapunov method, is posed. It is known that the search for the Lyapunov function is an extremely difficult problem that has no universal solution in stability theory. The methods of selection or search of the Lyapunov function for stability analysis of closed linear stationary systems and for nonlinear objects with explicitly expressed linear dynamical and nonlinear static parts are well studied. At the same time, no universal approaches to finding the Lyapunov function for a more general class of nonlinear systems have been identified. In this paper, we propose a new approach to the search of the Lyapunov function for analyzing the stability of smooth continuous dynamic nonlinear systems with a measurable state vector. The essence of the proposed approach consists in the representation of some function through the sum of nonlinear summands representing the elements of the object state vector multiplied by unknown coefficients. The search for these coefficients is performed using a classical genetic algorithm including mutation, selection, and crossover operations. The found coefficients provide all the necessary conditions for the Lyapunov function (within the framework of the second Lyapunov method). The genetic algorithm approach does not require a training sample which imposes restrictions in the form of the structure of control objects included in it. A new method for finding the Lyapunov function represented as a nonlinear series with known functions multiplied by unknown coefficients is proposed. The effectiveness of the proposed method is demonstrated using computer simulations with a fixed number of iterations and varying population size. The dependence of the number of successfully found Lyapunov functions on the number of iterations of the genetic algorithm has been established. The convergence of the genetic algorithm using Holland’s schemes is analyzed. It is shown that the values of the sought coefficients of the potential Lyapunov function, at each algorithm iteration, approach the coefficients of the Lyapunov function which was also represented as a Taylor series. The method proposed in this paper outperforms known analogs in terms of speed, considers the decomposition of the potential Lyapunov function into a Taylor series with unknown coefficients, instead of using counterexamples or template functions.

This paper studies the trajectory tracking problem and the controller gain adjustment problem for Wheeled Mobile Robots. The controller gain has a great influence on the robot’s trajectory tracking: it can influence both the tracking accuracy and the tracking speed. Therefore, it is very important to choose a suitable control gain during the controller design process. Current neural network gain controllers have a complex structure and require a lot of calculations to find the optimal value. To solve this problem, we design a trajectory tracking controller with a simple structure with adaptive gain by combining the controller with a neural network. The input to this controller is the robot’s attitude error. The controller has no hidden layer and directly outputs the trajectory tracking control law. Firstly, the kinematic controller is designed based on Lyapunov function method to ensure that the robot moves according to the reference trajectory. Then, the online gain adjustment algorithm is designed by using neural network to realize the fast adjustment of the controller gain and ensure the reliability of the controller. Finally, the backstepping method is utilized to design the velocity tracking controller based on the error between the virtual velocity and the actual velocity. Considering the influence of the external environment, we also design a nonlinear disturbance observer to estimate the total disturbance on the robot. We perform simulation experiment in MATLAB. The result of the experiment shows that the control algorithm proposed in this paper can realize the accurate tracking of the robot on the specified trajectory. The gain adjustment algorithm we designed can find the optimal gain value quickly and efficiently, thus improving the stability and efficiency of the controller. The method can be applied to most mobile robot trajectory tracking problems and solves the problem of control gain adjustment.

The progress in the stream of the power electronic converters has led to the expansion of various protection devices for the distribution system. This also has led to an assortment of flexible transmission devices aiming to enhance the stability of the system throughout a variety of power quality issues and, furthermore, for enabling flexible uninterrupted power transmission during turbulences. This paper augments the employment of two Custom Power Devices, namely, Dynamic Voltage Restorer and Distribution Static Compensator for dealing with various power quality issues associated with distributed generation systems. This paper also involves analysis of performance of proposed Custom Power Devices with various algorithms, like gravitational search algorithm, BAT algorithm and ANT colony optimization algorithm for improving the stability of the power system. The proposed system has been tested with various distributed systems, fault conditions, and assessment has been performed among different algorithms in terms of supply voltage, supply current, active power, reactive power, and power factor. The design and analysis of entire system has been executed using MATLAB/Simulink.

The introduction of new types of heat exchangers with phase transitions and the solution of problems of optimizing the design and operational characteristics are a priority within the framework of the energy saving program. Known methods for calculating the heat-hydrodynamic parameters of the flow of refrigerants often do not take into account the specifics of boiling processes at low temperatures as well as in channels with a small flow area. This paper presents the results of modeling heat transfer during the boiling of refrigerants in the channels of evaporators of heat and cold energy complexes, taking into account the true flow parameters. The proposed mathematical model of the boiling of the working substance in channels of various shapes is based on the true flow parameters which imply knowledge of the channel cross-sectional areas occupied by each of the phases. The value of the true volumetric steam content provides the most correct modeling of two-phase flows in a wide range of regime and geometric parameters. The paper uses the equations of material and heat balance in combination with the equation of heat transfer from the environment to the boiling refrigerant. The map of flow regimes is used as an empirical component. A program has been developed for calculating the proposed system of equations which is solved iteratively at each time step using the finite volume method. Comparison of calculation results with experimental data on models of round and rectangular channels with intracanal boiling of refrigerants at positive and negative saturation temperatures is performed. It is shown that the calculation error does not exceed 10 % for a round and 20 % for a rectangular flow section. The verification results showed the possibility of using the model in the framework of engineering calculations. The proposed mathematical model can be used as the basis for the calculation programs for existing evaporators and for the creation of new types of heat exchangers with in-tube boiling of the working substance. The proposed method allows optimizing both geometric and thermal-hydrodynamic parameters.

The article discusses the experimental and theoretical results of studying the optical properties for planar quartz surfaces modified with gold nanostars using Surface-Enhanced Raman Spectroscopy (SERS). Surfaces functionalized with nanoparticles, prototypes of optical sensors, have been obtained. It is shown that the obtained experimental Raman signal enhancement from the dye rhodamine 6G (R6G) can be at least order 104. The paper presents the results of calculation, synthesis and study of the optical and morphological properties of such structures. A complex method for creating and evaluating the optical properties of planar nanostructures and evaluating their optical properties is proposed. The method includes the approaches based on mathematical modeling using finite differences in the time domain (FDTD - Finite- Difference Time-Domain) evaluating electromagnetic field strengths near the surfaces of star-shaped gold nanoparticles in colloidal solutions and on a silicon surface. During the simulation, we studied such parameters as the particle size, the wavelength of the exciting radiation, and the dependence of the effective amplification of the electromagnetic field on the morphological parameters of the star. The theoretical approach to the calculation of such structures is shown to be promising for the subsequent chemical synthesis described in the article and the study of optical properties. In this paper, a theoretical calculation of the parameters of the electric field and optical properties is carried out near star-shaped nanoparticles of varying sizes. These parameters were calculated by the finite difference method in the time domain. The task included finding the optimal sizes of nanoparticles as well as varying the thickness of the surface layers in order to obtain the maximum scattering values and further use of similar structures in SERS experiments. Also, within the framework of this work, syntheses of star-shaped nanoparticles was carried out, their optical and morphological properties were studied, quartz surfaces were functionalized with nanoparticles, and sensor prototypes were created in order to further assess the Raman signal amplification. Based on the results of mathematical modeling, the optimal sizes for the synthesis of star-shaped NPs were determined. Synthesis of NPs was carried out by a chemical method using seeds. To carry out the experimental part, SERS spectra were obtained using Centaur U spectrometer (OOO NanoScanTechnology, Russia). The spectrometer was equipped with three different laser sources: 632.8 nm He-Ne laser (17 mW), 532 nm and 473 nm DPSS lasers (45 mW). During the experiment, a He-Ne laser with λ = 632 nm and DPSS laser with λ = 532 nm were used to match the excitation of the plasmon maximum for the nanostars. The optical scheme of the spectrometer included an Olympus BX41 microscope (Olympus, Japan) with a 100× objective (NA 0.9) for positioning the beam and collecting scattered photons. The monochromator of the spectrometer had a focal length of 800 mm. A holographic diffraction grating of 300 gr/mm, and was equipped with a 1024×256 pixel thermoelectric cooled CCD detector (Andor Tech., UK). As a result of the paper, surfaces functionalized by nanoparticles were obtained prototypes of optical sensors. It is shown that the experimental gain of the Raman signal can be no less than 104 times. The presented data will serve as the basis for obtaining the required sizes of nanostars in the methods of the controlled chemical synthesis of colloidal nanoparticles. The results presented in the article can be applied to the development of biocompatible and highly sensitive optical sensors based on the effect of Raman scattering of light.

Residual amplitude modulation in LiNbO3 phase modulator is one of the key factors that limit the accuracy of highsensitive fiber-optical sensors. A fiber-optical gyroscope is an angular velocity sensor whose sensitivity is better than 0.001 °/h. Optical light intensity changes after phase modulator is a reason for wrong phase difference that introduces an error in the angular velocity signal. Most existing residual amplitude modulation suppression methods are based on reduction of back reflections between an optical fiber and integrated optical waveguide, absorbing groove to suppress or reduce reflection on the bottom face, and algorithmic compensation. In this paper, new approach to reduce residual amplitude modulation in LiNbO3 for fiber optical gyroscope application is presented. Method feature is an application of additional differential signal modulation with uniform amplitude distribution in the input signal voltage range of the phase modulator. The proposed method allows to suppress residual amplitude modulation of the multifunctional integrated optical circuit phase modulator more than 3 times using additional triangle signal modulation with the frequency f = 200.09 MHz and power P = 36 dBm. This method is suitable for improving fiber optical gyroscope accuracy. Moreover, it could be applied for any fiber-optic sensors based on LiNbO3 phase modulator. The paper will be of interest to specialists in the field of highly sensitive fiber optical sensors, fiber, and integrated optics.

Monitoring systems of automated production lines requires high accuracy and processing speed of acquired data. Nowadays digital twin technologies are rapidly developing as part of Industry 4.0. Digital twin is a virtual representation of a physical system that mimics the behaviour of a real object, and is used in real-time control, monitoring and disturbance prediction, without influence on a real object. Digital twin is being used in many fields of application such as: healthcare, manufacturing, education, city development, etc. Nonetheless, despite the rising popularity of digital twin researches, there is no basic approach to digital twin synthesis. Mostly, in state of the art articles, systems with known parameters are considered. In this paper, approach to development of digital twin, based on internal model for multi-link mechanisms with unknown motion parameters, is presented. Described approach intended to ease the task of production line monitoring and extend digital twin technology application field. In this article adaptive controller design, based on internal model, is presented, theoretical explanations of design process are provided, and application of the control algorithm in the task of multi-link mechanism motion trajectory parameters estimation is described. In this work the experimental synthesis of digital twin for Kuka youBot manipulator based on presented approach in real time is described. Adaptive motion parameters estimation was made for two links of the manipulator for the sake of confirmation of presented approach usage in the task of digital twin for systems with unknown parameters. Motion trajectory parameters of the robot links were defined manually with the use of chaotic generators to estimate the accuracy of the adaptive control system. This approach was used in order to calculate the error of reference tracking by comparing the control signal for digital twin with the reference exogenous input for manipulator links. As the results of the experiment, the graphs of the error reference tracking for both links are presented. As the goal of the experiment, the convergence of reference tracking error to the field [–0.005, 0.005] radian was set, and as can be seen from graphs this goal was achieved. There is a small disturbance of the error convergence on the graphs within the desired field which was caused by noised measurements and delays of the chosen modelling environment real-time simulations. In the conclusion of this paper, further work to reduce the influence of mentioned causes is described. The results of this paper can be used in further digital twin technology researches. Presented approach can be implemented in robots remote control tasks, production lines technical condition monitoring and in general motion trajectory parameters estimation tasks for multi-link mechanisms.

This paper discusses the effect called undesirable extrusion dynamics that occur during material extrusion printing or fused deposition modeling. This effect is revealed during high acceleration and deceleration of printing head and results in over-extrusion on corners of parts and printed layer unevenness. To minimize this effect, modern control systems use Advance algorithms for dynamics control. However, such disadvantages as inertia, reduced printing speed, need for manual calibration, as well as uncertainty of the influence of material, nozzle geometry, and printing process parameters on the algorithm performance do not allow this group of solutions to be applied on an industrial scale. The paper presents a study of the influence of printing characteristics, such as material type, extruder type, printing temperature, layer and nozzle geometry, on extrusion dynamics through a series of experiments. The experiments were carried out on a Creality Ender 3 printer. The obtained experimental data will allow us to deepen the understanding of extrusion dynamics influence in FDM printing; they are also used in the present study to modify existing dynamics control algorithms. The paper proposes a modification of Advance algorithm based on machine learning. It is proposed to implement an algorithm containing two trained neural network models. One model predicts changes in printing head motion to minimize residual defects and increase average print speed. The second model predicts the compensation parameter for specific printing conditions without the need for manual calibration. A neural network model was trained to determine the compensation parameter depending on the type of material, layer thickness, nozzle geometry and printing temperature. The model was trained based on experimental data. The developed algorithm was introduced into Linear Advance algorithm of the Marlin firmware and tested on Creality Ender 3. The experiments showed that the developed model can successfully predict the required compensation and can be applied during the printing process. The proposed algorithm helps to facilitate and automate the process of extrusion dynamics compensation which will expand the possibilities of FDM printers’ application in industrial conditions. The obtained algorithm can improve the accuracy and printing speed which will subsequently help to increase the economic independence and competitiveness of small design organizations and enterprises in Russia that use 3D printers. This research expands the possibilities of rapid prototyping and may help to ensure the rapid creation of pilot batches.

The paper deals with the problem of acoustic events classification which is actively applied to the problems of a safe city, smart home, IoT devices, and for the detection of industrial accidence. A solution to improve the accuracy of classifiers without changing their structure and collecting additional data is proposed. The main data source for the experiments was the TUT Urban Acoustic Scenes 2018, Development Dataset. The paper presents the way to increase the accuracy of audio event classification by using the FN-corrector. The FN-corrector is a linear two-stage classifier performing the transformation of the feature space into a linearly separable space and the linear separation of one class from another. If a corrector is applied, the responses of the original classifier generate four classes: positive (P), negative (N), false positive (FP), and false negative (FN). As a result, it becomes possible to train two types of correctors: the FP-corrector separating positive and false positive classifier responses, and the FN-corrector separating negative and false negative classifier responses. In the experiments, the VGGish convolutional neural network was used as the initial classifier. The audio signal is converted into a spectrogram and is fed to the input of the neural network which forms the spectrogram feature description and performs a classification. As an example, two ”confused“ classes are selected to demonstrate the increase in classification accuracy. Using the feature description of audio recordings of these classes, an FN-corrector was built, trained and connected to the original classifier. The response from the classifier, as well as the feature description, has been passed to the corrector input. Next, the corrector translated the feature space into a new basis (into a linearly separable space) and classified the classifier answer responding to the question whether the original classifier makes a mistake on such a feature vector or not. If the original classifier made a mistake, then his answer is changed by the corrector to the opposite, otherwise the answer remains the same. The results of the experiments demonstrated a decrease in the level of class confusion and, accordingly, an increase in the accuracy of the original classifier without changing its structure and without collecting an additional data set. The results obtained can be used on IoT devices that have significant limitations on the size of the models used, as well as in solving the problems of domain adaptation which is relevant in audio analytics.

In current digital climate, education sector is evolving as the computer technology advances. Education is being digitized: online classes, online examination methods are conducted, etc. During examination, students are assessed by their answers having given for the question set by a teacher. Today many tools are available to assess the performance of a student using multi choice questions tools which provide instant evaluation, but there are available very limited and operational tools where subjective type answer of students are evaluated. This paper presents a web-based application to address this challenge. It automates the process of subjective answers checking and generates results through using natural language processing methods, like keyword matching semantic, lexical analysis and cosine similarity. Experiments show that appreciated by the teacher result and the system estimation does not have much difference which signifies that the system evaluates answers with a 97 % accuracy. The presented system not only reduces manpower but also eliminates the traditional method of conducting exclusively subjective exams using paper documents. It also eliminates the delays in the paper checking, result generation process. The cases of information leak are being reduced and the objectivity of the assessment is being increased.

The paper presents a methods of image local features extraction research in relation to people authentication problem by face thermogram. As a part of the study, there were formed two datasets for methods training and testing: photographic images and face images in the long-wavelength infrared specter (LWIR) with various factors. The novelty of this study is due to the approach to collecting datasets to verify the accuracy of authentication methods. The dataset was collected with more realistic conditions that affect the quality of authentication, such as changing facial expressions, wearing glasses, medical masks, applying make-up/cosmetics, changing the lighting and temperature conditions of the environment, rotating the head. The methods core is based on the idea of constructing a vector of image features while reducing the dimension and highlighting the boundaries. Likewise, the methods of this group cope well with extracting features task on images and are widely used in the tasks of authentication by 2D face image, as well as in other computer vision tasks. In this paper, four classical methods of local feature extraction are considered: the method of locally binary templates, Gabor wavelets, scale-invariant feature transformation, and Weber’s local descriptor. The classifiers for the feature vectors comparison in this research are SVM and the simplest Perceptron — the basic methods of machine learning. As part of the study, a comparative analysis of each method was carried out in relation to the collected datasets. The methods were trained and tested on a collected face dataset of over 632,000 images of 152 people. As a result of the comparative analysis, it can be concluded that the method of local binary features demonstrates the best result among the considered methods for both types of data: for face thermograms (for SVM — 0,57, for Perceptron — 0,58), for photographic images (for SVM — 0,71, for Perceptron — 0,73). Furthermore, the SIFT method showed similar results: for face thermograms (for SVM — 0,58, for Perceptron — 0,55), for photographic images (for SVM — 0,72, for Perceptron — 0,74). Gabor filters and Weber local descriptor application demonstrate a low accuracy rate in the authentication task by both types of data. The results of the work can be used in access control and management systems to increase the fault tolerance of person authentication. The appliance of the considered methods are effective in the tasks such as processing thermograms for authentication a person by so-called “secondary” signs, for example, by the veins and vessels on face patterns, in cases of facial expressions and appearance changes.

Problems of Wireless Sensor Networks (WSN) are associated with a significant increase in the number of devices on these networks. In this regard, the requirements for the protection and the security of WSN from external influences are increasing significantly. WSN security problems are solved by solving the problem of optimal path routing, energy conservation, and so on. This paper proposes a hybrid model of an efficient packet routing and delivery system to prevent Black-hole attacks. This type of attack is considered the most common on the network due to its unique characteristics. To detect such attacks, a deep learning model using a Convolutional Neural Network (CNN) is proposed. The learning algorithm must be reliable and trustworthy so that attack analysis can be considered at different levels to study the intelligent behavior of network attacks. The paper considers the problem of finding the optimal shortest path using Deep Q-Learning and convolutional neural networks to perform efficient routing and delivery of packets in a safer way. As a result of simulation, the achieved accuracy reached 98.57 %.

The paper proposes a mathematical model of the epidemic process, taking into account the dependence of the rates of cure and loss of immunity on time. Today, mathematical models of epidemics based on the basic Kermack–McKendrick model have become widespread. The most famous models are Susceptible-Infected-Recovered (SIR) and Susceptible-Exposed-Infected-Recovered (SEIR). These models are based on dividing the population into separate groups that are in different epidemic conditions. The description of the models is based on differential equations similar to the equations of birth and death in the process of radioactive transformations of elements in a radioactive chain. However, this approach does not take into account the dependence of the probabilities of the transition of the population from group to group on time spent in the treatment process and in the process of loss of acquired immunity. The known models do analyze the nature of the course of the epidemic for long periods of time, when the process can enter a stationary state. The paper proposes a mathematical model based on dividing the population into separate groups. The first group consists of healthy people susceptible to infection due to contact with members of the second group, which includes the infected population. Members of the third group are being treated, the fourth group includes members of the society who have recovered with antibodies and are vaccinated. The fifth group consists of deceased members of society. In contrast to the SIR and SEIR models, the proposed approach takes into account that immunity is lost over time, and people who survived again move to the group susceptible to infection. The dependences of the probabilities of transition from group to group on time spent both during the treatment process and in the loss of acquired immunity have been taken into account. Thus, the proposed mathematical model is based on five integro-differential equations, two of which are partial differential equations. A new mathematical model has been formulated that makes it possible to take into account the dependence of the cure rate and the probability of transition from the vaccinated state to the initial state on time spent in the corresponding state. It is shown that the proposed model is autocatalytic. With increasing time, a state of bistability is observed, when, under the same boundary conditions, two stable states coexist. Switching between states is determined by the epidemic spread control parameter found in the work. One of the stable states is stationary and leads to the end of the epidemic, the second one leads to the population’s extinction. It has been shown that, for the stationary regime, the form of the distribution function in terms of treatment time and exposure time in the vaccinated state does not affect the final result in any way. The conditions for suppressing the epidemic for managing the process of its development are formulated. Numerical experiments were carried out to simulate the epidemic spreading process, taking into account the constancy of all transition probabilities. Integration of the original system of equations was carried out using the Radaus algorithm for stiff differential equations. The results of numerical simulations have confirmed that the experimental data agree with the theory of the control parameter. The results of the work can be used to organize the management of the epidemic spreading process in order to suppress it as soon as possible by changing the value of the control parameter.

The paper considers the optical systems of virtual reality, which use an optical wedge to eliminate or reduce the conflict of convergence and accommodation (vergence- ccommodation conflict, VAC). The inclined surfaces of the optical wedge introduce specific aberrations into the optical system that can critically affect image quality. The authors analyzed wedge aberrations using relationships derived from the third-order aberration theory. In contrast to existing approaches, the relationships were obtained without the assumption of a small refractive angle or wedge thickness. The results demonstrate that in the scheme with an optical wedge, with characteristics typical for virtual reality systems, the dependence of astigmatism on the angular field is linear and significantly exceeds the other types of aberrations. It is shown that to obtain a high-quality image, the most successful compensation for such aberration can be achieved by using diffractive optical elements (kinoforms) or a Fresnel lens. The paper gives examples of optical systems with a wedge, developed taking into account the requirements for the overall dimensions of virtual reality systems and image quality. The obtained ratios for the aberrations of the optical wedge and the inclined surface make it possible to evaluate the correction capabilities of schemes where such elements are used with arbitrary characteristics. The proposed solutions can be used in virtual reality systems with a reduced value of vergence-accommodation conflict.

The paper considers the problem of controlling the movement of a mobile robot along a given smooth trajectory without measuring its position coordinates. To solve the problem, an adaptive observer of the local coordinates of a moving object is used by measuring the linear speed, yaw angle, and range to a beacon with known coordinates. Then the minimum distance from the robot to the given smooth trajectory is determined. Based on the estimates for the coordinates of the robot and the distance to the curve, we synthesized the control law of the movement along the trajectory with the desired speed under the conditions of uncertainty of the mathematical model. The motion control algorithm is based on the robust sequential compensator method, which ensures that the deviations of the robot from a given trajectory are limited. The proposed coordinate observer ensures asymptotic convergence of the estimation errors to zero. In this paper, we propose two algorithms for determining the minimum distance from the robot to the trajectory: an exact analytical calculation and a nonlinear observer that guarantees the convergence of the estimate to the true value in an arbitrarily short time. The trajectory regulator ensures the movement of the robot along a given trajectory with a limited error. The application of the proposed approach allows one to solve the issues of controlling the movement of a mobile robot without measuring the position coordinates. The approach can be widely applied for controlling self-driving vehicles when they run in tunnels or under a bridge, where it is not possible to measure their coordinates using the satellite navigation systems (GLONASS or GPS).

The development of the medical imaging field is becoming a significant challenge due to the growing need for automated, fast, and efficient diagnostics. Traditionally, blood cells are counted by using a hemocytometer along with other laboratory equipment and chemicals, which is a laborious task. The paper investigates the application of machine learning methods to the identification and classification of blood cells, which allow increasing the recognition rate without deteriorating quality. A comparative analysis of methods for solving the problem of recognizing blood cells based on artificial intelligence approaches is carried out. The paper uses support vector machine, k-nearest neighbors’ algorithm, deep learning (convolutional neural network), and forward propagation neural network. A set of images with cell samples was selected as the initial data for comparison. A comparative analysis of the quality of the considered algorithms was performed on a set of training data with more than 3000 images. It is shown that a program that implements artificial intelligence methods provides a cell recognition time within 4-6 seconds when using an office personal computer, which is significantly less than the time spent by medical workers on one study of a biomaterial. The implementation of the presented results makes it possible to automate the process of studying a biomaterial, reduce the time for conducting and obtaining the result of the analysis of whole blood cells (identification and counting), lessen the influence of operator errors on the result, unload computing resources, thereby increases the efficiency of digital medicine.

Recently, television cameras operating in the near-infrared range have become increasingly widespread. The advantage of shooting in the short wave infrared range is the ability to observe objects in low light and difficult weather conditions. Such cameras can use hybrid sensors that consist of an infrared photocathode and an electron-sensitive matrix based on silicon in a single vacuum volume. The paper investigates the capabilities of one of the latest samples of a similar camera, created at JSC “NRI Electron”. The images of a human, water, ice, snow and other objects in the wavelength range of 0.95–1.7 microns have been analyzed. The images were taken using a television camera based on a hybrid television infrared sensor, which consists of a photocathode and a silicon charge-coupled device in proximity range to each other in a single vacuum volume. Illumination of the objects in the near-infrared range was produced by a continuous spectrum lamp with a maximum of the detected radiation at a wavelength of 1.55 μm. The authors compared the images obtained in the near-infrared range with the ones obtained in the visible region. An explanation is given for the differences between snow images and water and ice images in the near-infrared range. As an example, the difference in light transmission between the surfaces of materials for diving equipment, such as coated and open cell neoprene, is demonstrated. Due to a significant contrast shown in the near-infrared range by images of various objects on the surface of water and ice, it is possible to create an effective system for searching objects on the water. The paper discusses the advantages of the proposed visual search system compared to other systems, including passive systems and the ones operating in the MWIR and LWIR. The research outlined the prospects of using the new camera for building an effective search system for objects and people on water surfaces.

The paper considers the problem of an effective microservices interaction and its organization to support data consistency in fault tolerant and high load systems. The “Saga” microservices orchestration template was used for microservices management. The authors assessed the expediency of asynchronous programming principles usage for designing the Saga coordinator. The simulation of processes in the Saga coordinator was conducted; it considers different specifics of asynchronous and synchronous configurations of distributed transactions (Sagas) management. Synchronous configuration group includes a coordinator with a fixed pool of threads and a coordinator that generates a new thread for each new Saga. Asynchronous configuration group consists of a coroutines based coordinator and a coordinator that uses Linux core scheduler. The set of simulations with different numbers of Sagas and available coordinator processors was executed. It was shown that the use of asynchronous approaches significantly reduces the Saga’s execution duration up to 9.74 times and improves the processor time utilisation value up to 88 %. The obtained data proves the efficiency of asynchronous programming principles applied to the design of the Saga coordinator. The difference in efficiency between the asynchronous algorithms that were implemented in this paper was insignificant. Asynchronous programming principles used to build the Saga coordinator allow it to handle bigger load and to use processor resources in a more efficient way. The outcome of this research can be applied during the design of fault tolerant and high load systems. The paper might be interesting to IT-specialists and researchers focusing on distributed computing.

Methods of studying human motion in computer vision systems can be divided into two types. These are analysis in twodimensional and three-dimensional space. The former uses a single camera image and/ or multiple body sensors. Such an approach leads to a rapid accumulation of error and, consequently, low accuracy of the figure representation. Multiple cameras are usually used in the case of three-dimensional space analysis, while the objects are represented as sets of volumetric elements. Despite the high accuracy of this method, it is associated with high computational complexity and internal network load. The purpose of the paper is to develop a model using a single camera, while approaching threedimensional space analysis methods in terms of accuracy. In this paper a human figure is represented as a skeleton. The skeleton is described by an acyclic connected graph. The general structure of a human figure is analyzed. Fifteen basic points are selected. Physical and logical connections between them were studied and mathematically described. The velocity and spatial characteristics of the points and connections outline the general dynamics of motion. The study describes a model of human motion and gives the option for model construction on the example of a particular image. The developed algorithm for collection and analysis of information estimates relative locations and velocity characteristics of the graph elements. The model can be used for acquisition of information about the reference dynamics of human movements. In case of detecting major differences between the reference and the reality, the behavior is defined as deviant. Thus, the obtained algorithm can be applied in computer vision systems for detection and analysis of human movements.

The paper proposes a method for studying the color rendition of digital cameras. This parameter is conventionally assessed visually by color targets in photography and design. The proposed method compares the chromaticity values of standard test objects with their measured values on a digital camera using special setup features. The setup includes a light source, a collimator for uniform illumination of a reflecting screen with a test object, and a research object, i.e., a digital camera. The camera is positioned at a 45 degree angle to the screen. This setup follows the recommendations of the Commission Internationale de l’Eclairage (CIE) for color measurements. To measure the colorimetric characteristics of the samples, the authors adopted the 0/45 illumination / observation scheme. The test object is illuminated with a light beam, the axis of which makes an angle not exceeding 10° from the normal to the sample surface. The sample is observed at an angle of 45° ± 5° from to the normal. The angle between the axis of the illuminating beam and any of its rays does not exceed 5°. A type A source (color temperature 2856 K) acts as an illuminator. Standardized reference sets of colored optical glasses (light filters) characterized by known chromaticity coordinates were chosen as test objects. To evaluate the results, specialized software has been developed that allows one to select individual pixels, calculate their brightness in order to find the chromaticity coordinates and compare the results with reference values. The method was tested using the Canon EOS 60D digital camera. At the time of measurement, digital filters for correction, anti-aliasing, sharpening, as well as color adjustment were turned off in the camera. The paper presents colorimetric measurements using 58 colored optical glasses. The averaged values fall into seven groups. The selected color space for measurements is sRGB. The measurement results proved the possibility of using the proposed technique for analysing and choosing appropriate digital recording devices for colorimetric measurements in such areas as medicine, chemistry and food industry.

The paper proposes an approach to obtaining images of the objects under investigation based on indirect optical location data. The goal of the study is to increase the graphic similarity of the images and to assign them measuring properties. To achieve this goal, the concept of photogrammetric processing of frame images obtained by conducting indirect optical location in a certain way is formulated. The graphical similarity of the images is proposed to be improved by extracting photometric data related to the object and the background from the registered optical radiation. Based on the selected data, a statistical evaluation of the sample average of the optical radiation intensity from these sources is carried out. The obtained estimates are used to form a monochrome digital image. Adding measurement properties is done by converting the coordinates of the digital image to relative coordinates that have a metric expression. The reason for the decrease in the graphical similarity of the images obtained on the basis of indirect optical location data is determined. In particular, the addition of light waves from different sources, during the allotted exposure time of the photodetector, leads to the merging of the object and the background in the resulting image. The paper presents an approach to the separation of photometric data from different sources that is based on the observation of the phase difference between the emitted and recorded light waves. The authors define the mathematical apparatus for linking the obtained images to the relative coordinate system that is adapted for the case of indirect optical location. The concept of conducting indirect optical location using a special optoelectronic complex is proposed. The study describes the requirements for the equipment of an optoelectronic complex that generates and registers optical radiation with the required parameters. The results of an experiment on the formation of images with measuring properties confirm the feasibility of using the proposed method. Conducting an indirect optical location opens the way to obtaining images of an area that is inaccessible to humans. In particular, the results of the experiment demonstrate that the use of the proposed concept provides images of an object placed behind a light-tight obstacle, which are characterized by the presence of measuring properties and reflect the details of the object under study with high graphical similarity.

The paper presents the results of mining and primary approbation of plasma method for producing pure white corundum. Upgrading ways of pure corundum production is an important task for industry as part of reducing the energy consumption and environmental contamination. The purposes of the research at this stage are as follows: the selection of raw materials, formative evaluation for characteristics of the technology, conducting an experiment on melting and assessment of the sample. The corundum melting is conducted in the reactor using high-voltage plasmatron. Mixture of argon and 25–30 percent of nitrogen is used as the working fluid. The authors suggest using a four-layered protection of a melting reactor in order to ensure both thermal insulation properties and strength characteristics. This is especially relevant under temperature difference of the order of 2000 K and elimination of defective crystallization of the melt from the walls of the reactor. As a result of an experiment on melting alumina marked G-00 using high-voltage air powered plasmatron, the sample with alumina oxide in the amount of 99.79 percent and with absolute hardness equal to 500 was obtained. Further experiments make it possible to determine the prospects of using the proposed technology to obtain samples with an increased content of aluminum oxide. The paper discusses the application of the described technology for industrial production of pure corundum single crystals. The technology will make it possible to obtain samples to be used as abrasives for optical systems and for the production of sapphire glasses and scalpels.

The paper focuses on revealing insider information leaks of financial markets during investment consulting. An original dataset was created, containing the records of the conversations between consultants and clients, presented in the form of dialogs in text format. The applicability of machine learning methods for automating the detection of leaks arising in a conversation between a consultant and a client has been studied. The authors examined the applicability of the following supervised machine learning methods for constructing and training a classifier: probabilistic (Naïve Bayes classifier), metric (k-nearest neighbors algorithm), logical (random forest), linear (support vector machine), and methods based on artificial neural networks. The paper considers various approaches to the construction of a natural language text model, such as tokenization (bag of words, word n-grams: bigrams and trigrams) and vectorization (one-hot encoding). The proposed algorithm for detecting financial markets insider information leaks is based on the use of support vector machine (SVM) and tokenization by bigrams. The obtained results demonstrate that SVM and bigram tokenization provide the highest leakage detection accuracy. The research results can be used in cybersecurity tools development, as well as for the further elaboration of natural language processing methods dealing with information security problems.

The paper considers the problems of modeling and identification of parameters for models of surface ships. The proposed identification method is applied to a modified second order Nomoto model for ship steering. The identification algorithm is based on the Dynamic Regressor Extension and Mixing Method (DREM) that is performed in two steps. At the first stage parameterization is used for a regression model, in which the regressor and regression depend on the measured signals, namely, longitudinal, lateral and angular velocities and steering angle. At the second stage a new regression model is built using linear stable filters and delays. Finally, the parameters are estimated by the standard gradient descent method. The paper proposes a new algorithm which identifies the parameters for models of surface ships. The authors analyzed the prospects of the proposed estimating method by computer experiments. Experiments have shown the advantage of the method: when using the gradient descent method, the transient time spent to estimate the signal parameters is much longer than using the DREM method. At the same time, in the case of using the DREM method, there is no overshoot. The results of the work can serve as a basis for methods, algorithms and software for designing ship automated navigation systems and control systems for other modes of transport. This is confirmed by the simulation results.

The paper presents an analysis of the existing methods for assessing information security risks, their features, advantages and disadvantages, as well as determines the possibility of using such techniques for assessing information security risks in financial institutions. Criteria for comparing information security risk assessment methods have been formed, the advantages and disadvantages of the methods are described. It is shown that, despite the requirements of regulators for assessing information security risks, most of the regulatory documents deal with operational risks. The evaluation of information security risks of credit and financial institutions does not have sufficient regulation and formalization. The authors substantiate the necessity of developing a method for assessing information security risks for credit and financial organizations, taking into account the features of risk assessment inherent to the mentioned organizations. The paper considers the need to create lists of existing threats to the credit and financial sector and their linking to existing vulnerabilities to optimize the process of assessing information security risks. The development of a methodology for assessing information security risks will increase the degree of compliance of credit and financial institutions with the requirements of international, state and industry standards through an optimal set of protection measures and models for evaluating information security risks.

Most of the medical data in hospital information systems databases are stored in an unstructured form. Techniques for processing unstructured records are widely presented in scientific papers focused on English data. This paper proposes a method for intellectual analysis of unstructured allergy anamnesis in Russian in order to identify the presence and type of allergy and intolerance of a patient. The method is based on machine learning algorithms and uses international standards for the exchange of medical data and terminology standards, such as FHIR and SNOMED CT. As a result of the experiment, about 12 thousand medical records were processed. F-measure for the developed classification models ranged from 0.93 to 0.96. The models showed high values of metrics for evaluating the effectiveness of the models. In the future, structured data can be used in models for predicting medical risks. Further development of methods for structuring medical texts will ensure the interoperability of medical data.

The paper provides a classification and outlines the current state of anti-thermal imaging protection of military equipment. Currently, improving the reliability of such objects in combat conditions is one of the key tasks. The authors carried out the analysis and considered the prospects for the development of existing systems of anti-thermal imaging protection for moving objects as an important factor in increasing their reliability. It has been shown that the most promising are active-type anti-thermal imaging protection systems. The paper proposes a way to improve the reliability of armored and other vehicles in modern conditions. As an example, an anti-thermal imaging protection system consisting of active cooling modules is considered for armored vehicles. It can operate in two modes: stealth and rapid supercooling of the object’s surface (“black hole”). During the operation of the anti-thermal imaging protection, the system uses controlled cooling of active modules with liquid nitrogen. A design is proposed and a method for calculating the parameters of active cooling modules is developed. The advantages of the developed anti-thermal imaging system for protecting the object are as follows: dual-mode operation of the system and the use of a pre-stored “cold” source, which makes it possible to eliminate the need for additional energy consumption during operation. The proposed system of modular active anti-thermal imaging protection can be used for different vehicles with appropriate adaptation to the object of the general design of the system and modification of the adjustable cooling active module.

The paper considers a design method for a side-emitting lens working with a single LED source and providing a narrow light beam in the horizontal direction within 360°. The authors deal with the composing method in the design, which is usually used to synthesize the initial scheme of the imaging systems. However, in this case, a similar approach is applied to the synthesis of a system, the task of which is to provide a certain shape and characteristics of the light beam. The stage of choosing an initial principal design and synthesis for non-imaging optics is especially important since this area is characterized by the use of so-called local optimization, the result of which strongly depends on the original system. Therefore, the stage of forming an initial approximation of the system becomes crucial. In this case, the composing method can provide the most effective choice of an initial scheme of a side-emitting lens. The application of the composing method and the theory of aberrations in the field of synthesis of the initial design of a side-emitting lens is shown. The paper describes a method for selecting the key parameters of the system, and presents the relationships that allow a preliminary evaluation of the characteristics of the designed system without the use of time-consuming calculation or optimization procedures. The presented approach makes it possible to ensure the choice of the initial point of the system for further optimization, as well as to achieve high efficiency of using the light flux by the optical system of the lens (up to 90 %), only due to the optimal size of the zones into which the beam is divided and to the optimal parameters of the generating curves. In this case, the lens profile is formed by two zones in each the profile is a conic curve, hence, the curve can be described by a small number of parameters, which is very convenient at the stage of searching the initial scheme. The proposed approach can be applied in the design of such systems, as well as applied at the stage of preliminary assessment of achievable characteristics, which can significantly speed up the development process.

The paper presents an approach to the parametric convergence performance improvement applied to the direct adaptive multi-sinusoidal disturbance compensation problem. The proposed method improves the performance of the existing solutions and ensures the transient monotonicity. The Dynamic Regressor Extension and Mixing (DREM) procedure followed by the discrete gradient estimator is applied for disturbance parameters estimation. The paper proves the applicability of Kreisselmeier’s scheme as an extension of the algorithm in procedure dynamic regressor extension. A numerical simulation is presented to illustrate the improvement of the transient processes of estimating the parameters of an unmeasured perturbation using the DREM procedure. The work can be used in solving practical problems in the fields of processing and evaluating harmonic and multi-harmonic signals, e.g., to suppress vibrations in electromechanical systems.

The paper presents the results of the development of an open-access web-based system operating in predictive and retrospective modes and providing the user with an interactive tool for monitoring spatial data using the example of visualizing the probability of observing aurora borealis. The work proposes an algorithm for web rendering of spatial images, which provides an increase in the reactivity of web applications due to the formation of a rendered layer on the server side, in contrast to the known approaches solving the problem of interpolation and generation of a spatial layer at the client level. The paper describes the architecture of the information system whose distinctive feature is the combination of various patterns of web programming, i.e. from a monolithic application to a microservice one with elements of a modular architecture of the “model–view–controller” type. The experimental studies allowed establishing an increase in the rendering speed of a spatial image by an average of 8.1 times. The results of the studies have shown that the considered approach to visualization as applied to the geophysical parameters in the region of the auroral oval will provide an increase in the efficiency of studying the dynamics of the auroral oval, which will help to reveal new knowledge regarding the topology of the magnetosphere and its changes, for example, during geomagnetic storms and substorms.

Subject of Research. The paper presents the study of algorithms for key point detection and description, widely used in computer vision. Typically, the corner detector acts as a key point detector, including neural key point detectors. For some types of images obtained in medicine, the application of such detectors is problematic due to the small number of detected key points. The paper considers a problem of a neural network key point detector training on unlabeled images. Method. We proposed the definition of key points not depending on specific visual features. A method was considered for training of a neural network model meant for detecting and describing key points on unlabeled data. The application of homographic image transformation was basic to the method. The neural network model was trained to detect the same key points on pairs of noisy images related to a homographic transformation. Only positive examples were used for detector training, just points correctly matched with features produced by the neural network model for key point description. Main Results. The unsupervised learning algorithm is used to train the neural network model. For the ease of comparison, the proposed model has a similar architecture and the same number of parameters as the supervised model. Model evaluation is performed on the three different datasets: natural images, synthetic images, and retinal photographs. The proposed model shows similar results to the supervised model on the natural images and better results on retinal photographs. Improvement of results is demonstrated after additional training of the proposed model on images from the target domain. This is an advantage over a model trained on a labeled dataset. For comparison, the harmonic average of such metrics is used as: the accuracy and the depth of matching by descriptors, reproducibility of key points and image coverage. Practical Relevance. The proposed algorithm makes it possible to train the neural network key point detector together with the feature extraction model on images from the target domain without costly dataset labeling and reduce labor costs for the development of the system that uses the detector.

The paper considers methods of countering speech synthesis attacks on voice biometric systems in banking. Voicebiometrics security is a large-scale problem significantly raised over the past few years. Automatic speaker verificationsystems (ASV) are vulnerable to various types of spoofing attacks: impersonation, replay attacks, voice conversion, and speech synthesis attacks. Speech synthesis attacks are the most dangerous as the technologies of speech synthesisare developing rapidly (GAN, Unit selection, RNN, etc.). Anti-spoofing approaches can be based on searching forphase and tone frequency anomalies appearing during speech synthesis and on a preliminary knowledge of the acoustic differences of specific speech synthesizers. ASV security remains an unsolved problem, because there is no universalsolution that does not depend on the speech synthesis methods used by the attacker. In this paper, we provide the analysisof existing speech synthesis technologies and the most promising attacks detection methods for banking and financialorganizations. Identification features should include emotional state and cepstral characteristics of voice. It is necessary to adjust the user’s voiceprint regularly. Analyzed signal should not be too smooth and containing unnatural noisesor sharp interruptions changes in the signal level. Analysis of speech intelligibility and semantics are also important.Dynamic passwords database should contain words that are difficult to synthesize and pronounce. The proposed approach could be used for design and development of authentication systems for banking and financial organizations resistantto speech synthesis attacks.

This paper considers the problem restoring a non-stationary heat flow from a coolant to a heat-storing substance of a separate element of a thermal accumulator. Solving the problem allows avoiding errors associated with averaging the heat flow over all battery cells, and provides the opportunity to find the optimal sizes and composition of the filler for each battery cell. The problem is especially relevant for cascade batteries where cells with different fillers are simultaneously used. A comparison is made of two methods for solving the problem. The first method is based on numerical simulation of the thermal energy storage discharge process using the Computational Fluid Dynamics software package. The second approach proposed by the authors is based on the parametric identification of a differential-difference model of heat transfer with the solution of the inverse problem of heat conduction together with coefficient smoothing calculation. The proposed method makes it possible to smooth out abruptly changing thermophysical characteristics and take into account the moving phase boundary of a substance. The method for solving the inverse heat conduction problem can significantly reduce the recovery time of non-stationary boundary conditions of heat transfer for the entire battery and, thus, reduce the requirements for computing resources when designing and optimizing the battery by facilitating experimental search. For the first time, the use of the method of parametric identification and calculation of smoothing coefficients for solving the Stefan problem was considered and proposed. The results obtained can be used to calculate the heat flow from an individual element of a thermal energy accumulator.

This paper addresses the problem of optimizing the use of temporal resources of a radar station (RS) under limited time resources. Special attention is given to the necessity of considering a multitude of compensatory optimality criteria when allocating the RS operating time. The proposed approach is based on the use of fuzzy set theory which represents an innovative solution in the context of this task. The task of managing the RS temporal resources is formulated as the search for an optimal work schedule among all potentially possible options. This schedule should minimize the values of all partial optimality criteria. Fuzzy set theory is applied to solve this problem, allowing for the consideration of uncertainty and variability in task execution conditions. An algorithm for managing the RS temporal resources was presented. The review results confirm the probable increase in efficiency, especially in conditions of acute shortage of temporal resources, ensuring their optimal distribution among current tasks. Furthermore, the algorithm enables decisions to be made about the possibility of performing special or additional tasks without compromising the main monitoring functions. The review of the proposed algorithm provides a basis for hypothesizing its advantages over traditional methods of managing the RS temporal resources. In particular, the use of fuzzy set theory allows for more flexible responses to changes in task execution conditions and enhances the overall adaptability of the system. In the future, this approach could be adapted and applied in other areas where there is a need for resource optimization under conditions of limitation and uncertainty of external factors.

More recently, permanent magnet synchronous motors (PMSM) have been widely applied to power source for different applications, such as high precision tracking systems, standalone electric and unmanned aerial vehicles, industrial robotics, marine propulsions, etc., due to their advantages to conventional competitors for example induction motor with squirrel-cage rotor. In order to reduce the cost of AC drive, the removal of the mechanical sensors is required. Hence, the sensorless motor control is more preferable and is based on electrical measurements, namely, three-phase currents and voltages. The paper is devoted to sensorless field-oriented control design procedure for a non-salient PMSM. The proposed control strategy is employed on full order sliding-mode observer which provides the output insensitivity to parameter changes and disturbances. In order to reduce th e high-frequency chattering and enhance the rotor position estimation quality and accuracy, the band-pass filter with tracking of the central frequency to the speed reference is applied. To obtain actual information about the unmeasurable rotor position and speed, the phase-locked loop with cascade connection of adaptive proportional-integral controller is employed. A simulation of the dynamic starting mode of a PMSM under zero initial conditions has been performed by MATLAB/Simulink environment. As can be concluded from the simulation results, proposed sensorless field-oriented control strategy provides quick response as well as low rotor position estimation error both transient and steady-state behavior. The research significance of proposed PMSM sensorless field-oriented control strategy is to provide the wide range of motor speed operation, strong robustness of estimated rotor position to parameter perturbations as well as quality suppression of high frequency chattering effect owing to the switching attribute and the internal control discontinuity of sliding mode, whereby the practical application of a sensorless variable-frequency synchronous electric drive is expanding.

The primary idea of this paper is the implementation of the Optimal Key-Tuned Rivest Shamir Adelman technique, a dual authentication approach for effective data sharing in the cloud within hospital data management. The system begins with user registration with the Trusted Center where user details are provided. An authentication scheme utilizing the Caesar cipher and the Secure Hashing Algorithm 512 ensures integrity. The encryption process employs the Optimal Key-Tuned Rivest Shamir Adelman scheme for secure file transmission. To enhance key creation procedures in the Rivest Shamir Adelman model, the Improved Butterfly Optimization Algorithm technique is utilized to maximize throughput. Finally, dual authentication is conducted on the receiver side for file access and downloads from the cloud server. This additional layer of authentication fortifies the system resilience against unauthorized access, ensuring that only legitimate users can interact with the healthcare data stored in the cloud. The results indicate that the system outperforms other state-of-the-art systems enabling secure sharing and downloading of health data in cloud environments.

Artificial intelligence has become widespread in image processing tasks. At the same time, the number of vulnerabilities is increasing in systems implementing these artificial intelligence technologies (the attack surface is increasing). The main threats to information security can be implemented by introducing malicious perturbations into the input data, regardless of their type. To detect such attacks, approaches and methods have been developed based, in particular, on the use of an auto-encoder or the analysis of layers of the target neural network. The disadvantage of existing methods, which significantly reduce the scope of their application, is binding to the dataset or model architecture. This paper discusses the issues of expanding the scope (increasing scalability) of methods for detecting L0-optimized perturbations introduced by unconventional pixel attacks. An approach to detecting these attacks using statistical analysis of input data, regardless of the model and dataset, is proposed. It is assumed that the pixels of the perturbation embedded in the image, as a result of the L0-optimized attack, will be considered both local and global outliers. Outlier detection is performed using statistical metrics such as deviation from nearest neighbors and Mahalanobis distance. The evaluation of each pixel (anomaly score) is performed as a product of the specified metrics. A threshold clipping algorithm is used to detect an attack. When a pixel is detected for which the received score exceeds a certain threshold, the image is recognized as distorted. The approach was tested on the CIFAR-10 and MNIST datasets. The developed method has demonstrated high accuracy in detecting attacks. On the CIFAR-10 dataset, the accuracy of detecting onepixel attack (accuracy) was 94.3 %, and when detecting a Jacobian based Saliency Map Attack (JSMA) — 98.3 %. The proposed approach is also applicable in the detection of modified pixels. The proposed approach is applicable for detecting one-pixel attacks and JSMA, but can potentially be used for any L0-optimized distortions. The approach is applicable for color and grayscale images regardless of the dataset. The proposed approach is potentially universal for the architecture of a neural network, since it uses only input data to detect attacks. The approach can be used to detect images modified by unconventional adversarial attacks in the training sample before the model is formed.

It is known that when optical radiation passes through the phase modulator of a multifunctional integrated-optical chip (MIOC), along with the modulation of the phase of the light wave, there is a change in the power of optical radiation at the output of the coupled waveguide. This modulation is parasitic, and its magnitude depends on the control voltage at the modulator electrodes. Amplitude modulation leads to an error in the output signal of highly sensitive phase sensors, in particular, in a fiber optic gyroscope. This paper presents an experimental study of the change in the spatial intensity distribution (mode field) at the end of channel waveguides of a multifunctional integrated-optical chip under the action of an applied voltage. The experimental setup was assembled with a radiation source in the form of a singlefrequency laser RIO ORION with a central emission wavelength of 1550 nm. The optical receiver was an infrared camera SP503U-1550 with radiation registration in the wavelength range 1440–1605 nm, pixel size 9.9 × 9.9 μm and matrix size 640 × 480 pixels. The multifunctional integrated-optical chip was fabricated by titanium diffusion technology in Ti:LiNbO3 X-cut lithium niobate crystal substrate. A constant control voltage in the range from –10 V to +10 V was applied to the electrodes of the MIOC phase modulator. The distribution of optical radiation intensity in MIOC waveguides and in a single-mode optical fiber with an elliptical ESC-4 straining sheath was analyzed by calculating the overlap integral. The effect of electric field on optical radiation in MIOC waveguides is experimentally demonstrated. It is demonstrated that at constant voltage at the control electrodes of the phase modulator change in the radiation intensity distribution at the output of channel waveguides is observed. The observed changes correlate with parasitic amplitude modulation. The occurrence of parasitic amplitude modulation is due to the propagation of parasitic optical radiation along the waveguide. This phenomenon is caused by the escape of lithium oxide from the surface layer of lithium niobate into the gas phase during the technological process of titanium diffusion. The studies have allowed us to better understand the mechanisms of parasitic amplitude modulation in the phase modulator of MIOC and to develop practical recommendations for their elimination. These results can be useful for specialists working on research in the field of highly sensitive phase sensors using integrated optic circuits.

For continuous wavelet transformation, wavelets based on derivatives of the Gauss function are used, and for multiscale analysis, Daubechies wavelets are used. The development of algorithms for forward and inverse continuous wavelet transform in the frequency domain made it possible in this work to synthesize digital filters with a finite impulse response (FIR) different from existing methods. The quality of the synthesized filters was checked by decomposition and subsequent reconstruction of the signals. To do this, several filters were synthesized that completely cover the frequency range of the signal. Since wavelets are bandpass filters, the authors called the filters wavelets. The more precisely the reconstructed signal repeats the shape of the original signal, the better the wavelet constructed by one method or another. A comparison of the accuracy of signal reconstruction shows that the best conversion result is obtained by using synthesized wavelets. The impulse responses of the FIR filters are synthesized so that their frequency response are similar to the frequency responses of wavelets based on derivatives of the Gaussian function of a large order. The greater the filter order, the closer the frequency response is to a square-wave shape. Algorithms for forward and inverse wavelet transformation of a signal in the frequency domain using wavelets based on derivatives of the Gauss function are proposed. Profiling of the program shows that the time of the wavelet transforms using the fast Fourier transform is 15,000 times less than with the direct numerical integration for sampling the signal of 32,768 samples. These algorithms can be used for wavelets with a square-wave frequency response. At the same time, the numerical calculation time is halved. The accuracy of the reconstruction was compared for wavelets based on second-order derivatives, Daubechies wavelets, and wavelets with a square-wave frequency response. The reconstruction accuracy is highest for the latest wavelets. The use of the wavelet construction method is preferable since this method is relatively simple and it is easy to synthesize multiband filters with any form of frequency response. If, when synthesizing using existing methods, a short transition band can be obtained only for long impulse responses, while the transition band using the method of constructing wavelets is absent even for filters of very small orders. The paper presents the impulse responses of twoband, three-band digital filters and their frequency response. FIR digital filters with a square-wave frequency response have a higher delay-band attenuation coefficient compared to existing filters, do not have transition band, and can be used to process one-dimensional and two-dimensional signals.