Table of contents

10th International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production (HPCST-2020). May 15-16, 2020, Barnaul, Russia

The 10th International Conference on High-Performance Computing Systems and Technologies in Scientific Research, Automation of Control and Production (HPCST-2020) took place at the Altai State University on May 15 - 16, 2020. Altai State University (AltSU) is located in the center of Barnaul city - the capital of Altai region of the south-west of Siberia.

HPCST is a regular scientific meeting that is held annually since 2011. It attracts specialists in the various fields of modern computer and information science, and their applications in automation of control and production, in mathematical modelling and computer simulation of processes and phenomena in natural sciences by means of parallel computing.

The aim of the traditional annual conference is to present state-of-art approaches and methods for solving contemporary scientific problems, to exchange the latest research results obtained by scientists both from universities and research institutions. All the results are valuable contributions to the modern computer and information science and to their applications and technology.

Taking into account the COVID-19 pandemic, the HPCST-2020 conference was held in the remote mode as a video conference with a presentation of materials on the conference's online resources. HPCST-2020 virtual meetings took place in the conference room (figures 2-3) of the university administration building using the Zoom remote videoconferencing system (figure 4).

List of Conference Photographs are available in this PDF.

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

□ Type of peer review: Single-blind / Double-blind / Triple-blind / Open / Other (please describe) : Single-blind peer review (by 2 referees) with the mandatory spell and style check

□ Conference submission management system: submissions were received and handled via e-mail

□ Number of submissions received: 56

□ Number of submissions sent for review: 51

□ Number of submissions accepted: 34

□ Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 60%

□ Average number of reviews per paper: 2

□ Total number of reviewers involved: 11

□ Any additional info on review process: all the papers were review by the session editor and assigned expert referee, spell-check and style check was performed by an invited technical writer

□ Contact person for queries: Vladimir A. Faerman, corresponding editor, fva@fb.tusur.ru

The article considers the VLSI architecture intended for streaming data processing using a configurable path based on sequential distributed arithmetic. The development of specialized VLSIs is advisable if there is a need for serial production of devices, and the domain of application of such VLSIs decreases as the capabilities of the CPU, GPU and FPGA expand. The alternative approach is to build configurable VLSIs that can efficiently perform computations in related applications. The solution under consideration is focused on performing stream operations, including FIR filters and other tasks based on the operation "multiplication and accumulation", for example, neural networks and deep learning algorithms. The architecture provides for compliance with the GALS (Globally Asynchronous, Locally Synchronous) approach, which allows placing many independent computing nodes in the VLSI. The characteristics of VLSI were evaluated and the areas of preferred application of the considered architecture were considered.

The use of third-party ready-made solutions to perform special computing tasks (SCT): processing text arrays in a natural language, the use of cryptography methods in data transmission networks, machine learning in solving applied problems, scientific computations and many other ones is a common practice in modern development of software systems. However, the use of third-party ready-made software solutions often leads to their poor optimization for parallel and distributed operation and to the difficulty in vertical and horizontal scaling, impossibility of modifying a solution, e.g., due to its legal protection, etc. In order to solve these problems, an asynchronous actor model can be used that facilitates developing software for processing special computing tasks. In addition, an asynchronous actor model allows parallel processing of input tasks, provides asynchronous operation, and extends its functionality to third-party ready-made solutions, that it is impossible or forbidden to modify to meet user's or optimization requirements. Methods, algorithms, and the entire logic of asynchronous actor operation involve transitions of actors from one state to another under the effect of input messages and returning the results of processed tasks to the frame system. This allows setting an automatic grammar and for using methods and approaches for developing software systems based on finite-state automata. The asynchronous actor operation scheme is represented by a directional state graph, which allows using the mathematical apparatus of the finite-state automaton theory (the Mealy model) to describe the same. The developed model is convenient for designing and organizing the SCT processing using computer systems. The use of the asynchronous actor model makes it possible, in special operation modes, to increase the performance of poorly optimized SCT without modifying the same, as compared to task processing without using the asynchronous actor model.

The acoustic emission method was applied to study aluminum-magnesium alloys produced by friction stir welding. Alloy specimens were tested under static tension with simultaneous recording of acoustic emission, applied load, and elongation. The recorded acoustic emission signals were processed using projection methods of multivariate data analysis; the informative features used were the coefficients of wavelet discrete decomposition which characterize the low-frequency form of the signal. It is shown that the proposed approach allows the partition of signals formed on different stages of plastic deformation and fracture. Strong differences in acoustic emission signals were revealed and described to be due to the formation of highly defect structure in the weld zones in different welding modes. The obtained results can be useful for acoustic emission diagnostics of welded joints in structures of metal alloys exposed to external loads.

The paper discusses the implementation of correlation algorithm for time delay estimation on a Raspberry Pi single-board computer. The implemented correlation algorithm is based on Fourier transform. In the course of the study, we applied two alternative solutions for the software implementation of discrete Fourier transform. The first solution stands on FFTW library and uses general-purpose quad-core ARM Cortex A53 processing unit. The alternative method uses VideoCore IV graphic processing unit and is implemented via firmware GPU_FFT library. We have performed a computational experiment on a Raspberry Pi 3B to determine which solution is more preferable for the implementation of correlator. After a comparative study we figured out that estimated processing time is highly dependent on computations parameters and input signals. For small FFT window sizes CPU is proved to be a preferable option. However, for large FFT windows GPU allows significantly accelerating the computations. At some point, you can achieve even better performance by using batching and GPU for direct FFT and CPU for inverse FFT. According with the results, we have concluded that both alternatives have their own potential advantages and particular drawback. We also establish, that Raspberry Pi 3 B computer with HiFiberry extension can be used as a real-time correlator for audio signals.

A method of noise reduction based on an adaptive threshold filtering over trainable wavelet transform was proposed. The restrictions on the trainable transform filter parameters were provided by a set of quadratic regularization terms. As an analog of the "hard" and "soft" threshold functions we used their smooth infinitely differentiable versions. The parameters of trainable wavelet transform, and threshold values were estimated by backpropagation and gradient-based optimization algorithm with an adaptive momentum estimation. Results of the proposed method were compared with an approach based on fixed discrete wavelet transform and non-adaptive global and level-depended threshold algorithms on the model problem. We used signal-to-noise ratio between suppressed and clean signals to numerically estimate the efficiency of noise reduction. We showed that the best results were obtained when the proposed trainable method with Daubechies 4 wavelet filters fine-tuning and adaptive level-dependent thresholding were applied.

The article uses the molecular-dynamic method to calculate the statistical characteristics of a quasi-breather in a CuPt₇ model crystal. In the calculations, a high-performance computing complex based on a GPU accelerator was used, which provided the necessary speed and accuracy of calculations. The phonon spectrum of this model crystal was calculated, and the dependences of the standard deviation, coefficient of variation, and average frequency of the model quasi-breather on its lifetime were revealed. The analysis of statistical data allows concluding that in the model under consideration, using the interatomic interaction potential obtained by the immersed atom (EAM) method, the quasi-breather model solution does not differ significantly from the corresponding exact breather. Moreover, the final destruction of the quasi-breather occurs at a time when the standard deviation of the frequencies exceeds the difference between the average frequency of the quasi-breather and the upper boundary of the phonon spectrum of the crystal. At this moment, the delocalization of vibrations and the dissipation of energy through the crystal in the form of low-amplitude thermal vibrations of the lattice occur. This may indicate the stability of the obtained discrete breather and the possibility of excitation in real alloys of the considered composition.

We considered the issues arising when Daugman's integrodifferential operator is used to localize iris edges. Daugman's integro-differential operator is a widely common method to localize the iris, however, problems of the operator optimization poorly presented in the literature. The article considers existing methods of optimization of the operator applied at the iris recognition step. Based on the provided research we proposed using Nelder-Mead and Differential Evolution methods to optimize the integro-differential operator. The problems of the iris localization and their solving methods were considered. The article focuses attention on non-cooperative iris recognition. The very general boundary conditions based on iris's anatomy which are not dependent on captured image properties were defined. The results of the comparative analysis of the accuracy and performance of selected optimization methods of Daugman's integrodifferential operator were presented at the experimental results chapter. It was found that the Differential evolution optimization method gives fine performance and correctness. It was concluded that the Differential evolution is expedient as Daugman's integro-differential operator optimization method.

The results of computational experiments on the formation of thermal spray WC-10Co4Cr coatings are presented. The effect of sprayed particles velocity (200-1000 m/s), temperature (1600-2500 K) and the size (15-40 microns), as well as substrate temperature (300-600 K), on the properties of coatings (porosity, roughness, adhesion) has been studied. Ranges of particle parameters have been determined, which ensure their spreading process without «splashing» and the formation of coatings with low porosity and high adhesion. A qualitative comparison of the calculation results with experimental data on high-velocity plasma spraying of WC-10Co4Cr coatings is carried out.

We present mathematical simulating results of a gas-liquid mixture flow in a cylindrical pipe. The gas-liquid mixture consists of the mineralized water and propane gas. To analyze the mineral composition of the fluid, a sensor is mounted in the pipe. The sensor affects the topology of the flow velocity vector field. The gas-liquid mixture flow is described by the unsteady Navier-Stokes equations. When the flow rate of gas-liquid mixtures exceeds 20 m/s, eddy flows occur in the pipe with obstacles. A method of discretization should take into account the problem specifics: rapidly changing gradients, the prevalence of the convective term in the Navier-Stokes equations. A computational scheme of discontinuous Galerkin method has the local conservative property and is best suited for solving such singularly perturbed problems. To perform a spatial discretization, a computational scheme of the discontinuous Galerkin method in the function spaces H(div) and L₂ is used. Application of the multiscale approach allows breaking down the solution of the simulation problem into several smaller ones that can be solved using parallel computations. Mathematical modeling results of the gas-liquid mixture flow in the pipe with different options for the sensor location are presented.

The analysis of transport accessibility is a standard task requiring the search for the optimal solution, the solution of which is necessary for the harmonious development of the urban environment in general, and the effective organization of the transportation process in particular. The article discusses the indicators necessary for determining transport accessibility based on analysis of the urban transport system and calculation methods using geographical information systems. The main parameter is time-based accessibility from the central part of the city to other transport zones. To determine the rank of the transport zone, the following statistical characteristics are required: road network density in urban areas; a number of jobs, a number of equipped parking spaces; the number of objects of gravity in transport zones. A decision support system based on geographic information systems can be carried out by two methods: the choice of a relatively ideal solution and simple additive weighing. Analysis of transport zones can improve the quality of statistical data on urban transport medium. The article presents the models, the use which is necessary for efficient operation of urban transport, as well as indicators necessary for the stable functioning of the infrastructure. It can be integrated into planning systems and sustainable development of urban transport and planning.

The method for classification of x-ray images, which is implemented in this article, improves the differential diagnosis of socially considerable diseases. The novelty of this method is that the input digital x-ray image is supplemented by a transparency mask which is found by image segmentation, and the classified sign vector is formed by pixels which aren't masked by the transparency mask. The original x-ray image is divided into segments to classify morphological structures with pathological formings. The classification of the selected segment is implemented by a modified convolutional neural network which uses pooling layers and layers of a fully-connected neural network. The proposed classifier allows dividing patients into two groups: patients without found pathology and patients with disorders of health condition. The found morphological pathological formings help clinicians to find the most promising way for prevention of the disease development at the patients, saving money and time.

Despite the great capabilities of controllers of the Simatic type, their library lacks a block for implementing the transfer functions necessary for programming complex control algorithms both in research by simulation and in industrial applications. This article discusses a method for software implementation of transfer functions of arbitrary order and delay in the Tİ A (Totally Integrated Automation) environment. The programs compiled in SCL and LAD languages and examples confirming the validity of the proposed method are given A program is presented that implements the solution of a difference equation in the SCL language, as well as programs for implementing the factorial and the number of combinations. These programs are designed as functions. The fourth program, compiled in the LAD language, is designed to build a transient process for a given transfer function in real time. The created software blocks allow developing software for the study of fairly complex regulatory systems by simulating and adapting to real industrial conditions without much difficulty.

The use of digital traces of social networks users has gained great popularity in various studies with the development of methods for analyzing big data. When processing data from social networks users, the problem of the incompleteness of the provided information arises (age, educational institution, year of admission/graduation are not specified). Users with such gaps do not fall into the field of view of the university as a result the number of potential applicants is significantly reduced. The aim of the project is to develop an algorithm for restoring information in a digital trace of a social networks user and its application to identify the group affiliation of schoolchildren whose digital trace contains incomplete information on the grade and place of study. The study was carried out on the data of schoolchildren from "The VKontakte" social network, corresponding to the ninth and eleventh grades, which were divided into four groups. The analysis of unique community subscriptions revealed significant differences in the age groups of schoolchildren. Then, based on gradient boosting, the algorithm that allows restoring missing information in the digital trace of schoolchildren was built. The optimization of the parameters of this algorithm based on numerical experiments allowed obtaining the precision of the order 0.6. The algorithm was used to identify groups of schoolchildren in 9^th and 11^th grades, in the digital trace of which there was incomplete information. The practical significance of the project is to expand the target audience of future university applicants and, as a result, the opportunity for the university to help them using career guidance measures in social networks to choose an educational program more consciously.

The article discusses the construction of a computer model to predict the problems occurrence in students in the educational process at the university. The following data sources of Altai State University were used for this purpose: "Admissions Office" (enrollees database) and "Dean's office" (database of students) for 2013-2018. These data were combined using developed SQL scripts. While analyzing the obtained combined data set, we had to face the difficulties typical for solving data analysis problems. Thus, it turned out that there are incomplete and inconsistent data or cases when one and the same entity is named differently, etc. In order to solve these problems, we wrote a script in the R programming language using regular expressions, the data were unified and standardized, and the missing data were restored using the information from other fields of the data set. Then we discarded the variables with the near-zero dispersion, which could not make a significant contribution to the developed predictive model. After that, the data set under study was divided into 2 parts: the 2013-2017 data were taken to build a predictive model with the use of the logistic regression algorithm, while the data for 2018 were used, in fact, to predict whether a particular student would be expelled. It should be mentioned that the 2013-2017 data were divided into the training and test samples in the proportion of 90% and 10% correspondingly. The test result of the computer model built in the R programming language showed satisfactory accuracy; the most significant factors affecting student expulsion were also identified. The paper substantiates the economic feasibility of using the developed computer model at the university.

The article considers the application of data mining methods to develop a diagnostic model for one of the most common and dangerous diabetes mellitus complications – diabetic polyneuropathy characterized by damage to peripheral nerve fibers. The article explores the possibility of diagnosing diabetic polyneuropathy with the use of machine learning methods. The data base of the study includes 3204 anonymized medical records of children and adolescents with type 1 diabetes residing in the territory of Altai krai. 1100 records hold data on diabetic polyneuropathy. Medical records contain different information: patient complaints, medical case history, test results. The attribute space is represented by 40 different indicators. In the course of the study, we considered the differences between the attribute values in two groups, built the attribute space ensuring the best classification quality. The article presents the results of applying various methods to transform the source data, evaluates the quality of the resulting model. The implementation of all the study phases was carried out with the use of the Python high-level programming language.

The subject of the study is the on-board guidance and navigation system for an autonomous landing of a space probe. The list of on-board equipment for safe landing of the spacecraft on the small bodies of the solar system (SBSS) is offered. The algorithm is proposed to combine all the on-board equipment into a single fault tolerance system. All the equipment is selected under the condition of the ability to identify failures at an early stage. The novelty of the method is in diversifying methods that are used in each stage of failure analysis. Such general method allows rejecting the results of some failure measurements from the further process thus preventing possible accident. The algorithm suggests two-stage control of the on-board systems that allows improving the fault tolerance. The first stage is based on the method of analysis of a number of double unequal measurements, but unlike the classical approach, it is assumed not to improve accuracy, but to search for errors. The second stage is based on the analysis of the parameters to control the internal equipment in order to predict failures.

Based on the aerosol model of IAP RAS, a methodology has been developed for determining the aerosol coefficient of asymmetry of scattered radiation for natural particles. The source of information is the calculation data for the brightness of the cloudless sky in solar almucantarat with different spectral transparency of the atmosphere and the albedo of the underlying surface. By solving the radiation transfer equation by the Monte Carlo method, the asymmetry coefficients of diffuse fluxes were calculated, including the effects of single and multiple scattering, as well as light reflection from the earth's surface. Tables of average values of the asymmetry coefficients are presented that assume the use of interpolation methods for calculating atmospheric parameters. A technique is proposed for determining the aerosol asymmetry coefficient from the results of observations of a similar integral coefficient, optical depth, and terrain albedo without using an apparatus of solving inverse problems. In this case, the brightness can be observed in any units, including directly the readings of the photometer. Software has been developed that implements this technique.

In terms of COVID-19 pandemic, the mechatronic system, essentially a smart window, supplemented with devices for interception and disinfection of drops and capsules with viruses and bacteria, both outside and inside. This allows preventing the ingress of infected aerosols into the room along with streams of air rising along the buildings and spreading inside it in the presence of infected people along with turbulent jets of air. With widespread use, the system helps to reduce the spread of infection, transmitted mainly by airborne droplets. The hardware for controlling the window system is performed on a board from the Arduino MEGA 2560 R3 ATMEGA16U2 family, two control boards with ten relays and ten sensor modules. Control program for the window system control circuit is written in the LabVIEW graphical programming environment (National Instrument USA).

As part of the project to create a comprehensive resource-saving technology for the associated production of nanostructure concentrates, the reliability of the software package "Automated control system for the technological process of obtaining MD1 and MD2 nanostructure concentrates" was evaluated in terms of providing thermal vortex enrichment. The calculation of the reliability of the system was performed to assess the level of reliability and quantitatively determine the reliability indicators for the implementation of the functions of ACS TO 2.12. The object to be calculated was identified, the goals and objectives of the calculation at this stage, the nomenclature and the required values of the calculated reliability indicators were determined, the calculation method was selected that is adequate to the features of the object, the goals of the calculation, the availability of the necessary information about the object and the source data for the calculation. The initial data for the calculation were obtained and pre-processed; the values of the reliability indicators of the object were calculated. From a comparison of the calculation results with the reference values of the integral safety level (SIL) in accordance with IEC 61508, it follows that the maximum safety level of the ACS TO 2.12 SIL 2, the system availability is 98.97%, and the system uptime is 2 years. The probability of a dangerous failure of the PAZ system is 1.31·10⁻⁴, which corresponds to a high value of the integral safety level (SIL 4).

This article discusses the development of two-level hierarchical control systems for complex technological processes. This area of research relates to the problems of creating robotic complexes as part of automation systems for managing continuous multi-stage processes according to economic criteria. For the synthesis of decentralized systems of optimal control of processes with a sequential structure, it is recommended to use the dynamic programming method, which allows providing optimal coordinating solutions and justify the setting of local tasks for managing the stages of the technological process, provided that the current states of the input products of these stages are accurately or approximately observed. For an n-stage technological process in conditions of complete information, the problem of a coordinating subsystem is written, the solutions of which do not change for a set of values of input variables of the process and the time period of constancy of external and internal perturbations. It is shown that the implementation of algorithms for controlling individual stages of the process can be performed on the basis of microprocessor technology. Estimates of control error were obtained using a simulation model of a process control system with specified parameters. The article considers the possibility of applying the dynamic programming method in the management of multi-stage technological processes in conditions of incomplete information.

This article presents the development of automatic clone detection for verification students programs - the Detector of Clones. The Levenshtein Distance is used for the initial assessment of the similarity of the two token sequences which is calculated by the Wagner-Fisher algorithm. Verification of two programs is carried out by the fingerprint method and by the winnowing method. To improve the results of plagiarism assessment, an additional calculation was added to the implementation of the winnowing method: the detector compares not only the labels themselves, but also the sequences near the matching labels. The detector of clones is formed for the cycle of disciplines Object Oriented Programming, Object Oriented Analysis and Design on the Moodle platform. These tools support C-like languages (C++ and C#). In general, the work of the detector undoubtedly made it possible to increase the consistency in verification of student programs.

The paper presents a neural network study of the data of wheat seed quality. It is established that the analysis of bioelectrical signals of wheat seeds based on a neural network can be used in practice for the solution of two problems - diagnostics of seed material quality and the evaluation of cleaning line quality (separation into fractions). The paper presents the results of initial data preparation, formation of a neural network, analysis of training data for two practical problems of classification. It was established using a neural network that there is a nonlinear dependence of the membrane potential maximum value and the signal rise time on the seed yield. The model makes it possible to predict yield in terms of the seed material quality. A nonlinear dependence of the maximum membrane potential, the signal rise time of wheat seeds and the seeds variety to one or another faction (speed of separation into the fractions in this example) was also established in this paper. Studies have shown that the seeds variety is an important informative feature for solving the problem of classifying seeds by fractions. Therefore, it is necessary to conduct additional studies with other wheat seeds varieties to apply this method in practice.

This article discusses the development of intelligent models based on the conceptual understanding of a dynamically complex environment. The method proposed in this work allows solving these problems based on a synthesis of the activity approach and situational analysis. As a result, the conceptual structure of the act of activity is realized. The combination of these structures leads to the construction of a decision matrix, which represents a knowledge base about a dynamically complex environment. An analysis of these interrelated aspects leads to the construction of four conceptual plans: the functional structure, processes, context and regularity. Conceptual plans make it possible to combine model ideas about the subject area, thereby simplifying the choice of intelligent modules for decision support systems. Recognition of the task of constructing conceptual structures as non-trivial, complex and time-consuming led to the idea of implementing the software system "Designer + Solver + Interpreter". The software toolkit allows not only visualization of conceptual structures and implementation of knowledge bases for intelligent models, but also the studies for completeness and adequacy.

As part of a series of works on the processing of aluminum and silicon waste products, including the project to create a comprehensive resource-saving technology for the production of nanostructure concentrates along the way, the algorithm of the automated system for controlling the technological process for producing concentrates of MD1 and MD2 nanostructures in part providing thermal vortex enrichment is described. Algorithms have been developed for the automated processing of incoming raw whole data into a real format in the parameter range, for controlling the three-position regulator (RO) with open/close commands with a built-in automatic step-by-step PI controller. The purpose and characteristics of the processes, the information used, the results of the solution, the decision algorithms, the requirements for the test example are described.

The characteristics of the software and hardware system for recording acoustic emission in a wide frequency range are given. This system is used in studies of structural and phase transformations of metals and alloys under complex thermo-mechanical loading. The software and hardware system is the author's development of the team and provides an affordable solution for recording and processing data in real time, which is a determining factor in the choice of technology for the study of structural-phase transformations of metals and alloys by method of acoustic emission. The requirements for acoustic emission technique differ slightly from the approaches common in the field of non-destructive testing. The hardware complex consists of a standard ADC with a sampling rate of at least 10 MHz, which provides spectrum registration in the range up to 1 MHz. The cascade of amplifiers are provides requirements for study by method of acoustic emission. The set includes a low-noise heater, an Arduino-based recording unit for related experimental parameters (temperature, mechanical stress, strain), and a personal computer. The software part of the system is a light scientific open source shell for conducting a physical experiment - the "dotScope", developed by the author's team. The program includes an extensible plugins system for working with various ADCs, plugins for real-time data processing, and plugins for post-processing.

This article presents options for implementing high-speed algorithms for controlling automatic manipulators operating as part of robotic complexes (RTCs). Software control systems for automatic manipulators with the use of noise-resistant coding algorithms are considered in the conditions of operation in production conditions, when there is instability in the supply of energy resources, the presence of sources of network interference, interference that violates the safe working conditions of radio-electronic equipment. Examples of implemented control algorithms with different software cycles are given, regarding into account the peculiarities of production. A comparative analysis is made with analogs that have similar technological characteristics.

The elements of polyhedral programming theory considering the extreme tasks with polyhedral both goal and limiting functions are presented. The authors discuss the application of polyhedral programming device for optimal control tasks by discrete dynamic objects with polyhedral performance criterions. The decision of two optimization tasks of discrete control processes is reduced. They are the control task by finite state and the task of terminal stabilization.

The hardware-software complex which allows carrying out defect detection in materials based on various aluminum alloys was developed using a transducer based on eddy current effects. The hardware-software complex included the developed software coded in C++. A digital displacement transducer operated by an Arduino microcontroller has been designed, which can automatically move the transducer over a test object. In order to test the system operability, a series of scans of plates made of duralumin and aluminum-magnesium alloys with knowingly existing internal defects in the form of cuts imitating the presence of cracks in the metal and located at depths from 1 to 5.5 mm was made. This paper provides information illustrating the correlations between the system response to a 700 Hz signal and the presence of internal material defects. The eddy-current transducer exciting winding signal frequency exerts significant influence on this process, and this has been also demonstrated in the study.

The transition of the railway industry from information management systems to systems with full management can be achieved by combining automated information systems integrated into production processes in the railway network. Russian Railways OAO acts as a driver for the development of modern technologies in the transport sector, aiming to increase efficiency in organizing the transportation process. Monitoring changes in customer needs, as well as focusing on increasing the value of services and products for consumers, including service quality improvement by digitalizing individual operations related to the cargo handling during loading, is becoming increasingly important. The introduction of the developed automated system for the preparation of technical specifications for the stowage and securing of cargo in rail cars and containers will increase production system organization quality in railway transport, as it will eliminate the incompetence, negligence and irresponsibility of workers associated with the handling, stowage and securing, reduce the time for preparing technical documentation, and improve the transport system operation quality. To achieve the stated goal, based on the studies, the author developed a computational decision-making procedure for the stowage and securing of cargo in the rail car, taking into account a possible two-coordinate shift. The procedure allows employees responsible for accepting cargo for transportation to assess the quality of the cargo securing according to the criterion of permissible shift at the initial stage of the transportation process. The developed automated system has many positive aspects. The security of the system significantly increases, the risk of errors is reduced, and the influence of the human factor is minimized. The complexity of the process of compiling a sketch of the stowage and securing of the cargo in the rail car loaded in accordance with the Technical Specifications is reduced. Most of the work is done by automated software, the cargo shipper has more time to control the loading process; time limits of various works and projects generally decrease.

The article presents the results of simulation of the operating modes of measuring transducers based on interconnected piezoresonators. The article discusses modulation options as a function of the measured effects of the parameters of equivalent electrical equivalent circuits of piezoresonators and coupling elements between them. The article describes the features of using coupled oscillations in systems with two degrees of freedom for constructing differential-type sensors with a frequency and amplitude output. The article gave examples of the practical implementation of measuring devices based on coupled oscillations of piezoresonators.

The paper discusses technologies for processing text-based medical data stored in the Microsoft Word text format. Processing such data is aimed at data mining the text for new, potentially useful knowledge that can later be used to study various diseases and to form a personalized approach to diagnosis and treatment. During the study, 3244 depersonalized medical records of children and adolescents in Altai Krai suffering from diabetes mellitus were processed. Information is stored in the records in both structured and unstructured forms. Most of the valuable data, such as the dynamics of the disease course, patient complaints, patient's life history, etc. are kept in natural language. The difficulty of processing text medical records is associated with a great number of abbreviations, synonyms and misprints, which makes it impossible to use a unified template. Therefore, the study is aimed at minimizing information losses while extracting knowledge by means of applying various text data mining methods. The practical outcome of this study is a database containing a large amount of valuable information on diabetes mellitus, various types of its clinical course and complications. The obtained data will be further used to build mining models for diagnosing and predicting the disease and its complications. To reach the goal of the research, we used the PostgreSQL DBMS and modern linguistically oriented software created within the framework of the Python programming language and its libraries: python-docx, natasha, Natural Language Toolkit (NLTK).

As a part of the development of a comprehensive resource-saving technology and the organization of high-tech production of nanostructures based on carbon and silicon dioxide to improve the properties of building and structural materials, the algorithms for the software package Automated Control System for the Technological Process for Obtaining Concentrates of MD1 and MD2 Nanostructures are described in part providing thermal vortex enrichment. Algorithms have been developed for controlling an analog value according to the PID control law, stopping the production line in emergency mode, and regenerating bag filters as they become clogged. The purpose and characteristics of the processes, the information used, the results of the solution, the decision algorithms and the requirements for the test example are described.