Bar structures are widespread in construction due to their economy, freedom of design shapes and sizes. As a result, automation of design and calculation of such structures is an urgent task. As part of the study, the task of developing a software module that generates a map of optimal cutting of rolled metal based on the results of calculations of rod structures has been implemented. The algorithm under consideration takes into account such features of the cutting optimization problem as taking into account the width of the blade, the possibility of using half the size of the rolled product, support for optimization of several sections, and welding of parts in case the length of the workpiece is exceeded. The software module is developed using JavaScript and C# languages. The ability to automatically generate cutting maps based on the results of optimization of rod structures increases the efficiency of designing building structures.

Keywords: Design in construction, bar structure, computing system, web development, design in construction, rod structure, computer system, web development, optimal cutting, rolled metal, cutting map

A method for recording holograms using digital cameras with high spatial resolution is considered. To register holograms obtained in optical setups with an inclined reference beam, a high resolution of registration systems is required. To do this, it is necessary to use media with a resolution of 2000-4000 lines per mm. The use of photographic plates requires a fairly long exposure and development time, which is usually done separately from the optical setup. In the case of holographic interferometry systems, it is necessary to provide for mounting the hologram back into the optical setup with sufficiently high accuracy. Therefore, digital holography methods have been developed to record holograms on photomatrices with limited resolution. These methods are based on the use of optical schemes at small angles (less than 5 degrees) between interfering beams. Recently, sensors with a single element size of 1.33 µm and 0.56 µm have appeared. This resolution makes it possible to return to registration schemes with angles between interfering beams of 30-60 degrees. This allows us to hope for the revival of holographic methods and methods of holographic interferometry at the modern level without the use of intermediate recording media.

Keywords: digital holography, high spatial resolution photo matrix, tilted reference beam holography, Fourier transform

This paper considers the problem of removing noise from an image based on the discrete cosine transform (DCT) algorithm. Despite its simplicity, the algorithm is still popular in image conversion. However, recently there has been a strong development of convolutional neural networks, leaving behind “traditional” signal processing methods. In this paper, we study image denoising using DCT and convolutional neural networks and creating an interpretable convolutional neural network to obtain accurate data. The basis was the Python programming language and the library for working with neural networks – PyTorch. Based on this, a neural network model was trained on The Berkeley Segmentation Dataset. Experiments have shown that the trained neural network shows results comparable to traditional image denoising algorithms.

Keywords: noise reduction, convolutional neural network, discrete cosine transform, machine learning, signal processing, Canny operator

This paper presents the process of developing an algorithm that is able to extract style and content from two different images and create a new image, preserving the content structure of one image and simultaneously applying the stylistic characteristics of the other image. This algorithm is able to adapt the style of one image to the content of the other image, creating unique artworks.

Keywords: neural networks, style transfer, image, machine learning, algorithm, dataset, software

The article proposes a general formalized model of the task of processing and extracting potential key skills from job descriptions to determine the relevance of training areas and possible areas of employment for graduates. The formalized model is used in the software implementation of the job clustering module based on the obtained sets of key skills within the framework of a comprehensive toolkit for remote career guidance.

Keywords: vacancies, demand for training areas, career guidance, digitalization of career guidance, formalized model, clustering, professions, key skills

This paper discusses statistical methods, as well as machine learning methods for choosing the optimal way to establish authorship for a passage of a work. The authors create a dataset from the passages of the corresponding authors, create a set of numerical features corresponding to each passage and apply various approaches to analyze authorship, such as correlation, similarity, t-test. An attempt is made to find the optimal method for the output layer of a graph convolutional neural network used for data preprocessing. The GCN neural network is being trained.

Keywords: t-test, cosine similarity, correlation, graph convolutional neural networks, natural language analysis

A Simulink model of a lightweight aircraft is being studied as part of the Aerospace Blockset package, including a system model of the aircraft, an environmental model, a model of pilot influences, and a visualization block. The structure of the flight model is considered and models of the effects of the environment and wind are disclosed in detail, consisting of blocks of physical terrain features, wind models and an atmospheric model, a gravity model, each of which is set to an altitude. The Wind Shear Model block calculates the amount of wind shear as a function of altitude and measured speed wind. The Discrete Wind Gust Model block determines the resulting wind speed as a function of the distance traveled, the amplitude and length of the gust. The turbulence equations comply with the MIL-F-8785C specification, which describes turbulence as a random process determined by velocity spectra. Simulation results are presented that reflect changes in the trajectory of movement under various wind influences specified in the wind speed gradient block.

Keywords: modeling, airplane flight, Simulink, Aerospace Blockset, crosswind, turbulence, turbulence equations, gravity model, motion trajectory

One of the causes of local overheating of submersible electric motor caused by the presence of a significant variation of electromagnetic parameters of rotor packages (RP) in the assembly of submersible electric motor is investigated in this paper. Due to the presence in the assembly of RPs with an active resistance much lower than the average resistance of the assembly, the electrical losses in RPs with resistance higher than the average increase, respectively, their heat generation increases. With the help of statistical analysis methods, the distribution of electromagnetic parameters as a two-dimensional random variable was investigated, the "convolution" of the two-dimensional distribution law was constructed. The analysis of the "convolution" of the two-dimensional law of distribution of electromagnetic parameters of the RP showed that there is a high probability of a significant scatter of parameters of the RP in the assembly.

Keywords: submersible electrical motor, rotor package, statistical analysis, local overheating, interrepair period

It is impossible to imagine the present time without software. Huge flows of information pass through computer computing systems. It is absolutely impossible to process unstructured, endlessly incoming data, so it is necessary to identify specific tasks and prepare information for processing. One such action is deduplication. This article discusses possible optimizations for the method of removing duplicates using databases.

Keywords: deduplication, database, field, string, text data, query, software, unstructured data

Reinforced concrete structures must have sufficient reliability throughout their entire service life. In problems related to predicting service life based on an assessment of the technical condition, reliability can be considered as the probability of failure-free operation of structures, which consists in the ability to perform the required functions under given conditions during the design life. One of the methods for solving this kind of problem is statistical methods. The beam reliability calculation was carried out. It was further assumed that the beam was subject to degradation. As a result, a graph was constructed of the dependence of reliability on the depth of corrosion penetration into the compressed concrete zone. This graph also shows how the category of the technical condition of the beam changes over time.

Keywords: reinforced concrete structure, bendable structure, prediction, service life, reliability, technical condition, degradation impact

The paper examines current issues of modeling and forecasting market parameters for transport companies providing services for the transportation of industrial enterprises’ good, such as cost, time, speed and volumes of delivery of finished products to consumers, and also assesses the potential capabilities of transport companies to provide the required quantity and quality of transport and logistics services. The aim of the study is to determine the area of reliable forecasts of transportation indicators for each interval value of the cargo delivery shoulder, taking into account the company’s market share. Modeling of the time parameters of cargo transportation was carried out based on road transportation conditions and the time of year. When implementing modeling procedures, the required statistical basis for parameters of travel time and distance on the route was formed on the basis of data from specialized applications for analyzing indicators of transport and logistics services of freight vehicles. A family of forecast curves was obtained for various variants of forecast models of speed and travel time, as well as interval values of delivery lengths for the initial set of transport and logistics companies. and development of new production on available floor spaces. The most important organizational economic targets of a diversification of management are presented by innovative activity of the industrial enterprise.

Keywords: statistical forecasting, transportation efficiency, benchmark models, tariffs for cargo transportation, piecewise linear approximation, areas of reliable forecasts, cargo transportation parameters, benchmark analysis, transport company market

This article explores various architectures of neural networks in order to create models in the field of agriculture, with an emphasis on their use in livestock farms. The paper describes the architecture of Kolmogorov-Arnold networks, considers the stages of data collection and preliminary preparation, the learning process of neural networks, as well as their implementation. As a result, models were developed using Kolmogorov-Arnold networks and a multilayer perceptron. The study compared the effectiveness of the proposed architectures. The experiment demonstrates that Kolmogorov-Arnold networks have higher accuracy in predictions, which makes them a promising tool for forecasting. The developed model has been integrated into the livestock information system being developed to predict the growth, health and other indicators of animals, allowing for more accurate management of the growing process.

Keywords: precision animal husbandry, Kolmogorov-Arnold network, modeling, neural network, monitoring, cultivation, data modeling, forecasting

This article presents the results of theoretical research in the field of methods for determining the forces arising in the traction return ropes of the balloon system used in transport, cargo and construction works. The emphasis is placed on the accuracy of the swivel positioning when exposed to a wind flow on the balloon. Theoretical calculations of the main parameters are given, such as: high-speed head, resultant lifting force, rope span, rope force, rope deflection, swivel movement and others. A technique is proposed that allows for a relatively simple and rapid calculation of rope forces in the process of performing cargo operations by an aerostat crane on a construction and installation site.

Keywords: balloon system, balloon crane, traction and return ropes, rope forces, drag, aerial construction and installation work, swivel

The work outlines the concept of “post-interpretation” of images and for its algorithmic implementation a model of a post-recognition interpreter is proposed. The recognition results of the initial images entering the recognition system are considered as post-images, and an artificial neural network is used as a post-recognizer. To assess the effectiveness of using the model, it is proposed to use the “expediency criterion” and numerical examples are considered to illustrate the features of its use in systems for recognizing and interpreting images with high risks. Data from preliminary results of experimental testing of a model for recognizing speech commands as part of an interactive operator's manual for performing various tasks and an assessment of its effectiveness are presented.

Keywords: intelligent data processing system, image interpretation, recognition reliability, decision-making criterion, artificial neural network

The development of business analytics, decision-making and resource planning systems is one of the most important components of almost any enterprise. In these matters, enterprises and production facilities of the penitentiary system are no exception. The paper examines the problem of the relationship between existing databases and statistical reporting forms of the production, economic and labor sectors of the penitentiary system. It has been established that indirectly interrelated parameters are quite difficult to compare due to different data recording systems, as well as approved statistical forms. One of the first steps in solving this problem could be the introduction of a generalized data indexing system. The paper discusses data indexing systems, the construction of their hierarchical structures, as well as the possibility of practical application using SQL. Examples of implementation using ORM technology and the Python language are considered.

Keywords: databases, indexing, ORM, SQL, Python, manufacturing sector, economic indicators, penitentiary system

The article discusses standard models of titanium dioxide-based memristors. A memristor is similar to a memory resistor and demonstrates a nonlinear resistance characteristic in which the charge parameter is a state variable. They can be used to create new types of electronic devices with high energy efficiency and performance, as well as to create machines that can learn and adapt to changing environmental conditions and in many practical applications: data storage memory (binary and multilevel), switches in logical electronic circuits, plastic components in neuromorphic artificial systems intelligence based on nanoelectronic components. It has been shown that when voltage is applied to charged ions, they begin to drift, and the boundary between the two regions shifts. When a sinusoidal alternating voltage of a given frequency is applied to the memristor, the shape of the volt-ampere characteristic (VAC) resembles a Lissajous diagram centered at the origin.

Keywords: memristor, model, voltage characteristic, nonlinearity

The article is devoted to the analysis of the UES of the South, which is part of the unified energy system of Russia (UES of Russia). An assessment of the change in the installed capacity of the power system over a period of 10 years and the causes that caused it has been made. A comparative analysis of changes in the structure of the installed capacity of the UES of the South by types of power plants at the beginning and end of the period under review is presented. Information on the largest commissioned generating facilities of the energy system, including solar and wind power plants, is reflected.

Keywords: energy system, power plants, installed capacity, structure, transmission lines, electrical substations, solar power plant, wind power plant.

The article studies the possibility of using the continuous form of the maximum consistency method when constructing regression models to calculate the forecast values of the air transport passenger turnover indicator in the Russian Federation. The method under study is compared with classical methods of regression analysis - least squares and moduli. To assess the predictive properties of the methods, the average relative forecast error and the continuous form of the criterion for the consistency of behavior between the calculated and actual values of the dependent variable are used. As a result of the analysis, a conclusion was made about the possibility of using the method under study to solve forecast problems.

Keywords: least squares method, continuous form of the maximum consistency method, modeling, passenger turnover, air transport, adequacy criteria

The article examines a new class of IT infrastructure monitoring systems that has been actively emerging in the last decade, the key feature of which is the widespread use of methods and techniques for working with big data. Depending on the market positioning, the systems under study are known under such names as AIOps, observability platform, all-in-one monitoring, umbrella monitoring. In their review of existing foreign and domestic commercial solutions, the authors focus on the use of big data methods in them. Based on the review, a classification of such products is proposed, which makes it possible to streamline the existing diversity and select the most suitable system for the tasks facing the organization in the field of monitoring an increasingly complex IT infrastructure. The relevance of the study is due to the lack of classification of the objects under study due to their relative novelty and pronounced practical nature.

Keywords: monitoring system, IT infrastructure, observability platform, AIOps, big data, machine learning

The work is aimed at developing and testing an algorithm for choosing the location of a new cargo storage warehouse, taking into account stochastic flows of cargo supplies to the warehouse and to consumers from the warehouse. When choosing a warehouse location, the costs that accompany the activities of a logistics company related to the organization of warehousing in the selected location, with the maintenance of the warehouse, storage of cargo, delivery of cargo from suppliers to the warehouse and from the warehouse to consumers are taken into account. The paper proposes an algorithm for solving the problem of choosing the location of a cargo storage warehouse, taking into account the forecast of the dynamics of cargo deliveries to the warehouse and to consumers from the warehouse. A mathematical toolkit is described that allows estimating the dynamics of costs for the organization and operation of a warehouse in conditions of non-stationary flows of incoming and outgoing cargo from a warehouse based on the application of the statistical modeling method. The approbation was carried out. The proposed toolkit has a novelty in terms of accounting for non-stationary flows of incoming and outgoing cargo to the warehouse and real transport routes when choosing the location of the warehouse.

Keywords: warehouse location, dynamics of warehouse costs, statistical modeling, mathematical model, logistics

Roads occupy an important place in the life of almost every person. The quality of the coating is the most significant characteristic of the roadway. To evaluate it, there are many systems, among which there are those that analyze the road surface using video information streams. In turn, the video is divided into frames, and the images are used to directly assess the road quality. Splitting video into frames in such systems works based on special software tools. To understand how effective a particular software is, a detailed analysis is needed. In this article, OpenCV, MoviePy and FFMpeg are selected as software tools for analysis. The research material is a two-minute video of the road surface with a frame rate 29.97 frames/s and mp4 format. The average time to get one frame from a video is used as an efficiency indicator. For each of the three software tools, 5 different experiments were conducted in which the frame size in pixels was consistently increased by 2 times: 40000, 80000, 160000, 320000, 640000. Each program has a linear dependence of O(n) average frame retrieving time on resolution, however, FFMpeg has the lowest absolute time indicators, as well as the lowest growth rate of the function, therefore it is the most effective tool compared to the others (OpenCV, MoviePy).

Keywords: comparison, analysis, effectiveness, software tool, library, program, video splitting, frame size, resolution, road surface

To date, the penitentiary system of the Russian Federation has collected quite extensive databases for the production sector. The collected data is a time series. However, when studying the mutual distributions of parameters, a number of problems arise, the main one of which is that a different data accounting system is maintained for different parameters: in some cases, data accounting is cumulative throughout the year, in other cases, actual values are taken into account (in other words, some time series are trending, while others are seasonal (cyclical)). Data accounting periods also differ: monthly, quarterly, or per year. Thus, at first glance, the related parameters are almost impossible to compare. The paper proposes a number of algorithms that would solve this problem. The aim of the work was to develop new algorithms that allow comparing trend and seasonal time series using the example of the industrial sector of the penitentiary system. The objectives of the study can be designated as: classification of parameters that are taken into account as seasonal and as trend time series; development of algorithms for their comparison; study of the applicability of the results obtained.

Keywords: algorithm, data processing, python, time series, penitentiary system, manufacturing sector.

In the modern world, it is increasingly necessary to process geographical information in a variety of forms. This paper discusses the concept of «tile», its purpose, features, as well as the process of retiling, which is a method of creating and updating tiles. This technology helps to increase the efficiency of modern cartographic services, reducing the loading time of maps. The main stages of the development of a microservice implementing the retiling logic are presented sequentially. The main data provider is the OpenStreetMap (OSM) open source project. The spatial data set is a core OSM product and contains up-to-date geographic data and information from around the world. The technology stack is based on the Python language, to which specialized modules for working with tiles are added, as well as a library for implementing a simple and high-quality API.

Keywords: Python, tile, retiling, OpenStreetMap, microservice, Flask-RESTX, mercantile

The article discusses one of the possible ways to transfer (migrate) variable services from proprietary to an available free and popular solution, as well as ways to improve the structure and eliminate problem areas.

Keywords: variables, configuration, service, Octopus, Git, Vault, migration

The quality of training of incompletely connected neural networks based on decision's roots is discussed. Using the example of limited data on patients with clinically diagnosed Alzheimer's disease and conditionally healthy patients, a decision's root and the corresponding neural network structure are found by preprocessing the data. The results of training an incompletely connected artificial neural network of this type are demonstrated for the first time. The results of training of this type of neural network allowed us to find a neural network with an acceptable level of accuracy for the practical application of the obtained neural network to support medical decision making - in the considered example for the diagnosis of Alzheimer's disease.

Keywords: neural networks, complex assessment mechanisms; decision roots, criteria trees, convolution matrices, data preprocessing