During the research, a new prestressing system was developed for carbon fiber reinforced polymer plates to reinforce damaged steel beams. A parametric analysis was performed using finite element modeling. The results showed that satisfactory amplification efficiency can be achieved using the new pre-voltage system. The prestressed carbon fiber significantly increased the performance when bending beams at the elastic and elastic-plastic stages due to the use of high-strength carbon fiber plates. In addition, as the pre-voltage level increased, the amplification efficiency increased. A simple increase in the area or modulus of elasticity of the carbon fiber plate slightly improved the hardening efficiency, while the simultaneous application of prestressing clearly increases the hardening efficiency.

Keywords: reinforcement, steel beam, prestressing, new system, carbon fiber plate

This paper considered the problem of detection and classification of surface objects in low visibility conditions such as rain and fog. The focus is on the application of state-of-the-art deep learning algorithms, in particular the YOLO architecture , to improve detection accuracy and speed. The introduction to the problem includes a discussion of the limitations of visibility degradation, the change in shape and size of objects depending on the viewing angle, and the lack of training data. The paper also presents the use of discrete wavelet transform to improve image quality and increase the robustness of the systems to adverse conditions. Experimental results show that the proposed algorithm achieves high accuracy and speed, which makes it suitable for application in drone video monitoring systems.

Keywords: YOLO, wavelet transform, overwater objects, drones, low visibility condition, Fourier transforms, Haar

In the work describes the extreme filtering method and the author's approaches that allow adapting it to work in real time: frame-by-frame processing and the method with signal loading. Further, solutions are presented that can be used to implement the above on real devices. The first solution is to use the Multiprocessing library for the Python language. The second approach involves creating a client-server application and sending asynchronous POST requests to implement the frame-by-frame signal processing method. The third method is also associated with the development of a client-server application, but with the WebSocket protocol, not HTTP, as in the previous approach. Then, the results are presented, and conclusions are made about the suitability of the author's approaches and solutions for working on real devices. It is noted that the solution based on the use of the WebSocket protocol is of particular interest. This solution is suitable for both the frame-by-frame signal processing method and the method with value loading. It is also noted that all approaches proposed by the author are workable, which is confirmed by the time values ​​and the coincidence of the graphs.

Keywords: extreme filtering, frame-by-frame signal processing method, method with value loading, Multiprocessing, HTTP, WebSocket, REST, JSON, Python, microcontrollers, single-board computers

Diagnosing the technical condition of complex objects and planning repair-restoration work is a pressing challenge in today’s economy. This paper presents an approach to solving this problem using an integral indicator developed by the authors: the Modified Technical Condition Index. A conceptual model for a continuous (cyclical) monitoring system of this integral indicator’s levels is proposed. To assess an object’s technical condition, a linguistic scale is introduced, which generates recommendations for repair-restoration actions. Additionally, a resource-constrained planning system for repair-restoration work is developed.
The novelty of this work lies in the proposed methodology for creating an evaluative linguistic scale based on the integral indicator. This scale enables qualitative assessment of an object’s condition and provides actionable recommendations for repair-restoration efforts. The paper also addresses resource-constrained planning of repair-restoration work using the Modified Technical Condition Index for complex technical objects.

Keywords: express diagnostics, planning repair-restoration work, integral technical condition indicator, conceptual model of continuous (cyclical) monitoring, technical condition level assessment

The article proposes an approach to automate the detection of polishing defects in blades using luminescent testing (LUM). Instead of manual visual inspection, a system was developed that utilizes a deep learning neural network for defect segmentation on images and a robotic setup for precise positioning of the camera and the blank. This ensures the repeatability of the inspection. The relevance is driven by the industry's need for high-precision and reliable real-time quality control methods. The mathematical model of the process, software architecture, hardware components, and the data collection process for neural network training are described. The results of applying the system for defect detection are presented. The development optimizes polishing processes.

Keywords: industrial blade polishing, intelligent video analytics, robotic optical scheme, mathematical model of technological process, Lum control

The main maintenance of a diversification of production as activity of subjects of managing is considered. being shown in purchase of the operating enterprises, the organizations of the new enterprises, redistribution of investments in interests of the organization 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: software systems, visualization, data, graphic systems, parts, models, diagrams, drawings

The paper considers two machine learning methods for predicting the growth of watercut on an oil field with the calculation of basic convergence metrics.

Keywords: watercut, statistics, machine learning, time series, oil production

The article is devoted to the developed code designer for the Scilab environment, which is intended to automate the process of creating software modules. The program allows you to generate code for Scilab through an intuitive interface, providing users with tools for working with variables, loops, graphs, system analysis and user-defined functions. The constructor allows you to write programs for Scilab without knowledge of a programming language.

Keywords: Scilab, code designer, programming automation, code generation, visual programming

Linear feedback shift registers (LFSR) and the pseudo-random sequences of maximum length (m-sequences) generated by them have become widely used in solving problems of mathematical modeling, cryptography, radar and communications. The wide distribution is due to their special properties, such as correlation. An interesting, but rarely discussed in the scientific literature of recent years, property of these sequences is the possibility of forming quasi-orthogonal matrices on their basis.In this paper, was conducted a study of methods for generating quasi-orthogonal matrices based on pseudo-random sequences of maximum length (m-sequences). An analysis of the existing method based on the cyclic shift of the m-sequence and the addition of a border to the resulting cyclic matrix is carried out. Proposed an alternative method based on the relationship between pseudo-random sequences of maximum length and quasi-orthogonal Mersenne and Hadamard matrices, which allows generating cyclic quasi-orthogonal matrices of symmetric structure without a border. A comparative analysis of the correlation properties of the matrices obtained by both methods and the original m-sequences is performed. It is shown that the proposed method inherits the correlation properties of m-sequences, provides more efficient storage, and is potentially better suited for privacy problems.

Keywords: orthogonal matrices, quasi-orthogonal matrices, Hadamard matrices, m-sequences

The article considers the options for visual programming of information support means for software and information complexes for UAV operators training. The main criterion indicators for systematically organizing the set of components for reusing program code are identified. An example of an unmanned payload carrier in various representative forms of visualization is given. A comparison of the labor intensity of developing the specified software and information implementations for the same unmanned robotics object with their normative labor intensity is shown. The variants of content filling during the development of the same material part of the considered device for various aspects of training specialists in the management and operation of UAV are considered. The principle of systematization of components by means of ordering the complexity of presentation and softwarе implementation is shown.

Keywords: risk forecasting, information support, training of unmanned aircraft systems operators, labor intensity assessment

The paper presents a method for quantitative assessment of zigzag trajectories of vehicles, which allows to identify potentially dangerous behavior of drivers. The algorithm analyzes changes in direction between trajectory segments and includes data preprocessing steps: merging of closely spaced points and trajectory simplification using a modified Ramer-Douglas-Pecker algorithm. Experiments on a balanced data set (20 trajectories) confirmed the effectiveness of the method: accuracy - 0.8, completeness - 1.0, F1-measure - 0.833. The developed approach can be applied in traffic monitoring, accident prevention and hazardous driving detection systems. Further research is aimed at improving the accuracy and adapting the method to real-world conditions.

Keywords: trajectory, trajectory analysis, zigzag, trajectory simplification, Ramer-Douglas-Pecker algorithm, yolo, object detection

The article deals with the principles of creating software used as part of sensing systems for restoring the visibility of the gas smoke protection service link in a smoke-filled environment during rescue operations. The architectural part of the device and the description of algorithms of the device operation are described. Attention is paid to the methods of forming a digital model of obstacle heights and visualization of the spatial situation. Approaches to filtering of erroneous sensor values and selection of significant contours of objects, processing of data from ultrasonic grating, infrared sensors, as well as temperature and humidity sensors are given. The role of the device in providing accurate navigation, reducing the time to search for the fire center and improving the overall safety of the gas smoke protection service unit when working in a smoky environment is emphasized.

Keywords: smoke protection service, smoke-filled environment, sensing device, algorithms, software, firefighting, reconnaissance, modeling, navigation, sensor data

The article explores the implementation of digital and mathematical technologies in decision support systems (DSS) aimed at enhancing the efficiency of livestock enterprises. In the context of digital transformation and increasing uncertainty in agriculture, the authors emphasize the importance of intelligent DSS capable of processing large datasets and supporting rapid, evidence-based decision-making. The purpose of the study is to identify effective technological and methodological approaches for optimizing livestock management, particularly in the area of animal feeding. Methods include the use of mathematical models, predictive algorithms, automated control systems, and big data analytics. The proposed DSS architecture enables real-time monitoring, adaptive ration formulation, and integration of physiological, environmental, and economic data. The paper provides practical examples of successful DSS applications, such as automated milking systems and health monitoring technologies, and analyzes their impact on productivity and cost reduction. A set of methodological recommendations is formulated to enhance management efficiency, including modular system design, staff training, and integration of IoT and AI technologies. The article concludes that intelligent DSS not only reduce feeding costs but also improve animal health, optimize resource use, and support sustainable agricultural practices. The results are of practical significance for researchers, developers, and farm managers aiming to implement data-driven solutions in livestock production.

Keywords: diversification of management, production diversification, financial and economic purposes of a diversification, technological purposes of ensuring flexibility of production

A class of mathematical methods for code channel division has been developed based on the use of pairs of orthogonal encoding and decoding matrices, the components of which are polynomials and integers. The principles of constructing schemes for implementing code channel combining on the transmitting side and arithmetic code channel division on the receiving side of the communication system and examples of such schemes are presented. The proposed approach will significantly simplify the design of encoding and decoding devices used in space and satellite communication systems.

Keywords: telecommunications systems, telecommunications devices, multiplexing, code division of channels, matrix analysis, encoding matrices, synthesis method, orthogonal matrices, integers

The article discusses a mathematical model of the production application distribution process on an aggregator platform. A formal approach based on a finite state machine and Petri nets is proposed to describe the states of orders, their transitions and constraints. A comprehensive model has been developed that takes into account the criteria for selecting a contractor, selecting equipment, and analyzing the production process, taking into account time, cost, and resource availability. The presented approaches ensure accuracy and efficiency in order management on digital production platforms.

Keywords: mathematical modeling, finite state machine, Petri net, digital production, service aggregator, choice of contractor

This work is devoted to describing the development and integration of two key subsystems of an insect-like six-legged robot: a gait control module and a computer vision system for autonomous navigation. It examines architectural solutions, algorithmic foundations, and the practical implementation of components that ensure stable movement and intelligent interaction of the robot with its surroundings.

Keywords: insect-like robot, gait control module, computer vision, autonomous navigation, ROS2, SLAM, RTABMap, NAV2, OctoMap, tripod gait, Raspberry Pi, LiDAR

The article discusses approaches to the systematic analysis of historical data collected from water treatment facilities. By using tools from mathematical statistics, machine learning methods, and visual analysis techniques, the article proposes a formalized approach to assessing the efficiency of water treatment equipment. This approach makes it possible to identify hidden patterns in the data, build robust models of interdependencies, and develop recommendations for optimizing the technological process.

Keywords: water treatment, telemetry data, time series analysis, machine learning, equipment efficiency

The article discusses a methodology for predicting global horizontal radiation for the day ahead, based on the concept of characteristic days – typical daily profiles of global horizontal insolation. The method is aimed at use in the absence of operational meteorological information and is intended as an alternative (backup) method of short-term forecasting in autonomous energy systems. As a test case, data from the Murino station (Khanty-Mansiysk Autonomous Okrug), obtained from the PVGIS service based on ERA5 reanalysis, was used. The average and median characteristic days for each month are constructed and the accuracy of forecasts using the RMSE, MAE, MdAE and R2 metrics is compared. It is shown that median profiles provide more stable results in conditions of increased weather variability. The method can be used for approximate planning of photovoltaic installations in remote and northern regions with limited access to meteorological data.

Keywords: solar radiation, global horizontal insolation, ERA5, statistical forecasting methods, forecasting in energy systems, forecasting horizon, forecasting for the day ahead, methods for constructing characteristic days, average and median profiles

A method is proposed for cascading connection of encoding and decoding devices to implement code division of channels. It is shown that by increasing the number of cascading levels, their implementation is significantly simplified and the number of operations performed is reduced. In this case, as many pairs of subscribers can simultaneously exchange information, what is the minimum order of the encoding and decoding devices in the system. The proposed approach will significantly simplify the design of encoding and decoding devices used in space and satellite communication systems.

Keywords: telecommunications systems, telecommunications devices, multiplexing, code division of channels, orthogonal matrices, integers, cascaded connection

In this paper, a star sensor tracking method without a star library based on the angular distance chain algorithm is proposed to solve the problem that traditional star sensors rely on a fixed star library and need to be configured to work with multiple units in the tracking mode. This method achieves star map matching by dynamically generating angular distance chains, avoiding the dependence on the global star library. Experiments show that the recognition time of the algorithm in the tracking mode is reduced to milliseconds, and the maximum pose determination error is no more than 0.035°, which proves its effectiveness and reliability. The study provides key technical support for the development of low-cost and lightweight star sensors that are suitable for scenarios such as deep space exploration and near-Earth satellite clusters.

Keywords: angular distance chain algorithm, star sensor without star library, star map recognition, tracking mode, orientation, dynamic matching, deep space exploration

Regression analysis based on the use of statistical data and their processing by special methods is an effective method of researching and forecasting the number of employees of structural units. In this paper, based on statistical information on 81 regional offices of the Social Fund of Russia, a regression analysis of the staffing of individual information protection divisions was carried out taking into account the total area and population of the regions. It is shown that a number of subjects are understaffed and some of them, on the contrary, are overstaffed.

Keywords: information protection, regression model, adequacy criteria, forecasting, staffing analysis, information protection units

The paper develops an algorithm for constructing an optimal lagged filtration operator for an L-Markov process. The explicit formula of the filtration operator is obtained on the basis of methods for calculating stochastic integrals and the theory of analytical functions of a complex variable using spectral analysis and the theory of L-Markov processes. An interesting example of an optimal lagged filtration operator for an L-Markov process is considered, which can be used for modeling and controlling complex stochastic systems. It is shown that this operator is represented as a linear combination of the values of the received signal and an integral with an exponentially decaying function.

Keywords: random process, L-Markov process, noise, lag filtering, spectral characteristic, filtering operator

The effectiveness of advanced pavement defect detection algorithms is considered depending on the data collection devices used, such as cameras, GPR, LiDAR and IMU sensors installed in smartphones. Rational use of these hardware and software tools will allow utilities to identify and eliminate road surface defects in a timely manner, thereby improving road safety.

Keywords: transportation sector, pavement defects, mobile road laboratories, neural network algorithms, computer vision

The article considers the issues of developing a database of wooden architecture objects in Karelia. The database includes 1009 attributed photographs obtained as part of the comprehensive expedition of the Ministry of Culture of Karelia in 1979-1980 and the comprehensive expedition to Syamozerye in 2000-2001. The expedition research was carried out by specialists and students of Petrozavodsk State University under the supervision of Academician Vyacheslav Petrovich Orfinsky. The database was developed in the MySQL database management system. The database scheme is provided, the tables are described, and an example of a photograph with attributes is presented. The database allows storing and editing materials from historical and architectural expeditions and research by employees of Petrozavodsk State University, as well as searching for photographs of wooden architecture objects in Karelia by various criteria, including date, location, type of object, and author.

Keywords: wooden architecture, database, expeditions, MySQL DBMS, photographs of wooden architecture objects

A Simulink model is considered that allows calculating transient processes of objects described using a transient function for any type of input action. An algorithm for the operation of the S-function that performs calculations using the Duhamel integral is described. It is shown that due to the features of the S-function, it can store the values of the previous step of the Simulink model calculation. This allows the input signal to be decomposed into step components and the time of occurrence of each step and its value to be stored. For each step of the input signal increment, the S-function calculates the response by scaling the transient response. Then, at each step of the calculation, the sum of such reactions is found. The S-function provides a procedure for freeing memory when the end point of the transient response is reached at each step. Thus, the amount of memory required for the calculation does not increase above a certain limit, and, in general, does not depend on the length of the model time. For calculations, the S-function uses matrix operations and does not use cycles. Due to this, the speed of model calculation is quite high. The article presents the results of calculations. Recommendations are given for setting the parameters of the model. A conclusion is formulated on the possibility of using the model for calculating dynamic modes.

Keywords: simulation modeling, Simulink, step response, step function, S-function, Duhamel integral.