Sukhoi State Technical University of Gomel

The paper presents the results of analyzing the evolutionary sequence of development of agroindustrial cooperation concepts. The models of building cooperative­integrative relations in agroindustrial production at the national and regional levels corresponding to the individual stages are described, and examples of their practical implementation are given. Constructive transitions in the substantiation of goals, forms and directions of agroindustrial cooperation development are defined. Sectoral trends characterizing new formats of building cooperative ties have been identified. The dynamics is visua­ lized, phase transitions of the development vector are defined and regularities of formation of the conceptual basis of agroindustrial cooperation in the system of national and international documents of strategic planning and management are substantiated. The necessity of methodological study of coherent economic structures as a form of target synchronization of joint activities of subjects in a dyna­ mic external environment is shown.

Effective management of a water supply system amid urban infrastructure growth requires considering numerous factors that determine its technological and energy operational modes. Energy consumption in water intake structures can be optimized through adaptive activation of pumping stations, factoring in equipment timing and composition. A key aspect of implementing such measures is accurately forecasting water consumption dynamics. Most studies analyze the consequences of water consumption factors but overlook their potential for rapid acquisition in building predictive models or their systematization for use in water supply management systems. In contrast, this study aims to identify statistically significant factors that can be rapidly obtained and applied in machine learning models to forecast water consumption. It uses data on the water supply regime of Gomel, a major industrial center in Belarus with over 500,000 residents, from 2017 to 2023. Factors considered include air temperature, precipitation, and temporal parameters, such as hours of the day and months of the year, examining their influence on water consumption dynamics and energy costs within the system. The methodological framework employs correlation and regression analyses to assess relationships among factors, using smoothing (moving average), filtering, and truncation by temperature thresholds, ANOVA, and Tukey’s test to process data and evaluate differences among groups. Results indicate that temperatures above 25 °C increase water consumption by 15.8% and energy costs by 15.6%. In cold periods, temperature effects are minimal, but temporal factors significantly influence consumption patterns. Density analysis identified two stable clusters of hourly water consumption.

This paper explores the application of machine learning methods for recognizing automobile light signals to enhance smart traffic light systems. For vehicle detection in video footage, the Keras library was employed along with the RetinaNet neural network architecture [1]. The YOLOv8 architecture was used for identifying the status of vehicle headlights and taillights. Data collection, annotation, and model training were conducted using the Roboflow platform. The research resulted in trained model weights capable of recognizing the state of front and rear lights on various vehicle types under different weather conditions. The paper proposes an adaptation of the YOLOv8-based neural network model for recognizing traffic light signals, which can be utilized for both static recognition in photographs and in real-time or video applications.

Highlights What are the main findings? An IoT-based information system has been developed, integrating piezoelectric pressure sensors to collect pressure data in the water supply system, enabling real-time monitoring of the hydraulic network’s condition and using this data for model training. Various architectural parameters of the LSTM model have been investigated, including the number of layers, neurons, the use of Dropout layers, the impact of seasonal factors, and the history depth on prediction accuracy. What is the implication of the main finding? The information system allows for the integration of standard devices into cloud platforms for model training, accelerating the process of real-time prediction and simulation. The research results, demonstrating the optimal model architecture, can be used in the early stages of training, reducing computational costs during the integration of pressure sensors into information systems and speeding up the model training process necessary for pressure prediction in emergency situations. Abstract This paper investigates the application of recurrent neural networks, specifically Long Short-Term Memory (LSTM) models, for pressure forecasting in urban water supply systems. The objective of this study was to evaluate the effectiveness of LSTM models for pressure prediction tasks. To acquire real-time pressure data, an information system based on Internet of Things (IoT) technology using the MQTT protocol was proposed. The paper presents a data pre-processing algorithm for model training, as well as an analysis of the influence of various architectural parameters, such as the number of LSTM layers, the utilization of Dropout layers for regularization, and the number of neurons in Dense (fully connected) layers. The impact of seasonal factors, including month, day of the week, and time of day, on the pressure forecast quality was also investigated. The results obtained demonstrate that the optimal model consists of two LSTM layers, one Dropout layer, and one Dense layer. The incorporation of seasonal parameters improved prediction accuracy. The model training time increased significantly with the number of layers and neurons, but this did not always result in improved forecast accuracy. The results showed that the optimally tuned LSTM model can achieve high accuracy and outperform traditional methods such as the Holt–Winters model. This study confirms the effectiveness of using LSTM for forecasting in the water supply field and highlights the importance of pre-optimizing the model parameters to achieve the best forecasting results.

The article proposes a methodical approach to the typology of rural areas based on the combined use of the concepts of center­periphery and sustainable development. A list of criteria for differentiation and structuring of rural areas is substantiated. A description of the key characteristics of territories of different levels of peripherality is given, taking into account the spatial, economic, social and environmental features of their functioning. An algorithm of actions for the formation of classification groups of rural settlements is presented.

Form-factor analysis of pseudoscalar π±- and vector ρ±- mesons with zero transmitted momentum has been carried out in the model based on the point form of Poincaré-invariant quantum mechanics. The original method of model parameters’ calculations from leptonic decays π±→ℓ±νℓ± , τ±→ρ±ντ± using pseudoscalar density gπ± constant is proposed. The method is generalized in radiative decays ρ0→ℓ+ℓ- and ρ±→π±γ with the following anomalous magnetic moments calculation of constituent u- and d- quarks. It has been shown that the obtained parameters lead to the values of magnetic and quadrupole moment of ρ±- meson which are comparable with other models as well as hadronic transition ρ±→π±π0 observables. A comparative analysis of the obtained values of μu and μd quark magnetic moments has been carried out. It has been found that the proposed model gives numerical evaluations which are comparable to other approaches and models.

In the process of contact wear, pitting is formed, which destroys the surface of the part. Existing methods for assessing contact fatigue (GOST 25.501–78, R 50–54–30–87) reveal a stress level at which pitting does not occur. At the same time, there is no information about surface hardening, which is one of the main ways to increase contact fatigue. In this case, traditional approaches to the study of the wear mechanism do not make it possible to predict the operational evolution of the loaded surface of the part. The authors have developed a universal method for determining the contact fatigue of materials, providing opportunities for resource-efficient design of parts operating under the action of pulsating contact stresses.•Design and operating principle of the patented testing device. •Universal methodology for determining the contact fatigue of materials. •Our novel test method demonstrated a convergence of finite element modeling and real test in terms of crack formation in maximum stress zones.

The article considers the influence of climatic factors on energy and water consumption of the urban water supply system. The purpose of the study is to identify the relationships between outdoor air temperature, precipitation and load on the water supply system to substantiate the factors necessary for creating seasonal models of water consumption and increаsing the energy efficiency of water intakes. The objective of the scientific work was to test the hypothesis, according to which an increase in air temperature leads to an increase in water consumption and, as a consequence, to an increase in energy costs for the operation of pumping stations and water treatment systems. At the same time, it was assumed that precipitation would have the opposite effect, reducing water consumption during periods of intense rainfall. The work used correlation analysis to assess the strength and direction of the relationships between air temperature, precipitation and energy and water consumption parameters. Regression analysis was used to quantitatively assess the impact of climatic factors. The moving average method was used to smooth the data and reduce the spread of random fluctuations. Data filtering and cutting methods were also used, which made it possible to divide them by temperature thresholds and conduct separate studies for different ranges. The obtained results demonstrate that the growth of energy consumption is closely related to the increase in water demand, which increases with each degree of outside air temperature. This is explained by the expected increase in water consumption for irrigation and household needs during warm periods. Above 25 °C, the temperature factor determined 15.8 % of water consumption, which also coincided with the growth of this contribution to the electricity consumption of the system (15.6 %). However, when analyzing data in the area of negative temperatures, no obvious relationship was observed between temperature and water demand. At the same time, a correlation was found between temperature and electricity consumption, which is associated with additional costs for maintaining the water supply system in cold climates. Conclusions are made about the need for further study of additional variables, such as types of weekdays (working days, weekends, holidays), seasons of the year, as well as other socio-economic factors affecting water consumption and energy costs. The comprehensive results of the work can be used for planning the work of water utilities, managing energy resources and developing strategies to improve energy efficiency in water supply systems.

Highlights What are the main findings? A method for clustering urban water supply consumers based on their geographic location and water consumption levels has been developed, allowing for the identification of key areas with high water demand and consideration of spatial distribution characteristics on the map. The effectiveness of applying the agglomerative clustering method has been demonstrated, which, combined with the silhouette coefficient, allows for selecting the optimal data partition strategy and distributing the territorial division of consumers across service zones. What are the implications of the main findings? The proposed geospatial clustering method allows for planning the placement of pressure sensors, taking into account the distance of consumers from water sources, consumption centers, and their cluster membership, which creates a foundation for solving hydraulic modeling tasks. The results of the study are aimed at addressing the task of determining the magnitude and influence zones of pressures generated by water sources on the key points of the urban water supply system, in order to optimize the operation modes of pump stations. Abstract For large cities with developing infrastructures, optimising water supply systems plays a crucial role. However, without a clear understanding of the network structure and water consumption patterns, addressing these challenges becomes significantly more complex. This paper proposes a methodology for geospatial data analysis aimed at solving two key tasks. The first is the delineation of service zones for infrastructure objects to enhance system manageability. The second involves the development of an approach for the optimal placement of devices to collect and transmit hydraulic network parameters, ensuring their alignment with both water supply sources and serviced areas. The study focuses on data from the water supply network of a city with a population exceeding half a million people, where hierarchical clustering using Ward’s method was applied to analyse territorial distribution. Four territorial clusters were identified, each characterised by unique attributes reflecting consumer concentration and water consumption volumes. The cluster boundaries were compared with the existing service scheme of the system, confirming their alignment with real infrastructure. The quality of clustering was further evaluated using the silhouette coefficient, which validated the high accuracy and reliability of the chosen approach. The paper demonstrates the effectiveness of cluster boundary visualisation for assessing the uniform distribution of pressure sensors within the urban water supply network. The results of the study show that integrating geographic data with water consumption information not only facilitates effective infrastructure planning and resource allocation but also lays the foundation for the digitalization of the hydraulic network, a critical component of sustainable development in modern smart cities.

The development of the water supply system for small settlements involves the use of frequency converters and specialized control algorithms capable of maintaining the pressure level established in the network within certain limits. The implementation of one of the standard schemes involves decommissioning a water tower, which, on the one hand, allows reducing the cost of its maintenance, on the other hand, if the pump fails, the water tower provides a certain supply of water to the consumer, which increases the overall uptime. The paper considers the potential for increasing the energy efficiency of a water supply system when operating well pumps on a water tower through the use of frequency converters. The study has analyzed the operating conditions of more than 300 wells. This has made it possible to establish that most pumps have overestimated pressure values when lifting water into the tower (median excess of about 30 m). For the wells under study, optimization of the operating modes of the pumping units has revealed energy saving potential of up to 50 % by reducing excess pressure and up to 2.0 % due to a reduction in starting power at the moment of engine acceleration. An assessment of the energy saving potential based on similarity theory emphasizes that when the pump motor speed is reduced, it is important to take into account the reduction in its performance, which is a significant limitation in the design of automated control systems. The study results confirm the significant theoretical and practical potential of using frequency converters to improve the efficiency of water supply systems without the need to mothball water towers. The research provides a basis for further developments in the field of optimization and automation of water supply systems in order to achieve high energy efficiency.

Polycrystalline thin films of bismuth-strontium tantalum SryBi2+xTa2O9 with different molar ratio Sr:Bi:Ta were obtained by sol-gel method. The formation of a phase with a perovskite structure has been established. Phase transitions have been confirmed by dielectric spectroscopy. In the mode of polarization switching spectroscopy, remnant piezoelectric hysteresis loops were obtained, which confirms the ferroelectric nature of the synthesized SryBi2+xTa2O9 films.

The article presents the results of systematization, analysis and generalization of existing foreign experience in the field of definition (identification) of rural areas and their typology. Distinctive features of classifying areas as rural, typical for the countries of the European Union and Organization for Economic Cooperation and Development member states, are revealed. The content, possibilities and limiting factors of using methodological approaches to developing typologies of rural areas are established.

The theoretical and methodological apparatus of scientific approaches (economic, interdisciplinary) is analyzed in terms of revealing the general theoretical context of the phenomenon of cooperation (preconditions, mechanics of manifestation, effects). Conclusions are drawn about the development of scientific understanding of its functions and role. The prototypes of the models of cooperative relations are established, the chronological order of change is determined, their – content is revealed. The evolutionary stages of development of the theory of agrarian cooperation are substantiated. The peculiarities of modification of methodological models of analysis of cooperation in modern conditions of scientific search are determined, the synthesized description of the studied category is given.

The role of employment and the importance of the agrarian labor market in the sustainable development of rural areas are substantiated. The factors of effective employment of rural population are determined. A comprehensive analysis of the conditions, features and problems of employment in rural areas of the Gomel region was carried out. Current problems, features and trends in rural population employment of the region are identified.