This article examines the issue of increasing the performance and scalability of transactional systems using the example of a sharded blockchain architecture. Particular attention is paid to the use of a search query—based approach, a model in which the user's transactional intentions are processed asynchronously and aggregatively. This allows you to significantly reduce the load on the network and achieve high throughput without compromising the user experience. The proposed architecture is based on fully controlled smart accounts, embedded wallets, and third-party processing of user search queries through a specialized module. As a result, scalability is achieved that meets the requirements of high-frequency trading and automated decentralized applications. Key performance metrics and application scenarios outside the financial sector are presented.

Keywords: blockchain, distributed ledger, transactional systems, distributed systems

Assessing the technical condition of equipment is an important task for ensuring operational strategy and planning maintenance work at an enterprise. One approach to evaluating equipment condition is the use of a well-known indicator called the 'technical condition index,' the calculation methodology for which has been approved by the Ministry of Energy of the Russian Federation. This methodology also proposes a scale for assessing the level of equipment technical condition. However, the question of the threshold or critical value of this indicator, which can determine the equipment's unsuitability for further operation, remains unresolved. This paper proposes a methodology for determining the threshold value of a modified technical condition index based on the allowable probability of failure-free operation of equipment using statistical methods. The novelty of the work lies in the proposed methodology for determining the threshold value of a modified technical condition index, developed by the author, which uses objective data for evaluation, unlike the subjective assessments of experts in existing methodologies. The proposed method was tested on a set of statistical data on the degradation of turbofan engines from NASA.

Keywords: technical condition index, modified technical condition index, threshold value, probability of equipment failure-free operation, complex technical object

The article proposes a scheme for the interaction of nodes in a secure data transmission network based on broadband wireless access equipment (BWAE). The variants of design and technological implementation of the BWAE are described, that is BWAE 7 equipment (with a seven-element antenna array) and BWAE 1 equipment (with one antenna device). For each option the composition of functionally complete devices and nodes is presented, the technical characteristics of the equipment are indicated. The functional description of components of the BWAE 7 and BWAE 1 equipment is provided.

Keywords: telecommunication equipment, information and monitoring network, wireless broadband access, data transmission, secure network

he article examines the configuration options for onboard communication equipment. Modeling and evaluation of antenna placement options onboard the unmanned aerial vehicle of helicopter type (UAV HT) are carried out taking into account the influence of design elements and payload on the antenna pattern, summary results of modeling the radiation patterns and analysis of losses due to the influence of design elements of the UAV HT with different antenna placements are presented. The loss budget is calculated for different combinations of ground and onboard equipment taking into account different ranges with a maximum altitude difference. Options for implementing a repeater based on the UAV HT are proposed.

Keywords: control system, unmanned repeater, onboard communication equipment, control channel, receiving and transmitting path

The combination of systems analysis and long-term planning is a crucial factor for ensuring sustainable development and enhancing the competitiveness of enterprises. In this context, the use of the Event Tree Analysis method plays a key role in assessing the achievement of strategic goals, tasks, and identifying potential risks. This study focuses on the development and application of an event tree to analyze various aspects of system operations, including goal setting, strategy development, and task execution. The application of the ETA method not only allows for modeling possible event scenarios but also enables the development of risk mitigation measures, contributing to long-term sustainability and successful system functioning.

Keywords: event tree, system analysis, strategic planning, risk management, threat minimization, sustainable development, enterprise competitiveness, quantitative analysis, qualitative analysis, dependent events, conditional probabilities, protective mechanisms

The issue of developing a prototype for an unmanned aerial vehicle (UAV) and creating a control system based on a computer-aided design (CAD) model as part of a project for inspecting construction sites is under consideration. Special attention has been paid to constructing a computer model of a quadcopter. Based on existing methods, energy calculations have been performed and a process for synthesizing controllers in orientation and positioning control circuits has been proposed, considering the sampling rate of the sensors utilized. The outcomes obtained through modeling confirm the suggested algorithm for adjusting controllers. The solution can be utilized by students and professionals in the development of autonomous UAVs or their computer models.

Keywords: quadcopter, computer modeling, PD controller synthesis, UAV design, stereo camera, room inspection

One of the key parameters used to assess the magnitude of the individual fire risk based on the appropriate calculation methodology is the evacuation start time. To calculate it, there is a need for information about the time of reaching the threshold value of the fire detector, which can be determined on the basis of a fire simulation for the room in which the fire is located. At the same time, it is required to dynamically evaluate the size of the area at each point of which at the height of the location of fire detectors there is an excess of the threshold value of the acting parameter, which is a rather complex task, the solution of which requires the use of automation. This paper proposes a method for automated assessment of the time for reaching the threshold value of the fire detector response based on the results of fire modeling when determining the calculated values of the individual fire risk. Functional model and basic algorithm of the proposed technology are presented. The developed methodology was tested using the example of modeling a fire in a commercial building based on the FDS software kernel for various scenarios. The results of a comparative analysis of solving the problems of estimating the time for reaching the threshold value of fire detectors for various criteria based on the proposed technology and manual method are presented.

Keywords: individual fire risk, fire dynamics simulation, field fire model, automation, algorithm, FDS

The article is devoted to the formalization of quality assessment criteria in the framework of the development of an automated quality management system at the stage of design preparation for the production of machine-building products. The main focus of the research is in the development of the terms of reference (TK). The author suggests formal criteria for assessing the quality of TK, aimed at forming comprehensive requirements for the design of the product and the organization of work. The methodology is based on a systematic analysis of domestic and foreign literature, as well as regulatory documents, and the formation of a graduated quantitative scale for each assessment criterion based on them. The key evaluation criteria are highlighted, each of which is assigned characteristics and scoring systems for quantitative analysis and the possibility of subsequent use when creating an automated quality management system at the checkpoint stage. The work contributes to improving the quality and competitiveness of products through a systematic assessment of the initial stage of development and the formation of the correct requirements for innovative products. The research results are focused both on research in scientific peer-reviewed journals of the Russian Federation, and with attention to international experience, which allows combining existing experience in the subject area.

Keywords: design preparation of production, quality assessment, formal criteria, terms of reference

This article explores the migration of the Chuvash Encyclopedia's website from the outdated ASP.NET platform to the modern Laravel framework. It provides a brief history of the regional online scientific reference resource, the reasons for updating its technical base, including security issues, incompatibility with modern browsers, and a lack of technical support. It also analyzes the key stages of its transition to the new Laravel platform. These include a thorough audit of the old encyclopedia website, including URL mapping, the design of a new database architecture on the modern MySQL 8.0 platform, which has been significantly optimized compared to the outdated version, as well as database migration from MSSQL to MySQL 8.0 and database processing using console commands. An example of a developed console command for automatically replacing URLs is provided. The result of this work was the launch of an updated website for the Chuvash Encyclopedia online at http://chuvenc.ru, which meets modern security and performance standards. New solutions were developed to migrate the outdated, yet socially significant, web resource to a modern platform with minimal data and functionality loss.

Keywords: Electronic Chuvash Encyclopedia, website, ASP.NET platform, Laravel framework, database, MySQL, data migration, data processing automation, console commands

The process of ensuring information security is inextricably linked with the assessment of compliance with the requirements. In the field of information protection, this process is called an information security audit. Currently, there are many international and domestic audit standards that describe various processes and methods for assessing compliance with requirements. One of the key drawbacks of these standards is the use of exclusively qualitative assessment without numerical calculations, which in turn does not allow making the procedure the most objective. The use of fuzzy logic allows providing the audit process with an appropriate quantitative assessment, while operating with understandable linguistic variables. The article analyzes existing standards and presents a conceptual model for applying the fuzzy set method in the process of information security audit.

Keywords: information security, information infrastructure, security audit, risk analysis, fuzzy sets, fuzzy logic

The article explores modern approaches to the integration of image processing algorithms and sensor equipment onboard unmanned aerial vehicles (UAVs) for monitoring and mitigation of emergencies affecting railway infrastructure. The research focuses on methods for efficient interaction with high-resolution optical cameras, LiDAR systems, and GPS modules, as well as on the use of distributed and cloud computing technologies for rapid data processing. Special attention is given to adaptive data compression techniques, caching strategies, and asynchronous message queues, which ensure reliable transmission under limited or unstable communication channels.
The work demonstrates practical integration scenarios using the DJI Mini 4 Pro UAV and the WebODM photogrammetric platform, showing a reduction of preliminary processing time from 45 to 6 minutes and an improvement in georeferencing accuracy from 7.8 m to 1.3 m through the use of GPS-EXIF metadata. Point cloud optimization methods, such as Voxel Grid filtering and Statistical Outlier Removal, are shown to decrease file size from 1.2 GB to 210 MB and reduce processing time from 52 to 17 minutes with minimal loss of accuracy.
The study highlights that combining onboard sensors with advanced processing pipelines significantly improves the timeliness, reliability, and accuracy of railway infrastructure assessments after emergencies. The proposed solutions enable automation of geospatial data workflows, enhance operational decision-making, and optimize resource allocation for recovery operations. The findings are relevant for the development of UAV-based monitoring systems in transportation, urban planning, and critical infrastructure protection.

Keywords: UAV, data transfer, distributed computing, LiDAR, WebODM, DJI Mini 4 Pro, infrastructure monitoring, adaptive compression, message queue

The paper discusses the issues of multi-criteria optimization of planning the loading of technological equipment at a machine-building enterprise within a calendar year. Planning and optimizing the loading of technological equipment is one of the key tasks of operational calendar planning at engineering enterprises. The paper presents a model for optimizing the load of technological equipment used in the production process. Within the optimization model, three groups of target indicators were identified: the performance indicator of the group of technological equipment within the calendar year; indicator of uniformity of process equipment group loading within the calendar year; the amount of losses from downtime of a group of process equipment within a calendar year. The paper presents the results of optimizing the load of the fleet of machine tools used within the framework of the machining workshop. Load optimization was carried out for certain groups of technological equipment: a group of lathes, a group of milling machines, a group of grinding machines. Equipment load optimization was carried out by redistributing the total labor intensity of the work performed for the corresponding groups of technological equipment between periods of the calendar year. The Pareto optimization method was used to determine the optimal option for loading groups of process equipment. The following optimization strategy has been defined: minimizing the total amount of losses from downtime of process equipment. The paper presents graphs of Pareto fronts for targets for turning group machines. As a result of optimization, the total amount of losses for certain groups of process equipment resulting from downtime decreased by 6.8% -10.2%. Thus, the use of the developed model to solve the problem of optimizing the load of the fleet of machine-tool equipment made it possible to increase the efficiency of the operational scheduling process at machine-building enterprises.

Keywords: scheduling, multi-criteria optimization, machine stock, targets, losses, process loading

The article is devoted to the analysis of methodological approaches to the definition and assessment of the psychofunctional state of a person. In connection with the need to improve the reliability of human-machine systems, the study of the psychofunctional state of a person controlling a dynamic object is of scientific interest, since to create reliable human-machine systems it is necessary to take into account the reliability factors of technical means and the human factor as well. The analysis of methodological approaches showed that to solve problems dedicated to increasing the reliability of "human-machine" systems, it is advisable to use a systems approach that considers a person not as an independent subject, but as an element of the system. The systems approach has a broad methodological base, allows us to study the psychofunctional state of a person in dynamics.

Keywords: psychofunctional state, functional state, systems approach, energy approach, behavioral approach, phenomenological approach, structural-integrative approach, electrophysiological methods, control of a dynamic object

This paper presents an adaptive pipeline architecture designed to enhance both throughput and reduce latency in real-time stream data processing within single- and multi-processor systems. Unlike predominantly conceptual models or narrowly focused algorithms, the practical impact of this architecture is demonstrated by achieving measurable performance gains through reducing redundant data copying and synchronization costs or by providing flexible control over input and output data ordering. The architecture employs shared memory to eliminate buffer duplication, uses data transfer channels that adapt based on the need for order preservation, and supports the replication of processes within or across CPU cores. Experimental results indicate that the proposed architecture delivers both high throughput and low latency while introducing minimal overhead for data transmission and process synchronization. By offering a flexible and scalable foundation, this architecture can be applied to a wide range of real-time applications, from video surveillance and robotics to distributed platforms for processing large data sets. It demonstrates versatility and robustness in adapting to varying computational demands, thereby ensuring both efficiency and reliability in high-performance environments.

Keywords: parallelism, multiprocessor computing, computational pipeline, performance scaling, queues, shared memory

The work is devoted to the problems of assessing and predicting the reliability of photovoltaic generation devices. The purpose of the work is to identify factors affecting the volume of electricity generation, as well as to build models and procedures for predicting the reliability of the panels during their use depending on these factors. An overview of the types of solar power plants and the photovoltaic panels used is given. An analysis of the factors affecting their reliability is performed, on the basis of which a hierarchy of fuzzy factors related to each other by fuzzy production rules is built. It is proposed to use a statistical two-parameter Weibull model to predict the reliability of the panels. An algorithm for neuro-fuzzy tuning of the reliability forecasting model depending on the factors considered is developed and software implemented, which can be used to create information and analytical systems for decision support in the design and operation of solar power plants.

Keywords: solar energy, photovoltaic panel, reliability prediction, statistical model, neuro-fuzzy network

Integration of heterogeneous field data and remote sensing information is a key and necessary step in modern geological exploration. This article proposes a method based on the creation of a regular spatial grid, which enables the efficient interpolation and integration of point, linear, and polygonal data represented in both vector and raster formats. The primary objective is to generate a structured and enriched dataset suitable for training predictive models, including neural networks. The proposed approach involves transforming geospatial data to ensure their accuracy and consistency within GIS environments. This method provides a reliable foundation for identifying prospective areas with high mineral potential and highlights the importance of rigorous data preparation in spatial modeling and analysis processes.

Keywords: reservoir exploration, data integration, interpolation, spatial grid, geochemistry, spatial modeling process, remote sensing, GIS

This study is devoted to the analysis of decision-making models in ensuring the protection of public order. The results obtained will allow us to formulate a new mathematical model of decision-making, which will allow us to obtain objective management decisions to ensure the protection of public order in the territory of the Republic of Tajikistan with the possibility of simulation. The object of the study is the process of ensuring the protection of public order. In the scientific literature and in open sources of information, there is a large number of works describing models and algorithms developed on the basis of various mathematical tools. The analysis of a number of papers on this topic will allow us to formulate a new mathematical model of decision-making, which will optimize and improve the quality of prepared decision-making projects while ensuring the protection of public order. The study revealed that the basis for improving the effectiveness of ensuring the safety of citizens during mass events is an effective management decision. 1) Based on this, an analysis of decision-making models is presented, the purpose of which is to determine the need to create a decision-making model while ensuring the protection of public order in the Republic of Tajikistan. 2) A model of decision-making in ensuring the protection of public order in the Republic of Tajikistan is proposed. The model is implemented based on the synthesis of mathematical modeling methods, including cluster analysis, pairwise comparison method and Petri nets. The model allows you to divide committed events, i.e. crimes into clusters according to previously defined criteria. At the final stage, the model allows you to simulate each event, thereby predicting the possible development of the event under study. The presented results of the analysis of decision-making models made it possible to formulate a new mathematical model of decision-making in ensuring the protection of public order in the interests of the Republic of Tajikistan.

Keywords: public order protection, mathematical model, cluster analysis, pairwise comparison method, expert assessments, Petri nets

This article presents an analysis of corporate network traffic over the SMTP protocol to identify malicious traffic. The relevance of the study is driven by the increasing number of email-based attacks, such as the distribution of viruses, spam, and phishing messages. The objective of the work is to develop an algorithm for detecting malicious traffic that combines traditional analysis methods with modern machine learning approaches. The article describes the research stages: data collection, preprocessing, model training, algorithm testing, and effectiveness analysis. The data used were collected with the Wireshark tool and include SMTP logs, message headers, and attachments. The experimental results demonstrated high accuracy in detecting malicious traffic, confirming the potential of the proposed approach.

Keywords: SMTP, malicious traffic, network traffic analysis, email, machine learning, Wireshark, spam, phishing, classification algorithms

The article presents the application of fuzzy modeling to solve the systemic task of qualitative assessment of the properties of land plots by an expert method using fuzzy modeling. The set of factors by which the suitability of the plot is estimated depends on the goals of the development project. The technique includes the decomposition of the model into additive models of internal and external factors and a combining multiplicative model, which reduces the dimensionality of the task of assessing the properties of the plot. At the second stage, a fuzzy model of expert assessment of the properties of land plots is formed. It includes a fuzzyification block using linear membership functions, max-min fuzzy inference technology, and defuzzification using the height method, which most adequately translates fuzzy expert assessments into clear numerical (point) values. At the third stage, the contribution coefficients of each factor in the assessment of the properties of plots are determined using the hierarchy analysis method and the fuzzy pairwise comparison scale.

Keywords: land plot, individual assessment, expert method, fuzzy modeling

This article presents a conceptual framework for assessing the maturity of construction control and supervision systems at construction sites. A multi-level assessment model has been developed, integrating the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation method. A five-level taxonomic system for grading the maturity of regulatory mechanisms in the construction industry is proposed. The procedures for forming a hierarchical structure of assessment indicators, constructing judgment matrices, determining weight coefficients, and applying the fuzzy comprehensive evaluation method to quantify the maturity level of supervision systems are described in detail. The developed methodology represents a universal tool for conducting comparative analysis of construction control and state supervision systems in various national and regional jurisdictions based on objective quantified criteria.

Keywords: construction control, state supervision, maturity model, Analytic Hierarchy Process, fuzzy comprehensive evaluation, quantification, assessment indicators

Optimization of automated management systems for facility protection complexes remains relevant today. This research paper provides an overview of the tools for implementing separate monitoring processes: device polling, processing of the received data, and transferring data to the graphic user interface. Based on the analysis of the reviewed information, a basis of solutions for developing management system of the technical means complex is planned to be formed. During the research, it was found that the combination of multi-threading architecture and adaptive polling algorithm allows to implement a large-scale polling; the clustering algorithm and special settings of frameworks for processing large-scale datasets can enhance job performance; WebSocket protocol has proved its efficiency for transferring the real-time data. The result of the evaluation of solutions was a set of tools for implementation of a hardware-software complex.

Keywords: sensor, management system, monitoring, SNMP manager, clustering, Hadoop, MapReduce, Spark, Apache Kafka, WebSocket

The paper examines the current state of the industrial Internet of Things market in Russia and around the world, the main areas of its application, as well as the prospects and challenges that businesses and industrial enterprises will face in implementing this technology. Special attention is paid to the advantages of implementing IIoT, such as increased productivity, reduced costs, improved security and transparency of processes. The barriers specific to the Russian market are discussed, including cybersecurity, hardware compatibility, and significant initial costs. Examples of successful implementations of IIoT technologies in various industries such as the oil and gas industry, logistics and chemical production are given. The emphasis is placed on the need for government support and adaptation of the regulatory framework to accelerate implementation. The article highlights the importance of an integrated approach to IIoT implementation, including using international experience and consolidating efforts to develop the digital economy in the face of global and local challenges.

Keywords: industrial Internet of Things, IIoT, industry 4.0, 5G, production automation, digital transformation

The widespread use of social media platforms has led to the accumulation of vast amounts of stored data, enabling the prediction of rare events based on user interaction analysis. This study presents a method for predicting rare events using graph theory, particularly graphlets. The social network VKontakte, with over 90 million users, serves as the data source. The ORCA algorithm is utilized to identify characteristic graph structures within the data. Throughout the study, user interactions were analyzed to identify precursors of rare events and assess prediction accuracy. The results demonstrate the effectiveness of the proposed method, its potential for threat monitoring, and the possibilities for further refinement of graphlet-based prediction models.

Keywords: social media, security event, event prediction, graph theory, graphlet, interaction analysis, time series analysis, correlation analysis, data processing, anomalous activity

In modern conditions of digital transformation, companies are actively implementing customer Relationship Management systems (CRM systems) to manage customer relationships. However, the issues of data protection, confidentiality and transparency of interaction remain critically important. This article explores the possibilities of using blockchain technology to enhance the security of CRM systems and improve trust between businesses and customers. The purpose of the work is to analyze the potential of using blockchain in data protection of CRM systems, as well as to assess its impact on the transparency of customer transactions. The paper examines the main threats to data security in CRM, the principles of blockchain technology and its key advantages in this context, including decentralization, immutability of records and protection from unauthorized access. Based on the analysis, promising areas of blockchain integration into CRM systems have been identified, practical recommendations for its application have been proposed, and the potential effectiveness of this technology has been assessed. The results of the study may be useful to companies interested in strengthening the protection of customer data and increasing the transparency of user interaction processes.

Keywords: blockchain, CRM-system, security, data protection, transparency, customer interaction

The article discusses the use of a recurrent neural network in the task of predicting pollutants in the air based on simulated data in the form of a time series. Neural recurrent network models with long Short-Term Memory (LSTM) are used to build the forecast. Unidirectional LSTM (hereinafter simply LSTM), as well as bidirectional LSTM (Bidirectional LSTM, hereinafter Bi-LSTM). Both algorithms were applied for temperature, humidity, pollutant concentration, and other parameters, taking into account both seasonal and short-term changes. The Bi-LSTM network showed the best performance and the least errors.

Keywords: environmental monitoring, data analysis, forecasting, recurrent neural networks, long-term short-term memory, unidirectional, bidirectional