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• ADAPTIVE SYSTEM FOR CONTROLLING TECHNICAL CONDITION WITH MULTIPLE-CURRENT MEASUREMENT PATHS

  D.L. Tukeev , Е. V. Kramarev , О.V. Afanaseva , D. А. Pervukhin

  254-264

  2026-07-07

  Abstract ▼

  The current stage of development in the methodology for analyzing and synthesizing complex technical systems is characterized by a substantial increase in requirements for their design speed without a loss of functional quality. This is achieved through the application of information technologies for designing complex systems and modeling their operation processes. Within this paradigm, solving the problem of creating adaptive multi-agent systems for monitoring the technical condition of highly critical objects appears relevant. These systems would use a set of varying-accuracy measurement channels for each type of monitored parameter. This will enable the operational selection of a measuring instrument and the formation of the most rational monitoring algorithm, ensuring the required monitoring effectiveness under significant financial constraints. The aim of this work is to substantiate the possibility of using varying-accuracy measurement channels when forming the structure of each technical condition monitoring channel to ensure a given reliability. To achieve this aim, the following tasks were set and successfully solved: – modern conditions for designing technical condition monitoring systems for complex technical systems were considered; constraining factors and trends in design theory development were identified; causes of potential shortcomings in prospective systems and ways to eliminate them were determined;– the form of the system performance criterion was defined as a generalized indicator, obtained based on an additive convolution of unit unconditional monitoring reliability indicators and weight coefficients of their importance; – a structural diagram of an adaptive system was synthesized based on a model of a single-parameter monitoring channel with measurement tracts of different accuracy and the capability to implement known methods for improving monitoring effectiveness; – a computational experiment was conducted, the results of which allowed for refining the identified patterns and proposing new recommendations. The results of the conducted research enabled the development of an adaptive algorithm for monitoring a multi-parameter Object of Control based on a multi-agent system. The behavior of its agents is modeled using retrospective information from previous monitoring cycles, predictive models based on this information, as well as the implementation of the principle of equal reliability and penalty functions in case of deviation from it.

• ALTERNATIVE APPROACHES TO NLP MODEL SCALE-UP: AN ANALYSIS OF APPROACHES TO OPTIMIZING DATA AND COMPUTATION VOLUME WHEN TRAINING LARGE-SCALE LANGUAGE MODELS

  К.I. Ralko , N. Е. Sergeev

  152-172

  2026-07-07

  Abstract ▼

  This paper focuses on overcoming the systemic limitations of the large-scale language model (LLM) scaling paradigm, which are related to data exhaustion and exponential growth in computational costs. This enables the development of more efficient approaches to building NLP models without sacrificing their performance. The goal of this study is to compare the performance of a standard transformer architecture (nanoGPT) and a model using semantic embeddings (nanoSonar) for language modeling tasks under resource constraints. Working with conceptual embeddings allows us to identify deeper linguistic patterns and reduce the amount of required training data, significantly improving modeling efficiency. The study utilized the TinyStories dataset, which includes short narratives with a clear structure. Before implementing the models, the data was preprocessed: for nanoGPT, tokenization was performed using the BPE method, and for nanoSonar, text was converted into semantic embeddings using a pretrained Sonar model. The models were evaluated using the loss and perplexity metrics. The results showed that the nanoSonar model provides significantly lower perplexity (6.609 versus 39.151 for nanoGPT) and demonstrates more robust training dynamics at later stages. This paper presents an analysis of modern approaches to scaling optimization (MoE, distillation, PEFT) and promising architectures (LRM, SSM, RWKV), and provides practical recommendations for applying models operating in the space of semantic embeddings to domain-specific problems and systems with limited computational resources. The results of this study can be useful in developing efficient language models that combine high generation quality with a cost-effective architecture.

• A UNIVERSAL MODEL OF ADAPTIVE MANAGEMENT OF CLOSED AGRICULTURAL PRODUCTION USING AI TECHNOLOGIES

  А.А. Kochkarov , А.К. Kulikov , V.М. Matsakova

  2026-04-29

  Abstract ▼

  The relevance of this research stems from the contradiction between the need to increase food production in an urbanized environment and the fragmentation of existing high-tech solutions (hydroponics, aeroponics, IoT), which are being implemented in isolation, without a unified management methodology. The lack of unified approaches to data collection and adaptive control of environmental parameters limits the scalability of vertical farms. The goal of this research is to develop and theoretically substantiate the architecture of a universal adaptive management model for closed-loop agricultural production systems, integrating various cultivation methods based on machine learning algorithms. The methodology is based on a systematic analysis of scientific publications and experimental data on the use of embedded devices and machine learning algorithms in hydroponic, aeroponic, and soil-based vertical greenhouses. Based on this data synthesis, parametric matrices were constructed to standardize technological processes. The main results include the development of a structural diagram of a universal model that enables the integration of disparate systems into a single platform with the ability to continuously monitor and perform predictive analytics. The minimum required sensor set is substantiated: pH, EC, temperature, humidity, CO₂, PAR, pressure, and nutrient solution flow. The proposed architecture enables dynamic switching between hydroponic, aeroponic, and indoor modes within a single phytotron. The conclusions and significance of this work lie in creating a foundation for designing scalable vertical farms with predictable profitability and resource efficiency indicators, while enabling continuous further training of AI algorithms for predictive microclimate management and early plant disease detection in urban environments

• ANALYSIS OF THE EFFECTIVENESS OF TRADITIONAL AND MODERN TECHNOLOGIES FOR MONITORING POWER TRANSMISSION LINES

  О. V. Afanaseva , Т.F. Tulyakov

  182-188

  2025-10-01

  Abstract ▼

  The article provides a comprehensive analysis of the effectiveness of traditional and modern technologies for monitoring power transmission lines (PTL). Power transmission lines are a critical element of the energy infrastructure, and their reliable operation directly affects economic stability and safety. Traditional monitoring methods, such as visual inspections and mechanical devices, have long remained the main control tools, but their limited accuracy, high dependence on the human factor and the inability to promptly detect hidden defects make them less effective in the face of increasing loads on power systems. Modern technologies, including unmanned aerial vehicles (UAVs), the Internet of Things (IoT), automated monitoring systems and digital twins, offer fundamentally new opportunities for monitoring the condition of PTLs. They provide high diagnostic accuracy, continuous data collection in real time, reduced operating costs and increased personnel safety. The article presents a classification of both traditional and modern methods, as well as a comparative analysis of their key parameters: accuracy, response speed, cost, safety and impact on operation. The results of the study demonstrate that modern technologies outperform traditional approaches in all the criteria considered. In particular, the use of IoT and UAVs allows minimizing the human factor, reducing inspection time and increasing data detail. Digital twin systems make it possible to predict possible accidents and optimize scheduled maintenance. However, successful implementation of innovative solutions requires additional investment, personnel training and integration with existing management systems. The conclusion is made about the strategic importance of switching to modern power transmission line monitoring technologies to improve the reliability and sustainability of the energy infrastructure. Despite high initial costs, their long-term benefits, including reduced accidents, resource savings and increased safety, fully justify the investment. The authors emphasize the need for further development of digital technologies in the energy sector to ensure stable and efficient operation of power grids

• USING PROJECT PLANNING TOOLS: GANTT CHART AND NETWORK DIAGRAM

  А.А. Bognyukov , D.Y. Zorkin , I.А. Tarasova

  102-110

  2025-10-01

  Abstract ▼

  An integrative model has been developed that combines calendar planning methods with software functionality (Excel, MS Project) for multi-level project optimization. Central focus is placed on three complementary methodologies: the Gantt chart, network diagram, and critical path analysis, which form the conceptual foundation for effective coordination of project processes. The study details the algorithm for creating a Gantt chart, which visualizes timeframes and task sequences, with emphasis on the functional capabilities of specialized software solutions, including Microsoft Project and Excel, enabling automated construction and adjustment of schedules. Further, the principles of constructing a network diagram, interpreted as a directed graph with edges (tasks) and vertices (events), are elaborated. This approach allows for identifying logical dependencies between project stages and determining the critical path – a sequence of operations with zero time reserves, defining the project’s minimum duration. Practical illustrations of critical path calculations are supported by examples demonstrating its role in optimizing time resources. A key aspect of the study is the analysis of time reserves, aimed at minimizing deadline risks through rational resource reallocation. The methodological framework is supplemented by visualization tools: resource requirement graphs and resource load diagrams, ensuring operational control over material and personnel assets across all project phases. The final element of the planning system is the calendar plan, which structures data on work titles, chronological intervals, and resource intensity. This document serves as an integrative foundation for synchronizing operational activities, ensuring adherence to established deadlines

• EXPERIENCE IN USING TRAINING SYSTEMS WITH VIRTUAL REALITY ELEMENTS FOR TRAINING SPECIALISTS OF MISSILE FORCES AND ARTILLERY USING ROBOTIC SYSTEMS FOR MILITARY PURPOSES

  A.I. Nagovicin, S.N. Pesterev, B.B. Molotkova, I.V. Aksenov

  2020-07-10

  Abstract ▼

  The paper presents the tasks to be solved by promising RTC VN in the interests of Rvi. The conclusion is formulated that the problem of training and improving the quality of knowledge of Rvi specialists using military robotic systems remains one of the urgent problems of higher mili-tary professional education and acquires new aspects of consideration. It is shown that one of the effective ways to solve the problem of training and improving the quality of knowledge of Rvi spe-cialists is to develop and implement computer-based training systems with elements of virtual real-ity and 3D visualization of the studied samples of equipment and weapons in the educational pro-cess. The main features of the computer information and reference system "compendium of the Rvi" developed at the Mikhailovsky military artillery Academy and used in the educational process are briefly described. Preliminary results of the conducted pedagogical experiment with the use of the "Rvi compendium" are presented, and the main factors that increase the effectiveness of the educational process are Noted. Based on the results of the pedagogical experiment made a rea-sonable inference that the use of KISS "compendium Rvia" allows to increase learning efficiency, to reduce terms of development of technology that is more efficient use of training time and as a result reduce the cost of training and the number of vehicles.

• NON-PARAMETRIC METHOD FOR DETECTING BREAKDOWN OF TIME SERIES USING THE RANDOM WALKS THEORY MECHANISM

  G. F. Filaretov , Z. Bouchaala

  2020-11-22

  Abstract ▼

  The task of the on-line detection of a sudden change in the probability properties of a time series
  is considered, which is usually interpreted as the detecting task of change point the characteristics
  (breakdown) in the observed stochastic process. The actuality of the development of research on this
  topic is noted, which is due to the emergence of ever new applied problems where methods and algorithms
  for breakdown detecting can be successfully used - in particular, when creating monitoring systems
  in industry, ecology, medicine, etc. Two main varieties of methods for breakdown detecting are
  discussed: parametric and nonparametric. It is noted that, although nonparametric methods, ceteris
  paribus, are inferior to parametric methods in terms of efficiency (the speed of breakdown detecting),
  they also have a number of advantages, without requiring, in particular, for their application detailed
  information about the probabilistic properties of the controlled process. This is fundamentally important
  for building monitoring systems, when detailed information about these properties may either be completely
  absent and then it is necessary to conduct a rather laborious preliminary study of it, or to be
  unreliable. An original sequential nonparametric algorithm for detecting discord is proposed based on
  the implementation of the random walk mechanism or, more specifically, using the theory of success
  runs. The operating principle of the control algorithm is explained and its description is given. The results
  of the study of the basic statistical characteristics of the algorithm, including the determination of
  its effectiveness, and results of comparison with known parametric methods, are given. The area of possible
  practical use of the proposed algorithm is highlighted, where its effectiveness remains quite high.
  The prospects of using the proposed algorithm as part of the software and algorithmic support of monitoring
  systems for various purposes are noted.

• ADVANCED HIGH-PERFORMANCE RECONFIGURABLE COMPUTERS WITH IMMERSION COOLING

  I.I. Levin, А. М. Fedorov, Y.I. Doronchenko, М. К. Raskladkin

  2021-02-25

  Abstract ▼

  The paper deals with prospects for the design of high-performance reconfigurable computing devices
  based on modern Xilinx UltraScale+ FPGAs. The aim of the research is the computational density
  up to 128 LSI FPGAs in one 3U 19’ product. Besides, it is necessary to provide the required powersupply and cooling of the system’s computing elements during execution of computationally expensive
  tasks. To provide the product’s required parameters in the given design package, we made the topology
  of our printed circuit boards and the design technology of their parts more complex. To cool the components
  of our computer system, we use the immersion technology. The distinction of the designed computer
  systems is wide capabilities of data exchange inside the block and among the blocks. It is crucial for
  tightly-coupled tasks, where the number of data transfers among functional devices is much higher than
  the number of such devices. As the main links between FPGAs, we use differential lines with multigigabit
  transceivers (MGT). The optical channels based system of data exchange among the blocks is
  provides the throughput over 2 Tbit/sec. We designed and produced a prototype of a computational
  module based on UltraScale+ FPGAs, and a prototype of a reconfigurable computational block. The
  computational block contains a general-purpose processor and all needed input-output interfaces. It is a
  stand-alone device. We used the new-generation computational module for implementation of several
  algorithms of various scientific and technical problems, and proved its wide applicability. We designed
  a modified immersion cooling subsystem, which dissipates total heat up to 20 kW. To achieve such level
  of heat dissipation, we implemented technical solutions concerning all components of the cooling system:
  the cooling agent, heat sinks, the pump, the heat-exchange unit. It is possible to unite several blocks
  into computer complexes with the performance up to tens of petaflops. Such complexes require a suitable
  engineering infrastructure.

• COMPUTER SIMULATION OF AVIATION SPRAYING WHEN IMPROVING THE TECHNOLOGY OF AERIAL-CHEMICAL WORKS

  V.P. Asovsky, A.S. Kuzmenko

  2021-12-24

  Abstract ▼

  The article considers some practical issues of solving the problems of improving the technology
  of aerial-chemical works using methods of computer modeling of its processes, in particular, on
  non-traditional modes of aviation spraying. These modes are typical for the treatment of areas with
  obstacles at the borders, when the introduction of working fluids is carried out when the aircraft
  descends in the approach to the production passage over the area at the required flight altitude and
  climb after its end. The carried out computational and theoretical studies on the example of the An-2
  biplane aircraft using the previously developed and tested multifactor software tools for modeling the
  processes of forming a vortex trace of an aircraft and depositing in it a spectrum of drops of working
  fluids characteristic of aviation spraying have shown that the use of unconventional technological
  treatment modes can significantly increase the productivity, safety and integral efficiency of aerialchemical
  works and measures for chemicalization of agricultural production in general. It is shown
  that to increase the efficiency of aviation spraying of areas limited by obstacles, it is technically possible
  and economically feasible to use a work scheme that provides for the beginning and end of processing
  of such areas at the stage of descent and climb at distances from obstacles corresponding to
  1-2 seconds of the aircraft flight (for An-2 aircraft at distances of 50–150 m at a flight altitude of up
  to 20 m). Such a scheme provides an increase in the productivity of aviation spraying up to 10–15 %,
  a reduction in the prime cost of treatments by 3–5 % and an increase in economic efficiency by
  2–3 % with an increase in their total effect by 6–8 %.

• DEVELOPMENT OF AN INTELLIGENT ROBOTIC HARVESTING SYSTEM

  Z.V. Nagoev, О.Z. Zagazezheva, К.C. Brzhikhatlov, I.А. Mambetov

  2025-04-27

  Abstract ▼

  In the context of the need to ensure food security, the tasks of optimizing production processes in the
  agricultural sector are becoming relevant. For example, given the shortage of labor in agriculture, it is
  necessary to develop and implement robotic systems to automate the processes of plant care, harvesting
  and processing. The article presents the results of the development of an autonomous robot for picking
  apples, created on the basis of a universal anthropomorphic robot developed at the Kabardino-BalkarianScientific Center of the Russian Academy of Sciences. The robot is equipped with two multi-link manipulators
  similar to human hands, which allows it to perform complex harvesting tasks. To ensure intelligent
  control of the entire system, a multi-agent neurocognitive architecture is used, which imitates the work of
  the human brain and allows the robot to adapt to changing environmental conditions. The robot is
  equipped with a set of sensors, including video cameras, ultrasonic and infrared rangefinders, lidar and
  encoders on the manipulator drives. This allows it to accurately determine the location of apples, assess
  their ripeness and plan the trajectory of the manipulators. Particular attention is paid to the development
  of a gripper that imitates a human hand and allows you to adjust the squeezing force, which minimizes the
  risk of damage to the fruit. A multi-agent neurocognitive architecture is used to control the robot, which
  provides autonomous decision-making based on sensor data. The system is able to build a map of the area,
  determine the position of the robot and plan a route, as well as recognize apples and assess their condition.
  The article also considers the problems associated with the automation of harvesting in agriculture,
  including a lack of labor and crop losses due to improper operation of equipment. The authors emphasize
  that automation and robotization of harvesting processes have great potential, especially for crops
  that require an individual approach, such as fruits and vegetables. The presented robot demonstrates high
  efficiency in solving these problems, which is confirmed by the results of field tests. The developed system
  can be adapted to work with other crops, which makes it a universal solution for the agricultural industry