Floating buoy technology has rapidly advanced and is integral to marine science, renewable energy harvesting, and environmental monitoring applications. This study synthesizes recent innovations in buoy designs, energy conversion technologies, and hybrid system integration. Key advancements include modular construction techniques, bio-inspired and hydrodynamic optimizations for improved stability and efficiency, and novel energy-harvesting mechanisms utilizing oscillating buoys, piezoelectric, and triboelectric systems. The integration of floating buoys with hybrid platforms, such as floating breakwaters and offshore wind turbines, demonstrates considerable potential for cost sharing and enhanced performance. Despite substantial progress, critical gaps remain, particularly in long-term operational validation, real-world performance under extreme conditions, scalability, and comprehensive environmental impact assessments. This study identifies these research gaps and outlines future directions to facilitate the widespread adoption of floating buoy technologies. The insights provided are crucial for guiding ongoing innovation, addressing existing limitations, and supporting sustainable blue-economy initiatives.
This study investigates the effectiveness of economic system management from a network perspective. Through ongoing communication, agents form networks that can be described in terms of two contours: an open contour, reflecting interactions with external agents, and an organisationally closed contour, confined to interactions within a single system. The latter contributes to system stability, yet it is rarely examined as an independent object of analysis. Economic systems are inherently dynamic: the number of agents and the connections among them change over time. As these changes occur, network effects may emerge, influencing overall system performance. Recognising and accounting for such effects is therefore essential when assessing managerial effectiveness. The study aims to develop a practical framework for identifying and managing organisationally closed economic systems based on network effects. This framework is structured as a management cycle comprising four stages: data collection, data analysis, generation of alternatives, and decision-making. System effectiveness is evaluated through two dimensions of the network effect: structural and functional. The structural dimension captures the non-additive growth in the number of connections as the number of agents increases. The functional dimension reflects the expansion of internally balanced turnover within the system. The proposed framework was applied to an actual economic entity, resulting in the identification of 18 organisationally closed economic systems. To assess the presence of a network effect, the study modelled an increase in the number of agents within the largest identified system (47 agents). The results demonstrate a clearly non-additive change in key indicators, confirming the existence of a network effect within the system.
The use of evolutionary genetic AI methods and, in particular, genetic algorithms (GA) ensures the construction of sufficiently universal optimization systems with various architectures and macroparameters. A systematic investigation of GA structures, parameters, and performance has made it possible to identify and synthesise key trends in their modification. The effects of GA structure and parameters on the timing and accuracy of fitness function optimization were performed on the OneMax binary chromosome coding test problem. Numerical studies of the solution of the problem of evolutionary genetic optimization have shown the applicability of a fuzzy controller to increase the efficiencyof GA. Numerical experiments have demonstrated that the average fitness value increases rapidly during the initial stage of the optimization process, which can be attributed to the high initial crossover probability ( Pc ). After 20-50 epochs, the optimization process reaches a stable regime. The fuzzy adaptation of the parameters of the genetic operators makes the algorithm more robust compared to fixed parameters. Recommendations have been formulated for the selection of macroparameters and for substantiating the choice of algorithm modification strategies in specific application domains, including the allocation of limited water resources.
The aim of this study is to conduct a comparative analysis and select domestic alternatives to the universal one-component, medium-strength anaerobic thread locker Loctite 243 (Germany). The evaluation criterion was to ensure comparable quality and reliability of locking performance while minimizing the final product cost. The objects of the study were the following alternative sealants: ROSLOCK 243, AXIOM AS311, ADHESOL 534, EFELE 113, SantekhMaster Blue Gel, Anakrol 2032, and RusBond A2.43. Under specified curing time and medium-strength conditions, key performance characteristics of the alternatives were determined, including breakaway torque and unscrewing torque.A comparative analysis of the experimental results against the manufacturers’ technical specifications confirmed that the declared performance characteristics correspond to the actual functional properties. Based on the study results, EFELE 113 and ROSLOCK 243 were identified as the optimal alternatives. Under standardized experimental conditions, their use enables a reduction in the final product cost by approximately 8.2 and 9.5 times, respectively. The adoption of these alternatives enhances the stability and efficiency of logistics processes, simplifies supply chains, and reduces associated risks, including those related to sanctions.
This study identifies and analyzes the factors influencing the formation, functioning, usability, and efficiency of augmented reality (AR) systems. The first group of factors is determined by the technical characteristics of the system and the information infrastructure. The quality of the sensors determines the degree of detail and reliability of the initial data; devices with low accuracy can cause delays, drift, or jitter, which negatively affect the stability of the virtual object. Accurate positioning and tracking depend on GPS signals, visual-inertial odometry, or marker-based systems that can be affected by multichannel interference, signal jamming, or sensor noise, resulting in a mismatch between the physical and virtual worlds. Network bandwidth limitations affect real-time data streaming, cloud rendering, and multi-user synchronization, and unreliable connections result in skips or delays. The second group of factors refers to environmental conditions. Fluctuations in lighting can cause noise, decrease contrast, and disrupt object detection algorithms, which require the use of reliable computer vision techniques. This study proposes a solution to problems that improves the quality of augmented reality content and is key to the creation and development of AR systems.
The present study aims to conduct a comparative analysis of dispersion media used for the synthesis and storage of copper nanoparticles derived from copper formate, and to evaluate their suitability for application in current collectors. Particle characteristics in two media, namely ethyl alcohol and a mixture of alcohol and ethylene glycol, were investigated using dynamic light scattering, rheological analysis, and refractometry. The results demonstrate that the combined solvent system produces nanoparticles with a smaller average diameter (56.7 nm compared to 107.1 nm in pure alcohol) and a narrower size distribution, with 83.4% of particles falling within the 64-128 nm range. To visualise the data, particle size histograms were constructed, and the distributions were approximated using normal and Pearson distribution models. Experimental findings further indicate that the rate of particle agglomeration in the alcohol - ethylene glycol medium is approximately two times lower than in pure alcohol. On the basis of these results, the alcohol - ethylene glycol mixture can be recommended as a stabilising dispersion medium for the long-term storage of copper nanodispersions intended for use in current collector applications.
The rapid onset of the COVID-19 crisis compelled immediate responses to mitigate infection risks, particularly in education. A swift transition to e-learning became a necessity, posing myriad challenges for students and institutions. Issues ranged from technical considerations to educators' preparedness and students' readiness, necessitating a reevaluation of the role of information technology in education. The didactic potential of e-learning tools is considered, and methodological recommendations are formulated for their integration into pedagogical practice, adaptation to both distance and traditional conditions. An analysis of relevant international studies informs the development ofa teaching method that optimizes distance-learning efficiency and minimizes network load. This method strategically balances synchronous and asynchronous learning, considering network traffic reduction, fostering equal educational opportunities regardless of location, health, or financial status. This study affirms the method's effectiveness through a com-parative analysis of the results with those of previous traditional semesters. This research contributes valuable insights for navigating the challenges posed by the pandemic in the education sector. This study aims to explore the pedagogical possibilities of e-learning tools and offer methodological recommendations for their incorporation into teaching practices, adaptable to both remote and conventional environments. Additionally, it seeks to develop and validate a teaching approach that enhances the efficiency of distance learning, reduces network load, and promotes equitable educational access, addressing the challenges associated with the rapid development and widespread adoption of e-learning technologies.
Industry is entering a new stage of technological development characterized by the integration of digital technologies into management and production processes. In this context, the study of information technologies, particularly blockchain, has become increasingly relevant. The purpose of this study is to examine the most significant trends in the application of blockchain technologies in industry. The objectives include analyzing the specific features of industrial enterprises, assessing their readiness for digital transformation, evaluating the economic effects of technology adoption, and identifying both the challenges and advantages associated with blockchain implementation. The study reviews changes in the formulation of national development goals toward greater economic digitalization and presents indicators for achieving these targets by 2030. It also considers the planned funding allocations for defense industry enterprises within the upcoming three-year budget cycle through 2027. The study identifies several challenges that may hinder the adoption of new technologies in defense enterprises, including stringent requirements for reliability, accuracy, and information security; the need to transform business models; continuous business process reengineering; and limited interest in promoting blockchain technologies at all stages of implementation. At the same time, the advantages of blockchain integration are summarized, such as reduced time and costs in identifying counterparties, improved information quality, and opportunities to develop proprietary digital platforms within enterprises. Finally, the study outlines several key directions for the further development of blockchain technologies in industry.
The study addresses key issues in the development of fiber-optic gyroscopes with an extended angular velocity measurement range for a Small-Sized Inertial Measuring Unit intended for a wide class of highly maneuverable objects. The study focuses on the output characteristics of fiber-optic gyroscopes with an angular velocity range exceeding 300°/s, as well as on zero-bias error between successive power-on cycles and zero-bias error under varying temperature conditions, with a view to their integration into a Small-Sized Inertial Measuring Unit. The results of experimental investigations into the output characteristics of fiber-optic gyroscopes (FOG) are presented, including their performance over the angular velocity range, across temperature variations, and under repeated power-on conditions for a Small-Sized Inertial Measuring Unit (IMU). The research methodology is based on the design of an open-loop fiber-optic gyroscope employing direct conversion, with its operating principle derived from the Sagnac effect. In addition, the feasibility of using fiber-optic gyroscopes operating at optical wavelengths of 1.3 μm and 1.75 μm with an extended angular velocity range has been examined. The findings confirm the suitability of such gyroscopes for incorporation into a Small-Sized Inertial Measuring Unit.
Metal structural elements remain the primary construction material in many modern structures, which are subject to stringent requirements for safe and reliable operation. During service, structural elements undergo deformation and are exposed to various physical fields and environmental conditions. Situations involving two or more concurrent degradation factors pose particular risks. This study presents selected results of experimental and theoretical studies on the influence of an electromagnetic field and the orientation of its field lines on the corrosion wear of thin-walled steel elements. It also examines the effect of a magnetic field on the corrosion behavior of deformed thin-walled samples. The experiments were conducted in both urban and rural environments. The samples were exposed to the test environment for a specified period. Deformation was introduced using different methods.An experimental - theoretical approach was employed to evaluate the degree of corrosion wear and to determine the mechanical properties of the samples. Tangential and bending stiffness were calculated using relationships derived for the case of pure bending. The results indicate that corrosion wear is greater in samples not subjected to a magnetic field than in those exposed to magnetic field effects. Samples with surfaces oriented parallel to the Earth’s magnetic field lines exhibit more pronounced corrosion. It was also found that the tangential stiffness of undeformed samples under magnetic field exposure is slightly higher than that of tensile-deformed samples, whereas the bending samples of tensile-deformed samples exceeds that of undeformed ones. The study reveals new effects of both theoretical and practical significance.
This study examines the automation of engineering calculations within an information and analytical training system for specialists in technosphere safety. It applies an optimization approach based on differential calculus to address tasks related to the rapid elimination of emergency consequences, including the search for missing vessel crew members under conditions of reduced visibility. The study demonstrates how Mathcad and Excel can be used to automate engineering calculations. It describes the sequential stages of solving technosphere safety problems, integrating the classical methods of differential calculus with their practical implementation in the Mathcad mathematical package and the Excel spreadsheet environment. The findings confirm that automated computation enhances the efficiency of rapid response and supports informed decision-making in emergency situations. Furthermore, incorporating digital technologies into engineering calculations contributes to improving the professional training of technosphere safety specialists.A distinctive aspect of the study is the analysis of a simulated man-made emergency conducted within the framework of the interdepartmental experimental and research exercise “Safe Arctic” in Murmansk, Russia. The authors emphasize the importance of real-time automation in managing technogenic emergencies, particularly through determining optimal area illumination. The study also examines relevant pedagogical approaches and presents the authors’ methods for solving professionally oriented tasks. A rational procedure for calculating area illumination using derivatives is proposed. The originality of the research lies in the methodology for determining the optimal height for illuminating an emergency zone, which combines differential calculus with a comparative analysis of function graphs generated through automated calculations. The results contribute to improving the effectiveness of rescue operations in conditions of limited visibility.
This study investigates the evaluation of a new approach for the pipeline route design process using the synthesis of artificial intelligence algorithms and Earth remote sensing data. For the effective construction of gas pipelines, a thorough comprehensive analysis of various geological, environmental, economic, and infrastructural factors is necessary. Route design is based on the principle of building a trajectory with the lowest cost. For this purpose, a multifactorial analysis of the territory was conducted according to key parameters that affect the financial costs during construction. The following groups of features were identified: water barriers, geomorphological factors, existing transport routes, specially protected natural areas, and proximity to large settlements. The approach of multifactorial suitability analysis was studied and adapted, on the basis of which the cost map used in the search for the path of lowest cost was formed. The main result of this study is the obtained software solution, which provides optimization of weighting coefficients in the multifactorial analysis of territories for laying main gas pipelines based on a genetic algorithm. The advantages of the proposed approach are the automation of the process and consideration of the regional characteristics of the territories. As a practical application, trajectories have been developed to solve the problem of gasification in the Krasnoyarsk Territory of the Russian Federation.
The article develops the concept of a Hybrid Earth Remote Sensing System (HERS) for Myanmar, integrating Low-Earth Orbit (LEO) satellites and Unmanned Aerial Vehicles (UAVs) to obtain near real-time, high-resolution geospatial data for environmental monitoring and disaster risk management tasks. Analysis of the existing Earth remote sensing infrastructure and implemented projects revealed several limitations: high latency of satellite systems, cloud-cover interference, restricted data availability, and institutional barriers, including weak interagency coordination, a shortage of trained personnel, and insufficient funding. As a result of the study, the HERS architecture is formulated, including integration of satellites and UAVs, the use of multifrequency and laser communication channels, and energy-efficient UAVs with modular payloads (SAR, hyperspectral, and infrared sensors), providing compatible processing and rapid data transmission to the national GIS infrastructure. It is shown that the proposed system improves the spatiotemporal resolution of observations, reduces the impact of cloud cover, lowers operational costs compared with predominantly satellite-based solutions, and expands the range of practical tasks; from monitoring agriculture, forests, and water resources to near real-time response to floods and cyclones. The practical significance of the work lies in the fact that implementation of HERS, together with the development of a national GIS platform and specialist training programs, increases Myanmar’s resilience to natural and anthropogenic threats and provides more evidence-based support for decision-making.
Space robotics is rapidly becoming essential as satellites and orbital debris continue to increase, creating demand for reliable capture and servicing technologies. A central challenge lies in minimizing the impact forces generated during contact, which can threaten both the robot and the target. This paper addresses the problem by introducing a configuration optimization approach that leverages the concept of integrated effective mass (IEM) to reduce capture contact forces. The contribution of this study is twofold: it demonstrates how IEM serves as a practical performance metric for predicting capture safety, and it validates configuration optimization as an effective strategy for mitigating impact forces in free-floating space robots. The methodology applied a Hunt - Crossley contact model with hysteresis damping to simulate robot-target interactions under various manipulator configurations. A 7-DOF free-floating robot was modeled, and IEM was computed through Jacobian-based dynamic analysis. The coefficient of restitution was also tuned to balance rebound and capture stability. Results reveal a strong nonlinear relationship between IEM and contact force. Configurations with low IEM generated substantially lower forces: for example, an IEM of 0.0413 kg produced only 442 N, while an IEM of 1.7199 kg resulted in forces exceeding 4142 N. By tuning the restitution coefficient to approximately 0.8, rebound effects were minimized without compromising stability. The simulations confirmed that configuration optimization can reduce capture forces by nearly an order of magnitude while avoiding singularities. In conclusion, this work shows that planning manipulator configurations based on IEM analysis is not merely theoretical but a practical tool for safer, more reliable on-orbit servicing and debris removal. These findings reinforce configuration optimization as a cornerstone for the next generation of space robotic operations.
The minimax formulation of the problem of linear stationary control based on incomplete data of multidimensional stationary in a broad sense random processes (vector useful signal) observed in an additive mixture with interference of the “white noise” type, when the spectral densities of disturbances in the measurement channel and in the measurement interference are completely unknown and belong to a certain set of non-negatively defined functions, is considered. Only the condition of linear regularity is imposed on the observed vector process. A guaranteeing estimate is considered, which means the best estimate of the parameters of a useful signal in the sense of a minimum standard error with the worst behavior of measurement errors and disturbances with spectral densities belonging to the set, with respect to which the optimal control is determined based on incomplete data. Regarding the spectral density of the useful signal, it is only known that it satisfies a given system of moment conditions and is concentrated on a given measurable subset of the frequency axis. It is shown that the factorization of the matrix spectral density makes it possible to obtain a solution to the problem of optimal minimax linear filtration and is necessary to solve the problem of linear optimal control based on incomplete data. The search for optimal control based on incomplete data from the emerging multidimensional antagonistic game is reduced to solving a specific system of relations. Matrix boundary value problem methods, Hilbert matrix transformations, and properties of matrix frequency characteristics are used in the solution. An illustrative example is presented.
Blockchain technology has gained attention not only in the financial sector but also in public and corporate governance. Its core attributes - decentralization, immutability, and data transparency - can foster a new level of trust and efficiency in managerial decision-making processes. Given the ongoing digital transformation and the growing demand for transparency, many state organizations and governmental bodies consider blockchain a tool for addressing pressing issues in transaction control, document flow, and supply chain management. The key opportunities and limitations of using blockchain technology to support management decision-making at the government and corporate levels are explored. The empirical base included Russian and international scientific publications, official reports by international organizations, and findings from pilot projects and final qualification papers. Research methods encompassed content analysis, comparative analysis of case studies, and systematic data processing to form conclusions and recommendations. The study revealed that blockchain can enhance the transparency and reliability of managerial processes, expedite document flow, and strengthen stakeholder trust. However, organizational and legal barriers, as well as technical challenges (scalability, integration with legacy systems), hinder widespread adoption. Effective application of blockchain in managerial decision-making demands a comprehensive approach: improving the regulatory framework, developing human capital, and establishing a robust digital infrastructure.
The study addresses issues related to optimizing the management of defense industry enterprises using BPMN notation. The defense-industrial complex (DIC), as a key sector of the economy, plays an important role in ensuring national security, maintaining the country’s technological sovereignty, and stimulating economic growth. The authors analyze existing management processes of DIC enterprises and identify the main problems: outdated technologies, lack of strategic planning, low innovation and investment activity, shortage of highly qualified personnel, and difficulties with banking support for the state defense order. The paper proposes an improved BPMN management scheme that includes the creation of an innovation center. The innovation center is envisioned as an independent federal institution performing functions such as conducting RD, acting as a technology accelerator, training personnel, developing economic strategies, and interacting with universities and technology startups. To assess the effectiveness of the proposed solutions in the DIC, formulas for Return on Innovation Investment, Technology Transfer Efficiency, and a personnel training indicator are presented. The authors emphasize that the use of this management scheme will significantly increase the innovation activity of DIC enterprises, enhance their resilience to external challenges, and accelerate the development and implementation of modern technologies in the defense sector of the Russian Federation.
The problem of low-frequency noise (baseline wander) in long-duration digital electrocardiogram (ECG) signals, which can distort critical diagnostic features such as the ST-segment and T-wave morphology, is considered. Digital filtering methods are studied with an emphasis on low-frequency noise extraction and correction using Chebyshev type II and Butterworth filters synthesized in Python. The results show that a 7th-order high-pass filter with a cutoff frequency of 1 Hz effectively isolates the zero-potential line, whereas the filtfilt function is essential to avoid phase distortions. The success of the filtering method depends on the rate of change of the zero-potential line, and further work is required to develop quantitative criteria for evaluating and correcting filter-induced distortions. The proposed approach aims to improve automated ECG analysis and reduce false alarms in cardiac-monitoring systems.
A comprehensive methodology for designing an aircraft pitch angle control system is proposed, combining mathematical modeling, aerodynamic parameter identification, and controller optimization. A comparative study was conducted on the accuracy of the Euler and 4th-order Runge-Kutta methods for numerical integration of longitudinal short period motion equations in identification tasks. It was established that the Runge-Kutta method provides higher accuracy for estimating aerodynamic force coefficients, while the Euler method is preferable for moment analysis, defining the criteria for algorithm selection during data generation. Automated tuning of the PID controller in Simulink achieved record dynamic system performance characteristics (without considering the actuator): rise time - 0.0709 s, overshoot - 11.6%, which is 20-30% superior to results from known counterparts. The developed approach demonstrates the possibility of replacing labor-intensive flight tests with digital models while maintaining accuracy, thereby reducing design time. The results confirm that the integration of numerical modeling, parametric identification, and optimization forms a new standard for preliminary studies in aviation technology, aligning with the digitalization trends in the aerospace industry.
The operation of spacecraft with nuclear power plants operating under the influence of their own external atmosphere is associated with the effect of radiation transfer from the near-reactor zone to the area near the instrument compartment. This phenomenon is called “induced radiation”. Induced radiation has a negative effect on the equipment in the area near the instrument compartment. To protect against induced radiation, this article suggests, together with traditional protection methods, using special devices that provide additional radiation protection for spacecraft with nuclear power plants. These include: a positively charged separation screen; gas nozzles for purging the outboard space; electronic plasma neutralizers with thermionic cathodes. The combined use of traditional methods and additional protection devices to reduce the negative impact of a nuclear reactor will significantly extend the service life of the spacecraft.
