Control, Navigation and Communication Systems. Academic Journal
Journal represent the research results on the development and improvement of control, navigation and communication systems in various areas
Національний університет «Полтавська політехніка імені Юрія Кондратюка»
ORGANISATIONAL AND TECHNICAL MEANS OF NORMALISING ULTRA-LOW FREQUENCY ELECTROMAGNETIC FIELD LEVELS
The main approaches to normalizing the electromagnetic environment in general-purpose buildings and structures have been investigated. It has been determined that the most common resonant systems for simultaneous compensation of reactive power and suppression of higher harmonics and interharmonics of industrial frequency electric current (voltage) are ineffective in the presence of a complex spectrum of harmonics and interharmonics. It has been experimentally determined that in modern buildings and structures with a large number of electrical consumers with non-linear volt-ampere characteristics, the spectrum of interharmonics, including subharmonics, is complex and unpredictable. It has been shown that modern universal systems for suppressing harmonics and interharmonics are expensive and are suitable for use in enterprises with high electricity consumption for energy saving. A scheme for suppressing harmonics and interharmonics of industrial frequency electric current with feedback using a transformer is proposed. This approach is appropriate for unpredictable changes in the harmonic composition of the voltage in the power supply system. It is shown that interharmonics generation is also possible in buildings with a relatively small contribution of non-linear electrical consumers to the total load. Interharmonics can be generated as a result of modulation phenomena in voltage drop processes when powerful electrical consumers are switched on. The procedure for developing organizational and technical measures for electromagnetic safety based on electromagnetic monitoring is provided. It is emphasized that at the first stage of such work, it is necessary to ensure uniformity of the load on individual phases of the power grid, conduct a complete overhaul of reactive power compensation systems and eliminate leakage currents.
Copyright (c) 2025 Nataliia Burdeina, Yaroslav Pidlisnyi http://creativecommons.org/licenses/by-nc/4.0
MEANS OF NORMALISING THE LEVELS OF PHYSICAL FACTORS AT HIGH-VOLTAGE ELECTRICAL SUBSTATIONS
The levels of electromagnetic fields, noise, and concentrations of air ions in the air of the premises of the control rooms of high-voltage electrical substations are investigated. It was found that the intensity of electromagnetic fields of industrial frequency and the density of energy flows of ultra-high frequency electromagnetic fields is at the standard level. Radio frequency electromagnetic fields and impulse noise exceed the maximum permissible levels. Air deionization is observed. It was established that the source of abnormal field levels is relay protection devices. At the same time, near the relay cabinets, the concentrations of air ions are significantly higher than the minimum permissible levels. Normalization of electromagnetic and acoustic field levels is achieved by using a universal perforated screen made of carbonyl iron composite material. The matrix was made of standard XC varnish. As a result of the shielding, the levels of electromagnetic fields in the radio range have been reduced to values far below the standard. The noise reduction indices for medium and high frequencies are 8–12 dB. Given that impulse noise is of medium and high frequency, this result is satisfactory. Normalization of air ion concentrations of both polarities is achieved by moving air ions from relay protection devices to workplaces by directed air movement through the openings of the electromagnetic and acoustic shield. The advantage of the composite screen is the absence of static charges that neutralize the charges of air ions.
Copyright (c) 2025 Valentyn Glyva, Dmytro Osadchiy http://creativecommons.org/licenses/by-nc/4.0
MEANS OF IMPROVING ENERGY EFFICIENCY AND PROTECTION FROM THE EFFECTS OF PHYSICAL FIELDS IN THE PROCESS OF BUILDING RESTORATION
The possibilities of creating a composite material for simultaneous blocking of infrared radiation and shielding of electromagnetic and acoustic fields of wide frequency ranges have been investigated. The model material is made on the basis of latex (matrix) and finely dispersed fillers of basalt and flaky graphite. The basalt component contains 18–20 % ferromagnets, which provides shielding of the magnetic component of the electromagnetic field. A calculation tool is provided that allows preliminary determination of the magnetic and electrophysical properties of the composition and assessment of thermal resistance. It has been experimentally established that a material with a thickness of 10 mm is suitable for blocking infrared radiation. At this thickness, its thermal resistance is close to that of mineral wool with a thickness of 50 mm. It has been shown that with a material thickness of 4 mm, there is a sharp increase in the shielding coefficient of the magnetic component of the industrial frequency electromagnetic field. The increase in the shielding coefficient of the 2.45 GHz electromagnetic field with increasing material thickness is more monotonous. At thicknesses greater than 4 mm, the shielding efficiency is sufficient for any external field intensity. Noise reduction indices in octave frequency bands were investigated. For low frequencies of the sound spectrum, they are 4–20 dB, for medium and high frequencies – 34–46 dB. This result is close to the efficiency of porous noise-reducing materials. To develop industrial technology for the production of protective composite material with the achieved quality indicators, it is necessary to select a material with a relative dielectric permeability of 34–40, which corresponds to the dielectric permeabilities of latexes.
Copyright (c) 2025 Viktor Gusev, Serhii Zozulya, Ruslan Levkivskyi http://creativecommons.org/licenses/by-nc/4.0
CONTROL MODELS FOR MOBILE ROBOT PARKING USING DISTANCE SENSOR DATA
Relevance. The growing demand for autonomous mobile systems capable of independent navigation and parking is driven by several critical factors. Firstly, the rapid robotization in logistics, security, delivery, and service industries necessitates reliable mechanisms for precise positioning of mobile platforms in spatially constrained environments. Secondly, in the context of autonomous vehicle development, the issue of automatic parking becomes a priority for enhancing safety, reducing energy consumption, and minimizing human involvement in control processes. Currently, a significant number of studies focus on the implementation of automatic parking systems; however, most of them either rely on high-cost sensors (such as LiDARs or deeplearning-based cameras) or fail to ensure the required accuracy under dynamic or unfamiliar environmental conditions. Against this backdrop, the use of ultrasonic sensors represents an effective alternative, enabling a necessary level of adaptability and sensitivity while maintaining low system cost. The relevance of this research is further reinforced by the need to develop a universal control model that is scalable, adaptive, and easily integrable into various types of mobile platforms. This work focuses not only on the theoretical formulation of the control model but also on its experimental validation using data from ultrasonic sensors that reflect the physical environment in real time. Therefore, the development of a mobile robot parking control model based on ultrasonic sensors is a timely and important task that combines scientific novelty with practical significance for the advancement of autonomous systems. The object of research. A parking control system for a mobile robot that operates based on data obtained from ultrasonic distance sensors. This system comprises both hardware components, such as ultrasonic sensors, actuators, and controllers, and software that implements algorithms for environmental analysis, decision-making related to parking maneuvers, and motion control. Purpose of the article. This article presents a comprehensive review of contemporary models for mobile robot parking control based on distance sensor data. The objective is to identify and critically evaluate effective approaches to sensor integration, control algorithm design, and architectural implementation of such systems. Particular attention is given to analyzing their applicability in real-world environments, with the aim of outlining development prospects that enhance system accuracy, reliability, and adaptability under dynamic and constrained conditions. Research results. As a result of the conducted review, it has been established that modern mobile robot parking control systems encompass a wide range of modeling approaches, varying in both mathematical complexity and sensor configurations. The analysis reveals that the choice of control model is directly influenced by the availability of computational resources, the robot’s chassis type, and the nature of the operational environment. Particular attention is given to the comparative assessment of sensors, with ultrasonic sensors remaining dominant in short-range positioning systems due to their low cost, ease of integration, and reliability in controlled conditions. Conversely, LiDAR sensors have demonstrated superior accuracy and spatial resolution, although they present higher implementation and maintenance complexity. Cameras and infrared sensors are regarded as supplementary data sources, functioning effectively only within well-defined conditions and with appropriate software support. The findings of the review confirm that an effective parking control system for mobile robots relies on a holistic approach that integrates sensor selection, control model design, algorithmic implementation, and system architecture. Such integration enables high accuracy and operational reliability even in complex, dynamic, or constrained environments. Conclusions. Effective mobile robot parking control is based on the integration of reliable sensor systems, particularly ultrasonic sensors and adaptive decision-making algorithms. Ultrasonic sensors remain the most suitable option for low-cost and simple systems, whereas hybrid approaches involving LiDAR or camera-based solutions offer higher precision. Among the control algorithms, finite state machines, fuzzy logic, and machine learning methods have demonstrated the greatest effectiveness. The most optimal system architecture is modular, with a clear separation between sensing, computation, and actuation layers, which ensures adaptability, accuracy, and operational stability under real-world conditions.
Copyright (c) 2025 A. Huk, V. Diachenko, M. Illarionov, Y. Titova http://creativecommons.org/licenses/by-nc/4.0
THERMOANALYTICAL COMPLEX FOR CHARACTERIZATION AND IDENTIFICATION OF SUBSTANCES BY THE METHOD OF DIFFERENTIAL THERMAL ANALYSIS AND SOME OF ITS POSSIBLE AREAS OF APPLICATION
A simple multi-purpose thermoanalytical complex with a combined differential-thermal method of research has been developed for the identification of substances by the temperatures of phase transformations (melting, boiling, crystallization, polymorphic transitions), thermal decomposition; studying the nature and temperature limits of a number of thermal effects - stepwise; closely located by temperature value; those that overlap (caused by a change in spatial modification, dehydration, decomposition, etc.); functional dependencies of physical properties of substances; qualitative, and in some cases quantitative analysis of mechanical mixtures of several substances; measurement of phas e transition temperatures of individual substances and systems, construction of state diagrams on their basis; study of kinetic and thermodynamic parameters of their phase and chemical transformations; determination of thermophysical and other properties of substances with a change in temperature, etc. The operation of the analytical tool is based on the use of the differentialthermal method of research of the sample and indifferent substance. It consists of easily dismountable electric furnaces with special holders and cassettes for samples and the standard, a device for linear program temperature control with phase control, a tablet two-coordinate compensation potentiometer for recording thermograms of the samples under study in ΔT-T coordinates. Its operating temperature range is determined by the range of values of the use of chromel-alumel (HA) converters, up to 1300 °C. High metrological characteristics of the complex are ensured by the use of a HA thermocouple in the negative feedback of the temperature control device; a number of circuit and design solutions for its implementation; precision control of the supply of average thermal energy to the heating zone by software setting the proportional to time law of the "sweep" value of the reference voltage of the setter. Depending on the goals of the implemented tasks, the device can be used independently in local systems or in a complex of means during thermoanalytical studies. The development can be used for fundamental scientific research; in production laboratories for rapid analysis of the phase composition of incoming raw materials and finished products, their testing, evaluation of reliability and determination of service life; certificatio n; when establishing functional relationships of the objects under study; clarification of the conditions for synthesis and modification of the properties of modern multifunctional materials for various purposes and other similar purposes.
Copyright (c) 2025 Oleksandr Dryuchko, Natalia Bunyakina, Bohdan Boryak, Ruslan Zakharchenko, Lyudmila Davydenko http://creativecommons.org/licenses/by-nc/4.0
MATHEMATICAL MODEL OF ROLLING STOCK OSCILLATIONS ON A CURVED TRACK SECTION FOR AN ON-BOARD DECISION SUPPORT SYSTEM
From the point of view of the effect that oscillations have on the train movement, the most influential is the process of passing a curved section of the track by the rolling stock. The article deals with the problems associated with dynamic processes during the movement of railway transport along curved sections of track. In particular, the paper analyses the wagging and lateral overrun oscillations, which have a significant impact on traffic safety, passenger comfort and the degree of wear of mechanical components. As a way to mitigate the problem of oscillations, the paper considers supplementing the decision support system with a new software component. As a result of the analysis of modern scientific research, a mathematical model of diesel train movement has been developed that takes into account the peculiarities of passing curved sections of the track. The model allows for the analysis of dynamic characteristics and can be used as a software component in decision support systems for onboard control systems of railway transport in Ukraine. It has been determined that the passage of a curved section of track at high speed significantly affects the safety of further traffic. In this regard, the identification of the critical speed is an urgent task and is the direction of further research.
Copyright (c) 2025 Oleksandr Yevtushenko, Oleksandr Zakovorotnyi http://creativecommons.org/licenses/by-nc/4.0
DESIGN AND ANALYSIS OF AN ELECTROCARDIOGRAM AMPLIFIER FOR DIGITAL SIGNAL PROCESSING SYSTEMS
The subject of the article is an electrocardiogram (ECG) signal amplifier designed for further processing by a pseudo-differential analog-to-digital converter (ADC) in a computer analysis system of cardiac signals. The purpose of the work is to synthesize an ECG amplifier circuit, calculate its key parameters, and simulate its operation in the LTspice software environment. The article solves the following tasks: determining the nature of noise affecting the ECG signal, calculating the resistor that determines the circuit gain, building the amplifier circuit, and its computer simulation. The following methods are used: simulation modeling of processes and technical devices; mathematical analysis of nonlinear electronic circuits (in particular, circuits based on operational amplifiers); analysis of technical documentation of manufacturers of electronic components; computer simulation modeling of electronic circuits. The following results were obtained: an ECG signal amplification circuit compatible with the pseudodifferential ADC AD4010 was proposed, and the ECG signal amplifier was simulated in the LTspice program. Conclusions: The designed ECG signal amplification circuit allows for the removal of common-mode noise with a frequency of 50 Hz and amplifies the input signal by 826 times. The circuit was simulated in the LTspice software.
Copyright (c) 2025 Olha Yeroshenko, Mykhailo Shylenko http://creativecommons.org/licenses/by-nc/4.0
EVALUATION OF POSITIONING ACCURACY FOR A LOW-COST FOUR-WHEELED MOBILE ROBOT WITH OPTICAL MOTION SENSORS
This paper investigates the positioning accuracy of a mobile robot built on a low-cost four-wheeled platform equipped with optical motion sensors. The design of the robot, the control system scheme, and the methodology for determining linear and angular displacements using odometry are described. Primary and secondary positioning errors are analyzed, including their systematic and random components. A calibration procedure was conducted, involving hardware weight balancing, PWM signal adjustments, and refinement of the odometric model through correction coefficients. Logarithmic approximations of the correction factors were constructed for different types of motion. Experimental results confirmed the effectiveness of the proposed approach: relative positioning errors were reduced on average by a factor of 2 to 4. Conclusions are drawn regarding further ways to improve positioning accuracy, taking into account the cost limitations of the hardware platform.
Copyright (c) 2025 Andrij Klyon, Andrii Tretiak, Olexandr Fomin, Sergiy Yastreba, Anatolii Burlakov http://creativecommons.org/licenses/by-nc/4.0
DESIGN MODELS OF BIT-STREAM IRRATIONAL FUNCTION ONLINE-COMPUTER
Topicality. Currently, in distributed real-time control systems it is necessary to ensure continuous reception and processing of information data streams as they arrive. In this case, the current task is to create stream computers that perform functional conversion of signals of sensor components, presented in the form of a pulse stream. The purpose of this work is to develop mathematical and automata design models for a bit-stream online-computer of irrational functions with a pulse (bit) data stream. The object of research is hardware bit-stream computers of irrational functions, the basis of which is the streaming method of calculations. The subject of the study are models and methods for designing bit-stream online-computers of irrational functions. Results. An improved mathematical model of a device for calculating irrational functions using the stepwise approximation method based on inverse functions and an automatic model of the computer based on Moore's finite state machine are proposed. Conclusion. The use of the proposed design models of a streaming computer allows minimizing the absolute error of calculations and increasing the efficiency of device design through the use of developed HDL templates for describing the computer model.
Copyright (c) 2025 Lina Larchenko, Bogdan Larchenko, Tetiana Rozhnova http://creativecommons.org/licenses/by-nc/4.0
SYNTHESIS OF DEDUCTIVE FORMULAS FOR PRIMITIVES
Relevance. Deductive analysis of digital systems and components is the most effective tool for test synthesis, assessing their quality, and diagnosing faults in real time. The essence of deductive modeling is to use synthesis digital subcircuits, which are a necessary hardware addition to the initial functionality, designed to transport incoming fault lists to external outputs. Subcircuits implemented in software or hardware exceed the useful functionality several times. Therefore, the effectiveness of using deductive analysis should be considered from the standpoint of increasing productivity, reducing equipment costs and integral time for designing a digital system and entering the electronic technology market. The purpose of the research is to reduce the time for modeling faults in logic circuits based on the synthesis of deductive functions. The object of the study is modeling faults in digital systems and components. The subject of the study is the deductive analysis of digital systems and components. Results. The study analyzed the main problems that accompany modern fault modeling. The trends of the latest modeling methods were considered. To build a defect modeling sequencer that is invariant to the input test sets, deductive formulas for transporting input fault lists to external outputs for X-functions from a finite number of variables are synthesized. The structure of a deductive simulator of logical X-functions is proposed. The advantages of a deductive simulator of logical X-functions were analyzed.
Copyright (c) 2025 Anna Hahanova, Irina Hahanova, Vladimir Obrizan, Olga Shevchenko, Heorhii Kulak http://creativecommons.org/licenses/by-nc/4.0
MULTI-CRITERIA EVALUATION OF SHIP MODERNIZATION STRATEGIES FOR CO2 EMISSION REDUCTION BASED ON THE TOPSIS METHOD
Relevance. In the context of implementing a decarbonization strategy for maritime transport, the task of selecting the optimal ship modernization strategy becomes particularly relevant. Such a strategy must reduce CO₂ emissions while maintaining economic viability and technical feasibility. Given the diversity of available alternatives—differing in cost, payback period, environmental impact, and risk—a comprehensive decision-making method is required. Object of research: a multicriteria model for evaluating ship modernization strategies. Purpose: to apply the TOPSIS method to determine the most effective ship modernization alternative, taking into account economic, environmental, and engineering factors. Results. The study analyzes five ship modernization strategies. An integrated efficiency indicator was calculated using five evaluation criteria. The analysis results show that the slow steaming strategy presents the most balanced profile. Conclusions. The TOPSIS model proved effective for ranking modernization alternatives based on multiple criteria and can be used to support informed decision-making in sustainable maritime transport project management.
Copyright (c) 2025 Mykola Bulgakov, Oleh Lohinov, Oleksii Melnyk http://creativecommons.org/licenses/by-nc/4.0
PROPOSALS FOR THE ESTIMATING THE REFLECTIVE SURFACE AREA OF AIRCRAFT BASED ON THREE-DIMENSIONAL MODELING SOFTWARE PACKAGES
Relevance. The development of military aircraft, both unmanned and manned, faces an acute challenge to reduce their radar visibility. There are sophisticated software products that can calculate the effective scattering surface of an aircraft of any shape with great accuracy. However, they are united by the demand on computing resources when modeling a radio signal reflected from a complex aircraft shape. Such demandingness leads to large time costs when it is necessary to iteratively change the shape of the aircraft. Object of research: the process of estimating the effective scattering surface of aircraft using three-dimensional modeling. Purpose: development of proposals for the use of three-dimensional modeling software packages for quick and approximate estimation of the area of aircraft surfaces that reflect electromagnetic radiation for a preliminary assessment of their visibility in the radar range. Research results. To reduce the cost of computing resources and quickly estimate the surface area of aircraft, its simplified form of the model is used, which reduces the accuracy of calculations. The paper substantiates the use of three-dimensional modeling packages, for example, Blender 3D, an open source software, to study radar reflection from an aircraft model, based on the methods and assumptions of geometric optics. Conclusions. The use of three-dimensional modeling packages for preliminary and rapid acquisition of the aircraft shape is relevant at the preliminary design stage. The use of various surface shaders for a three-dimensional aircraft model is necessary to simulate the refraction, reflection, and absorption of radio waves.
Copyright (c) 2025 Yevhenii Tolkachenko, Oleksii Kolomiitsev, Serhii Osiievskyi, Artem Samokish, Volodymyr Panchenko http://creativecommons.org/licenses/by-nc/4.0
PHYSICAL MECHANISMS OF CREATION OF TECHNICAL LEAKAGE CHANNELS ACOUSTIC INFORMATION
Relevance. Physical processes occurring in technical devices and systems create side electromagnetic and acoustic radiation in the surrounding space. Accordingly, to develop effective methods and means of information protection, it is necessary to understand the physical foundations of the creation of the specified side radiation. Object of research: physical processes leading to the appearance of technical channels of acoustic information leakage. Purpose of the article: to consider the physical mechanisms of creating technical channels of acoustic information leakage and measures to prevent these information leaks. Research results. The work revealed that acoustic and acousto-vibrational channels of information leakage are formed as a result of the propagation of acoustic waves in diffusive and elastic environment, respectively. Acoustoelectric channels of information leakage are formed as a result of the parasitic transformation of acoustic signals into electric ones on the elements of electronic devices. Acousto-optoelectronic channels are formed by removing the surface’s oscillations of engineering or building constructions. Channels of high-frequency binding are formed as a result of radiation by conductive elements of a modulated high-frequency signal. Conclusions. Thus, the physical mechanisms of creating technical channels for the leakage of acoustic information at the object of information activity were clarified and means of protection against them were considered. In particular, a common means of protection for all these channels of acoustic information leakage is the use of acoustic, vibration and linear noise at the object of information activity.
Copyright (c) 2025 Ali Al Ammouri, Ruslan Ishchenko, Petro Dyachenko, Ivan Nimych http://creativecommons.org/licenses/by-nc/4.0
METHOD FOR DETECTING ANOMALIES IN CORPORATE NETWORKS
The relevance of this study lies in the fact that existing anomaly detection methods often demonstrate insufficient accuracy and responsiveness in real-world operational environments. The object of research: the network traffic of a corporate information system, which is analyzed to detect abnormal behavior potentially indicating cyberattacks, security policy violations, or internal threats. Purpose of the article: the development, implementation, and experimental validation of an anomaly detection method for corporate networks based on an autoencoder model, which makes it possible to effectively identify deviations from normal network traffic without the need for pre-labeled data. Research results. In the modeling process, synthetic data simulating both typical and anomalous network activity was generated. Histograms and boxplots indicate that normal samples are characterized by low and stable mean squared error values, while anomalous samples demonstrate significant deviations. The ROC curve with AUC = 1.00 confirms that the model can reliably distinguish between the two categories. The confusion matrix showed a nearly perfect match between predicted and actual labels, indicating high accuracy and sensitivity of the model. The training curve demonstrates stable learning without overfitting, and the selected dynamic threshold minimized the false positive rate. The proposed approach can be integrated into security monitoring systems to detect atypical activities in real time. Conclusions. The conducted experiments demonstrated high classification accuracy, clear separation between normal and anomalous samples based on reconstruction error, and stable model training. The obtained results confirm the feasibility of using deep learning for automated network security monitoring, and the proposed method can be successfully applied in real corporate IT infrastructures to detect security incidents in real time.
Copyright (c) 2025 Yelyzaveta Hloba, Vladyslav Smirnov, Mykola Naraievskyi, Volodymyr Fedorchenko http://creativecommons.org/licenses/by-nc/4.0
ADVANCED PACKAGING TECHNOLOGIES FOR INTEGRATED CIRCUITS
Relevance. Given the global surge in demand for advanced semiconductor solutions, improving advanced packaging technologies is strategically important for the electronics industry. The purpose of this work is to analyze current trends and major challenges associated with advanced IC packaging technologies to support the selection of optimal chiplet interconnect testing models. The object of study is IC layout and packaging technologies. The subject of study includes technological solutions and design features of advanced IC packaging and layout. These include 2,5D integration, which enables ultra-high interconnect density, such as silicon interposer-based integration (CoWoS) and embedded multi-die interconnect bridge (EMIB). The study also considers materials and related technological processes that contribute to the creation of effective interconnects. Results. The study analyzes the key issues that accompany modern packaging technologies, including parasitic electrical characteristics, thermal loads, and mechanical stress, all of which can affect IC longevity and performance. It examines the advantages and drawbacks of advance packaging methods, particularly 2,5D integration technologies, which significantly improve component integration density, reduce electrical interconnect lengths, and enhance heat dissipation. A basic implementation of CoWoS and EMIB structures in Verilog hardware description language is presented as a starting point for building more complex simulation models.
Copyright (c) 2025 Oleg Demchenko, Svetlana Chumachenko http://creativecommons.org/licenses/by-nc/4.0
EVALUATION OF DATA TRANSMISSION EFFICIENCY IN AN ATMOSPHERIC-OPTICAL COMMUNICATION LINE BASED ON SINGLE-MODE MULTIFREQUENCY LASER RADIATION WITH SYNCHRONIZATION OF LONGITUDINAL MODES
The object of study of this paper is atmospheric-optical communication lines with the organization of data transmission based on single-mode multifrequency synchronized longitudinal laser radiation modes. The aim of this work is to present the results of evaluating the efficiency of data transmission in an atmospheric-optical communication line based on single-mode multifrequency synchronized longitudinal laser radiation modes by various indicators. An atmospheric-optical communication line is proposed, the main elements of which include separation of carrier frequencies from the spectrum of single-mode multi-frequency laser radiation with synchronization of longitudinal modes by means of a channel shaping device that allows the use of separate longitudinal modes; conversion of electrical information signals into a form suitable for modulation with carrier frequencies, followed by their modulation by amplitude, intensity, frequency, phase, or polarization; optical processing and transmission of the group combined optical signal through the communication line to the receiver, where it is focused, converted into an electrical information signal and further processed to extract data and transmitted to consumers. The obtained results of mathematical modeling make it possible to evaluate the capabilities of the laser radiation transmitter by various indicators and indicate that the proposed atmospheric-optical communication line with the organization of data transmission based on single-mode multifrequency with pulse synchronization.
Copyright (c) 2025 Oleksii Liubchenko http://creativecommons.org/licenses/by-nc/4.0
METHODS OF DATA PROCESSING AND ANALYSIS IN A CORPORATE NETWORK
Relevance . The relevance of studying methods of data processing and analysis in corporate networks is driven by the rapid development of information technologies, the growing volume of corporate data, and the need for prompt and accurate analysis to support effective decision-making. The importance of such methods is also linked to the challenges of ensuring cybersecurity in corporate networks, particularly the protection of information at all stages of its processing and transmission. The quality of the technologies and methods applied to data handling affects a company’s performance, competitiveness, and ability to adapt to rapidly changing market conditions. Therefore, systematizing knowledge about the most effective methods of working with corporate data remains a relevant task for both modern science and practical applications. The object of research is data processing processes within corporate networks, including the collection, transmission, storage, filtering, analysis, and protection of information circulating within the information and communication infrastructure of a modern enterprise. These processes are considered in the context of their impact on the efficiency of the corporate information system, data security, support for managerial decision-making, and integration with analytical and cloud platforms. Purpose of the article is to investigate the main stages and methods of data processing and analysis in the corporate environment, including data collection, preprocessing, storage, analytical evaluation, and information security, as well as to analyze modern tools and platforms that ensure efficient and secure data handling at the scale of a large organization. Research results. During the study, a comprehensive analysis of the stages and methods of data processing in the corporate environment was conducted. A systemic model of the corporate data lifecycle was established, covering all key stages – collection, preprocessing, storage, analytics, and protection. Each of these stages requires the application of a specific class of technologies and presents its own implementation challenges. Tools for data collection and preprocessing were classified, with ETL processes, logging, aggregation technologies, sampling, and normalization playing an important role in ensuring data cleanliness and suitability for further analysis. Modern data storage platforms were analyzed, including cloud-based (Azure, AWS, GCP) and on-premises solutions. The effectiveness of using OLAP and machine learning in analytical processing was evaluated. The role of information security in corporate networks was addressed. The necessity of implementing cryptographic protection, access control, as well as anonymization and masking mechanisms was demonstrated as a response to the risks of data loss or compromise. Conclusions. Modern methods of data processing in corporate networks have been examined, covering the stages of data collection, preprocessing, storage, analytics, and information security. It has been established that effective data management is achievable only through a comprehensive approach that combines technical tools, software platforms, and security policies. Particular attention was given to the use of cloud technologies, ETL tools, OLAP analytics, and machine learning algorithms. The importance of cryptographic protection, anonymization, and access control was emphasized. The obtained results can be applied to improve the efficiency of enterprise information systems and to implement analytical solutions in business practice.
Copyright (c) 2025 V. Rossikhin, Y. Tarapata, O. Iashchenko http://creativecommons.org/licenses/by-nc/4.0
IMPROVING THE EFFICIENCY OF THE FIRE CODE FOR COMBATING SHORT PULSE INTERFERENCE
Relevance. In modern telecommunications networks, it is extremely important to effectively protect information from short impulse noise, which can cause local packet errors. Such noise is particularly characteristic of environments with high levels of electromagnetic noise (e.g., IoT, power cables, satellite communications). To counteract such types of failures, it is advisable to use specialized codes, in particular the Fire code, which has a high ability to detect and correct sequential bit errors of fixed length. Research object: the Fire code in data transmission systems with impulse interference. Purpose of the article: to analyze the effectiveness and study the Fire code, optimize and improve the code's effectiveness using the proposed methods of generating polynomial optimization, hybrid coding, adaptive coding, and parallel processing. Research results. The article proposes and tests methods for improving the efficiency of the Fire code in conditions of impulse noise. A comparison of the probability of correct decoding for different methods was carried out. A comparison of processing delay and computational complexity was performed. The results of the analysis clearly demonstrate the advantages of the proposed methods for optimizing the Fire code, confirming their effectiveness in increasing the probability of correct decoding and reducing processing delay. The proposed methods were implemented in a prototype data transmission system. The results showed a reduction in the probability of decoding errors to 35% compared to the baseline code. Conclusions. Analysis of the Fire code confirmed its effectiveness in combating short impulse noise, but revealed limitations at high noise intensities and high computational complexity. The proposed optimization methods significantly improved the code's performance. The improved Fire code provides increased noise immunity in telecommunications networks, which allows it to be recommended for use in networks with strict transmission quality requirements.
Copyright (c) 2025 Oleksandr Shefer, Oleksandr Yevdochenko http://creativecommons.org/licenses/by-nc/4.0
FEATURES OF DETECTING ACADEMIC IMAGE PLAGIARISM
The rapid growth of visual content in academic documents highlights the issue of detecting academic image plagiarism. Unlike textual plagiarism, which is effectively identified by modern systems, visual plagiarism remains a challen ging task due to the diversity of its manifestations and the potential for manipulation. The aim of this work is to analyze existing approaches to image recognition and comparison for detecting academic plagiarism and to identify key features. The study examines computer vision algorithms, deep learning models, and other technologies for analyzing textual elements within images. A classification of visual plagiarism forms is proposed, including exact copying, affine transformations, semantic duplication, and image generation. The main features are identified: extensive possibilities for manipulation and specific forms of visual content representation, lack of a global image database, difficulty in extracting non-textual content, and legal restrictions on access to full texts. Conclusions: Image analysis for detecting academic plagiarism remains a relevant and promising research direction, which can be implemented through the following avenues: improving modification detection algorithms and integrating visual analysis into textual plagiarism detection systems, creating image repositories, and ensuring the availability of informational tools for experts and researchers.
Copyright (c) 2025 Yuliia Hlavcheva, Maksym Glavchev http://creativecommons.org/licenses/by-nc/4.0
ANALYSIS OF MATHEMATICAL MODELS OF RANDOM GRAPHS
Relevance. In the modern world, the majority of social, biological, technological, and communication processes occur in the form of complex network structures. The analysis of such systems requires the construction of mathematical models capable of adequately describing their topology, stochastic nature, and dynamic properties. One of the most powerful tools for this is the theory of random graphs, which enables the modeling of a wide range of real-world phenomena – from the spread of viruses and information to the functioning of critical infrastructures. Classical models, particularly the Erdős-Rényi model, laid the foundation of modern graph theory; however, they have limitations in describing networks with high clustering or uneven degree distributions. Therefore, in recent years, modern approaches have gained special significance, including small-world models, which reflect the properties of real social and biological systems with short paths and a high level of clustering, and scale-free graphs, which model networks with heterogeneous degree distributions. The relevance of this topic is due to the need to select and analyze an appropriate mathematical model that can accurately represent the properties of real networks, enable justified prediction of their behavior, identify vulnerabilities, and optimize the functioning of complex systems. In this context, the analysis of mathematical models of random graphs is an important area of modern applied mathematics, computer science, and systems theory. The object of research: Random graphs as mathematical structures that model the topology and dynamics of complex networked systems. Purpose of the article: Research, systematization, and comparative analysis of mathematical models of random graphs to determine their suitability for modeling various types of complex networked systems. Research results. The article presents an analysis of mathematical models of random graphs that underpin modern network science. Beginning with the theoretical foundations of graphs, both classical and contemporary models for constructing random networks are examined, alongside methods of their analysis and practical areas of application. The methods of analysis are critically important for the practical use of random graphs, as they enable the models to be applied to forecasting, diagnostics, and the management of complex systems. These methods also provide a foundation for integrating mathematical models with real-world data, which is a key objective of contemporary network science. Classical models allow for the formalization of randomness in network connections; however, they have significant limitations in capturing the real topological properties of complex networks – particularly high clustering, degree heterogeneity, and growth mechanisms. In contrast, modern models correspond much more closely to the structure of real-world systems. They make it possible to model such essential features as the emergence of hubs, clustering, short average path lengths, and robustness to failures. Conclusions. Mathematical models of random graphs are a universal tool for the analysis and synthesis of various networked systems. Their application allows not only for the formal description of a complex system’s structure, but also for the discovery of its hidden patterns, the prediction of its behavior under different conditions, and the optimization of its functioning while accounting for real-world constraints.
Copyright (c) 2025 Valeriy Gorbachov, Vitalii Fedorov http://creativecommons.org/licenses/by-nc/4.0
CLASSIFICATION OF NETWORK ATTACKS USING MACHINE LEARNING METHODS IN CONDITIONS OF TRAINING DATA IMBALANCE
The object of the research is the process of detecting network intrusions. The subject of the research is methods for classifying network intrusions. The aim of the research is to improve the quality and speed of ensemble classifiers in network intrusion classification problems under conditions of imbalance in training data. Methods used: machine learning methods, data preprocessing methods, ensemble classifiers, rebalancing method by synthetic minority augmentation. Results obtained: the effectiveness of using various approaches for classifying network intrusions under conditions of class imbalance in the training sample was investigated. A comprehensive approach was proposed, which involves preprocessing data using the SMOTE method for synthetic balancing of the training sample, as well as its subsequent analysis using ensemble machine learning models, which made it possible to improve the classification performance of minority classes. The best results were obtained when combining SMOTE with ensemble models, in particular Bagging, Gradient Boosting and AdaBoost. Conclusions. Based on the results of the study, an improved approach to network traffic classification was proposed, which combines pre-sampling by the SMOTE method with ensemble algorithms bagging and boosting. The combined use of these methods allowed to improve the value of the Recall metric for minority classes. Overall, the proposed approach provided an improvement in the classification quality: 18% for the Infiltration attack, 33% for the SQL Injection attack and up to 53% for the XSS attack compared to basic machine learning models without additional rebalancing of input data.
Copyright (c) 2025 Oleksii Hornostal, Viktor Chelak http://creativecommons.org/licenses/by-nc/4.0
NEURAL ARCHITECTURE COMPARISON FOR FACT VERIFICATION ON FEVER DATASET
The exponential growth of misinformation and fake news across digital platforms poses unprecedented challenges to information integrity, requiring sophisticated automated fact-checking systems capable of verifying claims against reliable evidence sources with high accuracy and computational efficiency. This study aims to evaluate and compare four hybrid neural architectures (BiLSTM-CNN, BiLSTM-RNN, BiLSTM-GRU, and BiLSTM-GNN) for automated fact verification using the FEVER dataset, investigating their effectiveness in claim-evidence verification under GPU memory constraints while analyzing training dynamics and generalization capabilities. The following results are obtained: The BiLSTM-CNN architecture achieved optimal performance with 79.5% accuracy, 79.5% recall, 77.9% F1-score, and 93.4% AUC-ROC, followed by BiLSTM-GNN (78.9% accuracy, 93.3% AUC-ROC) and BiLSTM-GRU (77.9% accuracy, 92.2% AUC-ROC), while BiLSTM-RNN exhibited catastrophic failure (33.3% accuracy). All successful architectures demonstrated significant overfitting with 15-17% train-validation accuracy gaps, indicating systematic generalization challenges with limited training data (40,000 samples). Conclusion. Multi-kernel convolutional feature extraction proves most effective for local pattern recognition in fact verification, while graph-inspired approaches show promising potential for relational reasoning. The consistent overfitting across architectures highlights the critical need for enhanced regularization, data augmentation, and ensemble methods to achieve robust performance in automated fact-checking systems under computational constraints.
Copyright (c) 2025 S. Datsenko http://creativecommons.org/licenses/by-nc/4.0
THE ROLE OF THE COURSE "INTRODUCTION TO THE SPECIALTY" IN SHAPING THE PROFESSIONAL IDENTITY OF INFORMATION TECHNOLOGY STUDENTS
The article explores the significance of the academic course "Introduction to the Specialty" in shaping the professional identity of students pursuing education in the field of knowledge F "Information Technology." Given the dynamic development of digital technologies, the growing role of the IT sector in the global economy, and the high level of competition in the labor market, not only professional training but also the formation of internal motivation, value-based attitudes toward the chosen profession, professional self-determination, and student reflection becomes increasingly important. The article analyzes conceptual approaches to defining the notion of "professional identity" in psychology and pedagogy, revealing its structure and the factors influencing its development among young people choosing the IT sphere. It emphasizes that professional identity encompasses not only knowledge and skills but also internal acceptance of oneself as a member of the IT community, readiness for professional interaction, adherence to ethical standards, independent decision-making, and personal development within the context of technological progress. Special attention is given to the content and structure of the course "Introduction to the Specialty," which, on one hand, serves an introductory and adaptive function, and on the other–aims to foster initial professional motivation, students’ understanding of their future professional activity, industry standards, employer expectations, employment prospects, and the development of soft skills, critical thinking, and a responsible attitude toward learning. Within the course, students become familiar with the history of IT development, the evolution of specialties, key directions and trends in modern information technologies, and examples of IT applications across various life spheres. It is established that the use of active learning methods (training sessions, project activities, business games, case analysis), the involvement of industry professionals from IT companies in teaching, the implementation of mentoring elements, and the individualization of educational paths actively promote the formation of professional identity even at the early stages of study. The article also highlights the importance of academic integrity, digital culture, and media literacy as integral components of the professional identity of modern IT specialists. The article presents the results of a first-year student survey, confirming the course’s positive impact on self-awareness of the future specialist role, increased motivation for learning, and the formation of an understanding of the professional competencies that need to be developed. In conclusion, the author emphasizes the need for methodological updates to the course content in line with changes in the professional environment, the implementation of an interdisciplinary approach, partnerships with IT companies, and the development of individual educational trajectories. The key conclusion is that the "Introduction to the Specialty" course is not only an important part of the curriculum but also a strategic tool for forming professional identity, supporting both the personal and professional development of future IT professionals.
Copyright (c) 2025 Tetyana Derkach, Maria Boyko, Vladislav Yastreba http://creativecommons.org/licenses/by-nc/4.0
DATA PROCESSING METHODS IN A CORPORATE NETWORK
Relevance. In the context of modern digital business transformation, corporate networks have become critically important components of enterprise information infrastructure, integrating numerous systems, devices, and services into a unified information environment. Every day, vast volumes of data are generated, transmitted, stored, and processed within these networks, encompassing all aspects of organizational activity – from financial operations and logistics to customer communications and internal management processes. The successful functioning of a corporate network is impossible without effective data processing, which enables the extraction of valuable insights from raw data, supports strategic decision-making, ensures information security, and optimizes resources. Amid intense competition, the rapid growth of information flows, and increasing demands for swift decision-making, data processing methods play a crucial role in enabling the analytical capabilities of enterprises. Data processing methods in corporate environments find applications across diverse business sectors. In the financial domain, they are used for transaction analysis, risk management, market fluctuation forecasting, and fraud detection. In logistics, they support route optimization, warehouse stock control, and real-time supply coordination. In marketing, they facilitate customer behavior analysis, audience segmentation, and personalized communication. In HR departments, they assist in employee performance evaluation and candidate selection. In healthcare, they support patient data analysis, service process optimization, and clinical decision-making. Furthermore, data processing forms the foundation for the development of artificial intelligence systems, digital twins, cybersecurity solutions, and automated enterprise management. Traditional approaches to data processing are gradually being replaced by advanced technologies based on Big Data, real-time stream processing, cloud computing, intelligent data analytics, and machine learning. In this context, issues related to data protection, integrity, availability, and compliance with legal and regulatory requirements for confidentiality gain particular importance. The purpose is to analyze modern methods and technologies for data processing in corporate networks, identify their advantages, disadvantages, and application areas, and classify approaches to data collection, cleansing, storage, and analysis. The object of research is enterprise corporate networks. The subject of research includes methods and technologies for data processing, storage, analysis, and protection. The results. As a result of the conducted research, a comprehensive understanding of modern data processing methods in corporate environments was formed. The architectural models of enterprise information systems were analyzed, key stages of data preparation identified, and approaches to their processing – from classical to intelligent – were characterized. The review revealed a wide range of data processing techniques, from traditional SQL queries and multidimensional analysis to real-time processing and machine learning applications. The choice of a particular approach depends on data volume, data inflow speed, latency sensitivity, and the specific goals of processing.
Copyright (c) 2025 Dmytro Diachenko, Matvii Korobeinikov, Oleksandr Korobeinikov, Andriy Kovalenko, Pavlo Kravchenko http://creativecommons.org/licenses/by-nc/4.0
INTELLIGENT WEB SYSTEMS FOR AUTOMATION OF PROCESSING AND MONITORING OF INFORMATION FLOWS
In the conditions of rapid growth of digital data and information flows on the Internet, there is a growing need for automated methods of their processing and monitoring for effective data acquisition and making informed conclusions. In order to cope with this data flow, intelligent web systems are being created. They use artificial intelligence (AI), machine learning (ML) and other advanced technologies to automatically collect, analyze and present information. The main purpose of this article is a comprehensive review of intelligent web systems aimed at automating the processing and monitoring of information flows. The theoretical foundations of such systems are considered, including semantic technologies and artificial intelligence methods, as well as modern approaches to text recognition and analysis based on deep learning. An analysis of modern approaches to automated text recognition (OCR and deep learning methods) and modern server infrastructure monitoring tools is presented. A conceptual model of integration of components of text processing systems and infrastructure monitoring is proposed. Key challenges and limitations of this approach are highlighted, and promising directions for further research are outlined.
Copyright (c) 2025 Vladyslav Zaika, Oleh Chuiev, Olga Morozova, Tetyana Nikitina http://creativecommons.org/licenses/by-nc/4.0
METHODOLOGY FOR AUTOMATED ASSESSMENT OF THEMATIC RELATEDNESS OF SCIENTIFIC PUBLICATIONS USING SEMANTIC ANALYSIS
Relevance. Automated assessment of thematic relatedness between doctoral theses and profiles of potential experts is needed for transparent and reproducible selection of official reviewers and composition of one -time specialized councils; the open NAQA.Svr data make such assessment technically feasible. Object of research: methods and tools for constructing semantic profiles of theses and researchers and for ranking them in a shared vector space. Purpose of the article. To develop and empirically validate a methodology for automated assessment of thematic relatedness of scientific publications based on semantic analysis. Research results. We assembled a corpus of 259 theses, 662 researcher profiles, and 3345 publications; texts were normalized, and publication titles were standardized using a large language model. Semantic representations were obtained with an OpenAI model. We compared two variants of thesis profiling (full description; keywords only) and two variants of researcher profiling (by publications; by keywords). Quality was evaluated against actual reviewer assignments using the metrics NDCG, Hit@k, and NDCG-lift. The best results were consistently achieved by the combination “thesis by keywords” and “researcher by publications,” which yields the highest top-rank accuracy and the largest gain over random selection. Conclusions. Combining a keyword-based thesis profile with a publication-aggregated researcher profile provides the best balance of accuracy and robustness and is practically suitable for preliminary reviewer selection. The proposed methodology is reproducible, scalable, and aligned with open data; promising directions include incorporating temporal weights of publications, handling bilingual terminol ogy, and accounting for procedural constraints in final assignments.
Copyright (c) 2025 Oleksandr Ivaniuk http://creativecommons.org/licenses/by-nc/4.0
REQUIREMENTS FOR MODERN PROCESSORS FOR SECURE OPERATION OF INFORMATION SYSTEMS AND NETWORKS
The article considers the main requirements for the technical support of computer architecture for the security of information systems and networks. It is proved that the problem of information protection requires the organization of a whole complex of special protection measures to prevent the loss of information contained in its transmission channels. The possibilities and consequences of abuse of information transmitted through telecommunications channels, which are developing and improving intensively, have been identified, and means of their prevention have been investigated. Thus, today there is a modern technology for protecting information transmitted via telecommunications channels, the sphere of influence of which includes not only communication channels, but also switching centers, peripheral devices, terminals, communication administrators, local computer networks, etc. It is justified that the analysis of requirements for modern technical and software components, among which the leading place should be given to the processor, is in the focus of our research. The consequences of non-compliance with the proposed requirements for the technical support of the computer architecture, which is a potential threat and a possible catalyst for the danger of information systems and networks, are investigated. The feasibility of implementing special tools, methods, and measures to prevent information loss has been established. It was determined that a thorough analysis requires studying the components of the set of recommendations for optimizing processor selection, based on the components and requirements for the security of information systems and networks, which are not sufficiently considered in the publications of domestic and foreign scientists. An analysis of processors included in the rating of the best models in recent years according to various criteria was performed, and the problem of choosing the optimal processor to meet the need for ensuring information security in the network was studied. Advice and recommendations on their selection for the security of information systems and networks are presented in numerous studies. Ways of improving the system are proposed, which are important to consider when modernizing the existing system in order to enable further updating of its components.
Copyright (c) 2025 Alla Kapiton , Tamara Franchuk , Dmytro Tyshсhenko , Alona Desiatko , Rostyslav Zakharov http://creativecommons.org/licenses/by-nc/4.0
METHODS FOR ANALYZING SOFTWARE SOURCE CODE
Relevance . The study of methods for analyzing source code is driven by several current trends in the field of software engineering. On the one hand, the increasing complexity and scale of software solutions necessitate the enhancement of software quality and stability. On the other hand, the growing frequency of cyber threats demands greater attention to the security of source code. Modern software systems are involved in critical areas such as financial operations, healthcare, industrial automation, and infrastructure management. Errors and deficiencies in such systems can lead to serious consequences, including significant economic losses, failures in the operation of essential services, and even threats to human life. In an environment of intensifying competition and rapid digitalization, software quality has become a key factor in the success of companies in the market. The implementation of effective source code analysis methods is becoming essential not only for large enterprises, but also for small and medium-sized businesses seeking to develop reliable and secure software solutions. Emphasis should be placed on the promising potential of integrating modern technologies of artificial intelligence and machine learning into the process of code analysis. Such approaches enable the automatic detection and classification of errors, which significantly reduces the time required for their identification and resolution, while also improving the accuracy and efficiency of the analysis. Thus, the development and deepening of research in the field of source code analysis methods is a vital task of modern software engineering, as it enables the resolution of urgent challenges related to software quality assurance and system security. The object of research. the source code of software is considered a structure subject to formal, semantic, and behavioral analysis, aimed at identifying errors, vulnerabilities, architectural flaws, and violations of coding standards. Purpose of the article. The study focuses on existing methods of source code analysis, particularly static and dynamic approaches, their tool support, and the prospects of applying modern technologies, especially artificial intelligence, to enhance the efficiency of error detection, and to ensure the quality, reliability, and security of software code throughout all stages of the software development lifecycle. Research results. The classification of software source code analysis methods has been systematized, including static, dynamic, hybrid, and intelligent approaches. A comparative analysis of static and dynamic techniques has been conducted based on key criteria such as efficiency, error coverage, resource intensity, and applicability at various stages of the software development lifecycle. Typical categories of errors detectable through dynamic analysis have been identified, including memory leaks, resource access errors, and performance issues. The potential of intelligent tools, particularly neural network-based models such as code2vec and VulLibMiner, has been examined for automated analysis and vulnerability prediction. The feasibility of a comprehensive approach that integrates both static and dynamic analysis has been substantiated as the most effective strategy for ensuring the quality and security of software systems. Conclusions. Static analysis is effective for early error detection and ensuring code compliance with established standards. Dynamic analysis is essential for identifying runtime errors such as memory leaks and race conditions. Neither method is universal; the best results are achieved through their combination. Intelligent approaches (AI/ML) significantly enhance the automation and accuracy of code analysis. The comprehensive implementation of code analysis contributes to the development of secure, high-quality, and maintainable software.
Copyright (c) 2025 S. Kuzhel , A. Lytvynov , O. Pliekhov http://creativecommons.org/licenses/by-nc/4.0
METHOD OF OPTIMAL LOCATION OF AUGMENTED REALITY OBJECTS
The object of the study is the process of arranging augmented reality objects in physical space, which is limited in size. The subject of the study is algorithms for the optimal arrangement of augmented reality objects in physical space of finite size. The purpose of the article is to develop a method for the optimal arrangement of augmented reality objects. The following results were obtained. An approach to the formation of the optimal perceptual distance is determined. A mathematical model is developed that allows you to determine the quantitative indicators of two main optimality criteria. An approach to determining the distance between AR objects and the boundaries of the real plane is proposed. The proposed algorithm for the optimal arrangement of augmented reality objects is based on this approach. Conclusions. A method for the optimal arrangement of AR objects is proposed, consisting of a mathematical model, determination of distances to the boundaries of the plane of the real object and the corresponding algorithm. The method allows you to vary the changes of the virtual object in real time.
Copyright (c) 2025 Heorhii Kuchuk, Dmytro Lysytsia, Dmytro Irkha, Dmytro Kyrylenko http://creativecommons.org/licenses/by-nc/4.0
TOOLS AND METHODS FOR EXPLOSIVE OBJECTS DETECTION USING ARTIFICIAL INTELLIGENCE AND COMPUTER VISION
Relevance. The problem of detecting explosive ordnance remains one of the most acute in the modern world and in Ukraine, in particular due to the growing number of armed conflicts and contamination of territories with landmines and unexploded ordnance. Traditional methods of demining are time-consuming, dangerous, time-consuming and not always effective, necessitating the introduction of innovative technologies based on artificial intelligence and computer vision. Object of research. The object of research is intelligent tools and methods for detecting explosive objects, in particular the proposed prototype combining deep learning (YOLOv8) and robotic platforms for real time. Purpose of the article. The article is aimed at analyzing existing solutions, developing and experimentally testing an efficient, portable system for automated mine detection using lightweight deep learning models capable of operating on mobile devices in a variety of environmental conditions. Research results. Two specialized datasets covering different types of mines (POM-2, POM-3, PMA-2 "starfish") and various environmental conditions, soil types, weather factors and the presence of obstacles were used, modernized and annotated in the work. To speed up the training of the AI models, distributed and parallel computing are applied. The YOLOv8-nano and YOLOv8-small models demonstrated high precision (up to 98.8%) and recall for major landmine classes, which was confirmed by the analysis of confusion matrices and key metrics. The focus is on the development and research of a prototype system for automated landmine detection based on deep learning and computer vision, integrated with robotic platforms and unmanned aerial vehicles. The system provides real-time operation (2-2.6 frames per second) on mobile devices, has a simple architecture and the ability to integrate with robotic and unmanned platforms. Conclusions. The proposed system is promising for humanitarian demining due to its high accuracy, mobility and ease of deployment. At the same time, the results of the experiments indicate the need for further improvement of models to increase resistance to changes in environmental conditions and reduce the number of false positives. The implementation of such solutions will contribute to increasing the efficiency and safety of demining in post-conflict regions.
Copyright (c) 2025 Denys Levchenko, Andrii Podorozhnyak, Nataliia Liubchenko http://creativecommons.org/licenses/by-nc/4.0
ADAPTIVE FILTERING AND DYNAMIC COMPUTATION OFFLOADING FOR RESILIENT TASK EXECUTION IN IIOT
Relevance. The execution of time-sensitive tasks in Industrial Internet of Things (IIoT) systems requires decentralized and fault-tolerant computing models that can operate under dynamic workloads, unstable node availability, and limited resources. Object of research: task management and offloading processes in edge–fog IIoT environments. Purpose of the article. Development of a method for decentralized, latency-aware task processing using adaptive filtering and dynamic computation offloading, which ensures high availability, efficient resource usage, and responsiveness in distributed edge systems. Research results. The paper presents the AFDCO method, which integrates local data filtering, node availability evaluation, latency-based offloading, and lightweight redundancy into a unified framework. This approach enables autonomous and fault-resilient task execution without relying on centralized controllers. Simulation results confirm that AFDCO reduces response time, improves task deadline compliance, and minimizes network and energy overhead. Conclusions. Compared to static or centralized task allocation models, the proposed method demonstrates better adaptability and robustness under variable conditions by dynamically adjusting execution and replication strategies based on system feedback. Scope of application of the obtained results: distributed IIoT systems, edge–fog computing platforms, and lowlatency industrial automation scenarios requiring decentralized execution and fault recovery.
Copyright (c) 2025 Eduard Malokhvii http://creativecommons.org/licenses/by-nc/4.0
SYSTEM FOR SIMULATION OF OVERCOMING OBSTACLES AND ORGANIZING COMMUNICATIONS IN HAZARDOUS ENVIRONMENTS: STRUCTURE AND EXPERIMENTAL EVALUATION
The paper presents a comprehensive simulation system for overcoming obstacles and organizing communications in hazardous environments using UAV swarms. The proposed models of environment, obstacles, dynamic influences, and UAVs enable the reproduction of scenarios in destroyed or hard-to-reach indoor areas, considering static and dynamic objects as well as cyber-physical impacts. The simulator architecture is implemented in Python with the Panda3D engine and integrated with data collection and analysis tools (InfluxDB, Grafana, Docker), providing flexible configuration of parameters and reproduction of diverse scenarios. The paper presents experimental results demonstrating the efficiency of routing algorithms (A*, Greedy BestFirst, etc.) and swarm coordination for deploying a Li-Fi-based communication chain. It is shown that the system serves as a valuable research and training tool for testing algorithms, analyzing swarm reliability, evaluating energy efficiency, and resilience to cyber impacts. Future development perspectives include integration with ROS, extension of the sensor library, and modeling of network-level communication protocols.
Copyright (c) 2025 Leonid Ostapenko, Vyacheslav Kharchenko http://creativecommons.org/licenses/by-nc/4.0
OPTIMIZATION OF 1-BIT QUANTIZED MATRIX MULTIPLICATION FOR LARGE LANGUAGE MODELS
With the rapid development and improvement of artificial intelligence systems, natural language processing has recently become one of the most relevant and in-demand tasks. Tools and algorithms based on large language models (LLMs) that enable natural language processing and speech-to-text conversion are actively used for automating various everyday tasks, as well as for service systems and real-time human interaction. Efficient and accurate natural language processing, taking into account syntactic and linguistic peculiarities, requires highly complex language models. However, large language models demand significant memory and computational resources, making their widespread use challenging on resource-constrained devices such as battery-powered mobile devices, embedded systems, and Internet of Things (IoT) devices. Thus, optimizing language model algorithms and reducing hardware costs for their deployment is an increasingly pressing issue. To accelerate execution and minimize memory requirements, quantization algorithms for language model parameters are employed. This work formulates key challenges associated with performing quantized matrix multiplication operations, explores popular approaches to implementing matrix multiplication algorithms on GPUs, and presents an optimized high-performance kernel for 1-bit quantized matrix multiplication.
Copyright (c) 2025 Dmytro Salnikov, Oleg Vasylchenkov, Dmytro Karaman http://creativecommons.org/licenses/by-nc/4.0
INFORMATION TECHNOLOGIES FOR CREATING MUSIC AND GAME PROJECTS: BIBLIOMETRIC ANALYSIS
Relevance. The development of information technology (IT) is contributing to the emergence of new forms of creative interaction, in particular in the field of music and gaming projects that combine music, game mechanics, and digital technologies. The integration of IT into such products creates innovative opportunities for learning, rehabilitation, and entertainment, which makes it necessary to systematize knowledge in this area. Object of research: scientific publications on the use of information technology for the implementation of music and gaming projects. Purpose of the article. to identify publications that form knowledge about modern IT for creating music and game projects. Research results. The article conducts a bibliometric analysis of 414 documents from the Scopus database using the query “music AND game AND projects” (1995-2025). The article identifies 24 subject areas grouped into six branches of knowledge. It was found that the majority of publications belong to computer science. The keywords are analyzed and structured into four semantic clusters: music game development technologies, educational multimedia platforms, psychological and therapeutic aspects, and socio-economic effects. The insufficient representation of areas related to robotics, multisensory systems, and music therapy in the game environment has been revealed. Conclusions. The obtained results allow us to expand our understanding of the scientific structure of the topic of music and game projects and identify areas for further research, in particular in the educational and rehabilitation field and in the development of interactive IT products. Scope of application of the results: educational, cultural, rehabilitation and creative digital platforms based on music and game interactions.
Copyright (c) 2025 Tetiana Fesenko, Danylo Serheiev, Oleksii Dolhopolov, Illia Serhorodtsev, Maksym Zhuk http://creativecommons.org/licenses/by-nc/4.0
ANALYSIS OF APPROACHES TO MODELING AND ARCHITECTURAL REPRESENTATION OF IMAGE PROCESSING INFORMATION TECHNOLOGY FROM ONBOARD OPTO-ELECTRONIC OBSERVATION SYSTEMS
The subject of the study in the article is the approaches to modeling and architectural representation of information technology. The aim is to analyze modeling approaches and architectural representation of image processing information technology from onboard optoelectronic observation systems. Tasks: to analyze existing approaches to modeling and architectural representation of information technologies, considering the specific features of image processing from onboard optoelectronic systems; to identify the most relevant approaches for the development of such technologies; and to provide recommendations for the application of unified models to ensure effective collaboration among specialists within a common technical environment. The methods used include analytical and empirical methods of comparative research, as well as methods for developing information technologies. The following results were obtained: the main approaches to modeling information technologies were analyzed and systematized, including functional, object-oriented, behavioral, and business modeling. It was determined that the effective design of image processing systems based on onboard optoelectronic platforms requires a comprehensive application of these approaches, depending on the specifics of the tasks. Architectural concepts such as monolithic, microservice, C4 model, TOGAF, and three-tier structures were also reviewed, which enable the formalization of the logic of complex IT solutions. In addition, modern tools for creating diagrams and models were described, supporting the design, verification, and documentation processes of such systems. The results can serve as a methodological basis for the development of information technologies in the field of onboard surveillance and similar complex technical systems. Conclusions: Modeling is a critically important component in the creation of information technologies for image processing from onboard optoelectronic systems. The effectiveness of such IT solutions is ensured through the integrated application of various modeling and architectural design approaches, allowing both technical and business requirements to be addressed. The combination of functional, object-oriented, behavioral, and business models, along with the use of modern architectural solutions and tools, contributes to the creation of reliable, scalable, and adaptive systems. Thus, modeling serves as a key factor in the successful development of complex information technologies in the field of optoelectronic observation. The research was conducted with grant support from the National Research Foundation of Ukraine within the framework of the "Science for Strengthening Ukraine's Defense Capability" competition, project title "Information Technology for Automated Image Segmentation of Objects in Strike FPV Drone Targeting Systems Based on Swarm Intelligence Algorithms," registration number 2023.04/0153.
Copyright (c) 2025 Hennadii Khudov, Irina Khizhnyak, Oleh Salnyk, Petro Mynko, Vitalii Andronov http://creativecommons.org/licenses/by-nc/4.0
INFORMATION SYSTEM FOR INTELLIGENT CUSTOMER CLASSIFICATION: ARCHITECTURE, IMPLEMENTATION, AND EXPERIMENTAL RESEARCH
Relevance. In the context of ongoing digital transformation of business processes, there is a growing demand for intelligent information systems capable of analyzing and processing large volumes of customer data. One of the key directions in this field is automated customer classification using machine learning algorithms, which significantly enhances the effectiveness of marketing strategies and decision-making. Object of the research: customer classification processes in information systems using machine learning methods. Purpose of the article: to design, implement, and investigate the architecture of software components of an information system for intelligent customer classification, taking into account requirements for scalability, performance, and classification accuracy. Research results. The article proposes an architectural model of an information system that includes modules for data collection, preprocessing, and customer classification. Several software components were implemented, integrating machine learning algorithms such as logistic regression, decision trees, and support vector machines. Experimental studies based on a real-world dataset demonstrated high classification accuracy and the system’s efficiency under limited computational resources. Conclusions. The developed information system ensures accurate customer classification and can be applied in commercial data analytics platforms. The research findings can be used to further improve intelligent software systems for data analysis.
Copyright (c) 2025 Oleksandr Shmatko, Daria Malyshenko, Olena Voloshchuk http://creativecommons.org/licenses/by-nc/4.0
METHODS AND ALGORITHMS FOR VIRTUAL MACHINE MIGRATION
The article discusses various aspects of virtual machine migration. The process of moving them between different hosts, data storages, or even between cloud environments. It can be performed in two modes: cold migration, when the virtual machine is previously turned off, and live (dynamic) migration, which occurs without stopping its operation. Thanks to live migration, it is possible to transfer active virtual machines, for example, between servers within a cluster, without interrupting the provision of services. To organize such a process, special administration tools are used, in particular Hyper-V Manager or System Center Virtual Machine Manager from Microsoft Learn.
Copyright (c) 2025 Serhii Pyrozhenko, Viacheslav Radchenko http://creativecommons.org/licenses/by-nc/4.0
FEATURES OF PLANNING MOVABLE CLOUD VOIP SERVICE
The article discusses approaches to planning a non-stationary cloud VoIP service, which is characterized by dynamic load variations and increased quality of service requirements. Key parameters of effective service operation are analyzed, including traffic forecasting, adaptive allocation of computing resources, infrastructure scalability, load balancing, and fault tolerance. It is shown that the use of cloud technologies ensures flexibility and high availability of VoIP services, while also reducing infrastructure costs. Special attention is paid to challenges related to minimizing network latency and maintaining stable voice call quality. The obtained results can be applied to optimize the processes of designing and managing cloud-based telecommunication systems.
Copyright (c) 2025 Yuliia Andrusenko , Serhii Datsenko http://creativecommons.org/licenses/by-nc/4.0