INTERNATIONAL SCIENTIFIC-PRACTICAL CONFERENCE PROBLEMS OF COMPUTER SCIENCES, SOFTWARE MODELING AND SECURITY OF DIGITAL SYSTEMS

BOUNDARY ELEMENT METHOD FOR ANALYSIS OF THREAD-LIKE INHOMOGENEITIES IN ANISOTROPIC THERMOELASTIC SOLIDS

2025-05-21T12:06:43+00:00

This study presents a robust numerical approach for analyzing thermoelastic anisotropic solids containing thin thread-like inhomogeneities. The specific features of applying the integral equation method to such inhomogeneities are examined. A solid boundary element technique is developed to handle 3D ill-posed boundary-value problems with boundary conditions defined along spatial curves. Mathematical models for thermoelastic anisotropic thread-like inhomogeneities are constructed, and several numerical examples are provided to demonstrate the effectiveness of the proposed approach.

APPLICATION OF SPHERICAL HARMONICS FOR COMPUTING FUNDAMENTAL SOLUTIONS OF 3D STATIC THERMOELASTIC PROBLEMS IN QUASICRYSTALS

2025-05-19T19:23:45+00:00

This paper explores the use of spherical harmonics for computing fundamental solutions of three-dimensional static thermoelastic problems in quasicrystals. Quasicrystals are complex anisotropic materials with unique thermo-mechanical behavior, requiring advanced modeling approaches. The fundamental solution serves as a key component in solving boundary value problems for such media. The Radon transform is employed to reduce the governing equations to a more manageable form. Its inverse, expressed as an integral over a hemisphere, is efficiently evaluated by expanding the integrand in spherical harmonics. The first harmonic represents the isotropic response, while higher-order terms capture anisotropic effects. This approach ensures fast convergence and enables semi-analytical representation of solutions. The proposed method enhances both the accuracy and computational efficiency of modeling thermoelastic behavior in quasicrystalline materials.

MACHINE LEARNING FOR FORECASTING DEMAND FOR ONLINE ORDERS

2025-05-08T15:40:48+00:00

Decision-making based on the integration of artificial intelligence for demand forecasting is becoming a necessity with the significant development of e-commerce. Businesses that implement AI technologies are well-adapted to market changes and achieve success in e-commerce, as well as satisfy customer expectations.

OPTIMAL DESIGN OF INTEGRATED CIRCUITS

2025-05-16T05:20:38+00:00

This paper is devoted to the open problem of optimal design of printed boards. We propose a new optimization model for this problem and use an efficient method of exact quadratic regularization to solve it. Computational experiments confirm the effectiveness of this technology in solving this problem.

MATHEMATICAL MODELING OF THE DISTRIBUTION OF HEAVY METALS POLLUTION BY NON-DESTRUCTIVE TESTING METHODS USING INTERLINATION OF THREE-VARIABLE FUNCTIONS

2025-05-20T18:13:50+00:00

The article builds a mathematical model that describes the distribution of heavy metal contamination of soil due to industrial emissions. The input data are experimental data obtained by non-destructive testing methods. To do this, the paper constructs an interlineation operator for a function of three variables based on its known traces on a system of arbitrarily placed parallel lines.

MODIFIED SEIRA MODELS OF THE SPREAD OF DISINFORMATION ON THE INTERNET

2025-05-20T05:25:24+00:00

In the context of a full-scale war, a country's information security becomes critically important. The information space is highly saturated with various sources, and fake news often serves as a tool for destabilizing public sentiment. The spread of disinformation can be interpreted similarly to the spread of a virus, where users transition between different states. This paper explores approaches to detecting disinformation and modeling the dynamics of its diffusion.

PROFIT FORECASTING OF COMPANIES THROUGH THE USE OF MATHEMATICAL FUNCTIONS IN EXCEL

2025-05-19T09:09:01+00:00

The Excel program is widely used in financial analysis due to its data visualization and processing capabilities. One of the current tasks is predicting the company's profit based on previous financial indicators. The research involves analyzing Excel's capabilities for building functional dependencies and selecting the most accurate model for forecasting the enterprise's profit based on statistical data.

MODERN LIBRARIES FOR WORKING WITH GEODATA IN R

2025-05-26T07:35:39+00:00

This paper reviews modern R libraries for processing and visualizing geodata. Particular attention is paid to such packages as sf, geodata, plotrix, rnaturalearth, which replaced outdated solutions and greatly simplified the analysis of spatial information. The purpose of the study was to create a cartographic visualization that displays the distribution of students by specialty in different regions of Ukraine using pie charts integrated into the map. An example of building such a visualization using the latest R tools was demonstrated, and the advantages of modern libraries over outdated approaches were outlined. The results confirm the expediency of using modern R tools for applied tasks in the field of education and demography.

SOME REFINEMENTS OF ALGORITHMS FOR TWO-DIMENSIONAL VISUAL PATTERN RECOGNITION

2025-05-26T18:05:53+00:00

This paper analyzes the current challenges of two-dimensional visual pattern recognition and formulates a general approach to refining recognition algorithms. The proposed theoretical model emphasizes structural invariance and robustness under noisy and incomplete visual conditions. The expected results involve developing a set of criteria for evaluating recognition stability and efficiency under real-world constraints.

USING BOOTSTRAP TECHNIQUES FOR DATA CLASSIFICATION WITH LINEAR AND LOGISTIC REGRESSION

2025-05-21T21:01:25+00:00

The paper focuses on exploring bootstrap techniques in data analysis through the application of linear and logistic regression methods, with implementation in R.

PLATFORM FOR RECOMMENDATIONS OF SELECTIVE EDUCATIONAL COMPONENTS USING THE ONTOLOGICAL METHOD

2025-05-26T16:33:37+00:00

The paper proposes an approach to building a personalized recommendation system for elective academic components based on ontology. The developed ontology describes the relationships between students, courses, knowledge categories, preferences, and grades. A semantic model is used to compute the similarity between student profiles and course characteristics. The system also incorporates historical academic data and course ratings to generate adaptive learning recommendations. A mathematical model integrates content-based and collaborative filtering techniques to personalize learning paths in higher education.

GEODETIC DATA IN THE COURSE «INTELLIGENT DATA ANALYSIS»

2025-05-24T15:23:05+00:00

This article presents methodological materials for a practical lesson involving geographic maps using the R software.The article describes the process of integrating search data from Google with a contour map of the world. Special attention is paid to the preparation, processing and formatting of data, their comparison with geographical coordinates and the creation of comparative visualisations.

USING STANDARD METRICS TO ASSESS THE QUALITY OF RECOMMENDATIONS WHEN IMPLEMENTING A NEURAL NETWORK INTO A PLATFORM FOR RECOMMENDING SELECTED EDUCATIONAL COMPONENTS

2025-05-26T21:12:49+00:00

The paper presents a neural network-based approach to building a personalized recommendation system for elective academic components. The proposed model combines embeddings of students and courses, capturing latent features such as interests, difficulty levels, and content categories. A multi-layer neural architecture processes student-course pairs to estimate the probability of student interest. The system is trained using historical selection data and optimized with a binary cross-entropy or ranking loss. Evaluation uses standard Top-N recommendation metrics, including Precision@10, Recall@10, Mean Average Precision (MAP), and NDCG@10. Experimental results show significantly improved recommendation accuracy compared to classical collaborative and content-based filtering methods.

CLASSIFICATION, FEATURES, AND DEVELOPMENT TRENDS OF RENDERING ALGORITHMS

2025-05-30T16:07:32+00:00

The paper examines modern rendering algorithms that underlie image generation in computer graphics. Classical and modern approaches are analyzed, including rasterization algorithms, ray tracing, global illumination, and hybrid methods. The directions of development of realistic rendering in the context of Web3D, real-time visualization, and hardware acceleration are outlined.

EXAMPLE OF APPLICATION OF INFORMATION APPROACH TO MARKETING TASKS

2025-06-03T17:13:12+00:00

The paper considers an example of applying entropy of statistical distribution to marketing problems. An algorithm for optimizing analytical studies of the structure of consumption of product types is proposed.

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2025-05-30T08:31:00+00:00

OBJECT CLASSIFICATION USING VARIOUS SEGMENTATION METHODS BASED ON COLOR HISTOGRAM

2025-05-20T10:10:38+00:00

This study evaluates color-based classification for beverage recognition using various segmentation and histogram-based methods. We implement five segmentation approaches, four vector creation methods, and five classification metrics on a dataset of beverage categories. After refining the dataset, our solution achieves 87.5% accuracy using threshold segmentation with average vector creation and KL divergence classification.

THE EFFECT OF FILTERING COLOR HISTOGRAM PEAKS ON IMAGES SIMILARITY ESTIMATION

2025-05-18T06:27:15+00:00

This work investigates the change of the correlation coefficient of the color (Hue) histograms depending on the number of peaks taken into account. The CQ100 images dataset was used for the research. The idea of the study is to exclude peaks of lower intensity from consideration and to find out how this affects the correlation coefficient.

METHODS OF CLASSIFICATION OF ELECTROENCEPHALOGRAM DATA FOR IDENTIFICATION OF ABSTRACT SYMBOLS PERCEPTION

2025-05-05T13:59:50+00:00

The developed methods for classifying electroencephalograms (EEGs) make it possible to detect brain responses to abstract stimuli, which form the basis for building brain-computer interface systems. The result of signal classification is the assignment of a test EEG to a corresponding cluster that represents a specific visual figure.

AI-APPROACHES TO RESOURCE OPTIMIZATION IN DYNAMIC CLOUD INFRASTRUCTURES

2025-05-19T16:46:20+00:00

This paper explores modern artificial intelligence (AI)-based approaches to resource optimization in cloud computing environments. It focuses on the use of deep reinforcement learning, evolutionary algorithms, and federated learning for managing dynamic workloads, enhancing energy efficiency, and ensuring cybersecurity. Recent studies demonstrating the advantages of hybrid AI systems are reviewed and generalized. The paper also emphasizes the importance of integrating such approaches into multi-tenant cloud infrastructures, taking into account platform-specific constraints and emerging threat vectors. Special attention is paid to data confidentiality, fault tolerance, and compliance with international security standards.

EDGE APPROACH TO DETECTING ANOMALIES IN ELECTRICITY CONSUMPTION

2025-05-18T17:32:19+00:00

The study presents an autonomous ESP32-based module with an INA219 sensor for early detection of energy consumption anomalies in household appliances. The key innovation is shifting machine-learning analytics to the network edge: a quantized TensorFlow Lite autoencoder learns the appliance’s normal profile within one week and then, in real time, compares the reconstruction error with a statistical threshold of μ + 2σ. Any excess instantly triggers an MQTT alert, eliminating the need to stream raw data to the cloud. Laboratory tests with a refrigerator, washing machine, and an electric kettle demonstrated 100% detection of abrupt surges (> 50%) and 92% detection of gradual drifts (~ 10% per week) with ~ 1 s alert latency. The modular firmware can be deployed on off-the-shelf smart sockets, enabling up to 15% annual energy savings and enhanced fire safety without compromising user privacy

TECHNOLOGY AND METHODS OF COLLECTING INFORMATION FOR IDENTIFYING METAL OBJECTS IN TOPSOIL

2025-05-19T13:10:44+00:00

Detection of metal objects lying at a shallow depth is a relevant task in archaeology, construction, ecology, mineral exploration and the field of mine safety. Research objective: To propose a method and technology for identifying a metal object with given parameters based on a comparison of modern methods and technologies for detecting metal objects. The paper analyzes existing detection methods such as electromagnetic induction metal detectors (EMI), ground penetrating radar (GPR), magnetometers, and non-linear junction detectors (NLJD). The choice of a pulse induction (PI) metal detector based on a Raspberry Pi single-board computer is justified as the optimal platform in terms of cost, performance, and versatility. The developed hardware part of the complex and an information system with a client-server architecture for data collection and primary processing are presented. A hypothetical stack of signal processing methods (band-pass filter, RPCA-GoDec, FFT, RBF-SVM) is proposed for identifying ferrous objects of a certain size.

ANALYSIS OF THE USE OF HEATMAP TECHNOLOGIES IN WEBSITE ANALYSIS

2025-05-28T08:53:01+00:00

This paper examines the application of heatmap technologies for analyzing user behavior on websites, focusing on their role in enhancing website usability. Heatmaps serve as an effective visualization tool that highlights areas of user interaction through color-coded data, helping designers and developers identify high- and low-attention zones. The study discusses various types of heatmaps—including click maps, scroll maps, and mouse movement maps—and how they provide insights into interface performance and user experience. Key functions include identifying usability issues, optimizing content placement, and improving call-to-action effectiveness. The paper also outlines the benefits and limitations of current heatmap tools, emphasizing the need for correct interpretation and integration with other web analytics methods. Overall, heatmaps offer a powerful means of optimizing website design by aligning it more closely with user behavior.

THE PRECISION FORMATION OF INFORMATIVE SIGNS RESEARCHING IN THE SYMBOLIC REPRESENTATION OF RASTER IMAGES FOR PATTERN RECOGNITION SYSTEMS

2025-05-16T18:34:42+00:00

This study explores the application of symbolic image representation as a method of visual data transformation. By converting raster images into symbolic forms, this approach reduces data dimensionality while preserving key informational features. The study assesses the effectiveness of symbolic representation in transmitting visual information by quantitatively evaluating the similarity between original and transformed images.

EXPLORING THE CAPABILITIES OF PLANTUML FOR ENHANCING ER DIAGRAM CONSTRUCTION

2025-05-09T04:55:09+00:00

This research analyzes PlantUML's capabilities for building ERD. The shortcomings of PlantUML's basic functionality for creating ERD are described. Additional PlantUML features are presented such as improving the appearance and readability of diagrams by highlighting primary and foreign keys, removing unnecessary elements, and creating legends for user convenience. A plugin module has been developed to enhance the readability of PlantUML code by structuring it into functions and procedures, making diagrams easier to create and maintain.

LONG-RANGE CORRELATIONS AS A CRITERION FOR RELEVANCE OF WORDS IN TEXTUAL DOCUMENTS

2025-05-10T13:38:28+00:00

Highly efficient detection of keywords is a basis for successful information retrieval. Here we present a new criterion of relevance of words in textual documents, which is associated with the long-range autocorrelations of word-token time series. The above approach is compared with a canonical keyword detection method based on word-token clustering in a text.

CLUSTERING-BASED PARAMETERS FOR DETECTION OF KEYWORDS IN NATURAL TEXTS WITH CORRECTIONS ON RANDOM TEXTS

2025-05-14T18:53:29+00:00

Clustering-based methods are efficient in detection of keywords in natural texts. Here we present a technique for correcting the appropriate word-relevance parameters with the data obtained for random texts and simulate the dependences of those parameters on the absolute and relative word-token frequencies.

REVIEW OF THE PROSPECTS OF PROCEDURAL GENERATION ALGORITHMS’ PERFORMANCE IN COMPUTER GAMES

2025-05-09T14:22:57+00:00

In the modern computer game industry, which is rapidly evolving and demands increased interactivity, realism and scalability of game systems, procedural generation algorithms have become an integral part of development. These algorithms enable the automatic creation of large volumes of content – from landscapes and levels to quests, narratives, and even graphic elements such as textures, materials and 2D/3D models. However, the performance of such algorithms directly depends on their time and space complexity, which becomes a critical factor when generating content in real time or on less powerful devices. Therefore, this analysis considers modern approaches to procedural content generation, particularly algorithms based on noise functions (Perlin noise, fractional Brownian motion), generative grammar (graph rewriting), space partitioning methods (Fortune’s algorithm for Voronyi tessellation) and genetic algorithms. In this regard, a detailed review of the prospects for optimization procedural content generation of these algorithms is relevant, which will allow choosing the most suitable solutions for specific game projects and ensuring a balance between content quality, performance, and visual appeal.

ANALYSIS OF DIALOGUE MODELING CRITERIA IN VIDEO GAMES (BASED ON THE GAME Cyberpunk 2077)

2025-05-28T08:54:33+00:00

This article analyzes the criteria for dialogue modeling in video games, using Cyberpunk 2077 as a case study. The author explores the role of dialogues as one of the key elements of interactive narrative, influencing the dynamics, pacing, and depth of gameplay. The functions of dialogues in the game are examined: slowing down or accelerating events, conveying plot information, world-building, character development, and contributing to variability and non-linearity of the storyline. A number of criteria determining the effectiveness of dialogues are identified — consistency with the character’s personality, the game world's atmosphere, logical structure, emotional expressiveness, interactivity, technical implementation, localization quality, and others. Particular attention is given to the sociolinguistic analysis of character speech in Cyberpunk 2077, including the use of slang, jargon, and multilingualism.

ANALYSIS OF A COMPANY'S FINANCIAL INDICATORS: MODERN METHODS AND TECHNOLOGIES

2025-04-15T15:08:25+00:00

The paper examines the financial indicators of an enterprise as a key tool for assessing its financial condition, efficiency, and sustainability. The focus is on the application of modern technologies — particularly artificial intelligence, machine learning, and big data analytics — to forecast financial indicators. The study justifies the integration of traditional statistical methods with intelligent algorithms to improve the accuracy of financial analysis and the effectiveness of managerial decision-making. The paper proposes approaches to automating the assessment of liquidity, profitability, financial stability, and investment attractiveness of enterprises, taking into account risks and market dynamics.

COMPUTER MODELING OF THE MECHANICAL PROPERTIES OF NANOTUBE COMPOSITES CONSIDERING THE ORIENTATION EFFECT

2025-05-13T18:18:39+00:00

This paper proposes a model for predicting the mechanical properties of composite materials based on their structural features at the nanoscale. The computer model considers not only the content, but also the predominant orientation of the filler in the rule of mixtures and the Halpin–Tsai equation. The predominant orientation of the filler is maintained by restricting the orientation angles of randomly arranged nanotubes.

IMPLEMENTATION OF NEURAL NETWORK METHODS FOR SHORT-TERM FORECASTING OF PRICE MOVEMENTS IN FINANCIAL MARKETS

2025-05-29T11:30:32+00:00

This study addresses the problem of short-term forecasting of order book dynamics for a financial instrument using full L2 data. Instead of traditional time series with simple numerical features, the approach relies on sequences of structured order book snapshots, each capturing market depth across 100 price levels. To facilitate this, a custom data collection tool was developed based on the BookmapAPI, enabling automatic generation of training samples with corresponding target variables, including maximum, minimum, and final bid and ask prices over a defined prediction horizon.

MODELING AN ACCESS CONTROL SYSTEM USING THE WOKWI PLATFORM

2025-05-19T20:34:09+00:00

The process of modeling a microcontroller access control system using the WOKWI online platform is considered. The functionality of the modeled system is shown, the key principles of its construction and the potential for further adaptation and expansion are described.

STUDY OF THE EFFECTIVENESS OF CLASSICAL AND NEURAL NETWORK METHODS FOR REGRESSION FORECASTING

2025-05-19T21:23:41+00:00

This paper presents a comparative analysis of classical and neural regression models for processing large datasets. Three approaches were implemented: Random Forest Regressor and two Dense Neural Networks — a basic PyTorch version and an improved TensorFlow model with Dropout and BatchNormalization layers. While the classical model achieved moderate accuracy (R² = 0.7404), the enhanced DNN yielded the best results (RMSE = 0.1570, R² = 0.9346). The study confirms the potential of neural networks for high-precision regression, provided that regularization, normalization, and hyperparameter tuning are applied.

ARCHITECTURE AND OPERATING PRINCIPLE OF THE DEEP LEARNING MODEL FOR IMAGE RECOGNITION IN BLOSSOM LENS

2025-05-20T19:05:33+00:00

Computer vision systems based on deep learning enable a high degree of automation in image classification tasks. Blossom Lens is an example of such implementation, designed for automatic flower recognition from digital images. The model achieves over 90% accuracy and integrates external knowledge sources, transforming the software into an educational tool..

COMPARATIVE ANALYSIS OF RELATIONAL AND NON-RELATIONAL DATABASES BASED ON A WEB APPLICATION DEVELOPED IN PYTHON

2025-04-22T14:08:32+00:00

The study explores approaches to data storage in modern web applications using both relational and non-relational databases. A hybrid architecture was implemented, combining PostgreSQL for structured information and MongoDB for handling nested comments. Performance testing of both DBMSs was conducted, confirming their efficiency in their respective use cases. The results demonstrated the viability of a combined approach for building flexible, scalable, and reliable information systems.

COMPARATIVE ANALYSIS OF INFORMATION SYSTEMS FOR SUPPORTING THE EDUCATIONAL PROCESS IN GENERAL SECONDARY EDUCATION INSTITUTIONS

2025-05-23T22:44:24+00:00

This thesis provides a comprehensive comparative analysis of four information systems: Google Classroom, Microsoft Teams, Moodle, and «Yedyna Shkola», which are widely implemented in Ukrainian secondary education institutions. The study examines both educational and technical aspects of the platforms, including functionality, security, integration capabilities and user experience.

METHODS OF APPLYING MACHINE LEARNING IN USER BEHAVIOR ANALYTICS FOR SAAS: FROM CLASSIFICATION TO PREDICTION

2025-05-16T10:45:24+00:00

This paper explores the application of machine learning methods for user behavior analytics in SaaS platforms to improve classification accuracy and churn prediction. It addresses challenges such as class imbalance, high data dimensionality, and temporal dynamics. The study compares the effectiveness of traditional and modern models (AdaBoost, transformers), and examines the impact of data preprocessing and class balancing (ADASYN) on performance. In the practical case, significant improvements were achieved after vectorizing categorical features and applying class balancing. The work highlights the potential of ML approaches to enhance retention strategies and improve the effectiveness of SaaS products.

ANALYSIS OF THE EFFECTIVENESS OF USING INTERACTIVE PLATFORMS FOR FOREIGN LANGUAGE

2025-05-14T11:49:53+00:00

This study examines the effectiveness of interactive platforms in foreigh language learning, focusing on their impact on motivation, engagement, and learning outcomes. It highlights advantages and disadvantages.

CHALLENGES OF DESIGNING A STORE'S NETWORK INFRASTRUCTURE

2025-05-31T23:15:39+00:00

The study identifies and categorises the key challenges that professionals encounter when designing a store's network infrastructure. The focus is on technical, organisational, and operational constraints. Taking into account modern technologies, regulatory requirements and best design practices, the paper proposes possible approaches to overcoming these challenges.

ANALOG AND DIGITAL OPTICAL RANGE INFORMATION SYSTEMS

2025-06-12T10:26:33+00:00

This study examines the latest approaches to the implementation of optical analog and digital systems based on a review of leading scientific articles of recent years. The current state and prospects for the development of analog and digital optical information systems were analyzed, their advantages, limitations and potential for practical applications, in particular, in optical computing, AI, industry and digital modeling, were identified.

MODERN COMMUNICATION AND MEASUREMENT RECEIVERS

2025-06-12T11:34:04+00:00

The article discusses the main types of modern receiving devices used in various fields of communication and measurement. The key characteristics, advantages, and applications of each type are described. The emphasis is placed on the latest research in the field of terahertz communication, coherent signal processing, visible light communication and integration of radar and communication functions.

TOOLS AND METHODS FOR MEASURING SPEECH SIGNAL PARAMETERS

2025-06-12T12:29:51+00:00

The paper analyzes methods of processing speech signals that will contribute to increasing the efficiency of voice control systems, in particular in conditions of noise, multilingualism and complexity of speech structure. The basic tasks of speech command processing systems are determined, the classical structural diagram of the voice control system, the stages of processing in the SGC and the classification of speech signal processing methods are considered.

DIGITAL FILTERS DESIGN IN SIGNAL PROCESSING

2025-05-28T14:33:33+00:00

The paper provides a comprehensive review and analysis of modern approaches, methods and trends in digital filter design in the context of digital signal processing. The role of optimization algorithms, hardware implementations on FPGAs and ASICs, and specific requirements of individual applications in the selection and development of digital filters is investigated.

INFORMATION SECURITY IN THE CONTEXT OF USER BEHAVIOR ANALYSIS

2025-05-19T20:14:44+00:00

This article examines the issue of studying the psychological characteristics of employees in an organization. Individual safety behavior patterns can be formed for workers, which will later be adjusted based on the collected statistics of their behavior.

ARMA AS A SUBJECT OF INFORMATION SECURITY IN THE ASPECT OF DIGITAL ASSET MANAGEMENT: LEGAL AND CYBERNETIC DIMENSIONS

2025-05-14T11:30:37+00:00

This paper explores the role of ARMA in Ukraine's information security, focusing on the management of digital assets like cryptocurrencies. It examines the legal challenges due to the unregulated status of virtual assets and the cybernetic measures ARMA employs to protect information systems.

METHOD FOR DISTRIBUTING CRYPTOGRAPHIC LOAD BETWEEN MICROCONTROLLERS IN EDGE ARCHITECTURES BASED ON ENERGY MODEL

2025-05-17T13:14:58+00:00

The article proposes a method for energy-efficient distribution of cryptographic workload between microcontrollers in edge architectures, taking into account their energy profiles. The approach is based on dynamic assessment of residual energy, load, and reliability of nodes. The model supports adaptability to changes in the network and allows reducing total energy consumption by 18–40% compared to baseline strategies. The simulations confirmed the effectiveness of the method for distributed systems with limited resources.

ANALYSIS OF CYBERATTACKS OF RECENT YEARS: LESSONS IN SELF-PROTECTION

2025-05-21T07:49:41+00:00

This paper analyzes major cyberattacks of recent years, focusing on their impact, strategies used by attackers, and the key lessons learned for improving cyber defense. High-profile incidents such as the NotPetya attack (2017), the SolarWinds breach (2020), the Viasat disruption during the Russian invasion of Ukraine (2022), and ransomware campaigns like the Colonial Pipeline attack (2021) are examined to illustrate the evolving nature of cyber threats. The study emphasizes the vulnerability of critical infrastructure, the importance of supply chain security, and the growing role of state-sponsored cyber operations. It also highlights Ukraine's experience in cyber defense during hybrid warfare, underscoring the value of international cooperation, zero-trust models, proactive threat detection, and public cyber hygiene.

PROTECTION AGAINST UNAUTHORIZED ACCESS

2025-05-26T10:36:28+00:00

This paper explores modern methods for securing information systems against unauthorized access. As cyber threats grow, ensuring data confidentiality, integrity, and availability is essential. The study highlights the need for a comprehensive security strategy combining organizational policies, technical controls, and advanced software. It addresses challenges in cloud environments and the use of AI for anomaly detection. Legal frameworks like GDPR and national standards are also examined. Effective protection requires continuous monitoring, strong access controls, and proactive threat response. Multi-layered defenses—such as encryption, two-factor authentication, and behavioral analytics – improve resilience against both internal and external threats.

FEATURES OF DATA PROTECTION SYSTEMS INTEGRATION INTO SOFTWARE: FROM CONCEPT TO IMPLEMENTATION

2025-05-09T11:26:08+00:00

This study explores the integration of data protection systems into software throughout its lifecycle, from concept to implementation. It focuses on the Ukrainian "Diia" app, demonstrating the "security by design" approach, where security is embedded from the start. The research emphasizes the importance of continuous integration to ensure effective protection against cyber threats.

HUMAN FACTOR AND SECURITY MANAGEMENT. INFORMATION SECURITY AUDIT: METHODOLOGY AND PRACTICAL CASES

2025-05-21T08:10:41+00:00

This paper examines the role of the human factor in information security systems, emphasizing that despite the presence of advanced technological solutions, policies, and procedures, employee behavior, knowledge, and motivation remain critical to effective cybersecurity. It details the main threats related to the human factor, including social engineering, accidental errors, insider threats, and sabotage. Special attention is given to the importance of continuous employee training, fostering a security-aware culture, implementing the principle of least privilege, using multi-factor authentication, monitoring, and conducting regular audits. The analysis covers international standards (ISO/IEC, NIST, COBIT) and practical audit cases, demonstrating the need for a comprehensive approach to managing human-related risks. The paper concludes that effective information security requires a balanced integration of technical measures, management strategies, and an understanding of the social and psychological dynamics within the organization.

THE IMPACT OF CYBER HACKATHONS ON THE TRAINING OF CYBERSECURITY AND COMPUTER NETWORK SPECIALISTS

2025-05-21T07:35:27+00:00

This article explores the role of cyber hackathons in training specialists in cybersecurity and computer networks. It analyzes their impact on the development of practical skills in comparison with traditional teaching methods and examines international practices of organizing such events. Based on data from hackathons such as DEF CON CTF, Pwn2Own, and Hack The Box, the study demonstrates that interactive competitions are an effective tool for building professional competencies. The results show that hackathon participants grasp complex concepts 30–50% faster than students in conventional courses.

SOFTWARE IMPLEMENTATION OF HIDDEN SECRET MESSAGE IN AN IMAGE USING THE PVD METHOD

2025-05-22T20:19:35+00:00

The paper presents the code of a training program for steganographic hiding of text information in graphic files. Hiding is implemented using the PVD (Pixel Value Difference) method in Python. The program can be used for both educational and practical purposes. The Pillow library was used to implement the program. This graphic library is not specialized for steganographic needs. A positive quality of the library is the ability to visualize the information hiding mechanism. This is interesting for educational purposes.

INTEGRATION OF FINOPS AND SOC 2 CONTROLS INTO THE COST MONITORING PROCESS IN A MULTI-CLOUD ENVIRONMENT

2025-04-07T12:59:07+00:00

With the growing popularity of multi-cloud architecture, organizations are increasingly facing challenges related to cost opacity, budget overruns, and fragmented control over cloud resource consumption. At the same time, there is a rising demand for compliance with information security standards, particularly SOC 2, which includes criteria for security, availability, and processing integrity (Trust Services Criteria).

This paper proposes an architectural solution that combines FinOps approaches to cost management with the implementation of SOC 2 controls. Based on tools such as Splunk, Cherwell, and automated event escalation mechanisms, a system was developed that can detect budget overruns, generate incidents, allocate responsibility among process participants, and ensure the logging of all critical events. The implemented logic of thresholds and responses is integrated with the ITSM environment and supports business processes related to financial and security monitoring.

The solution not only enables cost optimization in a multi-cloud environment but also forms an evidence base for audit in accordance with SOC 2 Type II. This demonstrates the effectiveness of an approach that combines economic efficiency, automation, and information security, and can be scaled for medium and large IT organizations.

ARTIFICIAL INTELLIGENCE IN THE SERVICE OF CYBER PROTECTION: PROSPECTS AND RISKS

2025-05-21T07:40:21+00:00

In the era of digital transformation, cyber security is of particular importance due to the growing number of threats in the virtual environment. Artificial intelligence is becoming a key tool in the fight against cyber attacks thanks to its ability to analyze large volumes of data and detect anomalies. Its use allows prompt response to threats and increases the effectiveness of protective systems. One of the main advantages of AI is the possibility of self-learning, which reduces the burden on specialists and increases the accuracy of decisions.

ARTIFICIAL INTELLIGENCE IN CYBERSECURITY: CHALLENGES, THREATS AND REGULATORY RESPONSES

2025-05-05T08:45:55+00:00

In 2025, artificial intelligence (AI) plays a vital role in cybersecurity. Its ability to learn, analyze vast data in real-time, and adapt to new threats makes it indispensable. While AI helps detect and neutralize attacks, it also enables new threats like prompt injection, deep fakes, and automated phishing. This paper reviews the current use of AI in cybersecurity, its pros and cons, and future directions including technical and ethical considerations.

INTEGRATION OF CYBERSECURITY INTO THE NATIONAL SECURITY SYSTEM OF UKRAINE: NEW CHALLENGES, OPPORTUNITIES AND RESULT

2025-05-21T07:56:51+00:00

Abstract. The text reveals the role of the digital sphere as a key element of the modern national security system of Ukraine. The emphasis is on the growing threat of cyberattacks, espionage, IPSO and other forms of hybrid warfare, which require a coordinated state response. The main challenges to integrating cybersecurity into the national security strategy are identified, in particular, the imperfection of the legislative framework, institutional fragmentation, personnel shortage, technological dependence and limited funding. At the same time, significant opportunities are emphasized: the development of public-private partnerships, international cooperation, a national cyber defense industry and the formation of a culture of digital security.

INFORMATION SECURITY AND CRYPTOGRAPHY: A COMPARATIVE ANALYSIS OF MODERN CRYPTOGRAPHIC ALGORITHMS – SYMMETRIC VS ASYMMETRIC METHODS

2025-05-21T07:53:24+00:00

A comprehensive analysis of modern cryptographic algorithms has been conducted, comparing symmetric (AES, 3DES) and asymmetric (RSA, ECC) encryption methods. Their advantages, disadvantages, and areas of application have been examined in the context of information security. The relevance of a hybrid approach, combining both methods to enhance data protection efficiency, has been substantiated. The significance of the topic is emphasized in light of the ongoing development of quantum technologies.

PHISHING, DDOS ATTACKS AND OTHER CYBERATTACKS - HOW TO PROTECT YOURSELF

2025-05-21T07:43:15+00:00

The paper analyzes scientific research and practice of implementing methods and tools to counter phishing, DDoS attacks and other types of cyberattacks. The features of cybersecurity are considered, including the classification of threats, methods for their detection and means of protection. The subject area of cyberdefense is analyzed, the main essences of attacks, their properties and potential consequences for computer systems are determined. The functional requirements for protective software are studied and methods for detecting threats based on their characteristics are considered.

CONSTRUCTION OF A SYSTEM FOR LOGGING AND MONITORING INFORMATION SECURITY EVENTS

2025-05-21T08:00:36+00:00

The abstracts consider the importance of building logging and event monitoring systems as one of the key areas of ensuring information security. Logging allows you to record user actions, system events, and network activity, which is the basis for detecting violations and responding to incidents. Monitoring systems, in particular SIEM platforms, provide real-time event analysis and automated threat notification. Special attention is paid to the stages of building a system, selecting tools, and organizing log storage. The role of personnel and the need for continuous improvement of cyber protection procedures are also taken into account. It is emphasized that an effective logging system is not only a technical solution, but also an element of a risk management strategy. The materials presented will be useful to cybersecurity specialists, IT managers, and students of relevant specialties.

RESEARCH ON CRYPTOGRAPHIC TRANSFORMATIONS IN THE RING OF CUT MESSAGES

2025-04-30T19:20:36+00:00

The study examines cryptographic transformations based on the ring of truncated messages, a mathematical structure with promising properties for information protection. The operations of addition and multiplication within this ring and their impact on encryption reliability and attack resistance are analyzed. Encryption algorithms have been developed, showing efficiency in ensuring data confidentiality and integrity under digital threat conditions.

CURRENT TRENDS AND CHALLENGES. RISK ASSESSMENT OF CYBER INCIDENTS FOR CRITICAL INFRASTRUCTURE

2025-05-21T08:04:38+00:00

This article explores the current trends and challenges in assessing cyber incident risks to critical infrastructure. With the growing digitalization of key sectors, such as energy, healthcare, and transportation, the vulnerability to cyber threats has significantly increased. The paper emphasizes the importance of dynamic risk assessment models, national strategies, and international cooperation. It also highlights the role of legal regulations, technological solutions, and human factors in building cyber resilience.

DETECTION OF MALICIOUS RESOURCES IN THE TELEGRAM SOCIAL NETWORK AND RULES FOR SAFE ONLINE BEHAVIOR

2025-05-21T08:07:55+00:00

This summary highlights the risks of fraudulent activity in Telegram, including phishing, identity theft, and deepfake video scams. It emphasizes the importance of digital literacy, two-factor authentication, and awareness of emerging cyber threats.

METHODS FOR PROTECTING PERSONAL DATA IN CLOUD SERVICES

2025-04-30T19:16:02+00:00

The article examines the functionality of cloud storage systems and the challenges of ensuring their information security. It highlights the evolution of data protection measures — from traditional network tools to advanced approaches such as client-side encryption, containerization, multi-factor authentication, and future directions in quantum cryptography. Special attention is given to the differences between private and corporate cloud usage, as well as issues of authorization and authentication within enterprise IT infrastructures.

CRYPTOGRAPHIC TRANSFORMATIONS BASED ON THE HADAMARD OPERATOR IN QUANTUM NETWORKS

2025-05-21T07:38:27+00:00

The paper presents a model for message encryption in quantum networks using the Hadamard operator. The use of this operator is considered as a fundamental tool for implementing superposition in the process of transforming classical bits into quantum states. An encryption protocol is proposed that can serve as a basis for secure message exchange between users in a quantum network.

METHODS OF PROTECTING CONFIDENTIAL DATA USING ENCRYPTION ALGORITHMS

2025-04-29T14:09:37+00:00

The report discusses the introduction of artificial intelligence and encryption algorithms for reliable data encryption

DIGITAL LOSS OF CLOUD SERVICES USAGE

2025-05-19T12:54:07+00:00

Digital traces of cloud services usage on Windows 10 were investigated for digital forensics purposes.

OPTICAL WAVEGUIDES IN INFORMATION TRANSMISSION

2025-05-31T13:09:30+00:00

The article presents a comprehensive analysis of the most relevant engineering and technological solutions in the field of waveguide design, integration with light sources and receivers, nonlinear optics and modulation. The materials have applied significance for the development of photonics, telecommunications, sensors, spectroscopy, quantum computing and miniature optoelectronic systems of the new generation.

COMPARISON OF MANAGED SOLUTIONS AND DIY APPROACH IN DATA LAKEHOUSE AS A DATA INTEGRATION STRATEGY

2025-05-23T12:04:06+00:00

The paper provides a comprehensive comparative analysis of Data Lakehouse implementation strategies, focusing on managed cloud solutions versus a Do-It-Yourself (DIY) approach using open-source technologies. Managed platforms offer quick deployment and ease of use but may lead to vendor lock-in and high long-term costs. In contrast, DIY solutions offer greater control, flexibility, and cost predictability but require more technical expertise and maintenance effort. The analysis highlights that managed solutions are well-suited for organizations seeking rapid implementation with minimal internal overhead. Meanwhile, DIY architectures allow for fine-grained customization and technological independence, particularly valuable in complex business contexts. However, DIY setups demand significant investment in skilled personnel and integration efforts. The study outlines the trade-offs between these approaches and emphasizes that the optimal choice depends on organizational needs, budget, and team capabilities.

OPTIMIZATION OF INTERNAL SOFTWARE QUALITY ASSURANCE PROCESSES BY IMPLEMENTING DEV-TESTING PRACTICES

2025-05-15T10:24:24+00:00

The paper highlights the effectiveness of implementing dev-testing as a tool for improving software quality at the development stage. The approach helps identify configuration and integration issues before QA, reducing bug rates and enhancing team workflow. Results demonstrate the method’s potential in reducing development cycle time and improving defect metrics.

USING ARTIFICIAL INTELLIGENCE TO SECURE SENSOR NETWORKS

2025-05-19T06:59:08+00:00

The study examines modern approaches and methods for protecting WSNs with AI, emphasizing its efficiency and speed. Key challenges and strategies for protecting advanced algorithms are also discussed.

SPECIFIC WAYS TO SOLVE THE PROBLEM OF INSUFFICIENT UNIQUE DATA FOR TRAINING NEURAL NETWORKS IN JURISPRUDENCE

2025-05-20T02:21:29+00:00

Neural networks and machine learning are increasingly being integrated into various legal domains, including document analysis, legal research, and predicting court case outcomes. This is driven by the desire to automate routine tasks and improve the efficiency of legal practice. However, a fundamental obstacle to training reliable and accurate models in jurisprudence is the problem of insufficient unique and labeled data. The legal field, with its complexity and need for expert labeling, inherently suffers from data scarcity more than some other fields. Using incorrect or insufficient data can lead to legal risks, biases, and decreased model quality, highlighting the importance of data uniqueness and high quality. This article will discuss several specific methodologies aimed at solving the problem of insufficient unique data for training neural networks in jurisprudence: data augmentation, synthetic data generation, transfer learning, and few-shot learning.

MULTITHREADING IN PYTHON AS A TOOL FOR INCREASING PROGRAM EFFICIENCY

2025-05-08T06:11:49+00:00

This paper explores the efficiency of multithreading in Python for I/O-bound tasks. A comparison between sequential and concurrent implementations is provided using real examples. The results demonstrate significant performance gains with native threading usage.

REAL-TIME AUTOMATION OF BOKSHI INDEX CALCULATION

2025-05-26T09:14:31+00:00

This paper addresses the automation of Bokshi Index calculation — a metric of weather variability. The solution utilizes the Ecowitt API, Python programming, and GitHub for scheduled script execution. The results are displayed on Blogger as a widget that updates in real time. The entire system is fully automated and requires no manual intervention.

DEVELOPMENT OF A HYBRID DATA ENCRYPTION SYSTEM

2025-05-26T08:24:28+00:00

A software application has been developed that allows encrypting and decrypting data and provides the simplicity of symmetric key exchange through unsecured channels.

RESEARCH INTO THE PRINCIPLES OF WEB APPLICATION DESIGN USING THE EXAMPLE OF DEVELOPING AN ELECTRONIC BOARD FOR DISTANCE LEARNING

2025-05-04T13:36:49+00:00

The principles of modern web application design were explored using the development of a real-time collaborative electronic board for educational purposes as a practical case. A set of contemporary technologies was selected to ensure scalability, responsiveness, and real-time interaction. As a result, a functional prototype was implemented, reflecting the specifics of distance learning tools and addressing the practical challenges of building interactive web applications.

GAME-BASED INCENTIVES IN THE DESIGN OF USER FEEDBACK SYSTEMS

2025-05-20T23:33:49+00:00

Bug detection and fixing are crucial for game stability and quality. While professional testing is key, player feedback is increasingly important. Many players lack motivation to report bugs. Implementing in-game rewards can encourage active bug reporting.

PERFORMANCE OPTIMIZATION METHODS FOR SINGLE-PAGE APPLICATIONS USING THE REACT FRAMEWORK

2025-05-19T13:03:52+00:00

The paper explores performance optimization methods for single-page applications using React. It focuses on lazy loading, code splitting, memoization, and dynamic imports. The impact of these techniques on client-side speed and efficiency is analyzed.

AUTOMATION OF ETL PROCESSES FOR LARGE DATA SETS

2025-05-18T08:47:48+00:00

The study examines current approaches and tools for ETL automation, highlighting their impact on processing performance and scalability. Key challenges and strategies for optimizing ETL workflows are also discussed.

DEVELOPMENT OF A WEB APPLICATION FOR ONLINE CHAT BASED ON NODE.JS

2025-05-19T15:33:48+00:00

This study presents the development of a real-time web-based chat application built using React for the frontend and Node.js for the backend. The application enables users to send and receive text messages, media files (including photos, videos, voice messages, GIFs), and documents of various types. Additional features include emoji support, language switching, message history viewing, and profile customization. The system ensures secure authentication and allows users to change their passwords within the interface. MongoDB serves as the primary database, with Supabase integrated for specific backend services. The architecture is designed for responsiveness, scalability, and a seamless user experience across different devices and browsers.

DEVELOPMENT OF A WEB APPLICATION FOR PROJECT MANAGEMENT BASED ON NODE.JS

2025-05-19T09:41:30+00:00

This study presents the development of a web application for managing projects and tasks, built using Node.js for the backend and React for the frontend. The system includes user authentication, project and task assignment, time tracking, financial monitoring, and messenger integration to enhance communication. The chosen architecture ensures scalability and usability, focusing on effective team coordination and transparent project execution.

RESEARCH AND DEVELOPMENT OF THE ORM-SYSTEM IN JAVA PROGRAMMING

2025-05-19T19:56:57+00:00

This paper presents the development of a lightweight, custom Object-Relational Mapping (ORM) system in Java aimed at simplifying database operations for Java applications. The project resulted in a functional and extensible solution that provides essential CRUD operations, automatic mapping between Java classes and database tables. Designed and implemented entirely by a solo developer, the system demonstrates how core ORM functionality can be achieved without relying on external libraries such as Hibernate. The research explores common patterns in ORM design and offers a practical example of building a database abstraction layer from scratch using JDBC and reflection. This project validates the feasibility of constructing a tailored ORM for educational or lightweight production use cases.

FEATURES OF USING THE DJANGO FRAMEWORK FOR WEBSITE DEVELOPMENT

2025-05-07T20:41:15+00:00

The paper analyzes the key features of the Django framework, including its architecture, built-in tools, and security mechanisms that enable efficient and rapid website development. Django is presented as a modern solution for building dynamic, scalable, and secure web applications.

DEVELOPMENT OF A SERVICE WITH AUTOMATED TEXT TRANSLATION USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES

2025-05-15T20:10:19+00:00

This paper presents a web application for automatic translation of song lyrics using artificial intelligence. The system combines Django and React, integrates the OpenAI API for translation, and supports model training based on user data, ensuring a high level of stylistic consistency with the original.

USING ASP.NET AND REACT.JS FOR THE DEVELOPMENT OF A PLATFORM SUPPORTING UKRAINIAN ARTISTS

2025-05-01T06:45:19+00:00

The article presents the architecture and implementation features of the ArtUA platform designed to support and promote Ukrainian artists. The project uses the ASP.NET framework for backend development and the React.js library for frontend. Special attention is paid to user interaction, scalability, and opportunities for creative community engagement. The platform ensures efficient content management and personalized artist portfolios.

DEVELOPMENT OF AN INFORMATION PLATFORM FOR ORGANIZING THE EDUCATIONAL PROCESS IN A FOREIGN LANGUAGE

2025-05-13T17:09:45+00:00

This paper presents the development of an information platform aimed at managing the educational process in a foreign language school. The system encompasses user roles such as administrator, teacher, and student, with core functionality including group management, lesson scheduling, Zoom integration, automatic homework generation, and performance monitoring.

DEVELOPMENT OF A WEB APPLICATION FOR SMM SPECIALISTS BASED ON NEXT.JS

2025-05-20T17:49:06+00:00

This study presents the development of the web application, aimed at optimizing daily tasks of SMM specialists. Built on the Next.js framework, the system focuses on usability, intuitive design, and performance. Key features include content creation, post scheduling, and visual theme management for Instagram profiles. The application’s architecture enables all essential tasks to be completed within a single environment, eliminating the need for third-party tools and enhancing workflow efficiency and content quality.

RESEARCH OF SEO AUTOMATION TECHNOLOGIES USING PLUGINS FOR CRM SYSTEMS

2025-05-19T18:43:01+00:00

This study examines modern technologies for automating SEO processes using plugins in CRM systems, focusing on WordPress. A comparative analysis of existing SEO plugins revealed limitations in CRM-specific workflows. To address this, a custom plugin was developed to automate metadata generation, sitemap updates, and keyword analysis.

RESEARCHING THE FEDORA DISTRIBUTION

2025-04-16T17:07:00+00:00

Fedora is one of the leading Linux distributions, widely used across various fields — from personal use to software development and enterprise solutions. The relevance of researching Fedora is driven by rapid changes in the technological landscape, increasing security demands, and the growing interest in open-source software.Given this dynamic environment, analyzing the capabilities and functionality of Fedora is important for developers, system administrators, and end users alike.

DEVELOPMENT OF THE WEB APPLICATION “SkillUp” FOR ORGANIZING ONLINE CURRICULUM BASED ON LARAVEL

2025-05-19T09:12:00+00:00

This study presents the development of an interactive online course interface using React.js with a component-based architecture built on functional components and hooks. State management is implemented via the Context API, providing centralized data handling and simplified code maintenance. React Router with lazy loading is employed for efficient routing and performance optimization. The responsive design is achieved through CSS Flexbox and Grid layouts to ensure proper display across various screen sizes. Interactive features include progress indicators, quiz-based assessments, and results visualization, while data exchange with the backend is handled via a RESTful JSON API.

RFVIEW: CENTOS AND WINDOWS 11

2025-04-16T17:11:16+00:00

A comparison of the CentOS and Windows 11 operating systems reveals significant differences in their functional purposes, usage approaches, and adaptability to various tasks. These systems represent different ideologies in software development, which affects their performance, security, compatibility, and overall user convenience. Studying both operating systems provides a deeper understanding of their strengths and weaknesses, helping users make an informed choice based on their specific needs and usage conditions

DEVELOPMENT OF A ROGUELIKE GAME ON UNITY

2025-05-19T02:22:28+00:00

This paper presents the development process of a RogueLike game using the Unity game engine. The research explores key aspects of the genre and the technical implementation within Unity. The result is a playable prototype demonstrating core RogueLike mechanics. The findings highlight the capabilities of Unity for indie game development.

DEVELOPMENT OF A WEB APPLICATION FOR PERSONALIZED RECIPE SEARCH

2025-05-20T09:01:34+00:00

This article presents the development of a modern web application for searching recipes by ingredients. The goal is to create a user-friendly and fast web platform based on current technologies such as React.js, Next.js, and MongoDB. The result is an intuitive system where users can search for recipes based on available ingredients, filter them by preferences, and view detailed nutritional information.

Generation of Sounds for Musical Instruments in a Tuning Software

2025-05-21T00:06:35+00:00

This study focuses on generating accurate sound models for musical instruments, such as guitar, violin, and bass, to develop a software tuner. By replicating acoustic characteristics like harmonics and timbre, the tuner analyzes input signals and provides precise tuning feedback. The approach leverages digital signal processing and libraries like Tone.js, offering potential for broader instrument support and mobile application integration.

REVIEW OF LINUX MINT AND WINDOWS 10

2025-04-16T17:02:18+00:00

In today's information environment, Linux-based operating systems play a key role, especially as servers, as well as in scientific, educational, and everyday use. Linux Mint is one of the most popular distributions, known for its user-friendliness and focus on ease of use [1]. Linux Mint consistently ranks in the top 5 distributions according to DistroWatch [2], second only to MX Linux. One of the main advantages of this distribution is its pre-installed graphical environment and low hardware requirements. The main editions of Linux Mint are: Cinnamon, which features a modern interface with smooth animations, customizable panels, and a user-friendly menu;MATE, a lightweight version with a classic interface, suitable for users with older PCs; XFCE, the least resource-demanding edition, ideal for very old or low-spec devices.

ANALYSIS OF VIRTUALBOX INTERACTION METHODS FOR INFRASTRUCTURE AUTOMATION

2025-05-16T12:42:57+00:00

Infrastructure as Code (IaC) has become a leading methodology in modern server infrastructure management. It enables automated deployment and consistent configuration of server environments by representing infrastructure definitions as code. This approach allows administrators to leverage version control, change tracking, code review, and CI/CD practices, resulting in more reliable and scalable systems. However, effective implementation of IaC requires programmable access to the underlying infrastructure via application programming interfaces (APIs). This paper focuses on the virtualization engine VirtualBox, which forms the core of our faculty’s infrastructure. Although VirtualBox provides several APIs, such as COM/XPCOM, a command-line interface, and a web service, its integration with modern IaC tools remains limited. The objective of this research is to explore these interfaces and design an object-oriented C# wrapper that enables seamless use of VirtualBox functionality within different virtual environment management tools.

THE DEVELOPMENT OF A CLOUD-BASED WEB APPLICATION FOR PERSONAL FINANCIAL MANAGEMENT

2025-05-07T20:13:26+00:00

The article presents the development process of a web application for personal financial management using Google Firebase cloud technologies. It describes the system architecture, selected development tools, interface design, and main functionality. The application enables users to track income and expenses, view analytics, create custom categories, and manage multiple accounts. Emphasis is placed on the importance of a clean and intuitive interface for effective financial planning.

DEVELOPMENT OF A TELEGRAM BOT AND APPLICATION ON THE MERN TECHNOLOGY STACK FOR MANAGING SUBSCRIPTIONS AND USERS OF INFORMATION RESOURCES

2025-05-19T11:28:03+00:00

This study presents the development of a subscription management system for Telegram-based information resources. The system consists of two integrated software components: a Telegram bot developed using Node.js and MongoDB, responsible for handling user subscription, payments and automated notifications and a web application built on the MERN stack (MongoDB, Express.js, React, Node.js), providing administrators with tools for user management, subscription status monitoring and system oversight. The solution ensures automation of subscription workflows, improves user experience and provides a scalable architecture for managing paid access to Telegram channels and groups

UBUNTU AS A UNIVERSAL OPERATING SYSTEM: AN ANALYSIS OF ADVANTAGES AND DISADVANTAGES

2025-04-16T17:08:50+00:00

Ubuntu is one of the most popular Linux-based operating systems. Its popularity is driven by ease of use, system stability, open-source nature, and strong community support. This system is widely used both in server environments and on personal computers due to its flexibility and adaptability to a variety of tasks.In academic literature, Ubuntu is examined from several key perspectives: its efficiency in server computing, its role in the development of cloud technologies, and its usability in everyday life. According to a number of researchers, Ubuntu is a leading OS in the implementation of cutting-edge technologies such as containerization (Docker, Kubernetes) and artificial intelligence support. Other authors emphasize its importance for educational and research purposes, thanks to its accessibility and support for a wide range of software.

ONLINE BOOK CROWDFUNDING PLATFORM

2025-04-14T20:49:43+00:00

This paper presents the development of a functional and cost-effective web platform for crowdfunding book projects, tailored to the needs of authors and readers. The project resulted in a Minimum Viable Product (MVP) built using Ruby on Rails, PostgreSQL, and modern frontend tools such as Tailwind CSS and Stimulus. The platform integrates key services, including Monobank and YouTube APIs, and supports full interaction between creators and audiences. The research demonstrates the feasibility of creating a scalable solution by a solo developer.

DEVELOPMENT OF A REMOTE DATA DELETION SYSTEM ON ANDROID DEVICES AS A MOBILE SECURITY ELEMENT

2025-05-19T11:49:54+00:00

This paper explores the development of a remote data deletion system for Android devices, focusing on data protection in case of device loss, theft, or compromise. Built using Flutter for cross-platform development, Firebase for cloud synchronization, and Android’s native APIs, the proposed solution enables secure and selective removal of personal content, contacts, messages, and application data. The system is designed to function under limited connectivity and enforces proper permission handling and user authentication to minimize risks of abuse. The architecture allows future integration of anomaly detection and AI-enhanced decision-making for proactive mobile security.