Information technologies in economics and environmental sciences
type: channel
description: ISSN: 3083-7502 UDC 33+502]:004.9 National University of Life and Environmental Sciences of Ukraine Year of foundation: 2017 Published 2 times a year State registration: Media identifier: R40-06595. Decision of the National Council of Ukraine on Television and Radio Broadcasting No. 2543, Protocol No. 25 dated 20 November 2025. The journal is published in electronic form (posted on the website of the NUBIP of Ukraine https://journals.nubip.edu.ua/index.php/Inf/uk) Thematic focus – dissemination of information about the results of scientific and research developments in: information technologies and management systems, computer systems and networks, information protection technologies in environmental management, economic cybernetics, artificial intelligence and machine learning.
publisher: Національний університет біоресурсів і природокористування України
language: en
publication name: Information technologies in economics and environmental sciences
issn: 3083-7502
items: ASPECTS OF DETECTING CYBER THREATS IN UNIVERSITY NETWORK TRAFFIC
items: CYBER RESILIENCE OF UKRAINIAN HIGHER EDUCATIONAL INSTITUTIONS IN A WARFARE CONDITION
items: SECURITY CONVERGENCE IN INDUSTRY 5.0: LESSONS FROM GAME ANTI-CHEAT SYSTEMS FOR DIGITAL TWIN PROTECTION IN COMPUTER SYSTEMS
items: CREATION OF A CLOUD IT ENVIRONMENT IN ORGANIZATIONS
items: RESEARCH ON THE IMPACT OF LARGE LANGUAGE MODELS ON WEBSITE DEVELOPMENT USING THE VUE FRAMEWORK
items: INFORMATION TECHNOLOGIES FOR AUTOMATING THE PROCESSING OF CANDIDATE CV TO INCREASE THE EFFICIENCY OF IT TEAM FORMATION
items: SOLID AS A SYSTEM OF CONSTRUCTIVE CONSTRAINTS IN SOFTWARE ARCHITECTURE DESIGN
items: HYBRID CLUSTERING OPTIMIZATION MODEL FOR INTELLIGENT DECISION SUPPORT SYSTEMS
items: ENHANCING HUMAN-COMPUTER INTERACTION: THE ROLE OF INTELLIGENT USER INTERFACES IN EMBEDDED AND IOT SYSTEMS
items: TECHNOLOGY FOR ANALYZING THE QUALITY OF HASH FUNCTION CHARACTERISTICS
items: DETERMINING THE STAGES OF STRAWBERRY MATURITY USING CONVOLUTIONAL NEURAL NETWORK MODELS
items: INTERACTION AND FEEDBACK LOOPS IN USER INTERFACE FOR DIGITAL ENGINEERING DESIGN
items: INFORMATION SYSTEM TO SUPPORT ASSESSMENT OF MASTER'S THESIS: AN EXAMPLE OF IMPLEMENTATION IN THE DIGITAL EDUCATIONAL ENVIRONMENT OF A HIGHER EDUCATION INSTITUTION
items: ANALYSIS OF THE EDUCATIONAL OFFER FOR ADMISSION TO HIGHER EDUCATION INSTITUTIONS IN 2024 USING POWER BI
items: AUTONOMOUS VEHICLES ESSE: UNSUPERVISED ONLINE LEARNING WITH SEMANTIC SEGMENTATION CONCEPT
items: DESIGN OF A CARTRIDGE TEMPERATURE MEASURING DEVICE
items: MODELING THE DYNAMICS OF TRAFFIC FLOWS BASED ON QUEUEING THEORY FOR INTEGRATION INTO INTELLIGENT TRANSPORTATION SYSTEMS
items: MATHEMATICAL MODELING AND ADAPTATION STRATEGIES IN THE CONFRONTATION BETWEEN CRYPTOCURRENCIES AND QUANTUM COMPUTERS
items: ALGORITHMS FOR THE DEVELOPMENT OF A KNOWLEDGE BASE TO ENHANCE DECISION SUPPORT SYSTEMS IN ADDRESSING CYBERSECURITY CHALLENGES
items: USE OF OLAP AND DATA MINING TECHNOLOGIES IN DECISION SUPPORT SYSTEMS IN GREENHOUSE FARMING
items: INTELLIGENT CYBER THREATS RECOGNITION SYSTEMS AS A COMPONENT OF THE INFORMATION SECURITY SYSTEM IN TRANSPORT
items: CHARACTERISTICS OF SORTING ALGORITHMS OPERATION IN PYTHON
items: DESIGNING A COMPUTER SYSTEM FOR ANALYSING THE CONDITION OF PLANTS
items: SMOOTHING INCOMPLETE DATA SERIES OF ENVIRONMENTAL MONITORING STATIONS USING PREDICTIVE MODELS
items: DETECTION OF COMMUNITIES IN SOCIAL NETWORKS
items: IMAGE RECOGNITION SYSTEM BASED ON A NEURAL NETWORK WITH DEEP LEARNING
items: Безперервне управління фінансовими ресурсами комерційного банку
items: Фінансові інструменти екологічної економіки
items: Деякі питання тестування та обробки формальних текстів за допомогою системи SAD
items: Криптографічна система з підтримкою базових алгоритмів зміни вхідних даних

ASPECTS OF DETECTING CYBER THREATS IN UNIVERSITY NETWORK TRAFFIC
type: item
description: Modern cyber threats to telecommunications systems and networks are characterized by a high degree of concealment, adaptability, and diversity. This complicates their rapid detection in network traffic, particularly at universities. Given the changing nature of cyberattacks, traditional methods based on signature analysis and fixed rules are proving insufficiently effective for identifying new or modified threats. In this regard, the development of intelligent hybrid approaches is becoming increasingly important. Such methods are capable of analyzing the behavioral characteristics of university traffic and adapting to its changes. The article presents a method for detecting cyber threats based on a combination of ensemble clustering and Bayesian probabilistic modeling methods. At the first stage, machine learning is used to identify hidden behavioral features of network connections in the university network based on various clustering algorithms. The resulting behavior embeddings are then used as input data for constructing a Bayesian network that describes the probabilistic dependencies between behavior parameters and anomaly features. The proposed approach not only allows detecting deviations from normal traffic behavior, but also ensures the interpretability of decisions in the field of information security. The practical value of the method lies in its potential for use in network traffic monitoring systems in corporate networks.
subject: Cybersecurity section
  topic: section
subject: network traffic
  topic: keywords
subject: network
  topic: keywords
subject: university
  topic: keywords
subject: behavioral analysis
  topic: keywords
subject: Bayesian network
  topic: keywords
subject: clustering
  topic: keywords
subject: machine learning
  topic: keywords
subject: method
  topic: keywords
subject: cybersecurity
  topic: keywords
creator: Valeriy Lakhno
creator: Sergii Mamchenko
creator: Volodymyr Matiievskyi
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 71
ending page: 78

CYBER RESILIENCE OF UKRAINIAN HIGHER EDUCATIONAL INSTITUTIONS IN A WARFARE CONDITION
type: item
description: The article examines the problem of ensuring cyber resilience of higher education institutions (HEIs) by developing and implementing a comprehensive cyber defense architecture. It is shown that the effectiveness of such a system is determined by the ability to integrate educational, administrative, and resource subsystems, taking into account their interdependence and specifics of functioning. The main risks and consequences of cyber attacks are considered. The principles of building a secure information infrastructure and the criteria that a reliable and effective HEI cybersecurity system must meet are outlined. A model for managing HEI information flows and resources using neural network technologies and intelligent decision support systems is proposed. The results of the study demonstrate the feasibility of using modeling tools to predict threats, optimize resource allocation, and increase the resilience of the educational environment to cyber risks.
subject: Cybersecurity section
  topic: section
subject: cybersecurity
  topic: keywords
subject: information infrastructure
  topic: keywords
subject: development trajectories
  topic: keywords
subject: cybersecurity systems
  topic: keywords
subject: infrastructure cyber resilience
  topic: keywords
subject: neural network technologies
  topic: keywords
subject: communication networks
  topic: keywords
creator: Yaroslav Shestack
creator: Svitlana Tsiutsiura
creator: Olena Kryvoruchko
creator: Valerii Lakhno
creator: Dmуtro Kasatkin
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 56
ending page: 70

SECURITY CONVERGENCE IN INDUSTRY 5.0: LESSONS FROM GAME ANTI-CHEAT SYSTEMS FOR DIGITAL TWIN PROTECTION IN COMPUTER SYSTEMS
type: item
description: Digital Twin (DT) systems are critical to the advancement of Industry 5.0, enabling synchronized, intelligent modeling of physical assets for simulation, monitoring, and predictive control. However, these platforms' growing integration of AI, telemetry data, and autonomous decision-making exposes them to escalating cybersecurity threats. This study explores how established security practices from the video game industry—specifically anti-cheat technologies—can be repurposed to address the evolving security demands of DTs. We conducted a comparative literature review and architecture mapping between video game environments and DT infrastructures, focusing on behavioral spoofing, telemetry injection, and runtime tampering. Additionally, we performed simulations using statistical and machine learning models (Z-score filters, SVM, LSTM) to assess the adaptability of game-based detection mechanisms. Results show that AI-assisted behavioral modeling significantly enhances threat detection accuracy while maintaining low latency. We propose a layered, privacy-conscious cybersecurity framework for digital twins based on these findings. This research demonstrates that the convergence of anti-cheat systems and computer engineering offers a viable strategy for building resilient and ethically aligned digital infrastructure in the Industry 5.0 era.
subject: Computer Engineering Section
  topic: section
subject: digital twin
  topic: keywords
subject: computer engineering
  topic: keywords
subject: industry 5.0
  topic: keywords
subject: cybersecurity
  topic: keywords
subject: game anti-cheat
  topic: keywords
subject: behavior modeling
  topic: keywords
subject: telemetry integrity
  topic: keywords
subject: intelligent infrastructure
  topic: keywords
creator: Volodymyr Nazarenko
creator: Dmytro Kasatkin
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 49
ending page: 55

CREATION OF A CLOUD IT ENVIRONMENT IN ORGANIZATIONS
type: item
description: The rapid development of information technologies is driving the widespread adoption of cloud computing across various areas of organizational activity. The diversity of cloud services, their providers, and service models necessitates a well-grounded selection of optimal solutions that best meet the needs of a particular organization, taking into account economic, technical, functional, and security criteria [1]. Selecting an appropriate configuration of cloud services is a complex task, as it requires consideration of numerous variable parameters and potential risks. Traditional approaches based on expert assessments prove to be insufficiently effective under the complex and dynamic conditions of the market, which highlights the relevance of automated decision support systems in this domain. One of the key stages in creating a cloud IT environment within organizations is the development of a decision support system that enables the structured analysis of available alternatives through mathematical models of multi-criteria analysis. The application of such methods makes it possible to formalize the process of comparing options, account for numerous parameters, and make well-founded management decisions. At the same time, the development of such systems is associated with a number of technical challenges, in particular ensuring the correct processing of input data, the optimal selection of evaluation methods, and the design of a flexible architecture capable of adapting to specific user requirements.
subject: Computer Engineering Section
  topic: section
subject: decision support systems (DSS)
  topic: keywords
subject: cloud services
  topic: keywords
subject: IT environment
  topic: keywords
creator: Yevheniy Nikitenko
creator: Anatolij Gladkij
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 42
ending page: 48

RESEARCH ON THE IMPACT OF LARGE LANGUAGE MODELS ON WEBSITE DEVELOPMENT USING THE VUE FRAMEWORK
type: item
description: This paper investigates the transformative impact of large language models (LLMs) on modern component-based web development, using the Vue.js framework as a representative case study. By synthesizing the results of a broad empirical study on software development with the assistance of LLMs, we analyze a paradigmatic shift from native framework-driven workflows to workflows augmented by LLMs. The analysis spans the entire project lifecycle, revealing significant productivity gains during the implementation and deployment phases, particularly in component creation, test automation, and infrastructure configuration. However, these advantages are counterbalanced by critical challenges, including concerns about code reliability, the perpetuation of version conflicts due to outdated training data, and the risk of cognitive offloading among developers. We argue that the integration of LLMs redefines the role of the senior developer, transforming it from a primary code generator into an expert validator and architectural overseer. The paper concludes by outlining key risks and proposing directions for future research, emphasizing the need to develop framework-specific benchmarks for evaluating the quality of AI-generated code and to conduct longitudinal studies on the maintainability of Vue.js applications developed with the assistance of LLMs.
subject: Computer Science Section
  topic: section
subject: large language models
  topic: keywords
subject: Vue.js
  topic: keywords
subject: web development
  topic: keywords
subject: intelligent automation
  topic: keywords
subject: UI components
  topic: keywords
subject: productivity
  topic: keywords
subject: software engineering
  topic: keywords
creator: Maksym Nedoshev
creator: Viktor Kyrychenko
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 36
ending page: 41

INFORMATION TECHNOLOGIES FOR AUTOMATING THE PROCESSING OF CANDIDATE CV TO INCREASE THE EFFICIENCY OF IT TEAM FORMATION
type: item
description: The article is devoted to the development of an information technology for automated processing of candidate CV in PDF format using the Python programming language. The approach to extracting, structuring, and further analyzing data with the use of the pdfplumber, spaCy, and pandas libraries is presented. The proposed module enables the identification of key resume elements, including education, skills, contact information, and work experience, followed by the formation of structured data in JSON format. Special attention is given to ensuring the universality of the algorithm for CV with arbitrary structure and Ukrainian-language content. The paper describes the main stages of implementing the software solution, including data flow diagrams, PDF processing schemes, and examples of unit testing of system functions. The developed technology can be used to automate the initial stage of recruitment and integrate with HR analytics systems, thereby improving the accuracy and speed of candidate data processing in the IT team formation process.
subject: Computer Science Section
  topic: section
subject: information technology
  topic: keywords
subject: Python
  topic: keywords
subject: CV
  topic: keywords
subject: recruitment automation
  topic: keywords
subject: spaCy
  topic: keywords
subject: NLP
  topic: keywords
subject: HR system
  topic: keywords
creator: Roman Zolotukha
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 28
ending page: 35

SOLID AS A SYSTEM OF CONSTRUCTIVE CONSTRAINTS IN SOFTWARE ARCHITECTURE DESIGN
type: item
description: The article presents SOLID as a system of constructive constraints that disciplines the degrees of freedom in design and transforms the evolution of software systems into a controlled process. It explains the relationship of the principles with the foundations of object-oriented programming, design patterns, and architectural styles. Non-obvious effects are examined, including premature abstractions under OCP, hidden configuration coupling under DIP/DI, class explosion and responsibility fragmentation under SRP/ISP, and semantic violations of LSP that are not captured by type signatures. An operational approach to decision validation is proposed through metrics, contract-based tests, and threshold controls for introducing abstractions, along with practical decision-making protocols.
subject: Software Engineering Section
  topic: section
subject: SOLID
  topic: keywords
subject: Object-Oriented Programming
  topic: keywords
subject: Software Architecture
  topic: keywords
subject: Design Patterns
  topic: keywords
subject: Cohesion
  topic: keywords
subject: Coupling
  topic: keywords
subject: Code Quality Metrics
  topic: keywords
subject: Dependency Inversion (DI/IoC)
  topic: keywords
creator: Ivan Kornilov
creator: Ganna Weigang
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 19
ending page: 27

HYBRID CLUSTERING OPTIMIZATION MODEL FOR INTELLIGENT DECISION SUPPORT SYSTEMS
type: item
description: The article presents a comprehensive approach to optimizing clustering algorithms within decision support systems (DSS) in big data environments. It analyzes issues of scalability, computational complexity, and result stability that are typical of classical methods such as K-Means, DBSCAN, and Agglomerative Clustering. An improved hybrid algorithm, K-Means++ Hybrid, is proposed, combining parallel computing mechanisms, adaptive parameter tuning, and dynamic control of the iterative search process. The methodological foundation of the research is based on systems analysis, mathematical modeling, and experimental testing using datasets from the UCI Repository and GPU acceleration technologies (CUDA). Experimental results confirm that the proposed approach reduces clustering execution time by approximately 43% compared to baseline algorithms, while increasing the silhouette coefficient to 0.73 and reducing CPU energy consumption by 20–25%. The resulting model demonstrates high robustness when processing heterogeneous datasets and can be integrated into systems for traffic flow analysis, financial risk assessment, and environmental monitoring. The developed approach provides a foundation for building adaptive intelligent data analysis modules that support scalability, result interpretability, and real-time operation in streaming analytics systems. Future research should focus on integrating hybrid clustering with deep learning models and evolutionary optimization algorithms.
subject: Software Engineering Section
  topic: section
subject: Clustering
  topic: keywords
subject: Big Data
  topic: keywords
subject: Decision Support Systems
  topic: keywords
subject: Algorithm Optimization
  topic: keywords
subject: Parallel Computing
  topic: keywords
subject: Hybrid Models
  topic: keywords
subject: Machine Learning
  topic: keywords
creator: Ganna Weigang
creator: Yurii Naurynskyi
creator: Kateryna Myronchuk
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-08-10
publication date: 2025-08-10
starting page: 8
ending page: 18

ENHANCING HUMAN-COMPUTER INTERACTION: THE ROLE OF INTELLIGENT USER INTERFACES IN EMBEDDED AND IOT SYSTEMS
type: item
description: The rapid evolution of innovative technologies has significantly transformed digital applications and human activities. Advances in hardware, digital software, and interactive user interfaces have made user experience (UX) design a critical factor in various industries, including healthcare, aerospace, construction, and military sectors. Human-Computer Interaction (HCI) is vital in enhancing system usability by ensuring intelligent interaction systems are user-centric and accessible. Integrating intelligent systems, the Internet of Things (IoT), and embedded technologies presents new challenges and opportunities in interface design. Additionally, as industries adopt intelligent automation and digital transformation strategies, the demand for adaptive, user-friendly interfaces grows. Understanding how users interact with these technologies is essential to optimizing efficiency and improving overall user satisfaction. This study explores the principles of HCI and interaction design, analyzing how digital and analog interfaces contribute to practical system usability. A qualitative approach was adopted, reviewing contemporary research on user interface (UI) design, interactive systems, and intelligent applications. The study also considers case studies from various industries where UX and interface optimization have significantly impacted system performance and user satisfaction. Data collection included literature analysis, expert interviews, and usability testing reports, ensuring a comprehensive understanding of the challenges and advancements in interaction design. The research methodology also incorporates a comparative analysis of traditional and emerging interface models to identify best practices in designing adaptive and intelligent systems. Findings indicate that well-designed interfaces enhance user engagement, efficiency, and system functionality. Factors influencing usability include adaptive design, accessibility considerations, and intuitive user experie…
subject: All articles from the issue
  topic: section
subject: user interface design
  topic: keywords
subject: user experience
  topic: keywords
subject: smart systems
  topic: keywords
subject: system interaction
  topic: keywords
subject: computer engineering
  topic: keywords
creator: Volodymyr Nazarenko
creator: Bohdan Ostroushko
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-01-25
publication date: 2025-01-25
starting page: 65
ending page: 77

TECHNOLOGY FOR ANALYZING THE QUALITY OF HASH FUNCTION CHARACTERISTICS
type: item
description: The technology for analyzing the quality of a hash function is proposed. To test it, a specially developed hash function, which is a simplified analog of MD5, is used. It is shown that the traditional quality assessment of the obtained hash values based on the number of collisions has a significant drawback - high computational complexity. Therefore, the technology of quality assessment is reduced to the approximation of the analytical expression of the function, which is amenable to mathematical analysis by traditional methods applicable to polynomials. A better quality hash function is a hash function whose histogram is as close as possible to the graph of the function y=x. This will correspond to the Gaussian distribution of values. When using the proposed technology, it is necessary to develop criteria for classifying functions according to deviations from the ideal distribution of values by one or more of the following indicators: variance; mathematical expectation; arithmetic mean; geometric mean, etc.
subject: All articles from the issue
  topic: section
subject: hash function
  topic: keywords
subject: collisions
  topic: keywords
subject: function interpolation
  topic: keywords
subject: function approximation
  topic: keywords
subject: quality of a hash function
  topic: keywords
creator: Andrii Sahun
creator: Maksym Misiura
creator: Milana Bilych
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-01-25
publication date: 2025-01-25
starting page: 78
ending page: 84

DETERMINING THE STAGES OF STRAWBERRY MATURITY USING CONVOLUTIONAL NEURAL NETWORK MODELS
type: item
description: Throughout the history of agriculture, crop cultivation and harvesting technologies have been constantly improving, easing the work in the field and increasing the efficiency of fruit harvesting. Today, modern technologies, including artificial intelligence, are also penetrating the agro-industrial sector. Its use is becoming increasingly widespread every year. This technology allows agricultural producers to obtain large amounts of data in real-time, analyze them, and make decisions regarding fertilizer application, pesticide use, irrigation, and determining the ripeness of fruits or plants. An equally important aspect of artificial intelligence solutions is the tracking of carbon footprints, which gives an advantage when entering European markets. The combination of the latest developments in unmanned vehicles and robots allows for an increase in productivity and production volumes in agriculture. An important part of modern agro-industry is computer vision — one of the fields of artificial intelligence, focused on creating intelligent systems capable of processing and analyzing visual information in a way similar to the human sensory system. Neural networks are often used in this technology for both image recognition and classification. This article presents a comparative analysis of various convolutional neural network models for classifying the ripeness stage of strawberries, namely MobileNetV2, MobileNetV3Small, and EfficientNetB0. The network was evaluated based on parameters such as training and validation accuracy, training and validation losses, and training time. The best results were found with the MobileNetV3Small network. The results and methodology of this research can be useful for both scientists and entrepreneurs working in the agro-industrial sector and implementing artificial intelligence in the production process.
subject: All articles from the issue
  topic: section
subject: artificial intelligence
  topic: keywords
subject: computer vision
  topic: keywords
subject: convolutional neural network
  topic: keywords
subject: MobileNet
  topic: keywords
subject: EfficientNet
  topic: keywords
creator: Oleksa Kachmarskyi
rights: Copyright (c) 2025 Information technologies in economics and environmental sciences https://creativecommons.org/licenses/by-sa/4.0
date: 2025-01-25
publication date: 2025-01-25
starting page: 14
ending page: 23

INTERACTION AND FEEDBACK LOOPS IN USER INTERFACE FOR DIGITAL ENGINEERING DESIGN
type: item
description: The article aims to review existing issues and look for novel ways of human-computer digital systems design and interaction. Such interaction takes place, as a rule, through an appropriate interface, which can be mechanical, digital, analog, with a touch screen, etc. For the end user of the relevant application or system, it is important how this interaction process will be implemented, presented, and programmed. That is, what controls, actions for interaction, and feedback mechanisms from the system to the user will be available. The research methods are based on the main methodologies of design and analysis of digital products with an emphasis on user experience, research of user requirements, the context of application use, and the presentation of the menu of interaction with a digital service. The article presents the results of a detailed description and modeling of the main process of user interaction with the feedback system (cyclic process). The context of using the application, the main desires and goals of the user when interacting, as well as the types of available options for interacting with the interactive system are taken into account. The seven-step process of user interaction presented in the paper includes functions, data, software systems and modules, appropriate software and hardware architecture, and methods of internal communication between cycle functions. A process of interactive interaction has been developed, which describes the full cycle from the beginning to the end of the user's work with any digital, analog, computing device, application, or service. This process can be used by designers, software developers, and scientists/researchers at the stage of planning a new interactive system or to improve an existing one.
subject: All articles from the issue
  topic: section
subject: HCI
  topic: keywords
subject: user interface
  topic: keywords
subject: computer engineering
  topic: keywords
subject: design engineering
  topic: keywords
subject: design
  topic: keywords
creator: Volodymyr Nazarenko
creator: Dmytro Kasatkin
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 53
ending page: 61

INFORMATION SYSTEM TO SUPPORT ASSESSMENT OF MASTER'S THESIS: AN EXAMPLE OF IMPLEMENTATION IN THE DIGITAL EDUCATIONAL ENVIRONMENT OF A HIGHER EDUCATION INSTITUTION
type: item
description: The digitization of education increasingly impacts fundamental business processes within modern higher education institutions. This study exemplifies the digitalization of specific processes involved in the preparation and presentation of master's thesis results. We have developed an information system designed to support the evaluation of master's theses through expert assessment and automated plagiarism detection, adhering to institutional regulations and general guidelines on academic integrity. Key business processes include user management, master's thesis evaluation management, and dissemination of research outcomes. These processes were decomposed following standards of structural and functional analysis and design, incorporating role assignment for potential system users. We propose implementing this system using the LMS Moodle platform, which facilitates resources for thesis text submission, document downloads, peer reviews, student counseling, and communication among educational stakeholders based on defined roles. Integration of the Unicheck plagiarism detection module within LMS Moodle enables efficient text similarity checks. Leveraging Learning Tools Interoperability (LTI) technology supported by LMS Moodle, electronic educational resources from the university's educational and informational portal can be seamlessly integrated with the master's theses repository. The study emphasizes that establishing an information and educational environment within a higher education institution and consolidating a unified user base will streamline the implementation of the proposed information system both organizationally and technologically, minimizing costs.
subject: All articles from the issue
  topic: section
subject: information system
  topic: keywords
subject: master's thesis
  topic: keywords
subject: assessment
  topic: keywords
subject: plagiarism check software
  topic: keywords
subject: LMS Moodle
  topic: keywords
creator: Maksym Mokriev
creator: Olena Kuzminska
rights: Copyright (c) 2025 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2025-01-25
publication date: 2025-01-25
starting page: 24
ending page: 36

ANALYSIS OF THE EDUCATIONAL OFFER FOR ADMISSION TO HIGHER EDUCATION INSTITUTIONS IN 2024 USING POWER BI
type: item
description: The article presents an analysis of the 2024 admission campaign to higher education institutions (HEIs) in Ukraine, investigating the relationship between the number of applications submitted by applicants and indicators characterizing educational offerings. The analysis was conducted using data from the Unified State Electronic Database on Education (USEDE) for 2024, applying the correlation-regression method. It is shown that there is a strong positive relationship between the volume of educational offerings and the number of applications to HEIs, while linear regression allows for a quantitative representation of this dependence, explaining nearly 50% of the sample. The article examines the impact of external factors, such as regional location, proximity to active combat zones, and HEI rankings, on the number of applications. The structure of the distribution of recommended places for admission under specific admission conditions is also presented. The conducted research reflects the peculiarities of demand formation for HEI services based on the results of the 2024 admission campaign and allows for optimizing approaches to planning educational programs, improving the efficiency of higher education institutions in Ukraine.
subject: All articles from the issue
  topic: section
creator: Inna Kostenko
creator: Yevhenii Klymenko
creator: Volodymyr Kharchenko
rights: Copyright (c) 2025 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2025-01-25
publication date: 2025-01-25
starting page: 37
ending page: 45

AUTONOMOUS VEHICLES ESSE: UNSUPERVISED ONLINE LEARNING WITH SEMANTIC SEGMENTATION CONCEPT
type: item
description: The presented study explores continuous adaptation techniques for monocular depth estimation and semantic segmentation to improve real-time scene understanding capabilities for autonomous vehicles and driver assistance systems. The proposed methodologies enable models to dynamically adjust to new information in video sequences, sustaining high performance amidst ongoing changes in scene appearance, lighting, and other contextual factors. The first contribution is continuous online adaptation for monocular depth estimation, eliminating the need for isolated fine-tuning techniques and retaining information across video frames. The method addresses data drift by perpetually adapting to new frames, preventing overfitting due to limited data diversity. Experience replay is integrated to stabilize the learning process and introduce minimal computational overhead. Techniques like auto-masking and velocity supervision help differentiate between stationary and moving objects, mitigating errors related to inconsistent depth cues. The study validates the effectiveness of the proposed approach through intra-dataset and cross-dataset adaptation scenarios, showing substantial accuracy gains while maintaining real-time runtime.
subject: All articles from the issue
  topic: section
subject: online adaptation
  topic: keywords
subject: unsupervised learning
  topic: keywords
subject: monocular depth estimation
  topic: keywords
subject: semantic segmentation
  topic: keywords
subject: autonomous cars
  topic: keywords
creator: Volodymyr Nazarenko
rights: Copyright (c) 2025 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2025-11-07
publication date: 2025-11-07
starting page: 8
ending page: 13

DESIGN OF A CARTRIDGE TEMPERATURE MEASURING DEVICE
type: item
description: The work is devoted to the current topic of designing and manufacturing mobile, portable, ergonomic and accurate devices for measuring disturbing extraneous factors (in particular, the temperature of the cartridge), which undoubtedly and significantly affect the accuracy of the performance of a military task, namely sniper shooting. The purpose of the article is to create a cartridge temperature measuring device that meets certain schematic, design and technological parameters, manufacture a product prototype, test it in operating conditions and debug the assembly process. In the material of the article, the effect of cartridge temperature on the qualitative characteristics of the shooting process was investigated, in particular, when the temperature of the charge and air changed by the same amount, it was concluded that an increase in the temperature of the charge of the cartridge and air contribute to a slight increase in the duration of the bullet’s flight and its final speed, but a significant increase in range her flight. The geometric design of the device is presented, namely, two variants of the design of a portable cartridge temperature measuring device were created depending on the indicator variant used. The area of the products differs by more than two times, the linear dimensions are 103x55 mm х mm and 54x39 mm х mm with almost the same height of the finished product, which is due to the use of different types of indicators and, accordingly, the need to be powered by different voltage ratings of power cells. Proposed prototypes of the device for measuring the temperature of the cartridge, which satisfy certain schematic, design and technological parameters, small batches of products of two varieties were directly manufactured, submitted for approval under operating conditions, and initial debugging of the assembly process was carried out. Based on the results of the tests, the supply chains of the components, the design of the device and the assembly tec…
subject: All articles from the issue
  topic: section
subject: cartridge
  topic: keywords
subject: temperature measurement
  topic: keywords
subject: device
  topic: keywords
subject: design
  topic: keywords
subject: indicator
  topic: keywords
subject: decoder
  topic: keywords
subject: layout
  topic: keywords
subject: geometric dimensions
  topic: keywords
subject: soldering
  topic: keywords
subject: assembly
  topic: keywords
subject: manufacturing
  topic: keywords
subject: testing
  topic: keywords
subject: production
  topic: keywords
creator: Viktorija Smolij
creator: Maryna Shepeleva
creator: Natan Smolij
creator: Nikita Shepelev
rights: Copyright (c) 2025 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2025-01-25
publication date: 2025-01-25
starting page: 54
ending page: 64

MODELING THE DYNAMICS OF TRAFFIC FLOWS BASED ON QUEUEING THEORY FOR INTEGRATION INTO INTELLIGENT TRANSPORTATION SYSTEMS
type: item
description: The article focuses on the study of traffic flow dynamics modeling in urban environments using queueing theory (QT). The research aims to develop a methodological approach to formalizing dynamic traffic flow processes, enabling their adaptation to modern intelligent transportation systems (ITS). Proposed mathematical models account for the stochastic nature of traffic flows and key performance indicators such as average waiting time, queue length, and throughput. Simulations of various transportation infrastructure scenarios integrating these models into ITS were conducted. The research findings confirm that applying QT under conditions of uneven traffic distribution significantly reduces delays, optimizes routing, and improves the efficiency of road infrastructure utilization. These results pave the way for further enhancements of urban transportation systems by integrating machine learning algorithms and big data analysis, allowing for consideration of the complex behavior of road users. The integration of QT models into ITS contributes to the improved efficiency of transport networks, fostering sustainable development of urban infrastructure. The proposed approaches are universal and can address pressing mobility challenges in contemporary urban agglomerations.
subject: All articles from the issue
  topic: section
subject: Traffic flow modeling
  topic: keywords
subject: queueing theory
  topic: keywords
subject: intelligent transportation systems
  topic: keywords
subject: traffic dynamics
  topic: keywords
subject: traffic flow optimization
  topic: keywords
subject: adaptive management
  topic: keywords
subject: urban mobility
  topic: keywords
subject: mathematical modeling
  topic: keywords
subject: transportation infrastructure
  topic: keywords
subject: congestion reduction
  topic: keywords
creator: Kateryna Myronchuk
creator: Ganna Weigang
rights: Copyright (c) 2025 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2025-01-25
publication date: 2025-01-25
starting page: 46
ending page: 53

MATHEMATICAL MODELING AND ADAPTATION STRATEGIES IN THE CONFRONTATION BETWEEN CRYPTOCURRENCIES AND QUANTUM COMPUTERS
type: item
description: This article is dedicated to studying the resilience of cryptocurrency systems (CCS) under new threats associated with the development of quantum computing. A differential game model is introduced, allowing for the formalization of the interaction between CCS and quantum computers (QC), as well as the analysis of their mutual influence. The research methodology is based on the application of differential game theory to model the dynamics of resource allocation between the parties and to evaluate their strategies under conditions of uncertainty and competition. Various scenarios of confrontation between CCS and quantum computing were considered during the modeling process, which made it possible to identify key patterns and factors that significantly affect the effectiveness of cryptographic protection, as well as the computational capabilities of attackers utilizing QCs. Special attention is given to the analysis of different methods for protecting digital assets under potential quantum threats. The results of the study may serve as a foundation for developing new cryptographic security standards and adaptive protection strategies that will remain effective amid the rapid growth of quantum computing capabilities
subject: All articles from the issue
  topic: section
subject: quantum computing
  topic: keywords
subject: cryptocurrencies
  topic: keywords
subject: cryptographic resilience
  topic: keywords
subject: mathematical modeling
  topic: keywords
subject: resource allocation
  topic: keywords
subject: quantum threats
  topic: keywords
subject: protection strategies
  topic: keywords
creator: Valeriy Lakhno
creator: Dmytro Kasatkin
rights: Copyright (c) 2025 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2025-01-25
publication date: 2025-01-25
starting page: 85
ending page: 91

ALGORITHMS FOR THE DEVELOPMENT OF A KNOWLEDGE BASE TO ENHANCE DECISION SUPPORT SYSTEMS IN ADDRESSING CYBERSECURITY CHALLENGES
type: item
description: This article presents the development of a modular decision support system (DSS) for cybersecurity, aimed at enhancing the protection of critical computer systems (CCS). The system is based on a fuzzy logic inference subsystem (FIS) model that utilizes data from sensors and SIEM systems to detect signs of threats, anomalies, and attacks through fuzzification of input values. A developed algorithm for forming a knowledge base of typical and emergency situations allows the system not only to effectively respond to known threats but also to analyze unforeseen situations. The application of the FIS module enables the creation of a multi-parameter image of CCS vulnerability, which ensures a more comprehensive and accurate assessment of their security.
subject: All articles from the issue
  topic: section
subject: critical computer systems
  topic: keywords
subject: cybersecurity
  topic: keywords
subject: decision support system
  topic: keywords
subject: security assessment
  topic: keywords
creator: Dmytro Kasatkin
creator: Semen Voloshyn
creator: Borys Gusev
creator: Volodymyr Matiievskyi
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 69
ending page: 78

USE OF OLAP AND DATA MINING TECHNOLOGIES IN DECISION SUPPORT SYSTEMS IN GREENHOUSE FARMING
type: item
description: In the modern world, technologies play a key role in many areas of life, including agriculture. Growing vegetables and fruits in closed ground structures is becoming increasingly popular and requires control over conditions and resources to increase yields, however, with the increase in the amount of data collected in monitoring systems, it becomes more difficult to effectively analyze the collected information. This article considers the use of OLAP and Data Mining technologies to increase the efficiency of growing vegetables and fruits in closed ground structures. The purpose of the study is to determine the feasibility and effectiveness of using these technologies to analyze large amounts of data collected during the cultivation of vegetables and fruits. The authors of the study analyze how OLAP and Data Mining can provide useful information for making decisions on optimizing growing processes to increase yields.
subject: All articles from the issue
  topic: section
subject: decision support system
  topic: keywords
subject: OLAP
  topic: keywords
subject: Data Mining
  topic: keywords
subject: data warehouse
  topic: keywords
subject: multidimensional cube
  topic: keywords
creator: Maryna Lendiel
creator: Bella Golub
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 8
ending page: 14

INTELLIGENT CYBER THREATS RECOGNITION SYSTEMS AS A COMPONENT OF THE INFORMATION SECURITY SYSTEM IN TRANSPORT
type: item
description: The transport industry, in particular the railway transport (RT), is increasingly using computerized systems for management, which makes it vulnerable to cyber attacks. Intelligent threat recognition systems are becoming important for the protection of information and cyber security in transport. Ensuring cyber security for information systems and automated control systems in transport is an important task for ensuring the national security of Ukraine. This makes it possible to prevent possible cyber attacks, preserve the confidentiality of information, ensure the reliable operation of the transport system and preserve the safety of citizens. The development and implementation of effective cyber security measures are necessary steps to ensure the stability and reliability of transport systems and the preservation of national security in Ukraine. This article describes the method of intelligent recognition of threats for information systems of transport management (on the example of railway transport – TZ). The method is based on discrete procedures and the use of logical functions and fuzzy sets.
subject: All articles from the issue
  topic: section
subject: transport
  topic: keywords
subject: automated control systems
  topic: keywords
subject: cyber security
  topic: keywords
subject: threat recognition
  topic: keywords
subject: intelligent systems
  topic: keywords
creator: Valeriy Lakhno
creator: Dmytro Kasatkin
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 62
ending page: 68

CHARACTERISTICS OF SORTING ALGORITHMS OPERATION IN PYTHON
type: item
description: This article is dedicated to the analysis of various sorting algorithms using the Python programming language and sorting algorithms in Cython. The study compares classic sorting methods, such as bubble sort, insertion sort, and quicksort, with the aim of determining their effectiveness for large datasets. Special attention is given to localization issues when sorting strings in non-English languages, particularly, the application of a specialized dictionary for the correct processing of the Ukrainian alphabet. Techniques for measuring performance and visualizing results in the form of graphs are presented, allowing a deeper assessment of the scaling of each algorithm depending on the dataset size.
subject: All articles from the issue
  topic: section
subject: Python
  topic: keywords
subject: Cython
  topic: keywords
subject: sorting algorithms
  topic: keywords
subject: large datasets
  topic: keywords
subject: localization
  topic: keywords
subject: Ukrainian alphabet
  topic: keywords
subject: sorting performance
  topic: keywords
subject: data visualization
  topic: keywords
creator: Viktor Kyrychenko
creator: Andrii Khomenko
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 15
ending page: 20

DESIGNING A COMPUTER SYSTEM FOR ANALYSING THE CONDITION OF PLANTS
type: item
description: This research is devoted to the topical issue of restoring agriculture in liberated territories, which is associated with the risks of mining, pollution, littering, overcoming the consequences of environmental disasters, soil degradation, etc., the need to carry out the specified work and conduct research on the possibility of growing plants in post-war conditions and the prospects for effective plant cultivation in areas of risky agriculture. The purpose of the article is to highlight the creation of an information system for analyzing the condition of plants, designed for agro-industrial activities related to the cultivation of bioenergy and cereal crops, which provides for the collection, processing, and recommendations on the condition of plants, which in turn allows determining the feasibility (rationality) of growing a particular plant variety in a particular region, plan field work, processing, and irrigation of plants. The article substantiates the need to conduct numerous experiments to identify plant development trends in the regions under study. It is proposed to use the collected statistical data to determine the appropriate (minimum necessary) amount of bioenergy and cereal crops, the necessary statistics on the reference indicators of normal plant development, and indicators of fruiting. A method is proposed for obtaining information about the current state of plants with detailed recording of development conditions and yield results, based on which means of abstraction should be used to develop the basis for an advisory information system built using appropriate methods of analysis and synthesis. A mathematical description of the determination of the effect of the environment and growing conditions (impact on plants) for any bioparameter is given: by plant weight, root or stem system length, number of damaged plants or number of seedlings, etc., designed to assess the suitability of a plant for agribusiness in a specific geographical region. The propo…
subject: All articles from the issue
  topic: section
subject: agro-industrial sector
  topic: keywords
subject: post-war recovery
  topic: keywords
subject: agricultural crops
  topic: keywords
subject: plant condition assessment
  topic: keywords
subject: development parameter calculation
  topic: keywords
subject: agrodrones
  topic: keywords
subject: plant parameter identification task
  topic: keywords
subject: information system
  topic: keywords
subject: Use-case
  topic: keywords
subject: Business Process Model and Notation
  topic: keywords
subject: Dataflow diagrams
  topic: keywords
creator: Viktorija Smolij
creator: Natan Smolij
creator: Anton Yantsevych
creator: Olexiy Iskorostenskyi
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 44
ending page: 52

SMOOTHING INCOMPLETE DATA SERIES OF ENVIRONMENTAL MONITORING STATIONS USING PREDICTIVE MODELS
type: item
description: The article examines the problem of incomplete data series in the analysis of data from environmental monitoring stations, its impact on the reliability of the obtained results and the prognostic suitability of input data, as well as data smoothing methods that allow minimizing the negative impact of data gaps. The absence of data in the series can manifest itself in practice as false zero values that can lead to significant deviations, as well as missing data, which in some cases hides trends in the dynamics of the series. At the same time, the analyst may not be aware of the presence of empty or null values, which, as a result, leads to false conclusions or predictions. Smoothing methods using a simple moving average and extrapolation allow to improve the quality of input data, and, as a result, to improve the predictive quality of the obtained predictive models. Using local forecasts to fill in missing values allows you to get the most accurate results instead of missing data and, as a result, improve the predictive quality of the developed forecast models. The accuracy of the results obtained instead of missing data is checked by calculating the main statistical indicators of the series with empty values and the complete series. Calculation of the parameters of forecasting models to fill the empty intervals can be based on previous data or the trend of the entire series. The results obtained in this study can be used in the future to fill incomplete series in the analysis of data from environmental monitoring stations or other series of data used for forecasting or analytical calculations.
subject: All articles from the issue
  topic: section
subject: environmental monitoring
  topic: keywords
subject: data series
  topic: keywords
subject: data series dynamics
  topic: keywords
subject: data gaps
  topic: keywords
subject: forecast
  topic: keywords
subject: predictive models
  topic: keywords
creator: Dmytro Nikolaienko
creator: Oleg Hustera
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 21
ending page: 30

DETECTION OF COMMUNITIES IN SOCIAL NETWORKS
type: item
description: One of the main threats is malicious programs (bots), fake accounts capable of imitating human behavior. At the moment, bots create a lot of problems, both for ordinary users and for those who use social networks to conduct a marketing campaign or conduct social research. Using bot profiles in social networks greatly distorts information about the real benefits and interests of portal users. Therefore, it is necessary to determine which users of the social network are programmed, and to be able to divide the flow of data into that generated by bots and by humans. The threatening scale of the use of social bots requires the creation of effective algorithms for their detection. Internet platforms and social services themselves are not too concerned about this problem. As a result, both ordinary users who organize various communities and companies that promote goods, brands, and services through social networks suffer. Thus, the task of recognizing malicious accounts in social networks and combating them remains relevant in the issue of cyber security. The solution to the problem will be the development of network analysis methods that are designed to identify and classify communities in social networks, assess their connectivity, degree of trust, as well as develop effective algorithms for detecting malicious accounts. The purpose of the work is to develop an improved algorithm for detecting malicious accounts in social networks, which is based on the study of modern methods.
subject: All articles from the issue
  topic: section
subject: social bots
  topic: keywords
subject: detection
  topic: keywords
subject: malicious accounts
  topic: keywords
subject: social networks
  topic: keywords
subject: cluster analysis
  topic: keywords
creator: Yevheniy Nikitenko
creator: Yevhen Ryndych
creator: Ivan Hoida
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 38
ending page: 43

IMAGE RECOGNITION SYSTEM BASED ON A NEURAL NETWORK WITH DEEP LEARNING
type: item
description: An object recognition system based on deep learning neural networks has been developed. Such an image recognition system is capable of accurately and quickly recognizing images known to it and similar to them in video content obtained from IP surveillance cameras. Depending on the video shooting conditions and the viewing angle of the IP camera, the algorithm of this system achieves a recognition accuracy of 96.38%. This image recognition rate is practically constant for 11 classes of identification and recognition objects. Such high results are achieved through the use of the CamVid video database as a training sample for the neural network. This database is based on 421 training and 280 test video images. The recognition system model provides for the optimization of training and identification function parameters, as well as changes in the method of measuring the distance between feature vectors (point distance measurement metrics).
subject: All articles from the issue
  topic: section
subject: neural network
  topic: keywords
subject: deep learning network
  topic: keywords
subject: feature classifier
  topic: keywords
subject: support vector
  topic: keywords
subject: graphic frame
  topic: keywords
subject: machine vision
  topic: keywords
creator: Andii Sahun
creator: Olena Panasko
rights: Copyright (c) 2024 Інформаційні технології в економіці та природокористуванні https://creativecommons.org/licenses/by-sa/4.0
date: 2024-11-08
publication date: 2024-11-08
starting page: 31
ending page: 37

Безперервне управління фінансовими ресурсами комерційного банку
type: item
description: Запропонована економіко-математична модель безперервного управління фінансовими ресурсами комерційного банку. Побудовані множини переваги для банку і для його загального контрагента, що характеризують такий початковий стан (обсяг) ресурсів сторін, за якого сторони або можуть взаємодіяти як завгодно довго, тобто зберігатимуть власний фінансовий ресурс, або, навпаки, можуть його втратити. Знайдені оптимальні стратегії сторін.
subject: Mathematics and economic cybernetics
  topic: section
creator: Інна Малюкова
creator: Володимир Малюков
rights: Copyright (c) 2020 Інформаційні технології в економіці та природокористуванні
date: 2020-04-15
publication date: 2020-04-15
starting page: 26
ending page: 34

Фінансові інструменти екологічної економіки
type: item
description: Досліджені структурні зміни світової економіки у зв’язку зі зміною парадигми сталого розвитку. Висвітлені ключові аспекти ринкового розв’язання проблеми зміни клімату. Доведено, що похідні фінансові інструменти грають ключову роль у скороченні викидів парникових газів у відповідності до трансформації післякризового міжнародного законодавства щодо регулювання фінансових ринків. Запропоновані пропозиції щодо централізованого клірингу фінансових інструментів у відповідності до трансформації міжнародного законодавства у фінансовій сфері.
subject: Economics and economic cybernetics
  topic: section
creator: Сергій Олексійович Силантьєв
rights: Copyright (c) 2020 Інформаційні технології в економіці та природокористуванні
date: 2020-04-15
publication date: 2020-04-15
starting page: 35
ending page: 41

Деякі питання тестування та обробки формальних текстів за допомогою системи SAD
type: item
description: Використовуючи систему автоматизації дедукції SAD, орієнтовану на верифікацію текстів, поданих формальною природною мовою, вивчаються питання розробки та використання комп’ютерних засобів інтелектуального тестування формалізуємих текстів, що відмінне від звичайного "питально-відповідного" способу тестування та засноване на декларативному способі подання інформації. Дається стисла характеристика лінгвістичних і логічних особливостей системи SAD, що свідчить про можливість її використання для дедуктивного тестування знань навчаємого. На конкретному прикладі демонструється застосування системи SAD для виконання верифікації замкненого математичного тексту, що свідчить про можливість використання системи для вирішення задач дедуктивного тестування. Обговорюються виникаючі задачі та пропонуються методи їх вирішення. Описуються можливі напрямки подальшого розвитку системи SAD, пов’язаних з усилянням її мовних можливостей, збагаченням інтерфейсних засобів та побудовою нових модулів її логічного апарату.
subject: Decision-making methods and management systems
  topic: section
creator: Олександр Вадимович Лялецький
rights: Copyright (c) 2020 Інформаційні технології в економіці та природокористуванні
date: 2020-04-15
publication date: 2020-04-15
starting page: 59
ending page: 65

Криптографічна система з підтримкою базових алгоритмів зміни вхідних даних
type: item
description: Анотація: Стаття присвячена розгляду існуючих моделей безпеки даних. Запропонований алгоритм дозволяє реалізувати модель шифрування з підтримкою базових алгоритмів зміни вхідних даних. На основі алгоритму шифрування інформації без заданої фіксації довжини, необхідно отримати вхідний ключ шифрування, який визначає характер даних. Також реалізована можливість отримати розмір даних, який перетворюється довільним чином після визначення розміру наступного блоку шифрування. Отримані дані, що визначають розмір блоку шифрування, так само шифруються. Це має дозволити швидко зашифровувати великий об'єм (розмір) даних без необхідності розбивати рядки на блоки. Ключові слова: криптосистема, модель, алгоритм, шифровка, розшифровка, ключ, блок шифрування, ідентифікатор, сигнатура, шифр заміни, шифр підстановки, взаємодоповнюючі сигнатури.
subject: Information protection and cybersecurity
  topic: section
creator: Катерина Володимирівна Лісіцина
rights: Copyright (c) 2020 Інформаційні технології в економіці та природокористуванні
date: 2020-04-15
publication date: 2020-04-15
starting page: 50
ending page: 58