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Документ Analysis of artificial intelligence based systems for automated generation of digital content(Хмельницький національний університет, 2024) Pavlova, O.; Kuzmin, A.This paper is aimed at the examination of contemporary challenges related to the integration of generative models API of artificial intelligence (AI) into a unified information system to facilitate the automated generation of digital content. In the context of rapid advancements in AI technologies and the increasing demand for diverse and personalized digital content, the integration of API-based generative models emerges as a crucial driver for progress in this field. The research findings underscore the significance of incorporating API-based generative AI models into a unified system, marking a significant step towards automating the process of digital content creation to meet modern market demands. By streamlining content generation workflows, such integration holds promise for enhancing efficiency and scalability while fostering creativity and innovation. Furthermore, the integration of generative AI models into a unified system presents opportunities for the development of personalized and innovative solutions tailored to the needs and preferences of end-users. This not only enhances user experiences but also enables the creation of content that resonates more effectively with target audiences across various domains. The findings gleaned from our research underscore the importance of integration of API-based generative AI models into a unified framework, representing a monumental stride toward the automation of digital content creation that caters to the exigencies of today's market dynamics. By streamlining content generation workflows and alleviating manual intervention, such integration holds immense promise in enhancing operational efficiency, scalability, and adaptability, while simultaneously nurturing a fertile ground for creativity and innovation to flourish. The further efforts of our research team are committed to the practical implementation of this concept and the exploration of its applicability across diverse domains. By continuing to refine and expand upon this integration, we aim to unlock new possibilities for automated content generation and drive further innovation in the digital content creation landscape.Документ Approaches of building a real-world object detector data source(Хмельницький національний університет, 2023) Pavlova, O.; Bashta, A.; Kuzmin, A.In our constantly developing world virtual, augmented, and mixed reality technologies are becoming integral parts of our daily lives. In the current stage of Information Technology field development, technologies of virtual, augmented and mixed reality can be seen in almost all areas of human life. Nowadays AR is used in Marketing and Advertising, Education, Medicine, Automotive, Game Development, Navigation and other areas of our everyday life. Therefore, object detection is a crucial task in computer vision and AI applications, enabling machines to identify and locate objects within images or video frames. The accuracy and performance of an object detector heavily rely on the quality and diversity of the training data. This paper is aimed at finding the approaches of building a real-world object detector data source to be able to create a model for detecting a sport games surfaces using the Action & Vision App. During this research several structured approaches of building an object detector data source have been built, drawing inspiration from Apple's Create ML documentation on the topic. Additionally, real-world applications available on both the App Store and Google Play that leverage object detection technology were showcased and analyzed. In the course of study a dataset of objects has been collected and then utilized to build a robust detection model, tailored to function seamlessly with Vision and Core ML frameworks on iOS devices. The trained object detection model, informed by the diverse dataset and robust training process, is employed to identify and outline tables and rectangles in each frame of the video stream. The model and the proposed approaches will be further applied to develop the method of object detection in the real world and create a mobile application for sport games simulation, that would help players to practice their skills out of the training field.Документ Automated system for determining speed of cars ahead(Хмельницький національний університет, 2023) Pavlova, O.; Bilinska, A.; Holovatiuk, A.; Binkovskyi, Y.; Melnychuk, D.Road accidents and speeding violations are pervasive issues that pose substantial threats to road users on a daily basis. In an ongoing effort to improve road safety and reduce the frequency of accidents, researchers and engineers have been dedicated to the development and implementation of new technologies. One such significant innovation is the utilization of speed control systems based on traffic cameras. This paper delves into a thorough exploration of the pivotal role and significance of speed control systems on our roadways. It investigates the operational principles, advantages, and various strategies employed to enhance the efficiency of these systems, with the ultimate goal of achieving optimal results in speed control and ensuring road safety. Speeding remains a widespread concern that significantly contributes to road accidents. Such incidents lead to injuries, fatalities, and extensive property damage, underscoring the urgent need for effective speed control measures. Among the arsenal of solutions available, speed control systems utilizing traffic cameras have emerged as a prominent and promising approach. These systems function by monitoring and recording the speed of vehicles at specific locations, which is later used to enforce speed limits and penalize offenders. The advantages of speed control systems based on traffic cameras are multifaceted. They offer an objective and reliable method for detecting and documenting speeding violations, eliminating the need for law enforcement personnel to be present at all times. This aspect not only frees up law enforcement resources but also ensures consistent and unbiased enforcement of speed limits. Additionally, the data collected by these systems can serve as a valuable resource for traffic management, accident analysis, and road safety researchДокумент Automated testing of web project functionality with using of error propagation analysis(Хмельницький національний університет, 2023) Zasornova, I.; Fedula, M.; Pavlova, O.; Kysil, T.Automated testing is indispensable in the area of software engineering, particularly for web project functionality, as the complexity of software systems continues to surge. This paper delves into the pivotal role of automated testing and how the integration of error propagation analysis, grounded in chaos theory, can elevate its efficacy. The objective is to elucidate the significance of this methodology and its application in bolstering the reliability and performance of web projects. Automated testing automates the execution of predefined test cases, offering efficiency gains, reduced human error, and swift defect detection in software development. Various testing approaches, including unit testing, integration testing, and regression testing, cater to distinct facets of software functionality, ensuring seamless operation of all components. Web project functionality is integral to the user experience, encompassing navigation menus, forms, and search features. Testing this functionality is imperative to unearth inconsistencies or errors that could compromise user satisfaction and task completion. This paper proposes a methodology for automated testing coupled with error propagation analysis, which involves scrutinizing how errors evolve through a system over time. Chaos theory, a branch of mathematics examining complex systems' behavior, is employed to understand how minor variations in initial conditions can precipitate substantial system behavior shifts. Traditional error propagation analysis hinges on linear, deterministic models, but real-world systems often exhibit nonlinear, chaotic characteristics, rendering such models inadequate. Chaos theory's non-linear dynamics model the intricate interactions between input variables and their effects on outputs, capturing the sensitivity of chaotic systems to initial conditions. This approach appreciates system complexity and intricate feedback loops, enhancing error analysis's robustness and accuracy. However, the application of chaos theory introduces complexity and computational demands, necessitating a balance between model intricacy and practicality. The proposed methodology unveil valuable insights into error propagation within web projects' functionality, pinpointing vulnerable components and areas ripe for improvement. The methodology's advantages include the ability to identify potential issues and vulnerabilities, ultimately enhancing web project reliability.Документ Decision-making support system regarding the optimizaion process of crop cultivation using remote sensing data(Хмельницький національний університет, 2024) Okrushko, D.; Pavlova, O.Документ Neural network based image recognition method for smart parking(Khmelnytskyi National University, 2021) Pavlova, O.; Kovalenko, V.; Hovorushchenko, T.; Avsiyevych, V.; Павлова, О.; Коваленко, В.; Говорущенко, Т.; Авсієвич, В.Currently, the issue of creating smart parking lots is extremely important due to the rapid growth of number of cars, especially in big cities. Thus the need for parking spaces and search facilities still remains an urgent problem. Assuming that every day the average motorist spends 20 minutes searching for such a place, this is about 120 hours a year, which could be spent on something more useful. Today, there are many projects of "smart" parking, but practical examples can be counted on the fingers, and information about the cost-effective aspect of their implementation is generally very limited. The paper provides analysis of the most common methods and tools for smart parking and proves the advantages of camera-based method. The research in general is aimed at image recognition for camera-based smart parking using convolutional neural network.Документ The concept of AI-based information systems for the analysis of learning foreign words(Хмельницький національний університет, 2024) Pavlova, O.; Kozyra, A.In the modern world, information systems based on artificial intelligence (AI) are increasingly used to automate learning and improve the educational process. One of the perspective areas of AI application is foreign language learning, particularly vocabulary acquisition. By integrating AI components, specifically those utilizing machine learning algorithms to analyze large volumes of data and provide automated recommendations to enhance the learning process, users gain constant access to selfassessment tools and automatic adjustment of cognitive workload.This paper examines the key role and significance of information systems for analyzing foreign language vocabulary acquisition with the help of AI. It investigates the working principles of such systems, their advantages, and various strategies used to enhance the efficiency of language learning, aiming for optimal results in acquiring new linguistic knowledge and improving learning outcomes. Learning new foreign terms is often a challenging task for many students, leading to a loss of motivation or slow progress, highlighting the urgent need for solutions that enhance material retention. Adapting to individual users, AI-based information systems have developed a range of services and platforms with global potential for language learning worldwide. These systems function by analyzing user behavior and success, based on specific indicators and metrics, whose numerical values are interpreted to identify patterns and correlations between user behavior and its impact on the system. The advantages of AI-based information systems for language learning are significant, offering an objective, reliable method for assessing learning achievements, eliminating the need for human intervention in many cases. Data collected by these systems serve as a valuable resource for analyzing user productivity, detecting common mistakes, creating effective study plans, and more. However, it's important to note that AI has not yet reached the level of understanding semantics or the cultural and historical nuances of certain words, complicating the implementation of more comprehensive functionality for evaluating and adjusting the learning process. This requires developers to prepare additional data through proprietary sources or gain useful input from user interactions with the system.Документ The concept of an information system for forecasting the temperature regime of the earth’s surface based on machine learning(Хмельницький національний університет, 2024) Pavlova, O.; Alekseiko, V.The paper presents the concept of an information system for forecasting the temperature regime of the Earth’s surface using machine learning. Forecasting is based on historical data for a specific area. In order to increase the accuracy of forecasting results, an analysis of the features of climate zones was carried out to identify patterns. A comparison of the dependence of the average earth’s surface monthly temperatures in countries depending on their location in climate zones was carried out. The analysis of sources and scientific publications confirmed the relevance of the chosen research topic. Historical aspects of forecasting changes in climatic indicators are considered. Modern methods and approaches to temperature forecasting, their advantages and disadvantages are analyzed. An overview of the subject area was conducted and the regularities of temperature changes according to climate features were determined. A comparison of temperature regimes for countries located in different climate zones was made. For clarity, graphs of temperature changes were plotted and average indicators were calculated for each climate zone. The results of the study confirm the need to adjust the temperature forecast for certain areas, taking into account their location in a specific climate zone. The revealed regularities in the temperature regime of the countries indicate the need for an individual approach to forecasting and the use of such machine learning methods that are best adapted to the dependencies observed in the climate zone. The architecture of the information system for forecasting future temperatures depending on the climatic features of the studied territories is proposed. A concept has been formed for further research to find more accurate and effective approaches to predicting climate parameters and achieving the goals of sustainable development.Документ Video repeater design concept for UAV control(Хмельницький національний університет, 2024) Pavlova, O.; Halytskyi, O.This study is aimed at the utilization of a video repeater for unmanned aerial vehicle (UAV) control, involving a comparative analysis of existing scientific literature, methodologies, and available solutions. Through comparative analysis, the method of using an external repeater emerged as the most promising, offering flexibility in selecting repeaters with superior performance and advanced capabilities. Notably, this approach allows for the utilization of a single repeater across multiple UAVs and facilitates convenient modification or upgrade of the repeater without necessitating alterations to the UAV itself. Following component selection, an experimental prototype was designed to facilitate empirical investigations. Additionally, a frequency transmission scheme was devised for quadcopter control employing the repeater. This research represents a significant advancement in the realm of UAV control systems, introducing a novel approach to video repeater integration that is poised to revolutionize operational efficiency and adaptability across diverse operational settings. This approach offers unparalleled flexibility in the selection of repeaters boasting superior performance and advanced capabilities. The insights gleaned from this study are poised to catalyze further advancements in UAV technology, particularly in the realm of optimizing video transmission for enhanced situational awareness and mission effectiveness. By shedding light on the efficacy of video repeater integration, this study lays the groundwork for future innovations aimed at pushing the boundaries of UAV capabilities and enhancing their utility across a myriad of applications. The findings from this study are anticipated to inform further developments in UAV technology, particularly in optimizing video transmission for improved situational awareness and mission effectivenessДокумент Метод діяльності та структура інтелектуального агента на основі онтологічного підходу для оцінювання початкових етапів життєвого циклу програмного забезпечення(Хмельницький національний університет, 2020) Павлова, О.О.; Лопатто, І.Ю.; Говорущенко, Т.О.; Pavlova, O.; Lopatto, I.; Hovorushchenko, T.Метою даного дослідження є автоматизація аналізу специфікацій вимог до програмного забезпечення (ПЗ) на предмет достатності інформації та підвищення рівня достатності інформації щодо характеристик якості ПЗ у специфікаціях вимог шляхом розроблення інтелектуального агента на основі онтологічного підходу для оцінювання початкових етапів життєвого циклу програмного забезпечення.