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Документ Method of selection of software design technology(Khmelnytskyi National University, 2021) Medzatyi, D.; Hovorushchenko, T.; Медзатий, Д.; Говорущенко, Т.The paper further develops the mathematical model of the software design technology (SDT) and the criteria for evaluating the SDT, which allow experts to evaluate each considered software design technology more accurately, taking into account all its components. The method and production rules of the selection of the software design technology proposed by the authors give the organization the opportunity to make a motivated and reasonable choice of the design technology for its further implementation.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 Using artificial intelligence accelerators to train computer game characters(Khmelnytskyi National University, 2021) Hnatchuk, Y.; Sierhieiev, Y.; Hnatchuk, A.; Гнатчук, Є.; Сєргєєв, Є.; Гнатчук, А.A review of the literature has shown that today, given the complexity of computational processes and the high cost of these processes, the gaming computer industry needs to improve hardware and software to increase the efficiency and speed of processing artificial intelligence algorithms. An analysis of existing machine learning tools and existing hardware solutions to accelerate artificial intelligence. A reasonable choice of hardware solutions that are most effective for the implementation of the task. Possibilities of practical use of the artificial intelligence accelerator are investigated. The effectiveness of the proposed solutions has been proven by experiments. The use of an artificial intelligence accelerator model allowed to accelerate the learning of a computer game character by 2.14 times compared to classical methods.Документ Method of choosing the programming environment for software(Khmelnytskyi National University, 2021) Stetsyuk, V.; Hovorushchenko, T.; Стецюк, В.; Говорущенко, Т.This paper shows an example of the application of the method of hierarchy analysis to build a hierarchy of programming environments, which provides support for selecting the optimal programming environment for software in accordance with the requirements of the developer and user. As a result of the application of the method of hierarchy analysis, a hierarchy of programming environments for software development was built, which will be useful for building criteria and production rules for selecting a programming environment for software. The constructed hierarchy has the following form: 1) Microsoft Visual Studio (33.1%); 2) Eclipse (19.6%); 3) PhpStorm (19.2%); 4) Netbeans (17.2%); 5) PyCharm (11%). Hierarchy analysis makes it possible to determine what is the best for software development is the Microsoft Visual Studio environment, but the price of such an environment is quite high. Next and almost equal in technical capabilities are the environments Eclipse, PhpStorm, Netbeans, PyCharm.Документ Method of estimating the laboriousness of the process of developing computer systems’ software(Хмельницький національний університет, 2021) Lopatto, I.; Lebiga, M.; Hovorushchenko, T.; Лопатто, І.; Лебіга, М.; Говорущенко, Т.The paper proposes a method for estimating the laboriousness of software development based on functional points, which allows to determine the number of functional points for a software project, and also allows in the early stages of the life cycle to estimate the size of a software project (for example, LOC-assessment). The developed method eliminates the dependence of evaluation on the subjects involved in the evaluation process.Документ Methods for cyberattacks detection in the computer networks as a mean of resilient IT-infrastructure construction: state-of-art(Хмельницький національний університет, 2021) Lysenko, S.; Sokalskyi, D.; Mykhasko, I.; Лисенко, С.; Сокальський, Д.; Михасько, Я.The paper presents a state-of-art of the methods for cyberattacks detection in the computer networks. The main accent was made on the concept of the resilience for the IT infrastructure. The concept of cyber resilience in the terms of cybersecurity was presented. The survey includes the set of approaches devoted to the problem of construction resilient infrastructures. All investigated approaches are aimed to construct and maintain infrastructure’s resilience for cyberattacks resistance. Mentioned techniques and frameworks keep the main principles to assure resilience. To do this there exists some requirements to construct such infrastructure: IT infrastructure has to include the set ready to use measures of preparation concerning the possible cyber threats; it must include the set of special measures for the protection, as well as for cyberattacks detection; important issue and required is the possibility to respond the attack and to be able to absorb the negative attacks’ impact; IT infrastructure must be as adaptive as it is possible, because today the dynamic of the attacks mutation is very high; IT infrastructure must be recoverable after the attacks were performed. In addition, the state-of-art found out that known approaches have domain-specific usage and it is important to develop new approaches and frameworks for the cyberattacks detection in the computer networks as a means of resilient IT-infrastructure construction.Документ Research of machine learning based methods for cyberattacks detection in the internet of things infrastructure(Хмельницький національний університет, 2021) Bobrovnikova, K.; Kapustian, M.; Denysiuk, D.; Бобровнікова, К.; Капустян, М.; Денисюк, Д.The growing demand for IoT devices is accelerating the pace of their production. In an effort to accelerate the launch of a new device and reduce its cost, manufacturers often neglect to comply with cybersecurity requirements for these devices. The lack of security updates and transparency regarding the security status of IoT devices, as well as unsafe deployment on the Internet, makes IoT devices the target of cybercrime attacks. Quarterly reports from cybersecurity companies show a low level of security of the Internet of Things infrastructure. Considering the widespread use of IoT devices not only in the private sector but also in objects for various purposes, including critical infrastructure objects, the security of these devices and the IoT infrastructure becomes more important. Nowadays, there are many different methods of detecting cyberattacks on the Internet of Things infrastructure. Advantages of applying the machine-based methods in comparison with signature analysis are the higher detection accuracy and fewer false positive, the possibility of detecting both anomalies and new features of attacks. However, these methods also have certain disadvantages. Among them there is the need for additional hardware resources and lower data processing speeds. The paper presents an overview of modern methods aimed at detecting cyberattacks and anomalies in the Internet of Things using machine learning methods. The main disadvantages of the known methods are the inability to detect and adaptively respond to zero-day attacks and multi-vector attacks. The latter shortcoming is the most critical, as evidenced by the constantly increasing number of cyber attacks on the Internet of Things infrastructure. A common limitation for most known approaches is the need for significant computing resources and the significant response time of cyberattack detection systemsДокумент Smart home system security risk assessment(Хмельницький національний університет, 2021) Morozova, O.; Tetskyi, A.; Nicheporuk, A.; Kruvak, D.; Tkachov, V; Морозова, О.; Тецький, А.; Нічепорук, А.; Кривак, Д.; Ткачов, В.The concept of the Internet of Things became the basis of the fourth industrial revolution, which allowed to transfer the processes of automation to a new saber. As a result, automation systems, such as smart homes, healthcare systems and car control systems, have become widespread. The developers of such systems primarily focus their efforts on the functional component, leaving safety issues in the background. However, when designing and operating IoT systems, it is equally important to assess potential bottlenecks and develop complete and comprehensive strategies to mitigate and eliminate the negative effects of cyberattacks. The purpose of this study is to identify possible cyber threats and assess their impact on critical information objects in the smart home system. To achieve this goal, the three-level architecture of the smart home system is considered and a review of known cyber threats for each level is conducted. The critical information objects in the smart home system are the containers in which the information objects are stored, the risk assessment criteria and the cyber threat scenarios. The information security risks of the smart home system were assessed using the OCTAVE Allegro methodology for the information object that presents the information collected by the smart home sensorsДокумент Web-based information technology for classifying and interpreting early pneumonia based on fine-tuned convolutional neural network(Khmelnytskyi National University, 2021-05-31) Radiuk, Pavlo; Barmak, Olexander; Радюк, Павло; Бармак, ОлександрThere have been rapid development and application of computer methods and information systems in digital medical diagnosis in recent years. However, although computer methods of medical imaging have proven helpful in diagnosing lung disease, for detecting early pneumonia on chest X-rays, the problem of cooperation between professional radiologists and specialists in computer science remains urgent. Thus, to address this issue, we propose information technology that medical professionals can employ to detect pneumonia on chest X-rays and interpret the results of the digital diagnosis. The technology is presented as a web-oriented system with an available and intuitive user interface. The information system contains three primary components: a module for disease prediction based on a classification model, a module responsible for hyperparameter tuning of the model, and a module for interpreting the diagnosis results. In combination, these three modules form a feasible tool to facilitate medical research in radiology. Moreover, a web-based system with a local server allows storing personal patient data on the user's computing device, as all calculations are performed locally.