Вісники та науково-технічні збірники, журнали

Permanent URI for this communityhttps://ena.lpnu.ua/handle/ntb/12

Browse

Search Results

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    Investigation of serverless architecture
    (Lviv Politechnic Publishing House, 2021) Lakhai, Vladyslav; Bachynskyy, Ruslan; Lviv Polytechnic National University
    Serverless computing is a new and still evolving type of cloud computing, which brings a new approach to the development of information systems. The main idea of serverless is to give an approach of doing computing without dealing with a server to a user. Such approach allows to reduce the cost of the system building and system support. It allows small companies to concentrate on their own system designing instead of thinking about infrastructure building and supporting. Also, a big problem of providing the system security on high level is on cloud’s provider engineering support service. Serverless approach allows to start business quickly without huge initial investment. There is an attempt to completely analyze features, benefits and drawbacks of serverless approach, its use cases and main patterns of Serverless architecture. What is more, different providers have been analyzed.
  • Thumbnail Image
    Item
    Methods of vehicle recognition and detecting traffic rules violations on motion picture based on opencv framework
    (Lviv Politechnic Publishing House, 2021) Fastiuk, Yevhen; Bachynskyy, Ruslan; Huzynets, Nataliia; Lviv Polytechnic National University
    In this era, people using vehicles is getting increased day by day. As pedestrians leading a dog for a walk, or hurrying to their workplace in the morning, we’ve all experienced unsafe, fast-moving vehicles operated by inattentive drivers that nearly mow us down. Many of us live in apartment complexes or housing neighborhoods where ignorant drivers disregard safety and zoom by, going way too fast. To plan, monitor and also control these vehicles is becoming a big challenge. In the article, we have come up with a solution to the above problem using the video surveillance considering the video data from the traffic cameras. Using computer vision and deep learning technology we will be able to recognize violations of rules. This article will describe modern CV and DL methods to recognize vehicle on the road and traffic violations of rules by them. Implementation of methods can be done using OpenCV Python as a tool. Our proposed solution can recognize vehicles, track their speed and help in counting the objects precisely.
  • Thumbnail Image
    Item
    A software service for the garbage type recognition based on the mobile computing devices with graphical data input
    (Lviv Politechnic Publishing House, 2020) Bachynskyy, Ruslan; Chaku, Oleksii; Huzynets, Nataliia; Lviv Polytechnic National University
    The article describes problems of determining the type and automatic sorting of household waste using mobile computing devices. All of the required hardware and partially software, required for implementation of this service, are already present in modern smartphones. iOS and Apple products were selected as the base for the service, due to such advantages over competitors: dual or triple depth camera (TDCS), powerful GPU, Neural Engine coprocessor, high autonomy (2750 mAh battery size), sensors that allow for user positioning and navigation in space (GPS, Glonass, Gyroscope) and most important feature is possibility of cross-platform designing, suitable for iOS and macOS (Project Catalina). The recognition process consists of several phases, including capturing of graphic image and detecting the object shape, shape analysis, computing the results, and saving new associations to the database. The analysis itself is implemented using a neural network that is able to learn during its operation. Initially, the algorithm is driven by the selection of photographs with a certain type for the base set of associations, each subsequent scan improves accuracy. Cross-platforming plays a very important role - it allows us to develop a single software service that is initially run on a macOS-based computer for faster learning and then can be easily used on an iOS mobile device. After identifying a particular type of garbage, the route to the nearest recycling point of such type of garbage will be proposed for user or user’s clarification will be requested. User can also manually browse categories and related items, manually search by name of item, and view locations for sorting and recycling in appropriate city. When a completely unknown object arrives, it is possible to refine the information in order to help further learning of the network.
  • Thumbnail Image
    Item
    Геоконтекстний інтернет-сервіс пошуку та збору оперативних новин з використанням нейронної мережі
    (Видавництво Львівської політехніки, 2018-02-26) Бачинський, Р. В.; Шеренговський, О. В.; Bachynskyy, Ruslan; Scherengovskyy, Oleg; Національний університет “Львівська політехніка”; Lviv Polytechnic National University
    Розглянуто методи збору та пошуку оперативних новин. Описано інтернет-сервіс збору та пошуку оперативних новин, наведено його структурну схему та алгоритми роботи. Забезпечено розширення функціональності сервісу врахуванням місцезнаходження та вподобань користувача у ході роботи сервісу, більшу швидкодію та передавання інформації за допомогою захищеного протоколу SSL. Реалізовано механізм навчання нейронної мережі, що застосовується сервісом.
  • Thumbnail Image
    Item
    Система криптографічного захисту bluetooth зв’язку між пристроєм інтернету речей та мобільним обчислювальним пристроєм
    (Видавництво Львівської політехніки, 2018-02-26) Бачинський, Р. В.; Купецький, А. В.; Bachynskyy, Ruslan; Kupetskyy, Andriy; Національний університет “Львівська політехніка”; Lviv Polytechnic National University
    Розглянуто захист каналу зв’язку між пристроями інтернету речей та пристроїв на базі ОС iOS. Проаналізовано способи шифрування каналу та розподіл спільних ключів у незахищеному середовищі. Описано та розроблено систему для захисту такого каналу.