"Degree Programme in Information Technology, MSc (Tech)" - Selaus Tutkinto-ohjelman ja opintosuunnan mukaanOpinnäytteet - ylempi korkeakoulututkinto

Viitteet 21-27 / 27

    • Predicting Materials’ Bulk Modulus with Machine Learning 

      Hailu, Nahom Aymere (2020)
      Diplomityö
      In material science, experiments and high-throughput models often consume a large amount of calendar time and computation resources, respectively. It is, therefore, essential to consider novel methods to accelerate the ...

    • Privacy analysis of voice user interfaces 

      Yeasmin, Farida (2020)
      Diplomityö
      A voice user interface (VUI) allows a user to interact with an application or system through voice or speech commands. A voice assistant device (VAD) primarily uses VUI to communicate with the user. The popularity of VADs ...

    • Robot joint type recognition using machine learning 

      Darvishmohammadi, Bahareh (2020)
      Diplomityö
      Reconfigurable robots and mountable measurement systems face attraction due to significant changes in development of wireless networks and internet of things. This research benefits cross disciplinary viewpoints to build ...

    • Secure Lifecycle Management of BLE Nodes 

      Rahman, Md Shohidur (2020)
      Diplomityö
      Aiming the novel applications in the healthcare, fitness, beacons, security, and home entertainment industries Bluetooth Special Interest Group (Bluetooth SIG) has designed and marketed a low power personal area ...

    • Time- and frequency-asynchronous aloha for ultra narrowband communications 

      Rahman, Md Ashiqur (2020)
      Diplomityö
      A low-power wide-area network (LPWAN) is a family of wireless access technologies which consume low power and cover wide areas. They are designed to operate in both licensed and unlicensed frequency bands. Among different ...

    • Tradeoff Between Latency and Throughput in 5G Networks with Hybrid-ARQ Retransmissions 

      Gillani, Syed Hassan Uz Zaman (2020)
      Pro gradu -tutkielma
      Ultra-reliable Low Latency Communications (URLLC) is one of the key enabling technology in Fifth Generation New Radio (5G-NR), which promises to provide reliability and ultra-low latency communication link for different ...

    • Unsupervised Domain Adaptation for Audio Classification 

      Gharib, Shayan (2020)
      Pro gradu -tutkielma
      Machine learning algorithms have achieved the state-of-the-art results by utilizing deep neural networks (DNNs) across different tasks in recent years. However, the performance of DNNs suffers from mismatched conditions ...