Innovations in data science and predictive analytics
Researchers are exploring Inverse Reinforcement Learning, Hierarchical Decision-Making Abstractions and other machine learning techniques to demonstrate how to dynamically detect, classify, understand and mitigate against unknown cyber threats.
The researchers investigated internet architectures that focus on data centric networking.
This exploratory project investigated the risk, issues and demands of interfacing theoretical energy management control algorithms with complex future aircraft architectures.
Through simulation and analysis, the researchers concluded that HAPS technology is capable of delivering broadband communications services – between 2Mbs and 30Mbs – to low-density and hard-to-reach areas.
Researchers are developing an accessible web-based tool to help engineers produce faster and more accurate simulations of high-quality meshing solutions.
This early stage research project demonstrated the benefits of using biometrics to verify – in real-time – the unique identity of each individual user.
Researchers have developed a proof-of-concept tool that uses graphical data to help diverse teams identify cyber and safety risks to critical SCADA infrastructure.
Researchers are creating enhanced intrusion detection systems to protect the SCADA systems – that underpin Critical National Infrastructure – from cyber threats.
Heart Rate Variability was analysed to indicate individual stress levels, with the results captured and displayed in real-time.
Airbus works with researchers at Swansea University to investigate the performance and stability of perovskite solar cells in a simulated stratospheric environment.
Research is underway to understand how adaptive smart antennas can be used in space to replace conventional patch antennas.