Virtual Rehabilitation: XR Design for Senior Users in Immersive Exergame Environments
Conference Proceeding
Charisis, V., Khan, S., AlTarteer, S., & Lagoo, R. (in press)
Virtual Rehabilitation: XR Design for Senior Users in Immersive Exergame Environments.
The global ageing population presents significant challenges, with healthcare systems strained to meet the needs of an increasingly elderly demographic. Societies face issues ...
Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems
Journal Article
Zhao, H., Yu, H., & Peng, L. (2024)
Event-Triggered Distributed Data-Driven Iterative Learning Bipartite Formation Control for Unknown Nonlinear Multiagent Systems. IEEE Transactions on Neural Networks and Learning Systems, 35(1), 417-427. https://doi.org/10.1109/tnnls.2022.3174885
In this study, we investigate the event-triggering time-varying trajectory bipartite formation tracking problem for a class of unknown nonaffine nonlinear discrete-time multia...
Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems
Journal Article
Zhao, H., Shan, J., Peng, L., & Yu, H. (in press)
Learning-based Robust Bipartite Consensus Control for a Class of Multiagent Systems. IEEE Transactions on Industrial Electronics, https://doi.org/10.1109/tie.2022.3174275
This paper studies the robust bipartite consensus problems for heterogeneous nonlinear nonaffine discrete-time multi-agent systems (MASs) with fixed and switching topologies a...
Distributed Event-triggered Bipartite Consensus for Multi-agent Systems Against Injection Attacks
Journal Article
Zhao, H., Shan, J., Peng, L., & Yu, H. (in press)
Distributed Event-triggered Bipartite Consensus for Multi-agent Systems Against Injection Attacks. IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/tii.2022.3157595
This paper studies fully distributed data-driven problems for nonlinear discrete-time multi-agent systems (MASs) with fixed and switching topologies preventing injection attac...
Diabetes research: at Edinburgh Napier University's School of Computing
Digital Artefact
Ryan, B., & Webster, G. (2020)
Diabetes research: at Edinburgh Napier University's School of Computing. [Blog]
This 'Diabetes Research' blog is initially about the seed-project 'Information Avoidance and diabetes'. This project is an initial investigation of how and why people with dia...
An AI approach to Collecting and Analyzing Human Interactions with Urban Environments
Journal Article
Ferrara, E., Fragale, L., Fortino, G., Song, W., Perra, C., di Mauro, M., & Liotta, A. (2019)
An AI approach to Collecting and Analyzing Human Interactions with Urban Environments. IEEE Access, 7, 141476-141486. https://doi.org/10.1109/access.2019.2943845
Thanks to advances in Internet of Things and crowd-sensing, it is possible to collect vast amounts of urban data, to better understand how citizens interact with cities and, i...
Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach
Journal Article
Di Mauro, M., & Liotta, A. (2019)
Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach. IEEE Transactions on Network and Service Management, 16(4), 1493-1506. https://doi.org/10.1109/tnsm.2019.2943776
The Next Generation 5G Networks can greatly benefit from the synergy between virtualization paradigms, such as the Network Function Virtualization (NFV), and service provision...
The Social Impact of Digital Youth Work: What Are We Looking For?
Journal Article
Pawluczuk, A., Webster, G., Smith, C., & Hall, H. (2019)
The Social Impact of Digital Youth Work: What Are We Looking For?. Media and Communication, 7(2), 59-68. https://doi.org/10.17645/mac.v7i2.1907
Digital youth work is an emerging field of research and practice which seeks to investigate and support youth-centred digital literacy initiatives. Whilst digital youth work p...
Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks
Journal Article
Savaglio, C., Pace, P., Aloi, G., Liotta, A., & Fortino, G. (2019)
Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks. IEEE Access, 7, 29355-29364. https://doi.org/10.1109/access.2019.2902371
High-density communications in wireless sensor networks (WSNs) demand for new approaches to meet stringent energy and spectrum requirements. We turn to reinforcement learning,...
Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities
Journal Article
Erhan, L., Ndubuaku, M., Ferrara, E., Richardson, M., Sheffield, D., Ferguson, F. J., …Liotta, A. (2019)
Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities. IEEE Access, 7, 19890-19906. https://doi.org/10.1109/access.2019.2897217
The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data ...