Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing
Journal Article
Buchanan, W. J., Imran, M. A., Ur-Rehman, M., Zhang, L., Abbasi, Q. H., Chrysoulas, C., …Papadopoulos, P. (2020)
Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing. Frontiers in Communications and Networks, https://doi.org/10.3389/frcmn.2020.583376
The outbreak of viruses have necessitated contact tracing and infection tracking methods. Despite various efforts, there is currently no standard scheme for the tracing and tr...
BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond
Journal Article
Xu, H., Zhang, L., Onireti, O., Fang, Y., Buchanan, W. J., & Imran, M. A. (2021)
BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond. IEEE Internet of Things, 8(5), 3915-3929. https://doi.org/10.1109/jiot.2020.3025953
The outbreak of COVID-19 pandemic has exposed an urgent need for effective contact tracing solutions through mobile phone applications to prevent the infection from spreading ...
Use Of Participatory Apps In Contact Tracing: Options And Implications for Public Health, Privacy and Trust
Report
Buchanan, B., Imran, M., Pagliari, C., Pell, J., & Rimpiläinen, S. (2020)
Use Of Participatory Apps In Contact Tracing: Options And Implications for Public Health, Privacy and Trust. Glasgow: Digital Health and Care Institute, University of Strathclyde
On December 31st, 2019, the World Health Organisation received a report from the Chinese government detailing a cluster of cases of ‘pneumonia of unknown origin’, later identi...
Machine Learning for Health and Social Care Demographics in Scotland
Presentation / Conference
Buchanan, W. J., Smales, A., Lawson, A., & Chute, C. (2019, November)
Machine Learning for Health and Social Care Demographics in Scotland. Paper presented at HEALTHINFO 2019, Valencia, Spain
This paper outlines an extensive study of applying machine learning to the analysis of publicly available health and social care data within Scotland, with a focus on learning...
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...
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 ...
Interference graphs to monitor and control schedules in low-power WPAN
Journal Article
van der Lee, T., Liotta, A., & Exarchakos, G. (2019)
Interference graphs to monitor and control schedules in low-power WPAN. Future Generation Computer Systems, 93, 111-120. https://doi.org/10.1016/j.future.2018.10.014
Highlights
• This study presents the complete and slotted interference graph model.
• The service uses the complete interference graph to evaluate the network.
• Slotted int...
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
Journal Article
Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, P. H., Gibescu, M., & Liotta, A. (2018)
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science. Nature Communications, 9(1), 1-12. https://doi.org/10.1038/s41467-018-04316-3
Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from ...