A Review of the Benefits of Automation and Robotic Application in Building Construction
Conference Proceeding
Ejidike, C. C., Mewomo, M. C., Olawumi, T. O., & Esangbedo, O. P. (2024)
A Review of the Benefits of Automation and Robotic Application in Building Construction. In Y. Turkan, J. Louis, F. Leite, & S. Ergan (Eds.), Computing in Civil Engineering 2023: Data, Sensing, and Analytics (796-803). https://doi.org/10.1061/9780784485224.096
Globally, building construction is complex and advanced in performance. The improvement of the economy and social benefits of building delivery depends critically on applying ...
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...
A Probabilistic Design Reuse Index for Engineering Designs
Journal Article
Vasantha, G., Corney, J., Stuart, S., Sherlock, A., Quigley, J., & Purves, D. (2020)
A Probabilistic Design Reuse Index for Engineering Designs. Journal of Mechanical Design, 142(10), https://doi.org/10.1115/1.4046435
Many companies offer a range of related products that are constructed using similar components and processes. This enables them to meet customer expectations of product variet...
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,...
Curvilinear MetaSurfaces for Surface Wave Manipulation.
Journal Article
La Spada, L., Spooner, C., Haq, S., & Hao, Y. (2019)
Curvilinear MetaSurfaces for Surface Wave Manipulation. Scientific Reports, 9(1), https://doi.org/10.1038/s41598-018-36451-8
Artificial sheet materials, known as MetaSurfaces, have been applied to fully control both space and surface waves due to their exceptional abilities to dynamically tailor wav...
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 ...