A Review on Deep Learning Approaches to Image Classification and Object Segmentation
Journal Article
Wu, H., Liu, Q., & Liu, X. (2019)
A Review on Deep Learning Approaches to Image Classification and Object Segmentation. Computers, Materials & Continua, 60(2), 575-597. https://doi.org/10.32604/cmc.2019.03595
Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Pr...
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...
Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing
Journal Article
Liu, Q., Wang, Z., Liu, X., & Linge, N. (2019)
Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing. International Journal of High Performance Computing and Networking, 14(4), 435-443. https://doi.org/10.1504/IJHPCN.2019.102350
In the wake of the development in science and technology, Cloud Computing has obtained more attention in different field. Meanwhile, outlier detection for data mining in Cloud...
Reviving legacy enterprise systems with microservice-based architecture within cloud environments
Conference Proceeding
Habibullah, S., Liu, X., Tan, Z., Zhang, Y., & Liu, Q. (2019)
Reviving legacy enterprise systems with microservice-based architecture within cloud environments. In Computer Science Conference Proceedingshttps://doi.org/10.5121/csit.2019.90713
Evolution has always been a challenge for enterprise computing systems. The microservice based architecture is a new design model which is rapidly becoming one of the most eff...
A Self-Organizing Memory Neural Network for Aerosol Concentration Prediction
Journal Article
Liu, Q., Zou, Y., & Liu, X. (2019)
A Self-Organizing Memory Neural Network for Aerosol Concentration Prediction. Computer Modeling in Engineering and Sciences, 119(3), 617-637. https://doi.org/10.32604/cmes.2019.06272
Haze-fog, which is an atmospheric aerosol caused by natural or man-made factors, seriously affects the physical and mental health of human beings. PM2.5 (a particulate matter ...
Non-intrusive load monitoring and its challenges in a NILM system framework
Journal Article
Liu, Q., Lu, M., Liu, X., & Linge, N. (2019)
Non-intrusive load monitoring and its challenges in a NILM system framework. International Journal of High Performance Computing and Networking, 14(1), 102-111. https://doi.org/10.1504/IJHPCN.2019.099748
With the increasing of energy demand and electricity price, researchers gain more and more interest among the residential load monitoring. In order to feed back the individual...
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 ...
Low-Complexity Non-Intrusive Load Monitoring Using Unsupervised Learning and Generalized Appliance Models
Journal Article
Liu, Q., Kamoto, K. M., Liu, X., Sun, M., & Linge, N. (2019)
Low-Complexity Non-Intrusive Load Monitoring Using Unsupervised Learning and Generalized Appliance Models. IEEE Transactions on Consumer Electronics, 65(1), 1-1. doi:10.1109/tce.2019.2891160
Awareness of electric energy usage has both societal and economic benefits, which include reduced energy bills and stress on non-renewable energy sources. In recent years, the...