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...
Power Consuming Activity Recognition in Home Environment
Conference Proceeding
Liu, X., & Liu, Q. (2017)
Power Consuming Activity Recognition in Home Environment. In X. Sun, H. Chao, X. You, & E. Bertino (Eds.), Cloud Computing and Security. ICCCS 2017, (361-372). https://doi.org/10.1007/978-3-319-68505-2_31
This work proposed an activity recognition model which focus on the power con-suming activity in home environment, to help residents modify their behavior. We set the IoT syst...
Evolution pattern for service evolution in clouds.
Conference Proceeding
Wang, Z., Liu, X. & Chalmers, K. (2011)
Evolution pattern for service evolution in clouds. In The 7th International Conference for Internet Technology and Secured Transactions (ICITST-2012)ISBN 978-1-908320-08-7
The proposed research will focus on
developing a novel approach to solve Software Service
Evolution problems in Computing Clouds. The
approach will support dynamic evolution o...
Improvements in or relating to component-based development
Patent
Liu, X., Wang, B. & Combe, C. (2008)
Improvements in or relating to component-based development
A patent on Context-oriented Generative Component Adaptation, has been registered in the UK, USA and at International Level (PCT), sponsored by a Proof of Concept grant:
Liu...
Achieve semantic-based precise component selection via an ontology model interlinking application domain and MVICS.
Conference Proceeding
Li, C., Liu, X., & Kennedy, J. (2010)
Achieve semantic-based precise component selection via an ontology model interlinking application domain and MVICS. In Proceedings of the 22nd International Conference on Software Engineering and Knowledge Engineering (SEKE'10)