Visual Encodings for Networks with Multiple Edge Types
Conference Proceeding
Vogogias, T., Archambault, D. W., Bach, B., & Kennedy, J. (2020)
Visual Encodings for Networks with Multiple Edge Types. In AVI '20: Proceedings of the International Conference on Advanced Visual Interfaces. https://doi.org/10.1145/3399715.3399827
This paper reports on a formal user study on visual encodings of networks with multiple edge types in adjacency matrices. Our tasks and conditions were inspired by real proble...
A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings
Journal Article
Liu, Q., Nakoty, F. M., Wu, X., Anaadumba, R., Liu, X., Zhang, Y., & Qi, L. (2020)
A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings. Computer Communications, 162, 187-195. https://doi.org/10.1016/j.comcom.2020.08.024
Compared to Intrusive Load Monitoring which uses smart power meters at each level to be monitored, Non-Intrusive Load Monitoring (NILM) is an ingenious way that relies on sign...
PM2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism
Journal Article
Chen, J., Chen, K., Wang, G., Wu, L., Liu, X., & Wei, G. (2019)
PM2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism. International Journal of Environmental Research and Public Health, 16(7), 1-21. https://doi.org/10.3390/ijerph16071159
In this paper, a vector autoregression (VAR) model has been constructed in order to analyze a two-way mechanism between PM2.5 pollution and industry development in Beijing via...
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 ...
Athos - A Model Driven Approach to Describe and Solve Optimisation Problems
Conference Proceeding
Hoffman, B., Chalmers, K., Urquhart, N., & Guckert, M. (2019)
Athos - A Model Driven Approach to Describe and Solve Optimisation Problems. https://doi.org/10.1145/3300111.3300114
Implementing solutions for optimisation problems with general purpose high-level programming languages is a time consuming task that can only be carried out by professional so...
Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks
Journal Article
Liu, Q., Zhang, J., Liu, X., Zhang, Y., Xu, X., Khosravi, M., & Bilal, M. (2022)
Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks. Physical Communication, 51, Article 101584. https://doi.org/10.1016/j.phycom.2021.101584
The intensification of the greenhouse effect is driving the implementation of energy saving and emission reduction policies, which lead to a wide variety of energy saving solu...
Ontology-Driven Automated Generation of Data Entry Interfaces to Databases
Conference Proceeding
Cannon, A., Kennedy, J. B., Paterson, T., & Watson, M. F. (2004)
Ontology-Driven Automated Generation of Data Entry Interfaces to Databases. In H. Williams, & L. Mackinnon (Eds.), Key Technologies for Data Management; Lecture Notes in Computer Science, 150-164. doi:10.1007/978-3-540-27811-5_15
This paper discusses an ontology based approach for the automatic generation of data entry interfaces to databases. An existing domain ontology is mapped to a system domain mo...
Visual Exploration of Alternative Taxonomies through Concepts
Journal Article
Graham, M., & Kennedy, J. (2007)
Visual Exploration of Alternative Taxonomies through Concepts. Ecological Informatics, 2, 248-261. https://doi.org/10.1016/j.ecoinf.2007.07.004
A graphical user interface is presented that allows users of taxonomic data to explore concept relationships between conflicting but related taxonomic classifications.
Ecolog...
Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm
Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2016)
Understanding Environmental Influence in an Open-Ended Evolutionary Algorithm. In Parallel Problem Solving from Nature – PPSN XIV; Lecture Notes in Computer Science. , (921-931). https://doi.org/10.1007/978-3-319-45823-6_86
It is well known that in open-ended evolution, the nature of the environment plays in key role in directing evolution. However, in Evolutionary Robotics, it is often unclear e...
A survey on rainfall forecasting using artificial neural network
Journal Article
Liu, Q., Zou, Y., Liu, X., & Linge, N. (2019)
A survey on rainfall forecasting using artificial neural network. International Journal of Embedded Systems, 11(2), 240-249. https://doi.org/10.1504/ijes.2018.10016095
Rainfall has a great impact on agriculture and people’s daily travel, so accurate prediction of precipitation is well worth studying for researchers. Traditional methods like ...