Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty (Extended Abstract)
Conference Proceeding
Sampath Kalutharage, C., Liu, X., & Chrysoulas, C. (2022)
Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty (Extended Abstract). In Attacks and Defenses for the Internet-of-Things: 5th International Workshop, ADIoT 2022. https://doi.org/10.1007/978-3-031-21311-3_8
Over the past few decades, Machine Learning (ML)-based intrusion detection systems (IDS) have become increasingly popular and continue to show remarkable performance in detect...
Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements and Challenges
Journal Article
Liu, Q., Yang, Z., Ji, R., Zhang, Y., Bilal, M., Liu, X., …Xu, X. (in press)
Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements and Challenges. IEEE Systems, Man, and Cybernetics Magazine,
Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation
Journal Article
Thomson, H., Yang, S., & Cochran, S. (2022)
Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation. Journal of Medical Ultrasonics, 49, 517-528. https://doi.org/10.1007/s10396-022-01230-6
Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered via radio-frequency ultrasound data. This paper describes how to implement the m...
A self-attention integrated spatiotemporal LSTM approach to edge-radar echo extrapolation in the Internet of Radars
Journal Article
Yang, Z., Wu, H., Liu, Q., Liu, X., Zhang, Y., & Cao, X. (in press)
A self-attention integrated spatiotemporal LSTM approach to edge-radar echo extrapolation in the Internet of Radars. ISA Transactions, https://doi.org/10.1016/j.isatra.2022.06.046
In recent years, the number of weather-related disasters significantly increases across the world. As a typical example, short-range extreme precipitation can cause severe flo...
CEMA-LSTM: Enhancing Contextual Feature Correlation for Radar Extrapolation Using Fine-Grained Echo Datasets
Journal Article
Yang, Z., Liu, Q., Wu, H., Liu, X., & Zhang, Y. (2023)
CEMA-LSTM: Enhancing Contextual Feature Correlation for Radar Extrapolation Using Fine-Grained Echo Datasets. Computer Modeling in Engineering and Sciences, 135(1), 45-64. https://doi.org/10.32604/cmes.2022.022045
Accurate precipitation nowcasting can provide great convenience to the public so they can conduct corresponding arrangements in advance to deal with the possible impact of upc...
Near-Data Prediction Based Speculative Optimization in a Distribution Environment
Journal Article
Liu, Q., Wu, X., Liu, X., Zhang, Y., & Hu, Y. (in press)
Near-Data Prediction Based Speculative Optimization in a Distribution Environment. Mobile Networks and Applications, https://doi.org/10.1007/s11036-021-01793-7
Hadoop is an open source from Apache with a distributed file system and MapReduce distributed computing framework. The current Apache 2.0 license agreement supports on-demand ...
Introduction to the Special Issue on Intelligent Models for Security and Resilience in Cyber Physical Systems
Journal Article
Liu, Q., Liu, X., Grosu, R., & Yang, C. (2022)
Introduction to the Special Issue on Intelligent Models for Security and Resilience in Cyber Physical Systems. Computer Modeling in Engineering and Sciences, 131(1), 23-26. https://doi.org/10.32604/cmes.2022.020646
This article has no abstract.
Using Semantic Technology to Model Persona for Adaptable Agents
Conference Proceeding
Nguyen, J., Farrenkopf, T., Guckert, M., Powers, S., & Urquhart, N. (2021)
Using Semantic Technology to Model Persona for Adaptable Agents. In ECMS 2021, 35th Proceedings (172-178). https://doi.org/10.7148/2021
In state of the art research a growing interest in the application of agent models for the simulation of road traffic can be observed. Software agents are particularly suitabl...
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...
An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars
Journal Article
Wu, H., Liu, Q., Liu, X., Zhang, Y., & Yang, Z. (2022)
An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars. World Wide Web, 25, 1923-1949. https://doi.org/10.1007/s11280-021-00988-y
Internet of Things (IoT) has been rapidly developed in recent years, being well applied in the fields of Environmental Surveillance, Smart Grid, Intelligent Transportation, an...