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. (2023)
Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges. IEEE Systems, Man, and Cybernetics Magazine, 9(4), 4-12. https://doi.org/10.1109/msmc.2022.3216943
Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting. In this article, recent relevant scientific investigation and pra...
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 (41-50). 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...
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...