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Outputs (45)

Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges (2023)
Journal Article
Liu, Q., Yang, Z., Ji, R., Zhang, Y., Bilal, M., Liu, X., Vimal, S., & 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 practical efforts using deep learning (DL) models for weather radar data analy... Read More about Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges.

Near-Data Prediction Based Speculative Optimization in a Distribution Environment (2022)
Journal Article
Liu, Q., Wu, X., Liu, X., Zhang, Y., & Hu, Y. (2022). Near-Data Prediction Based Speculative Optimization in a Distribution Environment. Mobile Networks and Applications, 27(6), 2339-2347. 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 payment by consumers for cloud platform services, helping users leverage th... Read More about Near-Data Prediction Based Speculative Optimization in a Distribution Environment.

Intelligent Question Answering System Based on Knowledge Graph (2022)
Presentation / Conference Contribution
Feng, X., Liu, Q., & Liu, X. (2021, December). Intelligent Question Answering System Based on Knowledge Graph. Presented at IEEE SmartCity-2021, Hainan, China

In order to build a smart city and pursue more efficient city management, various industries have introduced intelligent question answering into process management. The intelligent question answering system based on the knowledge graph is dedicated t... Read More about Intelligent Question Answering System Based on Knowledge Graph.

Improving Domestic NILM Using An Attention- Enabled Seq2Point Learning Approach (2022)
Presentation / Conference Contribution
Zhang, J., Sun, J., Gan, J., Liu, Q., & Liu, X. (2021, October). Improving Domestic NILM Using An Attention- Enabled Seq2Point Learning Approach. Presented at The 6th IEEE Cyber Science and Technology Congress (2021) (CyberSciTech 2021), AB, Canada [Online]

The past decade have seen a growth in Internet technology, the overlap of cyberspace and social space provides great convenience for people's life. The in-depth study of non-intrusive load management (NILM) promotes the development of multi-integrati... Read More about Improving Domestic NILM Using An Attention- Enabled Seq2Point Learning Approach.

An Intelligent Method for Upper Limb Posture Recognition Based on Limited MEMS Data (2022)
Presentation / Conference Contribution
Wu, Z., Wu, X., Liu, Q., & Liu, X. (2021, October). An Intelligent Method for Upper Limb Posture Recognition Based on Limited MEMS Data. Presented at The 6th IEEE Cyber Science and Technology Congress (2021) (CyberSciTech 2021), AB, Canada [Online]

There are more than 10 million new stroke cases worldwide every year, and stroke has become one of the main causes of death and disability. In recent years, with the rapid development of computer science and technology, through the combination of Int... Read More about An Intelligent Method for Upper Limb Posture Recognition Based on Limited MEMS Data.

Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks (2021)
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 solutions benefiting from the advancement of emerging technologies such as Wire... Read More about Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks.

A hybrid CNN-LSTM model for predicting PM2.5 in Beijing based on spatiotemporal correlation (2021)
Journal Article
Ding, C., Wang, G., Zhang, X., Liu, Q., & Liu, X. (2021). A hybrid CNN-LSTM model for predicting PM2.5 in Beijing based on spatiotemporal correlation. Environmental and Ecological Statistics, 128(3), 503-522. https://doi.org/10.1007/s10651-021-00501-8

Long-term exposure to air environments full of suspended particles, especially PM2.5, would seriously damage people's health and life (i.e., respiratory diseases and lung cancers). Therefore, accurate PM2.5 prediction is important for the government... Read More about A hybrid CNN-LSTM model for predicting PM2.5 in Beijing based on spatiotemporal correlation.

A fully connected deep learning approach to upper limb gesture recognition in a secure FES rehabilitation environment (2021)
Journal Article
Liu, Q., Wu, X., Jiang, Y., Liu, X., Zhang, Y., Xu, X., & Qi, L. (2021). A fully connected deep learning approach to upper limb gesture recognition in a secure FES rehabilitation environment. International Journal of Intelligent Systems, 36(5), 2387-2411. https://doi.org/10.1002/int.22383

Stroke is one of the leading causes of death and disability in the world. The rehabilitation of Patients' limb functions has great medical value, for example, the therapy of functional electrical stimulation (FES) systems, but suffers from effective... Read More about A fully connected deep learning approach to upper limb gesture recognition in a secure FES rehabilitation environment.