All Outputs (8)

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

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.

An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars (2021)
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/s11280-021-0098

Internet of Things (IoT) has been rapidly developed in recent years, being well applied in the fields of Environmental Surveillance, Smart Grid, Intelligent Transportation, and so on. As one of the typical earth-based meteorological observation metho... Read More about An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars.

A Survey of Semantic Construction and Application of Satellite Remote Sensing Images and Data (2021)
Journal Article
Lu, H., Liu, Q., Liu, X., & Zhang, Y. (2021). A Survey of Semantic Construction and Application of Satellite Remote Sensing Images and Data. Journal of Organizational and End User Computing, 33(6), Article 6. https://doi.org/10.4018/joeuc.20211101.oa6

With the rapid development of satellite technology, remote sensing data has entered the era of big data, and the intelligent processing of remote sensing image has been paid more and more attention. Through the semantic research of remote sensing dat... Read More about A Survey of Semantic Construction and Application of Satellite Remote Sensing Images and Data.

RSST-ARGM: a data-driven approach to long-term sea surface temperature prediction (2021)
Journal Article
Zhu, L., Liu, Q., Liu, X., & Zhang, Y. (2021). RSST-ARGM: a data-driven approach to long-term sea surface temperature prediction. EURASIP Journal on Wireless Communications and Networking, 2021, Article 171 (2021). https://doi.org/10.1186/s13638-021-02044

For the purpose of exploring the long-term variation of regional sea surface temperature (SST), this paper studies the historical SST in regional sea areas and the emission pattern of greenhouse gases, proposing a Grey model of regional SST atmospher... Read More about RSST-ARGM: a data-driven approach to long-term sea surface temperature prediction.

A Control and Posture Recognition Strategy for Upper-Limb Rehabilitation of Stroke Patients (2021)
Journal Article
Yu, X., Xiao, B., Tian, Y., Wu, Z., Liu, Q., Wang, J., …Liu, X. (2021). A Control and Posture Recognition Strategy for Upper-Limb Rehabilitation of Stroke Patients. Wireless Communications and Mobile Computing, 2021, Article 6630492. https://doi.org/10.

At present, the study of upper-limb posture recognition is still in the primary stage; due to the diversity of the objective environment and the complexity of the human body posture, the upper-limb posture has no public dataset. In this paper, an upp... Read More about A Control and Posture Recognition Strategy for Upper-Limb Rehabilitation of Stroke Patients.

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.

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.

A renewable energy forecasting and control approach to secured edge-level efficiency in a distributed micro-grid (2021)
Journal Article
Anaadumba, R., Liu, Q., Marah, B. D., Nakoty, F. M., Liu, X., & Zhang, Y. (2021). A renewable energy forecasting and control approach to secured edge-level efficiency in a distributed micro-grid. Cybersecurity, 4, Article 1 (2021). https://doi.org/10.1186

Energy forecasting using Renewable energy sources (RESs) is gradually gaining weight in the research field due to the benefits it presents to the modern-day environment. Not only does energy forecasting using renewable energy sources help mitigate th... Read More about A renewable energy forecasting and control approach to secured edge-level efficiency in a distributed micro-grid.