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All Outputs (49)

PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing (2024)
Journal Article
Zhang, Z., Liu, Q., Liu, X., Zhang, Y., Du, Z., & Cao, X. (2024). PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing. Journal of cloud computing: advances, systems and applications, 13(1), Article 76. https://doi.org/10.1186/s13677-024-00637-5

In the field of remote sensing image interpretation, automatically extracting water body information from high-resolution images is a key task. However, facing the complex multi-scale features in high-resolution remote sensing images, traditional met... Read More about PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing.

An Entity Ontology-Based Knowledge Graph Embedding Approach to News Credibility Assessment (2024)
Journal Article
Liu, Q., Jin, Y., Cao, X., Liu, X., Zhou, X., Zhang, Y., Xu, X., & Qi, L. (2024). An Entity Ontology-Based Knowledge Graph Embedding Approach to News Credibility Assessment. IEEE Transactions on Computational Social Systems, 11(4), 5308 - 5318. https://doi.org/10.1109/TCSS.2023.3342873

Fake news is a prevalent issue in modern society, leading to misinformation and societal harm. News credibility assessment is a crucial approach for evaluating the accuracy and authenticity of news. It plays a significant role in enhancing public awa... Read More about An Entity Ontology-Based Knowledge Graph Embedding Approach to News Credibility Assessment.

PFL-LDG: Privacy-preserving Federated Learning via Lightweight Device Grouping (2023)
Presentation / Conference Contribution
Wang, Z., Liu, Q., & Liu, X. (2023, August). PFL-LDG: Privacy-preserving Federated Learning via Lightweight Device Grouping. Presented at The 9th IEEE International Conference on Privacy Computing and Data Security (PCDS 2023) as Part of the IEEE Smart World Congress 2023, Portsmouth, UK

The rapid growth of private data from distributed edge networks, driven by the proliferation of IoT sensors, wearable devices, and smartphones, offers significant opportunities for AI applications. However, traditional distributed machine learning me... Read More about PFL-LDG: Privacy-preserving Federated Learning via Lightweight Device Grouping.

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.

A Multi-Swarm PSO Approach to Large-Scale Task Scheduling in a Sustainable Supply Chain Datacenter (2023)
Journal Article
Liu, Q., Zeng, L., Bilal, M., Song, H., Liu, X., Zhang, Y., & Cao, X. (2023). A Multi-Swarm PSO Approach to Large-Scale Task Scheduling in a Sustainable Supply Chain Datacenter. IEEE Transactions on Green Communications and Networking, 7(4), 1667 - 1677. https://doi.org/10.1109/tgcn.2023.3283509

Supply chain management is a vital part of ensuring service quality and production efficiency in industrial applications. With the development of cloud computing and data intelligence in modern industries, datacenters have become an important basic s... Read More about A Multi-Swarm PSO Approach to Large-Scale Task Scheduling in a Sustainable Supply Chain Datacenter.

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.

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/s42400-020-00065-3

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.

A Fast Classification Approach to Upper-Limb Posture Recognition (2020)
Presentation / Conference Contribution
Wu, X., Jiang, Y., Liu, Q., Wu, H., & Liu, X. (2020, November). A Fast Classification Approach to Upper-Limb Posture Recognition. Presented at IEEE International Conferences on Cyber, Physical and Social Computing (CPSCom2020), Rhodes, Greece

A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles (2020)
Journal Article
Liu, Q., Kamoto, K. M., Liu, X., Zhang, Y., Yang, Z., Khosravi, M. R., Xu, Y., & Qi, L. (2021). A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles. IEEE Sensors Journal, 21(14), 15895-15903. https://doi.org/10.1109/jsen.2020.3027684

Intelligent transportation systems (ITSs) have become popular in recent years as an essential requirement for safer and more efficient transportation systems. Internet of Electric vehicles (IoEV) as well as their hybrid forms provide an ideal means o... Read More about A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles.

A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings (2020)
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 signal readings at a single point to deduce the share of the devices that have... Read More about A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings.

A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers (2020)
Journal Article
Xiao, B., Jiang, Y., Liu, Q., Liu, X., & Sun, M. (2020). A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers. Computers, Materials & Continua, 64(1), 389-399. https://doi.org/10.32604/cmc.2020.06092

MEMS accelerometers are widely used in various fields due to their small size and low cost, and have good application prospects. However, the low accuracy limits its range of applications. To ensure data accuracy and safety we need to calibrate MEMS... Read More about A Survey of Error Analysis and Calibration Methods for MEMS Triaxial Accelerometers.

An Optimized Resource Scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes (2020)
Journal Article
Jiang, Y., Liu, Q., Dannah, W., Jin, D., Liu, X., & Sun, M. (2020). An Optimized Resource Scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes. Computers, Materials & Continua, 62(2), 713-729. https://doi.org/10.32604/cmc.2020.04604

Hadoop is a well-known parallel computing system for distributed computing and large-scale data processes. “Straggling” tasks, however, have a serious impact on task allocation and scheduling in a Hadoop system. Speculative Execution (SE) is an effic... Read More about An Optimized Resource Scheduling Strategy for Hadoop Speculative Execution Based on Non-cooperative Game Schemes.