All Outputs (9)

Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization (2024)
Journal Article
Zeng, L., Liu, Q., Shen, S., & Liu, X. (2024). Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization. Tsinghua Science and Technology, 29(3), 806 - 817. https://doi.org/10.26599/TST.2023.9010058

Edge computing nodes undertake more and more tasks as business density grows. How to efficiently allocate large-scale and dynamic workloads to edge computing resources has become a critical challenge. An edge task scheduling approach based on an impr... Read More about Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization.

Scalable Machine Learning Architectures for IPA-Driven Maintenance Task Allocation in Large-Scale Building Portfolios (2024)
Presentation / Conference Contribution
Huang, Z., Liu, X., Romdhani, I., & Shih, C. (2024, August). Scalable Machine Learning Architectures for IPA-Driven Maintenance Task Allocation in Large-Scale Building Portfolios. Presented at The 7th International Conference on Information Science and Systems (ICISS 2024), Edinburgh

This research presents a groundbreaking approach to Building Maintenance Management (BMM) by introducing an Intelligent Process Automation (IPA)-Driven Building Maintenance Management (IBMM) model. This innovative model harnesses the synergies betwee... Read More about Scalable Machine Learning Architectures for IPA-Driven Maintenance Task Allocation in Large-Scale Building Portfolios.

Neurosymbolic learning in the XAI framework for enhanced cyberattack detection with expert knowledge integration (2024)
Presentation / Conference Contribution
Kalutharage, C. S., Liu, X., Chrysoulas, C., & Bamgboye, O. (2024, June). Neurosymbolic learning in the XAI framework for enhanced cyberattack detection with expert knowledge integration. Presented at The 39th International Conference on ICT Systems Security and Privacy Protection (SEC 2024), Edinburgh

The perpetual evolution of cyberattacks, especially in the realm of Internet of Things (IoT) networks, necessitates advanced, adaptive, and intelligent defence mechanisms. The integration of expert knowledge can drastically enhance the efficacy of Io... Read More about Neurosymbolic learning in the XAI framework for enhanced cyberattack detection with expert knowledge integration.

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.

Towards Building a Smart Water Management System (SWAMS) in Nigeria (2024)
Presentation / Conference Contribution
Bamgboye, O., Chrysoulas, C., Liu, X., Watt, T., Sodiya, A., Oyeleye, M., & Kalutharage, S. (2024, June). Towards Building a Smart Water Management System (SWAMS) in Nigeria. Presented at The 22nd IEEE Mediterranean Electrotechnical Conference, Porto, Portugal

The water management landscape in Nigeria struggles with formidable obstacles characterized by a lack of adequate infrastructure, an uneven distribution of resources, and insufficient access to clean water, particularly in rural areas. These challeng... Read More about Towards Building a Smart Water Management System (SWAMS) in Nigeria.

A spatio-temporal graph convolutional approach to real-time load forecasting in an edge-enabled distributed Internet of Smart Grids energy system (2024)
Journal Article
Liu, Q., Pan, L., Cao, X., Gan, J., Huang, X., & Liu, X. (2024). A spatio-temporal graph convolutional approach to real-time load forecasting in an edge-enabled distributed Internet of Smart Grids energy system. Concurrency and Computation: Practice and Experience, 36(13), Article e8060. https://doi.org/10.1002/cpe.8060

As the edge nodes of the Internet of Smart Grids (IoSG), smart sockets enable all kinds of power load data to be analyzed at the edge, which create conditions for edge calculation and real-time (RT) load forecasting. In this article, an edge-cloud co... Read More about A spatio-temporal graph convolutional approach to real-time load forecasting in an edge-enabled distributed Internet of Smart Grids energy system.

Utilizing the Ensemble Learning and XAI for Performance Improvements in IoT Network Attack Detection (2024)
Presentation / Conference Contribution
Kalutharage, C. S., Liu, X., Chrysoulas, C., & Bamgboye, O. (2023, September). Utilizing the Ensemble Learning and XAI for Performance Improvements in IoT Network Attack Detection. Presented at The 4th International Workshop on Cyber-Physical Security for Critical Infrastructures Protection (CPS4CIP 2023) - in conjunction with ESORICS 2023, The Hague, Netherlands

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. (online). An Entity Ontology-Based Knowledge Graph Embedding Approach to News Credibility Assessment. IEEE Transactions on Computational Social Systems, 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.

DenMerD: a feature enhanced approach to radar beam blockage correction with edge-cloud computing (2024)
Journal Article
Liu, Q., Sun, J., Zhang, Y., & Liu, X. (2024). DenMerD: a feature enhanced approach to radar beam blockage correction with edge-cloud computing. Journal of cloud computing: advances, systems and applications, 13, Article 32. https://doi.org/10.1186/s13677-024-00607-x

In the field of meteorology, the global radar network is indispensable for detecting weather phenomena and offering early warning services. Nevertheless, radar data frequently exhibit anomalies, including gaps and clutter, arising from atmospheric re... Read More about DenMerD: a feature enhanced approach to radar beam blockage correction with edge-cloud computing.