All Outputs (15)

A Review on Deep Learning Approaches to Image Classification and Object Segmentation (2019)
Journal Article
Wu, H., Liu, Q., & Liu, X. (2019). A Review on Deep Learning Approaches to Image Classification and Object Segmentation. Computers, Materials & Continua, 60(2), 575-597. https://doi.org/10.32604/cmc.2019.03595

Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effe... Read More about A Review on Deep Learning Approaches to Image Classification and Object Segmentation.

PM2.5 Pollution: Health and Economic Effect Assessment Based on a Recursive Dynamic Computable General Equilibrium Model (2019)
Journal Article
Chen, K., Wang, G., Wu, L., Chen, J., Yuan, S., Liu, Q., & Liu, X. (2019). PM2.5 Pollution: Health and Economic Effect Assessment Based on a Recursive Dynamic Computable General Equilibrium Model. International Journal of Environmental Research and Public

At present particulate matter (PM₂.₅) pollution represents a serious threat to the public health and the national economic system in China. This paper optimizes the whitening coefficient in a grey Markov model by a genetic algorithm, predicts the con... Read More about PM2.5 Pollution: Health and Economic Effect Assessment Based on a Recursive Dynamic Computable General Equilibrium Model.

Application of Bluetooth Low Energy Beacons and Fog Computing for Smarter Environments in Emerging Economies (2019)
Presentation / Conference Contribution
Sun, M., Michael Kamoto, K., Liu, Q., Liu, X., & Qi, L. (2019). Application of Bluetooth Low Energy Beacons and Fog Computing for Smarter Environments in Emerging Economies.

The Internet of Things (IoT) has already begun to drastically alter the way people operate in various industries across the world, as well as how we interact with our environment. There is a lot of progress being made toward... Read More about Application of Bluetooth Low Energy Beacons and Fog Computing for Smarter Environments in Emerging Economies.

Near-Data Prediction Based Speculative Optimization in a Distribution Environment (2019)
Presentation / Conference Contribution
Sun, M., Wu, X., Jin, D., Xu, X., Liu, Q., & Liu, X. (2019). Near-Data Prediction Based Speculative Optimization in a Distribution Environment.

Apache Hadoop is an open source software framework that supports data-intensive distributed applications and is distributed under the Apache 2.0 licensing agreement, where consumers will no longer deal with complex configuration of softwar... Read More about Near-Data Prediction Based Speculative Optimization in a Distribution Environment.

Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing (2019)
Journal Article
Liu, Q., Wang, Z., Liu, X., & Linge, N. (2019). Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing. International Journal of High Performance Computing and Networking, 14(4), 435-443. https://doi.org/10.1504/IJHPCN.2019.102350

In the wake of the development in science and technology, Cloud Computing has obtained more attention in different field. Meanwhile, outlier detection for data mining in Cloud Computing is playing more and more significant role in different research... Read More about Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing.

Semantic Stream Management Framework for Data Consistency in Smart Spaces (2019)
Presentation / Conference Contribution
Bamgboye, O., Liu, X., & Cruickshank, P. (2019). Semantic Stream Management Framework for Data Consistency in Smart Spaces. . https://doi.org/10.1109/COMPSAC.2019.10188

Semantic technology can provide a bridge between smart applications and Internet of Things (IoT) to enable possible integration and interoperability of data produced by heterogeneous devices. In IoT, data quality plays an important role when it c... Read More about Semantic Stream Management Framework for Data Consistency in Smart Spaces.

Reviving legacy enterprise systems with microservice-based architecture within cloud environments (2019)
Presentation / Conference Contribution
Habibullah, S., Liu, X., Tan, Z., Zhang, Y., & Liu, Q. (2019). Reviving legacy enterprise systems with microservice-based architecture within cloud environments. In Computer Science Conference Proceedings. https://doi.org/10.5121/csit.2019.90713

Evolution has always been a challenge for enterprise computing systems. The microservice based architecture is a new design model which is rapidly becoming one of the most effective means to re-architect legacy enterprise systems and to reengineer th... Read More about Reviving legacy enterprise systems with microservice-based architecture within cloud environments.

An Auto-Calibration Approach to Robust and Secure Usage of Accelerometers for Human Motion Analysis in FES Therapies (2019)
Journal Article
Sun, M., Jiang, Y., Liu, Q., & Liu, X. (2019). An Auto-Calibration Approach to Robust and Secure Usage of Accelerometers for Human Motion Analysis in FES Therapies. Computers, Materials & Continua, 60(1), 67-83. https://doi.org/10.32604/cmc.2019.06079

A Functional Electrical stimulation (FES) therapy is a common rehabilitation intervention after stroke, and finite state machine (FSM) has proven to be an effective and intuitive FES control method. The FSM uses the data information generated by the... Read More about An Auto-Calibration Approach to Robust and Secure Usage of Accelerometers for Human Motion Analysis in FES Therapies.

Indirect Economic Impact Incurred by Haze Pollution: An Econometric and Input–Output Joint Model (2019)
Journal Article
Chen, J., Chen, K., Wang, G., Chen, R., Liu, X., & Wei, G. (2019). Indirect Economic Impact Incurred by Haze Pollution: An Econometric and Input–Output Joint Model. International Journal of Environmental Research and Public Health, 16(13), 2328. https:/

Econometrics and input–output models have been presented to construct a joint model (i.e., an EC + IO model) in the paper, which is characterized by incorporating the uncertainty of the real economy with the detailed departmental classification struc... Read More about Indirect Economic Impact Incurred by Haze Pollution: An Econometric and Input–Output Joint Model.

A Self-Organizing Memory Neural Network for Aerosol Concentration Prediction (2019)
Journal Article
Liu, Q., Zou, Y., & Liu, X. (2019). A Self-Organizing Memory Neural Network for Aerosol Concentration Prediction. Computer Modeling in Engineering and Sciences, 119(3), 617-637. https://doi.org/10.32604/cmes.2019.06272

Haze-fog, which is an atmospheric aerosol caused by natural or man-made factors, seriously affects the physical and mental health of human beings. PM2.5 (a particulate matter whose diameter is smaller than or equal to 2.5 microns) is the chief culpri... Read More about A Self-Organizing Memory Neural Network for Aerosol Concentration Prediction.

Non-intrusive load monitoring and its challenges in a NILM system framework (2019)
Journal Article
Liu, Q., Lu, M., Liu, X., & Linge, N. (2019). Non-intrusive load monitoring and its challenges in a NILM system framework. International Journal of High Performance Computing and Networking, 14(1), 102-111. https://doi.org/10.1504/IJHPCN.2019.099748

With the increasing of energy demand and electricity price, researchers gain more and more interest among the residential load monitoring. In order to feed back the individual appliance’s energy consumption instead of the whole-house energy consumpti... Read More about Non-intrusive load monitoring and its challenges in a NILM system framework.

A LSTM-Based Approach to Haze Prediction Using a Self-organizing Single Hidden Layer Scheme (2019)
Presentation / Conference Contribution
Liu, X., Liu, Q., Zou, Y., & Liu, Q. (2020). A LSTM-Based Approach to Haze Prediction Using a Self-organizing Single Hidden Layer Scheme. In Security with Intelligent Computing and Big-data Services (701-706). https://doi.org/10.1007/978-3-030-16946-6_57

The air quality in urban areas seriously affects the physical and mental health of human beings. And PM2.5 (a particulate matter whose diameter is smaller than or equal to 2.5 microns) is the chief culprit causing haze-fog. Since the meteorological d... Read More about A LSTM-Based Approach to Haze Prediction Using a Self-organizing Single Hidden Layer Scheme.

PM2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism (2019)
Journal Article
Chen, J., Chen, K., Wang, G., Wu, L., Liu, X., & Wei, G. (2019). PM2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism. International Journal of Environmental Research and Public Health, 16(7), Articl

In this paper, a vector autoregression (VAR) model has been constructed in order to analyze a two-way mechanism between PM2.5 pollution and industry development in Beijing via the combination of an impulse response function and variance decomposition... Read More about PM2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism.

Microgrids As A Service for Rural Electrification in Sub-Saharan Africa. (2019)
Journal Article
Liu, Q., Kamoto, K. M., & Liu, X. (2020). Microgrids As A Service for Rural Electrification in Sub-Saharan Africa. Computers, Materials & Continua, 63(3), 1249-1261. https://doi.org/10.32604/cmc.2020.05598

The majority of the population on the African continent is unable to access basic electricity services, this despite the abundance of renewable energy sources (RESs). The inability to adequately tap into these RESs has led to the continued dependence... Read More about Microgrids As A Service for Rural Electrification in Sub-Saharan Africa..

Low-Complexity Non-Intrusive Load Monitoring Using Unsupervised Learning and Generalized Appliance Models (2019)
Journal Article
Liu, Q., Kamoto, K. M., Liu, X., Sun, M., & Linge, N. (2019). Low-Complexity Non-Intrusive Load Monitoring Using Unsupervised Learning and Generalized Appliance Models. IEEE Transactions on Consumer Electronics, 65(1), 1-1. https://doi.org/10.1109/tce.201

Awareness of electric energy usage has both societal and economic benefits, which include reduced energy bills and stress on non-renewable energy sources. In recent years, there has been a surge in interest in the field of load monitoring, also refer... Read More about Low-Complexity Non-Intrusive Load Monitoring Using Unsupervised Learning and Generalized Appliance Models.