Prof Xiaodong Liu's Outputs (195)

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.

TRUSTD: Combat Fake Content using Blockchain and Collective Signature Technologies (2020)
Presentation / Conference Contribution
Jaroucheh, Z., Alissa, M., Buchanan, W. J., & Liu, X. (2020, July). TRUSTD: Combat Fake Content using Blockchain and Collective Signature Technologies. Presented at 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC 2020), Online

The growing trend of sharing news/contents, through social media platforms and the World Wide Web has been seen to impact our perception of the truth, altering our views about politics, economics, relationships, needs and wants. This is because of th... Read More about TRUSTD: Combat Fake Content using Blockchain and Collective Signature Technologies.

Monthly Precipitation Forecasts Using Wavelet Neural Networks Models in a Semiarid Environment (2020)
Journal Article
Estévez, J., Bellido-Jiménez, J. A., Liu, X., & García-Marín, A. P. (2020). Monthly Precipitation Forecasts Using Wavelet Neural Networks Models in a Semiarid Environment. Water, 12(7), Article 1909. https://doi.org/10.3390/w12071909

Accurate forecast of hydrological data such as precipitation is critical in order to provide useful information for water resources management, playing a key role in different sectors. Traditional forecasting methods present many limitations due to t... Read More about Monthly Precipitation Forecasts Using Wavelet Neural Networks Models in a Semiarid Environment.

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.

An Adaptive Kalman Filtering Approach to Sensing and Predicting Air Quality Index Values (2020)
Journal Article
Chen, J., Chen, K., Ding, C., Wang, G., Liu, Q., & Liu, X. (2020). An Adaptive Kalman Filtering Approach to Sensing and Predicting Air Quality Index Values. IEEE Access, 8, 4265-4272. https://doi.org/10.1109/access.2019.2963416

In recent years, Air Quality Index (AQI) have been widely used to describe the severity of haze and other air pollutions yet suffers from inefficiency and compatibility on real-time perception and prediction. In this paper, an Auto-Regressive (AR) pr... Read More about An Adaptive Kalman Filtering Approach to Sensing and Predicting Air Quality Index Values.

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 Health, 16(24), Article 5102. https://doi.org/10.3390/ijerph16245102

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, December). Application of Bluetooth Low Energy Beacons and Fog Computing for Smarter Environments in Emerging Economies. Presented at 9th EAI International Conference on Cloud Computing (CloudComp 2019), Sydney, Australia

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, December). Near-Data Prediction Based Speculative Optimization in a Distribution Environment. Presented at 9th EAI International Conference on Cloud Computing (CloudComp 2019), Sydney, Australia

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, July). Semantic Stream Management Framework for Data Consistency in Smart Spaces. Presented at IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), Milwaukee, Wisconsin, US

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, June). Reviving legacy enterprise systems with microservice-based architecture within cloud environments. Presented at 5th International Conference on Software Engineering (SOFT 2019), Copenhagen, Denmark

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://doi.org/10.3390/ijerph16132328

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.