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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.

Architecting Green Mobile Cloud Apps (2021)
Book Chapter
Jaachimma Chinenyeze, S., & Liu, X. (2021). Architecting Green Mobile Cloud Apps. In C. Calero, M. Á. Moraga, & M. Piattini (Eds.), Software Sustainability (183-214). Springer. https://doi.org/10.1007/978-3-030-69970-3_8

With the resource-constrained nature of mobile devices, and the resource-abundant offerings of the cloud, several promising optimization techniques have been proposed by the green computing research community. Prominent techniques and unique methods... Read More about Architecting Green Mobile Cloud Apps.

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/s13638-021-02044-9

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.

Blockchain-based identity and authentication scheme for MQTT protocol (2021)
Presentation / Conference Contribution
Abdelrazig Abubakar, M., Jaroucheh, Z., Al-Dubai, A., & Liu, X. (2021, March). Blockchain-based identity and authentication scheme for MQTT protocol. Presented at ICBCT '21: 2021 The 3rd International Conference on Blockchain Technology, Shanghai, China

The publish and subscribe messaging model has proven itself as a dominant messaging paradigm for IoT systems. An example of such is the commonly used Message Queuing Telemetry Transport (MQTT) protocol. However, the security concerns with this protoc... Read More about Blockchain-based identity and authentication scheme for MQTT protocol.

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., Sun, M., & 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/10.1155/2021/6630492

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.

Programming Languages: A Usage-based Statistical Analysis and Visualization (2021)
Presentation / Conference Contribution
Orlowska, A., Chrysoulas, C., Jaroucheh, Z., & Liu, X. (2021, March). Programming Languages: A Usage-based Statistical Analysis and Visualization. Presented at ICISS 2021: 2021 The 4th International Conference on Information Science and Systems, Edinburgh

Understanding the popularity, and its trend, of programming languages can be important to anticipate which languages are best studied for future use, which are widely supported for use in enterprise projects, and investigate which skills are easiest... Read More about Programming Languages: A Usage-based Statistical Analysis and Visualization.

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.

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.