Outputs (48)

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.

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.

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.

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.

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.

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.2019.2891160

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.

An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment (2018)
Journal Article
Jin, D.-D., Liu, Q., Liu, X., & Linge, N. (2019). An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment. Journal of Computers, 30(3), 130-142. https://doi.org/10.3966/199115992019063003010

Hadoop is a famous parallel computing framework that is applied to process large-scale data, but there exists such a task in hadoop framework, which is called “Straggling task” and has a serious impact on Hadoop. Speculative execution (SE) is an effe... Read More about An optimized Speculative Execution Strategy Based on Local Data Prediction in Heterogeneous Hadoop Environment.

A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network (2018)
Journal Article
Liu, X., Liu, Q., & Sun, M. (2018). A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network. Computers, Materials & Continua, 57(2), 179-194. https://doi.org/10.32604/cmc.2018.04025

In a home energy management system (HEMS), appliances are becoming diversified and intelligent, so that certain simple maintenance work can be completed by appliances themselves. During the measurement, collection and transmission of electricity load... Read More about A Dual-spine Approach to Load Error Repair in a HEMS Sensor Network.

SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data (2018)
Journal Article
Xiao, B., Wang, Z., Liu, Q., & Liu, X. (2018). SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data. Computers, Materials & Continua, 56(3), 365-379. https://doi.org/10.3970/cmc.2018.01830

In recent years, the rapid development of big data technology has also been favored by more and more scholars. Massive data storage and calculation problems have also been solved. At the same time, outlier detection problems in mass data have also co... Read More about SMK-means: An Improved Mini Batch K-means Algorithm Based on Mapreduce with Big Data.

Appliance Recognition Based on Continuous Quadratic Programming (2018)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2018, June). Appliance Recognition Based on Continuous Quadratic Programming. Presented at 4th International Conference on Cloud Computing and Security (ICCCS 2018), Haikou, China

The detailed information of residents' electricity consumption is of great significance to the planning of the use of electrical appliances and the reduction of electrical energy consumption. On the basis of analyzing the characteristics of residents... Read More about Appliance Recognition Based on Continuous Quadratic Programming.

A Self-organizing LSTM-Based Approach to PM2.5 Forecast (2018)
Presentation / Conference Contribution
Liu, X., Liu, Q., Zou, Y., & Wang, G. (2018, June). A Self-organizing LSTM-Based Approach to PM2.5 Forecast. Presented at 4th International Conference on Cloud Computing and Security (ICCCS 2018), Haikou, China

Nanjing has been listed as the one of the worst performers across China with respect to the high level of haze-fog, which impacts people's health greatly. For the severe condition of haze-fog, PM2.5 is the main cause element of haze-fog pollution in... Read More about A Self-organizing LSTM-Based Approach to PM2.5 Forecast.

CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN (2018)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2018, April). CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN. Presented at 2018 3rd International Conference on Computer and Communication Systems (ICCCS), Nagoya, Japan

Acoustic Communication is one of the most common and popular techniques used for Underwater Sensor Networks. The design of its communication protocol becomes a challenge due to its features of high delay and low bandwidth. Relevant research work has... Read More about CAMA-UAN: A Context-Aware MAC Scheme to the Underwater Acoustic Sensor Networks for the Improved CACA-UAN.

Home appliances classification based on multi-feature using ELM (2018)
Journal Article
Wu, Z., Liu, Q., Chen, F., Chen, F., Liu, X., & Linge, N. (2018). Home appliances classification based on multi-feature using ELM. International Journal of Sensor Networks, 28(1), 34. https://doi.org/10.1504/ijsnet.2018.094710

With the development of science and technology, the application in artificial intelligence has been more and more popular, as well as smart home has become a hot topic. And pattern recognition adapting to smart home attracts more attention, while the... Read More about Home appliances classification based on multi-feature using ELM.

A method for electric load data verification and repair in home environment (2018)
Journal Article
Liu, Q., Li, S., Liu, X., & Linge, N. (2018). A method for electric load data verification and repair in home environment. International Journal of Embedded Systems, 10(3), 248-256. https://doi.org/10.1504/ijes.2018.091788

Home energy management (HEM) and smart home have been popular among people; HEM collects and analyses the electric load data to make the power use safe, reliable, economical, efficient and environmentally friendly. Without the correct data, the corre... Read More about A method for electric load data verification and repair in home environment.

CACA-UAN: a context-aware communication approach to efficient and reliable underwater acoustic sensor networks (2018)
Journal Article
Liu, Q., Chen, X., Liu, X., & Linge, N. (2018). CACA-UAN: a context-aware communication approach to efficient and reliable underwater acoustic sensor networks. International Journal of Sensor Networks, 26(1), 1. https://doi.org/10.1504/ijsnet.2018.088364

Underwater Acoustic Sensor Networks (UANs) have emerged as a promising technology recently which can be applied in many areas such as military and civil, where the communication between devices is crucial and challenging due to the unique characteris... Read More about CACA-UAN: a context-aware communication approach to efficient and reliable underwater acoustic sensor networks.

A virtual uneven grid-based routing protocol for mobile sink-based WSNs in a smart home system (2017)
Journal Article
Liu, X., & Liu, Q. (2018). A virtual uneven grid-based routing protocol for mobile sink-based WSNs in a smart home system. Personal and Ubiquitous Computing, https://doi.org/10.1007/s00779-017-1093-2

In a non-uniformly distributed network, the dataconcentrating centre equipped with sparse nodes rapidly depletes its battery energy due to the hotspot problem. To solve this problem, a Virtual Uneven Grid-based Routing protocol (VUGR) is proposed in... Read More about A virtual uneven grid-based routing protocol for mobile sink-based WSNs in a smart home system.

An Energy-Efficiency Routing Scheme Based on Clusters with a Mobile Sink for WSNs (2017)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2017, June). An Energy-Efficiency Routing Scheme Based on Clusters with a Mobile Sink for WSNs. Presented at 3rd International Conference on Cloud Computing and Security (ICCCS 2017)

With the development of microelectronic devices and the radio, the application of WSN is more popular and can be applied in the various areas, which has attracted scholars. However, the requirements of performance for WSNs are becoming great in terms... Read More about An Energy-Efficiency Routing Scheme Based on Clusters with a Mobile Sink for WSNs.

Power Consuming Activity Recognition in Home Environment (2017)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2017, June). Power Consuming Activity Recognition in Home Environment. Presented at the 3rd International Conference on Cloud Computing and Security (ICCCS 2017)

This work proposed an activity recognition model which focus on the power con-suming activity in home environment, to help residents modify their behavior. We set the IoT system with lower number of sensors. The key data for identifying activity come... Read More about Power Consuming Activity Recognition in Home Environment.