Outputs (397)

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.

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.

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.

An AI approach to Collecting and Analyzing Human Interactions with Urban Environments (2019)
Journal Article
Ferrara, E., Fragale, L., Fortino, G., Song, W., Perra, C., di Mauro, M., & Liotta, A. (2019). An AI approach to Collecting and Analyzing Human Interactions with Urban Environments. IEEE Access, 7, 141476-141486. https://doi.org/10.1109/access.2019.2943845

Thanks to advances in Internet of Things and crowd-sensing, it is possible to collect vast amounts of urban data, to better understand how citizens interact with cities and, in turn, improve human well-being in urban environments. This is a scientifi... Read More about An AI approach to Collecting and Analyzing Human Interactions with Urban Environments.

Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach (2019)
Journal Article
Di Mauro, M., & Liotta, A. (2019). Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach. IEEE Transactions on Network and Service Management, 16(4), 1493-1506. https://doi.org/10.1109/tnsm.2019.2943776

The Next Generation 5G Networks can greatly benefit from the synergy between virtualization paradigms, such as the Network Function Virtualization (NFV), and service provisioning platforms such as the IP Multimedia Subsystem (IMS). The NFV concept is... Read More about Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach.

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.

Rich Data for Wind Turbine Power Performance Analysis (2019)
Data
Davison, B. (2019). Rich Data for Wind Turbine Power Performance Analysis. [Data]. https://doi.org/10.13020/1etn-1q17

This dataset was created in order to support comparative analyses concerning the relationships between meteorological parameters and wind turbine power output. It addresses some of the limitations of existing datasets such as those compiled for comme... Read More about Rich Data for Wind Turbine Power Performance Analysis.

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.

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.

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), Article 1159. https://doi.org/10.3390/ijerph16071159

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.

Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks (2019)
Journal Article
Savaglio, C., Pace, P., Aloi, G., Liotta, A., & Fortino, G. (2019). Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks. IEEE Access, 7, 29355-29364. https://doi.org/10.1109/access.2019.2902371

High-density communications in wireless sensor networks (WSNs) demand for new approaches to meet stringent energy and spectrum requirements. We turn to reinforcement learning, a prominent method in artificial intelligence, to design an energy-preserv... Read More about Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks.

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..

Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities (2019)
Journal Article
Erhan, L., Ndubuaku, M., Ferrara, E., Richardson, M., Sheffield, D., Ferguson, F. J., Brindley, P., & Liotta, A. (2019). Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities. IEEE Access, 7, 19890-19906. https://doi.org/10.1109/access.2019.2897217

The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data from our cities. In this paper, we investigate a novel way of analyzing dat... Read More about Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities.

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.

A tool for generating synthetic data (2018)
Presentation / Conference Contribution
Peng, T., & Telle, A. (2018, October). A tool for generating synthetic data. Presented at DATA '18 First International Conference on Data Science, E-learning and Information Systems, Madrid, Spain

It is popular to use real-world data to evaluate data mining techniques. However, there are some disadvantages to use real-world data for such purposes. Firstly, real-world data in most domains is difficult to obtain for several reasons, such as budg... Read More about A tool for generating synthetic data.