Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection (2020)
Journal Article
Tian, Z., Shi, W., Tan, Z., Qiu, J., Sun, Y., Jiang, F., & Liu, Y. (online). Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection. Mobile Networks and Applications, https://doi.org/10.1007/s11036-020-01656-7

Organizations' own personnel now have a greater ability than ever before to misuse their access to critical organizational assets. Insider threat detection is a key component in identifying rare anomalies in context, which is a growing concern for ma... Read More about Deep Learning and Dempster-Shafer Theory Based Insider Threat Detection.

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.

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.

Urban data management system: Towards Big Data analytics for Internet of Things based smart urban environment using customized Hadoop (2019)
Journal Article
Babar, M., Arif, F., Jan, M. A., Tan, Z., & Khan, F. (2019). Urban data management system: Towards Big Data analytics for Internet of Things based smart urban environment using customized Hadoop. Future Generation Computer Systems, 96, 398-409. https://doi.org/10.1016/j.future.2019.02.035

The unbroken amplfication of a versatile urban setup is challenged by huge Big Data processing. Understanding the voluminous data generated in a smart urban environment for decision making is a challenging task. Big Data analytics is performed to ob... Read More about Urban data management system: Towards Big Data analytics for Internet of Things based smart urban environment using customized Hadoop.

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 Look at the Effects of Handheld and Projected Augmented-reality on a Collaborative Task (2018)
Presentation / Conference Contribution
Mackamul, E. B., & Esteves, A. (2018, October). A Look at the Effects of Handheld and Projected Augmented-reality on a Collaborative Task. Presented at 6th ACM Symposium on Spatial User Interaction, Berlin, Germany

This paper presents a comparative study between two popular AR systems during a collocated collaborative task. The goal of the study is to start a body of knowledge that describes the effects of different AR approaches in users' experience and perfor... Read More about A Look at the Effects of Handheld and Projected Augmented-reality on a Collaborative Task.

NgramPOS: A Bigram-based Linguistic and Statistical Feature Process Model for Unstructured Text Classification (2018)
Journal Article
Yazdania, S., Tan, Z., Kakavand, M., & Lau, S. (2022). NgramPOS: A Bigram-based Linguistic and Statistical Feature Process Model for Unstructured Text Classification. Wireless Networks, 28(3), 1251-1261. https://doi.org/10.1007/s11276-018-01909-0

Research in financial domain has shown that sentiment aspects of stock news have a profound impact on volume trades, volatility, stock prices and firm earnings. With the ever growing social inetworking and online marketing sites, the reviews obtained... Read More about NgramPOS: A Bigram-based Linguistic and Statistical Feature Process Model for Unstructured Text Classification.

A Chain Topology for Efficient Monitoring of Food Grain Storage using Smart Sensors (2018)
Presentation / Conference Contribution
Kumar Mishra, A., Kumar Tripathy, A., Obaidat, M. S., Tan, Z., Prasad, M., Sadoun, B., & Puthal, D. (2018, July). A Chain Topology for Efficient Monitoring of Food Grain Storage using Smart Sensors. Presented at The 15th International Joint Conference on e-Business, Porto, Portugal

Due to lack of an efficient monitoring system to periodically record environmental parameters for food grain storage, a huge loss of food grains in storage is reported every year in many developing countries, especially south-Asian countries. Althoug... Read More about A Chain Topology for Efficient Monitoring of Food Grain Storage using Smart Sensors.

The Influence of Computer Self-efficacy and Subjective Norms on the Students’ Use of Learning Management Systems at King Abdulaziz University (2018)
Presentation / Conference Contribution
Binyamin, S. S., Rutter, M. J., & Smith, S. (2018, March). The Influence of Computer Self-efficacy and Subjective Norms on the Students’ Use of Learning Management Systems at King Abdulaziz University. Presented at 7th International Conference on Educational and Information Technology 2018, Oxford University, UK

Technology acceptance model (TAM) has been a standout amongst the most well-known models in understanding the users’ acceptance of technologies. This study develops a model to predict the factors that influence the use of learning management systems... Read More about The Influence of Computer Self-efficacy and Subjective Norms on the Students’ Use of Learning Management Systems at King Abdulaziz University.

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.

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.

Selection methods and diversity preservation in many-objective evolutionary algorithms (2018)
Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2018). Selection methods and diversity preservation in many-objective evolutionary algorithms. Data Technologies and Applications, https://doi.org/10.1108/dta-01-2018-0009

Purpose – One of the main components of multi-objective, and therefore, many-objective evolutionary algorithms is the selection mechanism. It is responsible for performing two main tasks simultaneously. First, it has to promote convergence by selecti... Read More about Selection methods and diversity preservation in many-objective evolutionary algorithms.

On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains (2018)
Presentation / Conference Contribution
Stone, C., Hart, E., & Paechter, B. (2018, September). On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains. Presented at Fifteenth International Conference on Parallel Problem Solving from Nature (PPSN XV), Coimbra, Portugal

Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, rely on a set of domain-specific low-level heuristics at lower levels. For some domains, there is a lack of available heuristics, while for novel problems, no heur... Read More about On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains.

Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors (2018)
Journal Article
Lenka, R. K., Rath, A. K., Tan, Z., Sharma, S., Puthal, D., Simha, N. V. R., Prasad, M., Raja, R., & Tripathi, S. S. (2018). Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors. IEEE Access, 6, 30162-30173. https://doi.org/10.1109/ACCESS.2018.2842760

Wireless Sensors are an important component to develop the Internet of Things (IoT) Sensing infrastructure. There are enormous numbers of sensors connected with each other to form a network (well known as wireless sensor networks) to complete IoT Inf... Read More about Building Scalable Cyber-Physical-Social Networking Infrastructure Using IoT and Low Power Sensors.

Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs (2018)
Presentation / Conference Contribution
Stone, C., Hart, E., & Paechter, B. (2018, April). Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs. Presented at 21st International Conference, EvoApplications 2018, Parma, Italy

In many industrial problem domains, when faced with a combinatorial optimisation problem, a “good enough, quick enough” solution to a problem is often required. Simple heuristics often suffice in this case. However, for many domains, a simple heurist... Read More about Automatic Generation of Constructive Heuristics for Multiple Types of Combinatorial Optimisation Problems with Grammatical Evolution and Geometric Graphs.

A Cognitive-IoE Approach to Ambient-intelligent Smart Home (2017)
Presentation / Conference Contribution
Jamnal, G., & Liu, X. (2017, April). A Cognitive-IoE Approach to Ambient-intelligent Smart Home. Presented at 2nd International Conference on Internet of Things, Big Data and Security, Porto, Portugal

In today’s world, we are living in busy metropolitan cities and want our homes to be ambient intelligent enough towards our cognitive requirements for assisted living in smart space environment and an excellent smart home control system should not re... Read More about A Cognitive-IoE Approach to Ambient-intelligent Smart Home.

Utilising natural cross-modal mappings for visual control of feature-based sound synthesis (2017)
Presentation / Conference Contribution
Tsiros, A., & Leplâtre, G. (2017, November). Utilising natural cross-modal mappings for visual control of feature-based sound synthesis. Presented at International Conference on Multimodal Interaction 2017

This paper presents the results of an investigation into audio-visual (AV) correspondences conducted as part of the development of Morpheme, a painting interface to control a corpus-based concatenative sound synthesis algorithm. Previous research has... Read More about Utilising natural cross-modal mappings for visual control of feature-based sound synthesis.

An Optimized Speculative Execution Strategy Based on Local Data Prediction in a Heterogeneous Hadoop Environment (2017)
Presentation / Conference Contribution
Liu, X., & Liu, Q. (2017, July). An Optimized Speculative Execution Strategy Based on Local Data Prediction in a Heterogeneous Hadoop Environment. Presented at 22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), Guangzhou, Guangdong, China

Hadoop is a famous distributed computing framework that is applied to process large-scale data. "Straggling tasks" have a serious impact on Hadoop performance due to imbalance of slow tasks distribution. Speculative execution (SE) presents a way to d... Read More about An Optimized Speculative Execution Strategy Based on Local Data Prediction in a Heterogeneous Hadoop Environment.

Towards self-defending control systems in cybersecurity analysis and measures in industrial automation systems (2017)
Presentation / Conference Contribution
Soufian, M. (2017, June). Towards self-defending control systems in cybersecurity analysis and measures in industrial automation systems. Presented at 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE), Edinburgh, Scotland

Towards self-defending control systems in cybersecurity analysis and measures in industrial automation systems.