Outputs (4095)

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..

A Study on the Effect of Feature Selection on Malware Analysis using Machine Learning (2019)
Presentation / Conference Contribution
Babaagba, K. O., & Adesanya, S. O. (2019, March). A Study on the Effect of Feature Selection on Malware Analysis using Machine Learning. Presented at ICEIT 2019: 2019 8th International Conference on Educational and Information Technology, Cambridge, UK

In this paper, the effect of feature selection in malware detection using machine learning techniques is studied. We employ supervised and unsupervised machine learning algorithms with and without feature selection. These include both classification... Read More about A Study on the Effect of Feature Selection on Malware Analysis using Machine Learning.

The Moderating Effect of Education and Experience on Students’ Use of Learning Management Systems in Saudi Higher Education (2019)
Presentation / Conference Contribution
Binyamin, S., Rutter, M. J., & Smith, S. (2019, March). The Moderating Effect of Education and Experience on Students’ Use of Learning Management Systems in Saudi Higher Education. Presented at 8th International Conference on Educational and Information Technology, Cambridge, UK

Based on the technology acceptance model, this research investigated the variables that affect students’ use of LMS in Saudi public universities. The study also examined the moderating impact of education and experience on the students’ behavior towa... Read More about The Moderating Effect of Education and Experience on Students’ Use of Learning Management Systems in Saudi Higher Education.

Weakly Supervised Segmentation of SAR Imagery Using Superpixel and Hierarchically Adversarial CRF (2019)
Journal Article
Ma, F., Gao, F., Sun, J., Zhou, H., & Hussain, A. (2019). Weakly Supervised Segmentation of SAR Imagery Using Superpixel and Hierarchically Adversarial CRF. Remote Sensing, 11(5), Article 512. https://doi.org/10.3390/rs11050512

Synthetic aperture radar (SAR) image segmentation aims at generating homogeneous regions from a pixel-based image and is the basis of image interpretation. However, most of the existing segmentation methods usually neglect the appearance and spatial... Read More about Weakly Supervised Segmentation of SAR Imagery Using Superpixel and Hierarchically Adversarial CRF.

An investigation into Scottish teenagers’ information literacy and search skills (2019)
Presentation / Conference Contribution
Brazier, D., Walton, G., & Harvey, M. (2018, October). An investigation into Scottish teenagers’ information literacy and search skills. Presented at ISIC: The Information Behaviour Conference 2018, Krakow, Poland

Introduction. This paper presents the results of a study investigating the information literacy and search skills of young people in Scotland.
Method. The participants, secondary school pupils between the ages of 13 and 14 (n=57), completed two out... Read More about An investigation into Scottish teenagers’ information literacy and search skills.

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.

A new security approach for the spectrum access in vehicular networks (2019)
Presentation / Conference Contribution
Alsarhan, A., Al-Dubai, A., Kilani, Y., & Alkhalidy, M. (2019, February). A new security approach for the spectrum access in vehicular networks. Presented at ICDS 2019 : The Thirteenth International Conference on Digital Society and eGovernments, Athens, Greece

Vehicular ad hoc networks (VANETs) have been instrumental in intelligent transportation systems that enhances road safety and road management significantly. This technology enables communication among vehicles where drivers can share road information... Read More about A new security approach for the spectrum access in vehicular networks.

Athos - A Model Driven Approach to Describe and Solve Optimisation Problems (2019)
Presentation / Conference Contribution
Hoffman, B., Chalmers, K., Urquhart, N., & Guckert, M. (2019, February). Athos - A Model Driven Approach to Describe and Solve Optimisation Problems. Presented at RWDSL'19: 4th ACM International Workshop on Real World Domain Specific Languages, Washington DC

Implementing solutions for optimisation problems with general purpose high-level programming languages is a time consuming task that can only be carried out by professional software developers who typically are not domain experts. We address this pro... Read More about Athos - A Model Driven Approach to Describe and Solve Optimisation Problems.

A Novel Two-Stage Deep Learning Model for Efficient Network Intrusion Detection (2019)
Journal Article
Khan, F. A., Gumaei, A., Derhab, A., & Hussain, A. (2019). A Novel Two-Stage Deep Learning Model for Efficient Network Intrusion Detection. IEEE Access, 7, 30373-30385. https://doi.org/10.1109/access.2019.2899721

The network intrusion detection system is an important tool for protecting computer networks against threats and malicious attacks. Many techniques have recently been proposed; however, these techniques face significant challenges due to the continuo... Read More about A Novel Two-Stage Deep Learning Model for Efficient Network Intrusion Detection.