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QoE-based Mobility-aware Collaborative Video Streaming on the Edge of 5G (2020)
Journal Article
Tuysuz, M. F., & Aydin, M. E. (in press). QoE-based Mobility-aware Collaborative Video Streaming on the Edge of 5G. IEEE Transactions on Industrial Informatics, 1-1. https://doi.org/10.1109/tii.2020.2972931

Today's Internet traffic is dominated by video streaming applications transmitted through wireless/cellular interfaces of mobile devices. Although ultra-high-definition videos are now easily transmitted through mobile devices, video quality level tha... Read More about QoE-based Mobility-aware Collaborative Video Streaming on the Edge of 5G.

Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods (2020)
Journal Article
Caleb-Solly, P., Gupta, P., & McClatchey, R. (2020). Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods. Neural Computing and Applications, https://doi.org/10.1007/s00521-020-04737-6

© 2020, The Author(s). This paper investigates the utility of unsupervised machine learning and data visualisation for tracking changes in user activity over time. This is done through analysing unlabelled data generated from passive and ambient smar... Read More about Tracking changes in user activity from unlabelled smart home sensor data using unsupervised learning methods.

A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation (2019)
Journal Article
Polatidis, N., Pimenidis, E., Fish, A., & Kapetanakis, S. (2019). A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation. International Journal on Artificial Intelligence Tools, 28(8), https://doi.org/10.1142/S021821301960011X

Recommender systems’ evaluation is usually based on predictive accuracy and information retrieval metrics, with better scores meaning recommendations are of higher quality. However, new algorithms are constantly developed and the comparison of result... Read More about A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation.

A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation (2019)
Journal Article
Polatidis, N., Pimenidis, E., Fish, A., & Kapetanakis, S. (2019). A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation. International Journal on Artificial Intelligence Tools, 28(8), https://doi.org/10.1142/S021821301960011X

Recommender systems’ evaluation is usually based on predictive accuracy and information retrieval metrics, with better scores meaning recommendations are of higher quality. However, new algorithms are constantly developed and the comparison of result... Read More about A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation.

An analytical framework for high-speed hardware particle swarm optimization (2019)
Journal Article
Damaj, I., Elshafei, M., El-Abd, M., & Aydin, M. E. (2020). An analytical framework for high-speed hardware particle swarm optimization. Microprocessors and Microsystems, 72, 102949. https://doi.org/10.1016/j.micpro.2019.102949

Engineering optimization techniques are computationally intensive and can challenge implementations on tightly-constrained embedded systems. Particle Swarm Optimization (PSO) is a well-known bio-inspired algorithm that is adopted in various applicati... Read More about An analytical framework for high-speed hardware particle swarm optimization.

Spatial-temporal data-driven service recommendation with privacy-preservation (2019)
Journal Article
Zhang, X., Qi, L., Li, S., Wan, S., Wen, Y., & Gong, W. (2020). Spatial-temporal data-driven service recommendation with privacy-preservation. Information Sciences, 515, 91-102. https://doi.org/10.1016/j.ins.2019.11.021

© 2019 Elsevier Inc. The ever-increasing popularity of web service sharing communities have produced a considerable amount of web services that share similar functionalities but vary in Quality of Services (QoS) performances. To alleviate the heavy s... Read More about Spatial-temporal data-driven service recommendation with privacy-preservation.

A Quantum Algorithm for Ray Casting using an Orthographic Camera (2019)
Conference Proceeding
Alves, C., Santos, L. P., & Bashford-Rogers, T. (2019). A Quantum Algorithm for Ray Casting using an Orthographic Camera

Quantum computing has the potential to provide solutions to many problems which are challenging or out of reach of classical computers. There are several problems in rendering which are amenable to being solved in quantum computers, but these have ye... Read More about A Quantum Algorithm for Ray Casting using an Orthographic Camera.

Contactless sensing of liquid marbles for detection, characterisation & computing (2019)
Journal Article
Draper, T. C., Phillips, N., Weerasekera, R., Mayne, R., Fullarton, C., de Lacy Costello, B., & Adamatzky, A. (2020). Contactless sensing of liquid marbles for detection, characterisation & computing. Lab on a Chip, 20(1), 136-146. https://doi.org/10.1039/c9lc01001g

Liquid marbles (LMs) are of growing interest in many fields, including microfluidics, microreactors, sensors, and signal carriers. The generation of LMs is generally performed manually, although there has recently been a burst of publications involvi... Read More about Contactless sensing of liquid marbles for detection, characterisation & computing.

Blockchain and edge computing–based architecture for participatory smart city applications (2019)
Journal Article
Khan, Z., Abbasi, A. G., & Pervez, Z. (in press). Blockchain and edge computing–based architecture for participatory smart city applications. Concurrency and Computation: Practice and Experience, https://doi.org/10.1002/cpe.5566

© 2019 John Wiley & Sons, Ltd. Smart cities aim to provide smart governance with the emphasis on gaining high transparency and trust in public services and enabling citizen participation in decision making processes. This means on the one hand data... Read More about Blockchain and edge computing–based architecture for participatory smart city applications.

WASOS: An Ontology for Modelling Traditional Knowledge of Sustainable Water Stewardship (2019)
Presentation / Conference
Vlachidis, A., & Everard, M. (2019, October). WASOS: An Ontology for Modelling Traditional Knowledge of Sustainable Water Stewardship. Paper presented at MTSR 2019 - Metadata and Semantics Research Conference

Recent work and publications concerning sustainable water stewardship in Raja-sthan (India) highlight how contemporary challenges are eroding traditional, communal approaches to water stewardship through mechanised extraction be-yond the renewable ca... Read More about WASOS: An Ontology for Modelling Traditional Knowledge of Sustainable Water Stewardship.

Threats on the horizon: Understanding security threats in the era of cyber-physical systems (2019)
Journal Article
Walker-Roberts, S., Hammoudeh, M., Aldabbas, O., Aydin, M., & Dehghantanha, A. (in press). Threats on the horizon: Understanding security threats in the era of cyber-physical systems. Journal of Supercomputing, https://doi.org/10.1007/s11227-019-03028-9

Disruptive innovations of the last few decades, such as smart cities and Industry 4.0, were made possible by higher integration of physical and digital elements. In today's pervasive cyber-physical systems, connecting more devices introduces new vuln... Read More about Threats on the horizon: Understanding security threats in the era of cyber-physical systems.

Tamil Talk: What you speak is what you get! (2019)
Presentation / Conference
Ogunshile, E., & Ramachandran, R. (2019, October). Tamil Talk: What you speak is what you get!. Paper presented at CONISOFT 2019 : IEEE 7th International Conference on Software Engineering Research and Innovation

Tamil is one of the longest surviving classical languages in the world. Speech to text in Tamil would benefit to a lot of native Tamil speakers throughout the world. There are many speech recognition and speech to text applications available for a... Read More about Tamil Talk: What you speak is what you get!.

Anomaly detection using pattern-of-life visual metaphors (2019)
Journal Article
Happa, J., Bashford-Rogers, T., Agrafiotis, I., Goldsmith, M., & Creese, S. (2019). Anomaly detection using pattern-of-life visual metaphors. IEEE Access, 7, 154018-154034. https://doi.org/10.1109/ACCESS.2019.2948490

Complex dependencies exist across the technology estate, users and purposes of machines. This can make it difficult to efficiently detect attacks. Visualization to date is mainly used to communicate patterns of raw logs, or to visualize the output of... Read More about Anomaly detection using pattern-of-life visual metaphors.

A honeybees-inspired heuristic algorithm for numerical optimisation (2019)
Journal Article
Dugenci, M., & Aydin, M. E. (2019). A honeybees-inspired heuristic algorithm for numerical optimisation. Neural Computing and Applications, https://doi.org/10.1007/s00521-019-04533-x

© 2019, The Author(s). Swarm intelligence is all about developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributors so that a c... Read More about A honeybees-inspired heuristic algorithm for numerical optimisation.

A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers (2019)
Journal Article
Ghinea, G., Comşa, I. S., Comsa, I., Zhang, S., Aydin, M., Kuonen, P., …Ghinea, G. (2019). A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers. Information, 10(10), 315. https://doi.org/10.3390/info10100315

Due to large-scale control problems in 5G access networks, the complexity of radio resource management is expected to increase significantly. Reinforcement learning is seen as a promising solution that can enable intelligent decision-making and reduc... Read More about A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers.