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Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World (2022)
Book
Urquhart, N. (2022). Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World. Cham: Springer. https://doi.org/10.1007/978-3-030-98108-2

This book explains classic routing and transportation problems and solutions, before offering insights based on successful real-world solutions. The chapters in Part I introduce and explain the traveling salesperson problem (TSP), vehicle routing pro... Read More about Nature Inspired Optimisation for Delivery Problems: From Theory to the Real World.

CEMA-LSTM: Enhancing Contextual Feature Correlation for Radar Extrapolation Using Fine-Grained Echo Datasets (2022)
Journal Article
Yang, Z., Liu, Q., Wu, H., Liu, X., & Zhang, Y. (in press). CEMA-LSTM: Enhancing Contextual Feature Correlation for Radar Extrapolation Using Fine-Grained Echo Datasets. Computer Modeling in Engineering and Sciences, https://doi.org/10.32604/cmes.2022.022045

Accurate precipitation nowcasting can provide great convenience to the public so they can conduct corresponding arrangements in advance to deal with the possible impact of upcoming heavy rain. Recent relevant research activities have shown their conc... Read More about CEMA-LSTM: Enhancing Contextual Feature Correlation for Radar Extrapolation Using Fine-Grained Echo Datasets.

Near-Data Prediction Based Speculative Optimization in a Distribution Environment (2022)
Journal Article
Liu, Q., Wu, X., Liu, X., Zhang, Y., & Hu, Y. (in press). Near-Data Prediction Based Speculative Optimization in a Distribution Environment. Mobile Networks and Applications, https://doi.org/10.1007/s11036-021-01793-7

Hadoop is an open source from Apache with a distributed file system and MapReduce distributed computing framework. The current Apache 2.0 license agreement supports on-demand payment by consumers for cloud platform services, helping users leverage th... Read More about Near-Data Prediction Based Speculative Optimization in a Distribution Environment.

Modelling the Impact of Individual Preferences on Traffic Policies (2022)
Journal Article
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (in press). Modelling the Impact of Individual Preferences on Traffic Policies. SN Computer Science,

Urban traffic is a system always prone to overload, often approaching breakdown during rush hour times. Well adjusted modifications of traffic policies, with appropriate interventions, promise potential improvements by inducing change in both individ... Read More about Modelling the Impact of Individual Preferences on Traffic Policies.

Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers (2022)
Conference Proceeding
Cardoso, R. P., Hart, E., Burth Kurka, D., & Pitt, J. (2022). Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers. In Applications of Evolutionary Computation: EvoApplications 2022 (418-434). https://doi.org/10.1007/978-3-031-02462-7_27

Using Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using gradient descent to train evolved architectures during the search can be comput... Read More about Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers.

Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn (2022)
Book Chapter
Hart, E. (2022). Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn. In A. E. Smith (Ed.), Women in Computational Intelligence: Key Advances and Perspectives on Emerging Topics (187-203). Cham: Springer. https://doi.org/10.1007/978-3-030-79092-9_9

Standard approaches to developing optimisation algorithms tend to involve selecting an algorithm and tuning it to work well on a large set of problem instances from the domain of interest. Once deployed, the algorithm remains static, failing to impro... Read More about Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn.

An investigation of the role of leadership in consensus decision-making (2022)
Journal Article
Perret, C., & Powers, S. T. (2022). An investigation of the role of leadership in consensus decision-making. Journal of Theoretical Biology, 543, Article 111094. https://doi.org/10.1016/j.jtbi.2022.111094

Leadership is a widespread phenomena in social organisms and it is recognised to facilitate coordination between individuals. While the role of leadership in group foraging or swarm movement is well understood, it is not clear if leaders would also b... Read More about An investigation of the role of leadership in consensus decision-making.

An Intelligent Method for Upper Limb Posture Recognition Based on Limited MEMS Data (2022)
Conference Proceeding
Wu, Z., Wu, X., Liu, Q., & Liu, X. (2022). An Intelligent Method for Upper Limb Posture Recognition Based on Limited MEMS Data. In 2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00082

There are more than 10 million new stroke cases worldwide every year, and stroke has become one of the main causes of death and disability. In recent years, with the rapid development of computer science and technology, through the combination of Int... Read More about An Intelligent Method for Upper Limb Posture Recognition Based on Limited MEMS Data.

Improving Domestic NILM Using An Attention- Enabled Seq2Point Learning Approach (2022)
Conference Proceeding
Zhang, J., Sun, J., Gan, J., Liu, Q., & Liu, X. (2022). Improving Domestic NILM Using An Attention- Enabled Seq2Point Learning Approach. In 2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00079

The past decade have seen a growth in Internet technology, the overlap of cyberspace and social space provides great convenience for people's life. The in-depth study of non-intrusive load management (NILM) promotes the development of multi-integrati... Read More about Improving Domestic NILM Using An Attention- Enabled Seq2Point Learning Approach.

Four levers of reciprocity across human societies: concepts, analysis and predictions (2022)
Journal Article
Lehmann, L., Powers, S. T., & van Schaik, C. P. (2022). Four levers of reciprocity across human societies: concepts, analysis and predictions. Evolutionary Human Sciences, 4, https://doi.org/10.1017/ehs.2022.7

This paper surveys five human societal types – mobile foragers, horticulturalists, pre-state agriculturalists, state-based agriculturalists and liberal democracies – from the perspective of three core social problems faced by interacting individuals:... Read More about Four levers of reciprocity across human societies: concepts, analysis and predictions.

Collimated Whole Volume Light Scattering in Homogeneous Finite Media (2022)
Journal Article
Velinov, Z., & Mitchell, K. (in press). Collimated Whole Volume Light Scattering in Homogeneous Finite Media. IEEE Transactions on Visualization and Computer Graphics, https://doi.org/10.1109/TVCG.2021.3135764

Crepuscular rays form when light encounters an optically thick or opaque medium which masks out portions of the visible scene. Real-time applications commonly estimate this phenomena by connecting paths between light sources and the camera after a si... Read More about Collimated Whole Volume Light Scattering in Homogeneous Finite Media.

Morpho-evolution with learning using a controller archive as an inheritance mechanism (2022)
Journal Article
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., …Tyrrell, A. M. (in press). Morpho-evolution with learning using a controller archive as an inheritance mechanism. IEEE Transactions on Cognitive and Developmental Systems, https://doi.org/10.1109/tcds.2022.3148543

Most work in evolutionary robotics centres on evolving a controller for a fixed body-plan. However, previous studiessuggest that simultaneously evolving both controller and body-plan could open up many interesting possibilities. However... Read More about Morpho-evolution with learning using a controller archive as an inheritance mechanism.

Using Semantic Technology to Model Persona for Adaptable Agents (2021)
Conference Proceeding
Nguyen, J., Farrenkopf, T., Guckert, M., Powers, S., & Urquhart, N. (2021). Using Semantic Technology to Model Persona for Adaptable Agents. In ECMS 2021, 35th Proceedings (172-178). https://doi.org/10.7148/2021

In state of the art research a growing interest in the application of agent models for the simulation of road traffic can be observed. Software agents are particularly suitable for the representation of travellers and their goal-oriented behaviour. A... Read More about Using Semantic Technology to Model Persona for Adaptable Agents.

Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks (2021)
Journal Article
Liu, Q., Zhang, J., Liu, X., Zhang, Y., Xu, X., Khosravi, M., & Bilal, M. (2022). Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks. Physical Communication, 51, https://doi.org/10.1016/j.phycom.2021.101584

The intensification of the greenhouse effect is driving the implementation of energy saving and emission reduction policies, which lead to a wide variety of energy saving solutions benefiting from the advancement of emerging technologies such as Wire... Read More about Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks.

An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars (2021)
Journal Article
Wu, H., Liu, Q., Liu, X., Zhang, Y., & Yang, Z. (in press). An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars. World Wide Web, https://doi.org/10.1007/s11280-021-00988-y

Internet of Things (IoT) has been rapidly developed in recent years, being well applied in the fields of Environmental Surveillance, Smart Grid, Intelligent Transportation, and so on. As one of the typical earth-based meteorological observation metho... Read More about An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars.

Developing Visualisations to Enhance an Insider Threat Product: A Case Study (2021)
Conference Proceeding
Graham, M., Kukla, R., Mandrychenko, O., Hart, D., & Kennedy, J. (2021). Developing Visualisations to Enhance an Insider Threat Product: A Case Study. In 2021 IEEE Symposium on Visualization for Cyber Security (VizSec) (47-57). https://doi.org/10.1109/VizSec53666.2021.00011

This paper describes the process of developing data visualisations to enhance a commercial software platform for combating insider threat, whose existing UI, while perfectly functional, was limited in its ability to allow analysts to easily spot the... Read More about Developing Visualisations to Enhance an Insider Threat Product: A Case Study.

Developing Visualisations to Enhance an Insider Threat Product: A Case Study (2021)
Presentation / Conference
Graham, M. (2021, October). Developing Visualisations to Enhance an Insider Threat Product: A Case Study. Presented at 18th IEEE Symposium on Visualization for Cyber Security, New Orleans, USA [Online]

This paper describes the process of developing data visualisations to enhance a commercial software platform for combating insider threat, whose existing UI, while perfectly functional, was limited in its ability to allow analysts to easily spot the... Read More about Developing Visualisations to Enhance an Insider Threat Product: A Case Study.

Architecting Green Mobile Cloud Apps (2021)
Book Chapter
Jaachimma Chinenyeze, S., & Liu, X. (2021). Architecting Green Mobile Cloud Apps. In C. Calero, M. Á. Moraga, & M. Piattini (Eds.), Software Sustainability (183-214). Cham: Springer. https://doi.org/10.1007/978-3-030-69970-3_8

With the resource-constrained nature of mobile devices, and the resource-abundant offerings of the cloud, several promising optimization techniques have been proposed by the green computing research community. Prominent techniques and unique methods... Read More about Architecting Green Mobile Cloud Apps.