Outputs (3461)

Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture (2024)
Presentation / Conference Contribution
Le Goff, L., & Hart, E. (2024, July). Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture. Presented at GECCO 2024 Embodied and Evolved Artificial Intelligence Workshop, Melbourne, Australia

Algorithmic frameworks for the joint optimisation of a robot's design and controller often utilise a learning loop nested within an evolutionary algorithm to refine the controller associated with a newly generated robot design. Intuitively, it is rea... Read More about Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture.

Neurosymbolic Learning in the XAI Framework for Enhanced Cyberattack Detection with Expert Knowledge Integration (2024)
Presentation / Conference Contribution
Kalutharage, C. S., Liu, X., Chrysoulas, C., & Bamgboye, O. (2024, June). Neurosymbolic Learning in the XAI Framework for Enhanced Cyberattack Detection with Expert Knowledge Integration. Presented at The 39th International Conference on ICT Systems Security and Privacy Protection (SEC 2024), Edinburgh

The perpetual evolution of cyberattacks, especially in the realm of Internet of Things (IoT) networks, necessitates advanced, adaptive, and intelligent defence mechanisms. The integration of expert knowledge can drastically enhance the efficacy of Io... Read More about Neurosymbolic Learning in the XAI Framework for Enhanced Cyberattack Detection with Expert Knowledge Integration.

Investigating Markers and Drivers of Gender Bias in Machine Translations (2024)
Presentation / Conference Contribution
Barclay, P., & Sami, A. (2024, March). Investigating Markers and Drivers of Gender Bias in Machine Translations. Presented at IEEE International Conference on Software Analysis, Evolution and Reengineering, Rovaniemi, Finland

Implicit gender bias in Large Language Models (LLMs) is a well-documented problem, and implications of gender introduced into automatic translations can perpetuate real-world biases. However, some LLMs use heuristics or post-processing to mask such b... Read More about Investigating Markers and Drivers of Gender Bias in Machine Translations.

Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution (2024)
Presentation / Conference Contribution
Marrero, A., Segredo, E., León, C., & Hart, E. (2024, July). Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. Presented at GECCO '24: Genetic and Evolutionary Computation Conference, Melbourne, Australia

The ability to generate example instances from a domain is important in order to benchmark algorithms and to generate data that covers an instance-space in order to train machine-learning models for algorithm selection. Quality-Diversity (QD) algorit... Read More about Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution.

Virtual Rehabilitation: XR Design for Senior Users in Immersive Exergame Environments (2024)
Presentation / Conference Contribution
Charisis, V., Khan, S., AlTarteer, S., & Lagoo, R. (2024, June). Virtual Rehabilitation: XR Design for Senior Users in Immersive Exergame Environments. Presented at 2024 IEEE Gaming, Entertainment, and Media Conference (GEM), Turin, Italy

The global ageing population presents significant challenges, with healthcare systems strained to meet the needs of an increasingly elderly demographic. Societies face issues related to healthcare costs, caregiving, and maintaining quality of life fo... Read More about Virtual Rehabilitation: XR Design for Senior Users in Immersive Exergame Environments.

Participatory Design with Domain Experts: A Delphi Study for a Career Support Chatbot (2024)
Presentation / Conference Contribution
Wilson, M., Brazier, D., Gkatzia, D., & Robertson, P. (2024, July). Participatory Design with Domain Experts: A Delphi Study for a Career Support Chatbot. Presented at ACM Conversational User Interfaces 2024 (CUI ’24), Luxembourg, Luxembourg

We present a study of collaboration with expert participants for the purpose of the responsible design of a conversational agent. The Delphi study was used to identify and develop design and evaluation criteria for an automated career support interve... Read More about Participatory Design with Domain Experts: A Delphi Study for a Career Support Chatbot.

A Novel Autonomous Adaptive Frame Size for Time-Slotted LoRa MAC Protocol (2024)
Journal Article
Alahmadi, H., Bouabdallah, F., Al-Dubai, A., & Ghaleb, B. (2024). A Novel Autonomous Adaptive Frame Size for Time-Slotted LoRa MAC Protocol. IEEE Transactions on Industrial Informatics, 20(10), 12284-12293. https://doi.org/10.1109/tii.2024.3417308

LoRa networks represent a promising technology for IoT applications due to their long range, low cost, and energy efficiency. However, their ALOHA-based access method and duty cycle restrictions can limit their scalability and reliability in high-den... Read More about A Novel Autonomous Adaptive Frame Size for Time-Slotted LoRa MAC Protocol.

Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization (2024)
Journal Article
Zeng, L., Liu, Q., Shen, S., & Liu, X. (2024). Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization. Tsinghua Science and Technology, 29(3), 806 - 817. https://doi.org/10.26599/TST.2023.9010058

Edge computing nodes undertake more and more tasks as business density grows. How to efficiently allocate large-scale and dynamic workloads to edge computing resources has become a critical challenge. An edge task scheduling approach based on an impr... Read More about Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization.

AI Literacy Framework for Marketing Education and Assessment Design. (2024)
Presentation / Conference Contribution
Kurtzke, S. (2024, June). AI Literacy Framework for Marketing Education and Assessment Design. Presented at Marketing Professional Advisory Group Meeting, Edinburgh Napier University, UK

This talk aims to collect feedback from marketing practitioners on an evidence-based AI Literacy Framework that shows how higher-order human and applied AI skills can be embedded in marketing curricula and through assessment. It sets out debates on A... Read More about AI Literacy Framework for Marketing Education and Assessment Design..

Employability attributes: Meeting deadlines, time management (2024)
Presentation / Conference Contribution
Cameron, J., Gutu, M., & Kurtzke, S. (2024, June). Employability attributes: Meeting deadlines, time management. Presented at Marketing Professional Advisory Group Meeting, Edinburgh Napier University, UK

This talk aims to excavate marketing practitioner insights on whether meeting deadlines and time management are important graduate attributes that should be carefully considered in an employability-focused curriculum. The presentation sets out debat... Read More about Employability attributes: Meeting deadlines, time management.

Efficient building retrofitting towards carbon-neutral built environment in developing economies: A scoping review (2024)
Presentation / Conference Contribution
Ejidike, C. C., Mewomo, M. C., Agbajor, F. D., Olawumi, T. O., & Luo, J. (2024, June). Efficient building retrofitting towards carbon-neutral built environment in developing economies: A scoping review. Presented at 1st International Conference on Net-Zero Built Environment, Oslo, Norway

The construction industry is widely recognized for its high energy consumption and carbon emissions in the built environment. This recognition is attributable to the underperformance of existing buildings within the built environment. Retrofitting bu... Read More about Efficient building retrofitting towards carbon-neutral built environment in developing economies: A scoping review.

Integrating AI Literacy in Higher Education: A Practical Framework (2024)
Presentation / Conference Contribution
Kurtzke, S. (2024, June). Integrating AI Literacy in Higher Education: A Practical Framework. Poster presented at The Gathering: Edinburgh Napier's Learning & Teaching Conference, Edinburgh, UK

This project is a rapid response to the UK Russell Group's 2023 first principle on the use of generative AI (GAI) tools to "support student and staff to become AI literate" (Russell Group, 2023, p. 1). The author, a lecturer in marketing, developed a... Read More about Integrating AI Literacy in Higher Education: A Practical Framework.

Persistency and stability of a class of nonlinear forced positive discrete-time systems with delays (2024)
Journal Article
Franco, D., Guiver, C., Logemann, H., & Perán, J. (2024). Persistency and stability of a class of nonlinear forced positive discrete-time systems with delays. Physica D: Nonlinear Phenomena, 467, Article 134260. https://doi.org/10.1016/j.physd.2024.134260

Persistence, excitability and stability properties are considered for a class of nonlinear, forced, positive discrete-time systems with delays. As will be illustrated, these equations arise in a number of biological and ecological contexts. Novel suf... Read More about Persistency and stability of a class of nonlinear forced positive discrete-time systems with delays.

PEMS: People Experience of Mountain Soundscapes (2024)
Presentation / Conference Contribution
Di Donato, B., & McGregor, I. (2024, June). PEMS: People Experience of Mountain Soundscapes. Paper presented at Forum Alpinum 2024, Kranjska Gora, Slovenia

This research delves into the intricate relationship between mountain auditory environments and the mountaineering experience, shedding light on the influence of individual sounds and overall soundscapes. While existing studies acknowledge the positi... Read More about PEMS: People Experience of Mountain Soundscapes.

Fandom as method: Decolonising research on social media communications through Chinese transnational fandoms of a Japanese Olympic figure skater (2024)
Journal Article
Chen, Z. T., Cameron, J., & Liu, N. X. (2024). Fandom as method: Decolonising research on social media communications through Chinese transnational fandoms of a Japanese Olympic figure skater. Journal of Current Chinese Affairs, 53(3), 402 - 427. https://doi.org/10.1177/18681026241255134

This paper focuses on international sports personality in figure staking Yuzuru Hanyu, who plays for Japan, and his transnational fandoms in China, to examine the politicisation of his evolving fandom during and after his performance at the 2022 Beij... Read More about Fandom as method: Decolonising research on social media communications through Chinese transnational fandoms of a Japanese Olympic figure skater.

Being in Two Places at the Same Time: a Future for Hybrid Learning Based on Student Preferences (2024)
Journal Article
Fabian, K., Smith, S., & Taylor-Smith, E. (2024). Being in Two Places at the Same Time: a Future for Hybrid Learning Based on Student Preferences. TechTrends, 68(4), 693-704. https://doi.org/10.1007/s11528-024-00974-x

The Covid-19 pandemic moved focus from face-to-face learning to hybrid in Higher Education; many educators did not have previous experience of this mode prior to this shift in learning locations. One form of hybrid learning is “synchronous hybrid lea... Read More about Being in Two Places at the Same Time: a Future for Hybrid Learning Based on Student Preferences.

Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System (2024)
Journal Article
Cheng, H., Tan, Z., Zhang, X., & Liu, Y. (online). Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System. Chinese Journal of Electronics, https://doi.org/10.23919/cje.2023.00.012

Aiming at the problems of the communication inefficiency and high energy consumption in vehicular networks, the platoon service recommendation systems (PSRS) are presented. Many schemes for evaluating the reputation of platoon head vehicles have been... Read More about Reliable and Fair Trustworthiness Evaluation Protocol for Platoon Service Recommendation System.

Operator-valued multiplier theorems for causal translation-invariant operators with applications to control theoretic input-output stability (2024)
Journal Article
Guiver, C., Logemann, H., & Opmeer, M. R. (2024). Operator-valued multiplier theorems for causal translation-invariant operators with applications to control theoretic input-output stability. Mathematics of Control, Signals, and Systems, 36(4), 729-773. https://doi.org/10.1007/s00498-024-00387-4

We prove an operator-valued Laplace multiplier theorem for causal translation-invariant linear operators which provides a characterization of continuity from Hα(R, U) to Hβ(R, U) (fractional U-valued Sobolev spaces, U a complex Hilbert space) in term... Read More about Operator-valued multiplier theorems for causal translation-invariant operators with applications to control theoretic input-output stability.

The energy-balance method for optimal control in renewable energy applications (2024)
Journal Article
Guiver, C., & Opmeer, M. R. (2024). The energy-balance method for optimal control in renewable energy applications. Renewable Energy Focus, 50, Article 100582. https://doi.org/10.1016/j.ref.2024.100582

A theoretical method is presented, called the energy-balance method, for maximising the energy extracted from a renewable energy converter in terms of determination of an optimal control. The method applies to control systems specified by linear grap... Read More about The energy-balance method for optimal control in renewable energy applications.

DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences (2024)
Presentation / Conference Contribution
Koniaris, B., Sinclair, D., & Mitchell, K. (2024, March). DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences. Presented at IEEE VR Workshop on Open Access Tools and Libraries for Virtual Reality, Orlando, FL

DanceMark is an open telemetry framework designed for latency-sensitive real-time networked immersive experiences, focusing on online dancing in virtual reality within the DanceGraph platform. The goal is to minimize end-to-end latency and enhance us... Read More about DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences.