All Outputs (4470)

Automated Human-Readable Label Generation in Open Intent Discovery (2024)
Presentation / Conference Contribution
Anderson, G., Hart, E., Gkatzia, D., & Beaver, I. (2024, September). Automated Human-Readable Label Generation in Open Intent Discovery. Presented at Interspeech 2024, Kos, Greece

The correct determination of user intent is key in dialog systems. However, an intent classifier often requires a large, labelled training dataset to identify a set of known intents. The creation of such a dataset is a complex and time-consuming task... Read More about Automated Human-Readable Label Generation in Open Intent Discovery.

Integrating Reality: A Hybrid SDN Testbed for Enhanced Realism in Edge Computing Simulations (2024)
Presentation / Conference Contribution
Almaini, A., Koßmann, T., Folz, J., Schramm, M., Heigl, M., & Al-Dubai, A. (2024, June). Integrating Reality: A Hybrid SDN Testbed for Enhanced Realism in Edge Computing Simulations. Presented at UNet24: The International Conference on Ubiquitous Networking, Marrakesh, Morocco

Recent advancements in Software-Defined Networking (SDN) have facilitated its deployment across diverse network types, including edge networks. Given the broad applicability of SDN and the complexity of large-scale environments, establishing a compre... Read More about Integrating Reality: A Hybrid SDN Testbed for Enhanced Realism in Edge Computing Simulations.

A Deep Dive into Effects of Structural Bias on CMA-ES Performance along Affine Trajectories (2024)
Presentation / Conference Contribution
van Stein, N., Thomson, S. L., & Kononova, A. V. (2024, September). A Deep Dive into Effects of Structural Bias on CMA-ES Performance along Affine Trajectories. Paper presented at Parallel Problem Solving from Nature (PPSN) 2024, Hagenberg, Austria

To guide the design of better iterative optimisation heuristics, it is imperative to understand how inherent structural biases within algorithm components affect the performance on a wide variety of search landscapes. This study explores the impact o... Read More about A Deep Dive into Effects of Structural Bias on CMA-ES Performance along Affine Trajectories.

Entropy, Search Trajectories, and Explainability for Frequency Fitness Assignment (2024)
Presentation / Conference Contribution
Thomson, S. L., Ochoa, G., van den Berg, D., Liang, T., & Weise, T. (2024, September). Entropy, Search Trajectories, and Explainability for Frequency Fitness Assignment. Presented at Parallel Problem Solving from Nature (PPSN 2024), Hagenberg, Austria

Local optima are a menace that can trap optimisation processes. Frequency fitness assignment (FFA) is an concept aiming to overcome this problem. It steers the search towards solutions with rare fitness instead of high-quality fitness. FFA-based algo... Read More about Entropy, Search Trajectories, and Explainability for Frequency Fitness Assignment.

Compression strength perpendicular to grain in hardwoods depending on test method (2024)
Presentation / Conference Contribution
Cramer, M. (2024, May). Compression strength perpendicular to grain in hardwoods depending on test method. Presented at 11th Hardwood Conference, Sopron, Hungary

Compression strength perpendicular to grain is an important timber property that governs the bearing strength of beams and might influence connection design. According to modern standards, the design value for compression strength is determined accor... Read More about Compression strength perpendicular to grain in hardwoods depending on test method.

Assessing the Performance of Ethereum and Hyperledger Fabric Under DDoS Attacks for Cyber-Physical Systems (2024)
Presentation / Conference Contribution
Jayadev, V., Moradpoor, N., & Petrovski, A. (2024, July). Assessing the Performance of Ethereum and Hyperledger Fabric Under DDoS Attacks for Cyber-Physical Systems. Paper presented at 19th International Conference on Availability, Reliability and Security (ARES 2024), Vienna, Austria

Blockchain technology offers a decentralized and secure platform for addressing various challenges in smart cities and cyber-physical systems, including identity management, trust and transparency, and supply chain management. However, blockchains ar... Read More about Assessing the Performance of Ethereum and Hyperledger Fabric Under DDoS Attacks for Cyber-Physical Systems.

Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances (2024)
Presentation / Conference Contribution
Hart, E., Sim, K., & Renau, Q. (2024, September). Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances. Presented at 18th International Conference on Parallel Problem Solving From Nature PPSN 2024, Hagenburg, Austria

Deep neural networks (DNN) are increasingly being used to perform algorithm-selection in combinatorial optimisation domains, particularly as they accommodate input representations which avoid designing and calculating features. Mounting evidence fro... Read More about Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances.

MoodFlow: Orchestrating Conversations with Emotionally Intelligent Avatars in Mixed Reality (2024)
Presentation / Conference Contribution
Casas, L., Hannah, S., & Mitchell, K. (2024, March). MoodFlow: Orchestrating Conversations with Emotionally Intelligent Avatars in Mixed Reality. Presented at ANIVAE 2024 : 7th IEEE VR Internal Workshop on Animation in Virtual and Augmented Environments, Orlando, Florida

MoodFlow presents a novel approach at the intersection of mixed reality and conversational artificial intelligence for emotionally intelligent avatars. Through a state machine embedded in user prompts, the system decodes emotional nuances, enabling a... Read More about MoodFlow: Orchestrating Conversations with Emotionally Intelligent Avatars in Mixed Reality.

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.

A method for constrained energy-maximising control of heaving wave-energy converters via a nonlinear frequency response (2024)
Presentation / Conference Contribution
Guiver, C. (2024, August). A method for constrained energy-maximising control of heaving wave-energy converters via a nonlinear frequency response. Presented at The 8th IEEE Conference on Control Technology and Applications (CCTA) 2024, Newcastle Upon Tyne

A theoretical grounding is presented for justifying how frequency domain methods may be applied in the determination of constrained extracted-energy maximising controls in wave-energy conversion applications subject to nonlinear models. A computation... Read More about A method for constrained energy-maximising control of heaving wave-energy converters via a nonlinear frequency response.

Reproducing Human Evaluation of Meaning Preservation in Paraphrase Generation (2024)
Presentation / Conference Contribution
Watson, L. N., & Gkatzia, D. (2024, May). Reproducing Human Evaluation of Meaning Preservation in Paraphrase Generation. Presented at HumEval2024 at LREC-COLING 2024, Turin, Italy

Reproducibility is a cornerstone of scientific research, ensuring the reliability and generalisability of findings. The ReproNLP Shared Task on Reproducibility of Evaluations in NLP aims to assess the reproducibility of human evaluation studies. This... Read More about Reproducing Human Evaluation of Meaning Preservation in Paraphrase Generation.

Proximity-Driven, Load-Balancing Task Offloading Algorithm for Enhanced Performance in Satellite-Enabled Mist Computing (2024)
Presentation / Conference Contribution
Babaghayou, M., Chaib, N., Maglaras, L., Yigit, Y., Ferrag, M. A., & Marsh, C. (2023, December). Proximity-Driven, Load-Balancing Task Offloading Algorithm for Enhanced Performance in Satellite-Enabled Mist Computing. Presented at 16th EAI International Conference, WiCON 2023, Athens, Greece

In an era of rapidly evolving mobile computing, integrating satellite technologies with the Internet of Things (IoT) creates new communication and data management horizons. Our research focuses on the emerging challenge of efficiently managing heavy... Read More about Proximity-Driven, Load-Balancing Task Offloading Algorithm for Enhanced Performance in Satellite-Enabled Mist Computing.

Beyond the Screen: Exploring Students' Views on Social Media's Impact in Education (2024)
Presentation / Conference Contribution
Demeke, W. (2024, March). Beyond the Screen: Exploring Students' Views on Social Media's Impact in Education. Presented at 12nd World Conference on Information Systems and Technologies, Lodz, Poland

This study delved into the intricate relationship between social media usage and academic outcomes among university students from diverse fields: en-gineering and art studies, health and social care studies, and business studies. The study employed a... Read More about Beyond the Screen: Exploring Students' Views on Social Media's Impact in Education.

Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments (2024)
Presentation / Conference Contribution
Casas, L., Mitchell, K., Tamariz, M., Hannah, S., Sinclair, D., Koniaris, B., & Kennedy, J. (2024, May). Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments. Presented at SIGCHI GenAI in UGC Workshop, Honolulu, Hawaii

We consider practical and social considerations of collaborating verbally with colleagues and friends, not confined by physical distance, but through seamless networked telepresence to interactively create shared virtual dance environments. In respon... Read More about Design Considerations of Voice Articulated Generative AI Virtual Reality Dance Environments.

Power Consumption Analysis For Smarter Robotics Via Industry 4.0 Methods And Technologies RS HYu V2 (2024)
Presentation / Conference Contribution
Samson, R., Goh, K., Sankarraj, A., Gkanatsios, A., & Yu, H. (2023, September). Power Consumption Analysis For Smarter Robotics Via Industry 4.0 Methods And Technologies RS HYu V2. Presented at 2023 International Conference on Innovation of Communication and Information Technology (ICIEICT 2023), Madrid, Spain

This paper examines the opportunities to apply industry 4.0 technology to practical applications, with a specific focus on sustainability and resource efficiency in industrial environments. The main objective of this paper is to design and implement... Read More about Power Consumption Analysis For Smarter Robotics Via Industry 4.0 Methods And Technologies RS HYu V2.

Safer and Efficient Factory by Predicting Worker Trajectories using Spatio-Temporal Graph Attention Networks (2024)
Presentation / Conference Contribution
K, S. S. K., Vasantha, G., Corney, J., Hanson, J., Quigley, J., El-Raoui, H., Thompson, N., & Sherlock, A. (2024, August). Safer and Efficient Factory by Predicting Worker Trajectories using Spatio-Temporal Graph Attention Networks. Presented at IDETC-CIE International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Washington, DC

Occupational accidents in manufacturing industries pose a significant risk, necessitating advanced strategies to ensure worker safety and enhance operational productivity. The unpredictable nature of worker movements, influenced by varied tasks such... Read More about Safer and Efficient Factory by Predicting Worker Trajectories using Spatio-Temporal Graph Attention Networks.

Optimal DC link voltage stabilisation technique for a grid-connected PV system (2024)
Presentation / Conference Contribution
Khan, T., Kahwash, F., Ahmed, J., & Goh, K. (2024, September). Optimal DC link voltage stabilisation technique for a grid-connected PV system. Paper presented at ECCE Europe 2024, Darmstadt, Germany

The integration and utilisation of renewable energy resources (RES) have seen significant growth due to increased demand and environmental concerns. These RES resources are often integrated through a DC link. The stability and maintaining the DC link... Read More about Optimal DC link voltage stabilisation technique for a grid-connected PV system.

Participatory Explorations in the Techno-Spiritual (2024)
Presentation / Conference Contribution
Grandison, T. (2024, June). Participatory Explorations in the Techno-Spiritual. Presented at The 22nd European Conference on Computer-Supported Cooperative Work, Rimini, Italy

This exploratory paper presents a pilot study conducted with 64 undergraduate students at Edinburgh Napier University in November 2023. The aim of this study was to understand how people who do not necessarily identify as religious engaged in what th... Read More about Participatory Explorations in the Techno-Spiritual.

Explaining evolutionary feature selection via local optima networks (2024)
Presentation / Conference Contribution
Adair, J., Thomson, S. L., & Brownlee, A. E. (2024, July). Explaining evolutionary feature selection via local optima networks. Presented at ACM Genetic and Evolutionary Computation Conference (GECCO) 2024, Melbourne, Australia

We analyse fitness landscapes of evolutionary feature selection to obtain information about feature importance in supervised machine learning. Local optima networks (LONs) are a compact representation of a landscape, and can potentially be adapted fo... Read More about Explaining evolutionary feature selection via local optima networks.

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.