All Outputs (96)

How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction (2024)
Presentation / Conference Contribution
Orme, M., Yu, Y., & Tan, Z. (2024, May). How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction. Presented at The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), Torino, Italy

This paper concerns the pressing need to understand and manage inappropriate language within the evolving human-robot interaction (HRI) landscape. As intelligent systems and robots transition from controlled laboratory settings to everyday households... Read More about How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction.

Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode (2024)
Presentation / Conference Contribution
Buchanan, W., Grierson, S., & Uribe, D. (2024, February). Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode. Presented at 10th International Conference on Information Systems Security and Privacy, Rome, Italy

Biometric data is often highly sensitive, and a leak of this data can lead to serious privacy breaches. Some of the most sensitive of this type of data relates to the usage of DNA data on individuals. A leak of this type of data without consent could... Read More about Privacy-Aware Single-Nucleotide Polymorphisms (SNPs) Using Bilinear Group Accumulators in Batch Mode.

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.

Multi-Attribute Analysis For Sustainable Reclamation Of Urban Industrial Sites: Case From Damascus Post-Conflict (2024)
Presentation / Conference Contribution
Khaddour, L., Osunsanmi, T., Olawumi, T., & Bradly, L. (2024, June). Multi-Attribute Analysis For Sustainable Reclamation Of Urban Industrial Sites: Case From Damascus Post-Conflict. Presented at The 2024 World Sustainable Built Environment Conference (WSBE24), Online

The reclamation of urban industrial zones presents intricate challenges within urban planning, notably in post-disaster scenarios aimed at revitalizing urban landscapes. This study delves into the complexities and decision-making intricacies involved... Read More about Multi-Attribute Analysis For Sustainable Reclamation Of Urban Industrial Sites: Case From Damascus Post-Conflict.

Creating Sustainable Internet of Things Futures: Aligning Legal and Design Research Agendas. (2024)
Presentation / Conference Contribution
Urquhart, L. D., Lechelt, S., Terras, M., Sailaja, N., Rezk, A. M., Castle-Green, T., Darzentas, D. P., Primlani, N., Owen, V., & Stead, M. (2024, July). Creating Sustainable Internet of Things Futures: Aligning Legal and Design Research Agendas. Paper presented at DIS '24: Designing Interactive Systems Conference, IT University of Copenhagen, Denmark

The way consumer Internet of Things (IoT) devices are built is leading to electronic waste (eWaste) growth. This arises from planned obsolescence, bundling of ‘smartness’ creating more routes to device failure, and lacking hardware modularity and rep... Read More about Creating Sustainable Internet of Things Futures: Aligning Legal and Design Research Agendas..

Factors Impacting Landscape Ruggedness in Control Problems: a Case Study (2024)
Presentation / Conference Contribution
Saliby, M. E., Medvet, E., Nadizar, G., Salvato, E., & Thomson, S. L. (2024, September). Factors Impacting Landscape Ruggedness in Control Problems: a Case Study. Paper presented at WIVACE 2024 (XVIII International Workshop on Artificial Life and Evolutionary Computation), Namur, Belgium

Understanding fitness landscapes in evolutionary robotics (ER) can provide valuable insights into the considered robotic problems as well as into the strategies found by evolutionary algorithms (EAs) to address them, ultimately guiding practitioners... Read More about Factors Impacting Landscape Ruggedness in Control Problems: a Case Study.

Hoop Diagrams: A Set Visualization Method (2024)
Presentation / Conference Contribution
Rodgers, P., Chapman, P., Blake, A., Nollenburg, M., Wallinger, M., & Dobler, A. (2024, September). Hoop Diagrams: A Set Visualization Method. Presented at 14th International Conference on the Theory and Application of Diagrams, Munster, Germany

We introduce Hoop Diagrams, a new visualization technique for set data. Hoop Diagrams are a circular visualization with hoops representing sets and sectors representing set intersections. We present an interactive tool for drawing Hoop Diagrams and d... Read More about Hoop Diagrams: A Set Visualization Method.

View from the (Virtual) Terraces: Football Fandom in Videogames (2024)
Presentation / Conference Contribution
Donald, I., & Reid, A. (2024, September). View from the (Virtual) Terraces: Football Fandom in Videogames. Presented at Video Game Cultures, Birmingham City University

Other is a concept that is fundamental to sports: the other team, other player(s), other fans. Football fans share a camaraderie and can enthuse a tribalism (Mangan, 1996) that is difficult to understand and replicate in the virtual world. Yet, that... Read More about View from the (Virtual) Terraces: Football Fandom in Videogames.

Scottish Mountain Soundscapes (2024)
Presentation / Conference Contribution
Di Donato, B., & McGregor, I. (2024, June). Scottish Mountain Soundscapes. Presented at Invited seminar at UniMont, University of Milan, Edolo, Italy

Mountain environments provide an immersive auditory experience shaped by natural forces and human interactions. This seminar presents results from an ongoing project that delves into people’s experiences of mountain soundscapes, with a focus on the i... Read More about Scottish Mountain Soundscapes.

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.

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.

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.

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.

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.

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.