Outputs (2327)

Automated Design of Metaheuristics Using Reinforcement Learning within a Novel General Search Framework (2022)
Journal Article
Yi, W., Qu, R., Jiao, L., & Niu, B. (2023). Automated Design of Metaheuristics Using Reinforcement Learning within a Novel General Search Framework. IEEE Transactions on Evolutionary Computation, 27(4), 1072-1084. https://doi.org/10.1109/TEVC.2022.3197298

Metaheuristic algorithms have been investigated intensively to address highly complex combinatorial optimisation problems. However, most metaheuristic algorithms have been designed manually by researchers of different expertise without a consistent f... Read More about Automated Design of Metaheuristics Using Reinforcement Learning within a Novel General Search Framework.

A rewriting coherence theorem with applications in homotopy type theory (2022)
Journal Article
Kraus, N., & von Raumer, J. (2022). A rewriting coherence theorem with applications in homotopy type theory. Mathematical Structures in Computer Science, 32(7), 982-1014. https://doi.org/10.1017/s0960129523000026

Higher-dimensional rewriting systems are tools to analyse the structure of formally reducing terms to normal forms, as well as comparing the different reduction paths that lead to those normal forms. This higher structure can be captured by finding a... Read More about A rewriting coherence theorem with applications in homotopy type theory.

Involving psychological therapy stakeholders in responsible research to develop an automated feedback tool: Learnings from the ExTRAPPOLATE project (2022)
Journal Article
Andrews, J. A., Rawsthorne, M., Manolescu, C., Burton McFaul, M., French, B., Rye, E., McNaughton, R., Baliousis, M., Smith, S., Biswas, S., Baker, E., Repper, D., Long, Y., Jilani, T., Clos, J., Higton, F., Moghaddam, N., & Malins, S. (2022). Involving psychological therapy stakeholders in responsible research to develop an automated feedback tool: Learnings from the ExTRAPPOLATE project. Journal of Responsible Technology, 11, Article 100044. https://doi.org/10.1016/j.jrt.2022.100044

Understanding stakeholders’ views on novel autonomous systems in healthcare is essential to ensure these are not abandoned after substantial investment has been made. The ExTRAPPOLATE project applied the principles of Responsible Research and Innovat... Read More about Involving psychological therapy stakeholders in responsible research to develop an automated feedback tool: Learnings from the ExTRAPPOLATE project.

Effects of Wording and Gendered Voices on Acceptability of Voice Assistants in Future Autonomous Vehicles (2022)
Presentation / Conference Contribution
Jestin, I., Fischer, J., Galvez Trigo, M. J., Large, D. R., & Burnett, G. (2022, July). Effects of Wording and Gendered Voices on Acceptability of Voice Assistants in Future Autonomous Vehicles. Presented at CUI 2022: 4th Conference on Conversational User Interfaces, Glasgow, UK

Voice assistants in future autonomous vehicles may play a major role in supporting the driver during periods of a transfer of control with the vehicle (handover and handback). However, little is known about the effects of different qualities of the v... Read More about Effects of Wording and Gendered Voices on Acceptability of Voice Assistants in Future Autonomous Vehicles.

Modelling the Turtle Python library in CSP (2022)
Presentation / Conference Contribution
MacConville, D., Farrell, M., Luckcuck, M., & Monahan, R. (2022, July). Modelling the Turtle Python library in CSP. Presented at Second Workshop on Agents and Robots for reliable Engineered Autonomy, Vienna, Austria

Software verification is an important tool in establishing the reliability of critical systems. One potential area of application is in the field of robotics, as robots take on more tasks in both day-to-day areas and highly specialised domains. Robot... Read More about Modelling the Turtle Python library in CSP.

Clinical laboratory parameters and comorbidities associated with severity of coronavirus disease 2019 (COVID-19) in Kurdistan Region of Iraq (2022)
Journal Article
Ali, H. N., Ali, K. M., Rostam, H. M., Ali, A. M., Tawfeeq, H. M., Fatah, M. H., & Figueredo, G. P. (2022). Clinical laboratory parameters and comorbidities associated with severity of coronavirus disease 2019 (COVID-19) in Kurdistan Region of Iraq. Practical Laboratory Medicine, 31, Article e00294. https://doi.org/10.1016/j.plabm.2022.e00294

Background: The pandemic coronavirus disease (COVID-19) dramatically spread worldwide. Considering several laboratory parameters and comorbidities may facilitate the assessment of disease severity. Early recognition of disease progression associated... Read More about Clinical laboratory parameters and comorbidities associated with severity of coronavirus disease 2019 (COVID-19) in Kurdistan Region of Iraq.

Accelerated pattern search with variable solution size for simultaneous instance selection and generation (2022)
Presentation / Conference Contribution
Le, H. L., Neri, F., Landa-Silva, D., & Triguero, I. (2022, July). Accelerated pattern search with variable solution size for simultaneous instance selection and generation. Poster presented at Genetic and Evolutionary Computation Conference Companion (GECCO 2022), Boston, USA and online

The search for the optimum in a mixed continuous-combinatorial space is a challenging task since it requires operators that handle both natures of the search domain. Instance reduction (IR), an important pre-processing technique in data science, is o... Read More about Accelerated pattern search with variable solution size for simultaneous instance selection and generation.

Counterfactual rule generation for fuzzy rule-based classification systems (2022)
Presentation / Conference Contribution
Zhang, T., Wagner, C., & Garibaldi, J. M. (2022, July). Counterfactual rule generation for fuzzy rule-based classification systems. Presented at 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Padua, Italy

EXplainable Artificial Intelligence (XAI) is of in-creasing importance as researchers and practitioners seek better transparency and verifiability of AI systems. Mamdani fuzzy systems can provide explanations based on their linguistic rules, and thus... Read More about Counterfactual rule generation for fuzzy rule-based classification systems.

Visualization of Interval Regression for Facilitating Data and Model Insight (2022)
Presentation / Conference Contribution
Kabir, S., & Wagner, C. (2022, July). Visualization of Interval Regression for Facilitating Data and Model Insight. Presented at IEEE World Congress on Computational Intelligence 2022 (IEEE WCCI 2022), Padova, Italy

With growing significance of interval-valued data, interest in artificial intelligence methods tailored to this data type is similarly increasing across a range of application domains. Here, regression, i.e., the modelling of the association between... Read More about Visualization of Interval Regression for Facilitating Data and Model Insight.

Quality Quantification in Deep Convolutional Neural Networks for Skin Lesion Segmentation using Fuzzy Uncertainty Measurement (2022)
Presentation / Conference Contribution
Lin, Q., Chen, X., Chen, C., & Garibaldi, J. M. (2022, July). Quality Quantification in Deep Convolutional Neural Networks for Skin Lesion Segmentation using Fuzzy Uncertainty Measurement. Presented at 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Padua, Italy

Deep convolutional neural networks (DCNN)-based methods have achieved promising performance in semantic image segmentation. However, in practical applications, it is important not only to produce the segmentation result but also to inform the segment... Read More about Quality Quantification in Deep Convolutional Neural Networks for Skin Lesion Segmentation using Fuzzy Uncertainty Measurement.