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Comparing Performance Potentials of Classical and Intuitionistic Fuzzy Systems in Terms of Sculpting the State Space (2019)
Journal Article
Mendel, J. M., Eyoh, I., & John, R. (2019). Comparing Performance Potentials of Classical and Intuitionistic Fuzzy Systems in Terms of Sculpting the State Space. IEEE Transactions on Fuzzy Systems, doi:10.1109/TFUZZ.2019.2933786

This paper provides new application-independent perspectives about the performance potential of an intuitionistic (I-) fuzzy system over a (classical) TSK fuzzy system. It does this by extending sculpting the state space works from a TSK fuzzy system... Read More

Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets (2019)
Conference Proceeding
Navarro, J., & Wagner, C. (2019). Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets

Recently, there has been much research into modelling of uncertainty in human perception through Fuzzy Sets (FSs). Most of this research has focused on allowing respondents to express their (intra) uncertainty using intervals. Here, depending on the... Read More

New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets (2019)
Journal Article
Mohamed, S. S., Abdalla, A., & John, R. I. (2019). New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets. Axioms, 8(2), doi:10.3390/axioms8020073

In this paper we propose a new approach to construct similarity measures using the entropy 1 measure for Interval-Valued Intuitionistic Fuzzy Sets. In addition, we provide several illustrative 2 examples to demonstrate the practicality and effectiven... Read More

Modelling the home health care nurse scheduling problem for patients with long-term conditions in the UK (2019)
Conference Proceeding
He, F., Chaussalet, T., & Qu, R. (2019). Modelling the home health care nurse scheduling problem for patients with long-term conditions in the UK

In this work, using a Behavioural Operational Research (BOR) perspective, we develop a model for the Home Health Care Nurse Scheduling Problem (HHCNSP) with application to renal patients taking Peritoneal Dialysis (PD) at their own homes as treatment... Read More

Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles (2019)
Journal Article
Agrawal, U., Soria, D., Wagner, C., Garibaldi, J., Ellis, I. O., Bartlett, J. M. S., …Green, A. R. (2019). Combining clustering and classification ensembles: A novel pipeline to identify breast cancer profiles. Artificial Intelligence in Medicine, 97, 27-37. doi:10.1016/j.artmed.2019.05.002

Breast Cancer is one of the most common causes of cancer death in women, representing a very complex disease with varied molecular alterations. To assist breast cancer prognosis, the classification of patients into biological groups is of great signi... Read More

Psychological interventions as vaccine adjuvants: A systematic review (2019)
Journal Article
Vedhara, K., Ayling, K., Sunger, K., Caldwell, D. M., Halliday, V., Fairclough, L., …Royal, S. (2019). Psychological interventions as vaccine adjuvants: A systematic review. Vaccine, 37(25), 3255-3266. doi:10.1016/j.vaccine.2019.04.091

Objectives: The effectiveness of vaccines is known to be altered by a range of psychological factors. We conducted a systematic review to evaluate the effects of psychological interventions on the ability of vaccines to protect against disease, as me... Read More

The need for fuzzy AI (2019)
Journal Article
Garibaldi, J. M. (2019). The need for fuzzy AI. IEEE/CAA Journal of Automatica Sinica, 6(3), 610-622. doi:10.1109/JAS.2019.1911465

Artificial intelligence (AI) is once again a topic of huge interest for computer scientists around the world. Whilst advances in the capability of machines are being made all around the world at an incredible rate, there is also increasing focus on t... Read More

New Directions for the IoT: Automate, Share, Build, and Care (2019)
Conference Proceeding
Fuentes, C., Porcheron, M., Fischer, J. E., Costanza, E., Verdezoto, N., Herskovic, V., …Takayama, L. (2019). New Directions for the IoT: Automate, Share, Build, and Care. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systemsdoi:10.1145/3290607.3299000

As the IoT is taking hold in the home, in healthcare, factories, and industry, new challenges and approaches arise for HCI research and design. For example, HCI is exploring agency delegation and automation to support the user in managing the deluge... Read More

Young adults' attitudes to sharing whole-genome sequencing information: a university-based survey (2019)
Journal Article
Stringer, P., Sharples, S., Thomson, B. J., & Garibaldi, J. M. (2019). Young adults' attitudes to sharing whole-genome sequencing information: a university-based survey. BMC Medical Genomics, 12, doi:10.1186/s12920-019-0499-2

Background Genomic services are increasingly accessible to young adults starting their independent lives with responsibility for their self-care, yet their attitudes to sharing genomic information remain under-researched. This study explored attitud... Read More

A measure of structural complexity of hierarchical fuzzy systems adapted from software engineering (2019)
Conference Proceeding
Razak, T. R., Garibaldi, J. M., & Wagner, C. (in press). A measure of structural complexity of hierarchical fuzzy systems adapted from software engineering

Hierarchical fuzzy systems (HFSs) have been seen as an effective approach to reduce the complexity of fuzzy logic systems (FLSs), largely as a result of reducing the number of rules. However, it is not clear completely how complexity of HFSs can be m... Read More

Enhancing supervised classifications with metamorphic relations (2018)
Conference Proceeding
Xu, L., Towey, D., French, A. P., Benford, S., Zhou, Z. Q., & Chen, T. Y. (2018). Enhancing supervised classifications with metamorphic relations. In MET '18: Proceedings of the 3rd International Workshop on Metamorphic Testing, 46-53. doi:10.1145/3193977.3193978

We report on a novel use of metamorphic relations (MRs) in machine learning: instead of conducting metamorphic testing, we use MRs for the augmentation of the machine learning algorithms themselves. In particular, we report on how MRs can enable enha... Read More

Transforming Big Data into Smart Data: an insight on the use of the k-nearest neighbours algorithm to obtain quality data (2018)
Journal Article
Triguero, I., Garcia-Gil, D., Maillo, J., Luengo, J., Garcia, S., & Herrera, F. (2019). Transforming Big Data into Smart Data: an insight on the use of the k-nearest neighbours algorithm to obtain quality data. 00 Journal not listed, 9(2), doi:10.1002/widm.1289

The k-nearest neighbours algorithm is characterised as a simple yet effective data mining technique. The main drawback of this technique appears when massive amounts of data -likely to contain noise and imperfections - are involved, turning this algo... Read More

AR Fighter: using HMDs to create vertigo play experiences (2018)
Conference Proceeding
Marshall, J., Byrne, R., & Mueller, F. ". (in press). AR Fighter: using HMDs to create vertigo play experiences

Game designers working with Head-Mounted Displays (HMDs) are usually advised to avoid causing disorientation in players. However, we argue that disorientation is a key element of what makes “vertigo play” (such as spinning in circles until dizzy, bal... Read More

A classification of hyper-heuristic approaches: revisited (2018)
Book
Burke, E. K., Hyde, M. R., Kendall, G., Ochoa, G., Özcan, E., & Woodward, J. R. (2018). A classification of hyper-heuristic approaches: revisited. In Handbook of metaheuristics, 453-477. Cham: Springer Publishing Company. doi:10.1007/978-3-319-91086-4_14

Hyper-heuristics comprise a set of approaches that aim to automate the development of computational search methodologies, initially to address operational research problems but more recently venturing into new domains such as bioinformatics, strategi... Read More

Lookahead policy and genetic algorithm for solving nurse rostering problems (2018)
Conference Proceeding
Peng, S., & Dario, L. (2018). Lookahead policy and genetic algorithm for solving nurse rostering problems. In n/a

Previous research has shown that value function approximation in dynamic programming does not perform too well when tackling difficult combinatorial optimisation problem such as multi-stage nurse rostering. This is because the large action space that... Read More

A preliminary study on automatic algorithm selection for short-term traffic forecasting (2018)
Conference Proceeding
Angarita-Zapata, J. S., Triguero, I., & Masegosa, A. D. (2018). A preliminary study on automatic algorithm selection for short-term traffic forecasting. In Intelligent Distributed Computing XII, 204-214. doi:10.1007/978-3-319-99626-4_18

Despite the broad range of Machine Learning (ML) algorithms, there are no clear baselines to find the best method and its configuration given a Short-Term Traffic Forecasting (STTF) problem. In ML, this is known as the Model Selection Problem (MSP).... Read More

Designing musical soundtracks for Brain Controlled Interface (BCI) systems (2018)
Conference Proceeding
Ramchurn, R., Chamberlain, A., & Benford, S. (2018). Designing musical soundtracks for Brain Controlled Interface (BCI) systems. doi:10.1145/3243274.3243288

This paper presents research based on the creation and development of two Brain Controlled Interface (BCI) based film experiences. The focus of this research is primarily on the audio in the films; the way that the overall experiences were designed,... Read More

Surfing with sound: an ethnography of the art of no-input mixing (2018)
Conference Proceeding
Chamberlain, A. (2018). Surfing with sound: an ethnography of the art of no-input mixing. doi:10.1145/3243274.3243289

The idea of No-Input Mixing may appear at first difficult to understand, after all there is no input, yet artists, performers and sound designers have used a variety of approaches using such feedback systems to create music. This paper uses ethnograp... Read More

The design of future music technologies: ‘sounding out’ AI, immersive experiences & brain controlled interfaces (2018)
Conference Proceeding
Chamberlain, A., Bødker, M., Kallionpää, M., Ramchurn, R., De Roure, D., Benford, S., …Gasselseder, H. (2018). The design of future music technologies: ‘sounding out’ AI, immersive experiences & brain controlled interfaces. In n/adoi:10.1145/3243274.3243314

This paper outlines some of the issues that we will be discussing in the workshop “The Design of Future Music Technologies: ‘Sounding Out’ AI, Immersive Experiences & Brain Controlled Interfaces.” Musical creation, performance and consumption is at a... Read More