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Metaheuristic optimisation of sound absorption performance of multilayered porous materials (2019)
Conference Proceeding
Ramamoorthy, V. T., Özcan, E., Parkes, A. J., Luc, J., & Bécot, F. (2019). Metaheuristic optimisation of sound absorption performance of multilayered porous materials. In Proceedings of the ICA 2019 and EAA Euroregio 23rd International Congress on Acoustics, integrating 4th EAA Euroregio 2019 9 - 13 September 2019, Aachen, Germany, 3213-3220

The optimization of multilayered-sound-packaging is a challenging task which involves searching the best/op-timal settings for a number of acoustic parameters. The search space size becomes too large to handle by brute force, as the number of those p... Read More

Probing IoT-based consumer services: 'insights' from the connected shower (2019)
Journal Article
Crabtree, A., Hyland, L., Colley, J., Flintham, M., Fischer, J. E., & Kwon, H. (2019). Probing IoT-based consumer services: 'insights' from the connected shower. Personal and Ubiquitous Computing, https://doi.org/10.1007/s00779-019-01303-3

This paper presents findings from the deployment of a technology probe-the connected shower-and implications for the development of 'living services' or autonomous context-aware consumer-oriented IoT services that exploit sensing to gain consumer 'in... Read More

An Intelligent Computer-Aided Scheme for Classifying Multiple Skin Lesions (2019)
Journal Article
Hameed, N., Hameed, F., Shabut, A., Khan, S., Cirstea, S., & Hossain, A. (2019). An Intelligent Computer-Aided Scheme for Classifying Multiple Skin Lesions. Computers, 8(3), https://doi.org/10.3390/computers8030062

Skin diseases cases are increasing on a daily basis and are dicult to handle due to the global imbalance between skin disease patients and dermatologists. Skin diseases are among the top 5 leading cause of the worldwide disease burden. To reduce thi... Read More

Fast and scalable approaches to accelerate the fuzzy k nearest neighbors classifier for big data (2019)
Journal Article
Maillo, J., García, S., Luengo, J., Herrera, F., & Triguero, I. (2019). Fast and scalable approaches to accelerate the fuzzy k nearest neighbors classifier for big data. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/TFUZZ.2019.2936356

One of the best-known and most effective methods in supervised classification is the k nearest neighbors algorithm (kNN). Several approaches have been proposed to improve its accuracy, where fuzzy approaches prove to be among the most successful, hig... Read More

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

A Novel Autonomous Perceptron Model for Pattern Classification Applications (2019)
Journal Article
Sagheer, A., Zidan, M., & Abdelsamea, M. M. (2019). A Novel Autonomous Perceptron Model for Pattern Classification Applications. Entropy, 21(8), https://doi.org/10.3390/e21080763

Pattern classification represents a challenging problem in machine learning and data science research domains, especially when there is a limited availability of training samples. In recent years, artificial neural network (ANN) algorithms have demon... 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

Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures (2019)
Conference Proceeding
Agrawal, U., Wagner, C., Garibaldi, J. M., & Soria, D. (2019). Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures

Aggregation operators are mathematical functions that enable the fusion of information from multiple sources. Fuzzy Integrals (FIs) are widely used aggregation operators, which combine information in respect to a Fuzzy Measure (FM) which captures 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

Untangling multi-stakeholder perspectives in digital mental healthcare (2019)
Conference Proceeding
Vallejos, E. P., Nilsson, T., Siebers, O., Siebert, P., Craven, M., & Fuentes, C. (2019). Untangling multi-stakeholder perspectives in digital mental healthcare

Digital mental healthcare constitutes a complex area for development of novel technological solutions. Designers are frequently forced to deal with requirements posed by a range of different stakeholders with particular needs, goals and interests whi... 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

Measuring similarity between discontinuous intervals : challenges and solutions (2019)
Conference Proceeding
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2019). Measuring similarity between discontinuous intervals : challenges and solutions. In Proceedings of 2019 IEEE Conference on Fuzzy Systems

Discontinuous intervals (DIs) arise in a wide range of contexts, from real world data capture of human opinion to α-cuts of non-convex fuzzy sets. Commonly, for assessing the similarity of DIs, the latter are converted into their continuous form, fol... 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