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Alzheimer's Disease (AD) Detect & Prevent -presymptomatic AD detection and prevention (2019)
Conference Proceeding
Dong, M., Husain, M., Brooks, D., Wilson, M., Craven, M., Destrebecq, F., …Baden-Kristensen, K. (in press). Alzheimer's Disease (AD) Detect & Prevent -presymptomatic AD detection and prevention. In K. Niedderrer, G. Ludden, R. Cain, & C. Wölfel (Eds.), International MinD Conference 2019 - Designing with and for People with Dementia: Well-being, Empowerment and Happiness, 151-154

Alzheimer's disease (AD) is a major cause of the rapidly growing and crushing aging challenge that threatens to economically undermine today's healthcare system. AD prevalence will grow to over 100 million cases in 2050. AD is incurable but can be pr... Read More

Parametric Virtual Design-based Multi-Objective Optimization for Sustainable Building Design (2019)
Conference Proceeding
Cheng, C., Ninic, J., & Tizani, W. (2019). Parametric Virtual Design-based Multi-Objective Optimization for Sustainable Building Design

With the development of Building Information Modelling aiming for automatic, the automating of sustainability analysis will be a certain requirement in the future. Unlike the current research stream, this paper investigates a novel approach of direct... Read More

Adult Education 100: reflections & reconstructions: conference proceedings 2019 (2019)
Conference Proceeding
Holford, J. (2019). Adult Education 100: reflections & reconstructions: conference proceedings 2019. In J. Holford (Ed.), Adult Education 100: reflections & reconstructions : conference proceedings 2019

Papers presented at the 49th Annual Conference of the Standing Conference on University Teaching and Research in the Education of Adults, held at the University of Nottingham, 2-4 July 2019

Towards a streamlined stacking sequence optimisation methodology for blended composite aircraft structures (2019)
Conference Proceeding
Ntourmas, G., Özcan, E., Chronopoulos, D., Glock, F., & Daoud, F. (2019). Towards a streamlined stacking sequence optimisation methodology for blended composite aircraft structures. In Proceedings of 8th European Conference for Aeronautics and Aerospace Sciences (EUCASS)

In order to fully exploit the benefits provided by using composite materials in large scale aerospace structures, more efficient detailed design optimisation techniques need to be developed. In the present work, the optimisation procedure is split up... Read More

Fuzzy Hot Spot Identification for Big Data: An Initial Approach (2019)
Conference Proceeding
Triguero, I., Tickle, R., Figueredo, G. P., Mesgarpour, M., ozcan, E., & John, R. I. (2019). Fuzzy Hot Spot Identification for Big Data: An Initial Approach. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)https://doi.org/10.1109/fuzz-ieee.2019.8858979

Hot spot identification problems are present across a wide range of areas, such as transportation, health care and energy. Hot spots are locations where a certain type of event occurs with high frequency. A recent big data approach is capable of iden... Read More

Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels (2019)
Conference Proceeding
Garibaldi, J. M., Pekaslan, D., & Wagner, C. (2019). Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)https://doi.org/10.1109/fuzz-ieee.2019.8858800

Most real-world environments are subject to different sources of uncertainty which may vary in magnitude over time. We propose that while Type-1 (T1) Non-Singleton Fuzzy Logic System (NSFLSs) have the potential to tackle uncertainty within the input... Read More

A Preliminary Approach for the Exploitation of Citizen Science Data for Fast and Robust Fuzzy k-Nearest Neighbour Classification (2019)
Conference Proceeding
Jimenez, M., Torres, M. T., John, R., & Triguero, I. (2019). A Preliminary Approach for the Exploitation of Citizen Science Data for Fast and Robust Fuzzy k-Nearest Neighbour Classification. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)https://doi.org/10.1109/fuzz-ieee.2019.8858830

Citizen science is becoming mainstream in a wide variety of real-world applications in astronomy or bioinformatics, in which, for example, classification tasks by experts are very time consuming. These projects engage amateur volunteers that are task... Read More

Uncertainty quantification in ultrasonic guided-waves based damage localization (2019)
Conference Proceeding
Cantero-Chinchilla, S., Chiachío, J., Chiachío, M., Chronopoulos, D., Jones, A., Essa, Y., & Martín De La Escalera, F. (2019). Uncertainty quantification in ultrasonic guided-waves based damage localization

Bayesian methods for inverse problems offer higher robustness to noise and uncertainty than deterministic, yet accurate, inference methods. Both types of techniques typically focus on finding optimal model parameters that minimize an objective functi... Read More

Assessment of an Enhanced Thin Film Model to Capture Wetting and Drying Behavior in an Aero-Engine Bearing Chamber (2019)
Conference Proceeding
Singh, K., Sharabi, M., Ambrose, S., Eastwick, C., Jefferson-Loveday, R., Cao, J., & Jacobs, A. (2019). Assessment of an Enhanced Thin Film Model to Capture Wetting and Drying Behavior in an Aero-Engine Bearing Chamber. In Proceedings of ASME Turbo Expo 2019 Turbomachinery Technical Conference & Exposition

In the present work, a wetting and drying model is coupled with Eulerian Thin-Film model (ETFM) to analyze the wetting and drying behavior inside the bearing chamber. In the enhanced model, an additional source term is included to account for the con... Read More

A study on the interpretability of a fuzzy system to control an inverted pendulum (2019)
Conference Proceeding
Zeren, B., Deveci, M., Coupland, S., John, R., & Ender¨ozcan, E. (2019). A study on the interpretability of a fuzzy system to control an inverted pendulum

Fuzzy systems mimic human reasoning and provide solutions to problems under uncertainty via 'computing with words'. This particular strength of fuzzy systems is often discarded in some real world applications where the fuzzy sets are designed for con... Read More

Prediction of Film Thickness of an Aero-Engine Bearing Chamber using Coupled VOF and Thin Film Model (2019)
Conference Proceeding
Singh, K., Sharabi, M., Ambrose, S., Eastwick, C., & Jefferson-Loveday, R. J. (2019). Prediction of Film Thickness of an Aero-Engine Bearing Chamber using Coupled VOF and Thin Film Model. In Proceedings of ASME Turbo Expo 2019 Turbomachinery Technical Conference & Exposition

In the present work, a coupled volume-of-fluid (VOF) model with Eulerian thin-film model (ETFM) approach is used to predict the film thickness in an aero-engine bearing chamber. Numerical studies are conducted for a wide range of shaft speeds with lu... 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

Supercontinuum sources for multimodal MIR-OCT imaging (2019)
Conference Proceeding
Zorin, I., Kilgus, J., Brandstetter, M., Su, R., & Heise, B. (2019). Supercontinuum sources for multimodal MIR-OCT imaging

In this paper we present a multimodal OCT imaging system operating in the NIR and MIR spectral region. NIR/MIR Supercontinuum source based multimodal OCT provides new insights in scattering materials. The system combines the modality of OCT and spect... Read More

DECSYS - Discrete and Ellipse-based response Capture SYStem (2019)
Conference Proceeding
Ellerby, Z., McCulloch, J., Young, J., & Wagner, C. (2019). DECSYS - Discrete and Ellipse-based response Capture SYStem

Data-driven techniques that capture uncertainty through intervals or fuzzy sets can substantially improve systematic reasoning about uncertain information. Recent years have seen renewed interest in the capture of intervals from a variety of sources-... Read More

On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets (2019)
Conference Proceeding
McCulloch, J., Ellerby, Z., & Wagner, C. (2019). On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets

The capture of interval-valued data is becoming an increasingly common approach in data collection (from survey based research to the collation of sensor data) as an efficient method of obtaining information about uncertainty associated with the data... Read More

A novel non-iterative parameter estimation method for interval type-2 fuzzy neural networks based on a dynamic cost function (2019)
Conference Proceeding
Khanesar, M. A., Hassan, S., Cambria, E., & Kayacan, E. (2019). A novel non-iterative parameter estimation method for interval type-2 fuzzy neural networks based on a dynamic cost function

Non-iterative methods for parameter estimation for interval type-2 neuro-fuzzy structure are fast to implement, when compared to online methods, and need no –or a few– parameters to be tuned. In this paper, a novel dynamic cost function, which define... 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

Image processing algorithm to determine an optimised 2D laser cutting trajectory (2019)
Conference Proceeding
Syam, W. P., Bansal, R., Benardos, P., Britchford, E., Hopkinson, A., Voisey, K., & Branson, D. T. (2019). Image processing algorithm to determine an optimised 2D laser cutting trajectory. In Proceedings of 25th IEEE International Conference on Automation & Computing (ICAC'19)

Laser cutting processes offer high-quality and fast cutting capability across a wide variety of materials, including metals, plastics and organic tissues. To enable 2D laser cutting process, a set of (x, y) Cartesian coordinates that form a cutting t... Read More

Towards an active learning approach to tool condition monitoring with Bayesian deep learning (2019)
Conference Proceeding
Martinez Arellano, G., & Ratchev, S. (2019). Towards an active learning approach to tool condition monitoring with Bayesian deep learning

With the current advances in the Internet of Things (IoT), smart sensors and Artificial Intelligence (AI), a new generation of condition monitoring solutions for smart manufacturing is starting to emerge. Computer Numerical Control (CNC) machines can... Read More