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A hybrid approach for stain normalisation in digital histopathological images (2019)
Journal Article
Bukenya, F. (2020). A hybrid approach for stain normalisation in digital histopathological images. Multimedia Tools and Applications, 79(3-4), 2339-2362. https://doi.org/10.1007/s11042-019-08262-0

Stain in-homogeneity adversely affects segmentation and quantifi-cation of tissues in histology images. Stain normalisation techniques have been used to standardise the appearance of images. However, most the available stain normalisation techniques... Read More about A hybrid approach for stain normalisation in digital histopathological images.

An Intelligent Toolkit for Benchmarking Data-Driven Aerospace Prognostics (2019)
Presentation / Conference Contribution
Rengasamy, D., Mase, J. M., Rothwell, B., & Figueredo, G. P. (2019, October). An Intelligent Toolkit for Benchmarking Data-Driven Aerospace Prognostics. Presented at 2019 IEEE Intelligent Transportation Systems Conference - ITSC, Auckland, New Zealand

© 2019 IEEE. Machine Learning (ML) has been largely employed to sensor data for predicting the Remaining Useful Life (RUL) of aircraft components with promising results. A review of the literature, however, has revealed a lack of consensus regarding... Read More about An Intelligent Toolkit for Benchmarking Data-Driven Aerospace Prognostics.

Clinical Scene Segmentation with Tiny Datasets (2019)
Presentation / Conference Contribution
Smith, T. J., Sharkey, D., Crowe, J., & Valstar, M. (2019, October). Clinical Scene Segmentation with Tiny Datasets. Presented at 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Seoul, Korea (South)

Many clinical procedures could benefit from automatic scene segmentation and subsequent action recognition. Using Convolutional Neural Networks to semantically segment meaningful parts of an image or video is still an unsolved problem. This becomes e... Read More about Clinical Scene Segmentation with Tiny Datasets.

A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic (2019)
Journal Article
Venkatesan, S., Nguyen-Van-Tam, J., & Siebers, P.-O. (2019). A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic. PLoS ONE, 14(10), Article e0223946. https://doi.org/10.1371/journal.pone.0223946

© 2019 Venkatesan et al. The importance of accounting for social and behavioural processes when studying public health emergencies has been well-recognised. For infectious disease outbreaks in particular, several methods of incorporating individual b... Read More about A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic.

Optimal Power Flow Based Architecture Design for Electrical Power System in More-Electric Aircraft (2019)
Presentation / Conference Contribution
Wang, X., Atkin, J., Bozhko, S., & Hill, C. I. (2019, October). Optimal Power Flow Based Architecture Design for Electrical Power System in More-Electric Aircraft. Presented at IEEE 45th Annual Conference of the Industrial Electronics Society (IECON'2019), Lisbon, Portugal

When designing an electric power system (EPS) architecture for a more electric aircraft (MEA), the total weight of the system is treated as one of the most important criteria. For the weight saving purpose, this paper proposes an optimal power flow (... Read More about Optimal Power Flow Based Architecture Design for Electrical Power System in More-Electric Aircraft.

A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering (2019)
Presentation / Conference Contribution
Razak, T. R., Garibaldi, J. M., & Wagner, C. (2019, June). A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering. Presented at International Conference on Fuzzy Systems (FUZZ-IEEE 2019), New Orleans, USA

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 about A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering.

Interdependent Multi-layer Spatial Temporal-based Caching in Heterogeneous Mobile Edge and Fog Networks (2019)
Presentation / Conference Contribution
Huynh, V. S. H., & Radenkovic, M. (2019, September). Interdependent Multi-layer Spatial Temporal-based Caching in Heterogeneous Mobile Edge and Fog Networks. Presented at 9th International Conference on Pervasive and Embedded Computing and Communication Systems (PECCS 2019), Vienna, Austria

Applications and services hosted in the mobile edge/fog networks today (e.g., augmented reality, self-driving, and various cognitive applications) may suffer from limited network coverage and localized congestion due to dynamic mobility of users and... Read More about Interdependent Multi-layer Spatial Temporal-based Caching in Heterogeneous Mobile Edge and Fog Networks.

Metaheuristic optimisation of sound absorption performance of multilayered porous materials (2019)
Presentation / Conference Contribution
Ramamoorthy, V. T., Özcan, E., Parkes, A. J., Luc, J., & Bécot, F.-X. (2019, September). Metaheuristic optimisation of sound absorption performance of multilayered porous materials. Presented at 23rd International Congress on Acoustics (ICA 2019), Aachen, Germany

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 about Metaheuristic optimisation of sound absorption performance of multilayered porous materials.

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. (2020). Probing IoT-based consumer services: 'insights' from the connected shower. Personal and Ubiquitous Computing, 24, 595–611. 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 about Probing IoT-based consumer services: 'insights' from the connected shower.

Application of a MILP-based Algorithm for Power Flow Optimisation within More-Electric Aircraft Electrical Power Systems (2019)
Presentation / Conference Contribution
Wang, X., Atkin, J., Bozhko, S., & Hill, C. (2019, September). Application of a MILP-based Algorithm for Power Flow Optimisation within More-Electric Aircraft Electrical Power Systems. Presented at 2019 21st European Conference on Power Electronics and Applications (EPE '19 ECCE Europe), Genova, Italy

This paper presents in detail how Mixed-Integer Linear Programming (MILP) can be used to solve the optimal power flow problem of Electrical Power Systems (EPSs) within More-Electric Aircraft (MEA). Continuous linear functions, integer variables and p... Read More about Application of a MILP-based Algorithm for Power Flow Optimisation within More-Electric Aircraft Electrical Power Systems.

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), Article 62. 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 about An Intelligent Computer-Aided Scheme for Classifying Multiple Skin Lesions.

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. (2020). Fast and Scalable Approaches to Accelerate the Fuzzy k Nearest Neighbors Classifier for Big Data. IEEE Transactions on Fuzzy Systems, 28(5), 874-886. 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 about Fast and Scalable Approaches to Accelerate the Fuzzy k Nearest Neighbors Classifier for Big Data.

Multi-Scale Topological Analysis of Asymmetric Tensor Fields on Surfaces (2019)
Journal Article
Khan, F., Roy, L., Zhang, E., Qu, B., Hung, S.-H., Yeh, H., Laramee, R. S., & Zhang, Y. (2020). Multi-Scale Topological Analysis of Asymmetric Tensor Fields on Surfaces. IEEE Transactions on Visualization and Computer Graphics, 26(1), 270 - 279. https://doi.org/10.1109/tvcg.2019.2934314

Asymmetric tensor fields have found applications in many science and engineering domains, such as fluid dynamics. Recent advances in the visualization and analysis of 2D asymmetric tensor fields focus on pointwise analysis of the tensor field and eff... Read More about Multi-Scale Topological Analysis of Asymmetric Tensor Fields on Surfaces.

“Off the beaten map”: Navigating with digital maps on moorland (2019)
Journal Article
Smith, T. A., Laurier, E., Reeves, S., & Dunkley, R. A. (2019). “Off the beaten map”: Navigating with digital maps on moorland. Transactions of the Institute of British Geographers, https://doi.org/10.1111/tran.12336

The information, practices and views in this article are those of the author(s) and do not necessarily reflect the opinion of the Royal Geographical Society (with IBG). © 2019 Royal Geographical Society (with the Institute of British Geographers) Res... Read More about “Off the beaten map”: Navigating with digital maps on moorland.

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), Article 763. 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 about A Novel Autonomous Perceptron Model for Pattern Classification Applications.

Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures (2019)
Presentation / Conference Contribution
Agrawal, U., Wagner, C., Garibaldi, J. M., & Soria, D. (2019, June). Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

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 about Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures.