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Uncertainty-Aware Forecasting of Renewable Energy Sources (2020)
Conference Proceeding
Pekaslan, D., Wagner, C., Garibaldi, J. M., Marín, L. G., & Sáez, D. (2020). Uncertainty-Aware Forecasting of Renewable Energy Sources. In 2020 IEEE International Conference on Big Data and Smart Computing (BigComp). https://doi.org/10.1109/bigcomp48618.2020.00-68

Smart grid systems are designed to enable the efficient capture and intelligent distribution of electricity across a distributed set of utilities. They are an essential component of increasingly important renewable energy sources, where it is vital t... Read More about Uncertainty-Aware Forecasting of Renewable Energy Sources.

Multigranulation Super-Trust Model for Attribute Reduction (2020)
Journal Article
Ding, W., Pedrycz, W., Triguero, I., Cao, Z., & Lin, C. (2020). Multigranulation Super-Trust Model for Attribute Reduction. IEEE Transactions on Fuzzy Systems, 29(6), 1395-1408. https://doi.org/10.1109/tfuzz.2020.2975152

As big data often contains a significant amount of uncertain, unstructured, and imprecise data that are structurally complex and incomplete, traditional attribute reduction methods are less effective when applied to large-scale incomplete information... Read More about Multigranulation Super-Trust Model for Attribute Reduction.

Intersection SPaT Estimation by means of Single-Source Connected Vehicle Data (2020)
Conference Proceeding
Rostami-Shahrbabaki, M., Bogenberger, K., Safavi, A. A., & Moemeni, A. (2020). Intersection SPaT Estimation by means of Single-Source Connected Vehicle Data

Current traffic management systems in urban networks require real-time estimation of the traffic states.With the development of in-vehicle and communication technologies, connected vehicle data has emerged as a new data source for traffic measurement... Read More about Intersection SPaT Estimation by means of Single-Source Connected Vehicle Data.

A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum] (2020)
Journal Article
Shukla, A. K., Kumar Bansal, S., Seth, T., Basu, A., John, R., & Muhuri, P. K. (2020). A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum]. IEEE Computational Intelligence Magazine, 15(1), 89-98. https://doi.org/10.1109/MCI.2019.2954669

© 2005-2012 IEEE. Fuzzy Sets and Systems is an area of computational intelligence, pioneered by Lotfi Zadeh over 50 years ago in a seminal paper in Information and Control. Fuzzy Sets (FSs) deal with uncertainty in our knowledge of a particular situa... Read More about A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum].

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)
Conference Proceeding
Rengasamy, D., Mase, J. M., Rothwell, B., & Figueredo, G. P. (2019). An Intelligent Toolkit for Benchmarking Data-Driven Aerospace Prognostics. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC) (4210-4215). https://doi.org/10.1109/ITSC.2019.8917115

© 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)
Conference Proceeding
Smith, T. J., Sharkey, D., Crowe, J., & Valstar, M. (2019). Clinical Scene Segmentation with Tiny Datasets. In 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) (1637-1645). https://doi.org/10.1109/ICCVW.2019.00203

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. (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), 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)
Conference Proceeding
Wang, X., Atkin, J., Bozhko, S., & Hill, C. I. (2019). Optimal Power Flow Based Architecture Design for Electrical Power System in More-Electric Aircraft. In Proceedings of the IEEE 45th Annual Conference of the Industrial Electronics Society (IECON'2019)

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)
Conference Proceeding
Razak, T. R., Garibaldi, J. M., & Wagner, C. (2019). A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) ( 1-7). https://doi.org/10.1109/FUZZ-IEEE.2019.8859011

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)
Conference Proceeding
Huynh, V. S. H., & Radenkovic, M. (2019). Interdependent Multi-layer Spatial Temporal-based Caching in Heterogeneous Mobile Edge and Fog Networks. In Proceedings of the 9th International Conference on Pervasive and Embedded Computing and Communication Systems (34-45). https://doi.org/10.5220/0008167900340045

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)
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 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.

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., Yeh, H., …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.