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Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning (2020)
Journal Article
Khan, F. A., Voß, U., Pound, M. P., & French, A. P. (2020). Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning. Frontiers in Plant Science, 11, Article 1275. https://doi.org/10.3389/fpls.2020.01275

© Copyright © 2020 Khan, Voß, Pound and French. Understanding plant growth processes is important for many aspects of biology and food security. Automating the observations of plant development—a process referred to as plant phenotyping—is increasing... Read More about Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning.

Choosing Sample Sizes for Statistical Measures on Interval-Valued Data (2020)
Conference Proceeding
McCulloch, J., Ellerby, Z., & Wagner, C. (2020). Choosing Sample Sizes for Statistical Measures on Interval-Valued Data. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-8). https://doi.org/10.1109/FUZZ48607.2020.9177745

Intervals have frequently been used in the literature to represent uncertainty in data, from eliciting uncertain judgements from experts to representing uncertainty in sensor measurements. This widespread use of intervals has led to research on inter... Read More about Choosing Sample Sizes for Statistical Measures on Interval-Valued Data.

An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities (2020)
Journal Article
Standen, P., Brown, D. J., Taheri, M., Galvez Trigo, M. J., Boulton, H., Burton, A., …Hortal, E. (2020). An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities. British Journal of Educational Technology, 51(5), 1748-1765. https://doi.org/10.1111/bjet.13010

Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a... Read More about An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities.

Constrained Interval Type-2 Fuzzy Classification Systems for Explainable AI (XAI) (2020)
Conference Proceeding
D'Alterio, P., Garibaldi, J. M., & John, R. I. (2020). Constrained Interval Type-2 Fuzzy Classification Systems for Explainable AI (XAI). In Proceedings of IEEE World Congress on Computational Intelligence (WCCI) 2020

In recent year, there has been a growing need for intelligent systems that not only are able to provide reliable classifications but can also produce explanations for the decisions they make. The demand for increased explainability has led to the eme... Read More about Constrained Interval Type-2 Fuzzy Classification Systems for Explainable AI (XAI).

Juzzy Constrained: Software for Constrained Interval Type-2 Fuzzy Sets and Systems in Java (2020)
Conference Proceeding
D'Alterio, P., Garibaldi, J. M., John, R. I., & Wagner, C. (2020). Juzzy Constrained: Software for Constrained Interval Type-2 Fuzzy Sets and Systems in Java. In Proceedings of IEEE World Congress on Computational Intelligence (WCCI) 2020

Constrained interval type-2 (CIT2) fuzzy sets are a class of type-2 fuzzy sets that has been recently proposed as a way to extend type-1 membership functions to interval type-2 (IT2) while keeping a semantic connection between the IT2 fuzzy set and t... Read More about Juzzy Constrained: Software for Constrained Interval Type-2 Fuzzy Sets and Systems in Java.

Developing a measure of online wellbeing and user trust (2020)
Book Chapter
DOWTHWAITE, L., Perez Vallejos, E., Creswick, H., Portillo, V., Patel, M., & Zhao, J. (2020). Developing a measure of online wellbeing and user trust. In M. Arias-Oliva, J. Pelegrín-Borondo, K. Murata, & A. María Lara Palma (Eds.), Societal Challenges in the Smart Society (21-33). Logrono: Universidad de La Rioja

Intention-Aware Multiagent Scheduling (2020)
Conference Proceeding
Dann, M., Thangarajah, J., Yao, Y., & Logan, B. (2020). Intention-Aware Multiagent Scheduling. In B. An, N. Yorke-Smith, A. El Fallah Seghrouchni, & G. Sukthankar (Eds.), Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020)

The Belief Desire Intention (BDI) model of agency is a popular and mature paradigm for designing and implementing multiagent systems. There are several agent implementation platforms that follow the BDI model. In BDI systems, the agents typically hav... Read More about Intention-Aware Multiagent Scheduling.

Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks (2020)
Journal Article
Soltaninejad, M., Sturrock, C. J., Griffiths, M., Pridmore, T. P., & Pound, M. P. (2020). Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks. IEEE Transactions on Image Processing, 29, 6667-6679. https://doi.org/10.1109/TIP.2020.2992893

© 1992-2012 IEEE. We address the complex problem of reliably segmenting root structure from soil in X-ray Computed Tomography (CT) images. We utilise a deep learning approach, and propose a state-of-the-art multi-resolution architecture based on enco... Read More about Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks.

Objective Assessment of Subjective Tasks in Crowdsourcing Applications (2020)
Conference Proceeding
Haralabopoulos, G., Tsikandilakis, M., Torres, M. T., & Mcauley, D. (2020). Objective Assessment of Subjective Tasks in Crowdsourcing Applications. In Proceedings of the 12th Language Resources and Evaluation Conference. , (15-25)

Labelling, or annotation, is the process by which we assign labels to an item with regards to a task. In some Artificial Intelligence problems, such as Computer Vision tasks, the goal is to obtain objective labels. However, in problems such as text a... Read More about Objective Assessment of Subjective Tasks in Crowdsourcing Applications.

Immune-Instructive Polymers Control Macrophage Phenotype and Modulate the Foreign Body Response In Vivo (2020)
Journal Article
Rostam, H. M., Fisher, L. E., Hook, A. L., Burroughs, L., Luckett, J. C., Figueredo, G. P., …Ghaemmaghami, A. M. (2020). Immune-Instructive Polymers Control Macrophage Phenotype and Modulate the Foreign Body Response In Vivo. Matter, 2(6), 1564-1581. https://doi.org/10.1016/j.matt.2020.03.018

© 2020 The Author(s) Implantation of medical devices can result in inflammation. A large library of polymers is screened, and a selection found to promote macrophage differentiation towards pro- or anti-inflammatory phenotypes. The bioinstructive pro... Read More about Immune-Instructive Polymers Control Macrophage Phenotype and Modulate the Foreign Body Response In Vivo.

Sensitizing Scenarios: Sensitizing Designer Teams to Theory (2020)
Conference Proceeding
Waern, A., Rajkowska, P., Johansson, K. B., Back, J., Spence, J., & Løvlie, A. S. (2020). Sensitizing Scenarios: Sensitizing Designer Teams to Theory. In CHI 20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (1–13). https://doi.org/10.1145/3313831.3376620

Concepts and theories that emerge within the social sciences tend to be nuanced, dealing with complex social phenomena. While their relevance to design could be high, it is difficult to make sense of them in design projects, especially when participa... Read More about Sensitizing Scenarios: Sensitizing Designer Teams to Theory.

Parameterised Resource-Bounded ATL (2020)
Conference Proceeding
Alechina, N., Demri, S., & Logan, B. (2020). Parameterised Resource-Bounded ATL. In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (7040-7046). https://doi.org/10.1609/aaai.v34i05.6189

It is often advantageous to be able to extract resource requirements in resource logics of strategic ability, rather than to verify whether a fixed resource requirement is sufficient for achieving a goal. We study Parameterised Resource-Bounded Alter... Read More about Parameterised Resource-Bounded ATL.

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].