Skip to main content

Research Repository

Advanced Search

All Outputs (36)

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.

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.

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).

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.

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.

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.

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.

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.

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.

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. In 2019 IEEE International Conference on Fuzzy Systems (1-7). https://doi.org/10.1109/FUZZ-IEEE.2019.8858821

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.

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 about Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets.

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 about Modelling the home health care nurse scheduling problem for patients with long-term conditions in the UK.

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 about Untangling multi-stakeholder perspectives in digital mental healthcare.