All Outputs (38)

Choosing Sample Sizes for Statistical Measures on Interval-Valued Data (2020)
Presentation / Conference Contribution
McCulloch, J., Ellerby, Z., & Wagner, C. (2020, July). Choosing Sample Sizes for Statistical Measures on Interval-Valued Data. Presented at 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Glasgow, United Kingdom

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)
Presentation / Conference Contribution
D'Alterio, P., Garibaldi, J. M., John, R. I., & Wagner, C. (2020, July). Juzzy Constrained: Software for Constrained Interval Type-2 Fuzzy Sets and Systems in Java. Presented at IEEE World Congress on Computational Intelligence (WCCI) 2020, Glasgow, UK

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)
Presentation / Conference Contribution
D'Alterio, P., Garibaldi, J. M., & John, R. I. (2020, July). Constrained Interval Type-2 Fuzzy Classification Systems for Explainable AI (XAI). Presented at IEEE World Congress on Computational Intelligence (WCCI) 2020, Glasgow, UK

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)
Presentation / Conference Contribution
Dann, M., Thangarajah, J., Yao, Y., & Logan, B. (2020, May). Intention-Aware Multiagent Scheduling. Presented at 19th International Conference on Autonomous Agents and Multiagent Systems, Auckland, New Zealand

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)
Presentation / Conference Contribution
Haralabopoulos, G., Tsikandilakis, M., Torres, M. T., & Mcauley, D. (2020, May). Objective Assessment of Subjective Tasks in Crowdsourcing Applications. Presented at Language Resources and Evaluation Conference (LREC 2020), Marseille, France

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)
Presentation / Conference Contribution
Waern, A., Rajkowska, P., Johansson, K. B., Back, J., Spence, J., & Løvlie, A. S. (2020, April). Sensitizing Scenarios: Sensitizing Designer Teams to Theory. Presented at CHI '20: CHI Conference on Human Factors in Computing Systems, Honolulu HI USA

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)
Presentation / Conference Contribution
Alechina, N., Demri, S., & Logan, B. (2020, February). Parameterised Resource-Bounded ATL. Presented at Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, NY, USA

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)
Presentation / Conference Contribution
Pekaslan, D., Wagner, C., Garibaldi, J. M., Marín, L. G., & Sáez, D. (2020, February). Uncertainty-Aware Forecasting of Renewable Energy Sources. Presented at 2020 IEEE International Conference on Big Data and Smart Computing (BigComp), Busan, Korea (South)

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)
Presentation / Conference Contribution
Rostami-Shahrbabaki, M., Bogenberger, K., Safavi, A. A., & Moemeni, A. (2020, January). Intersection SPaT Estimation by means of Single-Source Connected Vehicle Data. Presented at Transportation Research Board (TRB) Annual Meeting 2020, Washington DC, USA

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)
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.

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.

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.

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.

Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets (2019)
Presentation / Conference Contribution
Navarro, J., & Wagner, C. (2019, June). Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets. Presented at 2019 IEEE International Conference on Fuzzy Systems, New Orleans, Lousiana, USA

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.

From Cubes to Twisted Cubes via Graph Morphisms in Type Theory (2019)
Presentation / Conference Contribution
Pinyo, G., & Kraus, N. (2019, June). From Cubes to Twisted Cubes via Graph Morphisms in Type Theory. Paper presented at TYPES 2019, Oslo, Norway

Cube categories are used to encode higher-dimensional categorical structures. They have recently gained significant attention in the community of homotopy type theory and univalent foundations, where types carry the structure of such higher groupoids... Read More about From Cubes to Twisted Cubes via Graph Morphisms in Type Theory.

Modelling the home health care nurse scheduling problem for patients with long-term conditions in the UK (2019)
Presentation / Conference Contribution
He, F., Chaussalet, T., & Qu, R. (2019, June). Modelling the home health care nurse scheduling problem for patients with long-term conditions in the UK. Presented at 33rd International ECMS Conference on Modelling and Simulation (ECMS 2019), Universita degli Studi della Campania, Caserta, Area of Napoli, Italy

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.