All Outputs (166)

Come and play: interactive theatre for early years (2018)
Presentation / Conference Contribution
Patel, R., Schnadelbach, H., & Koleva, B. (2018). Come and play: interactive theatre for early years. . https://doi.org/10.1145/3173225.3173251

The convergence of theatre and digital technologies can play a valuable role in theatre for early years, but, how an audience of under-5’s experiences and engages with these spaces is largely unexplored. We present an interactive performance installa... Read More about Come and play: interactive theatre for early years.

Towards a cubical type theory without an interval (2018)
Journal Article
Altenkirch, T., & Kaposi, A. (2018). Towards a cubical type theory without an interval. LIPIcs, 3:1-3:27. https://doi.org/10.4230/LIPIcs.TYPES.2015.3

Following the cubical set model of type theory which validates the univalence axiom, cubical type theories have been developed that interpret the identity type using an interval pretype. These theories start from a geometric view of equality. A proof... Read More about Towards a cubical type theory without an interval.

Riemannian competitive learning for symmetric positive definite matrices clustering (2018)
Journal Article
Zheng, L., Qiu, G., & Huang, J. (2018). Riemannian competitive learning for symmetric positive definite matrices clustering. Neurocomputing, 295, 153-164. https://doi.org/10.1016/j.neucom.2018.03.015

Symmetric positive definite (SPD) matrices have achieved considerable success in numerous computer vision applications including activity recognition, texture classification, and diffusion tensor imaging. Traditional pattern recognition methods devel... Read More about Riemannian competitive learning for symmetric positive definite matrices clustering.

To kit or not to kit: analysing the value of model-based kitting for additive manufacturing (2018)
Journal Article
Khajavi, S. H., Baumers, M., Holmström, J., Özcan, E., Atkin, J., Jackson, W. G., & Li, W. (2018). To kit or not to kit: analysing the value of model-based kitting for additive manufacturing. Computers in Industry, 98, https://doi.org/10.1016/j.compind.2018.01.022

The use of additive manufacturing (AM) for the production of functional parts is increasing. Thus, AM based practices that can reduce supply chain costs gain in importance. We take a forward-looking approach and study how AM can be used more effectiv... Read More about To kit or not to kit: analysing the value of model-based kitting for additive manufacturing.

Responsible Research and Innovation in Industry—Challenges, Insights and Perspectives (2018)
Journal Article
Martinuzzi, A., Blok, V., Brem, A., Stahl, B., & Schönherr, N. (2018). Responsible Research and Innovation in Industry—Challenges, Insights and Perspectives. Sustainability, 10(3), Article 702. https://doi.org/10.3390/su10030702

The responsibility of industry towards society and the environment is a much discussed topic, both in academia and in business. Responsible Research and Innovation (RRI) has recently emerged as a new concept with the potential to advance this discour... Read More about Responsible Research and Innovation in Industry—Challenges, Insights and Perspectives.

Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs (2018)
Journal Article
Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R., & Garibaldi, J. M. (2018). Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs. IEEE/ASME Transactions on Mechatronics, 23(2), 725-734. https://doi.org/10.1109/TMECH.2018.2810947

Input uncertainty, e.g., noise on the on-board camera and inertial measurement unit, in vision-based control of unmanned aerial vehicles (UAVs) is an inevitable problem. In order to handle input uncertainties as well as further analyze the interactio... Read More about Input uncertainty sensitivity enhanced non-singleton fuzzy logic controllers for long-term navigation of quadrotor UAVs.

Corneal nerve fractal dimension: a novel corneal nerve metric for the diagnosis of diabetic sensorimotor polyneuropathy (2018)
Journal Article
Chen, X., Graham, J., Petropoulos, I. N., Ponirakis, G., Asghar, O., & Alam, U. (2018). Corneal nerve fractal dimension: a novel corneal nerve metric for the diagnosis of diabetic sensorimotor polyneuropathy. Investigative Ophthalmology & Visual Science, 59(2), https://doi.org/10.1167/iovs.17-23342

Objective: Corneal confocal microscopy (CCM), an in vivo ophthalmic imaging modality, is a noninvasive and objective imaging biomarker for identifying small nerve fiber damage. We have evaluated the diagnostic performance of previously established CC... Read More about Corneal nerve fractal dimension: a novel corneal nerve metric for the diagnosis of diabetic sensorimotor polyneuropathy.

Smart Brushing for Parallel Coordinates (2018)
Journal Article
Roberts, R. C., Laramee, R. S., Smith, G. A., Brookes, P., & D'Cruze, T. (2019). Smart Brushing for Parallel Coordinates. IEEE Transactions on Visualization and Computer Graphics, 25(3), 1575-1590. https://doi.org/10.1109/tvcg.2018.2808969

The Parallel Coordinates plot is a popular tool for the visualization of high-dimensional data. One of the main challenges when using parallel coordinates is occlusion and overplotting resulting from large data sets. Brushing is a popular approach to... Read More about Smart Brushing for Parallel Coordinates.

Type-2 fuzzy elliptic membership functions for modeling uncertainty (2018)
Journal Article
Kayacan, E., Sarabakha, A., Coupland, S., John, R., & Khanesard, M. A. (2018). Type-2 fuzzy elliptic membership functions for modeling uncertainty. Engineering Applications of Artificial Intelligence, 70, https://doi.org/10.1016/j.engappai.2018.02.004

Whereas type-1 and type-2 membership functions (MFs) are the core of any fuzzy logic system, there are no performance criteria available to evaluate the goodness or correctness of the fuzzy MFs. In this paper, we make extensive analysis in terms of t... Read More about Type-2 fuzzy elliptic membership functions for modeling uncertainty.

Provenance Network Analytics: An approach to data analytics using data provenance (2018)
Journal Article
Huynh, T. D., Ebden, M., Fischer, J., Roberts, S., & Moreau, L. (2018). Provenance Network Analytics: An approach to data analytics using data provenance. Data Mining and Knowledge Discovery, 32(3), 708-735. https://doi.org/10.1007/s10618-017-0549-3

Provenance network analytics is a novel data analytics approach that helps infer properties of data, such as quality or importance, from their provenance. Instead of analysing application data, which are typically domain-dependent, it analyses the da... Read More about Provenance Network Analytics: An approach to data analytics using data provenance.

Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome (2018)
Journal Article
Liu, J.-F., Dineen, R. A., Avula, S., Chambers, T., Dutta, M., Jaspan, T., …Walker, D. A. (in press). Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome. British Journal of Neurosurgery, https://doi.org/10.1080/02688697.2018.1431204

BACKGROUND: Despite previous identification of pre-operative clinical and radiological predictors of post-operative paediatric cerebellar mutism syndrome (CMS), a unifying pre-operative risk stratification model for use during surgical consent is cur... Read More about Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome.

Hybrid learning for interval type-2 intuitionistic fuzzy logic systems as applied to identification and prediction problems (2018)
Journal Article
Eyoh, I., John, R., de Maere, G., & Kayacan, E. (2018). Hybrid learning for interval type-2 intuitionistic fuzzy logic systems as applied to identification and prediction problems. IEEE Transactions on Fuzzy Systems, 26(5), 2672-2685. https://doi.org/10.1109/TFUZZ.2018.2803751

This paper presents a novel application of a hybrid learning approach to the optimisation of membership and non-membership functions of a newly developed interval type-2 intuitionistic fuzzy logic system (IT2 IFLS) of a Takagi-Sugeno-Kang (TSK) fuzzy... Read More about Hybrid learning for interval type-2 intuitionistic fuzzy logic systems as applied to identification and prediction problems.

Synthesis of orchestrations of transducers for manufacturing (2018)
Presentation / Conference Contribution
De Giacomo, G., Vardi, M. Y., Felli, P., Alechina, N., & Logan, B. (2018). Synthesis of orchestrations of transducers for manufacturing.

In this paper, we model manufacturing processes and facilities as transducers (automata with output). The problem of whether a given manufacturing process can be realized by a given set of manufacturing resources can then be stated as an orchestratio... Read More about Synthesis of orchestrations of transducers for manufacturing.

On the complexity of resource-bounded logics (2018)
Journal Article
Alechina, N., Bulling, N., Demri, S., & Logan, B. S. (2018). On the complexity of resource-bounded logics. Theoretical Computer Science, 750, 69-100. https://doi.org/10.1016/j.tcs.2018.01.019

We revisit decidability results for resource-bounded logics and use decision problems on vector addition systems with states (VASS) in order to establish complexity characterisations of (decidable) model checking problems. We show that the model chec... Read More about On the complexity of resource-bounded logics.

Fuzzy C-means-based scenario bundling for stochastic service network design (2018)
Presentation / Conference Contribution
Jiang, X., Bai, R., Landa-Silva, D., & Aickelin, U. (2018). Fuzzy C-means-based scenario bundling for stochastic service network design. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings (1-8). https://doi.org/10.1109/SSCI.2017.8280905

Stochastic service network designs with uncertain demand represented by a set of scenarios can be modelled as a large-scale two-stage stochastic mixed-integer program (SMIP). The progressive hedging algorithm (PHA) is a decomposition method for solvi... Read More about Fuzzy C-means-based scenario bundling for stochastic service network design.

Preface (2018)
Journal Article
Hanzalek, Z., Kendall, G., McCollum, B., Sucha, P., & Berghe, G. V. (2018). Preface. Journal of Scheduling, 21, 129-130. https://doi.org/10.1007/s10951-018-0557-1

This is a Preface to a special of the journal that contains 8 selected papers from the 2015 Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA) that was held in Prague, Czech Republic (25–28 August 2015).

A Method for Evaluating Options for Motif Detection in Electricity Meter Data (2018)
Journal Article
Dent, I., Craig, T., Aickelin, U., & Rodden, T. (2018). A Method for Evaluating Options for Motif Detection in Electricity Meter Data. International Journal of Data Science, 16(1), 1-28. https://doi.org/10.6339/jds.201801_16%281%29.0001

Investigation of household electricity usage patterns, and matching the patterns to behaviours, is an important area of research given the centrality of such patterns in addressing the needs of the electricity industry. Additional knowledge of househ... Read More about A Method for Evaluating Options for Motif Detection in Electricity Meter Data.

Building accountability into the Internet of Things: the IoT Databox model (2018)
Journal Article
Crabtree, A., Lodge, T., Colley, J., Greenhalgh, C., Glover, K., Haddadi, H., …McAuley, D. (2018). Building accountability into the Internet of Things: the IoT Databox model. Journal of Reliable Intelligent Environments, 4(1), 39-55. https://doi.org/10.1007/s40860-018-0054-5

© 2018, The Author(s). This paper outlines the IoT Databox model as a means of making the Internet of Things (IoT) accountable to individuals. Accountability is a key to building consumer trust and is mandated by the European Union’s general data pro... Read More about Building accountability into the Internet of Things: the IoT Databox model.

Using goal programming on estimated Pareto fronts to solve multiobjective problems (2018)
Presentation / Conference Contribution
Pinheiro, R. L., Landa-Silva, D., Laesanklang, W., & Constantino, A. A. (2018). Using goal programming on estimated Pareto fronts to solve multiobjective problems. In n Proceedings of the 7th International Conference on Operations Research and Enterprise Systems ICORES - Volume 1 (132-143). https://doi.org/10.5220/0006718901320143

Modern multiobjective algorithms can be computationally inefficient in producing good approximation sets for highly constrained many-objective problems. Such problems are common in real-world applications where decision-makers need to assess multiple... Read More about Using goal programming on estimated Pareto fronts to solve multiobjective problems.

Programming agent deliberation using procedural reflection (2018)
Journal Article
Leask, S., & Logan, B. (in press). Programming agent deliberation using procedural reflection. Fundamenta Informaticae, 158, https://doi.org/10.3233/FI-2018-1643

A key advantage of BDI-based approaches to agent programming, is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However, while state-of-the-art BDI-based agent programming languages allow th... Read More about Programming agent deliberation using procedural reflection.