Outputs (82)

Deep Adaptive Temporal Pooling for Activity Recognition (2018)
Presentation / Conference Contribution
Song, S., Cheung, N.-M., Chandrasekhar, V., & Mandal, B. (2018, October). Deep Adaptive Temporal Pooling for Activity Recognition. Presented at MM '18: ACM Multimedia Conference, Seoul Republic of Korea

Deep neural networks have recently achieved competitive accuracy for human activity recognition. However, there is room for improvement, especially in modeling of long-term temporal importance and determining the activity relevance of different tempo... Read More about Deep Adaptive Temporal Pooling for Activity Recognition.

A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets (2018)
Presentation / Conference Contribution
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2018, July). A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets. Presented at 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Rio de Janeiro

Similarity measures are useful for reasoning about fuzzy sets. Hence, many classical set-theoretic similarity measures have been extended for comparing fuzzy sets. In previous work, a set-theoretic similarity measure considering the bidirectional sub... Read More about A Bidirectional Subsethood Based Similarity Measure for Fuzzy Sets.

Fault Detection in Steel-Reinforced Concrete Using Echo State Networks (2018)
Presentation / Conference Contribution
Wootton, A. J., Day, C. R., & Haycock, P. W. (2018, July). Fault Detection in Steel-Reinforced Concrete Using Echo State Networks

The cost of maintaining and repairing the world's ageing reinforced concrete infrastructure continues to increase, and is expected to cost the United States economy alone $58 billion by 2020. Consequently, the use of non-destructive testing technolog... Read More about Fault Detection in Steel-Reinforced Concrete Using Echo State Networks.

Nonlinear tubular organ modeling and analysis for tracheal angioedema by swelling-morphoelasticity (2018)
Journal Article
Fu. (2018). Nonlinear tubular organ modeling and analysis for tracheal angioedema by swelling-morphoelasticity. Journal of Engineering Mathematics, 95 - 117. https://doi.org/10.1007/s10665-018-9967-5

We study one of the important human tubular organs, the trachea, under deformation caused by the disease angioedema. This pathology can suddenly increase the volume of the trachea and cause serious breathing difficulty. Two popular theories, the swel... Read More about Nonlinear tubular organ modeling and analysis for tracheal angioedema by swelling-morphoelasticity.

An evaluation of the Gent and Gent-Gent material models using inflation of a plane membrane (2018)
Journal Article
Fu. (2018). An evaluation of the Gent and Gent-Gent material models using inflation of a plane membrane. International Journal of Mechanical Sciences, 39-48. https://doi.org/10.1016/j.ijmecsci.2018.07.035

The Gent material model is the simplest extension of the neo-Hookean material model that can describe the finite extensibility of the polymeric chains comprising the elastomer network. However, it is known that its fitting to experimental results of... Read More about An evaluation of the Gent and Gent-Gent material models using inflation of a plane membrane.

Social Learning in Repeated Cooperation Games in Uncertain Environments (2018)
Journal Article
(2018). Social Learning in Repeated Cooperation Games in Uncertain Environments. Cognitive Systems Research, 24-39. https://doi.org/10.1016/j.cogsys.2018.04.013

Cooperation and social learning are fundamental mechanisms that maintain social organisation among animals and humans. Social institutions can be conceptualised abstractly as cooperation games with social learning. In some ca ses potential cooperatio... Read More about Social Learning in Repeated Cooperation Games in Uncertain Environments.

Reliability Assessment of New and Updated Consumer-Grade Activity and Heart Rate Monitors (2018)
Presentation / Conference Contribution
Oniani, S., Woolley, S. I., Miguel Pires, I., Garcia, N. M., Collins, T., Ledger, S., & Pandyan, A. (2018, September). Reliability Assessment of New and Updated Consumer-Grade Activity and Heart Rate Monitors. Presented at SENSORDEVICES 2018: The Ninth International Conference on Sensor Device Technologies and Applications, Venice

The aim of this paper is to address the need for reliability assessments of new and updated consumer-grade activity and heart rate monitoring devices. This issue is central to the use of these sensor devices and it is particularly important in their... Read More about Reliability Assessment of New and Updated Consumer-Grade Activity and Heart Rate Monitors.

Making a maths degree work for the workplace (2018)
Journal Article
(2018). Making a maths degree work for the workplace. Higher Education Pedagogies, 403-416. https://doi.org/10.1080/23752696.2018.1499420

This article will provide ideas for teaching methods that aim to provide undergraduate students with the experience of working with mathematics in a business context. These teaching methods have been employed at a mainstream U.K. university in a fina... Read More about Making a maths degree work for the workplace.

A reduced model for electrodes-coated dielectric plates (2018)
Journal Article
Fu. (2018). A reduced model for electrodes-coated dielectric plates. International Journal of Non-Linear Mechanics, 60-69. https://doi.org/10.1016/j.ijnonlinmec.2018.09.001

We derive a reduced theory describing the incremental deformation of an electrodes-coated dielectric plate that takes the leading-order thickness effect into account. By focusing on deformations that are symmetric with respect to the mid-plane, a pow... Read More about A reduced model for electrodes-coated dielectric plates.

Deep Residual Network With Subclass Discriminant Analysis For Crowd Behavior Recognition (2018)
Presentation / Conference Contribution
Mandal, B., Fajtl, J., Argyriou, V., Monekosso, D., & Remagnino, P. (2018, October). Deep Residual Network With Subclass Discriminant Analysis For Crowd Behavior Recognition. Presented at 2018 IEEE International Conference on Image Processing, Athens

In this work, we extract rich representations of crowd behavior from video using a fine-tuned deep convolutional neural residual network. Using spatial partitioning trees we create subclasses within the feature maps from each of the crowd behavior a... Read More about Deep Residual Network With Subclass Discriminant Analysis For Crowd Behavior Recognition.