All Outputs (1084)

Strengthening student engagement: evaluating the role of the digital skills agenda in higher education. (2019)
Presentation / Conference
LAWANI, A., SINGH, A., MCNEIL, A., DURACK, B. and KALUTARAGE, H. 2019. Strengthening student engagement: evaluating the role of the digital skills agenda in higher education. Presented at the 2019 Department for the Enhancement of Learning, Teaching and Access (DELTA) learning and teaching conference (LTC 2019): learning without borders, 2 May 2019, Aberdeen, UK.

Digital technology can contribute to all three areas of the TEF: teaching quality; learning environment; and student outcomes (Davies S, Mullan and Feldman 2017). Digital skills are helpful in designing enhanced and effective learning activities (Cop... Read More about Strengthening student engagement: evaluating the role of the digital skills agenda in higher education..

Coastal wetland mapping with sentinel-2 MSI imagery based on gravitational optimized multilayer perceptron and morphological attribute profiles. (2019)
Journal Article
ZHANG, A., SUN, G., MA, P., JIA, X., REN, J., HUANG, H. and ZHANG, X. 2019. Coastal wetland mapping with sentinel-2 MSI imagery based on gravitational optimized multilayer perceptron and morphological attribute profiles. Remote sensing [online], 11(8), article 952. Available from: https://doi.org/10.3390/rs11080952

Coastal wetland mapping plays an essential role in monitoring climate change, the hydrological cycle, and water resources. In this study, a novel classification framework based on the gravitational optimized multilayer perceptron classifier and exten... Read More about Coastal wetland mapping with sentinel-2 MSI imagery based on gravitational optimized multilayer perceptron and morphological attribute profiles..

Implementing GDPR in the Charity Sector: A Case Study (2019)
Conference Proceeding
HENRIKSEN-BULMER, J., FAILY, S. and JEARY, S. 2019. Implementing GDPR in the charity sector: a case study. In Kosta, E., Pierson, J., Slamanig, D., Fischer-Hübner, S. and Krenn, S. (eds.) Privacy and identity management: fairness, accountability and transparency in the age of Big Data: revised selected papers from the 13th International Federation for Information Processing Working Groups 9.2, 9.6/11.7, 11.6, Special Interest Group 9.2.2 international summer school (IFIP Summer School 2018), 20-24 August 2018, Vienna, Austria. IFIP advances in information and communication technology, 547. Cham: Springer [online], pages 173-188. Available from: https://doi.org/10.1007/978-3-030-16744-8_12

Due to their organisational characteristics, many charities are poorly prepared for the General Data Protection Regulation (GDPR). We present an exemplar process for implementing GDPR and the DPIA Data Wheel, a DPIA framework devised as part of the c... Read More about Implementing GDPR in the Charity Sector: A Case Study.

Building extraction from high-resolution aerial imagery using a generative adversarial network with spatial and channel attention mechanisms. (2019)
Journal Article
PAN, X., YANG, F., GAO, L., CHEN, Z., ZHANG, B., FAN, H. and REN, J. 2019. Building extraction from high-resolution aerial imagery using a generative adversarial network with spatial and channel attention mechanisms. Remote sensing [online], 11(8), article 917. Available from: https://doi.org/10.3390/rs11080917

Segmentation of high-resolution remote sensing images is an important challenge with wide practical applications. The increasing spatial resolution provides fine details for image segmentation but also incurs segmentation ambiguities. In this paper,... Read More about Building extraction from high-resolution aerial imagery using a generative adversarial network with spatial and channel attention mechanisms..

Understanding factors influencing public transport passengers' pre-travel information-seeking behaviour. (2019)
Journal Article
YEBOAH, G., COTTRILL, C.D., NELSON, J.D., CORSAR, D., MARKOVIC, M. and EDWARDS, P. 2019. Understanding factors influencing public transport passengers’ pre-travel information-seeking behaviour. Public transport [online], 11(1), pages 135-158. Available from: https://doi.org/10.1007/s12469-019-00198-w

This paper investigates factors influencing public transport passengers’ pre-travel information-seeking behaviours in a British urban environment. Public transport traveller surveys were conducted to better understand the journey stages at which info... Read More about Understanding factors influencing public transport passengers' pre-travel information-seeking behaviour..

Minimality and simplicity of rules for the internet-of-things. (2019)
Conference Proceeding
PANARETOS, A., CORSAR, D. and VASCONCELOS, W.W. 2019. Minimality and simplicity of rules for the internet-of things. In Lujak, M. (ed.) Agreement technologies: revised selected papers from the 6th International conference on agreement technologies (AT 2018), 6-7 December 2018, Bergen, Norway. Lecture notes in computer science, 11327. Cham: Springer [online], pages 64-72. Available from: https://doi.org/10.1007/978-3-030-17294-7_5

Rule-based systems have been increasing in popularity in recent years. They allow for easier handling of both simple and complicated problems utilising a set of rules created in various ways (e.g., manually, or (semi-) automatically, via, say, machin... Read More about Minimality and simplicity of rules for the internet-of-things..

Flood risk management in sponge cities: the role of integrated simulation and 3D visualization. (2019)
Journal Article
WANG, C., HOU, J., MILLER, D., BROWN, I. and JIANG, Y. 2019. Flood risk management in sponge cities: the role of integrated simulation and 3D visualization. International journal of disaster risk reduction [online], 39, article ID 101139. Available from: https://doi.org/10.1016/j.ijdrr.2019.101139

The Sponge City concept has been promoted as a major programme of work to address increasing flood risk in urban areas, in combination with wider benefits for water resources and urban renewal. However, realization of the concept requires collaborati... Read More about Flood risk management in sponge cities: the role of integrated simulation and 3D visualization..

A weighted multiple classifier framework based on random projection. (2019)
Journal Article
NGUYEN, T.T., DANG, M.T., LIEW, A. W.-C. and BEZDEK, J.C. 2019. A weighted multiple classifier framework based on random projection. Information science [online], 490, pages 36-58. Available from: https://doi.org/10.1016/j.ins.2019.03.067

In this paper, we propose a weighted multiple classifier framework based on random projections. Similar to the mechanism of other homogeneous ensemble methods, the base classifiers in our approach are obtained by a learning algorithm on different tra... Read More about A weighted multiple classifier framework based on random projection..

A new type of eye movement model based on recurrent neural networks for simulating the gaze behavior of human reading. (2019)
Journal Article
WANG, X., ZHAO, X. and REN, J. 2019. A new type of eye movement model based on recurrent neural networks for simulating the gaze behavior of human reading. Complexity [online], 2019: complex deep learning and evolutionary computing models in computer vision, article ID 8641074. Available from: https://doi.org/10.1155/2019/8641074

Traditional eye movement models are based on psychological assumptions and empirical data that are not able to simulate eye movement on previously unseen text data. To address this problem, a new type of eye movement model is presented and tested in... Read More about A new type of eye movement model based on recurrent neural networks for simulating the gaze behavior of human reading..

EEG-based brain-computer interfaces using motor-imagery: techniques and challenges. (2019)
Journal Article
PADFIELD, N., ZABALZA, J., ZHAO, H., MASERO, V. and REN, J. 2019. EEG-based brain-computer interfaces using motor-imagery: techniques and challenges. Sensors [online], 19(6), article 1423. Available from: https://doi.org/10.3390/s19061423

Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those using motor-imagery (MI) data, have the potential to become groundbreaking technologies in both clinical and entertainment settings. MI data is generated when a s... Read More about EEG-based brain-computer interfaces using motor-imagery: techniques and challenges..

A review of digital video tampering: from simple editing to full synthesis. (2019)
Journal Article
JOHNSTON, P. and ELYAN, E. 2019. A review of digital video tampering: from simple editing to full synthesis. Digital investigation [online], 29, pages 67-81. Available from: https://doi.org/10.1016/j.diin.2019.03.006

Video tampering methods have witnessed considerable progress in recent years. This is partly due to the rapid development of advanced deep learning methods, and also due to the large volume of video footage that is now in the public domain. Historica... Read More about A review of digital video tampering: from simple editing to full synthesis..

Local block multilayer sparse extreme learning machine for effective feature extraction and classification of hyperspectral images. (2019)
Journal Article
CAO, F., YANG, Z., REN, J., CHEN, W., HAN, G. and SHEN, Y. 2019. Local block multilayer sparse extreme learning machine for effective feature extraction and classification of hyperspectral images. IEEE transactions on geoscience and remote sensing [online], 57(8), pages 5580-5594. Available from: https://doi.org/10.1109/tgrs.2019.2900509

Although extreme learning machines (ELM) have been successfully applied for the classification of hyperspectral images (HSIs), they still suffer from three main drawbacks. These include: 1) ineffective feature extraction (FE) in HSIs due to a single... Read More about Local block multilayer sparse extreme learning machine for effective feature extraction and classification of hyperspectral images..

Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments: a case study. (2019)
Journal Article
ZABALZA, J., FEI, Z., WONG, C., YAN, Y., MINEO, C., YANG, E., RODDEN, T., MEHNEN, J., PHAM, Q.-C. and REN, J. 2019. Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments: a case study. Sensors [online], 19(6), article 1354. Available from: https://doi.org/10.3390/s19061354

Traditional industry is seeing an increasing demand for more autonomous and flexible manufacturing in unstructured settings, a shift away from the fixed, isolated workspaces where robots perform predefined actions repetitively. This work presents a c... Read More about Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments: a case study..

Fall prediction using behavioural modelling from sensor data in smart homes. (2019)
Journal Article
FORBES, G., MASSIE, S. and CRAW, S. 2020. Fall prediction using behavioural modelling from sensor data in smart homes. Artificial intelligence review [online], 53(2), pages 1071-1091. Available from: https://doi.org/10.1007/s10462-019-09687-7

The number of methods for identifying potential fall risk is growing as the rate of elderly fallers continues to rise in the UK. Assessments for identifying risk of falling are usually performed in hospitals and other laboratory environments, however... Read More about Fall prediction using behavioural modelling from sensor data in smart homes..

A lossless online Bayesian classifier. (2019)
Journal Article
NGUYEN, T.T.T., NGUYEN, T.T., SHARMA, R. and LIEW, A. W.-C. 2019. A lossless online Bayesian classifier. Information sciences [online], 489, pages 1-17. Available from: https://doi.org/10.1016/j.ins.2019.03.031

We are living in a world progressively driven by data. Besides the issue that big data cannot be entirely stored in the main memory as required by traditional offline learning methods, the problem of learning data that can only be collected over time... Read More about A lossless online Bayesian classifier..

Weakly supervised deep semantic segmentation using CNN and ELM with semantic candidate regions. (2019)
Journal Article
XU, X., LI, G., XIE, G., REN, J. and XIE, X. 2019. Weakly supervised deep semantic segmentation using CNN and ELM with semantic candidate regions. Complexity [online], 2019: complex deep learning and evolutionary computing models in computer vision, article 9180391. Available from: https://doi.org/10.1155/2019/9180391

The task of semantic segmentation is to obtain strong pixel-level annotations for each pixel in the image. For fully supervised semantic segmentation, the task is achieved by a segmentation model trained using pixel-level annotations. However, the pi... Read More about Weakly supervised deep semantic segmentation using CNN and ELM with semantic candidate regions..

Phronesis, authentic learning and the solution of open-ended problems in computer science. (2019)
Conference Proceeding
MCDERMOTT, R., ZARB, M., BALLEW, W., DANIELS, M. and ISOMÖTTÖNEN, V. 2018. Phronesis, authentic learning and the solution of open-ended problems in computer science. In Proceedings of the 48th Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference (FIE 2018): fostering innovation through diversity, 3-6 October 2018, San Jose, USA. Piscataway: IEEE [online], article ID 8658512. Available from: https://doi.org/10.1109/fie.2018.8658512

One of the most significant changes in Higher Education pedagogy that has occurred over the past fifty years is the idea that university students should not just be taught theoretical subject knowledge but should engage with practical aspects of thei... Read More about Phronesis, authentic learning and the solution of open-ended problems in computer science..

Why are we here? The educational value model (EVM) as a framework to investigate the role of students' professional identity development. (2019)
Conference Proceeding
NYLÉN, A., DANIELS, M., PEARS, A., CAJANDER, Å., MCDERMOTT, R. and ISOMÖTTÖNEN, V. 2018. Why are we here? The educational value nodel (EVM) as a framework to investigate the role of students’ professional identity development. In Proceedings of the 48th Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference 2018 (FIE 2018): fostering innovation through diversity, 3-6 October 2018, San Jose, USA. Piscataway: IEEE [online], article ID 8659055. Available from: https://doi.org/10.1109/fie.2018.8659055

Education can be seen as a preparation for a future profession, where some educational programs very clearly prepare their students for a certain profession, e.g. plumber, nurse and architect. The possible professions for students following education... Read More about Why are we here? The educational value model (EVM) as a framework to investigate the role of students' professional identity development..

Investigation into the use of learning agreements to enhance stakeholder engagement and promote self-efficacy in computing education. (2019)
Conference Proceeding
BALLEW, W., MCDERMOTT, R., ZARB, M., DANIELS, M. and CLEAR, T. 2018. Investigation into the use of learning agreements to enhance stakeholder engagement and promote self-efficacy in computing education. In Proceedings of the 48th Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education 2018 (FIE 2018): fostering innovation through diversity, 3-6 October 2018, San Jose, USA. Piscataway: IEEE [online], article ID 865138. Available from: https://doi.org/10.1109/fie.2018.8659138

We examine controversial issues surrounding the locus of control in the implementation of learning agreements, plans or contracts, in the context of the U.K. university-level Graduate Apprenticeship scheme. We begin by giving an account of the stakeh... Read More about Investigation into the use of learning agreements to enhance stakeholder engagement and promote self-efficacy in computing education..

Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images. (2019)
Journal Article
SUN, H., REN, J., ZHAO, H., YAN, Y., ZABALZA, J. and MARSHALL, S. 2019. Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images. Remote sensing [online], 11(5), article 536. Available from: https://doi.org/10.3390/rs11050536

To improve the performance of the sparse representation classification (SRC), we propose a superpixel-based feature specific sparse representation framework (SPFS-SRC) for spectral-spatial classification of hyperspectral images (HSI) at superpixel le... Read More about Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images..