All Outputs (393)

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..

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..

Autonomous supervision and optimization of product quality in a multi-stage manufacturing process based on self-adaptive prediction models. (2019)
Journal Article
LUGHOFER, E., ZAVOIANU, A.-C., POLLAK, R., PRATAMA, M., MEYER-HEYE, P., ZÖRRER, H., EITZINGER, C. and RADAUER, T. 2019. Autonomous supervision and optimization of product quality in a multi-stage manufacturing process based on self-adaptive prediction models. Journal of process control [online], 76, pages 27-45. Available from: https://doi.org/10.1016/j.jprocont.2019.02.005

In modern manufacturing facilities, there are basically two essential phases for assuring high production quality with low (or even zero) defects and waste in order to save costs for companies. The first phase concerns the early recognition of potent... Read More about Autonomous supervision and optimization of product quality in a multi-stage manufacturing process based on self-adaptive prediction models..

Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. (2019)
Journal Article
MCDERMOTT, C.D., ISAACS, J.P. and PETROVSKI, A.V. 2019. Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks. Informatics [online], 6(1), article 8. Available from: https://doi.org/10.3390/informatics6010008

The growth of the Internet of Things (IoT), and demand for low-cost, easy-to-deploy devices, has led to the production of swathes of insecure Internet-connected devices. Many can be exploited and leveraged to perform large-scale attacks on the Intern... Read More about Evaluating awareness and perception of botnet activity within consumer Internet-of-Things (IoT) networks..

Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation. (2019)
Journal Article
OCHEI, L.C., PETROVSKI, A. and BASS, J.M. 2019. Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation. Journal of cloud computing [online], 8, article 1. Available from: https://doi.org/10.1186/s13677-018-0124-5

One of the challenges of deploying multitenant cloud-hosted services that are designed to use (or be integrated with) several components is how to implement the required degree of isolation between the components when there is a change in the workloa... Read More about Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation..

Privacy risk assessment in context: a meta-model based on contextual integrity. (2019)
Journal Article
HENRIKSEN-BULMER, J., FAILY, S. and JEARY, S. 2019. Privacy risk assessment in context: a meta-model based on contextual integrity. Computers and security [online], 82, pages 270-283. Available from: https://doi.org/10.1016/j.cose.2019.01.003

Publishing data in open format is a growing trend, particularly for public bodies who have a legal obligation to make data available as open data. We look at the privacy implications of publishing open data and, in particular, how organisations can m... Read More about Privacy risk assessment in context: a meta-model based on contextual integrity..

Searching for global employability: can students capitalize on enabling learning environments? (2019)
Journal Article
ISOMÖTTÖNEN, V., DANIELS, M., CAJANDER, A., PEARS, A. and MCDERMOT, R. 2019. Searching for global employability: can students capitalize on enabling learning environments? ACM transactions on computing education, 19(2), article ID 11. Available from: https://doi.org/10.1145/3277568

Literature on global employability signifies “enabling” learning environments where students encounter ill-formed and open-ended problems and are required to adapt and be creative. Varying forms of “projects,” co-located and distributed, have populat... Read More about Searching for global employability: can students capitalize on enabling learning environments?.

Multi-label classification via label correlation and first order feature dependance in a data stream. (2019)
Journal Article
NGUYEN, T.T., NGUYEN, T.T.T., LUONG, A.V., NGUYEN, Q.V.H., LIEW, A.W.-C. and STANTIC, B. 2019. Multi-label classification via label correlation and first order feature dependance in a data stream. Pattern recognition [online], 90, pages 35-51. Available from: https://doi.org/10.1016/j.patcog.2019.01.007

Many batch learning algorithms have been introduced for offline multi-label classification (MLC) over the years. However, the increasing data volume in many applications such as social networks, sensor networks, and traffic monitoring has posed many... Read More about Multi-label classification via label correlation and first order feature dependance in a data stream..

Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. (2018)
Journal Article
OCHEI, L.C., BASS, J.M. and PETROVSKI, A. 2018. Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis. Journal of cloud computing [online], 7, article ID 22. Available from: https://doi.org/10.1186/s13677-018-0121-8

A challenge, when implementing multi-tenancy in a cloud-hosted software service, is how to ensure that the performance and resource consumption of one tenant does not adversely affect other tenants. Software designers and architects must achieve an o... Read More about Degrees of tenant isolation for cloud-hosted software services: a cross-case analysis..

X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks. (2018)
Journal Article
AL-KADRI, M.O., AIJAZ, A. and NALLANATHAN, A. 2019. X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks. IEEE wireless communications [online], 26(2), pages 70-77. Available from: https://doi.org/10.1109/MWC.2017.1700243

The recent developments in self-interference (SI) cancellation techniques have led to the practical realization of FD radios that can perform simultaneous transmission and reception. FD technology is attractive for various legacy communications stand... Read More about X-FDR: a cross-layer routing protocol for multi-hop full-duplex wireless networks..

Real-time relative permeability prediction using deep learning. (2018)
Journal Article
ARIGBE, O.D., OYENEYIN, M.B., ARANA, I. and GHAZI, M.D. 2019. Real-time relative permeability prediction using deep learning. Journal of petroleum exploration and production technologies [online], 9(2), pages 1271-1284. Available from: https://doi.org/10.1007/s13202-018-0578-5

A review of the existing two and three phase relative permeability correlations shows a lot of pitfalls and restrictions imposed by (a) their assumptions (b) generalization ability and (c) difficulty with updating in real time for different reservoir... Read More about Real-time relative permeability prediction using deep learning..

Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP). (2018)
Journal Article
ANI, M., OLUYEMI, G., PETROVSKI, A. and REZAEI-GOMARI, S. 2019. Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP). Journal of petroleum science and engineering [online], 174, pages 833-843. Available from: https://doi.org/10.1016/j.petrol.2018.11.024

The selection of an optimal model from a set of multiple realizations for dynamic reservoir modelling and production forecasts has been a persistent issue for reservoir modelers and decision makers. Current evidence has shown that many presumably goo... Read More about Ranking of geostatistical models and uncertainty quantification using signal detection principle (SDP)..

Emotion-aware polarity lexicons for Twitter sentiment analysis. (2018)
Journal Article
BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and P, D. 2021. Emotion-aware polarity lexicons for Twitter sentiment analysis. Expert systems [online], 38(7): artificial intelligence/EDMA 2017, article e12332. Available from: https://doi.org/10.1111/exsy.12332

Theoretical frameworks in psychology map the relationships between emotions and sentiments. In this paper we study the role of such mapping for computational emotion detection from text (e.g. social media) with a aim to understand the usefulness of a... Read More about Emotion-aware polarity lexicons for Twitter sentiment analysis..

Combining heterogeneous classifiers via granular prototypes. (2018)
Journal Article
NGUYEN, T.T., NGUYEN, M.P., PHAM, X.C., LIEW, A. W.-C. and PEDRYCZ, W. 2018. Combining heterogeneous classifiers via granular prototypes. Applied soft computing [online], 73, pages 795-815. Available from: https://doi.org/10.1016/j.asoc.2018.09.021

In this study, a novel framework to combine multiple classifiers in an ensemble system is introduced. Here we exploit the concept of information granule to construct granular prototypes for each class on the outputs of an ensemble of base classifiers... Read More about Combining heterogeneous classifiers via granular prototypes..