All Outputs (98)

Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform. (2021)
Journal Article
WANG, J., YANG, M., DING, Z., ZHENG, Q., WANG, D., KPALMA, K. and REN, J. 2021. Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform. Sensors [online], 21(20), article 6720. Available from: https://doi.org/10.3390/s21206720

Variations in the quantity of plankton impact the entire marine ecosystem. It is of great significance to accurately assess the dynamic evolution of the plankton for monitoring the marine environment and global climate change. In this paper, a novel... Read More about Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform..

A data-driven decision support tool for offshore oil and gas decommissioning. (2021)
Journal Article
VUTTIPITTAYAMONGKOL, P., TUNG, A. and ELYAN, E. 2021. A data-driven decision support tool for offshore oil and gas decommissioning. IEEE access [online], 9, pages 137063-137082. Available from: https://doi.org/10.1109/ACCESS.2021.3117891

A growing number of oil and gas offshore infrastructures across the globe are approaching the end of their operational life. It is a major challenge for the industry to plan and make a decision on the decommissioning as the processes are resource exh... Read More about A data-driven decision support tool for offshore oil and gas decommissioning..

Harris Tweed: a glocal case study. (2021)
Journal Article
CROSS, K., STEED, J. and JIANG, Y. 2021. Harris Tweed: a global case study. Fashion, style and popular culture [online], 8(4), pages 475-494. Available from: https://doi.org/10.1386/fspc_00102_1

Fast and effectively disposable fashion has seen clothing reduced to transient items, worn for a short period of time then discarded. This has pushed down prices, moving textile and clothing production to low-cost labour countries and decimating the... Read More about Harris Tweed: a glocal case study..

A next-generation telemedicine and health advice system. (2021)
Conference Proceeding
SIDDIQUI, S., HOPGOOD, A., GOOD, A., GEGOV, A., HOSSAIN, E., RAHMAN, W., FERDOUS, R., ARIFEEN, M. and KHAN, Z. 2021. A next-generation telemedicine and health advice system. In Yang, X.-S., Sherratt, S., Dey, N. and Joshi, A. (eds.) Proceedings of sixth International congress on information and communication technology, 25-26 February 2021, London, UK. Lecture notes in networks and systems, 236. Singapore: Springer [online], pages 981-989. Available from: https://doi.org/10.1007/978-981-16-2380-6_87

This project aims to create a real-time health advice platform andtelemedicine system that can reach healthcare providers and healthcare deprived people. A pragmatic approach is being used to understand the research problem of this study, which allow... Read More about A next-generation telemedicine and health advice system..

Actionable feature discovery in counterfactuals using feature relevance explainers. (2021)
Conference Proceeding
WIRATUNGA, N., WIJEKOON, A., NKISI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. Actionable feature discovery in counterfactuals using feature relevance explainers. In Borck, H., Eisenstadt, V., Sánchez-Ruiz, A. and Floyd, M. (eds.) Workshop proceedings of the 29th International conference on case-based reasoning (ICCBR-WS 2021), 13-16 September 2021, [virtual event]. CEUR workshop proceedings, 3017. Aachen: CEUR-WS [online], pages 63-74. Available from: http://ceur-ws.org/Vol-3017/101.pdf

Counterfactual explanations focus on 'actionable knowledge' to help end-users understand how a Machine Learning model outcome could be changed to a more desirable outcome. For this purpose a counterfactual explainer needs to be able to reason with si... Read More about Actionable feature discovery in counterfactuals using feature relevance explainers..

Agents United: an open platform for multi-agent conversational systems. (2021)
Conference Proceeding
BEINEMA, T., DAVISON, D., REIDSMA, D. et al. 2021. Agents United: an open platform for multi-agent conversational systems. In Proceedings of 21st ACM (Association for Computing Machinery) Intelligent virtual agents international conference 2021 (IVA '21), 14-17 September 2021, [virtual conference]. New York: ACM [online], pages 17-24. Available from: https://doi.org/10.1145/3472306.3478352

The development of applications with intelligent virtual agents (IVA) often comes with integration of multiple complex components. In this article we present the Agents United Platform: an open source platform that researchers and developers can use... Read More about Agents United: an open platform for multi-agent conversational systems..

A case-based approach to data-to-text generation. (2021)
Conference Proceeding
UPADHYAY, A., MASSIE, S., SINGH, R.K., GUPTA, G. and OJHA, M. 2021. A case-based approach to data-to-text generation. In Sánchez-Ruiz, A.A. and Floyd, M.W. (eds.) Case-based reasoning research and development: proceedings of 29th International conference case-based reasoning 2021 (ICCBR 2021), 13-16 September 2021, Salamanca, Spain. Lecture notes in computer science (LNCS), 12877. Cham: Springer [online], pages 232-247. Available from: https://doi.org/10.1007/978-3-030-86957-1_16

Traditional Data-to-Text Generation (D2T) systems utilise carefully crafted domain specific rules and templates to generate high quality accurate texts. More recent approaches use neural systems to learn domain rules from the training data to produce... Read More about A case-based approach to data-to-text generation..

SpaSSA: superpixelwise adaptive SSA for unsupervised spatial-spectral feature extraction in hyperspectral image. (2021)
Journal Article
SUN, G., FU, H., REN, J., ZHANG, A., ZABALZA, J., JIA, X. and ZHAO, H. 2022. SpaSSA: superpixelwise adaptive SSA for unsupervised spatial-spectral feature extraction in hyperspectral image. IEEE transactions on cybernetics [online], 52(7), pages 6158-6169. Available from: https://doi.org/10.1109/TCYB.2021.3104100

Singular spectral analysis (SSA) has recently been successfully applied to feature extraction in hyperspectral image (HSI), including conventional (1-D) SSA in spectral domain and 2-D SSA in spatial domain. However, there are some drawbacks, such as... Read More about SpaSSA: superpixelwise adaptive SSA for unsupervised spatial-spectral feature extraction in hyperspectral image..

A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams. (2021)
Conference Proceeding
TORAL, L., MORENO-GARCIA, C.F., ELYAN, E. and MEMON, S. 2021. A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams. In Barney Smith, E.H. and Pal, U. (eds.) Document analysis and recognition: ICDAR 2021 workshops, part II: proceedings of 16th International conference on document analysis and recognition 2021 (ICDAR 2021), 5-10 September 2021, Lausanne, Switzerland. Lecture notes in computer science, 12917. Cham: Springer [online], pages 268-276. Available from: https://doi.org/10.1007/978-3-030-86159-9_18

Corrosion circuit mark up in engineering drawings is one of the most crucial tasks performed by engineers. This process is currently done manually, which can result in errors and misinterpretations depending on the person assigned for the task. In th... Read More about A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams..

Towards a declarative approach to constructing dialogue games. (2021)
Conference Proceeding
SNAITH, M. and WELLS, S. 2021. Towards a declarative approach to constructing dialogue games. In Grasso, F., Green, N.L., Schneider, J. and Wells, S. (eds.) Proceedings of the 21st Workshop on computational models on natural argument (CMNA 2021), 2-3 September 2021, [virtual conference]. CEUR workshop proceedings, 2937. Aachen: CEUR-WS [online], pages 9-18. Available from: http://ceur-ws.org/Vol-2937/paper2.pdf

In this paper we sketch a new approach to the development of dialogue games that builds upon the knowledge gained from several decades of dialogue game research across a variety of communities and which leverages the capabilities of the Dialogue Game... Read More about Towards a declarative approach to constructing dialogue games..

Cost-effective and efficient detection of autism from screening test data using light gradient boosting machine. (2021)
Conference Proceeding
KAMMA, S.P., BANO, S., NIHARIKA, G.L., CHILUKURI, G.S. and GHANTA, D. 2022. Cost-effective and efficient detection of autism from screening test data using light gradient boosting machine. In Raj, J.S., Palanisamy, R., Perikos, I. and Shi, Y. (eds.) Proceedings of the 4th International conference on intelligent sustainable systems (ICISS 2021), 26-27 February 2021, Tirunelveli, India. Lecture notes in networks and systems, 213. Singapore: Springer [online], pages 777-789. Available from: https://doi.org/10.1007/978-981-16-2422-3_61

Autism spectrum disorder (ASD) is a developmental disorder that affects the brain. Autism constrains a person’s ability to interact and communicate with others. The cause of autism, in general, is unknown though genetics does play a role in the manif... Read More about Cost-effective and efficient detection of autism from screening test data using light gradient boosting machine..

Multi-head attention-based long short-term memory for depression detection from speech. (2021)
Journal Article
ZHAO, Y., LIANG, Z., DU, J., ZHANG, L., LIU, C. and ZHAO, L. 2021. Multi-head attention-based long short-term memory for depression detection from speech. Frontiers in neurorobotics [online], 15, article 684037. Available from: https://doi.org/10.3389/fnbot.2021.684037

Depression is a mental disorder that threatens the health and normal life of people. Hence, it is essential to provide an effective way to detect depression. However, research on depression detection mainly focuses on utilizing different parallel fea... Read More about Multi-head attention-based long short-term memory for depression detection from speech..

An application of FEA and machine learning for the prediction and optimisation of casing buckling and deformation responses in shale gas wells in an in-situ operation. (2021)
Journal Article
MOHAMMED, A.I., BARTLETT, M., OYENEYIN, B., KAYVANTASH, K. and NJUGUNA, J. 2021. An application of FEA and machine learning for the prediction and optimisation of casing buckling and deformation responses in shale gas wells in an in-situ operation. Journal of natural gas science and engineering [online], 95, article 104221. Available from: https://doi.org/10.1016/j.jngse.2021.104221

This paper proposes a novel way to study the casing structural integrity using two approaches of finite element analysis (FEA) and machine learning. The approach in this study is unique, as it captures the pertinent parameters influencing the casing... Read More about An application of FEA and machine learning for the prediction and optimisation of casing buckling and deformation responses in shale gas wells in an in-situ operation..

Sparse learning of band power features with genetic channel selection for effective classification of EEG signals. (2021)
Journal Article
PADFIELD, N., REN, J., MURRAY, P. and ZHAO, H. 2021. Sparse learning of band power features with genetic channel selection for effective classification of EEG signals. Neurocomputing [online], 463, pages 566-579. Available from: https://doi.org/10.1016/j.neucom.2021.08.067

In this paper, we present a genetic algorithm (GA) based band power feature sparse learning (SL) approach for classification of electroencephalogram (EEG) (GABSLEEG) in motor imagery (MI) based brain-computer interfacing (BCI). The band power in the... Read More about Sparse learning of band power features with genetic channel selection for effective classification of EEG signals..

Artificial intelligence surgery: how do we get to autonomous actions in surgery? (2021)
Journal Article
GUMBS, A.A., FRIGERIO, I., SPOLVERATO, G., CRONER, R., ILLANES, A., CHOUILLARD, E. and ELYAN, E. 2021. Artificial intelligence surgery: how do we get to autonomous actions in surgery? Sensors [online], 21(16), article 5526. Available from: https://doi.org/10.3390/s21165526

Most surgeons are skeptical as to the feasibility of autonomous actions in surgery. Interestingly, many examples of autonomous actions already exist and have been around for years. Since the beginning of this millennium, the field of artificial intel... Read More about Artificial intelligence surgery: how do we get to autonomous actions in surgery?.

Visualising personas as goal models to find security tensions. (2021)
Journal Article
FAILY, S., IACOB, C., ALI, R. and KI-ARIES, D. 2021. Visualising personas as goal models to find security tensions. Information and computer security [online], 29(5), pages 787-815. Available from: https://doi.org/10.1108/ICS-03-2021-0035

This paper aims to present a tool-supported approach for visualising personas as social goal models, which can subsequently be used to identify security tensions. The authors devised an approach to partially automate the construction of social goal m... Read More about Visualising personas as goal models to find security tensions..

Spectral-spatial self-attention networks for hyperspectral image classification. (2021)
Journal Article
ZHANG, X., SUN, G., JIA, X., WU, L., ZHANG, A., REN, J., FU, H. and YAO, Y. 2022. Spectral-spatial self-attention networks for hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 60, article 5512115. Available from: https://doi.org/10.1109/TGRS.2021.3102143

This study presents a spectral-spatial self-attention network (SSSAN) for classification of hyperspectral images (HSIs), which can adaptively integrate local features with long-range dependencies related to the pixel to be classified. Specifically, i... Read More about Spectral-spatial self-attention networks for hyperspectral image classification..

Deep neural networks based error level analysis for lossless image compression based forgery detection. (2021)
Conference Proceeding
SRI, C.G., BANO, S., DEEPIKA, T., KOLA, N. and PRANATHI, Y.L. 2021. Deep neural networks based error level analysis for lossless image compression based forgery detection. In Proceedings of the 2021 International conference on intelligent technologies (CONIT 2021), 25-27 June 2021, Hubli, India. Piscataway: IEEE [online]. Available from: https://doi.org/10.1109/CONIT51480.2021.9498357

The proposed model is implemented in deep learning based on counterfeit feature extraction and Error Level Analysis (ELA) techniques. Error level analysis is used to improve the efficiency of distinguishing copy-move images produced by Deep Fake from... Read More about Deep neural networks based error level analysis for lossless image compression based forgery detection..

Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. (2021)
Journal Article
SANDAL, L.F., BACH, K., ØVERÅS, C.K., WIRATUNGA, N., COOPER, K, et al. 2021. Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial. JAMA internal medicine [online], 181(10), pages 1288-1296. Available from: https://doi.org/10.1001/jamainternmed.2021.4097

Importance: Lower back pain (LBP) is a prevalent and challenging condition in primary care. The effectiveness of an individually tailored self-management support tool delivered via a smartphone app has not been rigorously tested. Objective: To invest... Read More about Effectiveness of app-delivered, tailored self-management support for adults with lower back pain-related disability: a selfBACK randomized clinical trial..

Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. (2021)
Journal Article
ACEVES-MARTINS, A., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. Nutrition reviews [online], 80(3), pages 544-560. Available from: https://doi.org/10.1093/nutrit/nuab041

Context: Prevalence of overweight and obesity has been rising in the past 3 decades among Mexican children and adolescents. Objective: To systematically review experimental studies evaluating interventions to treat obesity in Mexican children and ado... Read More about Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis..