Outputs (30)

Developments in virtual learning environments and the global workplace. (2021)
Book
SWARTZ, S., BARBOSA, B., CRAWFORD, I. and LUCK, S. (eds.) 2021. Developments in virtual learning environments and the global workplace. Hershey, PA: IGI Global [online]. Available from: https://doi.org/10.4018/978-1-7998-7331-0

Although institutions of higher education have recognized the need for preparing their graduates for a digitalized, global workplace, these efforts have been sporadic, individualized, and varied from discipline to discipline. Nevertheless, over the p... Read More about Developments in virtual learning environments and the global workplace..

DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods. (2021)
Presentation / Conference Contribution
WIRATUNGA, N., WIJEKOON, A., NKISI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods. In Proceedings of 33rd IEEE (Institute of Electrical and Electronics Engineers) International conference on tools with artificial intelligence 2021 (ICTAI 2021), 1-3 November 2021, Washington, USA [virtual conference]. Piscataway: IEEE [online], pages 1466-1473. Available from: https://doi.org/10.1109/ICTAI52525.2021.00233

Counterfactual explanations focus on 'actionable knowledge' to help end-users understand how a machine learning outcome could be changed to a more desirable outcome. For this purpose a counterfactual explainer needs to discover input dependencies tha... Read More about DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods..

Learning arts organisations: innovation through a poetics of relation. (2021)
Journal Article
GULARI, M.N. and FREMANTLE, C. 2021. Learning arts organisations: innovation through a poetics of relation. Arts [online], 10(4): eight hours labour, eight hours recreation, eight hours rest: what we will need is more time for what we will (?), article 83. Available from: https://doi.org/10.3390/arts10040083

Arts organisations have had to reimagine their ways of working, as a result of the Covid-19 pandemic. The pandemic has severely challenged the venue-based sectors and exposed the fragility of the existing business model of the ‘receiving house'. We u... Read More about Learning arts organisations: innovation through a poetics of relation..

An optimized machine learning and big data approach to crime detection. (2021)
Journal Article
PALANIVINAYAGAM, A., GOPAL, S.S., BHATTACHARYA, S., ANUMBE, N., IBEKE, E. and BIAMBA, C. 2021. An optimized machine learning and big data approach to crime detection. Wireless communications and mobile computing [online], 2021, article ID 5291528. Available from: https://doi.org/10.1155/2021/5291528

Crime detection is one of the most important research applications in machine learning. Identifying and reducing crime rates is crucial to developing a healthy society. Big Data techniques are applied to collect and analyse data: determine the requir... Read More about An optimized machine learning and big data approach to crime detection..

Recurrent neural network and reinforcement learning model for COVID-19 prediction. (2021)
Journal Article
KUMAR, R.L., KHAN, F., DIN, S., BAND, S.S., MOSAVI, A. and IBEKE, E. 2021. Recurrent neural network and reinforcement learning model for COVID-19 prediction. Frontiers in public health [online], 9, article 744100. Available from: https://doi.org/10.3389/fpubh.2021.744100

Detection and prediction of the novel Coronavirus present new challenges for the medical research community due to its widespread across the globe. Methods driven by Artificial Intelligence can help predict specific parameters, hazards, and outcomes... Read More about Recurrent neural network and reinforcement learning model for COVID-19 prediction..

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 study of university law students’ self-perceived digital competences. (2021)
Journal Article
MARTZOUKOU, K., KOSTAGIOLAS, P., LAVRANOS, C., LAUTERBACH, T. and FULTON, C. 2022. A study of university law students' self-perceived digital competences. Journal of librarianship and information science [online], 54(4), pages 751-769. Available from: https://doi.org/10.1177/09610006211048004

The concept of digital competences incorporates the effective use of constantly-changing digital tools and media for learning and performing digital tasks, digital behaviours (such as online communication, teamwork, ethical sharing of information), a... Read More about A study of university law students’ self-perceived digital competences..

Optimal coordination of PSS and SSSC controllers in power system using ant colony optimization algorithm. (2021)
Journal Article
KAMARPOSHTI, M.A., COLAK, I., IWENDI, C., BAND, S.S. and IBEKE, E. 2022. Optimal coordination of PSS and SSSC controllers in power system using ant colony optimization algorithm. Journal of circuits, systems and computers [online], 31(4), article 2250060. Available from: https://doi.org/10.1142/S0218126622500608

Volatility leads to disruption in synchronism between generators of a continuous system. The frequency of the volatility is usually between a few tenths of Hz to several Hz. This volatility is sometimes divided into two types, local and interregional... Read More about Optimal coordination of PSS and SSSC controllers in power system using ant colony optimization algorithm..

Tackling pandemics in smart cities using machine learning architecture. (2021)
Journal Article
NGABO, D., DONG, W., IBEKE, E., IWENDI, C. and MASABO, E. 2021. Tackling pandemics in smart cities using machine learning architecture. Mathematical biosciences and engineering [online], 18(6): the advances in cybersecurity theory and applications, pages 8444-8461. Available from: https://doi.org/10.3934/mbe.2021418

With the recent advancement in analytic techniques and the increasing generation of healthcare data, artificial intelligence (AI) is reinventing the healthcare system for tackling pandemics securely in smart cities. AI tools continue register numerou... Read More about Tackling pandemics in smart cities using machine learning architecture..

Pointer-based item-to-item collaborative filtering recommendation system using a machine learning model. (2021)
Journal Article
IWENDI, C., IBEKE, E., EGGONI, H., VELAGALA, S. and SRIVASTAVA, G. 2022. Pointer-based item-to-item collaborative filtering recommendation system using a machine learning model. International journal of information technology and decision making [online], 21(1), pages 463-484. Available from: https://doi.org/10.1142/S0219622021500619

The creation of digital marketing has enabled companies to adopt personalized item recommendations for their customers. This process keeps them ahead of the competition. One of the techniques used in item recommendation is known as item-based recomme... Read More about Pointer-based item-to-item collaborative filtering recommendation system using a machine learning model..

Actionable feature discovery in counterfactuals using feature relevance explainers. (2021)
Presentation / Conference Contribution
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..

A case-based approach to data-to-text generation. (2021)
Presentation / Conference Contribution
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..

Women's use and abuse of the news media during the COVID-19 pandemic on Mumsnet. (2021)
Journal Article
PEDERSEN, S. and BURNETT, S. 2022. Women's use and abuse of the news media during the COVID-19 pandemic on Mumsnet. Digital journalism [online], 10(6): the Coronavirus pandemic and the transformation of (digital) journalism, pages 1098-1114. Available from: https://doi.org/10.1080/21670811.2021.1967768

This article analyses news sources used by women to discuss the COVID-19 pandemic on the UK parenting website Mumsnet. By using a non-political online ‘third space’ aimed at women, Mumsnetters are able to avoid the aggression women face when they att... Read More about Women's use and abuse of the news media during the COVID-19 pandemic on Mumsnet..

A deep learning digitisation framework to mark up corrosion circuits in piping and instrumentation diagrams. (2021)
Presentation / Conference Contribution
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..

Class-decomposition and augmentation for imbalanced data sentiment analysis. (2021)
Presentation / Conference Contribution
MORENO-GARCIA, C.F., JAYNE, C. and ELYAN, E. 2021. Class-decomposition and augmentation for imbalanced data sentiment analysis. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533603. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533603

Significant progress has been made in the area of text classification and natural language processing. However, like many other datasets from across different domains, text-based datasets may suffer from class-imbalance. This problem leads to model's... Read More about Class-decomposition and augmentation for imbalanced data sentiment analysis..

Re-thinking digital skill development post COVID 19: views from the workplace. (2021)
Presentation / Conference Contribution
CRAWFORD, I. 2021. Re-thinking digital skill development post COVID 19: views from the workplace. Presented at the 13th international conference on Education and new learning technologies 2021 (EDULEARN 2021), 5-6 July 2021, [virtual conference].

As a result of the revolutionary change in remote and online working practices triggered by the pandemic in 2020, the need for universities to prepare students for the international, virtual, workplace has never been greater. To remain competitive in... Read More about Re-thinking digital skill development post COVID 19: views from the workplace..

Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. (2021)
Presentation / Conference Contribution
DANG, T., NGUYEN, T.T., MORENO-GARCIA, C.F., ELYAN, E. and MCCALL, J. 2021. Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. In Proceeding of 2021 IEEE (Institute of electrical and electronics engineers) Congress on evolutionary computation (CEC 2021), 28 June - 1 July 2021, Kraków, Poland : [virtual conference]. Piscataway: IEEE [online], pages 744-751. Available from: https://doi.org/10.1109/CEC45853.2021.9504929

In recent years, deep learning has rapidly become a method of choice for segmentation of medical images. Deep neural architectures such as UNet and FPN have achieved high performances on many medical datasets. However, medical image analysis algorith... Read More about Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation..

Image pre-processing and segmentation for real-time subsea corrosion inspection. (2021)
Presentation / Conference Contribution
PIRIE, C. and MORENO-GARCIA, C.F. 2021. Image pre-processing and segmentation for real-time subsea corrosion inspection. In Iliadis, L., Macintyre, J., Jayne, C. and Pimenidis, E. (eds.). Proceedings of the 22nd Engineering applications of neural networks conference (EANN2021), 25-27 June 2021, Halkidiki, Greece. Proceedings of the International Neural Networks Society (INNS), 3. Cham: Springer [online], pages 220-231. Available from: https://doi.org/10.1007/978-3-030-80568-5_19

Inspection engineering is a highly important field in the Oil & Gas sector for analysing the health of offshore assets. Corrosion, a naturally occurring phenomenon, arises as a result of a chemical reaction between a metal and its environment, causin... Read More about Image pre-processing and segmentation for real-time subsea corrosion inspection..

Counterfactual explanations for student outcome prediction with Moodle footprints. (2021)
Presentation / Conference Contribution
WIJEKOON, A., WIRATUNGA, N., NKILSI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. Counterfactual explanations for student outcome prediction with Moodle footprints. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 1, pages 1-8. Available from: http://ceur-ws.org/Vol-2894/short1.pdf

Counterfactual explanations focus on “actionable knowledge” to help end-users understand how a machine learning outcome could be changed to one that is more desirable. For this purpose a counterfactual explainer needs to be able to reason with simila... Read More about Counterfactual explanations for student outcome prediction with Moodle footprints..

E-learning and COVID-19: the Nigerian experience: challenges of teaching technical courses in tertiary institutions. (2021)
Presentation / Conference Contribution
UGOCHUKWU-IBE, I.M. and IBEKE, E. 2021. E-learning and COVID-19: the Nigerian experience: challenges of teaching technical courses in tertiary institutions. In Xhina, E. and Hoxha, K. (eds.) Recent trends and applications in computer science and information technology: proceedings of 4th Recent trends and applications in computer science and information technology international conference 2021 (RTA-CSIT 2021), 21-22 May 2021 [virtual conference]. CEUR workshop proceedings, 2872. Aachen: CEUR-WS [online], pages 46-51. Available from: http://ceur-ws.org/Vol-2872/paper07.pdf

This paper examines the challenges of teaching technical courses through e-learning in Nigerian tertiary institutions during the COVID-19 pandemic lockdown. The COVID-19 pandemic has widespread after-effect on education systems all over the world, wi... Read More about E-learning and COVID-19: the Nigerian experience: challenges of teaching technical courses in tertiary institutions..