Outputs (150)

Enhancing the drilling efficiency through the application of machine learning and optimization algorithm. (2023)
Journal Article
BOUKREDERA, F.S., YOUCEFI, M.R., HADJADJ, A., EZENKWU, C.P., VAZIRI, V. and APHALE, S.S. 2023. Enhancing the drilling efficiency through the application of machine learning and optimization algorithm. Engineering applications of artificial intelligence [online], 126(part C), article 107035. Available from: https://doi.org/10.1016/j.engappai.2023.107035

This article presents a novel Artificial Intelligence (AI) workflow to enhance drilling performance by mitigating the adverse impact of drill-string vibrations on drilling efficiency. The study employs three supervised machine learning (ML) algorithm... Read More about Enhancing the drilling efficiency through the application of machine learning and optimization algorithm..

CBR driven interactive explainable AI. (2023)
Presentation / Conference Contribution
WIJEKOON, A., WIRATUNGA, N., MARTIN, K., CORSAR, D., NKISI-ORJI, I., PALIHAWADANA, C., BRIDGE, D., PRADEEP, P., AGUDO, B.D. and CARO-MARTÍNEZ, M. 2023. CBR driven interactive explainable AI. In MASSIE, S. and CHAKRABORTI, S. (eds.) 2023. Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023, (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages169-184. Available from: https://doi.org/10.1007/978-3-031-40177-0_11

Explainable AI (XAI) can greatly enhance user trust and satisfaction in AI-assisted decision-making processes. Numerous explanation techniques (explainers) exist in the literature, and recent findings suggest that addressing multiple user needs requi... Read More about CBR driven interactive explainable AI..

Failure-driven transformational case reuse of explanation strategies in CloodCBR. (2023)
Presentation / Conference Contribution
NKISI-ORJI, I., PALIHAWADANA, C., WIRATUNGA, N., WIJEKOON, A. and CORSAR, D. 2023. Failure-driven transformational case reuse of explanation strategies in CloodCBR. In Massie, S. and Chakraborti, S. (eds.) Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023 (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages 279-293. Available from: https://doi.org/10.1007/978-3-031-40177-0_18

In this paper, we propose a novel approach to improve problem-solving efficiency through the reuse of case solutions. Specifically, we introduce the concept of failure-driven transformational case reuse of explanation strategies, which involves trans... Read More about Failure-driven transformational case reuse of explanation strategies in CloodCBR..

Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning (ICCBR 2023). (2023)
Presentation / Conference Contribution
MASSIE, S. and CHAKRABORTI, S. (eds.) 2023. Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science, 14141. Cham: Springer [online]. Available from: https://doi.org/10.1007/978-3-031-40177-0

This volume contains the papers presented at the 31st International Conference on Case-Based Reasoning (ICCBR 2023), which was held on July 17–20, 2023, at Robert Gordon University in Aberdeen, Scotland, UK. ICCBR is the premier annual meeting of the... Read More about Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning (ICCBR 2023)..

A cross-sectional study of discipline-based self-perceived digital literacy competencies of nursing students. (2023)
Journal Article
MARTZOUKOU, K., LUDERS, E.S., MAIR, J., KOSTAGIOLAS, P., JOHNSON, N., WORK, F. and FULTON, C. 2024. A cross-sectional study of discipline-based self-perceived digital literacy competencies of nursing students. Journal of advanced nursing [online], 80(2), pages 656-672. Available from: https://doi.org/10.1111/jan.15801

This study offers an empirical exploration of self-assessed digital competencies of students, most of whom studied in nursing courses, using a discipline-based self-assessment survey tool. A range of digital competencies were explored: information an... Read More about A cross-sectional study of discipline-based self-perceived digital literacy competencies of nursing students..

CBR assisted context-aware surface realisation for data-to-text generation. (2023)
Presentation / Conference Contribution
UPADHYAY, A. and MASSIE, S. 2023. CBR assisted context-aware surface realisation for data-to-text generation. In MASSIE, S. and CHAKRABORTI, S. (eds.) 2023. Case-based reasoning research and development: proceedings of the 31st International conference on case-based reasoning 2023, (ICCBR 2023), 17-20 July 2023, Aberdeen, UK. Lecture notes in computer science (LNCS), 14141. Cham: Springer [online], pages 34-49. Available from: https://doi.org/10.1007/978-3-031-40177-0_3

Current state-of-the-art neural systems for Data-to-Text Generation (D2T) struggle to generate content from past events with interesting insights. This is because these systems have limited access to historic data and can also hallucinate inaccurate... Read More about CBR assisted context-aware surface realisation for data-to-text generation..

AGREE: a feature attribution aggregation framework to address explainer disagreements with alignment metrics. (2023)
Presentation / Conference Contribution
PIRIE, C., WIRATUNGA, N., WIJEKOON, A. and MORENO-GARCIA, C.F. 2023. AGREE: a feature attribution aggregation framework to address explainer disagreements with alignment metrics. In Malburg, L. and Verma, D. (eds.) Workshop proceedings of the 31st International conference on case-based reasoning (ICCBR-WS 2023), 17 July 2023, Aberdeen, UK. CEUR workshop proceedings, 3438. Aachen: CEUR-WS [online], pages 184-199. Available from: https://ceur-ws.org/Vol-3438/paper_14.pdf

As deep learning models become increasingly complex, practitioners are relying more on post hoc explanation methods to understand the decisions of black-box learners. However, there is growing concern about the reliability of feature attribution expl... Read More about AGREE: a feature attribution aggregation framework to address explainer disagreements with alignment metrics..

Machine learning for risk stratification of diabetic foot ulcers using biomarkers. (2023)
Presentation / Conference Contribution
MARTIN, K., UPADHYAY, A., WIJEKOON, A., WIRATUNGA, N. and MASSIE, S. 2023. Machine learning for risk stratification of diabetic foot ulcers using biomarkers. In Mikyška, J., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational science: proceedings of the 23rd International conference on computational science 2023 (ICCS 2023): computing at the cutting edge of science (ICCS 2023), 3-5 July 2023, Prague, Czech Republic: [virtual event]. Lecture notes in computer science, 14075. Cham: Springer [online], part III, pages 153-161. Available from: https://doi.org/10.1007/978-3-031-36024-4_11

Development of a Diabetic Foot Ulcer (DFU) causes a sharp decline in a patient's health and quality of life. The process of risk stratification is crucial for informing the care that a patient should receive to help manage their Diabetes before an ul... Read More about Machine learning for risk stratification of diabetic foot ulcers using biomarkers..

Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections. (2023)
Presentation / Conference Contribution
TORAL-QUIJAS, L.A., ELYAN, E., MORENO-GARCÍA, C.F. and STANDER, J. 2023. Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections. In Iliadis, L, Maglogiannis, I., Alonso, S., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 24th International conference on engineering applications of neural networks (EAAAI/EANN 2023), 14-17 June 2023, León, Spain. Communications in computer and information science, 1826. Cham: Springer [online], pages 217-226. Available from: https://doi.org/10.1007/978-3-031-34204-2_19

Inspecting circumferential welds in caissons is a critical task for ensuring the safety and reliability of structures in the offshore industry. However, identifying and classifying different types of circumferential welds can be challenging in subsea... Read More about Digital transformation for offshore assets: a deep learning framework for weld classification in remote visual inspections..

Towards autonomous developmental artificial intelligence: case study for explainable AI. (2023)
Presentation / Conference Contribution
STARKEY, A. and EZENKWU, C.P. 2023. Towards autonomous developmental artificial intelligence: case study for explainable AI. In Maglogiannis, I., Iliadis, L., MacIntyre, J. and Dominguez, M. (eds.) Artificial intelligence applications and innovations: proceedings of the 19th IFIP (International Federation for Information Processing) WG 12.5 Artificial intelligence applications and innovations international conference (AIAI 2023), 14-17 June 2023, León, Spain. IFIP advances in information and communication technology, 676. Cham: Springer [online], pages 94-105. Available from: https://doi.org/10.1007/978-3-031-34107-6_8

State-of-the-art autonomous AI algorithms such as reinforcement learning and deep learning techniques suffer from high computational complexity, poor explainability ability, and a limited capacity for incremental adaptive learning. In response to the... Read More about Towards autonomous developmental artificial intelligence: case study for explainable AI..

iSee: intelligent sharing of explanation experiences. (2023)
Presentation / Conference Contribution
MARTIN, K., WIJEKOON, A., WIRATUNGA, N., PALIHAWADANA, C., NKISI-ORJI, I., CORSAR, D., DÍAZ-AGUDO, B., RECIO-GARCÍA, J.A., CARO-MARTÍNEZ, M., BRIDGE, D., PRADEEP, P., LIRET, A. and FLEISCH, B. 2022. iSee: intelligent sharing of explanation experiences. In Reuss, P. and Schönborn, J. (eds.) Workshop proceedings of the 30th International conference on case-based reasoning (ICCBR-WS 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3389. Aachen: CEUR-WS [online], pages 231-232. Available from: https://ceur-ws.org/Vol-3389/ICCBR_2022_Workshop_paper_83.pdf

The right to an explanation of the decision reached by a machine learning (ML) model is now an EU regulation. However, different system stakeholders may have different background knowledge, competencies and goals, thus requiring different kinds of ex... Read More about iSee: intelligent sharing of explanation experiences..

Introducing Clood CBR: a cloud based CBR framework. (2023)
Presentation / Conference Contribution
PALIHAWADANA, C., NKISI-ORJI, I., WIRATUNGA, N., CORSAR, D. and WIJEKOON, A. 2022. Introducing Clood CBR: a cloud based CBR framework. In Reuss, P. and Schönborn, J. (eds.) Workshop proceedings of the 30th International conference on case-based reasoning (ICCBR-WS 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3389. Aachen: CEUR-WS [online], pages 233-234. Available from: https://ceur-ws.org/Vol-3389/ICCBR_2022_Workshop_paper_108.pdf

CBR applications have been deployed in a wide range of sectors, from pharmaceuticals; to defence and aerospace to IoT and transportation, to poetry and music generation; for example. However, a majority of applications have been built using monolithi... Read More about Introducing Clood CBR: a cloud based CBR framework..

An archetypal determination of mobile cloud computing for emergency applications using decision tree algorithm. (2023)
Journal Article
HAI, T., ZHOU, J., LU, Y., JAWAWI, D., WANG, D., SELVARAJAN, S., MANOHARAN, H. and IBEKE, E. 2023. An archetypal determination of mobile cloud computing for emergency applications using decision tree algorithm. Journal of cloud computing [online], 12, article 73. Available from: https://doi.org/10.1186/s13677-023-00449-z

Numerous users are experiencing unsafe communications due to the growth of big network mediums, where no node communication is detected in emergency scenarios. Many people find it difficult to communicate in emergency situations as a result of such c... Read More about An archetypal determination of mobile cloud computing for emergency applications using decision tree algorithm..

iSee: intelligent sharing of explanation experience of users for users. (2023)
Presentation / Conference Contribution
WIJEKOON, A., WIRATUNGA, N., PALIHAWADANA, C., NKISI-ORJI, I., CORSAR, D. and MARTIN, K. 2023. iSee: intelligent sharing of explanation experience of users for users. In IUI '23 companion: companion proceedings of the 28th Intelligent user interfaces international conference 2023 (IUI 2023), 27-31 March 2023, Sydney, Australia. New York: ACM [online], pages 79-82. Available from: https://doi.org/10.1145/3581754.3584137

The right to obtain an explanation of the decision reached by an Artificial Intelligence (AI) model is now an EU regulation. Different stakeholders of an AI system (e.g. managers, developers, auditors, etc.) may have different background knowledge, c... Read More about iSee: intelligent sharing of explanation experience of users for users..

Automated well-log pattern alignment and depth-matching techniques: an empirical review and recommendations. (2023)
Journal Article
EZENKWU, C.P., GUNTORO, J., STARKEY, A., VAZIRI, V. and ADDARIO, M. 2023. Automated well-log pattern alignment and depth-matching techniques: an empirical review and recommendations. Petrophysics [online], 64(1), pages 115-129. Available from: https://doi.org/10.30632/PJV64N1-2023a9

Well logging has been an integral part of decision making at different stages (drilling, completion, production, abandonment) of a well's history. However, the traditional human-reliant approach to well-log interpretation, which has been the most com... Read More about Automated well-log pattern alignment and depth-matching techniques: an empirical review and recommendations..

Achieving online dialogic learning using breakout rooms. (2023)
Journal Article
DOUGLAS, S. 2023. Achieving online dialogic learning using breakout rooms. Research in learning technology [online], 31, article number 2882. Available from: https://doi.org/10.25304/rlt.v31.2882

Breakout rooms are an increasingly used tool in online teaching. This study uses Laurillard's (2013) Conversational Framework to evaluate the effectiveness of breakout rooms in achieving learning through peer-to-peer dialogue in large-scale teaching.... Read More about Achieving online dialogic learning using breakout rooms..

The intersection of fashion, immersive technology and sustainability: a literature review. (2023)
Journal Article
MESJAR, L., CROSS, K., JIANG, Y. and STEED, J. 2023. The intersection of fashion, immersive technology and sustainability: a literature review. Sustainability [online], 15(4), article number 3761. Available from: https://doi.org/10.3390/su15043761

Fashion industry emissions, resource use and waste are attracting increasing consumer and government attention, with broad agreement that a new approach is required along the supply chain. Following the COVID-19 pandemic, a move to digitalisation fac... Read More about The intersection of fashion, immersive technology and sustainability: a literature review..

Augmenting sustainable fashion on Instagram. (2023)
Journal Article
MARCELLA-HOOD, M. 2023. Augmenting sustainable fashion on Instagram. Sustainability [online], 15(4), article number 3609. Available from: https://doi.org/10.3390/su15043609

Media discourse surrounding fashion and sustainability tends to be negative, emphasising the problems that exist across the various stages of the lifecycle of a garment. Although consumers are increasingly aware of at least some of the issues surroun... Read More about Augmenting sustainable fashion on Instagram..

Sentiment computation of UK-originated Covid-19 vaccine Tweets: a chronological analysis and news effect. (2023)
Journal Article
AMUJO, O., IBEKE, E., FUZI, R., OGARA, U. and IWENDI, C. 2023. Sentiment computation of UK-originated Covid-19 vaccine Tweets: a chronological analysis and news effect. Sustainability [online], 15(4), article 3212. Available from: https://doi.org/10.3390/su15043212

This study aimed to analyse public sentiments of UK-originated tweets related to COVID-19 vaccines, and it applied six chronological time periods, between January and December 2021. The dates were related to six BBC news reports about the most signif... Read More about Sentiment computation of UK-originated Covid-19 vaccine Tweets: a chronological analysis and news effect..

Why would anyone join the "nofap" movement? (2023)
Newspaper / Magazine
SMITH, D.S. 2023. Why would anyone join the "nofap" movement? Current affairs [online], 30 January 2023. Available from: https://www.currentaffairs.org/news/2023/01/making-sense-of-nofap-culture

In this contribution to "Current Affairs", the author explains the theory behind the "nofap" challenge, in which participants don't masturbate or watch porn. It has grown into a large online movement. The author explores the gender politics of these... Read More about Why would anyone join the "nofap" movement?.