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Welcome to OpenAIR@RGU

OpenAIR@RGU is the open access institutional repository of Robert Gordon University. It contains examples of research outputs produced by staff and research students, as well as related information about the university's funded projects and staff research interests. Further information is available in the repository policy. Any questions about submissions to the repository or problems with access to any of its content should be sent to the Publications Team at publications@rgu.ac.uk



Latest Additions

Wear-resistant and adherent nanodiamond composite thin film for durable and sustainable silicon carbide mechanical seals. (2024)
Journal Article
EGIZA, M., RAGAB DIAB, M., ZIA, A.W., MURASAWA, K., FAISAL, N. and YOSHITAKE, T. 2024. Wear-resistant and adherent nanodiamond composite thin film for durable and sustainable silicon carbide mechanical seals. Wear [online], In Press, article number 205394. Available from: https://doi.org/10.1016/j.wear.2024.205394

In response to environmental concerns, there is a growing demand for durable and sustainable mechanical seals, particularly in high-risk industries like chemical, petroleum, and nuclear sectors. This work proposes augmenting the durability and sustai... Read More about Wear-resistant and adherent nanodiamond composite thin film for durable and sustainable silicon carbide mechanical seals..

How to remember the victims of Covid-19: experiences of the First World War. (2022)
Digital Artefact
FOSTER, A.-M. 2022. How to remember the victims of Covid-19: experiences of the First World War. Hosted on Policy paper (History & Policy) [online]. Available from: https://tinyurl.com/3hh422kk

When planning memorial events for those who have died during the Covid-19 pandemic, it is important to recognise that the bulk of memorialisation occurs in domestic spaces. The importance of the home in commemoration was recognised by memorial produc... Read More about How to remember the victims of Covid-19: experiences of the First World War..

Artificial intelligence-based conversational agents used for sustainable fashion: systematic literature review. (2024)
Journal Article
HERNANDEZ MANZO, D.S., JIANG, Y., ELYAN, E. and ISAACS, J. [2024]. Artificial intelligence-based conversational agents used for sustainable fashion: systematic literature review. International journal of human-computer interaction [online], (accepted). To be made available from: https://doi.org/10.1080/10447318.2024.2352920

In the past five years, the textile industry has undergone significant transformations in response to evolving fashion trends and increased consumer garment turnover. To address the environmental impacts of fast fashion, the industry is embracing art... Read More about Artificial intelligence-based conversational agents used for sustainable fashion: systematic literature review..

The impact of big data analytics on the detection of errors and fraud in accounting processes. (2024)
Journal Article
SHALHOOB, H., HALAWANI, B., ALHARBI, M. and BABIKER, I. 2024. The impact of big data analytics on the detection of errors and fraud in accounting processes. RGSA: revista de gestão social e ambiental [online], 18(1), e06115. Available from: https://doi.org/10.24857/rgsa.v18n1-121

This study aims to discuss and investigate the role of big data analytics (BDA) in promoting error detection and preventing fraud in accounting operations. It uses a secondary method of data collection (desk study) to explore the potential impact of... Read More about The impact of big data analytics on the detection of errors and fraud in accounting processes..

Remaining useful life prediction and state of health diagnosis of lithium-ion batteries with multiscale health features based on optimized CatBoost algorithm. (2024)
Journal Article
ZHOU, Y., WANG, S., XIE, Y., ZENG, J. and FERNANDEZ, C. 2024. Remaining useful life prediction and state of health diagnosis of lithium-ion batteries with multiscale health features based on optimized CatBoost algorithm. Energy [online], 300, article number 131575. Available from: https://doi.org/10.1016/j.energy.2024.131575

Due to the large-scale application of electric vehicles, the remaining service life prediction and health status diagnosis of lithium-ion batteries as their power core is particularly important, and the essence of RUL prediction and SOH diagnosis is... Read More about Remaining useful life prediction and state of health diagnosis of lithium-ion batteries with multiscale health features based on optimized CatBoost algorithm..