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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

The transition of care between emergency department and primary care: an integrative systematic review. [Protocol] (2022)
Other
HAIN, K., PATERSON, C. and SCARVELL, J.M. [2022]. The transition of care between emergency department and primary care: an integrative systematic review. [Protocol]. PROSPERO [online], item number CRD42022316165. Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022316165

The review will consider studies involving the transition of care from ED to primary care. The follow up care may be provided by GPs, nurses, nurse practitioners, allied health practices, and via communications technologies such as telehealth and vid... Read More about The transition of care between emergency department and primary care: an integrative systematic review. [Protocol].

The transition of care between emergency department and primary care: an integrative systematic review. (2024)
Journal Article
HAIN, K., SCARVELL, J.M. and PATERSON, C. [2024]. The transition of care between emergency department and primary care: an integrative systematic review. Journal of clinical nursing [online], Early View. Available from: https://doi.org/10.1111/jocn.17434

To identify the barriers and enablers of effective transitions of care between the emergency department and primary care providers. Successful patient care transitions from the emergency department to primary care providers are important because this... Read More about The transition of care between emergency department and primary care: an integrative systematic review..

Improved multi-head bi-directional long and short-term memory temporal convolutional network for lithium-ion batteries state of charge estimation in energy storage systems. (2024)
Presentation / Conference Contribution
LI, Y., WANG, S., LIU, D., CUI, Y., FERNANDEZ, C. and BLAABJERG, F. 2024. Improved multi-head bi-directional long and short-term memory temporal convolutional network for lithium-ion batteries state of charge estimation in energy storage systems. In Proceedings of the 25th IEEE (Institute of Electrical and Electronics Engineers) China conference on system simulation technology and its application 2024 (CCSSTA 2024), 21-23 July 2024, Tianjin, China. Piscataway: IEEE [online], pages 581-586. Available from: https://doi.org/10.1109/CCSSTA62096.2024.10691761

Lithium-ion batteries with their high voltage, large capacity, high discharge rate, no memory effect, and green environmental protection advantages are widely used in communication, power stations, backup power, and other energy storage fields. Accur... Read More about Improved multi-head bi-directional long and short-term memory temporal convolutional network for lithium-ion batteries state of charge estimation in energy storage systems..

Remaining useful life prediction hybrid model of lithium-ion battery based on improved GWO-LightGBM. (2024)
Presentation / Conference Contribution
ZHOU, Y., WANG, S., SHEN, X., SOJIB, A.S.M. and FERNANDEZ, C. 2024. Remaining useful life prediction hybrid model of lithium-ion battery based on improved GWO-LightGBM. In Proceedings of the 25th IEEE (Institute of Electrical and Electronics Engineers) China conference on system simulation technology and its application 2024 (CCSSTA 2024), 21-23 July 2024, Tianjin, China. Piscataway: IEEE [online], pages 553-556. Available from: https://doi.org/10.1109/CCSSTA62096.2024.10691744

Lithium-ion batteries, as the core of new energy vehicles, determine the safety of new energy vehicles. Remaining useful life of the battery is the most important parameter, and it is particularly important to estimate the remaining life accurately.... Read More about Remaining useful life prediction hybrid model of lithium-ion battery based on improved GWO-LightGBM..

Optimising for dense deployments in commercial ambient human sensing with WiFi CSI. (2024)
Presentation / Conference Contribution
FORBES, G. and MASSIE, S. 2024. Optimising for dense developments in commercial ambient human sensing with WiFi CSI. In Proceedings of the 30th IEEE (Institute of Electrical and Electronics Engineers) international conference on Embedded and real-time computing systems and applications 2024 (RTCSA 2024), 21-23 August 2024, Sokcho, Republic of Korea. Piscataway: IEEE [online], pages 124-129. Available from: https://doi.org/10.1109/RTCSA62462.2024.00027

WiFi Channel State Information (CSI) is widely-used in research for human sensing applications, yet its actual deployment in commercial real-time applications remains sparse with few examples. Existing demonstrations in research literature predominan... Read More about Optimising for dense deployments in commercial ambient human sensing with WiFi CSI..