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Welcome to USIR

Welcome to the University of Salford repository (USIR), an Open Access showcase for the published research output of the university. Our collection contains a wide range of research across multiple formats and subject areas.

Whenever possible, outputs will be made openly available here in full digital format for download, with many under a Creative Commons license. See our Policies for further information https://salford-repository.worktribe.com/policies.

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Latest Additions

Building information modelling (BIM) stage 2 implementation strategy for the construction industry in Malaysia (2019)
Journal Article
Roslan, A., Abd Hamid, Z., Zura, M., Zura Mohd. Zain, M., Mat Kilau, N., Dzulkalnine, N., & Husairi Hussain, A. (2019). Building information modelling (BIM) stage 2 implementation strategy for the construction industry in Malaysia. Malaysian construction research journal, 6(1), 165-173

Building Information Modelling (BIM) within the Malaysian construction industry continue to thrive under the Construction Industry Transformation Programme (CITP) 2016 to 2020. Embracing new technology and modern construction, such as information and... Read More about Building information modelling (BIM) stage 2 implementation strategy for the construction industry in Malaysia.

Using FLO text-messages to enhance health behaviours and self-management of long-term conditions in South-Asian patients (2024)
Journal Article
Chaudhry, T., Ormandy, P., & Vasilica, C. (in press). Using FLO text-messages to enhance health behaviours and self-management of long-term conditions in South-Asian patients. Digital Health, 10, https://doi.org/10.1177/20552076241242558

Objectives: Cultural and communication differences faced by South-Asian (SA) ethnic minority groups have led to challenges in the delivery of health care and complex management of long-term conditions (LTCs). We aim to explore the use of text-messagi... Read More about Using FLO text-messages to enhance health behaviours and self-management of long-term conditions in South-Asian patients.

The Use of AI to Analyze Social Media Attacks for Predictive Analytics (2024)
Journal Article
Adekunle, T., Lawrence, M., Alabi, O., Ebong, G., Ajiboye, G., & Bamisaye, T. (in press). The Use of AI to Analyze Social Media Attacks for Predictive Analytics. #Journal not on list, 9(1), 17-24. https://doi.org/10.11648/j.ajomis.20240901.12

Social engineering, on the other hand, presents weaknesses that are difficult to directly quantify in penetration testing. The majority of expert social engineers utilize phishing and adware tactics to convince victims to provide information voluntar... Read More about The Use of AI to Analyze Social Media Attacks for Predictive Analytics.