Welcome to OpenAIR@RGU

Young men with intellectual disabilities' perceptions of HPV and HPV vaccine: a qualitative study on how to communicate HPV vaccine information. (2025)
Journal Article
CARNEGIE, E., GRAY-BRUNTON, C., KENNEDY, C., POW, J., WILLIS, D. and WHITTAKER, A. [2025]. Young men with intellectual disabilities' perceptions of HPV and HPV vaccine: a qualitative study on how to communicate HPV vaccine information. Human vaccines and immunotherapeutics [online], (accepted).

The success of vaccination programs relies on acceptance of recommended vaccines by communities and individuals. There is a paucity of evidence regarding how young men with intellectual disabilities actively produce or receive inclusive and accessibl... Read More about Young men with intellectual disabilities' perceptions of HPV and HPV vaccine: a qualitative study on how to communicate HPV vaccine information..

Without fail: muscular adaptations in single set resistance training performed to failure or with repetitions-in-reserve. (2025)
Journal Article
HERMANN, T., MOHAN, A.E., ENES, A., SAPUPPO, M., PIÑERO, A., ZAMANZADEH, A., ROBERTS, M., COLEMAN, M., KORAKAKIS, P.A., WOLF, M., REFALO, M., SWINTON, P.A. and SCHOENFELD, B.J. [2025]. Without fail: muscular adaptations in single set resistance training performed to failure or with repetitions-in-reserve. Medicine and science in sports and exercise [online], (accepted).

This study compared the effects of single-set resistance training performed with maximal effort (failure) vs submaximal effort on muscular adaptations. Forty-two young, resistance-trained men and women were randomly assigned to 1 of 2 parallel groups... Read More about Without fail: muscular adaptations in single set resistance training performed to failure or with repetitions-in-reserve..

Enhanced detection of APT vector lateral movement in organizational networks using lightweight machine learning. (2025)
Journal Article
NICHO, M., ADELAIYE, O., MCDERMOTT, C.D. and GIRIJA, S. 2025. Enhanced detection of APT vector lateral movement in organizational networks using lightweight machine learning. Computers, materials and continua [online], 83(1), pages 281-308. Available from: https://doi.org/10.32604/cmc.2025.059597

The successful penetration of government, corporate, and organizational IT systems by state and non-state actors deploying APT vectors continues at an alarming pace. Advanced Persistent Threat (APT) attacks continue to pose significant challenges for... Read More about Enhanced detection of APT vector lateral movement in organizational networks using lightweight machine learning..

Evaluating cross-domain sentiment analysis using convolutional neural network for Amazon dataset. (2025)
Journal Article
AZIZ, A.A., OTHMAN, A.N., EZENKWU, P. and MADI, E.N. 2025. Evaluating cross-domain sentiment analysis using convolutional neural network for Amazon dataset. Journal of advanced research in applied sciences and engineering technology [online], 63(2), pages 207-214. Available from: https://doi.org/10.37934/araset.63.2.207214

Sentiment Analysis (SA) has garnered extensive research attention over the past decades as a means to comprehend users' attitudes and opinions in various domains. With the proliferation of online communities and the rapid generation of social media c... Read More about Evaluating cross-domain sentiment analysis using convolutional neural network for Amazon dataset..

Assuring privacy of AI-powered community driven Android code vulnerability detection. (2025)
Presentation / Conference Contribution
SENANAYAKE, J., KALUTARAGE, H., PIRAS, L., AL-KADRI, M.O. and PETROVSKI, A. 2025. Assuring privacy of AI-powered community driven Android code vulnerability detection. In Garcia-Alfaro, J., Kalutarage, H., Yanai, N. et al. (eds.) Computer security: ESORICS 2024 international workshops: revised selected papers from the proceedings of eleven international workshops held in conjunction with the 29th European Symposium on Research in Computer Security (ESORICS 2024), 16-20 September 2024, Bydgoszcz, Poland. Part II. Lecture notes in computer science, 15264. Cham: Springer [online], pages 457-476. Available from: https://doi.org/10.1007/978-3-031-82362-6_27

The challenge of training AI models is heightened by the limited availability of data, particularly when public datasets are insufficient. While obtaining data from private sources may seem like a viable solution, privacy concerns often prevent data... Read More about Assuring privacy of AI-powered community driven Android code vulnerability detection..