Browse by University of Suffolk Author
Razzaq, Abdul, Zhang, Tao, Numair, Muhammad, Alreshidi, Abdulrahman, Jing, Cheng, Aljaloud, Abdulaziz, Ghayyur, Shahbaz, A, K., Ahmed, Salman and Qurat Ul Ain, Mumtaz (2024) Transforming academic assessment: The metaverse-backed Web 3 secure exam system. Computer Applications in Engineering Education. ISSN 1099-0542
Mohamed Mohideen, Mohamed Azarudheen, Nadeem, Shahroz, Hardy, James, Ali, Haider, Tariq, Umair Ullah, Sabrina, Fariza, Waqar, Muhammad and Ahmed, Salman (2024) Behind the code: identifying zero-day exploits in WordPress. Future Internet, 16 (7). ISSN 1999-5903
Ahmed, Salman (2024) An evaluation of BERT applied for AIOps. In: Tommy Flowers Network – Posters, 6-8 March 2024, Adastral Park Knight Studio.
Ahmed, Salman, Singh, Muskaan, Bhattacharyya, Saugat and Coyle, Damien (2024) Decoding neural activity for part-of-speech tagging (POS). In: 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 01-04 October 2023, Honolulu, Oahu, HI, USA.
Ahmed, Salman, Singh, Muskaan, Doherty, Brendan, Ramlan, Effirul, Harkin, Kathryn, Bucholc, Magda and Coyle, Damien (2023) Knowledge-based intelligent system for IT incident DevOps. In: IEEE/ACM International Conference on Software Engineering, 15th May 2023, Melbourne, Australia.
Ahmed, Salman, Singh, Muskaan, Doherty, Brendan, Ramlan, Effirul, Harkin, Kathryn and Coyle, Damien (2023) AI for information technology operation (AIOps): a review of IT incident risk prediction. In: International Conference on Soft Computing & Machine Intelligence (ISCMI), 26th-27th November 2022, Toronto, Canada.
Ahmed, Salman, Singh, Muskaan, Doherty, Brendan, Ramlan, Effirul, Harkin, Kathryn and Coyle, Damien (2023) Multiple severity-level classifications for IT incident risk prediction. In: International Conference on Soft Computing & Machine Intelligence (ISCMI), 26th-27th November 2022, Toronto, Canada.
Ahmed, Salman, Singh, Muskaan, Doherty, Brendan, Ramlan, Effirul, Harkin, Kathryn, Bucholc, Magda and Coyle, Damien (2023) An empirical analysis of state-of-art classification models in an IT incident severity prediction framework. Applied Sciences, 13 (6). ISSN 2076-3417