Countering Burst Header Packet Flooding Attack in Optical Burst Switching Network. - Adel D. Rajab; Chin-Tser Huang; Mohammed Al-Shargabi; Jorge Arturo Cobb (ISPEC, 2016)

An enhanced burst assembly scheme over optical burst switching networks. - Mohammed Al-Shargabi; Faisal Saeed; Abdul Samad Ismail; Sevia M. Idrus (Int. J. Inf. Commun. Technol., 2017)

Decision tree rule learning approach to counter burst header packet flooding attack in Optical Burst Switching network. - Adel D. Rajab; Chin-Tser Huang; Mohammed Al-Shargabi (Opt. Switch. Netw., 2018)

A Learning Outcome Inspired Survey Instrument for Assessing the Quality of Continuous Improvement Cycle. - Abdallah Namoun; Ahmad Taleb; Mohammed Al-Shargabi; Mohamed Benaida (Int. J. Inf. Commun. Technol. Educ., 2019)

A Developed Robust Model and Artificial Intelligence Techniques to Predict Drilling Fluid Density and Equivalent Circulation Density in Real Time. - Mohammed Al-Rubaii; Mohammed Al-Shargabi; Bayan Aldahlawi; Dhafer Al-Shehri; Konstantin M. Minaev (Sensors, 2023)

Machine learning insights to CO2-EOR and storage simulations through a five-spot pattern - a theoretical study. - Shadfar Davoodi; Hung Vo Thanh; David A. Wood 003; Mohammad Mehrad; Mohammed Al-Shargabi; Valeriy S. Rukavishnikov (Expert Syst. Appl., 2024)

A novel data-driven model for real-time prediction of static Young's modulus applying mud-logging data. - Shadfar Davoodi; Mohammad Mehrad; David A. Wood 003; Mohammed Al-Shargabi; Grachik Eremyan; Tamara Shulgina (Earth Sci. Informatics, 2024)

Advancement of artificial intelligence applications in hydrocarbon well drilling technology: A review. - Shadfar Davoodi; Mohammed Al-Shargabi; David A. Wood 003; Mohammad Mehrad (Appl. Soft Comput., 2025)