Prof Hassan Abdalla


NameProf Hassan Abdalla
Job titleExecutive Dean
Email addressh.s.abdalla@uel.ac.uk
Research instituteUEL

Research outputs

A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images

Van Druten, J., Sharif, S., Chan, S. S., Chong, C. and Abdalla, H. 2019. A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images. in: Proceedings: 2019 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE.

A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis

van Druten, Jacqueline, Sharif, M., Khashu, Minesh and Abdalla, H. 2019. A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis. in: Miraz, Mahdi H., Exce, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 101-106

Neural Predictors of Gait Stability When Walking Freely in the Real-World.

Pizzamiglio, S., Abdalla, H., Naeem, U. and Turner, D. 2018. Neural Predictors of Gait Stability When Walking Freely in the Real-World. Journal of NeuroEngineering and Rehabilitation. 15 (11).

An investigation into energy consumption behaviour and lifestyles in UK homes: Developing a smart application as a tool for reducing home energy use

Shi, W., Elsharkawy, Heba and Abdalla, H. 2017. An investigation into energy consumption behaviour and lifestyles in UK homes: Developing a smart application as a tool for reducing home energy use. in: Brotas, Luisa, Roaf, Susan and Nicol, Fergus (ed.) Design to Thrive: Proceedings of the 33rd PLEA International Conference 2017 NCEUB.

Energy Saving of the Domestic Housing Stocks: Application Development as a Plug-In for Energy Simulation Software

Shi, W., Abdalla, H., Elsharkawy, Heba and Chandler, A. 2017. Energy Saving of the Domestic Housing Stocks: Application Development as a Plug-In for Energy Simulation Software. International Journal of Parallel, Emergent and Distributed Systems. 32 (Sup 1), pp. S114-S132.

Investigation Into ERP-Based Symbiotic Simulation Project Implentation On Ford Engine Production Line: Challenges, Opportunities and Prospects

Chiroma, Emmanuel, Ladbrook, John and Abdalla, H. 2016. Investigation Into ERP-Based Symbiotic Simulation Project Implentation On Ford Engine Production Line: Challenges, Opportunities and Prospects. in: Bruzzone, Agostino G., De Felice, Fabio, Frydman, Claudia, Massei, Marina, Merkuryev, Yuri and Solis, Adriano (ed.) Proceedings of the International Conference on Modelling and Applied Simulation 2016 DIME Università Di Genova. pp. 57-64

A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing

Pizzamiglio, S., Naeem, U., ur Réhman, Shafiq, Sharif, M., Abdalla, H. and Turner, D. 2017. A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing. Procedia Computer Science. 113, pp. 89-96.

Neural correlates of single- and dual-task walking in the real world

Pizzamiglio, Sara, Naeem, U., Abdalla, H. and Turner, D. 2017. Neural correlates of single- and dual-task walking in the real world. Frontiers in Human Neuroscience. 11, p. Art 460.

A Cost Effective and Light Weight Unipolar Electroadhesion Pad Technology for Adhesion Mechanism of Wall Climbing Robot

Yehya, Muhammd Irshad, Hussain, Salman, Wasim, Ahmad, Jahanza, Mirza and Abdalla, H. 2016. A Cost Effective and Light Weight Unipolar Electroadhesion Pad Technology for Adhesion Mechanism of Wall Climbing Robot. International Journal of Robotics and Mechatronics. 2 (1), pp. 1-10.

Predicting the tensile strength, impact toughness, and hardness of friction stir-welded AA6061-T6 using response surface methodology

Safeen, Wasif, Hussain, Salman, Wasim, Ahmad, Jahanzaib, Mirza, Aziz, Haris and Abdalla, H. 2016. Predicting the tensile strength, impact toughness, and hardness of friction stir-welded AA6061-T6 using response surface methodology. The International Journal of Advanced Manufacturing Technology. 87 (5-8), pp. 1765-1781.
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