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Durham University

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Staff Profile

Dr Noura Al Moubayed - all publications

Chapter in book

  • Gajbhiye, Amit, Winterbotton, Tom, Al Moubayed, Noura & Bradley, Steven (Accepted). Lecture Notes in Computer Science. In Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models. Springer.
  • Gajbhiye, Amit, Winterbottom, Thomas, Al Moubayed, Noura & Bradley, Steven (2020). Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models. In Artificial Neural Networks and Machine Learning – ICANN 2020. Farkaš, Igor, Masulli, Paolo & Wermter, Stefan Springer. 12396: 633-646.
  • Al Moubayed, N., Wall, D. & McGough, A. S. (2017). Identifying Changes in the Cybersecurity Threat Landscape using the LDA-Web Topic Modelling Data Search Engine. In Human aspects of information security, privacy and trust: 5th International Conference, HAS 2017, held as part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, proceedings. Tryfonas, Theo Cham: Springer. 287-295.
  • Al Moubayed, N, Petrovski, A & McCall, J (2013). Mutual Information for Performance Assessment of Multi Objective Optimisers: Preliminary Results. In Intelligent Data Engineering and Automated Learning – IDEAL 2013. Springer Berlin Heidelberg. 8206: 537-544.
  • Al Moubayed, N, Petrovski,A & McCall,J (2012). D 2 MOPSO: Multi-Objective Particle Swarm Optimizer Based on Decomposition and Dominance. In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg. 7245: 75-86.
  • Al Moubayed, N, Petrovski, A & McCall, J (2011). Clustering-Based Leaders’ Selection in Multi-Objective Particle Swarm Optimisation. In Intelligent Data Engineering and Automated Learning - IDEAL 2011. Springer Berlin Heidelberg. 6936: 100.
  • Al Moubayed, N, Petrovski, A & McCall, J (2010). A Novel Smart Multi-Objective Particle Swarm Optimisation using Decomposition. In Parallel Problem Solving from Nature, PPSN XI. Springer Berlin Heidelberg. 1-10.

Journal Article

  • Alhassan, Zakhriya, Watson, Matthew, Budgen, David, Alshammari, Riyad, Alessa, Ali & Al Moubayed, Noura (2021). Improving Current Glycated Hemoglobin Prediction in Adults: Use of Machine Learning Algorithms with Electronic Health Records (Preprint). JMIR Medical Informatics
  • Al Moubayed, Noura, McGough, Stephen & Awwad Shiekh Hasan, Bashar (2020). Beyond the topics: how deep learning can improve the discriminability of probabilistic topic modelling. PeerJ Computer Science 6: e252.
  • Alhassan, Zakhriya, Budgen, David, Alshammari, Riyad & Moubayed, Noura Al (2020). Predicting Current Glycated Hemoglobin Levels in Adults From Electronic Health Records: Validation of Multiple Logistic Regression Algorithm. Journal of Medical Internet Research 8(7): e18963.
  • Al Moubayed, N, Petrovski, A & McCall, J (2014). D2MOPSO: MOPSO Based on Decomposition and Dominance with Archiving Using Crowding Distance in Objective and Solution Spaces. Evolutionary Computation 22(1): 47-77.

Conference Paper

  • Watson, Matthew & Al Moubayed, Noura (2020), Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning, The 25th International Conference on Pattern Recognition (ICPR2020). Milan, Italy, IEEE.
  • Yucer, S, Akcay, S, Al Moubayed, N & Breckon, T.P (2020), Exploring Racial Bias within Face Recognition via per-subject Adversarially-Enabled Data Augmentation, Computer Vision and Pattern Recognition Workshops. Seattle, USA, IEEE.
  • Winterbottom, T, Xiao, S, McLean, A & Al Moubayed, N (2020), On Modality Bias in the TVQA Dataset, The British Machine Vision Conference (BMVC). Manchester, UK.
  • Alhassan, Zakhriya, Budgen, David, Alessa, Ali, Alshammari, Riyad, Daghstani, Tahini & Al Moubayed, Noura (2019), Collaborative Denoising Autoencoder for High Glycated Haemoglobin Prediction, in Tetko, Igor V. Kůrková, Věra Karpov, Pavel & Theis, Fabian eds, Lecture Notes in Computer Science 11731: 28th International Conference on Artificial Neural Networks, ICANN2019. Munich, Germany, Springer, Cham, 338-350.
  • Aznan, N.K.N., Connolly, J.D., Al Moubayed, N. & Breckon, T.P. (2019), Using Variable Natural Environment Brain-Computer Interface Stimuli for Real-time Humanoid Robot Navigation, 2019 IEEE International Conference on Robotics and Automation (ICRA). Montreal, Canada, IEEE, 4889-4895.
  • Gajbhiye, Amit, Jaf, Sardar, Al-Moubayed, Noura, McGough, A. Stephen & Bradley, Steven (2018), An Exploration of Dropout with RNNs for Natural Language Inference, in Kurková, V., Manolopoulos, Yannis, Hammer, Barbara, Iliadis, Lazaros S. & Maglogiannis, Ilias G. eds, Lecture Notes in Computer Science, 11141 ICANN 2018: 27th International Conference on Artificial Neural Networks. Rhodes, Springer, Cham, 157-167.
  • Gajbhiye, Amit, Jaf, Sardar, Al-Moubayed, Noura, Bradley, Steven & McGough, A. Stephen (2018), CAM: A Combined Attention Model for Natural Language Inference, in Abe, Naoki Liu, Huan Pu, Calton Hu, Xiaohua Ahmed, Nesreen Qiao, Mu Song, Yang Kossmann, Donald Liu, Bing Lee, Kisung Tang, Jiliang He, Jingrui & Saltz, Jeffrey eds, IEEE International Conference on BIG DATA. Seattle, United States of America, IEEE, Piscataway, N.J., 1009-1014.
  • Vissol-Gaudin, E., Kotsialos, A., Groves, C., Pearson, C., Zeze, D.A., Petty, M.C. & Al-moubayed, N. (2018), Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers, 2018 IEEE World Congress on Computational Intelligence (WCCI 2018). Rio de Janeiro, Brazil, IEEE, Piscataway, 646-653.
  • Aznan, N.K.N., Bonner, S., Connolly, J.D., Al Moubayed, N. & Breckon, T.P. (2018), On the Classification of SSVEP-Based Dry-EEG Signals via Convolutional Neural Networks, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018). Miyazaki, Japan, IEEE, Piscataway, NJ, 3726-3731.
  • Alhassan, Z, Budgen, D, Alshammari, R, Daghstani, T, McGough, S & Al Moubayed, N (2018), Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data, 17th International Conference in Machine Learning and Applications (ICMLA2018). Orlando, Florida, USA, IEEE.
  • Alhassan, Zakhriya, McGough, A. Stephen, Alshammari, Riyad, Daghstani, Tahani, Budgen, David & Al Moubayed, Noura (2018), Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data, IEEE 17th International Conference on Machine Learning and Applications (ICMLA 2018). Orlando, Fl, USA, IEEE, 541-546.
  • Alhassan, Zakhriya, McGough, Stephen, Alshammari, Riyad, Daghstani, Tahini, Budgen, David & Al Moubayed, Noura (2018), Type-2 Diabetes Mellitus Diagnosis from Time Series Clinical Data using Deep Learning Models, in Kůrková, Věra, Manolopoulos, Yannis, Hammer, Barbara, Iliadis, Lazaros & Maglogiannis, Ilias eds, Lecture Notes in Computer Science 1141: International Conference on Artificial Neural Networks (ICANN). Rhodes, Greece, Springer, 468-478.
  • McGough, S Forshaw, M, Brennan,J Al Moubayed, N & Bonner, S (2018), Using Machine Learning to reduce the energy wasted in Volunteer Computing Environments, 9th International Green and Sustainable Computing Conference. Pittsburgh, PA, US, IEEE, 1-8.
  • Al Moubayed, Noura, Hasan, Bashar Awwad Shiekh & McGough, Andrew Stephen (2017), Enhanced detection of movement onset in EEG through deep oversampling, 30th International Joint Conference on Neural Networks (IJCNN 2017). Anchorage, Alaska, USA, IEEE, Piscataway, 71-78.
  • A. S, McGough, N, Al Moubayed & M, Forshaw (2017), Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems, ICPE '17 Companion 3rd International Workshop on Energy-aware Simulation (ENERGY-SIM’17). L'Aquila, ACM, New York, 55-60.
  • Al Moubayed, N., Breckon, T.P., Matthews, P.C. & McGough, A.S. (2016), SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder, in Villa, Alessandro E.P., Masulli, Paolo & Pons Rivero, Antonio J. eds, Lecture Notes in Computer Science 9887: Springer International Publishing, Cham, 423-430.
  • Al Moubayed, N., Vazquez-Alvarez, Y., McKay, A. & Vinciarelli, A. (2014), Face-Based Automatic Personality Perception, MM '14 22nd ACM international conference on Multimedia - MM '14. Orlando, Florida, USA, Association for Computing Machinery (ACM), New York, NY, USA, 1153-1156.
  • Al Moubayed, N , Awwad Shiekh Hasan, B Gan, J Q Petrovski, A & McCall, J (2012), Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces, 2012 IEEE Congress on Evolutionary Computation. Brisbane, Australia, IEEE, 1-7.
  • Al Moubayed, N, Petrovski, A & McCall, J (2011), Clustering based leaders' selection in multi-objective evolutionary algorithms, Proceedings of the 13th annual conference companion on Genetic and evolutionary computation - GECCO '11. Dublin, Irland, ACM.
  • Al Moubayed, N, Petrovski, A & McCall, J (2011), Multi-objective Optimisation of Cancer Chemotherapy using Smart PSO with Decomposition, 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM). Paris, France, IEEE, 81 - 88.
  • Al Moubayed, N , Awwad Shiekh Hasan, B, Gan, J Q Petrovski, A & McCall, J (2010), Binary-SDMOPSO and its application in channel selection for Brain-Computer Interfaces, 2010 UK Workshop on Computational Intelligence (UKCI). Colchester, UK, IEEE, 1-6.
  • Windisch, A & Al Moubayed, N (2009), Signal Generation for Search-Based Testing of Continuous Systems, 2009 International Conference on Software Testing, Verification, and Validation Workshops. Denver, CO, IEEE.
  • Al Moubayed, N & Windisch, A (2009), Temporal White-Box Testing Using Evolutionary Algorithms, 2009 International Conference on Software Testing, Verification, and Validation Workshops. Denver, CO, IEEE, 150.
  • Al Moubayed, N & Awwad Shiekh Hasan, B (2009), Temporal White-Box Testing Using Evolutionary and Search-base Algorithms, 9th Annual Workshop on Computational Intelligence. Colchester, UK.

Doctoral Thesis

  • Al Moubayed, N (Accepted). Multi-objective particle swarm optimisation: methods and applications. Robert Gordon University. PhD.