Publications

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Ali, J. M., and A. E. Hassanien, "An Iris Recognition System to Enhance E-Security, Advanced Modeling and Optimization", vol, vol. 5, pp. 93–104, 2003. Abstract

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Ali, J. M. H., and A. E. Hassanien, "An iris recognition system to enhance e-security environment based on wavelet theory", AMO-Advanced Modeling and Optimization, vol. 5, no. 2, pp. 93–104, 2003. Abstract
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Banerjee, S., N. Ghali, and A. E. Hassanien, Investigating Optimization in Retail Inventory: A Bio-inspired Perspective towards Retail Recommender System, , 2012. Abstract
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Banerjee, S., N. Ghali, and A. E. Hassanien, Investigating Optimization in Retail Inventory: A Bio-inspired Perspective towards Retail Recommender System, , 2012. Abstract

Interaction with different person leads to different kinds of ideas and sharing or some nourishing effects which might influence others to believe or trust or even join some association and subsequently become the member of that community. This will facilitate to enjoy all kinds of social privileges. These concepts of grouping similar objects can be experienced as well as could be implemented on any social networks. The concept of homophily
could assist to design the affiliation graph with similar and close similar entities of every member of any social network which tends identifying the most popular community. This paper propose and discuss a novel data-mining algorithm from the perspective of graph properties of a social network such as
embeddedness, betweenness and graph occupancy. Finally, the implication of homophily graph for cultivating leading community of social network has also been solicited.

Salama, M. A., N. El-Bendary, A. E. Hassanien, K. Revett, and A. A. Fahmy, "Interval-based attribute evaluation algorithm", Computer Science and Information Systems (FedCSIS), 2011 Federated Conference on: IEEE, pp. 153–156, 2011. Abstract
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Salama, M. A., N. El-Bendary, A. E. Hassanien, K. Revett, and A. A. Fahmy, "Interval-based attribute evaluation algorithm", Computer Science and Information Systems (FedCSIS), 2011 Federated Conference on: IEEE, pp. 153–156, 2011. Abstract
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Sayed, G. I., and A. E. Hassanien, "Interphase cells removal from metaphase chromosome images based on meta-heuristic grey wolf optimizer", IEEE iInternational Computer Engineering Conference - ICENCO , Cairo, 30 Dec, 2015.
Sayed, G. I., and A. E. Hassanien, "Interphase cells removal from metaphase chromosome images based on meta-heuristic Grey Wolf Optimizer", Computer Engineering Conference (ICENCO), 2015 11th International: IEEE, pp. 261–266, 2015. Abstract
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Hassanien, A. E., "International Conference on Intelligent Systems Design and Applications (ISDA)", International Conference on Intelligent Systems Design and Applications (ISDA), Egypt, IEEE, 2010.
El-Said, S. A., H. M. A. Atta, and A. E. Hassanien, "Interactive soft tissue modelling for virtual reality surgery simulation and planning", International Journal of Computer Aided Engineering and Technology, vol. 9, no. 1: Inderscience Publishers (IEL), pp. 38–61, 2017. Abstract
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Kacprzyk, J., and L. C. Jain, Intelligent Systems Reference Library, Volume 26, , 2012. Abstract
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Kacprzyk, J., and L. C. Jain, Intelligent Systems Reference Library, Volume 26, , 2012. Abstract
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Fouad, M. M., M. A. Mahmood, H. Mahmoud, Adham Mohamed, and A. E. Hassanien, "Intelligent road surface quality evaluation using rough mereology", Hybrid Intelligent Systems (HIS), 2014 14th International Conference on: IEEE, pp. 18–22, 2014. Abstract
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Mahmoud, S., N. El-Bendary, M. A. Mahmood, and A. E. Hassanien, "An Intelligent Recommender system for drinking water quality", . 13th IEEE International Conference on Hybrid Intelligent Systems |(HIS13) . pp. 286-291, 2013, Tunisia, , 4-6 Dec, 2013.
Mahmoud, S., N. El-Bendary, M. A. Mahmood, and A. E. Hassanien, "An intelligent recommender system for drinking water quality", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 285–290, 2013. Abstract
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Mahmood A. Mahmood, N. El-Bendary, Jan Platoš, A. E. Hassanien, and H. A. Hefny, "An Intelligent Multi-agent Recommender System. ", Innovations in Bio-inspired Computing and Applications. Advances in Intelligent Systems and Computing(Springer) , Czech republic , 2013.
Mahmood, M. A., N. El-Bendary, A. E. Hassanien, and H. A. Hefny, "An Intelligent Multi-Agent Recommender System using Rough Mereology", In Proceedings of the 4th International Conference on Innovations in Bio-inspired Computing and Applications. Advances in Intelligent Systems and Computing (Springer) Volume 237, pp 201-213, 2013. Abstract

This article presents a Multi-Agent approach for handling the problem of recommendation. The proposed system works via two main agents; namely, the matching agent and the recommendation agent. Experimental results showed that the proposed rough mereology based Multi-agent system for solving the recommendation problem is scalable and has possibilities for future modification and adaptability to other problem domains. Moreover, it succeeded in reducing the information overload while recommending relevant decisions to users. The system achieved high accuracy in ranking using users profile and information system profiles. The resulted value of the Mean Absolute Error (MAE) is acceptable compared to other recommender systems applied other computational intelligence approaches.

Mahmood, M. A., N. El-Bendary, Jan Platoš, A. E. Hassanien, and H. A. Hefny, "An Intelligent Multi-agent Recommender System", Innovations in Bio-inspired Computing and Applications: Springer International Publishing, pp. 201–213, 2014. Abstract
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Lamiaa M. El Bakrawy, N. I.Ghali, and A. E. Hassanien, "Intelligent Machine Learning in Image Authentication.", signal processing system, vol. 78, issue 2, pp. 223-237 , 2015. Website
El Bakrawy, L. M., N. I. Ghali, and A. E. Hassanien, "Intelligent Machine Learning in Image Authentication", Journal of Signal Processing Systems, vol. 78, no. 2: Springer US, pp. 223–237, 2015. Abstract
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Kareem Kamal A.Ghany, and A. E. Hassanien, An Intelligent Hybrid Biometrics System, , Cairo, EGYPT , Cairo University , 2014. thesis_presentation.pdf
Hassanien, A. E., "Intelligent Hybrid Anomaly Network Intrusion Detection System.", Communication and Networking - International Conference, FGCN 2011, Jeju Island, Korea, 8-10 December, 2011. Abstract

Intrusion detection systems (IDSs) is an essential key for network defense. The hybrid intrusion detection system combines the individual base classifiers and feature selection algorithm to maximize detection accuracy and minimize computational complexity. We investigated the performance of Genetic algorithm-based feature selection system to reduce the data features space and then the hidden naïve bays (HNB) system were adapted to classify the network intrusion into five outcomes: normal, and four anomaly types including denial of service, user-to-root, remote-to-local, and probing. In order to evaluate the performance of introduced hybrid intrusion system, several groups of experiments are conducted and demonstrated on NSL-KDD dataset. Moreover, the performances of intelligent hybrid intrusion system have been compared with the results of well-known feature selection algorithms. It is found that, hybrid intrusion system produces consistently better performances on selecting the subsets of features which resulting better classification accuracies (98.63%).

Hassanien, A. E., "Intelligent Hybrid Anomaly Network Intrusion Detection System.", Communication and Networking-International Conference, FGCN 2011, 2011. Abstract

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Eid, H. F., A. Darwish, A. E. Hassanien, and T. - H. Kim, "Intelligent hybrid anomaly network intrusion detection system", Communication and networking: Springer Berlin Heidelberg, pp. 209–218, 2012. Abstract
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Eid, H. F., A. Darwish, A. E. Hassanien, and T. - H. Kim, "Intelligent hybrid anomaly network intrusion detection system", Communication and networking: Springer Berlin Heidelberg, pp. 209–218, 2012. Abstract
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