Publications

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2014
Reham Gharbia, A. T. Azar, A. E. Baz, and A. E. Hassanien, "Image fusion techniques in remote sensing", arXiv preprint arXiv:1403.5473, 2014. Abstract
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Awad, A. I., and A. E. Hassanien, "Impact of some biometric modalities on forensic science", Computational Intelligence in Digital Forensics: Forensic Investigation and Applications: Springer International Publishing, pp. 47–62, 2014. Abstract
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Fattah, M. A., M. I. Waly, M. A. A. ELsoud, A. E. Hassanien, M. F. Tolba, J. Platos, and G. Schaefer, "An improved prediction approach for progression of ocular hypertension to primary open angle glaucoma", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 405–412, 2014. Abstract
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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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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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2013
Fattah, M. A., N. Elbendary, M. A. Elsoud, H. Aboul Ella, and M. Tolba, "An Intelligent Approach for Galaxies Images Classification.", 13th IEEE International Conference on Hybrid Intelligent Systems (HIS13) Tunisia, pp. 168-173, 2013, Tunisia, , 4-6 Dec., 2013.
Fattah, M. A., N. Elbendary, M. A. Elsoud, H. Aboul Ella, and M. Tolba, "An Intelligent Approach for Galaxies Images Classification.", 13th IEEE International Conference on Hybrid Intelligent Systems (HIS13) Tunisia, pp. 168-173, 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", . 13th IEEE International Conference on Hybrid Intelligent Systems |(HIS13) . pp. 286-291, 2013, Tunisia, , 4-6 Dec, 2013.
Liu, H., Y. Ji, and A. E. Hassanien, "Image Color Transfer Approach by Analogy with Taylor Expansion. vol. 2 issue 2, 2013", International Journal of System Dynamics Applications,, vol. 2, issue 2, pp. 43-54, 2013. AbstractWebsite

The Taylor expansion has shown in many fields to be an extremely powerful tool. In this paper, we investigated image features and their relationships by analogy with Taylor expansion. The kind of expansion could be helpful for us to analyze image feature and engraftment, such as transferring color between images. By analogy with Taylor expansion, we designed the image color transfer algorithm by the first and second-order information. The luminance histogram represents the first-order information of image, and the co-occurrence matrix represents the second-order information of image. Some results illustrate our algorithm is effective. In our study, each polynomial in our analogy Taylor expansion of images is considered as one of image features, which makes us re-understand images and its features. It provided us a cue that the features of image, such as color, texture, dimension, time series, would be not isolated but mutual relational based on image expansion.

W. Ghonaim, N. I.Ghali, A. E. Hassanien, and S. Banerjee:, "An improvement of chaos-based hash function in cryptanalysis approach: An experience with chaotic neural networks and semi-collision attack", Memetic Computing Springer, vol. 5, issue 3, pp. 179-185, 2013. Website
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 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.
Liu, H., Y. Ji, and A. E. Hassanien, "Image Color Transfer Approach by Analogy with Taylor Expansion", International Journal of System Dynamics Applications (IJSDA), vol. 2, no. 2: IGI Global, pp. 43–54, 2013. Abstract
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Asad, A. H., A. T. Azar, M. M. M. Fouad, and A. E. Hassanien, "An improved ant colony system for retinal blood vessel segmentation", Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on: IEEE, pp. 199–205, 2013. Abstract
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Eid, H. F., A. T. Azar, and A. E. Hassanien, "Improved real-time discretize network intrusion detection system", Proceedings of seventh international conference on bio-inspired computing: theories and applications (BIC-TA 2012): Springer India, pp. 99–109, 2013. Abstract
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Eid, H. F., A. T. Azar, and A. E. Hassanien, "Improved real-time discretize network intrusion detection system", Proceedings of seventh international conference on bio-inspired computing: theories and applications (BIC-TA 2012): Springer India, pp. 99–109, 2013. Abstract
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Ghonaim, W., N. I. Ghali, A. E. Hassanien, and S. Banerjee, "An improvement of chaos-based hash function in cryptanalysis approach: An experience with chaotic neural networks and semi-collision attack", Memetic Computing, vol. 5, no. 3: Springer Berlin Heidelberg, pp. 179–185, 2013. Abstract
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Ghonaim, W., N. I. Ghali, A. E. Hassanien, and S. Banerjee, "An improvement of chaos-based hash function in cryptanalysis approach: An experience with chaotic neural networks and semi-collision attack", Memetic Computing, vol. 5, no. 3: Springer Berlin Heidelberg, pp. 179–185, 2013. Abstract
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Fattah, M. A., N. El-Bendary, M. A. A. ELsoud, A. E. Hassanien, and M. F. Tolba, "An intelligent approach for galaxies images classification", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 167–172, 2013. 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", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 285–290, 2013. Abstract
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2012
Sami, M., N. El-Bendary, R. C. Berwick, and A. E. Hassanien, "Incorporating Random Forest Trees with Particle Swarm Optimization for Automatic Image Annotation", IEEE Federated Conference on Computer Science and Information Systems, pp. 791–797, Wroclaw - Poland, 9-13 Sept, 2012. Abstractincorporating_random_forest_trees_with.pdf

This paper presents an automatic image annotation approach that integrates the random forest classifier with particle swarm optimization algorithm for classes’ scores weighting.
The proposed hybrid approach refines the output of multiclass classification that is based on the usage of random forest classifier for automatically labeling images with a number of
words. Each input image is segmented using the normalized cuts segmentation algorithm in order to create a descriptor for each segment. Images feature vectors are clustered into K clusters and a random forest classifier is trained for each cluster. Particle swarm optimization algorithm is employed as a search strategy to identify an optimal weighting for classes’ scores from random forest classifiers. The proposed approach has been applied on Corel5K benchmark dataset. Experimental results and comparative performance evaluation, for results obtained from the proposed approach and other related researches, demonstrate that the proposed approach outperforms the performance
of other approaches, considering annotation accuracy, for the
experimented dataset.

Ahmed H. Asad, A. T. Azar, and A. E. Hassanien, "Integrated Features Based on Gray-Level and Hu Moment Invariants with Ant Colony System for Retinal Blood Vessels Segmentation", International Journal of Systems Biology and Biomedical Technologies, , vol. 1, issue 4, pp. 61-74, 2012. AbstractWebsite

Abnormality detection plays an important role in many real-life applications. Retinal vessel segmentation
algorithms are the critical components of circulatory blood vessel Analysis systems for detecting the various
abnormalities in retinal images. Traditionally, the vascular network is mapped by hand in a time-consuming
process that requires both training and skill. Automating the process allows consistency, and most importantly, frees up the time that a skilled technician or doctor would normally use for manual screening. Several studies were carried out on the segmentation of blood vessels in general; however, only a small number of them were associated to retinal blood vessels. In this paper, an approach for segmenting retinal blood vessels is
proposed using only ant colony system. Eight features are selected for the developed system; four are based on gray-level and the other features on Hu moment-invariants. The features are directly computed from values of image pixels, so they take about 90 seconds in computation. The performance of the proposed structure is evaluated in terms of accuracy, sensitivity and specificity. The results showed that the overall accuracy and sensitivity of the presented approach achieved 90.28% and 74%, respectively

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.

Hamdy, A., H. Hefny, M. A. Salama, A. E. Hassanien, and T. - H. Kim, "The importance of handling multivariate attributes in the identification of heart valve diseases using heart signals", Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on: IEEE, pp. 75–79, 2012. Abstract
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Hamdy, A., H. Hefny, M. A. Salama, A. E. Hassanien, and T. - H. Kim, "The importance of handling multivariate attributes in the identification of heart valve diseases using heart signals", Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on: IEEE, pp. 75–79, 2012. Abstract
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