Publications

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Ali, J. M. H., and A. E. Hassanien, "PCNN for detection of masses in digital mammogram", Neural Network World, vol. 16, no. 2: Institute of Computer Science, pp. 129, 2006. Abstract
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Ali, J. M., and A. E. Hassanien, "Mathematical Morphology Approach for Enhancement Digital Mammography Images", IASTED, International Conference on Biomedical Engineering (BioMED2004) February, pp. 16–18, 2004. 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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Ali, A. F., and A. - E. Hassanien, "A Survey of Metaheuristics Methods for Bioinformatics Applications", Applications of Intelligent Optimization in Biology and Medicine: Springer International Publishing, pp. 23–46, 2016. Abstract
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Ali, A. F., A. E. Hassanien, V. Snasel, and M. F.Tolba, "A new hybrid particle swarm optimization with variable neighborhood search for solving unconstrained global optimization problems", The 5th International Conference on Innovations in Bio-Inspired Computing and Applications (Springer) IBICA2014, Ostrava, Czech Republic., 22-24 June, 2014.
Ali, A. F., A. E. Hassanien, and V. Snasel, "Memetic Artificial Bee Colony for integer programming ", The 2nd International Conference on Advanced Machine Learning Technologies and Applications , Egypt, November 17-19, , 2014.
Ali, J. M. H., and A. E. Hassanien, "PCNN for detection of masses in digital mammogram", Neural Network World, vol. 16, no. 2: Institute of Computer Science, pp. 129, 2006. Abstract
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Ali, M. A. S., and A. E. Hassanien, "An observational study to identify the role of online communication in offline social networks", International Conference on Advanced Machine Learning Technologies and Applications: Springer International Publishing, pp. 509–522, 2014. Abstract
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Alnashar, H. S., M. A. Fattah, M. M. Mosbah, and A. E. Hassanien, "Cloud computing framework for solving virtual college educations: A case of egyptian virtual university", Information Systems Design and Intelligent Applications: Springer India, pp. 395–407, 2015. Abstract
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Alshabrawy, O. S., M. E. Ghoneim, A. A. Salama, and A. E. Hassanien, "Underdetermined blind separation of an unknown number of sources based on fourier transform and matrix factorization", Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on: IEEE, pp. 19–25, 2013. Abstract
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Alshabrawy, O. S., and A. E. Hassanien, "Underdetermined blind separation of mixtures of an unknown number of sources with additive white and pink noises", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 241–250, 2014. Abstract
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Alshabrawy, O. S., M. E. Ghoneim, W. A. Awad, and A. E. Hassanien, "Underdetermined blind source separation based on fuzzy c-means and semi-nonnegative matrix factorization", Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on: IEEE, pp. 695–700, 2012. Abstract
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Alshabrawy, O. S., A. E. Hassanien, W. A. Awad, and A. Salama, "Blind Separation of Underdetermined Mixtures with Additive White and Pink Noises", 13th IEEE International Conference on Hybrid Intelligent Systems (HIS13) Tunisia, pp. 306-312, 2013, Tunisia, 4-6 Dec, 2013.
Alshabrawy, O. S., M. E. Ghoneim, W. A. Awad, and A. E. Hassanien, "Underdetermined Blind Source Separation based on Fuzzy C-Means and Semi-Nonnegative Matrix Factorization", IEEE Federated Conference on Computer Science and Information Systems, pp. 723–728, Wroclaw - Poland, 9-13 Sept, 2012. Abstractunderdetermined_blind_source_separation_based_on_fuzzy.pdf

Conventional blind source separation is based on
over-determined with more sensors than sources but the underdetermined
is a challenging case and more convenient to actual
situation. Non-negative Matrix Factorization (NMF) has been
widely applied to Blind Source Separation (BSS) problems.
However, the separation results are sensitive to the initialization
of parameters of NMF. Avoiding the subjectivity of choosing
parameters, we used the Fuzzy C-Means (FCM) clustering
technique to estimate the mixing matrix and to reduce the requirement
for sparsity.Also, decreasing the constraints is regarded
in this paper by using Semi-NMF. In this paper we propose
a new two-step algorithm in order to solve the underdetermined
blind source separation. We show how to combine the FCM clustering technique with the gradient-based NMF with the multi-layer technique. The simulation results show that our proposed algorithm can separate the source signals with high signal-to-noise ratio and quite low cost time compared with some algorithms.

Alshabrawy, O. S., M. E. Ghoneim, A. A. Salama, and A. E. Hassanien, "Underdetermined blind separation of an unknown number of sources based on fourier transform and matrix factorization", Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on: IEEE, pp. 19–25, 2013. Abstract
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Alshabrawy, O. S., A. E. Hassanien, W. A. Awad, and A. A. Salama, "Blind separation of underdetermined mixtures with additive white and pink noises", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 305–311, 2013. Abstract
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Alshabrawy, O. S., M. E. Ghoneim, W. A. Awad, and A. E. Hassanien, "Underdetermined blind source separation based on fuzzy c-means and semi-nonnegative matrix factorization", Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on: IEEE, pp. 695–700, 2012. Abstract
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Alshabrawy, O. S., A. E. Hassanien, W. A. Awad, and A. A. Salama, 2013 13th International Conference on Hybrid Intelligent Systems (HIS), , 2013. Abstract

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Amin, I. I., A. E. Hassanien, Hesham A. Hefny, and S. K. Kassim, "Visualizing and identifying the DNA methylation markers in breast cancer tumor subtypes", The 5th International Conference on Innovations in Bio-Inspired Computing and Applications (Springer) IBICA2014, Ostrava, Czech Republic., 22-24 June, 2014. Abstractibica2014_p14.pdf

DNA methylation is an epigenetic mechanism that cells use to control
gene expression. DNA methylation has become one of the hottest topics in cancer
research, especially for abnormally hypermethylated tumor suppressor genes
or hypomethylaed oncogenes research. The analysis of DNA methylation data
determines the differential hypermethlated or hypomethylated genes that are candidate
to be cancer biomarkers. Visualization the DNA methylation status may
lead to discover new relationships between hypomethylated and hypermethylated
genes, therefore this paper applied a mathematical modelling theory called formal
concept analysis for visualizing DNA methylation status.

Amin, R., T. Gaber, G. ElTaweel, and A. E. Hassanien, "Biometric and traditional mobile authentication techniques: Overviews and open issues", Bio-inspiring cyber security and cloud services: trends and innovations: Springer Berlin Heidelberg, pp. 423–446, 2014. Abstract
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Amin, I. I., S. K. Kassim, A. E. Hassanien, and H. A. Hefny, "Using formal concept analysis for mining hyomethylated genes among breast cancer tumors subtypes", Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on: IEEE, pp. 521–526, 2013. Abstract
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Amin, I. I., S. K. Kassim, A. E. Hassanien, and H. A. Hefny, "Applying formal concept analysis for visualizing DNA methylation status in breast cancer tumor subtypes", Computer Engineering Conference (ICENCO), 2013 9th International: IEEE, pp. 37–42, 2013. Abstract
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Amin, I. I., S. K. Kassim, A. E. Hassanien, and H. A. Hefny, "Formal concept analysis for mining hypermethylated genes in breast cancer tumor subtypes", Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on: IEEE, pp. 764–769, 2012. Abstract
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Amin, I. I., S. K. Kassim, A. E. Hassanien, and H. A. Hefny, "Formal concept analysis for mining hypermethylated genes in breast cancer tumor subtypes", Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on: IEEE, pp. 764–769, 2012. Abstract
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Amin, I. I., S. K. Kassim, A. E. Hassanien, and H. Hefny, "Formal concept analysis for mining hypermethylated genes in breast cancer tumor subtypes", 12th International Conference on Intelligent Systems Design and Applications (ISDA), , Kochi, India, pp. 764 - 769, 2012. Abstract

The main purpose of this paper is to show the use of formal concept analysis (FCA) as data mining approach for mining the common hypermethylated genes between breast cancer subtypes, by extracting formal concepts which representing sets of significant hypermethylated genes for each breast cancer subtypes, then the formal context is built which leading to construct a concept lattice which is composed of formal concepts. This lattice can be used as knowledge discovery and knowledge representation therefore, becoming more interesting for the biologists.