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Samanta, S., D. Kundu, S. Chakraborty, N. Dey, T. Gaber, A. E. Hassanien, and T. - H. Kim, "Wooden Surface Classification based on Haralick and The Neural Networks", Information Science and Industrial Applications (ISI), 2015 Fourth International Conference on: IEEE, pp. 33–39, 2015. Abstract
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Khairy, M., Alaa Tharwat, T. Gaber, and A. E. Hassanien, "A wheelchair control system using the human machine interaction: Single-modal and Multi-modal approaches", ournal of Intelligent Systems (JISYS), vol. In press, 2017.
Dey, N., A. S. Ashour, S. Chakraborty, S. Banerjee, E. Gospodinova, M. Gospodinov, and A. E. Hassanien, "Watermarking in Biomedical Signal Processing", Intelligent Techniques in Signal Processing for Multimedia Security: Springer International Publishing, pp. 345–369, 2017. Abstract
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Hossam Moftah, Walaa Elmasry, N. Ghali, A. E. Hassanien, and M. Showman, "Volume Identification and Estimation of MRI Brain Tumor.", The IEEE International Conference on Hybrid Intelligent Systems (HIS2012)., Pune. India, 4-7 Dec. 2012, , pp. 120 - 124, 2012. Abstract

This paper deals with two dimensional magnetic resonance imaging (MRI) sequence of brain slices which include many objects to identify and estimate the volume of the brain tumors. More than twenty five features based on shape, color and texture was extracted to obtain feature vector for each object to characterize the tumor and identify it. Experimental results show that the accuracy of the estimation of tissue volumes is very high.

Moftah, H. M., N. I. Ghali, A. E. Hassanien, and M. A. Ismail, "Volume identification and estimation of MRI brain tumor", Hybrid Intelligent Systems (HIS), 2012 12th International Conference on: IEEE, pp. 120–124, 2012. Abstract
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Ghali, N. I., O. Soluiman, N. El-Bendary, T. M. Nassef, S. A. Ahmed, Y. M. Elbarawy, and A. E. Hassanien, "Virtual reality technology for blind and visual impaired people: Reviews and Recent Advances,", Engineering Advances in Robotics and Virtual Reality, Germany, Intelligent Systems Reference Library - Springer, 2012. Abstract

Virtual reality technology enables people to become immersed in a computer-simulated and three-dimensional environment. In this chapter, we investigate the effects of the virtual reality technology on disabled people such as blind and visually impaired people (VIP) in order to enhance their computer skills and prepare them to make use of recent technology in their daily life. As well as, they need to advance their information technology skills beyond the basic computer training and skills. This chapter describes what best tools and practices in information technology to support disabled people such as deaf-blind and visual impaired people in their activities such as mobility systems, computer games, accessibility of e-learning, web-based information system, and wearable finger-braille interface for navigation of deaf-blind. Moreover, we will show how physical disabled people can benefits from the innovative virtual reality techniques and discuss some representative examples to illustrate how virtual reality technology can be utilized to address the information technology problem of blind and visual impaired people. Challenges to be addressed and an extensive bibliography are included.

Ghali, N. I., O. Soluiman, N. El-Bendary, T. M. Nassef, S. A. Ahmed, Y. M. Elbarawy, and A. E. Hassanien, "Virtual reality technology for blind and visual impaired people: reviews and recent advances", Advances in Robotics and Virtual Reality: Springer Berlin Heidelberg, pp. 363–385, 2012. Abstract
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Ghali, N. I., O. Soluiman, N. El-Bendary, T. M. Nassef, S. A. Ahmed, Y. M. Elbarawy, and A. E. Hassanien, "Virtual reality technology for blind and visual impaired people: reviews and recent advances", Advances in Robotics and Virtual Reality: Springer Berlin Heidelberg, pp. 363–385, 2012. 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", 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, 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., 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., 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., 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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Alaa Tharwat, T. Gaber, and A. E. Hassanien, "Two biometric approaches for cattle identification based on features and classifiers fusion", International Journal of Image Mining, vol. 1, no. 4: Inderscience Publishers (IEL), pp. 342–365, 2015. Abstract
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Alaa Tharwat, T. Gaber, M. M. Fouad, V. Snasel, and A. E. Hassanien, "Towards an automated zebrafish-based toxicity test model using machine learning", Procedia Computer Science, vol. 65: Elsevier, pp. 643–651, 2015. Abstract
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Alaa Tharwat, A. M. Ghanem, and A. E. Hassanien, "Three different classifiers for facial age estimation based on k-nearest neighbor", Computer Engineering Conference (ICENCO), 2013 9th International: IEEE, pp. 55–60, 2013. Abstract
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Gaber, T., G. Ismail, A. Anter, M. Soliman, M. Ali, N. Semary, A. E. Hassanien, and V. Snasel, "Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm", Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE: IEEE, pp. 4254–4257, 2015. Abstract
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Sara Ahmed, T. Gaber, and A. E. Hassanien, "Telemetry Data Mining Techniques, Applications, and Challenges", Handbook of Research on Machine Learning Innovations and Trends, USA, IGI, 2017. Abstract

The most recent rise of telemetry is around the use of Radio-telemetry technology for tracking the traces of moving objects. Initially, the radio telemetry was first used in the 1960s for studying the behavior and ecology of wild animals. Nowadays, there's a wide spectrum application of can benefits from radio telemetry technology with tracking methods, such as path discovery, location prediction, movement behavior analysis, and so on. Accordingly, rapid advance of telemetry tracking system boosts the generation of large-scale trajectory data of tracking traces of moving objects. In this study, we survey various applications of trajectory data mining and review an extensive collection of existing trajectory data mining techniques to be used as a guideline for designing future trajectory data mining solutions.

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KAMAL, K. A. R. E. E. M., A. GHANY, M. A. Moneim, N. I. Ghali, A. E. Hassanien, and H. A. Hefny, A symmetric bio-hash function based on fingerprint minutiae and principal curves approach, , 2011. Abstract
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KAMAL, K. A. R. E. E. M., A. GHANY, M. A. Moneim, N. I. Ghali, A. E. Hassanien, and H. A. Hefny, A symmetric bio-hash function based on fingerprint minutiae and principal curves approach, , 2011. Abstract
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El Bakrawy, L. M., N. I. Ghali, A. E. Hassanien, and J. F. Peters, "Strict authentication of multimodal biometric images using near sets", Soft Computing in Industrial Applications: Springer Berlin Heidelberg, pp. 249–258, 2011. Abstract
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El Bakrawy, L. M., N. I. Ghali, A. E. Hassanien, and J. F. Peters, "Strict authentication of multimodal biometric images using near sets", Soft Computing in Industrial Applications: Springer Berlin Heidelberg, pp. 249–258, 2011. Abstract
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Hassanien, A. E., A. Abraham, and C. Grosan, "Spiking neural network and wavelets for hiding iris data in digital images", Soft Computing-A Fusion of Foundations, Methodologies and Applications, vol. 13, no. 4: Springer Berlin/Heidelberg, pp. 401–416, 2009. Abstract
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Hassanien, A. E., A. Abraham, and C. Grosan, "Spiking neural network and wavelets for hiding iris data in digital images", Soft Computing-A Fusion of Foundations, Methodologies and Applications, vol. 13, no. 4: Springer Berlin/Heidelberg, pp. 401–416, 2009. Abstract
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Ghali, N., M. Panda, A. E. Hassanien, A. Abraham, and V. Snasel, "Social Networks: Computational Aspects and Mining", Computational Social Networks: Tools, Perspectives and Applications, London, Computer and Communication Networks Springer Series, 2012. Abstract

Computational social science is a new emerging field that has overlapping regions from Mathematics, Psychology, Computer Sciences, Sociology,and Management. Social computing is concerned with the intersection of social behavior and computational systems. It supports any sort of social behavior in or through computational systems. It is based on creating or recreating social conventions and social contexts through the use of software and technology. Thus, blogs, email, instant messaging, social network services, wikis, social bookmarking, and other instances of what is often called social software illustrate ideas from social computing. Social network analysis is the study of relationships among social entities. It is becoming an important tool for investigators. However all the necessary information is often distributed over a number of Web sites. Interest in this field is blossoming as traditional practitioners in the social and behavioral sciences are being joined by researchers from statistics, graph theory, machine learning and data mining. In this chapter, we illustrate the concept of social networks from a computational point of view, with a focus on practical services, tools, and applications and open avenues for further research. Challenges to be addressed and future directions of research are presented and an extensive bibliography is also included.

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