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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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Kudelka, M., V. Snásel, Z. Horak, and A. E. Hassanien, "Web Communities Defined by Web Page Content", IEEE/WIC/ACM International Conference on Web Intelligence and International Conference on Intelligent Agent Technology , Sydney, NSW, Australia, pp.385-389 , 9-12 December, 2008. Abstract

In this paper we are looking for a relationship between the intent of Web pages, their architecture and the communities who take part in their usage and creation. For us, the Web page is entity carrying information about these communities. Our paper describes techniques, which can be used to extract mentioned information as well as tools usable in analysis of these information. Information about communities could be used in several ways thanks to our approach. Finally we present an experiment which proves the feasibility of our approach.

Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "The way of improving PSO performance: medical imaging watermarking case study", International Conference on Rough Sets and Current Trends in Computing: Springer Berlin Heidelberg, pp. 237–242, 2012. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "The way of improving PSO performance: medical imaging watermarking case study", International Conference on Rough Sets and Current Trends in Computing: Springer Berlin Heidelberg, pp. 237–242, 2012. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "The way of improving PSO performance: medical imaging watermarking case study", International Conference on Rough Sets and Current Trends in Computing: Springer Berlin Heidelberg, pp. 237–242, 2012. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "Watermarking 3D Triangular Mesh Models Using Intelligent Vertex Selection", Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015: Springer International Publishing, pp. 617–627, 2016. Abstract
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Asmaa Hashem Sweidan, N. El-Bendary, O. M. Hegazy, A. E. Hassanien, and V. Snasel, "Water Pollution Detection System Based on Fish Gills as a Biomarker", International Conference on Communications, management, and Information technology (ICCMIT'2015), 2015. Abstract

This article presents an automatic system for assessing water quality based on fish gills microscopic images. As fish gills are a good biomarker for assessing water quality, the proposed system uses fish gills microscopic images in order to detect water pollution. The proposed system consists of three phases; namely pre-processing, feature extraction, and classification phases. Since the shape is the main characteristic of fish gills microscopic images, the proposed system uses shape feature based on edge detection and wavelets transform for classifying the water-quality degree. Furthermore, it implemented Principal Components Analysis (PCA) along with Support Vector Machines (SVMs) algorithms for feature extraction and water quality degree classification. The datasets used for experiments were constructed based on real sample images for fish gills. Training dataset is divided into four classes representing the different histopathological changes and the corresponding water quality degrees. Experimental results showed that the proposed classification system has obtained water quality classification accuracy of 95.41%, using the SVMs linear kernel function and 10-fold cross validation with 37 images per class for training.

Asmaa Hashem Sweidan, N. El-Bendary, O. M. Hegazy, A. E. Hassanien, and V. Snasel, "Water pollution detection system based on fish gills as a biomarker", Procedia Computer Science, vol. 65: Elsevier, pp. 601–611, 2015. 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.

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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Sami, M., N. El-Bendary, T. - H. Kim, and A. E. Hassanien, "Using Particle Swarm Optimization for Image Regions Annotation", Future Generation Information Technology (FGIT 2012),, 241--250. Springer, Heidelberg. Kangwondo, Korea , cember 16-19,, 2012. Abstract77090241.pdf

In this paper, we propose an automatic image annotation approach
for region labeling that takes advantage of both context and semantics present
in segmented images. The proposed approach is based on multi-class K-nearest
neighbor, k-means and particle swarm optimization (PSO) algorithms for feature
weighting, in conjunction with normalized cuts-based image segmentation technique.
This hybrid approach refines the output of multi-class classification that
is based on the usage of K-nearest neighbor classifier for automatically labeling
images regions from different classes. Each input image is segmented using the
normalized cuts segmentation algorithm then a descriptor created for each segment.
The PSO algorithm is employed as a search strategy for identifying an optimal
feature subset. Extensive experimental results demonstrate that the proposed
approach provides an increase in accuracy of annotation performance by about
40%, via applying PSO models, compared to having no PSO models applied, for
the used dataset.

Sami, M., N. El-Bendary, T. - H. Kim, and A. E. Hassanien, "Using particle swarm optimization for image regions annotation", International Conference on Future Generation Information Technology: Springer Berlin Heidelberg, pp. 241–250, 2012. Abstract
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Sami, M., N. El-Bendary, T. - H. Kim, and A. E. Hassanien, "Using particle swarm optimization for image regions annotation", International Conference on Future Generation Information Technology: Springer Berlin Heidelberg, pp. 241–250, 2012. Abstract
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Amin, I. I., Samar K. Kassim, A. E. Hassanien, and H. A. Hefny, "Using formal concept analysis for mining hyomethylated genes among breast cancer tumors subtypes ", IEEE International Conference on Advances in Computing, Communications and Informatics (ICACCI-2013) , Mysore, India, August 22-25, 2013. pid2853599_3_2.pdf
Salama, M. A., A. E. Hassanien, and A. A. Fahmy, "Uni-class pattern-based classification model", Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on: IEEE, pp. 1293–1297, 2010. Abstract
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Salama, M. A., A. E. Hassanien, and A. A. Fahmy, "Uni-class pattern-based classification model", Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on: IEEE, pp. 1293–1297, 2010. 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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Skowron, J. P. A. F., V. M. E. W. Orłowska, and R. S. W. Ziarko, Transactions on Rough Sets VII, , 2007. Abstract
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Skowron, J. P. A. F., V. M. E. W. Orłowska, and R. S. W. Ziarko, Transactions on Rough Sets VII, , 2007. Abstract
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Sahlol, A. T., A. A. Ewees, A. M. H.;, and A. E. Hassanien, "Training feedforward neural networks using Sine-Cosine algorithm to improve the prediction of liver enzymes on fish farmed on nano-selenite", 12th International Computer Engineering Conference (ICENCO),, Cairo, 28-29 Dec, 2016. Abstract

Analytical prediction of oxidative stress biomarkers in ecosystem provides an expressive result for many stressors. These oxidative stress biomarkers including superoxide dismutase, glutathione peroxidase and catalase activity in fish liver tissue were analyzed within feeding different levels of selenium nanoparticles. Se-nanoparticles represent a salient defense mechanism in oxidative stress within certain limits; however, stress can be engendered from toxic levels of these nanoparticles. For instance, prediction of the level of pollution and/or stressors was elucidated to be improved with different levels of selenium nanoparticles using the bio-inspired Sine-Cosine algorithm (SCA). In this paper, we improved the prediction accuracy of liver enzymes of fish fed by nano-selenite by developing a neural network model based on SCA, that can train and update the weights and the biases of the network until reaching the optimum value. The performance of the proposed model is better and achieved more efficient than other models.

Sahlol, A. T., A. A. Ewees, A. M. Hemdan, and A. E. Hassanien, "Training feedforward neural networks using Sine-Cosine algorithm to improve the prediction of liver enzymes on fish farmed on nano-selenite", Computer Engineering Conference (ICENCO), 2016 12th International: IEEE, pp. 35–40, 2016. Abstract
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Salama, M. A., N. El-Bendary, and A. E. Hassanien, "Towards secure mobile agent based e-cash system", Proceedings of the First International Workshop on Security and Privacy Preserving in e-Societies: ACM, pp. 1–6, 2011. Abstract
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