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Ismail, F. H., A. F. Ali, S. Esmat, and A. E. Hassanien, "Newcastle Disease Virus Clustering Based on Swarm Rapid Centroid Estimation", Advances in Nature and Biologically Inspired Computing: Springer International Publishing, pp. 359–367, 2016. Abstract
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Sato, M., A. E. Hassanien, and M. Nakajima, "Non-Linear Image Registration: Combining Viscous Fluid Deformations and Elastic Body Splines", 映像情報メディア学会技術報告, vol. 22, no. 45: 一般社団法人映像情報メディア学会, pp. 1–6, 1998. Abstract
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Sato, M., A. E. Hassanien, and M. Nakajima, "Nonlinear registration of medical images using Cauchy-Navier spline transformation", Medical Imaging'99: International Society for Optics and Photonics, pp. 774–781, 1999. Abstract
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Kudelka, M., V. Snasel, Z. Horak, A. E. Hassanien, A. Abraham, and J. D. Velásquez, "A novel approach for comparing web sites by using MicroGenres", Engineering Applications of Artificial Intelligence,, vol. 35, pp. 178-198, 2014. AbstractWebsite

In this paper, a novel approach is introduced to compare web sites by analysing their web page content. Each web page can be expressed as a set of entities called MicroGenres, which in turn are abstractions about design patterns and genres for representing the page content. This description is useful for web page and web site classification and for a deeper insight into the web site׳s social context.

The web site comparison is useful for extracting patterns which can be used for improving Web search engine effectiveness, the identification of best practices in web site design and of course in the organization of web page content to personalize the web user experience on a web site.

The effectiveness of the proposed approach was tested in a real world case, with e-shop web sites showing that a web site can be represented in a high level of abstraction by using MicroGenres, the contents of which can then be compared and given a measure corresponding to web site similarity. This measure is very useful for detecting web communities on the Web, i.e., a group of web sites sharing similar contents, and the result is essential in performing a focused and effective information search as well as minimizing web page retrieval.

Kudelka, M., V. Snasel, Z. Horak, A. E. Hassanien, A. Abraham, and J. D. Velásquez, "A novel approach for comparing web sites by using MicroGenres", Engineering Applications of Artificial Intelligence, vol. 35: Pergamon, pp. 187–198, 2014. Abstract
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Gaber, T., N. Zhang, and A. E. Hassanien, "A novel approach to allow multiple resales of DRM-protected contents", Computer Engineering & Systems (ICCES), 2013 8th International Conference on: IEEE, pp. 86–91, 2013. Abstract
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Hassanien, A. E., M. A. Fattah, K. M. AMIN, and S. MOHAMED, "A Novel Hybrid Binarization Technique for Images of Historical Arabic Manuscripts", Studies in Informatics and Control, , vol. 24, issue 3, pp. 271-282, 2015. AbstractWebsite

In this paper, a novel binarization approach based on neutrosophic sets and sauvola’s approach is presented.
This approach is used for historical Arabic manuscript images which have problems with types of noise. The input RGB image is changed into the NS domain, which is shown using three subsets, namely, the percentage of indeterminacy in a subset, the percentage of falsity in a subset and the percentage of truth in a subset. The entropy in NS is used for evaluating the indeterminacy with the most important operation ”λ mean” operation in order to minimize indeterminacy which can be used to reduce noise. Finally, the manuscript is binarized using an adaptive thresholding technique. The main advantage of the proposed approach is that it preserves weak connections and provides smooth and continuous strokes. The performance of the proposed approach is evaluated both objectively and subjectively against standard databases and manually collected data base. The proposed method gives high results compared with other famous binarization approaches

Hassanien, A. E., M. A. Fattah, K. M. AMIN, and S. MOHAMED, "A novel hybrid binarization technique for images of historical Arabic manuscripts", Studies in Informatics and Control, vol. 24, no. 3, pp. 271–282, 2015. Abstract
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