Publications

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2010
Hassanien, A. E., H. Al-Qaheri, Václav Snášel, and J. F. Peters, "Machine learning techniques for prostate ultrasound image diagnosis", Advances in Machine Learning I: Springer Berlin Heidelberg, pp. 385–403, 2010. Abstract
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Banerjee, S., H. Al-Qaheri, and A. E. Hassanien, "Mining social networks for viral marketing using fuzzy logic", Mathematical/Analytical Modelling and Computer Simulation (AMS), 2010 Fourth Asia International Conference on: IEEE, pp. 24–28, 2010. Abstract
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Banerjee, S., H. Al-Qaheri, and A. E. Hassanien, "Mining social networks for viral marketing using fuzzy logic", Mathematical/Analytical Modelling and Computer Simulation (AMS), 2010 Fourth Asia International Conference on: IEEE, pp. 24–28, 2010. Abstract
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Salama, M. A., A. E. Hassanien, and A. A. Fahmy, "Pattern-based subspace classification model", Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on: IEEE, pp. 357–362, 2010. Abstract
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Salama, M. A., A. E. Hassanien, and A. A. Fahmy, "Pattern-based subspace classification model", Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on: IEEE, pp. 357–362, 2010. Abstract
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Heba, E. F., A. Darwish, A. E. Hassanien, and A. Abraham, "Principle components analysis and support vector machine based intrusion detection system", Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on: IEEE, pp. 363–367, 2010. Abstract
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Heba, E. F., A. Darwish, A. E. Hassanien, and A. Abraham, "Principle components analysis and support vector machine based intrusion detection system", Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on: IEEE, pp. 363–367, 2010. Abstract
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Hassanien, A. E., G. Schaefer, and H. AlQaheri, "Prostate Boundary Detection in Ultrasound Images Based on Type-II Fuzzy Sets and Modified Fuzzy C-Means", Soft Computing in Industrial Applications: Springer Berlin Heidelberg, pp. 187–195, 2010. Abstract
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Hassanien, A. E., G. Schaefer, and H. AlQaheri, "Prostate Boundary Detection in Ultrasound Images Based on Type-II Fuzzy Sets and Modified Fuzzy C-Means", Soft Computing in Industrial Applications: Springer Berlin Heidelberg, pp. 187–195, 2010. Abstract
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Salama, M. A., A. E. Hassanien, and A. A. Fahmy, "Reducing the influence of normalization on data classification", Computer Information Systems and Industrial Management Applications (CISIM), 2010 International Conference on: IEEE, pp. 609–613, 2010. Abstract
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Salama, M. A., A. E. Hassanien, and A. A. Fahmy, "Reducing the influence of normalization on data classification", Computer Information Systems and Industrial Management Applications (CISIM), 2010 International Conference on: IEEE, pp. 609–613, 2010. Abstract
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Hassanien, A. E., H. Al-Qaheri, and A. Abraham, "Rough Hybrid Scheme", Rough Fuzzy Image Analysis: Foundations and Methodologies: CRC Press, pp. 5–1, 2010. Abstract
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Banerjee, S., H. Al-Qaheri, E. - S. A. El-Dahshan, and A. E. Hassanien, "Rough set approach in ultrasound biomicroscopy glaucoma analysis", Advances in Computer Science and Information Technology: Springer Berlin Heidelberg, pp. 491–498, 2010. Abstract
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Banerjee, S., H. Al-Qaheri, E. - S. A. El-Dahshan, and A. E. Hassanien, "Rough set approach in ultrasound biomicroscopy glaucoma analysis", Advances in Computer Science and Information Technology: Springer Berlin Heidelberg, pp. 491–498, 2010. Abstract
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Liu, H., A. Abraham, and A. E. Hassanien, "Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm", Future Generation Computer Systems, vol. 26, no. 8: Elsevier, pp. 1336–1343, 2010. Abstract
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Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, and V. Snasel, "Semi-automatic annotation system for home videos", Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on: IEEE, pp. 1275–1280, 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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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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Kudělka, M., Václav Snášel, Z. Horák, A. E. Hassanien, and A. Abraham, "Web communities defined by web page content", Computational Social Network Analysis: Springer London, pp. 349–370, 2010. Abstract
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Kudělka, M., Václav Snášel, Z. Horák, A. E. Hassanien, and A. Abraham, "Web communities defined by web page content", Computational Social Network Analysis: Springer London, pp. 349–370, 2010. Abstract
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2009
Kudelka, M., V. Snásel, Z. Horak, and A. E. Hassanien, "From Web Pages to Web Communities", Annual International Workshop on DAtabases, TExts, Specifications and Objects, Spindleruv Mlyn, Czech Republic , April 15-17, 2009. 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. From our point of view, the Web page is entity carrying information about these communities and this 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 illustrates the benefits of our approach.

Hassanien, A. E., Computational Intelligence in Medical Imaging: Techniques and Applications, , USA, Chapman and Hall/CRC , 2009. AbstractWebsite

A compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical image processing as well as improve medical imaging research. The contributors also cover state-of-the-art research toward integrating medical image processing with artificial intelligence and machine learning approaches.

Grosan, C., A. Abraham, and A. - E. Hassanien, "Designing resilient networks using multicriteria metaheuristics", Telecommunication Systems , vol. 40, issue 1-2, pp. 75-88, 2009. AbstractWebsite

The paper deals with the design of resilient networks that are fault tolerant against link failures. Usually,
fault tolerance is achieved by providing backup paths, which are used in case of an edge failure on a primary path. We consider this task as a multiobjective optimization problem: to provide resilience in networks while minimizing the cost subject to capacity constraint. We propose a stochastic approach,
which can generate multiple Pareto solutions in a single run. The feasibility of the proposed method is illustrated by considering several network design problems using a single weighted average of objectives and a direct multiobjective optimization approach using the Pareto dominance concept.

Aboul-Ella Hassanien, Ajith Abraham, A. V. W. P., Foundations of Computational Intelligence Volume 1: Learning and Approximation, , Germany , Studies in Computational Intelligence, Springer Verlag, Vol. 201 , 2009. AbstractWebsite

Learning methods and approximation algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time. Both kinds of problems have a large number of applications arising from a variety of fields, such as algorithmic game theory, approximation classes, coloring and partitioning, competitive analysis, computational finance, cuts and connectivity, geometric problems, inapproximability results, mechanism design, network design, packing and covering, paradigms for design and analysis of approximation and online algorithms, randomization techniques, real-world applications, scheduling problems and so on. The past years have witnessed a large number of interesting applications using various techniques of Computational Intelligence such as rough sets, connectionist learning; fuzzy logic; evolutionary computing; artificial immune systems; swarm intelligence; reinforcement learning, intelligent multimedia processing etc.. In spite of numerous successful applications of Computational Intelligence in business and industry, it is sometimes difficult to explain the performance of these techniques and algorithms from a theoretical perspective. Therefore, we encouraged authors to present original ideas dealing with the incorporation of different mechanisms of Computational Intelligent dealing with Learning and Approximation algorithms and underlying processes.

Aboul-Ella Hassanien, Ajith Abraham, F. H., Foundations of Computational Intelligence Volume 2: Approximate Reasoning, , Germany, Studies in Computational Intelligence, Springer Verlag, Vol. 202 , 2009. AbstractWebsite

Human reasoning usually is very approximate and involves various types of uncertainties. Approximate reasoning is the computational modelling of any part of the process used by humans to reason about natural phenomena or to solve real world problems. The scope of this book includes fuzzy sets, Dempster-Shafer theory, multi-valued logic, probability, random sets, and rough set, near set and hybrid intelligent systems. Besides research articles and expository papers on theory and algorithms of approximation reasoning, papers on numerical experiments and real world applications were also encouraged. This Volume comprises of 12 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Intelligence techniques for approximation reasoning. The Volume is divided into 2 parts: Part-I: Approximate Reasoning – Theoretical Foundations and Part-II: Approximate Reasoning – Success Stories and Real World Applications