Publications

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D
Mukherjee, A., N. Dey, N. Kausar, A. S. Ashour, R. Taiar, and A. E. Hassanien, " A Disaster Management Specific Mobility Model for Flying Ad-hoc Network", International Journal of Rough Sets and Data Analysis (IJRSDA), vol. 3, issue 3, 2016. AbstractWebsite

The extended Mobile Ad-hoc Network architecture is a paramount research domain due to a wide enhancement of smart phone and open source Unmanned Aerial Vehicle (UAV) technology. The novelty of the current work is to design a disaster aware mobility modeling for a Flying Ad-hoc network infrastructure, where the UAV group is considered as nodes of such ecosystem. This can perform a collaborative task of a message relay, where the mobility modeling under a “Post Disaster” is the main subject of interest, which is proposed with a multi-UAV prototype test bed. The impact of various parameters like UAV node attitude, geometric dilution precision of satellite, Global Positioning System visibility, and real life atmospheric upon the mobility model is analyzed. The results are mapped with the realistic disaster situation. A cluster based mobility model using the map oriented navigation of nodes is emulated with the prototype test bed.

G
Wahid, R., N. I. Ghali, H. S. Own, T. - H. Kim, and A. ella Hassanien., " A Gaussian Mixture Models Approach to Human Heart Signal Verification Using Different Feature Extraction Algorithms ", International Conference on Bio-Science and Bio-Technology (BSBT2012),, , Kangwondo, Korea, , Springer, Heidelberg , pp. pp. 16--24, 2012. Abstract3530016.pdf

In this paper the possibility of using the human heart signal
feature for human verification is investigated. The presented approach
consists of two different robust feature extraction algorithms with a specified
configuration in conjunction with Gaussian mixture modeling. The
similarity of two samples is estimated by measuring the difference between
their negative log-likelihood of the features. To evaluate the performance
and the uniqueness of the presented approach tests using a
high resolution auscultation digital stethoscope are done for nearly 80
heart sound samples. The experimental results obtained show that the
accuracy offered by the employed Gaussian mixture modeling reach up
to 100% for 7 samples using the first feature extraction algorithm and
6 samples using the second feature extraction algorithm and varies with
average 85%.

C
Torky, M., R. Babers, R. A. Ibrahim, A. E. Hassanien, G. Schaefer, I. Korovin, and S. Y. Zhu, " Credibility investigation of newsworthy tweets using a visualising Petri net model", 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), , USA, 9-12 Oct. 2016. Abstract

Investigating information credibility is an important problem in online social networks such as Twitter. Since misleading information can get easily propagated in Twitter, ranking tweets according to their credibility can help to detect rumors and identify misinformation. In this paper, we propose a Petri net model to visualise tweet credibility in Twitter. We consider the uniform resource locator (URL) as an effective feature in evaluating tweet credibility since it is used to identify the source of tweets, especially for newsworthy tweets. We perform an experimental evaluation on about 1000 tweets, and show that the proposed model is effective for assigning tweets to two classes: credible and incredible tweets, which each class being further divided into two sub-classes (“credible” and “seem credible” and “doubtful” and “incredible” tweets, respectively) based on appropriate features.

H
Hassanien, A. E., M. A. Fattah, S. Aboulenin, G. Schaefer, S. Y. Zhu, and I. Korovin, " Historic handwritten manuscript binarisation using whale optimization, Systems", IEEE International Conference on Systems, Man, and Cybernetics (SMC), 9, 9-12 Oct. 2016. Abstract

Preserving the content of historic handwritten manuscripts is important for a variety of reasons. On the other hand, digital libraries are rapidly expanding and thus facilitate to store this information directly in digital form. For digitising text documents, a crucial step is to binarise the captured images to separate the text from the background. In this paper, we propose an effective approach for binarisation of handwritten Arabic manuscripts which employs a whale optimisation algorithm, incorporating a fuzzy c-means objective function, to obtain optimal thresholds. Experimental results confirm the effectiveness of the proposed approach compared to earlier methods.

1
Karam, H., A. E. Hassanien, and M. Nakajima, "15-1 Polar Decomposition Interpolations for Linear Fractal Metamorphosis", 映像情報メディア学会年次大会講演予稿集, no. 1998: 一般社団法人映像情報メディア学会, pp. 200–201, 1998. Abstract
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Hassanien, A. E., H. Karam, and M. Nakajima, "15-2 Image Metamorphosis for Inter Slice Interpolation of Medical Images", 映像情報メディア学会年次大会講演予稿集, no. 1998: 一般社団法人映像情報メディア学会, pp. 202–203, 1998. Abstract
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A
Kilany, M., A. E. Hassanien, and A. Badr, "Accelerometer-based human activity classification using Water Wave Optimization approach", Computer Engineering Conference (ICENCO), 2015 11th International: IEEE, pp. 175–180, 2015. Abstract
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Hassanien, A. E., T. - H. Kim, P. S. Rajan, and K. K. K. Hari, "Analysis of Energy Utilization through Mobile Ad Hoc Network with AODV", Proc. of the Intl. Conf. on Computer Applications, vol. 1, 2012. Abstract

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Karam, H., A. - E. Hassanien, and M. Nakajima, "Animation of linear fractal shapes using polar decomposistion interpolation", Journal of ITE, vol. 53, no. 3, 1999. Abstract
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Hossam Moftah, Walaa Elmasry, A. E. Hassanien, Adel Alimi, H. Karray, and M. Tolba, "Ant-based clustering algorithm for magnetic resonance breast image segmentation", 13th IEEE International Conference on Hybrid Intelligent Systems | (HIS13) . pp. 162-167, Tunisia, , 4-6 Dec, 2013.
Moftah, H. M., A. E. Hassanien, A. M. Alimi, H. Karray, and M. F. Tolba, "Ant-based clustering algorithm for magnetic resonance breast image segmentation", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 161–166, 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, "Applying formal concept analysis for visualizing DNA methylation statusamong breast cancer tumors subtypes", The 9th IEEE International Computer Engineering Conference (ICENCO 2013) pp. 37 - 42, Cairo, EGYPT -, December 29-30, , 2013.
Václav Snášel, A. Keprt, A. Abraham, and A. E. Hassanien, "Approximate string matching by fuzzy automata", Man-Machine Interactions: Springer Berlin Heidelberg, pp. 281–290, 2009. Abstract
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Václav Snášel, A. Keprt, A. Abraham, and A. E. Hassanien, "Approximate string matching by fuzzy automata", Man-Machine Interactions: Springer Berlin Heidelberg, pp. 281–290, 2009. Abstract
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Fattah, M. A., M. A. A. ELsoud, A. E. Hassanien, and T. - H. Kim, "Automated classification of galaxies using invariant moments", International Conference on Future Generation Information Technology: Springer Berlin Heidelberg, pp. 103–111, 2012. Abstract
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Fattah, M. A., M. A. A. ELsoud, A. E. Hassanien, and T. - H. Kim, "Automated classification of galaxies using invariant moments", International Conference on Future Generation Information Technology: Springer Berlin Heidelberg, pp. 103–111, 2012. Abstract
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El-Bendary, N., T. - H. Kim, A. E. Hassanien, and M. Sami, "Automatic image annotation approach based on optimization of classes scores", Computing -Spriner , vol. 96, issue 5, pp. 381-402 , 2014. Website
El-Bendary, N., T. - H. Kim, A. E. Hassanien, and M. Sami, "Automatic image annotation approach based on optimization of classes scores", Computing, vol. 96, no. 5: Springer Vienna, pp. 381–402, 2014. Abstract
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B
Kilany, M., A. E. Hassanien, A. Badr, P. - W. Tsai, and J. - S. Pan, "A Behavioral Action Sequences Process Design", International Conference on Advanced Intelligent Systems and Informatics: Springer International Publishing, pp. 502–512, 2016. Abstract
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Heba, E., M. Salama, A. E. Hassanien, and T. - H. Kim, "Bi-Layer Behavioral-Based Feature Selection Approach for Network Intrusion Classification", Security Technology - International Conference, SecTech 2011, pp.195-203, Jeju Island, Korea, December 8-10,, 2011. Abstract

To satisfy the ever growing need for effective screening and diagnostic tests, medical practitioners have turned their attention to high resolution, high throughput methods. One approach is to use mass spectrometry based methods for disease diagnosis. Effective diagnosis is achieved by classifying the mass spectra as belonging to healthy or diseased individuals. Unfortunately, the high resolution mass spectrometry data contains a large degree of noisy, redundant and irrelevant information, making accurate classification difficult. To overcome these obstacles, feature extraction methods are used to select or create small sets of relevant features. This paper compares existing feature selection methods to a novel wrapper-based feature selection and centroid-based classification method. A key contribution is the exposition of different feature extraction techniques, which encompass dimensionality reduction and feature selection methods. The experiments, on two cancer data sets, indicate that feature selection algorithms tend to both reduce data dimensionality and increase classification accuracy, while the dimensionality reduction techniques sacrifice performance as a result of lowering the number of features. In order to evaluate the dimensionality reduction and feature selection techniques, we use a simple classifier, thereby making the approach tractable. In relation to previous research, the proposed algorithm is very competitive in terms of (i) classification accuracy, (ii) size of feature sets, (iii) usage of computational resources during both training and classification phases.

Eid, H. F., M. A. Salama, A. E. Hassanien, and T. - H. Kim, "Bi-layer behavioral-based feature selection approach for network intrusion classification", International Conference on Security Technology: Springer Berlin Heidelberg, pp. 195–203, 2011. Abstract
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Eid, H. F., M. A. Salama, A. E. Hassanien, and T. - H. Kim, "Bi-layer behavioral-based feature selection approach for network intrusion classification", International Conference on Security Technology: Springer Berlin Heidelberg, pp. 195–203, 2011. Abstract
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