Publications

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Conference Paper
Moftah, H. M., W. H. Elmasry, N. El-Bendary, A. E. Hassanien, and K. Nakamatsu, "Evaluating the effects of k-means clustering approach on medical images", Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on: IEEE, pp. 455–459, 2012. Abstract
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Moftah, H. M., W. H. Elmasry, N. El-Bendary, A. E. Hassanien, and K. Nakamatsu, "Evaluating the effects of k-means clustering approach on medical images", Intelligent Systems Design and Applications (ISDA), 2012 12th International Conference on: IEEE, pp. 455–459, 2012. Abstract
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Mohamed Tahoun, Abd El Rahman Shabayek, A. E. Hassanien, and R. Reulke, "An Evaluation of Local Features on Satellite Images ", The 37th International Conference on Telecommunications and Signal Processing (TSP), which will be held during 2014, ., Berlin, Germany, July 1-3,, 2014. tahoun_shabayek_abo_reulke_tsp2014_berlin.pdf
Mohamed Tahoun, Abd El Rahman Shabayek, A. E. Hassanien, and R. Reulke, "An evaluation of local features on satellite images", Telecommunications and Signal Processing (TSP), 2015 38th International Conference on: IEEE, pp. 1–6, 2015. Abstract
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Nadi, M., N. El-Bendary, H. Mahmoud, and A. E. Hassanien, "Fall detection system of elderly people based on integral image and histogram of oriented gradient feature", Hybrid Intelligent Systems (HIS), 2014 14th International Conference on: IEEE, pp. 23–29, 2014. Abstract
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Moustafa Zein, A. Adl, A. E. Hassanien, A. Badr, and T. - H. Kim, "Friendship Classification from Psychological Theories to Computational Model", 2015 Fourth International Conference on Information Science and Industrial Applications (ISI): IEEE, pp. 55–60, 2015. Abstract
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Abder-Rahman Ali, Micael Couceiro, A. E. Hassenian, M. F. Tolba, and V. Snasel, "Fuzzy C-Means Based Liver CT Image Segmentation with Optimum Number of Clusters", The 5th International Conference on Innovations in Bio-Inspired Computing and Applications (Springer) IBICA2014, Ostrava, Czech Republic., 22-24 June, 2014. Abstractibica2014_p10.pdf

In this paper, we investigate the e ect of using an optimum
number of clusters with Fuzzy C-Means clustering, for Liver CT image
segmentation. The optimum number of clusters to be used was measured
using the average silhouette value. The evaluation was carried out using
the Jaccard index, in which we concluded that using the optimum number
of clusters may not necessarily lead to the best segmentation results.

Abder-Rahman Ali, Micael Couceiro, A. E. Hassanien, M. F. Tolba, and Václav Snášel, "Fuzzy c-means based liver ct image segmentation with optimum number of clusters", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 131–139, 2014. Abstract
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Elmasry, W. H., H. M. Moftah, N. El-Bendary, and A. E. Hassanien, "Graph Partitioning based Automatic Segmentation Approach for CT Scan Liver Images", IEEE Federated Conference on Computer Science and Information Systems, pp. 205–208, Wroclaw - Poland , 9-13 Sept, 2012. Abstractgraph_partitioning_based_automatic_segmentation.pdf

Manual segmentation of liver computerized tomography (CT) images is very time consuming, so it is desired to develop a computer-based approach for the analysis of liver
CT images that can precisely segment the liver without any human intervention. This paper presents normalized cuts graph partitioning approach for liver segmentation from CT images. To evaluate the performance of the presented approach, we present tests on different liver CT images. Experimental results obtained show that the overall accuracy offered by the employed normalized cuts technique is high compared to the well known K-means segmentation approach.

Elmasry, W. H., H. M. Moftah, N. El-Bendary, and A. E. Hassanien, "Graph partitioning based automatic segmentation approach for ct scan liver images", Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on: IEEE, pp. 183–186, 2012. Abstract
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Elmasry, W. H., H. M. Moftah, N. El-Bendary, and A. E. Hassanien, "Graph partitioning based automatic segmentation approach for ct scan liver images", Computer Science and Information Systems (FedCSIS), 2012 Federated Conference on: IEEE, pp. 183–186, 2012. Abstract
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Asmaa Hashem Sweidan, N. El-Bendary, A. E. Hassanien, A. E. -karim Mohamed, and O. Hegazy, "Grey wolf optimizer and case-based reasoning model for water quality assessment", the 1st International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer, Beni Suef University, Beni Suef, Egypt, Nov. 28-30, 2015. Abstract

This paper presents a bio-inspired optimized classification model for
assessing water quality. As fish gills histopathology is a good biomarker for indicating
water pollution, the proposed classification model uses fish gills microscopic
images in order to asses water pollution and determine water quality.
The proposed model comprises five phases; namely, case representation for
defining case attributes via pre-processing and feature extraction steps, retrieve,
reuse/adapt, revise, and retain phases. Wavelet transform and edge detection algorithms
have been utilized for feature extraction stage. Case-based reasoning
(CBR) has been employed, along with the bio-inspired Gray Wolf Optimization
(GWO) algorithm, for optimizing feature selection and the k case retrieval parameters
in order to asses water pollution. The datasets used for conducted experiments
in this research contain real sample microscopic images for fish gills
exposed to copper and water pH in different histopathlogical stages. Experimental
results showed that the average accuracy achieved by the proposed GWO-CBR
classification model exceeded 97.2% considering variety of water pollutants.

Asmaa Hashem Sweidan, N. El-Bendary, A. E. Hassanien, O. M. Hegazy, and A. E. - K. Mohamed, "Grey Wolf Optimizer and Case-Based Reasoning Model for Water Quality Assessment", The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt: Springer International Publishing, pp. 229–239, 2016. Abstract
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Moustafa Zein, A. E. Hassanien, A. Badr, and T. - H. Kim, "Human Activity Classification Approach on Smartphone Using Monkey Search Algorithm", Advanced Communication and Networking (ACN), 2015 Seventh International Conference on: IEEE, pp. 84–88, 2015. Abstract
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Mostafa, A., A. Fouad, M. Houseni, N. Allam, A. E. Hassanien, H. Hefny, and I. Aslanishvili, "A Hybrid Grey Wolf Based Segmentation with Statistical Image for CT Liver Images", International Conference on Advanced Intelligent Systems and Informatics: Springer International Publishing, pp. 846–855, 2016. Abstract
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Mahmoud, R., N. El-Bendary, H. M. O. Mokhtar, and A. E. Hassanien, "ICF based automation system for spinal cord injuries rehabilitation", Computer Engineering & Systems (ICCES), 2014 9th International Conference on: IEEE, pp. 192–197, 2014. Abstract
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Moustafa Zeina, A. A. Fatma Yakouba, A. E. Hassanien, and V. Snasel, "Identifying Circles of Relations from Smartphone Photo Gallery", International Conference on Communications, management, and Information technology (ICCMIT'2015) Volume 65, 2015, Pages 582–591, Ostrava, Czech Republic, 2015. Abstract

Geotagged photos carry hidden data about the surrounding area, and the owner of the photo. Moreover; Geotagged photos have background information about the user, where the alternative resources of Geo-spatial data lack background information. In this study, we propose identification for the circles of relations of the smartphone user from Geotagged photos. The proposed solution mainly depends on a framework, which is based on smartphone photo gallery. The framework extracts a degree of relation between smartphone user and circles of relations entities. Circles of relations incorporate closest people, places, where the participant visits, and interests. The circles of relations are represented in a social graph, which shows the clusters of social relations and interests of smartphone user. The social graph clarifies the nature and the degree of the relations for the participants. The results of framework introduced the relation between the level of variety of participant social relations, and the degree of relations.

Alaa Tharwat, Mahir M. Sharif, A. E. Hassanien, and H. A. Hefny, "Improving Enzyme Function Classification Performance Based on Score Fusion Method.", 10th International Conference Hybrid Artificial Intelligent System, Bilbao, Spain, 23 June, 2015.
Hafez, A. I., H. M. Zawbaa, E. Emary, H. A. Mahmoud, and A. E. Hassanien, "An innovative approach for feature selection based on chicken swarm optimization", Soft Computing and Pattern Recognition (SoCPaR), 2015 7th International Conference of: IEEE, pp. 19–24, 2015. Abstract
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Mahmood, M. A., N. El-Bendary, A. E. Hassanien, and H. A. Hefny, "An Intelligent Multi-Agent Recommender System using Rough Mereology", In Proceedings of the 4th International Conference on Innovations in Bio-inspired Computing and Applications. Advances in Intelligent Systems and Computing (Springer) Volume 237, pp 201-213, 2013. Abstract

This article presents a Multi-Agent approach for handling the problem of recommendation. The proposed system works via two main agents; namely, the matching agent and the recommendation agent. Experimental results showed that the proposed rough mereology based Multi-agent system for solving the recommendation problem is scalable and has possibilities for future modification and adaptability to other problem domains. Moreover, it succeeded in reducing the information overload while recommending relevant decisions to users. The system achieved high accuracy in ranking using users profile and information system profiles. The resulted value of the Mean Absolute Error (MAE) is acceptable compared to other recommender systems applied other computational intelligence approaches.

Mahmood A. Mahmood, N. El-Bendary, Jan Platoš, A. E. Hassanien, and H. A. Hefny, "An Intelligent Multi-agent Recommender System. ", Innovations in Bio-inspired Computing and Applications. Advances in Intelligent Systems and Computing(Springer) , Czech republic , 2013.
Mahmoud, S., N. El-Bendary, M. A. Mahmood, and A. E. Hassanien, "An Intelligent Recommender system for drinking water quality", . 13th IEEE International Conference on Hybrid Intelligent Systems |(HIS13) . pp. 286-291, 2013, Tunisia, , 4-6 Dec, 2013.
Mahmoud, S., N. El-Bendary, M. A. Mahmood, and A. E. Hassanien, "An intelligent recommender system for drinking water quality", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 285–290, 2013. Abstract
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Fouad, M. M., M. A. Mahmood, H. Mahmoud, Adham Mohamed, and A. E. Hassanien, "Intelligent road surface quality evaluation using rough mereology", Hybrid Intelligent Systems (HIS), 2014 14th International Conference on: IEEE, pp. 18–22, 2014. Abstract
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Mostafa, A., A. E. Hassanien, N. I. Ghali, and H. Hefny, "Level Set-based Liver Image Segmentation with Watershed and ANN Classifier", The IEEE International Conference on Hybrid Intelligent Systems (HIS2012). , Pune. India. 4-7, Dec. 2012,. Abstract

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