Publications

Export 165 results:
Sort by: [ Author  (Desc)] Title Type Year
A B C D [E] F G H I J K L M N O P Q R S T U V W X Y Z   [Show ALL]
E
Emary, E., Waleed Yamany, and A. E. Hassanien, "New approach for feature selection based on rough set and bat algorithm", Computer Engineering & Systems (ICCES), 2014 9th International Conference on: IEEE, pp. 346–353, 2014. Abstract
n/a
Emary, E., H. M. Zawbaa, and A. E. Hassanien, "Binary ant lion approaches for feature selection", Neurocomputing, vol. 213: Elsevier, pp. 54–65, 2016. Abstract
n/a
Elshazly, H. I., A. M. Elkorany, A. E. Hassanien, and M. Waly, " Chronic eye disease diagnosis using ensemble-based classifier", The second International Conference on Engineering and Technology (ICET 2014) , German Uni - Cairo Egypt, 19 Apr - 20 Apr , 2014.
Elshazly, H. I., A. F. Ali, H. Mahmoud, A. M. Elkorany, and A. E. Hassanien, "Weighted reduct selection metaheuristic based approach for rules reduction and visualization", Computing, Communication and Automation (ICCCA), 2016 International Conference on: IEEE, pp. 274–280, 2016. Abstract
n/a
Elshazly, H. I., N. I. Ghali, A. M. E. Korany, and A. E. Hassanien, "Rough sets and genetic algorithms: A hybrid approach to breast cancer classification", Information and Communication Technologies (WICT), 2012 World Congress on: IEEE, pp. 260–265, 2012. Abstract
n/a
Elshazly, H. I., N. I. Ghali, A. M. E. Korany, and A. E. Hassanien, "Rough sets and genetic algorithms: A hybrid approach to breast cancer classification", Information and Communication Technologies (WICT), 2012 World Congress on: IEEE, pp. 260–265, 2012. Abstract
n/a
Elshazly, H. I., A. M. Elkorany, A. E. Hassanien, and A. T. Azar, "Ensemble classifiers for biomedical data: performance evaluation", Computer Engineering & Systems (ICCES), 2013 8th International Conference on: IEEE, pp. 184–189, 2013. Abstract
n/a
Elshazly, Hanaa, N.; Ghali, A. Korany, and A. E. Hassanien, "Rough sets and genetic algorithms: A hybrid approach to breast cancer classification", World Congress on Information and Communication Technologies (WICT), pp. 260 - 265 , India, Oct. 30 2012-Nov. Abstract

The use of computational intelligence systems such as rough sets, neural networks, fuzzy set, genetic algorithms, etc., for predictions and classification has been widely established. This paper presents a generic classification model based on a rough set approach and decision rules. To increase the efficiency of the classification process, boolean reasoning discretization algorithm is used to discretize the data sets. The approach is tested by a comparatif study of three different classifiers (decision rules, naive bayes and k-nearest neighbor) over three distinct discretization techniques (equal bigning, entropy and boolean reasoning). The rough set reduction technique is applied to find all the reducts of the data which contains the minimal subset of attributes that are associated with a class label for prediction. In this paper we adopt the genetic algorithms approach to reach reducts. Finally, decision rules were used as a classifier to evaluate the performance of the predicted reducts and classes. To evaluate the performance of our approach, we present tests on breast cancer data set. The experimental results obtained, show that the overall classification accuracy offered by the employed rough set approach and decision rules is high compared with other classification techniques including Bayes and k-nearest neighbor.

Elshazly, H., A. T. Azar, A. El-Korany, and A. E. Hassanien, "Hybrid system for lymphatic diseases diagnosis", Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on: IEEE, pp. 343–347, 2013. Abstract
n/a
Elshazly, H. I., H. I. Elshazly, A. E. Hassanien, and A. M. Elkorany, "Hybrid System based on Rough Sets and Genetic Algorithms for Medical Data Classifications", International Journal of Fuzzy System Applications (IJFSA) , vol. 3, issue 4, 2013.
Elshazly, H. I., N. I. Ghali, A. M. E. Korany, and A. E. Hassanien, "Rough sets and genetic algorithms: A hybrid approach to breast cancer classification", Information and Communication Technologies (WICT), 2012 World Congress on: IEEE, pp. 260–265, 2012. Abstract
n/a
Elshazly, H. I., A. M. Elkorany, and A. E. Hassanien, "Ensemble-based classifiers for prostate cancer diagnosis", Computer Engineering Conference (ICENCO), 2013 9th International: IEEE, pp. 49–54, 2013. Abstract
n/a
Elshazly, H. I., A. M. Elkorany, and A. E. Hassanien, "Ensemble-based classifiers for prostate cancer Diagnosis", The 9th IEEE International Computer Engineering Conference (ICENCO 2013) pp. 49 - 54, Cairo, EGYPT -, December 29-30, 2013.
Elshazly, H. I., A. T. Azar, A. E. Hassanien, and A. M. Elkorany, "Hybrid system based on rough sets and genetic algorithms for medical data classifications", International Journal of Fuzzy System Applications (IJFSA), vol. 3, no. 4: IGI Global, pp. 31–46, 2013. Abstract
n/a
Elshazly, H., A. T. Azar, A. El-Korany, and A. E. Hassanien, "Hybrid System for Lymphatic Diseases Diagnosis ", International Conference on Advances in Computing, Communications and Informatics , (ICACCI-2013) Mysore, India , August 22-25, 2013. hybridabo12_2.pdf
Elshazly, H. I., A. M. Elkorany, and A. E. Hassanien, "Lymph diseases diagnosis approach based on support vector machines with different kernel functions", Computer Engineering & Systems (ICCES), 2014 9th International Conference on: IEEE, pp. 198–203, 2014. Abstract
n/a
Elshazly, H. I., M. Waly, A. M. Elkorany, and A. E. Hassanien, "Chronic eye disease diagnosis using ensemble-based classifier", Engineering and Technology (ICET), 2014 International Conference on: IEEE, pp. 1–6, 2014. Abstract
n/a
Elmasry, W. H., H. M. Moftah, N. El-Bendary, and A. E. Hassanien, "Performance evaluation of computed tomography liver image segmentation approaches", Hybrid Intelligent Systems (HIS), 2012 12th International Conference on: IEEE, pp. 109–114, 2012. Abstract
n/a
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
n/a
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
n/a
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.

Ella Hassanien, A., M. E. Abdelhafez, and H. S. Own, "Rough set analysis in knowledge discovery: a case of Kuwaiti diabetic children patients", Advances in Fuzzy Systems, pp. 1–13, 2007. Abstract
n/a
Elhoseny, M., A. Farouk, A. Shehab, and A. E. Hassanien, "Secure Image Processing and Transmission Schema in Cluster-Based Wireless Sensor Network", Handbook of Research on Machine Learning Innovations and Trends, USA, IGI, 2017. Abstract

WSN as a new category of computer-based computing platforms and network structures is showing new applications in different areas such as environmental monitoring, health care and military applications. Although there are a lot of secure image processing schemas designed for image transmission over a network, the limited resources and the dynamic environment make it invisible to be used with Wireless Sensor Networks (WSNs). In addition, the current secure data transmission schemas in WSN are concentrated on the text data and are not applicable for image transmission's applications. Furthermore, secure image transmission is a big challenging issue in WSNs especially for the application that uses image as its main data such as military applications. The reason why is because the limited resources of the sensor nodes which are usually deployed in unattended environments. This chapter introduces a secure image processing and transmission schema in WSN using Elliptic Curve Cryptography (ECC) and Homomorphic Encryption (HE).

Elhoseny, M., N. Metawa, and A. E. Hassanien, "An automated information system to ensure quality in higher education institutions,", 2016 12th International Computer Engineering Conference (ICENCO), , Cairo, 28-29 Dec, 2016. Abstract

Despite the great efforts to assure quality in higher education institutions, the ambiguity of its related concepts and requirements constitute a big challenge when trying to implement it as an automated information system. The present work introduces a framework for an automated information system that manages the quality assurance in higher educations institutions. The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions. In addition, the proposed system helps all higher education stockholders to handle and monitor their tasks. Moreover, it aims to help the quality assurance center in a higher education institution to apply its qualitys standards, and to make sure that they are being maintained and enhanced. This information system contains a core module and 17 sub-modules, which are described in this paper.

Elhoseny, M., N. Metawa, and A. E. Hassanien, "An automated information system to ensure quality in higher education institutions", Computer Engineering Conference (ICENCO), 2016 12th International: IEEE, pp. 196–201, 2016. Abstract
n/a
Tourism