Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 31181

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Improving Quality of Business Networks for Information Systems
Computer networks are essential part in computerbased information systems. The performance of these networks has a great influence on the whole information system. Measuring the usability criteria and customers satisfaction on small computer network is very important. In this article, an effective approach for measuring the usability of business network in an information system is introduced. The usability process for networking provides us with a flexible and a cost-effective way to assess the usability of a network and its products. In addition, the proposed approach can be used to certify network product usability late in the development cycle. Furthermore, it can be used to help in developing usable interfaces very early in the cycle and to give a way to measure, track, and improve usability. Moreover, a new approach for fast information processing over computer networks is presented. The entire data are collected together in a long vector and then tested as a one input pattern. Proposed fast time delay neural networks (FTDNNs) use cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented time delay neural networks is less than that needed by conventional time delay neural networks (CTDNNs). Simulation results using MATLAB confirm the theoretical computations.
Digital Object Identifier (DOI):


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[42] Hazem M. El-Bakry, "An Efficient Algorithm for Pattern Detection using Combined Classifiers and Data Fusion," Accepted for publication in Information Fusion Journal.
[43] Hazem M. El-Bakry, "A Novel High Speed Neural Model for Fast Pattern Recognition," Accepted for publication in Soft Computing Journal.
[44] Hazem M. El-Bakry, "Fast Virus Detection by using High Speed Time Delay Neural Networks," Accepted for publication in journal of computer virology.
[45] Hazem M. El-Bakry, "New Fast Principal Component Analysis For Real- Time Face Detection," Accepted for publication in MG&V Journal.
[46] Hazem M. El-Bakry, "A New Neural Design for Faster Pattern Detection Using Cross Correlation and Matrix Decomposition," Accepted for publication in Neural World journal.
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[49] Hazem M. El-Bakry and Mohamed Hamada, "A New Implementation for High Speed Neural Networks in Frequency Space," Lecture Notes in Artificial Intelligence, Springer, KES 2008, Part I, LNAI 5177, pp. 33-40.
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[68] Hazem M. El-Bakry, and Qiangfu Zhao, "A Fast Neural Algorithm for Serial Code Detection in a Stream of Sequential Data," International Journal of Information Technology, vol.2, no.1, pp. 71-90, 2005.
[69] Hazem M. El-Bakry, and Qiangfu Zhao, "Fast Complex Valued Time Delay Neural Networks," International Journal of Computational Intelligence, vol.2, no.1, pp. 16-26, 2005.
[70] Hazem M. El-bakry, and Nikos Mastorakis "Fast Information Processing over Business Networks," Proc. of 9th WSEAS International Conference on Applied Informatics and Communications (AIC'09), Moscow, Russia, August 26-28, 2009, pp.305-324.
[71] Hazem M. El-bakry, and Nikos Mastorakis "An Efficient Electronic Archiving Approach for Office Automation," Proc. of European Computing and Computational Intelligence International Conference, Tbilisi, Georgia, June 26-28, 2009, pp. 130-144.
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