Ashraf Khalaf

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I'm an assciate professor in Electronics and Communication Dept., Faculty of Engineering, Minia University. Here is my details: Ashraf A. M. Khalaf (IEEE M’98) received his B.Sc. and M.sc. degrees in 1989, and 1994 respectively. He received his Ph.D from Graduate School of Natural Science and Technology, Kanazawa university, Japan, 2000. He is currently works as an associate professor at electronics and communications engineering Department, Minia University, Egypt.. His research interest includes digital signal processing and its applications in communications, neural networks, and optical communications.

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Assessment of periodontal defects using cone beam computed tomography

Egyptian Journal of Oral & Maxillofacial Surgery, 2011

... doi: 10.1097/01.OMX.0000395513.60344.ff. Research Papers. Assessment of periodontal defects u... more

A new-one-time-pad stream cipher: new design, hardware implementation and its application in security of UAVs

International Journal of Wireless and Mobile Computing, 2020

UAVs are used in military and civilian fields. Security of UAV Data Link is still unsatisfactory ... more UAVs are used in military and civilian fields. Security of UAV Data Link is still unsatisfactory especially if a strong adversary model is considered. This paper describes a new design of AENOTP, tested for security in UAVs Data Link. AENOTP algorithm combines NOTP with AE technique to ensure encryption and authentication along with data integrity. AE is a technique that ensures the security of the transported data. The design and analysis of AENOTP gives a fast and enhanced stream cipher AE architecture based on the unpredictability concept. Implementation of AENOTP measures encryption and decryption of any sent and received data. AENOTP shows high speed of generating the key stream bits of the OTP stream cipher and high speed of the proposed algorithm of 75 Mbits/sec. It achieves high level of security for any transmitted data. It can easily resist different attacks such as linear and differential attacks.

Time series prediction using a hybrid model of neural network and FIR filter

1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227)

Time series prediction is a very important technology in a wide variety of field. The actual time... more Time series prediction is a very important technology in a wide variety of field. The actual time series contains both linear and nonlinear properties. The amplitude of the time series to be predicted is usually continuous value. For this reason, we combine nonlinear and linear predictors in a cascade form. In order to estimate the minimum size of the proposed predictor, we propose a nonlinearity analysis for the time series of interest.Computer simulations using the sunspot data have demonstrated the efficiency of the proposed predictor and the nonlinearity analysis.

Ashraf Khalaf

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