Publications

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Owis, A. H., H. M. Mohammed, H. R. Dwidar, and Daniele Mortari, "GPS Satellite Range and Relative Velocity Computation", Theory and Applications of Mathematics & Computer Science, vol. 2, issue 1, pp. p53-60, 2012.
Owis, M. I., A. M. Youssef, and Y. M. I. Kadah, Novel Techniques for Cardiac Arrhythmia Detection, , 2001. Abstract
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Owis, A. I., A. M. Abo-youssef, and A. H. Osman, "Leaves of Cordia boissieri A. DC. as a potential source of bioactive secondary metabolites for protection against metabolic syndrome-induced in rats", Z. Naturforsch, vol. 4, issue 2, pp. 1-12, 2016.
Owis, M. I., A. H. Abou-Zied, A. - B. M. Youssef, and Y. M. Kadah, "Robust feature extraction from ECG signals based on nonlinear dynamical modeling", Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2, 2001. Abstract
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Owis, M., A. H. Abou-Zied, A. - B. M. Youssef, Y. M. Kadah, and others, "Robust feature extraction from ECG signals based on nonlinear dynamical modeling", Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE, vol. 2: IEEE, pp. 1585–1588, 2001. Abstract
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Owis, F., A. H. Nayfeh, and D. T. Mook, "Control of roll motion using a system of spoilers", Seventh Semi-Annual Meeting–MURI-Nonlinear Active Control of Dynamical Systems, 2000. Abstract
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Owis, A. I., A. M. Abo-youssef, and A. H. Osman, "Protective effect of Cordia boissieri A. DC. (Boraginaceae) on metabolic syndrome", . Journal of Applied Pharmaceutical Science , vol. 6, issue 8, pp. 083-089, 2016. 1954_pdf_osman_pharm_papaper.pdf
i. Owis, M., A. h. Abou-zied, A. bm. Youssef, and Y. m. Kadah, "Study of features based on nonlinear dynamical modeling in ECG arrhythmia detection and classification", Biomedical Engineering, 2002. Abstract
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Owis, M. I., A. H. Abou-Zied, A. Youssef, and Y. M. Kadah, "Robust feature extraction from ECG signals based on nonlinear dynamical modeling", Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE, vol. 2: IEEE, pp. 1585-1588, 2001. Abstract
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Owis, F. M., and A. H. Nayfeh, "Computations of the compressible multiphase flow over the cavitating high-speed torpedo", Journal of fluids engineering, vol. 125, no. 3: American Society of Mechanical Engineers, pp. 459–468, 2003. Abstract
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Owis, A. H., H. M. Mohammed, H. R. Dwidar, and D. Mortari, "Accurate Doppler Shift Computation of an Artificial Satellite", First International Conference on New Trends and Applications of GNSS, Giza Egypt, 1-4 Sep., 2012.
Owis, M. I., A. H. Abou-Zied, A. - B. M. Youssef, and Y. M. Kadah, "Study of features based on nonlinear dynamical modeling in ECG arrhythmia detection and classification", IEEE Trans on Biomedical. Engineering, vol. 49, no. 7, pp. 733–736, 2002. Abstract

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Owis, F., and P. Balakumar, "Linear and nonlinear stability of jets using DNS", APS Division of Fluid Dynamics Meeting Abstracts, vol. 1, 1998. Abstract
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Owis, M. I., A. S. A. Mohamed, Abou-Bakr, and M. E. Rasmy, "Quality Assessment of Ultrasound Images after Transmission", International Congress of Ultrasonography, In collaboration with Gastroenterology & Hepatology Department, Hannover University – Germany, Cairo, Egypt, 1996. Abstract
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Owis, F., and P. Balakumar, lo-13Januaty2000/Reno, NV, , 2000. Abstract
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Own, H., and A. E. Hassanien, "Automatic Image Registration Algorithm Based on Multiresolution Local Contrast Entropy and Mutual Information", International Journal of Computers and Their Applications, vol. 12, issue 1, pp. 9-15, 2005.
Own, H. S., and A. E. Hassanien, "Rough wavelet hybrid image classification scheme", Journal of Convergence Information Technology, vol. 3, no. 4, pp. 65–75, 2008. Abstract
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Own, H. S., and A. E. Hassanien, "Rough Wavelet Hybrid Image Classification Scheme", Journal of Convergence Information Technology, vol. 3, issue 4, pp. 65-75, 2008. AbstractWebsite

This paper introduces a new computer-aided classification system for detection of prostate cancer in
Transrectal Ultrasound images (TRUS). To increase the efficiency of the computer aided classification
process, an intensity adjustment process is applied first, based on the Pulse Coupled Neural Network
(PCNN) with a median filter. This is followed by applying a PCNN-based segmentation algorithm to
detect the boundary of the prostate image. Combining the adjustment and segmentation enable to eliminate PCNN sensitivity to the setting of the various PCNN parameters whose optimal selection can be difficult and can vary even for the same problem. Then, wavelet based features have been extracted and
normalized, followed by application of a rough set analysis to discover the dependency between the
attributes and to generate a set of reduct that contains a minimal number of attributes. Finally, a rough
confusion matrix is designed that contain information about actual and predicted classifications done by a
classification system. Experimental results show that the introduced system is very successful and has high detection accuracy

Own, H. S., N. I. GHALL, and E. L. L. A. H. A. S. S. A. N. I. E. N. ABOUL, "Hybrid Dual-Tree Wavelet Transform and Adaptive Threshold for Image Denoising", International journal of imaging and robotics, vol. 9, no. 1: CESER Publications, pp. 17–25, 2013. Abstract
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Own, H. S., and A. E. Hassanien, "Rough wavelet hybrid image classification scheme", Journal of Convergence Information Technology, vol. 3, no. 4, pp. 65–75, 2008. Abstract
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Own, H., and A. E. Hassanien, "Q-shift Complex Wavelet-based Image Registration Algorithm", Proceedings of the 4th International Conference on Computer Recognition Systems, CORES'05, pp. 403-410, Rydzyna Castle, Poland, May 22-25,, 2005. Abstract

This paper presents an efficient image registration technique using the Q-shift complex wavelet transform (Q-shift CWT). It is chosen for its key advantages compared to other wavelet transforms; such as shift invariance, directional selectivity, perfect reconstruction, limited redundancy and efficient computation. The experiments show that the proposed algorithm improves the computational efficiency and yields robust and consistent image registration compared with the classical wavelet transform.

Own, H., and A. Hassanien, "Q-shift Complex Wavelet-based Image Registration Algorithm", Computer Recognition Systems: Springer Berlin/Heidelberg, pp. 403–410, 2005. Abstract
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Own, H., and A. Hassanien, "Q-shift Complex Wavelet-based Image Registration Algorithm", Computer Recognition Systems: Springer Berlin/Heidelberg, pp. 403–410, 2005. Abstract
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Own, H. S., N. I. GHALL, and E. L. L. A. H. A. S. S. A. N. I. E. N. ABOUL, "Hybrid Dual-Tree Wavelet Transform and Adaptive Threshold for Image Denoising", International journal of imaging and robotics, vol. 9, no. 1: CESER Publications, pp. 17–25, 2013. Abstract
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