A Systematic Inspection into the Criteria of Lecturer Performance in Educational Domain
Osama H. Al-Masri1, Sulfeeza Mohd Drus2, Ahmad Aabed Al-Hayy AlDalaien3
1Osama H. Al-Masri*, College of Graduate Studies, Universiti Tenaga Nasional Jalan Ikram-UNITEN, Kajang, Selangor Darul Ehsan, Malaysia.
2Sulfeeza Mohd Drus, Department of Information Systems, Universiti Tenaga Nasional Jalan Ikram-UNITEN, Kajang, Selangor Darul Ehsan, Malaysia
3Ahmad Aabed Al-Hayy AlDalaien, College of Graduate Studies, Universiti Tenaga Nasional Jalan Ikram-UNITEN, Kajang, Selangor Darul Ehsan, Malaysia.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 1587-1592 | Volume-9 Issue-1, October 2019 | Retrieval Number: A2628109119/2019©BEIESP | DOI: 10.35940/ijeat.A2628.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this novel technique, a modified singular value decomposition named normalized singular value decomposition (NSVD) used for select the original image features to embedding the watermark image into these features. So, the quality of the original image won’t be affected. To select the Normalization Constant of NSVD, the optimization technique used is Genetic Algorithm (GA). In embedding stage, Particle Swarm Optimization (PSO) is used to optimize watermarking constant. Instead of these preliminaries the novel approach also used normalized block processing (NBP) to make the watermarked image more robust to rotation and flipping attacks. The various experiments are conducted on the novel approach to estimate the performance. The experimental results achieved good Robustness for most of the attacks compared to conventional approaches.
Keywords: NBP, IWT, DCT, NSVD, PSNR, NCC, SSIM.