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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Kohbalan Moorthy
Universiti Malaysia Pahang
Computer Science & IT Electrical & Electronics Engineering

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A Blind Multiple Watermarks based on Human Visual Characteristics Ferda Ernawan; Siau-Chuin Liew; Zuriani Mustaffa; Kohbalan Moorthy
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (689.989 KB) | DOI: 10.11591/ijece.v8i4.pp2578-2587

Abstract

Digital watermarking is an alternative solution to prevent unauthorized duplication, distribution and breach of ownership right. This paper proposes a watermarking scheme for multiple watermarks embedding. The embedding of multiple watermarks use a block-based scheme based on human visual characteristics. A threshold is used to determine the watermark values by modifying first column of the orthogonal U matrix obtained from Singular Value Decomposition (SVD). The tradeoff between normalize cross-correlation and imperceptibility of watermarked image from quantization steps was used to achieve an optimal threshold value. The results show that our proposed multiple watermarks scheme exhibit robustness against signal processing attacks. The proposed scheme demonstrates that the watermark recovery from chrominance blue was resistant against different types of attacks.
The importance of data classification using machine learning methods in microarray data Aws Naser Jaber; Kohbalan Moorthy; Logenthiran Machap; Safaai Deris
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 2: April 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i2.15948

Abstract

The detection of genetic mutations has attracted global attention. several methods have proposed to detect diseases such as cancers and tumours. One of them is microarrays, which is a type of representation for gene expression that is helpful in diagnosis. To unleash the full potential of microarrays, machine-learning algorithms and gene selection methods can be implemented to facilitate processing on microarrays and to overcome other potential challenges. One of these challenges involves high dimensional data that are redundant, irrelevant, and noisy. To alleviate this problem, this representation should be simplified. For example, the feature selection process can be implemented by reducing the number of features adopted in clustering and classification. A subset of genes can be selected from a pool of gene expression data recorded on DNA micro-arrays. This paper reviews existing classification techniques and gene selection methods. The effectiveness of emerging techniques, such as the swarm intelligence technique in feature selection and classification in microarrays, are reported as well. These emerging techniques can be used in detecting cancer. The swarm intelligence technique can be combined with other statistical methods for attaining better results.
Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm Mohd Arfian Ismail; Vitaliy Mezhuyev; Kohbalan Moorthy; Shahreen Kasim; Ashraf Osman Ibrahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i1.pp27-35

Abstract

This paper present a hybrid method of Newton method, Differential Evolution Algorithm (DE) and Cooperative Coevolution Algorithm (CCA). The proposed method is used to solve the optimisation problem in optimise the production of biochemical systems. The problems are maximising the biochemical systems production and simultaneously minimising the total amount of chemical reaction concentration involves. Besides that, the size of biochemical systems also contributed to the problem in optimising the biochemical systems production. In the proposed method, the Newton method is used in dealing biochemical system, DE for optimisation process while CCA is used to increase the performance of DE. In order to evaluate the performance of the proposed method, the proposed method is tested on two benchmark biochemical systems. Then, the result that obtained by the proposed method is compare with other works and the finding shows that the proposed method performs well compare to the other works.
Co-Authors Ashraf Osman Ibrahim Aws Naser Jaber Ferda Ernawan Logenthiran Machap Mohd Arfian Ismail Safaai Deris Shahreen Kasim Siau-Chuin Liew Vitaliy Mezhuyev Zuriani Mustaffa