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Abdennaceur Kachouri

Researcher at University of Sfax

Publications -  178
Citations -  2534

Abdennaceur Kachouri is an academic researcher from University of Sfax. The author has contributed to research in topics: Wireless sensor network & Cluster analysis. The author has an hindex of 21, co-authored 168 publications receiving 1860 citations. Previous affiliations of Abdennaceur Kachouri include Information Technology University & University of Gabès.

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A novel chaos-based image encryption using DNA sequence operation and Secure Hash Algorithm SHA-2

TL;DR: The theoretical analysis and experimental results show that the algorithm improves the encoding efficiency, enhances the security of the ciphertext and has a large key space and a high key sensitivity, and it is able to resist against the statistical and exhaustive attacks.
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Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

TL;DR: The promising results of the proposed sleep staging framework suggest that it may be a valuable alternative to existing automatic methods and that it could accelerate visual scoring by providing a robust starting hypnogram that can be further fine-tuned by expert inspection.
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A novel chaos based optical image encryption using fractional Fourier transform and DNA sequence operation

TL;DR: A new method for optical image encryption using fractional Fourier transform, DNA sequence operation and chaos theory is proposed, which has good encryption effect, larger secret key space and high sensitivity to the secret key.
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Hash key-based image encryption using crossover operator and chaos

TL;DR: Experimental results and security analysis show that the scheme can achieve good encryption result through only one round encryption process, the key space is large enough to resist against common attacks, so the scheme is reliable to be applied in image encryption and secure communication.
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A New Approach for Clustering in Wireless Sensors Networks Based on LEACH

TL;DR: In this article, a new method is proposed to optimize Low Energy Adaptive Clustering Hierarchy (O- LEACH) to improve existing LEACH and LEACH-C by selecting cluster according to the residual energy of nodes dynamically.