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Palaniappan Ramu

Researcher at Indian Institute of Technology Madras

Publications -  61
Citations -  1101

Palaniappan Ramu is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Computer science & Steganography. The author has an hindex of 13, co-authored 41 publications receiving 847 citations. Previous affiliations of Palaniappan Ramu include University of Florida.

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Journal ArticleDOI

Multiple tail median approach for high reliability estimation

TL;DR: In this paper, the authors proposed a multiple tail median (MTM) approach, which employs all the five techniques simultaneously and uses the median estimate as the best estimate, which is used as an estimate of the order of magnitude of error in the median.
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QR code based patient data protection in ECG steganography

TL;DR: Current work investigates ECG steganography using Discrete Wavelet Transform (DWT) and Quick Response (QR) code and results reveal that imperceptibility decreased for increasing patient data size and increasing scaling factors.
Journal ArticleDOI

Pull out strength calculator for pedicle screws using a surrogate ensemble approach

TL;DR: A predictive model for pullout strength of pedicle screw was developed using experimental values and surrogate models which can be used in pre-surgical planning and decision support system for spine surgeon.
Proceedings ArticleDOI

Safety Factor and Inverse Reliability Measures

TL;DR: The relationship between the two inverse measures of probabilities performance measure and probability sufficiency factor is established, and their advantages compared to the direct measures of probability and reliability index are described.
Journal ArticleDOI

Optimal design of savonius wind turbines using ensemble of surrogates and CFD analysis

TL;DR: Novelty of the current work is the use of WAS, an ensemble of surrogates that consists of polynomial response surface, kriging and radial basis functions, which performs better compared to any surrogate individually thus avoiding misleading optima and eliminates surrogate dependent optima.