Palaniappan Ramu

ECG Steganography provides secured transmission of secret information such as patient personal information through ECG signals. This paper proposes an approach that uses discrete wavelet transform to decompose signals and singular value decomposition (SVD) to embed the secret information into the decomposed ECG signal. The novelty of the proposed method is to embed the watermark using SVD into the two dimensional (2D) ECG image. The embedding of secret information in a selected sub band of the decomposed ECG is achieved by replacing the singular values of the decomposed cover image by the singular values of the secret data. The performance assessment of the proposed approach allows understanding the suitable sub-band to hide secret data and the signal degradation that will affect diagnosability. Performance is measured using metrics like Kullback–Leibler divergence (KL), percentage residual difference (PRD), peak signal to noise ratio (PSNR) and bit error rate (BER). A dynamic location selection approach for embedding the singular values is also discussed. The proposed approach is demonstrated on a MIT-BIH database and the observations validate that HH is the ideal sub-band to hide data. It is also observed that the signal degradation (less than 0.6 %) is very less in the proposed approach even with the secret data being as large as the sub band size. So, it does not affect the diagnosability and is reliable to transmit patient information.

Background and objective Pedicle screw instrumentation is widely used in the treatment of spinal disorders and deformities. Currently, the surgeon decides the holding power of instrumentation based on the perioperative feeling which is subjective in nature. The objective of the paper is to develop a surrogate model which will predict the pullout strength of pedicle screw based on density, insertion angle, insertion depth and reinsertion. Methods A Taguchi's orthogonal array was used to design an experiment to find the factors effecting pullout strength of pedicle screw. The pullout studies were carried using polyaxial pedicle screw on rigid polyurethane foam block according to American society for testing of materials (ASTM F543). Analysis of variance (ANOVA) and Tukey's honestly significant difference multiple comparison tests were done to find factor effect. Based on the experimental results, surrogate models based on Krigging, polynomial response surface and radial basis function were developed for predicting the pullout strength for different combination of factors. An ensemble of these surrogates based on weighted average surrogate model was also evaluated for prediction. Results Density, insertion depth, insertion angle and reinsertion have a significant effect (p < 0.05) on pullout strength of pedicle screw. Weighted average surrogate performed the best in predicting the pull out strength amongst the surrogate models considered in this study and acted as insurance against bad prediction. Conclusions A predictive model for pullout strength of pedicle screw was developed using experimental values and surrogate models. This can be used in pre-surgical planning and decision support system for spine surgeon.

Groundwater resources in many villages of the developing countries have been undergoing rapid decline over last few decades due to their unsustainable large scale exploitation. One of the main reasons for such overexploitation is the inability of village communities to collectively visualize and understand clearly the long term implications of such overexploitation. There is hence an urgent need to create awareness among stakeholders about the unsustainable nature of such overexploitation and to facilitate sustainable usage. Spatio-temporal participatory modeling of their water management practices can help greatly in promoting such awareness among village communities. These modeling tools can then be used by these stakeholders to analyze various future scenarios and plan their actions in an informed way. In this paper, a participatory modeling framework for carrying out water balance studies at village level is proposed and is demonstrated using case study of a South Indian village. Stakeholders analyzed their past actions and future plans using simulations. Classes needed for simulation and rules for their behaviour, such as what influences the decision of a farmer to sow a crop or to sink a well, were gathered through discussions with knowledgeable stakeholders. An open source Geographical Information System. 'Quantum GIS', extended using Python programming was used as the platform for carrying out and visually presenting these spatio-temporal simulations to the stakeholders.

In order to reduce the computational expense in identifying limit state functions, an efficient adaptive convex hull strategy is presented in this paper. High fidelity simulations are performed at selected subset of an initial design of experiments. A cluster of unwanted behavior is identified and a convex hull is wrapped around it. The faces of the hull form the limit states. The hull is progressively updated with limited additional sample evaluations around the boundary of initial hull. Once the boundaries or areas converge, accounting for uncertainties and estimating reliability indices are straight forward. © 2012 by Palaniappan Ramu.

Connected health enables patient centric interventions resulting in better healthcare and hence better living. In order to accomplish this, bio-signals, medical and diagnosis information are shared and accessed by multiple actors and it is important to protect the privacy of patient data. Steganography is widely used to protect patient data by hiding it in the medical information. Current work investigates ECG steganography using Discrete Wavelet Transform (DWT) and Quick Response (QR) code. Steganography deteriorates the ECG signal and it is important to minimize this deterioration to preserve diagnosability. 1D ECG signal is converted to 2D ECG image and decomposed into sub-bands by subjecting it to DWT. The novelty of the proposed approach lies in converting the patient data into QR code and using it as watermark in ECG steganography. The QR code is embedded in the 2D image using additive quantization scheme. The performance of proposed method is measured using Peak Signal to Noise Ratio, Percentage Residual Difference and Kullback–Leibler distance. These metrics are used as a measure of imperceptibility while the data loss during retrieval is measured by Bit Retrieval Rate. The proposed method is demonstrated on normal ECG signals obtained from MIT-BIH database for different QR code versions. Metrics reveal that imperceptibility decreased for increasing patient data size and increasing scaling factors. Metrics were independent of the sub-band and the proposed method allows reliable patient data protection with full retrieval ability.

Reliability estimation of highly safe structures can be performed efficiently using tail modeling. Classical tail modeling is based on performing a relatively small number of limitstate evaluations through a sampling scheme, selecting a proper threshold value to specify the tail part and then fitting a tail model to the tail part. In this procedure, the limit-state calculations that do not belong to the tail part are mostly discarded, so majority of limitstate evaluations are wasted. Tail modeling can be performed more efficiently if the limitstate evaluations can be guided so that samples can be drawn from the tail part only. Our earlier study showed that the guidance of limit-state function calculations can be achieved by using support vector machines, and the accuracy of reliability estimations can be improved. In this paper, simultaneous construction of support vector machines with adaptive sampling is proposed to increase the accuracy. The performance of the proposed method is evaluated through two structural mechanics example problems: (i) tuned vibration absorber problem and (ii) ten-bar truss problem. It is found for these example problems that the proposed method further increases the accuracy of reliability index predictions.

Current study presents fluid flow analysis using CFD and a surrogate based framework for design optimization of Savonius wind turbines. The CFD model used for the study is validated with results from a physical model in water tunnel experiment. Four variables that best define blade geometry are considered and a feasible design space consisting of different combinations of these variables that provide positive overlap ratio is identified. The feasible space is then sampled with Latin hyper cube design of experiment. Numerical simulations utilizing K-epsilon turbulence model are performed at each point in the Design of Experiments to obtain coefficient of performance and weighted average surrogate (WAS) is fitted to them. Novelty of the current work is the use of WAS for design of savonius turbine. The WAS is an ensemble of surrogates that consists of polynomial response surface, kriging and radial basis functions. Error metrics reveal that WAS performs better compared to any surrogate individually thus avoiding misleading optima and eliminates surrogate dependent optima. WAS is used to explore the design space and perform optimization with limited number of CFD analyses. It is observed that at the optimal profile, there is more power on the rotors and primary recirculation in the immediate downstream of rotor is high, enforcing maximum momentum on turbine.

The Savonius wind turbine, a class of vertical axis wind turbine (VAWT), is simple and provides a better cost-benefit ratio. It works on the principle of differential drag and is effective in rooftop and ground mounting. Despite the advantages of Savonius wind rotors, they are not preferred due to their low aerodynamic performance levels. In order to address this, several experimental and numerical studies have been carried out in recent years. The primary aim of this work is to provide a simple methodology for the robust optimal design of the Savonius wind turbine. In the parameter design stage, the performance of the turbine is maximized using the traditional Taguchi method. An L27 orthogonal array is used considering five factors of three levels each, which affect Cp. Wind speed is considered to be the noise factor. Signal-noise ratio (SNR) metric is used to find the optimal settings for robust design. The aerodynamic performance of the turbine is investigated through dynamic computational fluid dynamics (CFD) models of the design sets. The numerical models used for the simulations are also discussed.

Biomedi cal signals transmitted over the internet are usually tagged with patient information. Data hiding techniq ues such as steganography ensures the security of such data by hiding the data into signa ls. However, data hiding results in signal deterioration that might affect diag nosability. A novel technique which uses curvelet transforms to hide patient information into their ECG signal is presented. Curvelet transform decomposes the ECG signal into frequency sub-bands. A quantisation approach is used to embed patient data into coeffi cients whose values are around zero, in the high-frequency subband. Performance metrics provide the measure of watermar k imperceptibility of the proposed approach. BER is used to m easure the ability to extract patient data. The proposed approach is dem onstrated on the MIT-BIH database and the observations validate that its performance is superior compared with the random locations approach. Although the performance of the proposed approach decreases as patient information size increases, the peak signal-to-noise ratio values are high. Therefore, the proposed approach can be used for the safe transfer of patient data.