A Privacy Preserving for Medical Images Using Watermarking

Now a day’s security is an important issue in transmission of images over network. Provide security to an images and data is very important. For that purpose we can use various techniques. In this technique watermarking is important for provide security and authentication. Watermarking is secret code applied on images or text. Watermarking is used for provide security as well as protect the copyrights of user. Watermarking technique is used in Hospital Data Management for protect the patient diagnostic, X-ray images and information. In these paper we introduce new concept which is useful for provide security patient medical images and his information. In Hospital Data management System there is need of effective data management; authentication, data Storage, and secure access control watermarking provide these various facilities to system. The main objective of this paper is embedding, and extracting watermark without loss of data. In that we used invisible watermarking also used concept reversible watermarking to retrieve original image

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Not AvailablePresent study was undertaken to identify the incidence rate for five major pathogens viz., Staphylococcus aureus (S. aureus), Staphylococcus epidermidis (S. epidermidis), Streptococcus agalactiae (S. agalactiae), Streptococcus dysgalactiae (S. dysgalactiae) and Escherichia coli (E. coli) in the milk samples collected from Bangalore and Kolar district by PCR based microorganism detection technique. A total of 214 composite milk samples were screened by CMT and then PCR based detection of pathogens for the samples was carried out. Results revealed presence of S. aureus in 28.5 per cent of the total animals screened, S. epidermis was identified in 15.42 per cent cases. E. coli followed and the incidence rate was 13.55 per cent with regard to E. coli. S. agalactiae and S. dysgalactiae were identified in 10.28 per cent and 3.74 per cent of the cases respectively. None of the pathogens considered in this study were detected in 117 milk samples, these samples were also observed to be normal for CMT. Present study supported the fact that PCR based identification of mastitis causing pathogens from milk is a rapid and reliable method to reveal the exact bacterial etiology of mastitis.Not Availabl

Superiority of Hybrid Soft Computing Models in Daily Suspended Sediment Estimation in Highly Dynamic Rivers

Estimating sediment flow rate from a drainage area plays an essential role in better watershed planning and management. In this study, the validity of simple and wavelet-coupled Artificial Intelligence (AI) models was analyzed for daily Suspended Sediment (SSC) estimation of highly dynamic Koyna River basin of India. Simple AI models such as the Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were developed by supplying the original time series data as an input without pre-processing through a Wavelet (W) transform. The hybrid wavelet-coupled W-ANN and W-ANFIS models were developed by supplying the decomposed time series sub-signals using Discrete Wavelet Transform (DWT). In total, three mother wavelets, namely Haar, Daubechies, and Coiflets were employed to decompose original time series data into different multi-frequency sub-signals at an appropriate decomposition level. Quantitative and qualitative performance evaluation criteria were used to select the best model for daily SSC estimation. The reliability of the developed models was also assessed using uncertainty analysis. Finally, it was revealed that the data pre-processing using wavelet transform improves the model’s predictive efficiency and reliability significantly. In this study, it was observed that the performance of the Coiflet wavelet-coupled ANFIS model is superior to other models and can be applied for daily SSC estimation of the highly dynamic rivers. As per sensitivity analysis, previous one-day SSC (St-1) is the most crucial input variable for daily SSC estimation of the Koyna River basin