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Articles by R. Bhaskaran
Total Records ( 2 ) for R. Bhaskaran
  D. Neeraja , B.M. Veeregowda , M. Sobha Rani , D. Rathnamma , R. Bhaskaran , G. Leena , S.H. Somshekhar , M. Saminathan , K. Dhama and S. Chakraborty
  Bovine tuberculosis (bTB), caused by Mycobacterium bovis which belongs to Mycobacterium tuberculosis complex (MTC), is a globally distributed zoonotic disease in cattle. The present study was conducted in a dairy herd with the history of prevalence of bovine tuberculosis. Two Cell Mediated Immunity (CMI) based tests, Single Intradermal Test (SID), gamma interferon (IFN-γ) assay and a serological test (enzyme linked immunosorbant assay, ELISA) were employed for the diagnosis of tuberculosis in 45 animals. Of these, 8 (17.77%) were positive by SID test, 10 (22.22%) by interferon gamma assay and none of the animals were found positive by ELISA. Both the CMI tests performed were found better than the antibody detection. Between the CMI tests, IFN-γ assay showed better sensitivity than the SID test; combination of tests showed better detection of the bTB infection in animals. ELISA results indicated that animals were still in progressive stages of infection and the sensitivity of the tests depends on the stage of infection in the study subjects. As a whole, 26.67% of the animals tested in the farm were found to be positive and/or reactors to tuberculosis. It indicates that both the CMI tests were better than those targeting antibody detection. ELISA did not detect even a single animal as positive. These results indicate that no single test is able to detect all the infected animals and also not having 100 % sensitivity and specificity. So combination of tests always can be better employed for the diagnosis of bovine tuberculosis.
  R. Bhaskaran and S. Saranraj
  In this study, we present a novel frame work for on-demand localization for autonomous deployment in UWSN to find the location and position of the sensor node with minimal error rate, based on the communication link types from the anchor nodes to sensor nodes underwater sensor networks contain anchor nodes and sensor nodes or initiator nodes which initiates the request in order to find its own position with the help of anchor nodes. These nodes listen to the broadcast message localize themselves without consuming additional resources. This proposed research classifies the links LOS (Line Of Sight), OLOS (Object based LOS) and SLOS (Sea based LOS) respectively, based on binary evaluation theorem using propagation delay, absorption loss and reflection loss as a key factor. Location estimation of sensor node can be computed whenever there is a change in network topology. Position accuracy can be achieved by classifying the links types and compute the values of selected links. This study focuses on the classification of the links and how it can be analyzed to produce location accuracy in UWSN.
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