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Articles by R. Ravi
Total Records ( 3 ) for R. Ravi
  R. Ravi and S. Radhakrishnan
  A Virtual Private Network (VPN) aims to emulate the services provided by a private network over the shared Internet. The endpoints of VPN are connected using abstractions such as Virtual Channels (VCs). Reliability of an end-to-end VPN connection depends on the reliability of the links and nodes. VPN service providers provide new services with Quality of Service (QoS), guarantees are also resilient to failures. Supporting QoS connections requires the existence of routing mechanisms that computes the QoS paths, where these paths satisfy the QoS constraints. Resilience to failures, on the other hand, is achieved by providing, each primary QoS path, a set of alternative QoS paths, upon a failure of either a link or a node. We aim at to minimize the total bandwidth reserved on the backup edges. The above objectives, coupled with the need to minimize the global use of network resources, imply that the cost of both the primary path and the restoration topology should be a major consideration of the routing process. It turns out that the widely used approach of disjoint primary, restoration paths is not an optimal strategy. Hence, the proposed approximation restoration algorithms construct a restoration topology and this topology protects a portion of the primary QoS path. This approach guarantees to find a restoration topology with optimal cost which satisfies the QoS constraints.
  M. Subadra , N.S. Marimuthu , R. Ravi and G.S. Vijayakumar
  A recent development in odour sensing technology and artificial intelligence, as E-nose system, has rediscovered the use of smell in clinical diagnosis. Nowadays, this technology is becoming an interesting alternative for medical point-of-care devices. This study analyses the possibility of E-nose for rapid and accurate detection of micro-organisms in normal sterile body fluids, to ensure correct chemotherapy. In this study, 75 samples of different kinds of bacteria which are the major cause for Sepsis and Urinary Tract Infection were inoculated in 20 mL growth medium and incubated for 2 h for volatile generation. These samples were analysed with an electronic nose. The instrument, equipped with 12 Metal Oxide Semiconductor (MOS) sensors, was used to generate a pattern of the volatile compounds present in the pathological samples. The sensor responses were evaluated by Principal Component Analysis (PCA) and Artificial Neural Network (ANN). Good results were obtained in the classification of bacterial samples by using a neural network model based on a multilayer perceptron that learned using a back propagation algorithm. The methodology is simple, rapid and the results suggest that the electronic nose could be a used as a tool for detection.
  Usha Dharmaraj , R. Ravi and N.G. Malleshi
  The decorticated finger millet was subjected to high temperature short time treatment to prepare the expanded product. The product with 5.64 expansion ratio showed a cream color and was very light in weight with a bulk density of 0.14 g/ml and contained 4.69 g/100 g protein, 0.74 g/100 g ether extractives, 72 g/100 g carbohydrates, 11 g/100 g dietary fiber, and 190 mg/100 g calcium. The expanded millet was a crisp product with very low compression values (2.14 N) and contained two thin concentric layers with a vacuole inside. The pasting profile of the product revealed substantial initial viscosity and negligible set back viscosity. The functional and textural properties indicated the possible usage of the product in snacks and supplementary foods.
 
 
 
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