Bongale A.M.,College of Engineering, Pune |
Nirmala C.R.,Bapuji Institute of Engineering & Technology
International Journal of Applied Engineering Research | Year: 2016
Clustering in Wireless Sensor Networks (WSNs) has been proven to enhance lifetime of the network. Reducing the energy consumption and parallelly prolonging network lifetime is the research goal of most of the cluster based routing protocols. In this paper, a routing scheme based on Energy and Optimal Inter Cluster Head Distance (EOICHD) for WSNs has been proposed. EOICHD considers parameters such as residual energy and optimal inter cluster head distance to elect the cluster head (CH) nodes. EOICHD ensures that (a) elected CHs are always separated by certain predefined distance (b) election of CHs within close proximity of one another is avoided and (c) CHs are scattered to cover most of the sensing region. Experimental evaluation shows that EOCIHD is far better than LEACH and LEACH-C protocol in terms of network stability, energy consumption, cluster head election pattern, and number of alive nodes over simulation duration. © Research India Publications.
Nijalingappa P.,Bapuji Institute of Engineering Technology
Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2015 | Year: 2015
The effects of the eye abnormalities are mostly gradual in nature which shows the necessity for an accurate abnormality identification system. Abnormality in retina is one among them. Diabetic Retinopathy (DR) is a disease that causes damage to the retina of human eye, which is caused by complications of diabetes. DR is one of the main causes of vision loss and its prevalence keeps rising. Diabetic Retinopathy, a frequent diabetic retinal disease is caused due to the blood vessels in the retina get changes from its original shape. Diabetic Retinopathy generally affects both the human eyes. Most of the ophthalmologists depend on the visual interpretation for the identification of the types of diseases. But, inaccurate diagnosis will change the course of treatment planning which leads to fatal results. Hence, there is a requirement for a bias free automated system which yields highly accurate results. In this paper, we are classifying the various stages of DR. We first present a summary of diabetic retinopathy and its causes. Then, a literature review of the automatic detection of diabetic retinopathy techniques is presented. Explanation and restrictions of retina databases which are used to test the performance of these detection algorithms are given. © 2015 IEEE.
Mutalik S.,Bapuji Institute of Engineering Technology |
VinodKumar C.S.,Ss Institute Of Medical Science And Research Center |
Swamy S.,Bapuji Institute of Engineering Technology |
Manjappa S.,Bapuji Institute of Engineering Technology
Journal of Pure and Applied Microbiology | Year: 2012
Early in the twentieth century, petroleum derived fuels (fossil fuels) began to appear and quickly dominated the market. Low prices persisted for several decades until the advent of the "oil crisis" in the 1970, demanding for alternative to fossil fuel. Current ethanol production processes using crops such as sugar cane and corn are well-established; however, utilization of a cheaper substrate such as lignocellulose could make bioethanol more competitive with fossil fuel. The processing and utilization of this substrate is complex. Lignocellulosic biomass contains carbohydrate fractions that can be converted into ethanol. In order to convert these fractions, the cellulose and hemicelluloses must ultimately be converted or hydrolysed into monosaccharides; it is the hydrolysis that has historically proven to be problematic. Biologically mediated processes are promising for energy conversion, in particular for the conversion of lignocellulosic biomass into fuels. The objective of the present study is to optimise cellulosic ethanol production from bagasse and maize by using Fibrobacter succinogenes isolated from rumen of herbivores animals. In this process cellulose is converted into monosaccharides by Fibrobacter succinogenes. These monosaccharides were subjected to alcoholic fermentation by Saccharomyces cerevisiae. This process of fermentation was followed by distillation at 78°C for alcohol extraction. Optimum temperature, pH and substrate concentration for hydrolyses of bagasse and maize was 39°C, 6 and 3.5% respectively for Fibrobacter succinogenes. For the feed stock of concentration 3.5% of bagasse and maize, ethanol yield of 16.8g/l for bagasse and 13.9 g/l for maize was obtained.
Mutalik S.,S S Institute of Medical science |
Mutalik S.,Bapuji Institute of Engineering Technology |
Vinod Kumar C.S.,S S Institute of Medical science |
Vinod Kumar C.S.,Bapuji Institute of Engineering Technology |
And 4 more authors.
Indian Journal of Biotechnology | Year: 2012
Ethanol is an alternative to fossil fuel. Current ethanol production processes using crops, such as, sugarcane and corn are well-established. However, utilization of a cheaper substrate, such as, lignocellulose makes bioethanol more purposeful. Biologically mediated processes are promising for energy conversion, in particular, for the conversion of lignocellulosic biomass into fuels. In the present study, optimized cellulosic ethanol production from bagasse and sorghum using Ruminococcus albus isolated from rumen of herbivores animals was attempted. R. albus could depolymerise cellulose and hemicellulose as well as could tolerate stress conditions (variable substrate concentration, pH, and temperature). Optimum temperature, pH and substrate concentration for hydrolyses of both bagasse and sorghum by R. albus were found to be 39°C, 8.8 and 3.5%, respectively. For the feed stock (3.5%) of bagasse and sorghum, ethanol yield of 19.8 g/L and 17.42 g/L, respectively was obtained.
Ravindra K.B.,Bapuji Institute of Engineering & Technology |
Murugesh Babu K.,Bapuji Institute of Engineering & Technology
Journal of Natural Fibers | Year: 2016
The present study was aimed at development of microbial resistant textile product using a natural bioactive agent. Ocimum sanctum leaf extract was applied on cotton and polyester/cotton blended fabrics for imparting antibacterial properties to the textile product for health care applications. The fabrics were treated with herbal extract of different concentrations, along with glutaraldehyde as cross-linking agent and sodium hypophosphite as catalyst by exhaust method. Antimicrobial assessment was performed quantitatively by percentage reduction test (AATCC-147-1998) against test organisms gram-positive bacteria staphylococcus aureus (ATCC 6538) and gram-negative bacteria Escherichia coli (ATCC 11230). The results provided evidence that the treated fabric inhibited the growth of gram-positive bacteria by more than 92% as compared to the control samples. Gas chromatography mass spectrometry analysis confirmed the presence of eugenol in Ocimum sanctum extract. Although, the treated fabrics showed enhanced crease recovery property, there was a marginal reduction in tensile properties. Improvement in crease recovery property of treated blended fabric was slightly less as compared to treated cotton fabric. The antimicrobial treatment negatively affects the bending properties and this negative effect was found to be slightly less for blended fabric as compared to pure cotton fabric. © 2016 Taylor & Francis.