Vishākhapatnam, India
Vishākhapatnam, India

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Venkata Ramana Chary R.,Padmasri Drbv Raju Institute Of Technology | Rajya Lakshmi D.,GITAM Institute of Technology
2012 International Conference on Machine Vision and Image Processing, MVIP 2012 | Year: 2012

Computer vision field over the last decades, Content-Based Image Retrieval (CBIR) systems are used in order to search, retrieve and browse image from databases. This accumulation of large collections of digital images has created the need for efficient and intelligent schemes for classifying and retrieval of images. In our proposed method, we are using, Clustering Algorithms for retrieving the images from huge volumes of data with better performance. This requires image processing, feature extraction, classification of images and retrieval steps in order to develop an efficient image retrieval system. In this work, processing is done through the image clustering method [1] which is used for feature extraction which is taken place. For retrieval of images, mean values are calculated between Query image and database images and all clustered mean values are considered as a sorted order. When the comparisons are allowed between the images, in our observation we founded excellent performance and similarities in between images. The main aim of this work is to extract images with good similarity when the images are retrieved based on query image. © 2012 IEEE.

Venkata Ramana Chary R.,BVRIT | Rajya Lakshmi D.,GITAM Institute of Technology
Lecture Notes in Electrical Engineering | Year: 2013

Image retrieval has been one of the most interesting and vivid research areas in the field of computer vision over the last decades. Image Retrieval systems are used in order to automatically index, search, retrieve, and surf image databases. Gathering of large collections of digital images has created the need for efficient and intelligent schemes for classifying and retrieval of images. In our proposed method, we are using Clustering Algorithm for retrieving the images from huge volumes of data with better performance. This requires image processing methods like color histogram feature extraction, classification of images, retrieval, and indexing steps in order to develop an efficient image retrieval system. In this work, processing is done through the image clustering method which is used for feature extraction taken place, classification is done using K-means [1] classification algorithm [2]. For retrieval of images, Euclidian distance method values are calculated between query image and database images. The main aim of this work is to extract images with similarity when the images are retrieved based on query image. © 2013 Springer Science+Business Media.

Kiranmai Reddy M.,GITAM Institute of Technology | Avasn Maruthi Y.,GITAM Institute of Science | Aruna Lakshmi K.,Gandhi Institute of Technology and Management
Rasayan Journal of Chemistry | Year: 2010

The increasing urbanization, industrialization has direct impact on urban waste. Solid waste management is an important factor of environmental hygiene and needs to be integrated with total environmental planning. Biodegradation is termed as natural process of recycling. Fungi play an important role in biodegradation as they are more active in carbon assimilation than bacteria and actinomycetes. The results of physico-chemical parameters of selected soil samples at different depths showed an increase in organic carbon content than surface soils and sub surface soils. The pH of all samples was neutral to slightly alkaline, shows the favorable condition for the growth of fungi. The scope of the present work attempts to search for an effective method of delignification by using lignolytic soil fungi. The cellulose and lignin degradation has been effectively done by Phanerochaete Chrysosporium (80%) and Aspergillus flavus (75%). Where Phanerochaete Chrysosporium shown the maximum release of carbon dioxide during biodegradation. Pre and post degradation studies were carried where there is a decrease in pH of the soils were observed due to the degradation by fungal species.

Kumar P.C.,GITAM Institute of Technology | Kumar P.C.,Andhra University | Murali M.,GITAM Institute of Technology | Murali M.,Andhra University | And 4 more authors.
Pollution Research | Year: 2010

Disposal of industrial solid wastes has emerged as major environmental problem. The suitability and demand for usage of different industrial wastes like flyash, slag etc. in favoured to conserve the natural resources base and reduction in consumption of naturals materials in construction to attain sustainable development. In the present investigation, an attempt has be made to study the improvement of strength and durability of concrete by using industrial waste (Flyash). The present study focuses on the durability characteristics of M20 grade concrete with partial replacement of fly ash 00/0, 250/0, 35% and 45% in cement for this 100 & 100 & 100 mm cubes were cast and immersed in the Sulphuric acid solution of 0.1,1 and 3 percentages of concentration. The reduction in strengths and weight has been found at intervals of 3 days up to 28 days. The final characteristic strength results shows beneficial effects of increase in durability with higher percentage of fly ash repayment compared to normal concrete when exposed to various concentrations of acid. Use of flyash observed, to have a significant impact is strength and durability of concrete when the flyash is available locally in large quantities. Copyright © EM International.

Reddy V.V.,Jayamukhi Institute of Technological science | Kumar A.,National Institute of Technology Warangal | Valli P.M.,GITAM Institute of Technology | Reddy C.S.,Jawaharlal Nehru Technological University Anantapur
Journal of the Brazilian Society of Mechanical Sciences and Engineering | Year: 2015

In the present work, an investigation has been made into the electrical discharge machining process (EDM) when both graphite powder and surfactant-mixed dielectric fluid were used during EDM of precipitation hardening stainless steel PH17-4. The addition of graphite powder in the dielectric fluid results in uniform distribution of discharge, which improves surface finish. However, agglomeration of graphite particles is found in the dielectric due to the electrostatic forces among the graphite powder particles. The addition of surfactant in the dielectric increases dielectric conductivity and in turn reduces relay time of discharge. This increases actual discharge time, which results in more material removal. At the same time, uniform distribution of graphite powder particles in the dielectric fluid is achieved. This leads to increase in discharge frequency, which results in increase in material removal rate and surface finish. Taguchi parameter design approach was used to get an optimal parametric setting of EDM process parameters namely: peak current, surfactant concentration and graphite powder concentration that yields to optimal process performance characteristics such as material removal rate, surface roughness, white layer thickness and surface crack density. Individual effect of process parameters on performance characteristics was also studied. To identify the significance of parameters on measured response, the analysis of variance has been carried out. Further, mathematical models were developed by performing nonlinear regression analysis to predict process performance characteristics. Confirmation tests were conducted at their respective optimal parametric settings to verify the predicted optimal values of performance characteristics. © 2014, The Brazilian Society of Mechanical Sciences and Engineering.

Lalitha P.,GITAM Institute of Science | Reddy N.N.R.,GITAM Institute of Science | Arunalakshmi K.,GITAM Institute of Technology
Bioremediation Journal | Year: 2011

A problem of paramount importance that has attracted the attention of environmental biologists is the discharge of highly colored effluents into the environment by various industries, which use a wide range of synthetic dyes. The existing chemical methods for dye degradation are not only expensive but also contributes to secondary pollution due to high dose of the chemicals used. Hence an alternative is to exploit the potential of microorganisms to alleviate this problem. The current paper deals with the isolation, characterization, and sugar utilization for better growth of Aspergillus flavus, a marine fungus from the Bay of Bengal. The goal is to assess the bioremediation potential of a variety of synthetic, paper mill, and color photography dyes. A correlation between the amount of sugar used, biomass, and quality of protein produced was observed. This fungus is capable of reducing between 80% and 90% of synthetic dyes and 100% color photography effluents within 3 to 7 days, and 8 days, respectively. Significant effect of carbon sources was observed in the decolorization of the synthetic dye crystal violet, up to 90% in 3 to 7 days, by Aspergillus flavus. The organism showed better growth with fructose as the sole carbon source for the least sugar consumption. Therefore, this fungus can be used as an economical and eco-friendly tool to minimize the pollution by industries to a significant extent. Copyright © 2011 Taylor & Francis Group, LLC.

Kumar K.S.,Gitam Institute of Technology | Sitamahalakshmi T.,Gitam Institute of Technology
International Journal of Applied Engineering Research | Year: 2016

Scientific diagnosis and analysis is the primary concern for the optimal treatment of cancer patients. Better analysis of the data helps the radiologist in providing effective treatment and preventive measures. In this paper, algorithm on support vector machine (SVM), probabilistic neural network (PNN) is presented. The SVM algorithm implements Radial basis kernel function (RBF). SVM constructs an optimal hyper plane for classifying data. PNN maps any input pattern to a number of classifications and guaranteed to convergence to an optimal classifier. The problem addressed here is to what extent the results of SVM with RBF and PNN changes for different datasets and which algorithm has best performance on each dataset. These algorithms are applied on breast cancer datasets. The performance of the algorithm was evaluated with tenfold cross validation. Performance metrics is used to evaluate the performance of the classifier. The experimental result shows that support vector machine have more promising accuracies than Probabilistic neural network. © Research India Publications.

Kumar M.V.,GITAM Institute of Technology | Swaminathan R.,Indian Institute of Technology Kharagpur | Roy R.,GITAM Institute of Technology
2013 IEEE International Conference on Signal Processing, Computing and Control, ISPCC 2013 | Year: 2013

The current scenario of transportation infrastructure demands the need for developing efficient intelligent transportation systems (ITS) because of the increased population, changes in population density, traffic congestion, etc. Recent literature on ITS discuss on the need for green cooperative diversity techniques to improve the energy efficiency of the wireless nodes which are embedded in the transportation infrastructure. In the present work, we propose single-input-multiple-output (SIMO) and spatial modulation (SM) techniques for multiple antenna cooperative ITS in order to improve the energy efficiency of wireless nodes. Moreover, the symbol error probability (SEP) performance and energy efficiency of the proposed techniques are analyzed and compared with the traditional techniques. From the simulation results, it has been inferred that energy efficiency of cooperative ITS can be improved by employing SIMO technique, whereas both energy and spectral efficiency improvement can be obtained by employing SM technique. © 2013 IEEE.

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