Anwarullah M.,AmbaGarden |
Vasudeva Rao V.,SNIST |
Sharma K.V.,University of Malaysia
Heat and Mass Transfer/Waerme- und Stoffuebertragung | Year: 2012
An experimental investigation is carried out to study the enhancement of heat transfer from surface of the electronic components by impingement of a circular air jet. Local and stagnation Nusselt number on the impinged surface of the electronic components are presented for different nozzle configurations. Reynolds number, based on nozzle diameter (d) is varied between 5,500 and 28,500 and nozzle-to-electronic component spacing from 2 to 10 nozzle diameters. The measured data were correlated into a simple equation and compared to the predictions of several other correlations proposed by other researchers. The heat transfer mechanisms involved in the enhanced performance are discussed. The study provides a lot of useful information for the application of impinging jet heat transfer in electronic industry. © Springer-Verlag 2012.
Reddy G.S.,VNRVJIET |
Rajinikanth T.V.,SNIST |
Souvenir of the 2014 IEEE International Advance Computing Conference, IACC 2014 | Year: 2014
Text clustering is an unsupervised process forming its basis solely on finding the similarity relationship between documents with the output as a set of clusters . In this research, a commonality measure is defined to find commonality between two text files which is used as a similarity measure. The main idea is to apply any existing frequent item finding algorithm such as apriori or fp-tree to the initial set of text files to reduce the dimension of the input text files. A document feature vector is formed for all the documents. Then a vector is formed for all the static text input files. The algorithm outputs a set of clusters from the initial input of text files considered. © 2014 IEEE.
Madhu G.,VNRVJIET |
Rajinikanth T.V.,SNIST |
Govardhan A.,University of Hyderabad
Procedia Computer Science | Year: 2014
In real-time data mining applications discrete values play vital role in knowledge representation as they are easy to handle and very close to knowledge level representation than continuous attributes. Discretization is a major step in data mining process where continuous attributes are transformed into discrete values. However, most of the classifications algorithms are require discrete values as the input. Even though some data mining algorithms directly contract with continuous attributes, the learning process yields low quality results. In this paper, we introduce a new discretization method based on standard deviation technique called 'z-score' for continuous attributes on biomedical datasets. We compare performance of the proposed algorithm with the state-of-the-art discretization techniques. The experiment results show the efficiency in terms of accuracy and also minimize the classifier confusion for decision making process. © 2014 Published by Elsevier B.V.
Mukundha C.,SNIST |
Prabha I.,IARE |
Journal of Theoretical and Applied Information Technology | Year: 2016
Now days we have observed that the fast change in the cloud network by the Software Defined Networking (SDN) paradigm that differentiate the control plane from the data plane to give the flexibility for programmability and centralized control of the cloud networks, SDN networks not only provide simplification of cloud network management it also provides more security with SDN by implementing firewalls with in the SDNs. The demand of cloud increased day by day with the increasing of usage of cloud. The SDN is provided with Open Flow network, cloud network states are dynamically updated and configurations are frequently changed. Open Flow accepts various Field actions that can dynamically change the packet headers. A firewall embedded in SDN can immediately enforce updated rules in the firewall policy to check security violations. Cloud computing allows all categories of users to use applications without installation and access their personal files at any system with internet access. Here we present that the way forward is to integrate SDN and fully utilize its feature to solve the security problems in cloud networks. We focus on the security aspect and investigate how to enhance the security with SDN firewalls for the cloud networks. © 2005-2016 JATIT & LLS. All rights reserved.
Umakanta Sastry V.,Sreenidhi Institute of Science and Technology |
Ravi Shankar N.,SNIST |
Durga Bhavani S.,Jawaharlal Nehru Technological University Anantapur
International Journal of Network Security | Year: 2010
This paper deals with a modification of the Hill cipher. In this, we have introduced interweaving in each step of the iteration. The interweaving of the resulting plaintext, at each stage of the iteration, and the multiplication with the key matrix leads to confusion and diffusion. From the cryptanalysis performed in this investigation, we have found that the cipher is a strong one.
Kranthi Kumar K.,SNIST |
Gopal T.V.,JNTUH College of Engineering
2014 International Conference on Signal Propagation and Computer Technology, ICSPCT 2014 | Year: 2014
This paper, proposes a Non-Continuation based Self Re-Weighting approach for CBIR systems, to reduce semantic gap which is a bottle neck of CBIR. The assumption for previous FRW approaches are that the length of feature vectors for images are fixed and uses only the information from the set of images sent back in the early query result for feature re-weighting. The proposed system automatically recalculates the weight of features for an image, which estimate the user perception from the user feedback on retrieved set based on obtained interval. In this approach we examined systematically with other feature re-weighting methods and proved that our approach outperforms other approaches. Which we experimented with COREL database with 25 different categories and each category contains with 100 numbers of relevant images. The experimental results demonstrated the advantage of our approach in terms of precision and recall. © 2014 IEEE.
Kumar K. K.,SNIST |
Gopal T.V.,JNTUH College of Engineering
Proceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014 | Year: 2014
In this paper, we propose an approach using multilevel and multiple approaches for Feature Reweighting for CBIR system to reduce semantic gap using Relevance feedback. The first step of this approach does analysis on the positive and negative images, Second step calculates normalized feature component sets of images, Third step calculates overall distances between given query image and database images, and the next step calculates Relevance score along with confidence of the image, it is used for Feature Reweighting. All the above methods are performed individually in the previous systems, where as in our propose system we perform all these together. The assumption for the previous relevance feedback systems are that, all the above methods are performed against to the user given feedback. This increases the number of iterations for the retrieval systems. The propose system can do analysis of images, overall distance calculation, automatically calculates the weight of features for an image based on the confidence and score of the relevance before user feedback. And these results are carried forward to the next iteration for further calculations after the user feedback. © 2014 IEEE.
Jyothi B.V.,CBIT |
ISMS 2010 - UKSim/AMSS 1st International Conference on Intelligent Systems, Modelling and Simulation | Year: 2010
In this paper, we describe two new approaches to content-based image retrieval (CBIR) based on preference information provided by the user interacting with an image search system. First, we present the existing methods of image retrieval with relevance feedback, which serve then as a reference for the new approaches. The first extension of the distance function-based CBIR approach makes it possible to apply this approach to complex objects .Next we discuss the second approach for image retrieval. That new algorithm is based on an approximation of user preferences by a neural network. Finally we discuss the advantages and disadvantages and further improvements and future scope in this particular area. © 2010 IEEE.
Ilamathi R.,SNIST |
Nirmala G.S.,Vellore Institute of Technology |
Muruganandam L.,Vellore Institute of Technology
International Journal of ChemTech Research | Year: 2014
Our work aims to throw light on biosorption of heavy metals in a Liquid Solid Fluidized Bed as a successful alternative for heavy metal removal. The design and fabrication of LSFB has been discussed. Batch studies and fluidized bed studies were carried out to study the biosorption behavior for chromium, nickel, copper and cadmium by alginate beads containing a mixed consortium of Yeast, Pseudomonas aeruginosa, Bacillus subtilis and Escherichia coli. Fluidized bed studies were carried out in 1m length and 5cm diameter column, with an optimized adsorbent dosage of 1g/L, a flowrate of 132 LPH, a bed height of length of the reactor. Efficiency of biosorption for copper, cadmium, chromium and nickel in LSFB was found to be 84.62%, 67.17%, 49.25% and 61.02%. The efficiencies were found to depend on the pH, temperature, initial metal concentration, and the residence time of the beads in the fluidized beds. Desorption of the exhausted beads was successful, however, with a reduced biosorption capacity. Pretreatment of the culture was found to increase the capacity of metal uptake.
Bhutada S.,SNIST |
Balaram V.V.S.S.S.,SNIST |
International Journal of Applied Engineering Research | Year: 2016
Dynamic topic extraction is a method helpful to understand the hidden knowledge from the textual database in order to systematize and supervise the growing text. The important challenge in this process is to insert new documents into appropriate categories. On the other hand misplacing of documents propagates the wrong information to the future topic hierarchy, thereby declining the quality of the knowledge extraction process. So, the effective extraction of topics and insertion of dynamic documents to a corresponding category is very important. Accordingly, a new method called, Dynamic Semantic Latent Dirichlet Allocation (DSLDA) is proposed in this paper by extending SLDA by handling the dynamic updates. Dynamic handling of documents requires much dimensional space to extract the feature words for dynamic process. In order to alleviate this problem, a method is developed using holoentropy which enables feature evaluation function to select the most important features from the document. The advantage of holoentropy is that, it can measure the global disorder of a data set by computing the total correlation to ensure the attribute relationship. These two proposals i.e. DSLDA and holoentropy are to be effectively integrated in the proposed system to dynamically handle the input documents and thereby, updating the topics using membership and representative information. The experimentation is performed using two different textual databases and the performance of the proposed DSLDA is validated using F-measure, Entropy, Rand and Jaccord Coefficient. © Research India Publications.