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Vijaya Lakshmi T.R.,MGIT | Sastry P.N.,CBIT | Rajinikanth T.V.,SNIST
Advances in Intelligent Systems and Computing | Year: 2017

Recognizing Indian handwritten text is relatively complex compared to recognized foreign language such as English. In this work optimization techniques are presented to recognize Telugu handwritten characters. By extracting cell-based directional features from these characters, optimum features are selected by implementing optimization algorithms such as differential evolution and particle swarm optimization. An improvement of 3.5 % recognition accuracy is achieved using differential evolution algorithm. The optimization techniques are compared with the existing hybrid approach of Telugu script. © Springer Nature Singapore Pte Ltd. 2017.

Kumar Y.J.N.,Gokaraju Rangaraju Institute of Engineering and Technology | Kanth T.V.R.,SNIST
International Journal of Electrical and Computer Engineering | Year: 2017

The rainfall conditions across wide geographical location and varied topographic conditions of India throw challenge to researchers and scientists in predicting rainfall effectively. India is Agriculture based country and it mainly depends on rainfall. Seasons in India are divided into four, which is winter in January and February, summer is from March to May, monsoon is from June to September and post monsoon is from October to December. India is Agriculture based country and it mainly depends on rainfall. It is very difficult to develop suitable rainfall patterns from the highly volatile weather conditions. In this Paper, it is proposed that Map based Spatial Analysis of rainfall data of Andhra Pradesh and Telangana states is made using R software apart from Hybrid Machine learning techniques. A Study will be made on rainfall patterns based on spatial locations. The Visual analytics were also made for effective study using statistical methods and Data Mining Techniques. This paper also introduced Spatial mining for effective retrieval of Remote sensed Data to deal with retrieval of information from the database and presents them in the form of map using R software. Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved.

Sujatha C.N.,SNIST
Smart Innovation, Systems and Technologies | Year: 2018

In this paper, singular value decomposition based color image authentication scheme is proposed. Singular values of the host image are modified with that of a secret image. Modifications are optimized to obtain the maximum robustness without losing visual quality. Experiments are done using color images as host and watermark. Simulation results show that the present algorithm is highly resistant to various image processing attacks with significant improvement in perceptibility. The performance is measured objectively in terms of Mean Square Error, Peak Signal to Noise Ratio and Correlation Factor. © 2018, Springer International Publishing AG.

Kumar N.V.,SNIST | Sreelatha K.,SNIST | Kumar C.S.,SNIST
India International Conference on Information Processing, IICIP 2016 - Proceedings | Year: 2017

Watermark is pattern of bits inserted into a digital image, that identifies the file's copyright information (author rights etc). The name watermarking is derived from the faintly visible marks imprinted on organizational stationery. A robust and novel strategic approach for insertion-extraction of a digital watermark in color images is presented. Watermarks are generally intended to be visible but are invisible. Invisible insertion of the watermark is performed in the most significant regions of the host image such that tampering of that portion to remove or to destroy will degrade the esthetic quality and value of the image. One feature of the algorithm is that these user defined characters are used as a region of interest for the water marking process and eliminates the changes of watermark removal. Specifically we are interested to develop dithering techniques intended to embed color watermarking into color image. Here we have proposed and implemented dithering techniques in various color spaces like RGB and HSV. An attempt is made to develop full color water marking scheme using those techniques. © 2016 IEEE.

Kiranmayee B.V.,VNRVJIET | Rajinikanth T.V.,SNIST | Nagini S.,VNRVJIET
Proceedings of the 2016 2nd International Conference on Contemporary Computing and Informatics, IC3I 2016 | Year: 2017

Data mining techniques are used for mining useful trends or patterns from textual and image data sets. Medical data mining is very important field as it has significant utility in healthcare domain in the real world. The mining techniques can help the healthcare industry to improve quality of services and grow faster with state-of-the-art technologies. Technology usage is not limited to decision making in enterprises, but spread to every walk of life in all fields. This paper is focused on brain tumour detection which is an essential decision making feature and is a part of healthcare application. This paper proposed a methodology for brain tumour detection which has both training and testing phases. A prototype application has been built to demonstrate the usefulness of the proposed algorithm. The experimental results reveal that the application can be integrated with decision support systems in healthcare domain for improving quality of services. © 2016 IEEE.

Nagini S.,VNRVJIET | Kanth T.V.R.,SNIST | Kiranmayee B.V.,VNRVJIET
Proceedings of the 2016 2nd International Conference on Contemporary Computing and Informatics, IC3I 2016 | Year: 2017

India's economy primarily depends on agriculture yield growth and their allied agro industry products. The agriculture yield prediction is the toughest task for agricultural departments across the globe. The agriculture yield depends on various factors. Particularly countries like India, majority of agriculture growth depends on rain water, which is highly unpredictable. Agriculture growth depends on different parameters, namely Water, Nitrogen, Weather, Soil characteristics, Crop rotation, Soil moisture, Surface temperature and Rain water etc. In our paper, lot of Explorative Data Analysis is done and various predictive models were designed. Further various regression models like Linear, Multiple Linear, Non-linear models are tested for the effective prediction or the forecast of the agriculture yield for various crops in Andhra Pradesh and Telangana states. © 2016 IEEE.

Reddy G.S.,VNRVJIET | Rajinikanth T.V.,SNIST | Rao A.A.,JNTUA
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 [14]. 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.

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.

Jyothi B.V.,CBIT | Eswaran K.,SNIST
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.

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