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Pathak R.K.,Thadomal Shahani Engineering College
Asian Journal of Microbiology, Biotechnology and Environmental Sciences | Year: 2012

Protease are among the oldest enzyme known to human being with the molecular weight ranging from 18 to 90 Kda. They are the enzymes that catalyzes the splitting of proteins into smaller peptide fractions and amino acids by a process known as proteolysis. These are found in wide diversity of sources like plant, animals and microorganisms. The microorganisms being the major source. Protease catalyzes the total hydrolysis of protein and have broad scope of usage in the industries. The increasing demand of protease in industries led to isolation of microorganisms producing protease. In the present study the microorganisms were isolated from alkaline soil collected from beach. The serial dilution was performed and 5 bacterial strains were isolated. The growth characteristics were studied. The microorganisms producing protease were screened using folin- lowry method and the activity of enzyme was determined. © Global Science Publications.

Sarode T.,Thadomal Shahani Engineering College | Save J.,Narsee Monjee Institute of Management and Higher Studies
International Journal of Electrical and Computer Engineering | Year: 2016

Thousands of images are generated everyday, which implies the need to build an easy, faster, automated classifier to classify and organize these images. Classification means selecting an appropriate class for a given image from a set of pre-defined classes. The main objective of this work is to explore feature vector generation using Walsh transform for classification. In the first method, we applied Walsh transform on the columns of an image to generate feature vectors. In second method, Walsh wavelet matrix is used for feature vector generation. In third method we proposed to apply vector quantization (VQ) on feature vectors generated by earlier methods. It gives better accuracy, fast computation and less storage space as compared with the earlier methods. Nearest neighbor and nearest mean classification algorithms are used to classify input test image. Image database used for the experimentation contains 2000 images. All these methods generate large number of outputs for single test image by considering four similarity measures, six sizes of feature vector, two ways of classification, four VQ techniques, three sizes of codebook, and five combinations of wavelet transform matrix generation. We observed improvement in accuracy from 63.22% to 74% (55% training data) through the series of techniques. Copyright © 2016 Institute of Advanced Engineering and Science. All rights reserved.

Menghani G.,Thadomal Shahani Engineering College
2010 1st International Conference on Parallel, Distributed and Grid Computing, PDGC - 2010 | Year: 2010

Scheduling of tasks in a heterogeneous computing (HC) environment is a critical task. It is also a well-known NP-complete problem, and hence several researchers have presented a number of heuristics for the same. The paper begins with introducing a new heuristic called Sympathy, and later a variant called Segmented Sympathy. A new Genetic Algorithm based heuristic using the Segmented Sympathy heuristic is proposed, which is aimed at improving over the speed and makespan of the implementation by Braun et al. Finally, the results of Simulation reveal that the proposed Genetic Algorithm gave up to 8.34% and on an average 3.42% better makespans. The new heuristic is also about 160% faster with respect to the execution time. © 2010 IEEE.

Antony N.,Thadomal Shahani Engineering College | Deshpande A.,G.H. Raisoni College of Engineering
Advances in Intelligent Systems and Computing | Year: 2016

Due to increasing demand to derive knowledge from data, there is need for efficient data mining algorithms. We have proposed an algorithm to get clusters of arbitrary shapes with the help of Density Based clustering algorithms. Density Based clustering algorithms need Epsilon Value (Eps) and Minimum Points Value (MinPt) to create clusters. Hence in this paper, a method is proposed which accepts the domain knowledge about the dataset as an input and calculation of Eps and MinPt is automated which helps to make the data certain to some extent. Domain knowledge adds some relevance to data, hence this data with knowledge will never be ignored during clustering. In this method, we first create grids for dataset as per user’s requirement then it derives the default Eps and MinPt which are inputs for Density Based Clustering Algorithm for Large Datasets (DBSCALE) algorithm. The results taken after implementation shows the proposed method gives better clusters. © Springer Science+Business Media Singapore 2016.

Pathak R.K.,Thadomal Shahani Engineering College
Asian Journal of Microbiology, Biotechnology and Environmental Sciences | Year: 2011

Immobilization, has emerged since last decade as a very powerful tool to improve almost all enzyme properties like stability, activity, specificity and selectivity, and reduction of inhibition. The immobilization may help to solve some of the problems of enzymes as industrial biocatalysts like enzyme recovery for reuse. In the present study 5 bacterial strains were isolated from alkaline soil collected from a beach. These cells were screened for protease activity. The initial activity of the cell was measured. The strain having high activity was selected for immobilization. The microorganisms were immobilized in various matrices, such as ca-alginate, polyacrylamide, agar-agar, and gelatin. The batch of 36 hrs was performed and the activity of the enzyme was measured for different matrices. The Polyacrylamide showed the maximum enzyme activity. The batches were performed for 9 days to check the potential application and it was observed that the enzyme activity was high for first 6 days and later it started reducing. © Global Science Publications.

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