Thadomal Shahani Engineering College

Mumbai, India

Thadomal Shahani Engineering College

Mumbai, India
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Punjabi R.,Thadomal Shahani Engineering College | Bajaj R.,Thadomal Shahani Engineering College
2016 IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2016 - Proceedings | Year: 2016

The 'DevOps' phenomenon that advocates a collaborative and unified method for delivering software, has been gaining tremendous attention from various sectors of the IT industry with organizations adopting this movement exhibiting significant growth in performance. It can be challenging for an organization to commence their DevOps journey owing to the abundant and diverse resources available. There is a need to have an all-inclusive picture of DevOps and how its related concepts can be leveraged to improve delivery of software applications to end-users while enhancing quality and reducing lead time. This paper strives to bring insight into the practices associated with DevOps. An end-To-end solution is provided through an integrated toolchain and a customizable workflow. The role of Docker containers is considered in the context of extending infrastructure provisioning capability of the workflow. In a bid to accelerate delivery and improve testability of applications, a framework to automate Model-View-Controller architectures has been proposed. Through these processes, the cyclical journey of an application is traced from 'User Stories' to a running state - 'User Reality' on the cloud. © 2016 IEEE.

Shaikh A.,Thadomal Shahani Engineering College | Gadge J.,Thadomal Shahani Engineering College
Proceedings - 2nd International Conference on Computing, Communication, Control and Automation, ICCUBEA 2016 | Year: 2016

The data security in cloud computing is formidable task. The privacy of shared data and its integrity in untrusted public environment is highly subject to skepticism. Many approaches have been designed to audit cloud data. However issues with existing mechanism are weak authorization and access data control which is also a threat to identity privacy in dynamic group environment. In this paper a new framework is proposed for securing privacy and identity of owner and its data. This framework is referred as Privacy Preserving Authentication Privilege Access Data Integrity (PP-APADI). It leverages the enhance identity management using two factor authorization and enforced fine grained privilege access control in shared pool of resources . It uses Cipher-Text Attribute Based Encryption (CP-ABE) for anonymous data access control. Besides random dynamic group key signature and efficient revocation handling mechanism is used to dual the security layer. This combined approach helps public auditing in cloud data without exploiting privacy of owner to public verifier. It also supports file sharing, recovery and replacement in a multi-Tenant dynamic group environment.

Ganwani J.,Thadomal Shahani Engineering College | Gadge J.,Thadomal Shahani Engineering College
Proceedings - 2nd International Conference on Computing, Communication, Control and Automation, ICCUBEA 2016 | Year: 2016

Research papers are often referred by researchers. But finding the desired or relevant research paper quickly and accurately is very difficult. As there are lot of research papers in given dataset and keeps enormously increasing. There is a need to avail automated processing approach for tackling such a huge volume of dataset to retrieve relevant papers accurately. This paper proposes a framework which works in two phases. In first phase, papers are stored in a dataset. Initially the Information Gain is calculated for finding features of each document in dataset. These features of document are used for classification. For classification of document, Naïve Bayes approach is used. In second phase, relevant documents are retrieved based on search query. In this features of search query are extracted using Information Gain. The extracted features are used for retrieving relevant research papers. The extracted features of query and features of document stored in a dataset are compared using cosine similarity approach.

Kolkur S.,Thadomal Shahani Engineering College | Kalbande D.R.,Sardar Patel Institute of Technology
Proceedings of 2016 International Conference on ICT in Business, Industry, and Government, ICTBIG 2016 | Year: 2017

Skin diseases are most common form of infections occurring in people of all ages. As the costs of dermatologists to monitor every patient is very high, there is a need for a computerized system to evaluate patient's risk of skin disease using images of their skin lesions. Many researchers have used different preprocessing, segmentation and classification techniques to determine whether a skin image suffers from diseases or not. Feature extraction is very important for predictive modeling applications. Feature extraction in image processing is a method of capturing visual content of images for indexing and retrieval. Primitive image features can be either general features, such as extraction of color, texture and shape or domain specific features. Texture based features are widely used in image analysis for medical diagnosis. This paper presents a comprehensive survey of texture based feature extraction for detection of skin diseases and proposes a system based on the findings. © 2016 IEEE.

Kolkur S.,Thadomal Shahani Engineering College
ACM International Conference Proceeding Series | Year: 2016

ESD is an acronym for Erythemato-Squamous Diseases, which is a set of six skin diseases [6]. The Erythemato-Squamous Diseases (ESDs) require huge computational efforts to predict the diseases because all the six diseases studied in this group have more than 90% common features. The main focus of this paper is to study the use of machine learning algorithms in R software for prediction of ESD Diseases. In this paper, different algorithms are studied and implemented in R. Accuracy of these algorithms is compared. © 2016 ACM.

Dhannawat R.,Usha Mittal Institute of Technology | Patankar A.B.,Thadomal Shahani Engineering College
Procedia Computer Science | Year: 2016

Image denoising without any idea about kind of noise is very cumbersome as compared to known noise. This paper proposed a novel technique for blind image denoising using SVD and local pixel grouping. The technique is checked against salt & pepper noise and Gaussian noise for gray as well as color images and compared with state of art algorithm LPGPCA. It is found that the proposed technique gives better results when compared using objective criteria. © 2016 The Authors.

Gupta J.,Thadomal Shahani Engineering College | Gadge J.,Thadomal Shahani Engineering College
2014 International Conference on Circuits, Systems, Communication and Information Technology Applications, CSCITA 2014 | Year: 2014

Recommendation systems attempt to predict the preference or rating that a user would give to an item. Knowledge discovery techniques can be applied to the problem of making personalized recommendations about items or information during a user's visit to a website. Collaborative Filtering algorithms give recommendations to a user based on the ratings of other users in the system. Traditional collaborative filtering algorithms face issues such as scalability, sparsity and cold start. In the proposed framework, prediction using item based collaborative filtering is combined with prediction using demographics based user clusters in an adaptive weighted scheme. The proposed solution will be scalable while addressing user cold start. © 2014 IEEE.

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.

Khan S.,Thadomal Shahani Engineering College | Kulkarni A.,Thadomal Shahani Engineering College
Proceedings of the 2010 International Conference on Signal and Image Processing, ICSIP 2010 | Year: 2010

There is various forgeries possible on digital images such as image tampering, copy-move forgery and image compositing. Out of these, copy-move forgery is a type of image forgery, in which a part of original digital image is copied and pasted to another part in the same original image to make it, forged one. This paper describes blind image forensics approach for detecting copy-move forgery. In this technique forged image is reduced in dimension using DWT (Discrete Wavelet Transform) [1]. Then the compressed image is divided into overlapping blocks of fixed size. These blocks are sorted using lexicographic sorting and duplicated blocks are identified using Phase Correlation as similarity criterion. Detected forgery is displayed with the help of duplication map that gives count of pixels forged. This approach drastically reduces the time needed for the detection process and improves the accuracy of detection. ©2010 IEEE.

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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