MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

&nbsp;

MIT World Peace University

School of Computer Engineering & Technology

Developments in technology and the Internet have led to an increase in number of digital images and videos. Thousands of images are added to WWW every day. Content based Image Retrieval (CBIR) system typically consists of a query example image, given by the user as an input, from which low-level image features are extracted. These low level image features are used to find images in the database which are most similar to the query image and ranked according their similarity. This chapter evaluates various CBIR techniques based on fuzzy logic and neural networks and proposes a novel fuzzy approach to classify the colour images based on their content, to pose a query in terms of natural language and fuse the queries based on neural networks for fast and efficient retrieval. A number of experiments were conducted for classification, and retrieval of images on sets of images and promising results were obtained. © 2012, IGI Global.

Engineering and Technology

Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques

Machine learning approach for content based image retrieval

For the latest development in the direction of embedded system and wireless network, this project work describes wireless image transmission based on the embedded system. The Project Work Includes Following Features of Image Transmission using WIFI from S3C2440A to PC, S3C2440A is the h/w, with QTOPIA OS, PC with LINUX(Ubuntu) and with Socket code being in C/C++ language. Here S3C2440A will be working as Server and PC with Linux Platform(UBUNTU) will be working as Client. Experimental results show the throughput, transmission time and delay evaluation for various image file types along with speed gain using image compression. © 2012 IEEE.

World University root node

Proceedings of the 2012 12th International Conference on Hybrid Intelligent Systems, HIS 2012

Performance evaluation of wireless image transmission: An approach using embedded system

International Journal of Applied Information Systems

Generating UML diagrams from natural language specifications

As more and more web services that provide the same functionality are developed, it is a major issue to consider not only the functional requirements but also the non functional requirement (NFR) during web service discovery process. The NFR define the Quality of Service (QoS) of the system. Much work has been done on web service discovery process that considers the functional requirements as selection criteria. However not many service discovery strategies consider the QoS properties. On the basis of our study and survey, we advocate that the best performance is achieved by use of both functional and NFR properties. We believe that the user NFR should be expressed explicitly to aid in selecting a web service that best fulfils them. To support this claim we present a detailed survey of web service discovery systems that makes use of QoS factors. Paper also highlights the importance of ontology to represent the non functional requirements in web service discovery. We emphasize how Ontology if built and refined by domain experts can be used for web service discovery process with the purpose of reuse and improved design. © 2012 IEEE.

Proceedings of the 2012 World Congress on Information and Communication Technologies, WICT 2012

Survey of QoS based web service discovery

International Journal of Computer Applications

Mining Association Rules Using Hash Table

Fault Management of Computer Networks based on Probe Station and Probe Set Selection Algorithms

Document clustering is the task of grouping a set of documents into clusters so that the documents in the same cluster are similar to each other than to those in other clusters. One of the applications of document clustering is in web search engine retrieval system to help the users find relevant information quicker, and allow them to focus their search in the appropriate direction. K-means is a commonly used algorithm for document clustering, but it has some disadvantages. The main limitations of K-means are: 1) The number of clusters K has to be given as input and 2) Based on the initializations it converges to different local minima. 3) It is slow and cannot be used for large number of data points.4) It cannot handle empty clusters. In this paper, we have developed a novel algorithm to eliminate all these basic drawbacks of K-means.

IET Conference Publications

Document clustering algorithm using modified K-means

Developments in the technology and the Internet have led to increase in number of digital images and videos. Thousands of images are added to WWW every day. To retrieve the specific images efficiently from database or from Internet is becoming a challenge now a day. As a result, the necessity of retrieving images has emerged to be important to various professional areas. This paper proposes a novel fuzzy approach to classify the colour images based on their content, to pose a query in terms of natural language and fuse the queries based on neural networks for fast and efficient retrieval. Number of experiments was conducted for classification and retrieval of images on sets of images and promising results were obtained. The results were analysed and compared with other similar image retrieval system. © 2012 IEEE.

Proceedings of the International Joint Conference on Neural Networks

Hybrid technique for colour image classification and efficient retrieval based on fuzzy logic and neural networks

Recently, content based image retrieval (CBIR) has gained active research focus due to wide applications such as crime prevention, medicine, historical research and digital libraries. With digital explosion, image collections in databases in distributed locations over the Internet pose a challenge to retrieve images that are relevant to user queries efficiently and accurately. It becomes increasingly important to develop new CBIR techniques that are effective and scalable for real-time processing of very large image collections. To address this, the paper proposes a novel MapReduce neural network framework for CBIR from large data collection in a cloud environment. We adopt natural language queries that use a fuzzy approach to classify the colour images based on their content and apply Map and Reduce functions that can operate in cloud clusters for arriving at accurate results in real-time. Preliminary experimental results for classifying and retrieving images from large data sets were quite convincing to carry out further experimental evaluations. © 2012 IEEE.

MapReduce neural network framework for efficient content based image retrieval from large datasets in the cloud

This paper focused on peak to average power ratio (PAPR) reduction scheme for OFDM system. OFDM has several properties which make it an attractive modulation scheme for high speed transmission. the main draw back of OFDM is high PAPR. The high PAPR causes the interference and degraded the performance of the system while OFDM signal pass through the amplifier. Here a simple scheme clip and filter is used to reduce the PAPR of OFDM system. Simulation results are show that the improvement in performance of OFDM system by reducing the PAPR using clip and filter scheme. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of C3IT