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;

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MIT World Peace University

Engineering and Technology

Fractal analysis can be used for the detection of masses exhibiting circular and lobulated shape margins in screening mammograms. Currently, mammograms have been one of the most versatile methods for the early detection of breast cancer. However, one of the characteristic lesions of breast cancer appears as dense regions of breast sizes and properties known as breast masses. To classify these breast masses into benign and malignant, fractal analysis can be used. The most versatile method for fractal analysis is based on Power Spectral Analysis (PSA) using the signatures of contours. The experimental results using fractal analysis provides an accuracy of 82% for circular and lobulated margin breast masses. © 2013 IEEE.

World University root node

School of Electronics & Communication Engineering

Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2013

Classification of circular and lobulated masses in mammograms using fractal analysis

Images are often corrupted with noise during acquisition, transmission and retrieval from storage media. So the need for efficient image de-noising methods has grown with the massive and easy production of digital images and movies. Furthermore, de-noising is often necessary as a pre-processing step in image compression, segmentation, recognition etc. Therefore, de-noising has been an important and widely studied problem in image processing and computer vision. Basically, the image de-noising methods are divided into two types: local and non-local. The methods that only exploit the spatial redundancy in local neighborhoods are referred as Local methods. The methods that estimate pixel intensity based on information from the whole image and thereby exploiting the presence of similar patterns and features in an image are referred as Non-Local. A non local method called as Non-Local Means[3] estimates a noise-free pixel intensity as a weighted average of all pixel intensities in the image, and the weights are proportional to the similarity between the local neighbourhood of the pixel being processed and local neighbourhoods of surrounding pixels. The method is quite spontaneous and powerful that results in comparable PSNR and visual quality to other non-local methods. © 2013 IEEE.

International Conference on Signal Processing, Image Processing and Pattern Recognition 2013, ICSIPR 2013

Image de-noising by non-local means algorithm

With the increase of ubiquitous data all over the internet, intelligent classroom systems that integrate traditional learning techniques with modern e-learning tools have become quite popular and necessary today. Although a substantial amount of work has been done in the field of e-learning, specifically in automation of objective question and answer evaluation, personalized learning, adaptive evaluation systems, the field of qualitative analysis of a student's subjective paragraph answers remains unexplored to a large extent. The traditional board, chalk, talk based classroom scenario involves a teacher setting question papers based on the concepts taught, checks the answers written by students manually and thus evaluates the students' performance. However, setting question papers remains a time consuming process with the teacher having to bother about question quality, level of difficulty and redundancy. In addition the process of manually correcting students' answers is a cumbersome and tedious task. In this paper, we put forth the design, analysis and implementation details along with some preliminary results to build a system that integrates all the above mentioned tasks with minimal teacher involvement that not only automates the traditional classroom scenario but also overcomes its inherent shortcomings and fallacies. © 2013 IEEE.

School of Computer Engineering & Technology

2013 6th International Conference on Emerging Trends in Engineering and Technology

Intelligent Classroom System for Qualitative Analysis of Students' Conceptual Understanding

The article summarizes and compares the materials used for orthopedic joint orthoplasty. The issues related to manufacturing the implants as indigenous product are discussed. The article gives broad view of utility of materials that are used by Indian manufacturing companies for biomedical application The article discusses about the trends in Indian manufacturing scenario, and tries to give broad idea for possible improvements to be undertaken while product design of implant ,with reference to increasing Indian market for implant manufacturers. The attempt is made to analyze the structural response of Zirconium and tantalum as implant for fixation. The Finite Element analysis gives preliminary bone implant response under flexural loads.

School of Civil Engineering

Trends in Biomaterials and Artificial Organs

Comparative study of initial structural stability of oxinium hip joint fixation with steel hip joint fixation

Fault diagnosis is a central aspect of network fault management. Since faults are unavoidable in communication systems, their quick detection and isolation is essential for the robustness, reliability, and accessibility of a system. Probing technique for fault localization involves placement of probe stations (Probe stations are specially instrumented nodes from where probes can be sent to monitor the network) which affects the diagnosis capability of the probes sent by the probe stations. Probe station locations affect probing efficiency, monitoring capability, and deployment cost. At the same time, probe station selection affects the selection of probe set for fault localization. We are presenting a novel approach for minimal probe station selection with an objective to reduce probe set size that will be used for fault localization. The probe station selected through this approach results into reduced deployment cost as well as it helps in producing smaller probe set for fault localization reducing overall operation cost. We provide experimental evaluation of the proposed algorithms through simulation results. © 2013 IEEE.

Proceedings of the 2013 International Conference on Information Systems and Computer Networks, ISCON 2013

Probe station placement algorithm for probe set reduction in network fault localization

International Conference on recent trends in engineering \& Technology -2013 {\ldots}

Experimental Study of Ferrocement Panels

Performance Analysis of Stereo Matching Using Segmentation Based Disparity Map

Detection of gradual transition and the elimination of disturbances caused by illumination change or fast object and camera motion are the major challenges to the current shot boundary detection techniques. These disturbances are often mistaken as shot boundaries. Therefore, it is a challenging task to develop a method that is not only insensitive to various disturbances but also sensitive enough to capture a shot change. To address these challenges, we propose an algorithm for shot boundary detection in the presence of illumination change, fast object motion, and fast camera motion. This is important for accurate and robust detection of shot boundaries and in turn critical for high-level content-based analysis of video. First, the propose algorithm extracts structure features from each video frame by using dual-tree complex wavelet transform. Then, spatial domain structure similarity is computed between adjacent frames. The declaration of shot boundaries are decided based on carefully chosen thresholds. Experimental study is performed on a number of videos that include significant illumination change and fast motion of camera and objects. The performance comparison of the proposed algorithm with other existing techniques validates its effectiveness in terms of better Recall, Precision, and F1 score. © 2011 Springer-Verlag London Limited.

Signal, Image and Video Processing

Shot boundary detection in the presence of illumination and motion

Now a days,A biometrics techniques such as ﬁngerprints,palm prints,faces and irises recognition have been widely used in many different applications such as door access control system ,a secure personal authentication for computers,online banking, automatic teller machines for transaction and border-crossing controls system. but The research on ﬁnger vein recognition or authentication technology has become a new hot spot due to its superior security features and user acceptance in recent years.As Finger vein recognition uses the unique patterns of ﬁnger veins images to identify individuals at a high level of accuracy and security.The major concern in a Biometric Identiﬁcation System is its accuracy. In spite of the improvements in image acquisition and image processing techniques, the amount of research still being carried out in person veriﬁcation and identiﬁcation show that a recognition system which gives 0 percentage FAR (False Acceptance Rate) and FRR (False Rejection Rate) is still not a reality.In this work, we propose to formulate the framework for the ﬁnger vein feature extraction using multi-orientation Gabor ﬁlters. The morphological operations are further employed to enhance the extracted vein structures. The proposed method extracts the ﬁnger-vein pattern from the unclear image by using Gabor ﬁlter.Hence This paper will gives a new approach or technique to improve the performance of ﬁnger vein identiﬁcation systems which is presented in the literature.