Pratibha Rohit Dumane
@dbit.in
Assistant Professor
Don Bosco Institute of Technology
EDUCATION
M.E. Electronics
RESEARCH, TEACHING, or OTHER INTERESTS
Engineering, Multidisciplinary, Artificial Intelligence, Signal Processing
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Samuel Jacob, Mandar Warde, and Pratibha Dumane
IEEE
Augmented reality has found itself as an excellent candidate to deliver content for education. There is a definite need for improved visualization when it comes to Engineering education. AR could present itself as a good candidate to do so. This paper presents the use of Augmented Reality for engineering education. The need for visualization finds itself at the core of imparting Engineering education and there are various platforms to do so. We continue the work presented in an earlier publication where we have implemented our smartbooks concept for delivering an engaging AR experience. We have presented the use of AR for delivering content for three fundamental engineering subjects: Engineering mechanics, engineering drawing and electrical engineering. We have also explored a different user interface to improve our AR content delivery. Examples for each are demonstrated and so are their use cases. Measuring the impact of using AR was a particular challenge with variable usage across students. We have defined certain metrics (engagement factor) that help us correlate usage with impact. We have measured the impact of our AR implementation through well designed questionnaires, and used the academic scores of the candidates as an output metric to measure impact. The objective of this research is to present a case for the use of AR in being a front-runner ICT technology for delivering engineering education.
Satishkumar S. Chavan, Carl Fernandes, Pratibha R. Dumane, and Satishkumar L. Varma
Springer Singapore
Bilal H. Hungund, Anas Shaikh, Ghazi Owais, Aabidi Sayyed Ali, and Pratibha Dumane
IEEE
Examination plays a vital role in any education system. It has been observed that most of the activities being managed in any examination cell or by any examination conducting authority are traditionally manually conducted activities. With the availability of computers and internet, it is time that the examination activities are automated. This will not only help in automation of the routinely conducted activities but also help in utilizing the manpower available for enhancing the processes and their skill sets. It will help in efficiently utilizing the resources available for conducting an examination in the organization. The paper focuses on the activities that can be effectively managed in the context of an Examination Cell. An automated system will benefit both students and exam cell coordinators to easily handle the manual processes involved. Automation of the various routine, manual and repetitive activities will help in optimal utilization of the infrastructural resources as well as manpower resources.
Selena Dias, Tanmay Kumbhar, Tyrel Menezes, Caroline Pinto, and Pratibha Dumane
Science Publishing Corporation
Cryptography is a secured transfer of information between users to avoid leakage of information. Research of techniques for cryptography using public key is done to have a need of great computational power besides being highly complex and time consuming for obtaining the key. Neural networks are found to have an edge over these shortcomings for obtaining the keys. In this paper, n – state sequential machine is used to examine Artificial Neural Network as a toll for cryptography. The results thereby obtained demonstrate the use of artificial neural network for cryptography.
Pratibha R. Dumane, Anuja D. Sarate, and Satishkumar S. Chavan
Springer Singapore
G. Sawant, A. Singh, K. Kadam, R. Mazarello, and P. Dumane
ACM
Today, perhaps the biggest area of concern in the transmission of signals is bandwidth and its availability. Speech synthesis means the production of a speech signal by using stored speech parameters. These parameters are generated by a process known as speech analysis. A popular technique used for speech analysis and synthesis is linear predictive coding (LPC). In this technique, the previous n samples of a speech signal are used to predict the next sample of the signal. The prediction error, which is the error between such a reconstructed sample and the actual sample, is minimised. It is possible to synthesize a signal with a reduced bit rate and reasonably good quality. Such signals can be extremely useful for low bandwidth and therefore, low bit rate applications. In this paper, we examine the LPC technique in detail and propose a system for speech synthesis based on LPC. The aim is to synthesize speech of acceptable quality, with a sizeable reduction in bit rate.