Dr Tapan Kumar Jain
@iiitn.ac.in
Chair ECE Department
Indian Institute of Information Technology Nagpur
RESEARCH INTERESTS
Wireless
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Dhanhanjay Pachori, Rajesh Kumar Tripathy, and Tapan Kumar Jain
Institute of Electrical and Electronics Engineers (IEEE)
Atrial fibrillation (AF) is one of the most common arrhythmia. AF can be a reason for strokes and damage to heart activities. The electrocardiogram (ECG) is commonly used for AF detection. It should be noted that the burst AF does not show any symptoms and is difficult to detect using ECG. As an alternative to ECG, photoplethysmography (PPG) is used for AF diagnosis, which is easy to record and suitable for long-term monitoring. This letter proposes a new classification framework for automated AF detection based on variational mode decomposition (VMD). The proposed framework has been studied on a publicly available dataset. The proposed VMD-based classification framework outperformed other state-of-the-art methods used for AF detection and achieved the highest accuracy of 99.08% using ten-fold cross-validation. The results of the proposed methodology have shown significant improvement, and the developed sensor-based system has proved suitability to real-time clinical practices.
Shailendra W. Shende, Jitendra V. Tembhurne, and Tapan Kumar Jain
Springer International Publishing
Tausif Diwan, Jitendra V. Tembhurne, Tapan Kumar Jain, and Pooja Jain
Springer International Publishing
Abhishek Pathak, Jitendra V. Tembhurne, C. Kalaiarasan, and Tapan Jain
Springer International Publishing
Jitendra V. Tembhurne, Tausif Diwan, and Tapan Kumar Jain
Springer International Publishing
Rakhi Wajgi, Jitendra V. Tembhurne, Dipak Wajgi, and Tapan Jain
Springer International Publishing
Dipak Wajgi, Jitendra V. Tembhurne, Rakhi Wajgi, and Tapan Jain
Springer International Publishing
Vaijayanti Panse and Tapan Kumar Jain
Institute of Electrical and Electronics Engineers (IEEE)
Vaijayanti Panse, Prabhat Kumar Sharma, Tapan Kumar Jain, and Ashwin Kothari
Elsevier BV
Sambhav Kumar Jain, Tapan K. Jain, Saumya Shanker, and Srikant Srivastava
Defence Scientific Information and Documentation Centre
An Inertial Navigation System (INS) independently measures the Position, Velocity, and Attitude (PVA) of thevehicle to navigate it towards the target. Since INS is a dead-reckoning system, it requires accurate initialization toprovide the navigation (PVA) solution. In the case of an air-launched tactical missile, the aircraft navigation system(Master INS) information is used to initialize accurately the missile INS (Slave INS). Rapid transfer alignment isneeded in today’s combat operation to converge slave INS initialization in the shortest possible time using aircraftnavigation information. The transfer alignment consists of first initializing the missile INS and establishing anavigation solution (PVA) using the missile IMU rates and accelerations, then a Kalman filter is used to, estimatethe errors between the Slave INS and Master INS. The proposed method’s simulation results show that a tacticalmissile INS can be aligned to an acceptable accuracy in a very short time based on the aircraft’s attitude information and with natural maneuvers experienced during aircraft take-off.
Mayur Selukar, Pooja Jain, and Tapan Kumar
Elsevier BV
Mayur Selukar, Pooja Jain, and Tapan Kumar
Springer Science and Business Media LLC
Vaijayanti Panse, Tapan Kumar Jain, Prabhat Kumar Sharma, and Ashwin Kothari
Elsevier BV
Vaijayanti Panse, Tapan Kumar Jain, and Ashwin Kothari
IEEE
The radio frequency energy harvesting (RF-EH) technique provides a potential way to power the battery-constrained wireless devices in the future generation wireless networks. In this paper, we investigate a dual-hop decode-and-forward (DF) cooperative network with RF-EH using non-linear hybrid power-time-splitting (PTS) based model. In the proposed system, the best relay is obtained by considering the instantaneous signal-to-noise ratios (SNRs) of source (S) to relay (R) links using three selection schemes, namely, absolute SNR-based selection, normalized SNR-based selection and random selection. Considering the DF protocol at R, we evaluate the outage and throughput performances of the system over independent and identically distributed Rayleigh fading channels. The derived results are validated through Monte-Carlo simulations.
Rahul Jain, Pooja Jain, Tapan Kumar, and Gaurav Dhiman
Springer Science and Business Media LLC
Joey Pinto, Pooja Jain, and Tapan Kumar
Springer Science and Business Media LLC
Kritika Dhawale, Ankit Singh Vohra, Pooja Jain, and Tapan Kumar
Springer Singapore
Pooja Jain, Vaibhav Agasti, and Tapan Kumar
Springer Singapore
Ilayaraja Sreesurya, Himani Rathi, Pooja Jain, and Tapan Kumar Jain
Springer Science and Business Media LLC
Sentiment analysis, an application of machine learning in business is the process of identifying and cataloging comments, reviews, tweets, feedback, and even random rants according to the tone or sentiments conveyed by it. The data is analysed using machine learning approach of Long Short Term Memory (LSTM) rating the sentiments on a scale ranging from −100 to 100. A new proposed activation function is used for LSTM giving best results as compared to the existing Artificial Neural Network (ANN) techniques. Depending upon the mined opinion, the business intelligence tools evaluate the products or services of a company eventually resulting in the increase of the sales of that company. The results clearly show that BI extracted from SA is quite instrumental in driving business effectiveness and innovation.
Tapan Jain
IEEE
Steganography techniques have been used since ancient time. Today when all the confidential data are being sent digitally then the need for steganography to be applied to digital media has increased all the more. This paper aims to achieve a thorough understanding of the existing spatial domain steganography techniques. It focuses on understanding the advantages and limitations of existing algorithms so that a more effective technique combing best features of one or more techniques can be proposed. Then an algorithm is proposed which focuses on steganalysis of images classifying them as stego or cover using neural network. It compares the performance of neural network based on the different inputs to the neural network. The experimental implementation show that LSB is best suited for steganography and feature extraction as an input, gives the best steganalysis results. To reduce the storage space, differential storage is used.
Ankit K. Barai, Pooja Jain, and Tapan Kumar
Springer Singapore
Joey Pinto, Pooja Jain, and Tapan Kumar
Inderscience Publishers
RECENT SCHOLAR PUBLICATIONS
MOST CITED SCHOLAR PUBLICATIONS
GRANT DETAILS
One Funded Project from DRDO
Industry, Institute, or Organisation Collaboration
MoU: TCS Innovation Lab
INDUSTRY EXPERIENCE
Four years:
2005-2007, KLA Tencor India Private Limited.
2007-2009, CRMnext, Acidaes Solutions Private Limited.