Institution
College of Engineering, Pune
About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Sliding mode control & Control theory. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.
Topics: Sliding mode control, Control theory, Feature extraction, Cloud computing, Wireless sensor network
Papers published on a yearly basis
Papers
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02 Apr 2021TL;DR: In this article, the authors compared different wavelet transform functions for denoising EEG signals and concluded that wavelet transforms are more efficient than other filtering techniques in noise removal while sustaining diagnostic information in both the signal.
Abstract: Electroencephalography (EEG) provides diagnostic information related to various brain disorders. Various types of interferences, like line interference, EOG, and ECG, muscle movement, cause artifacts in EEG data. Therefore, denoising EEG data plays a vital role in preserving the specific frequency content of the signal. Several filtering techniques are available to detach the noise to preserve the integrity of EEG signals. In this paper, we have compared different filtering techniques i.e., Adaptive filters, LPF Butterworth filter, Notch filter, wavelets on epileptic EEG signals, and sleep EEG signal. Our result suggests that the wavelet transform is the best option for denoising the EEG signal as it is more efficient in denoising the EEG signal without losing the original information. To select the best suitable wavelet function for denoising, Symlet4, Haar, Daubechies4, Biorthogonal2.6, Coiflets3, Discrete Meyer, Reverse Biorthogonal 6.8, Reverse Biorthogonal 2.8 has been used, and it is observed that wavelet function Bio-orthogonal 2.6 is the best suitable for denoising of EEG signal. Finally, a comparison between different filters has been done by two parameters MSE, PSNR. After a comparative analysis, we conclude that a wavelet transform is a useful tool than other filtering techniques in noise removal while sustaining diagnostic information in both the signal.
7 citations
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01 Aug 2015TL;DR: An Automatic Question Generation system that focuses on questions that can be generated in English from structured data, which takes a data table as input and generates questions of varying types.
Abstract: For competitive examinations (e.g. GMAT, CAT) and for various offline and online academic courses, test questions need to be written by human authors. These question-writing tasks take significant manual effort and time. To simplify this effort, we propose an Automatic Question Generation system that focuses on questions that can be generated in English from structured data. This paper explains an approach, which takes a data table as input and generates questions of varying types. The data is preprocessed and categorized according to their class (numeric and nonnumeric). Appropriate templates are used to create various kinds of questions. A custom tagger is built, which takes the data entry and assigns it an entity, such that it can be generalized to a particular entity name. For uncategorized or unrecognized entities, options to add or modify entities are also provided. Preliminary experimental work carried out using this template system shows promising results. To the best of our knowledge, this is the first such question generation system based on structured data in the form of tables.
7 citations
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TL;DR: In this article, the authors have investigated the high temperature compression, stress-relaxation, and strain-rate change behavior of the INRAFM steel and found that the rate-controlling mechanisms at the thermally activated region of high temperature were found to be the nonconservative movement of jogged screw dislocations and thermal breaking of attractive junctions.
Abstract: India-specific reduced activity ferritic martensitic steel (INRAFM), a modified 9Cr-1Mo grade, has been developed by India as its own structural material for fabrication of the Indian Test Blanket Module (TBM) to be installed in the International Thermonuclear Energy Reactor (ITER). The extensive study on mechanical and physical properties of this material has been currently going on for appraisal of this material before being put to use in the ITER. High temperature compression, stress–relaxation, and strain-rate change behavior of the INRAFM steel have been investigated. The optical microscopic and scanning electron microscopic characterizations were carried out to observe the microstructural changes that occur during uniaxial compressive deformation test. Comparable true plastic stress values at 300 °C and 500 °C and a high drop in true plastic stress at 600 °C were observed during the compression test. Stress–relaxation behaviors were investigated at 500 °C, 550 °C, and 600 °C at a strain rate of 10−3 s−1. The creep properties of the steel at different temperatures were predicted from the stress–relaxation test. The Norton’s stress exponent (n) was found to decrease with the increasing temperature. Using Bird–Mukherjee–Dorn relationship, the temperature-compensated normalized strain rate vs stress was plotted. The stress exponent (n) value of 10.05 was obtained from the normalized plot. The increasing nature of the strain rate sensitivity (m) with the test temperature was found from strain-rate change test. The low plastic stability with m ~ 0.06 was observed at 600 °C. The activation volume (V*) values were obtained in the range of 100 to 300 b3. By comparing the experimental values with the literature, the rate-controlling mechanisms at the thermally activated region of high temperature were found to be the nonconservative movement of jogged screw dislocations and thermal breaking of attractive junctions.
7 citations
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13 Jun 2013TL;DR: In this article, the design of sliding mode control strategy based on Time Delay Control (TDC) is presented, in which the time delayed signals of system variables are used to estimate and compensate the system uncertainties and external disturbances.
Abstract: In this paper, the design of sliding mode control strategy based on Time Delay Control (TDC) is presented. TDC is a control technique in which the time delayed signals of system variables are used to estimate and compensate the system uncertainties and external disturbances. This paper shows how TDC works when the plant have an external unmeasurable disturbance and with uncertain parameters. Finally, all the results are experimentally verified on the Quanser QET DCMCT kit.
7 citations
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01 Oct 2016TL;DR: The multiplier architecture proposed in this paper is based on the urdhva triyakbham sutra of ancient Indian Vedic mathematics (vertical and crosswise) and the effectiveness of this method is to be tested against the conventional multiplication in mathematics with the focus as easy and faster multiplication.
Abstract: In this work the authors proposed a multiplier circuit which is one of the important hardware block in most of the digital and high performance systems such as ALU in the microprocessors and controllers. Multiplication is one of the most time consuming operation as a number of bit increase multiplication become cumbersome in the processors. The multiplier architecture proposed in this paper is based on the urdhva triyakbham sutra of ancient Indian Vedic mathematics (vertical and crosswise). The effectiveness of this method is to be tested against the conventional multiplication in mathematics with the focus as easy and faster multiplication. The number of digits varied and the algorithm is tested for its suitability over conventional multiplier. The results are tabulated in term of number of gates, time required for multiplication with respect to number of digits.
7 citations
Authors
Showing all 4264 results
Name | H-index | Papers | Citations |
---|---|---|---|
Devavrat Shah | 66 | 374 | 18772 |
Kenji Higashi | 57 | 510 | 14336 |
Bijnan Bandyopadhyay | 38 | 360 | 5611 |
Kalpana Joshi | 27 | 100 | 2452 |
Nikhil Naik | 25 | 55 | 3562 |
J.K. Chakravartty | 23 | 153 | 1711 |
M. D. Uplane | 21 | 75 | 1567 |
Shrivijay B. Phadke | 21 | 68 | 1989 |
Kiyohito Okamura | 21 | 89 | 1157 |
Sudeep D. Thepade | 21 | 241 | 2173 |
Rajendra Kumar Goyal | 20 | 71 | 1236 |
Avinash M. Dongare | 20 | 83 | 1149 |
Parikshit N. Mahalle | 17 | 118 | 1534 |
Parag Kulkarni | 17 | 116 | 1633 |
Elumalai Natarajan | 17 | 56 | 1470 |