Institution
Indian Institute of Technology Indore
Education•Indore, Madhya Pradesh, India•
About: Indian Institute of Technology Indore is a education organization based out in Indore, Madhya Pradesh, India. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 1606 authors who have published 4803 publications receiving 66500 citations.
Topics: Computer science, Chemistry, Catalysis, Fading, Raman spectroscopy
Papers published on a yearly basis
Papers
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TL;DR: A novel class of orthogonal wavelet filter banks which are localized in time–frequency domain to detect FC and NFC EEG signals automatically and help in localization of the affected brain area which needs to undergo surgery is employed.
Abstract: It is difficult to detect subtle and vital differences in electroencephalogram (EEG) signals simply by visual inspection. Further, the non-stationary nature of EEG signals makes the task more difficult. Determination of epileptic focus is essential for the treatment of pharmacoresistant focal epilepsy. This requires accurate separation of focal and non-focal groups of EEG signals. Hence, an intelligent system that can detect and discriminate focal–class (FC) and non–focal–class (NFC) of EEG signals automatically can aid the clinicians in their diagnosis. In order to facilitate accurate analysis of non-stationary signals, joint time–frequency localized bases are highly desirable. The performance of wavelet bases is found to be effective in analyzing transient and abrupt behavior of EEG signals. Hence, we employ a novel class of orthogonal wavelet filter banks which are localized in time–frequency domain to detect FC and NFC EEG signals automatically. We classify EEG signals as FC and NFC using the proposed wavelet based system. We compute various entropies from the wavelet coefficients of the signals. These entropies are used as discriminating features for the classification of FC and NFC of EEG signals. The features are ranked using Student’s t-test ranking algorithm and then fed to Least Squares-Support Vector Machine (LS–SVM) to classify the signals. Our proposed method achieved the highest classification accuracy of 94.25%. We have obtained 91.95% sensitivity and 96.56% specificity, respectively, using this method. The classification of FC and NFC of EEG signals helps in localization of the affected brain area which needs to undergo surgery.
148 citations
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TL;DR: The production of the double-strange baryon resonances (Sigma (1385+/-), Xi (1530)(0)) has been measured at mid-rapidity (vertical bar y vertical bar < 0.5) in proton-proton collisions at root s = 7 TeV with the ALICE detector at the LHC as discussed by the authors.
Abstract: The production of the strange and double-strange baryon resonances (Sigma (1385)(+/-), Xi (1530)(0)) has been measured at mid-rapidity (vertical bar y vertical bar < 0.5) in proton-proton collisions at root s = 7 TeV with the ALICE detector at the LHC. Transverse momentum spectra for inelastic collisions are compared to QCD-inspired models, which in general underpredict the data. A search for the phi (1860) pentaquark, decaying in the Xi pi channel, has been carried out but no evidence is seen.
147 citations
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TL;DR: This is the first work on smart grids, which integrates these two important security components (privacy preserving data aggregation and access control) and the first paper which addresses access control in smart grids.
Abstract: We propose a decentralized security framework for smart grids that supports data aggregation and access control. Data can be aggregated by home area network (HAN), building area network (BAN), and neighboring area network (NAN) in such a way that the privacy of customers is protected. We use homomorphic encryption technique to achieve this. The consumer data that is collected is sent to the substations where it is monitored by remote terminal units (RTU). The proposed access control mechanism uses attribute-based encryption (ABE) which gives selective access to consumer data stored in data repositories and used by different smart grid users. RTUs and users have attributes and cryptographic keys distributed by several key distribution centers (KDC). RTUs send data encrypted under a set of attributes. Since RTUs are maintained in the substations they are well protected in control rooms and are assumed to be trusted. Users can decrypt information provided they have valid attributes. The access control scheme is distributed in nature and does not rely on a single KDC to distribute the keys which makes the approach robust. To the best of our knowledge, ours is the first work on smart grids, which integrates these two important security components (privacy preserving data aggregation and access control) and the first paper which addresses access control in smart grids.
147 citations
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TL;DR: In this article, a review of the current state of the art for sustainable manufacturing of gears is presented, which also recommends ways to improve the productivity and quality while simultaneously ensuring environmental sustainability.
147 citations
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TL;DR: In this paper, the authors present a comprehensive study of the die and mold repairing industries and assist the selection of the most appropriate process depending upon the availability of resources with thorough knowledge of the advantages and limitations.
145 citations
Authors
Showing all 1738 results
Name | H-index | Papers | Citations |
---|---|---|---|
Raghunath Sahoo | 106 | 556 | 37588 |
Biswajeet Pradhan | 98 | 735 | 32900 |
A. Kumar | 96 | 505 | 33973 |
Franco Meddi | 84 | 476 | 24084 |
Manish Sharma | 82 | 1407 | 33361 |
Anindya Roy | 59 | 301 | 14306 |
Krishna R. Reddy | 58 | 400 | 11076 |
Sudipan De | 54 | 99 | 10774 |
Sudip Chakraborty | 51 | 343 | 9319 |
Shaikh M. Mobin | 51 | 515 | 11467 |
Ashok Kumar | 50 | 405 | 10001 |
Ankhi Roy | 49 | 259 | 8634 |
Aditya Nath Mishra | 49 | 139 | 7607 |
Ram Bilas Pachori | 48 | 182 | 8140 |
Pragati Sahoo | 47 | 133 | 6535 |