Institution
Delhi Technological University
Education•New Delhi, India•
About: Delhi Technological University is a education organization based out in New Delhi, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 4427 authors who have published 6761 publications receiving 71035 citations. The organization is also known as: Delhi College of Engineering & DTU.
Topics: Computer science, Control theory, Artificial neural network, Photovoltaic system, Deep learning
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a condition on 1+β zp'(z)/p^n(z) or p(z)+\beta zp')(z/p''n''p''prec(1+Az)/1+Bz or \sqrt{1+z}.
29 citations
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01 Feb 2020TL;DR: This study extracts the band power, a frequency-domain feature, from the EEG signals and compares the classification accuracies for Valence and Arousal domain for different classifiers, finding the proposed Long Short-Term Memory (LSTM) model achieves the best classification accuracy.
Abstract: This work aims to investigate the performance of the Long Short-Term Memory (LSTM) Model for EEG-Based Emotion Recognition. For the experimentation, we use the publicly available DEAP dataset, which consists of preprocessed EEG and physiological signals. Our work limits itself to the study of only the EEG signals to have a scope for developing an efficient headgear model for real-time monitoring of emotions. In this study, we extract the band power, a frequency-domain feature, from the EEG signals and compare the classification accuracies for Valence and Arousal domain for different classifiers. The proposed Long Short-Term Memory (LSTM) model achieves the best classification accuracy of 94.69% and 93.13% for Valence and Arousal scales, respectively, illustrating a significant average increment of 16% in valence and 18% in arousal in comparison to other classifiers.
29 citations
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TL;DR: In this article, the authors analyse the state of the digital economy by observing growth patterns of some Developmental Variables (GDP and GDP Per capita) and some digitisation variables.
Abstract: This paper aims at analysing the state of the Digital Economy by observing growth patterns of some Developmental Variables (GDP and GDP Per capita) and some digitisation variables. We have analysed...
29 citations
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TL;DR: The simulation results show that the incorporation of flexibility in a manufacturing system is vital, and the choice of the extent of flexibility is driven by the market and economic factors.
29 citations
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05 Jan 2021TL;DR: In this article, an AA7075 composite reinforced with silicon carbide particles has been fabricated using friction stir processing (FSP) in two different rotational speed i.e. 700 and 1000 rpm.
Abstract: In the present research work, AA7075 composite reinforced with silicon carbide particles has been fabricated using Friction stir processing (FSP). The silicon carbide particles having a size of 40 μm were placed in grooves of length 160 mm, width 2 mm, depth 3.5 mm, that were generated on the AA7075 plate. The square pin tool is utilized for fabricating the composite at two different rotational speed i.e. 700 and 1000 rpm. Effect of processing, particle addition and tool rotational speed is analyzed on mechanical and wear properties of the material. On friction stir processing the microhardness value and elongation of the material increased. Reinforcement addition contributed to decrease in ductility and tensile strength while on the contrary microhardness and wear resistance of the material improved. Tool rotational speed showed a direct relation with the tested mechanical and wear properties. Adhesive wear was the prominent wear mechanism and Fe layer formation was observed on the worn surface, contributing to increased wear resistance. These fabricated composites can find vast application in industries like automotive, defence and aerospace.
29 citations
Authors
Showing all 4530 results
Name | H-index | Papers | Citations |
---|---|---|---|
Shaji Kumar | 111 | 1265 | 53237 |
Lars A. Buchhave | 105 | 408 | 46100 |
Anil Kumar | 99 | 2124 | 64825 |
Bansi D. Malhotra | 75 | 375 | 19419 |
C. P. Singh | 68 | 337 | 17448 |
Ramesh Chandra | 66 | 620 | 16293 |
Rajiv S. Mishra | 64 | 591 | 22210 |
William W. Craig | 58 | 316 | 14311 |
S.G. Deshmukh | 56 | 183 | 11566 |
Jay Singh | 51 | 301 | 8655 |
Neeraj Kumar | 50 | 207 | 7670 |
Erling Halfdan Stenby | 50 | 285 | 8500 |
Devendra Singh | 49 | 314 | 10386 |
Federico Calle-Vallejo | 46 | 113 | 11239 |
Rajesh Singh | 46 | 692 | 10339 |