Institution
Indian Institute of Technology Bombay
Education•Mumbai, India•
About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Population & Thin film. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.
Papers published on a yearly basis
Papers
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TL;DR: The effectiveness of low cost agro-based materials namely, Tamarindus indica seed (TS), crushed coconut shell (CS), almond shell (AS), ground nut shell (GS) and walnut shell (WS) were evaluated for Cr(VI) removal and batch test indicated that hexavalent chromium sorption capacity (q(e)) followed the sequence.
276 citations
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TL;DR: In this paper, the authors measured the transverse momentum spectra of pi(+/-), K-+/- and p((p) over bar) up to p(T) = 20 GeV/c at mid-rapidity in pp, peripheral (60-80%) and central (0-5%) Pb-Pb collisions.
276 citations
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15 Feb 2018TL;DR: Empirical evaluation on three different applications establishes that (1) domain-guided perturbation provides consistently better generalization to unseen domains, compared to generic instance perturbations methods, and that (2) data augmentation is a more stable and accurate method than domain adversarial training.
Abstract: We present CROSSGRAD, a method to use multi-domain training data to learn a classifier that generalizes to new domains. CROSSGRAD does not need an adaptation phase via labeled or unlabeled data, or domain features in the new domain. Most existing domain adaptation methods attempt to erase domain signals using techniques like domain adversarial training. In contrast, CROSSGRAD is free to use domain signals for predicting labels, if it can prevent overfitting on training domains. We conceptualize the task in a Bayesian setting, in which a sampling step is implemented as data augmentation, based on domain-guided perturbations of input instances. CROSSGRAD parallelly trains a label and a domain classifier on examples perturbed by loss gradients of each other's objectives. This enables us to directly perturb inputs, without separating and re-mixing domain signals while making various distributional assumptions. Empirical evaluation on three different applications where this setting is natural establishes that (1) domain-guided perturbation provides consistently better generalization to unseen domains, compared to generic instance perturbation methods, and that (2) data augmentation is a more stable and accurate method than domain adversarial training.
276 citations
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TL;DR: In this article, a clear correlation between defect-related emissions and the magnetization of ZnO nanorods synthesized by a one-step aqueous chemical method is demonstrated.
Abstract: A clear correlation between defect-related emissions and the magnetization of ZnO nanorods synthesized by a one-step aqueous chemical method is demonstrated. The relative contribution of the emission bands arising from various types of defects is determined and found to be linked with the size of the nanorods and annealing conditions. When the size of the nanorods and the annealing temperature are increased, the magnetization of pure ZnO nanorods decreases with the reduction of a defect-rotated band originating from singly charged oxygen vacancies (V + o ). With a sufficient increase of annealing temperature (at 900 °C), the nanorods show diamagnetic behavior. Combining with the electron paramagnetic resonance results, a direct link between the magnetization and the relative occupancy of the singly charged oxygen vacancies present on the surface of ZnO nanorods is established.
276 citations
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TL;DR: Different applications of fiber reinforced polymer composites (FRPCs) for external strengthening in civil construction are reviewed in this paper, where experimental as well as analytical and numerical research contributions have been focussed in the review.
275 citations
Authors
Showing all 17055 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jovan Milosevic | 152 | 1433 | 106802 |
C. N. R. Rao | 133 | 1646 | 86718 |
Robert R. Edelman | 119 | 605 | 49475 |
Claude Andre Pruneau | 114 | 610 | 45500 |
Sanjeev Kumar | 113 | 1325 | 54386 |
Basanta Kumar Nandi | 112 | 572 | 43331 |
Shaji Kumar | 111 | 1265 | 53237 |
Josep M. Guerrero | 110 | 1197 | 60890 |
R. Varma | 109 | 497 | 41970 |
Vijay P. Singh | 106 | 1699 | 55831 |
Vinayak P. Dravid | 103 | 817 | 43612 |
Swagata Mukherjee | 101 | 1048 | 46234 |
Anil Kumar | 99 | 2124 | 64825 |
Dhiman Chakraborty | 96 | 529 | 44459 |
Michael D. Ward | 95 | 823 | 36892 |