Search

Your search keyword '"Chauhan, J"' showing total 686 results
Start Over Author "Chauhan, J"
Sorry, I don't understand your search. ×
686 results on '"Chauhan, J"'

62. SPINTRONICS: Electrical switching of an antiferromagnet

Author

Wadley, P., Howells, B., Železný, J., Andrews, C., Hills, V., Campion, R. P., Novák, V., Olejník, K., Maccherozzi, F., Dhesi, S. S., Martin, S. Y., Wagner, T., Wunderlich, J., Freimuth, F., Mokrousov, Y., Kuneš, J., Chauhan, J. S., Grzybowski, M. J., Rushforth, A. W., Edmonds, K. W., Gallagher, B. L., and Jungwirth, T.

Published
2016
Full Text
View/download PDF

63. JUTE AND ALLIED FIBRE CROPS IN INDIA: PRODUCTION, GROWTH, BREEDING AND SEED CHAIN.

Author

CHAUHAN, J. S., KAR, G., MISHRA, J. P., KAR, C. S., SINGH, K. H., CHOUDHURY, P. R., CHAUDHARY, SONU KUMAR, MOHAN, CHANDER, SINGH, R. K., and YADAVA, D.K.

Subjects
*JUTE fiber, *PLANT fibers, *AGRICULTURAL productivity, *CROP growth
Abstract

Jute and allied fibres viz., mesta including kenaf, roselle, ramie, sunhemp, sisal and flax are important industrial crops and the sources of livelihood of about 4 million farm families and supports direct employment to about 3.7 lakh workers. They accounted for about 0.36%, 0.51% and 0.45 of the gross-, net cropped area and total arable land, respectively, in India during 2018-19. The contribution of jute crop to the global acreage and production during 2018 was 49.4% and 53.7%, respectively. Its contribution to global production was reduced to 50.5% during 2019. The present paper analyses the growth of jute and allied crops during 1950-51 to 2020-21; scenario of area, production and yield; breeding and seed production during 2010-11-2021-22. The Compound Annual Growth rate was 0.21%, 1.52% and 1.31%, respectively, for area, production and yield during 1950-51 to 2020-21. The area and production of jute and allied fibres have decreased substantially during the last 12 years despite the enhancement of yield ha-1 from 2197 kg ha-1 in 2010-11 to 2709 kg ha-1 in 2021-22. Of the total 310 varieties of fibre crops (including cotton) released and notified during 2011-23, 43 were of these crops. In jute, leading varieties in the seed chain contributing highest to the breeder seed indent, such as Navin, Suren (JRO 204) and JRO 128 were old released during 1978, 2007 and 2002, respectively, and very old varieties released up to 1995 had a considerably high share in breeder seed indent during 2021-22. During the period under study (2014-15 to 2021-22), there was no indent for breeder seed production of mesta except in 2016-17 and 2021-22 and against the indent of 0.5 q for two varieties, Satyen (JRKM 9-1, released in 2016) and Central Kenaf 2 (JBMP 2, released in 2016), 1.7 q breeder seed was produced during 2016-17. But, during 2021-22 only 22 kg breeder seed against the indent of 9 kg for three varieties HC7910 (Ujjal), released during 1977; HS 4288, released during 1967 and JRM 5 (Shrestha), released during 2010, was produced. In sunhemp, only five varieties, SUIN 037, SUIN 053, JRG 610 (Prankur), PAU 1691 and Chhindwara 1 (Jabalpur 1) were indented for breeder seed production from 2016-17 to 2021-22 released during 2013, 2009, 2015, 2008 and 1973, respectively. Therefore, old varieties for jute and sunhemp need to be replaced in the seed chain. However, no systematic seed production is being followed for other fibre crops like mesta, ramie, sisal and flax. Public sector organizations contributed only up to 30% of the seed requirement of jute in the country. Therefore, there is an urgent need to increase the share of the public sector in seed production to ensure 'seed security' as well as its affordability and timely availability. The possibility should also be explored for jute seed production in areas close to the proximity to the area of cultivation by incentivizing seed production. Systematic seed/planting materials production of other crops such as ramie, sisal and flax that have very low acreage but important fibre crops with specific niches of cultivation should also be initiated / strengthened to ensure availability of quality seed/planting materials to the farmers. Since these are industrial crops, therefore, there is an urgent need to develop linkages with private sector especially textile industry, Farmers' Producing Organizations and Non-Government Organizations for enhancing production of seed/planting materials and also expanding them in new niches by developing suitable models and incentivizing production of fibres from these crops. [ABSTRACT FROM AUTHOR]

Published
2023

65. P70.03 Computational Omics Biology Model (CBM) Identifies Amplifications of Chromosome 6p to Predict Chemotherapy Resistance

Author

Velcheti, V., primary, Ganti, A.K., additional, Kumar, A., additional, Patil, V., additional, Khandelwal, S., additional, S, R., additional, S, K., additional, Lunkad, N., additional, S, V., additional, Narvekar, Y., additional, Pampana, A., additional, Mundkur, N., additional, Patel, S., additional, Behura, L., additional, Mandal, R., additional, Velkuru, Y., additional, Balakrishnan, V., additional, Chauhan, J., additional, G, P., additional, Gupta, N., additional, Patil, M., additional, Prakash, A., additional, Kr, R., additional, Sahu, D., additional, and Castro, M., additional

Published
2021
Full Text
View/download PDF

73. ContAuth

Author

Chauhan, J, Kwon, YD, Hui, P, and Mascolo, C

Subjects
Breathing Gestures, Incremental Learning, EMG, Neural Networks, Gait, Behavior based Authentication
Abstract

User authentication is key in user authorization on smart and personal devices. Over the years, several authentication mechanisms have been proposed: these also include behavioral-based biometrics. However, behavioral-based biometrics suffer from two issues: they are prone to degradation in performance (accuracy) over time (e.g., due to data distribution changes arising from user behavior) and the need to learn the machine learning model from scratch, when adding new users. In this paper, we propose ContAuth, a system that can enhance the robustness of behavioral-based authentication. ContAuth continuously adapts to new incoming data (data incremental learning) and is able to add new users without retraining (class incremental learning). Specifically, ContAuth combines deep learning models with online learning models to achieve learning on the fly, thereby preventing a severe drop in the accuracy between sessions (over time). To add new users, ContAuth employs class incremental learning methods. We evaluate ContAuth on multiple behavior-based user authentication modalities: breathing, gait. and EMG. Our results show that our framework can help True Positive Rate (TPR) to remain high (>85 %) compared to other methods for all the modalities except EMG (>70%) across the sessions while keeping False Positive Rates (FPR) at a minimum (0-10%). It can achieve up to 35% improvement in TPR over a traditional deep learning model. Additionally, iCaRL (an incremental learning method) enables ContAuth to allow the addition of new users by alleviating catastrophic forgetting, to a large extent. Finally, we also show that ContAuth can be deployed efficiently and effectively on device, further providing data privacy.

Published
2021
Full Text
View/download PDF

79. The black hole transient MAXI J1348–630: evolution of the compact and transient jets during its 2019/2020 outburst

Author

Carotenuto, F, primary, Corbel, S, additional, Tremou, E, additional, Russell, T D, additional, Tzioumis, A, additional, Fender, R P, additional, Woudt, P A, additional, Motta, S E, additional, Miller-Jones, J C A, additional, Chauhan, J, additional, Tetarenko, A J, additional, Sivakoff, G R, additional, Heywood, I, additional, Horesh, A, additional, van der Horst, A J, additional, Koerding, E, additional, and Mooley, K P, additional

Published
2021
Full Text
View/download PDF

80. Strong low-frequency radio flaring from Cygnus X-3 observed with LOFAR

Author

Broderick, J W, primary, Russell, T D, additional, Fender, R P, additional, Trushkin, S A, additional, Green, D A, additional, Chauhan, J, additional, Nizhelskij, N A, additional, Tsybulev, P G, additional, Bursov, N N, additional, Shevchenko, A V, additional, Pooley, G G, additional, Williams, D R A, additional, Bright, J S, additional, Rowlinson, A, additional, and Corbel, S, additional

Published
2021
Full Text
View/download PDF

82. Magneto-Seebeck microscopy of domain switching in collinear antiferromagnet CuMnAs

Author

Janda, T., Godinho, J., Ostatnicky, T., Pfitzner, E., Ulrich, G., Hoehl, A., Reimers, S., Metzger, T., Campion, R. P., Heberle, J., Wadley, P., Edmonds, K. W., Amin, O. J., Chauhan, J. S., Dhesi, S. S., Maccherozzi, F., Otxoa, R. M., Roy, P. E., N?mec, P., Jungwirth, T., Kaestner, B., and Wunderlich, J.

Abstract

Antiferromagnets offer spintronic device characteristics unparalleled in ferromagnets owing to their lack of stray fields, THz spin dynamics, and rich materials landscape. Microscopic imaging of antiferromagnetic domains is one of the key prerequisites for understanding physical principles of the device operation. However, adapting common magnetometry techniques to the dipolar-field-free antiferromagnets has been a major challenge. Here we demonstrate in a collinear antiferromagnet a thermoelectric detection method by combining the magneto-Seebeck effect with local heat gradients generated by scanning far-field or near-field techniques. In a 20-nm epilayer of uniaxial CuMnAs we observe reversible 180∘ switching of the Néel vector via domain wall displacement, controlled by the polarity of the current pulses. We also image polarity-dependent 90∘ switching of the Néel vector in a thicker biaxial film, and domain shattering induced at higher pulse amplitudes. The antiferromagnetic domain maps obtained by our laboratory technique are compared to measurements by the established synchrotron-based technique of x-ray photoemission electron microscopy using x-ray magnetic linear dichroism.

Published
2020

83. Integrated Pest Management for Acacia: Prospects and Challenges

Author

Kaushik P, Saini I, Chauhan J, and Kumar T

Subjects
Integrated pest management, biology, Agroforestry, other, Acacia, Business, biology.organism_classification
Abstract

Species of Acacia have been extensively entrenched in the tropical, and semi-arid regions as well as in the southern hemisphere. Acacia species have been bounteous faces the pest and pathogenic pressure. Integrated Pest Management (IPM) is an immensely important aspect of producing a healthy Acacia plantation without harmful impacts on the environment. Here an attempt was made to determine the possibilities of integrated pest management for Acacia. Overall, this information will be helpful to increase awareness about the integrated pest management of the members of the genus Acacia.

Published
2020

84. A Brief Perspective on Acacia a Member of Family Leguminosae

Author

Chauhan J, Singh T, Saini I, and Kaushik P

Subjects
Insect pest, biology, Agroforestry, Perspective (graphical), Acacia, biochemistry, Family Leguminosae, biology.organism_classification
Abstract

Tree members of the genus Acacia have benefits that are obvious for enhancing soil fertility in farming, forestry and agroforestry in regions with nutrient-poor soils, and for restoring degraded ecosystems and lands. Nevertheless, the species of the genus Acacia have got the potential to bring about significant adverse impacts on biodiversity or ecosystem functioning when it gets invasive. The ecology of the species in nearly all areas of its created range remains poorly understood. Here we have compiled the information regarding the importance, cultivation and the production of important species of genus Acacia. We hope this information will be useful to get awareness about the crucial trees in the genus Acacia.

Published
2020

85. ContAuth

Author

Chauhan, J, Kwon, YD, Hui, P, Mascolo, C, Kwon, Young Dae [0000-0002-5216-9057], Mascolo, Cecilia [0000-0001-9614-4380], and Apollo - University of Cambridge Repository

Subjects
Breathing Gestures, Incremental Learning, EMG, Neural Networks, Gait, Behavior based Authentication
Abstract

User authentication is key in user authorization on smart and personal devices. Over the years, several authentication mechanisms have been proposed: these also include behavioral-based biometrics. However, behavioral-based biometrics suffer from two issues: they are prone to degradation in performance (accuracy) over time (e.g., due to data distribution changes arising from user behavior) and the need to learn the machine learning model from scratch, when adding new users. In this paper, we propose ContAuth, a system that can enhance the robustness of behavioral-based authentication. ContAuth continuously adapts to new incoming data (data incremental learning) and is able to add new users without retraining (class incremental learning). Specifically, ContAuth combines deep learning models with online learning models to achieve learning on the fly, thereby preventing a severe drop in the accuracy between sessions (over time). To add new users, ContAuth employs class incremental learning methods. We evaluate ContAuth on multiple behavior-based user authentication modalities: breathing, gait. and EMG. Our results show that our framework can help True Positive Rate (TPR) to remain high (>85 %) compared to other methods for all the modalities except EMG (>70%) across the sessions while keeping False Positive Rates (FPR) at a minimum (0-10%). It can achieve up to 35% improvement in TPR over a traditional deep learning model. Additionally, iCaRL (an incremental learning method) enables ContAuth to allow the addition of new users by alleviating catastrophic forgetting, to a large extent. Finally, we also show that ContAuth can be deployed efficiently and effectively on device, further providing data privacy.

Published
2020

86. Learning attention-based embeddings for relation prediction in knowledge graphs

Author

Nathani, Deepak, Chauhan, J., Sharma, C., Kaul, M, Nathani, Deepak, Chauhan, J., Sharma, C., and Kaul, M

Abstract

The recent proliferation of knowledge graphs (KGs) coupled with incomplete or partial information, in the form of missing relations (links) between entities, has fueled a lot of research on knowledge base completion (also known as relation prediction). Several recent works suggest that convolutional neural network (CNN) based models generate richer and more expressive feature embeddings and hence also perform well on relation prediction. However, we observe that these KG embeddings treat triples independently and thus fail to cover the complex and hidden information that is inherently implicit in the local neighborhood surrounding a triple. To this effect, our paper proposes a novel attention-based feature embedding that captures both entity and relation features in any given entity's neighborhood. Additionally, we also encapsulate relation clusters and multi-hop relations in our model. Our empirical study offers insights into the efficacy of our attention-based model and we show marked performance gains in comparison to state-of-the-art methods on all datasets.

Published
2020

89. Measuring the distance to the black hole candidate X-ray binary MAXI J1348–630 using H i absorption

Author

Chauhan, J, primary, Miller-Jones, J C A, additional, Raja, W, additional, Allison, J R, additional, Jacob, P F L, additional, Anderson, G E, additional, Carotenuto, F, additional, Corbel, S, additional, Fender, R, additional, Hotan, A, additional, Whiting, M, additional, Woudt, P A, additional, Koribalski, B, additional, and Mahony, E, additional

Published
2020
Full Text
View/download PDF

90. Repurposing Atovaquone as a Tumor Hypoxia Modifier: A Window of Opportunity Study in Patients with Resectable Non-small Cell Lung Cancer

Author

Skwarski, M., primary, McGowan, D.R., additional, Belcher, E., additional, Di Chiara, F., additional, Stavroulias, D., additional, Prevo, R., additional, Macklin, P.S., additional, Chauhan, J., additional, O'Reilly, D., additional, Green, M., additional, Ferencz, P., additional, Rodriguez-Berriguete, G., additional, Flight, H., additional, Qi, C., additional, Holmes, J., additional, Buffa, F., additional, McCole, M., additional, Bulte, D., additional, Macpherson, R., additional, and Higgins, G.S., additional

Published
2020
Full Text
View/download PDF

91. Magneto-Seebeck microscopy of domain switching in collinear antiferromagnet CuMnAs

Author

Janda, T., primary, Godinho, J., additional, Ostatnicky, T., additional, Pfitzner, E., additional, Ulrich, G., additional, Hoehl, A., additional, Reimers, S., additional, Šobáň, Z., additional, Metzger, T., additional, Reichlová, H., additional, Novák, V., additional, Campion, R. P., additional, Heberle, J., additional, Wadley, P., additional, Edmonds, K. W., additional, Amin, O. J., additional, Chauhan, J. S., additional, Dhesi, S. S., additional, Maccherozzi, F., additional, Otxoa, R. M., additional, Roy, P. E., additional, Olejník, K., additional, Němec, P., additional, Jungwirth, T., additional, Kaestner, B., additional, and Wunderlich, J., additional

Published
2020
Full Text
View/download PDF

96. Science with the Murchison Widefield Array: Phase I results and Phase II opportunities – Corrigendum

Author

Beardsley, A. P., primary, Johnston-Hollitt, M., additional, Trott, C. M., additional, Pober, J. C., additional, Morgan, J., additional, Oberoi, D., additional, Kaplan, D. L., additional, Lynch, C. R., additional, Anderson, G. E., additional, McCauley, P. I., additional, Croft, S., additional, James, C. W., additional, Wong, O. I., additional, Tremblay, C. D., additional, Norris, R. P., additional, Cairns, I. H., additional, Lonsdale, C. J., additional, Hancock, P. J., additional, Gaensler, B. M., additional, Bhat, N. D. R., additional, Li, W., additional, Hurley-Walker, N., additional, Callingham, J. R., additional, Seymour, N., additional, Yoshiura, S., additional, Joseph, R. C., additional, Takahashi, K., additional, Sokolowski, M., additional, Miller-Jones, J. C. A., additional, Chauhan, J. V., additional, Bojičić, I., additional, Filipović, M. D., additional, Leahy, D., additional, Su, H., additional, Tian, W. W., additional, McSweeney, S. J., additional, Meyers, B. W., additional, Kitaeff, S., additional, Vernstrom, T., additional, Gürkan, G., additional, Heald, G., additional, Xue, M., additional, Riseley, C. J., additional, Duchesne, S. W., additional, Bowman, J. D., additional, Jacobs, D. C., additional, Crosse, B., additional, Emrich, D., additional, Franzen, T. M. O., additional, Horsley, L., additional, Kenney, D., additional, Morales, M. F., additional, Pallot, D., additional, Steele, K., additional, Tingay, S. J., additional, Walker, M., additional, Wayth, R. B., additional, Williams, A., additional, and Wu, C., additional

Published
2020
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results