Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Anisha Nazareth"'
Publikováno v:
Transitioning to Reduced Inequalities ISBN: 9783039211616
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::427d361f9fae9d843c7b14d232daf9aa
https://doi.org/10.3390/books978-3-03921-161-6-2
https://doi.org/10.3390/books978-3-03921-161-6-2
Autor:
Zoha Shawoo, Jenny Yi-Chen Han, Katarina Inga, Elvine Kwamboka, Christina Daszkiewicz, Minh Tran, Emily Ghosh, Rocio A. Diaz-Chavez, Claudia Coleoni, Anisha Nazareth
This discussion brief aims to provide insights into ways that individual researchers can aim to shift rather than reinforce unequal power relations in climate and environment research that disadvantage marginalized communities and the Global South. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12a3a0dda02ab4e1e0d69425828cf646
https://doi.org/10.51414/sei2021.028
https://doi.org/10.51414/sei2021.028
In the 25 years from 1990 to 2015, annual global carbon emissions grew by 60%, approximately doubling total global cumulative emissions. This has brought the world perilously close to exceeding 2°C of warming, and it is now on the verge of exceeding
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f09f2885599def1657d1d196f76530a
https://doi.org/10.21201/2020.6492
https://doi.org/10.21201/2020.6492
Autor:
Mark S. Ackerman, Aditya Johri, Priyank Chandra, Vaishnav Kameswaran, Hariharan Subramonyam, Anisha Nazareth, Anandhi Viswanathan, Joyojeet Pal, Sile O'Modhrain
Publikováno v:
CHI
Studies on technology adoption typically assume that a user's perception of usability and usefulness of technology are central to its adoption. Specifically, in the case of accessibility and assistive technology, research has traditionally focused on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9a5d6cd5a811eaa70a0640ecdbfa1b4
https://doi.org/10.1145/3025453.3025895
https://doi.org/10.1145/3025453.3025895
Autor:
Karri Navin, Anisha Nazareth, Piyush Singh Bora, Shrisha Rao, P. S. Anusha, Vishwanath Acharya
Publikováno v:
Current Science. 115:249
Astronomical datasets are typically very large, and manually classifying the data in them is effectively impossible. We use machine learning algorithms to provide classifications (as stars, quasars and galaxies) for more than one billion objects give
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::868e4440ac8f51f0d003dbaba2e289a4
https://doi.org/10.18520/cs/v115/i2/249-257
https://doi.org/10.18520/cs/v115/i2/249-257