Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Dai, William"'
Autor:
Snehalkumar, Gaikwad, S., Morina, Durim, Ginzberg, Adam, Mullings, Catherine, Goyal, Shirish, Gamage, Dilrukshi, Diemert, Christopher, Burton, Mathias, Zhou, Sharon, Whiting, Mark, Ziulkoski, Karolina, Ballav, Alipta, Gilbee, Aaron, Niranga, Senadhipathige S., Sehgal, Vibhor, Lin, Jasmine, Kristianto, Leonardy, Richmond-Fuller, Angela, Regino, Jeff, Chhibber, Nalin, Majeti, Dinesh, Sharma, Sachin, Mananova, Kamila, Dhakal, Dinesh, Dai, William, Purynova, Victoria, Sandeep, Samarth, Chandrakanthan, Varshine, Sarma, Tejas, Matin, Sekandar, Nasser, Ahmed, Nistala, Rohit, Stolzoff, Alexander, Milland, Kristy, Mathur, Vinayak, Vaish, Rajan, Bernstein, Michael S.
Publikováno v:
Proceedings of the 29th Annual Symposium on User Interface Software and Technology, 2016
Paid crowdsourcing platforms suffer from low-quality work and unfair rejections, but paradoxically, most workers and requesters have high reputation scores. These inflated scores, which make high-quality work and workers difficult to find, stem from
Externí odkaz:
http://arxiv.org/abs/1904.06722
Autor:
Gaikwad, Snehalkumar "Neil" S., Chhibber, Nalin, Sehgal, Vibhor, Ballav, Alipta, Mullings, Catherine, Nasser, Ahmed, Richmond-Fuller, Angela, Gilbee, Aaron, Gamage, Dilrukshi, Whiting, Mark, Zhou, Sharon, Matin, Sekandar, Niranga, Senadhipathige, Goyal, Shirish, Majeti, Dinesh, Srinivas, Preethi, Ginzberg, Adam, Mananova, Kamila, Ziulkoski, Karolina, Regino, Jeff, Sarma, Tejas, Sinha, Akshansh, Paul, Abhratanu, Diemert, Christopher, Murag, Mahesh, Dai, William, Pandey, Manoj, Vaish, Rajan, Bernstein, Michael
Low-quality results have been a long-standing problem on microtask crowdsourcing platforms, driving away requesters and justifying low wages for workers. To date, workers have been blamed for low-quality results: they are said to make as little effor
Externí odkaz:
http://arxiv.org/abs/1707.05645
Publikováno v:
In Journal of Computational Physics 1 November 2015 300:643-664
Publikováno v:
In Journal of Computational Physics 15 January 2015 281:982-1002
Autor:
Gaikwad, Snehalkumar \\'Neil\\' S., Chhibber, Nalin, Sehgal, Vibhor, Ballav, Alipta, Mullings, Catherine, Nasser, Ahmed, Richmond-Fuller, Angela, Gilbee, Aaron, Gamage, Dilrukshi, Whiting, Mark, Zhou, Sharon, Matin, Sekandar, Niranga, Senadhipathige, Goyal, Shirish, Majeti, Dinesh, Srinivas, Preethi, Ginzberg, Adam, Mananova, Kamila, Ziulkoski, Karolina, Regino, Jeff, Sarma, Tejas, Sinha, Akshansh, Paul, Abhratanu, Diemert, Christopher, Murag, Mahesh, Dai, William, Pandey, Manoj, Vaish, Rajan, Bernstein, Michael
Low-quality results have been a long-standing problem on microtask crowdsourcing platforms, driving away requesters and justifying low wages for workers. To date, workers have been blamed for low-quality results: they are said to make as little effor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd233a2159fd68b1ffaabf9f8d801224
In this paper, we present an approach for a patch-based adaptive mesh refinement (AMR) for multi-physics simulations. The approach consists of clustering, symmetry preserving, mesh continuity, flux correction, communications, and management of patche
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::e602bc1aa6507908bb8888560e682b71
https://zenodo.org/record/1273659
https://zenodo.org/record/1273659
Autor:
Ramis, Borja, Gonzalez, Luis, Iarovyi, Sergii, Lobov, Andrei, Martinez Lastra, Jose L., Vyatkin, Valeriy, Dai, William
Publikováno v:
2014 12th IEEE International Conference on Industrial Informatics (INDIN); 2014, p733-739, 7p
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Akademický článek
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