Zobrazeno 1 - 10
of 182
pro vyhledávání: '"Pang-Ning Tan"'
Autor:
Tyler Wagner, Noah R. Lottig, Meridith L. Bartley, Ephraim M. Hanks, Erin M. Schliep, Nathan B. Wikle, Katelyn B. S. King, Ian McCullough, Jemma Stachelek, Kendra S. Cheruvelil, Christopher T. Filstrup, Jean Francois Lapierre, Boyang Liu, Patricia A. Soranno, Pang‐Ning Tan, Qi Wang, Katherine Webster, Jiayu Zhou
Publikováno v:
Limnology and Oceanography Letters, Vol 5, Iss 2, Pp 228-235 (2020)
Abstract Aquatic scientists require robust, accurate information about nutrient concentrations and indicators of algal biomass in unsampled lakes in order to understand and predict the effects of global climate and land‐use change. Historically, la
Externí odkaz:
https://doaj.org/article/14d22d27c9234f8d90f94499276810c3
Publikováno v:
Frontiers in Big Data, Vol 4 (2021)
The US Drought Monitor (USDM) is a hallmark in real time drought monitoring and assessment as it was developed by multiple agencies to provide an accurate and timely assessment of drought conditions in the US on a weekly basis. The map is built based
Externí odkaz:
https://doaj.org/article/b82df35832a94046887f98753b3552d3
Publikováno v:
JMIR Public Health and Surveillance, Vol 7, Iss 6, p e23105 (2021)
BackgroundDespite numerous counteracting efforts, antivaccine content linked to delays and refusals to vaccinate has grown persistently on social media, while only a few provaccine campaigns have succeeded in engaging with or persuading the public to
Externí odkaz:
https://doaj.org/article/d70741a3969c4c7ebd42267a9ff1117f
Autor:
Saleem Alhabash, Courtland VanDam, Pang-Ning Tan, Sandi W. Smith, Gregory Viken, Duygu Kanver, Liang Tian, Luiz Figueira
Publikováno v:
SAGE Open, Vol 8 (2018)
Past research has suggested an associative relationship between social media use and alcohol consumption, especially among the younger generations. The current study takes a generalizable approach to examining the prevalence of posting about alcohol
Externí odkaz:
https://doaj.org/article/0c9a946b51ab4d5ca9c852e17d99bb60
Autor:
Samantha K. Oliver, C. Emi Fergus, Nicholas K. Skaff, Tyler Wagner, Pang‐Ning Tan, Kendra Spence Cheruvelil, Patricia A. Soranno
Publikováno v:
Ecosphere, Vol 9, Iss 4, Pp n/a-n/a (2018)
Abstract Science is increasingly being conducted in large, interdisciplinary teams. As team size increases, challenges can arise during manuscript development, where achieving one team goal (e.g., inclusivity) may be in direct conflict with other goa
Externí odkaz:
https://doaj.org/article/947c8c11d01645eab517433585d164f6
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:4245-4253
Geospatio-temporal data are pervasive across numerous application domains.These rich datasets can be harnessed to predict extreme events such as disease outbreaks, flooding, crime spikes, etc. However, since the extreme events are rare, predicting th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ba2ed5178c6d4592aafc3dc980625c6
https://doi.org/10.1609/aaai.v36i4.20344
https://doi.org/10.1609/aaai.v36i4.20344
Publikováno v:
2022 IEEE International Conference on Data Mining (ICDM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9280b45877d25c8115d192e6748ea080
https://doi.org/10.1109/icdm54844.2022.00139
https://doi.org/10.1109/icdm54844.2022.00139
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 33:2764-2775
Predictive modeling of large-scale spatio-temporal data is an important but challenging problem as it requires training models that can simultaneously predict the target variables of interest at multiple locations while preserving the spatial and tem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::840c66baf26d4dc0d54a5c4b6c4bdb04
https://doi.org/10.1109/tkde.2019.2956713
https://doi.org/10.1109/tkde.2019.2956713
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9791a9902f9c4f1d8b6a574f72bd5e8
https://doi.org/10.1145/3534678.3539464
https://doi.org/10.1145/3534678.3539464
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3201ccf8ecdd466d961e15447081f28
https://doi.org/10.1109/ijcnn55064.2022.9892919
https://doi.org/10.1109/ijcnn55064.2022.9892919