Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Andrew S. Lan"'
Autor:
Johanna-Lisa Bosch, Inmaculada Álvarez-Manzaneda, John P. Smol, Neal Michelutti, Gregory J. Robertson, Sabina I. Wilhelm, William A. Montevecchi, Andrew S. Lang, Kathryn E. Hargan
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Seabird colonies with long-term monitoring records, i.e., > 50 years, are rare. The population data for northern gannets (Morus bassanus) in Cape St. Mary’s (CSM) Ecological Reserve (Newfoundland and Labrador, Canada) is robust, extending
Externí odkaz:
https://doaj.org/article/a501c78bccf4484c9ae0f09c9ad5a2f3
Autor:
Danielle S. McNamara, Tracy Arner, Reese Butterfuss, Debshila Basu Mallick, Andrew S. Lan, Rod D. Roscoe, Henry L. Roediger, Richard G. Baraniuk
Publikováno v:
Artificial Intelligence in STEM Education ISBN: 9781003181187
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac6c66ea647d6f87c90b615e925b6554
https://doi.org/10.1201/9781003181187-23
https://doi.org/10.1201/9781003181187-23
Autor:
Wenjun Hu, Maria Gorlatova, Jose Manjarres, Guohao Lan, Zida Liu, David R. Smith, Andrew S. Lan, Mohammadreza F. Imani
Publikováno v:
IEEE Internet of Things Journal. 8:14110-14126
Conventional radio-frequency (RF) sensing systems rely on either frequency diversity or spatial diversity to ensure high sensing accuracy. Such reliance introduces several practical limitations that hinder the pervasive deployment of existing solutio
Publikováno v:
IEEE Signal Processing Magazine. 38:37-50
The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to ultimately meet her desired goal. This concept emerged several years ago and is being ado
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Autor:
Andrew S. Lan, Aritra Ghosh
Publikováno v:
IJCAI
Computerized adaptive testing (CAT) refers to a form of tests that are personalized to every student/test taker. CAT methods adaptively select the next most informative question/item for each student given their responses to previous questions, effec
Autor:
Andrew S. Lan, Aritra Ghosh
Publikováno v:
CVPR Workshops
Deep neural network-based classifiers trained with the categorical cross-entropy (CCE) loss are sensitive to label noise in the training data. One common type of method that can mitigate the impact of label noise can be viewed as supervised robust me
Autor:
Andrew S. Lan, Sachit Nagpal, Anthony F. Botelho, Neil T. Heffernan, Ryan S. Baker, Shamya Karumbaiah
Publikováno v:
LAK
Despite the abundance of data generated from students’ activities in virtual learning environments, the use of supervised machine learning in learning analytics is limited by the availability of labeled data, which can be difficult to collect for c
Autor:
Brian Zylich, Andrew S. Lan
Publikováno v:
LAK
To adapt materials for an individual learner, intelligent tutoring systems must estimate their knowledge or abilities. Depending on the content taught by the tutor, there have historically been different approaches to student modeling. Unlike common
Autor:
Jolene A. Giacinti, Anthony V. Signore, Megan E. B. Jones, Laura Bourque, Stéphane Lair, Claire Jardine, Brian Stevens, Trent Bollinger, Dayna Goldsmith, Margo Pybus, Iga Stasiak, Richard Davis, Neil Pople, Larissa Nituch, Rodney W. Brook, Davor Ojkic, Ariane Massé, Gabrielle Dimitri-Masson, Glen J. Parsons, Meghan Baker, Carmencita Yason, Jane Harms, Naima Jutha, Jon Neely, Yohannes Berhane, Oliver Lung, Shannon K. French, Lawrna Myers, Jennifer F. Provencher, Stephanie Avery-Gomm, Gregory J. Robertson, Tatsiana Barychka, Kirsty E. B. Gurney, Jordan Wight, Ishraq Rahman, Kathryn Hargan, Andrew S. Lang, William A. Montevecchi, Tori V. Burt, Michael G. C. Brown, Cynthia Pekarik, Trevor Thompson, Angela McLaughlin, Megan Willie, Laurie Wilson, Scott A. Flemming, Megan V. Ross, Jim Leafloor, Frank Baldwin, Chris Sharp, Hannah Lewis, Matthieu Beaumont, Al Hanson, Robert A. Ronconi, Eric Reed, Margaret Campbell, Michelle Saunders, Catherine Soos
Publikováno v:
mBio, Vol 15, Iss 8 (2024)
ABSTRACT Following the detection of novel highly pathogenic avian influenza virus (HPAIV) H5N1 clade 2.3.4.4b in Newfoundland, Canada, in late 2021, avian influenza virus (AIV) surveillance in wild birds was scaled up across Canada. Herein, we presen
Externí odkaz:
https://doaj.org/article/18754202dc1644a89ad0b1ccecde07b5