Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Andrew S. Lan"'
Autor:
Jordan Wight, Ishraq Rahman, Hannah L. Wallace, Joshua T. Cunningham, Sheena Roul, Gregory J. Robertson, Rodney S. Russell, Wanhong Xu, Dmytro Zhmendak, Tamiru N. Alkie, Yohannes Berhane, Kathryn E. Hargan, Andrew S. Lang
Publikováno v:
Veterinary Research, Vol 55, Iss 1, Pp 1-14 (2024)
Abstract Highly pathogenic avian influenza (HPAI) H5N1 clade 2.3.4.4b viruses were first detected in St. John’s, Canada in late 2021. To investigate the patterns of avian influenza virus (AIV) infection and immune responses subsequent to the arriva
Externí odkaz:
https://doaj.org/article/27544dd2887f41bd8f7c39e1901e718e
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c8141f617b34ade139abd6334d035a7
https://doi.org/10.1109/jiot.2021.3070225
https://doi.org/10.1109/jiot.2021.3070225
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6453476149ed883e91b2b5b903ba778e
https://doi.org/10.1109/msp.2021.3055032
https://doi.org/10.1109/msp.2021.3055032
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
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d69493051c182de5ef26c29e5e347999
https://doi.org/10.1109/bigdata52589.2021.9671942
https://doi.org/10.1109/bigdata52589.2021.9671942
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f977ec960acac336ee728ca66d8ba8f
https://doi.org/10.24963/ijcai.2021/332
https://doi.org/10.24963/ijcai.2021/332
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d65b087a44f2acf2d4b4bca388f9a1da
https://doi.org/10.1109/cvprw53098.2021.00304
https://doi.org/10.1109/cvprw53098.2021.00304
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da2f0eb09ba854afc6504e0fdb5c58af
https://doi.org/10.1145/3448139.3448154
https://doi.org/10.1145/3448139.3448154
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe94889de60bf579588abc5f8166e853
https://doi.org/10.1145/3448139.3448153
https://doi.org/10.1145/3448139.3448153