Zobrazeno 1 - 10
of 5 158
pro vyhledávání: '"Michael A. Flynn"'
Autor:
Sarah Turnbull
Publikováno v:
Journal of Refugee Studies. 32:711-713
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b1398498907de39469bc0781906f1ec
https://doi.org/10.1093/jrs/fez078
https://doi.org/10.1093/jrs/fez078
Autor:
Jacqueline M. Sivén, PhD, MA, MPH, Julia F. Coburn, MA, Tristan P. Call, PhD, Dillon Mahoney, PhD, Rebeca Rodríguez Flores, BA, Harpriya Kaur, PhD, MPH, Michael A. Flynn, MA, Cammie K. Chaumont Menéndez, PhD, MPH, MS
Publikováno v:
AJPM Focus, Vol 2, Iss 4, Pp 100128- (2023)
Introduction: The objective of this project was to investigate U.S. meat and poultry processing workers’ knowledge of COVID-19; their perceived ability to protect themselves from infection; and perspectives on COVID-19 vaccines to inform COVID-19 p
Externí odkaz:
https://doaj.org/article/c9973f65c6d3495586d7838210799243
Autor:
Turnbull, Sarah1 (AUTHOR) s3turnbull@uwaterloo.ca
Publikováno v:
Journal of Refugee Studies. Dec2019, Vol. 32 Issue 4, p711-713. 3p.
Autor:
Maxamillian A. N. Moss, Dagen D. Hughes, Ian Crawford, Martin W. Gallagher, Michael J. Flynn, David O. Topping
Publikováno v:
Atmosphere, Vol 14, Iss 9, p 1416 (2023)
In a comparative study contrasting new and traditional clustering techniques, the capabilities of K-means, the hierarchal clustering algorithm (HCA), and GenieClust were examined. Both K-means and HCA demonstrated strong consistency in cluster profil
Externí odkaz:
https://doaj.org/article/49ed5e98b4d74693bd3c1a4b8d091b47
Autor:
Cecilia B. Rosales, Hilda Dávila Chávez, Michael A. Flynn, Juanita Lara, Isaura Angélica Lira Chávez, Leonardo Olivares Marín, Alejandra Romero Rangel, Ricardo Hirata Okamoto, Maria Gudelia Rangel Gómez
Publikováno v:
Frontiers in Public Health, Vol 10 (2023)
Hardly reached communities in the United States greatly benefit from collective efforts and partnerships from Community Based Organizations, Health Institutions and Government Agencies, yet the effort to engage in this collaborative effort is minimal
Externí odkaz:
https://doaj.org/article/873435340bf14646b8a2a30a69bf7056
Autor:
Pratikkumar H. Vekaria, Areej Syed, Jeffrey Anderson, Brendon Cornett, Amine Bourbia, Michael G. Flynn, Rahul Kashyap, Asif R. Shah
Publikováno v:
Frontiers in Medicine, Vol 9 (2022)
BackgroundWe conducted a retrospective cohort study on COVID-19 patients with and without dementia by extracting data from the HCA Healthcare Enterprise Data Warehouse between January-September 2020.AimsTo describe the role of patients' baseline char
Externí odkaz:
https://doaj.org/article/23d6b5730ddd459d9cde248baed2a533
Publikováno v:
JMIR Dermatology, Vol 5, Iss 3, p e37517 (2022)
BackgroundStore-and-forward (SAF) teledermatology uses electronically stored information, including patient photographs and demographic information, for clinical decision-making asynchronous to the patient encounter. The integration of SAF teledermat
Externí odkaz:
https://doaj.org/article/f628eabdbef54fa1b1491fc19fb52d2e
Autor:
Suzanne M. Lange, Jacob P. Ambrose, Michael C. Flynn, William T. Lowrance, Heidi A. Hanson, Brock B. O’Neil
Publikováno v:
Cancer Medicine, Vol 10, Iss 6, Pp 2075-2079 (2021)
Abstract Introduction Prostate cancer screening using prostate‐specific antigen (PSA) testing remains widespread. The prevalence of PSA testing in young men is unknown and may be an appropriate target for improving health care by decreasing low‐v
Externí odkaz:
https://doaj.org/article/90e25189372f4acfbc859ef971aa2026
Publikováno v:
IEEE Open Journal of the Solid-State Circuits Society, Vol 1, Pp 149-161 (2021)
The Noise-Shaping (NS) SAR is an attractive new ADC architecture that emerged in the last decade. It combines the advantages of the SAR and the DSM architectures. NS SAR shows excellent potential for high efficiency and low cost, and is highly suited
Externí odkaz:
https://doaj.org/article/090269d7c71743b9a299a8172c680005
Autor:
Justin M. Correll, Vishishtha Bothra, Fuxi Cai, Yong Lim, Seung Hwan Lee, Seungjong Lee, Wei D. Lu, Zhengya Zhang, Michael P. Flynn
Publikováno v:
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 6, Iss 1, Pp 36-44 (2020)
Analog compute-in-memory with resistive random access memory (RRAM) devices promises to overcome the data movement bottleneck in data-intensive artificial intelligence (AI) and machine learning. RRAM crossbar arrays improve the efficiency of vector-m
Externí odkaz:
https://doaj.org/article/3d1d7a52eebe4f4f88627fff7858e676