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Items where Division is "Current Faculties > Faculty of Engineering and Physical Sciences > Web Science Institute > CDT Web Science Innovation
Web Science Institute > CDT Web Science Innovation" and Year is 2022

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Group by: No Grouping | Authors/Creators | Item Type
Jump to: B | C | F | G | K | L | M | P | R | S | T | Z
Number of items: 18.

B

An investigation into facial depth data for audio-visual speech recognition - Stefan Bleeck and Travis James Francis Paul Ralph-Donaldson
Type: Conference or Workshop Item | 2022 | Item not available on this server.

Type: Dataset | 2022 | University of Southampton

C

A data-driven analysis of the interplay between criminological theory and predictive policing algorithms - Age Chapman, Pamela Ugwudike, Philip Grylls, David Gammack and Jacqueline, Anne Ayling
Type: Conference or Workshop Item | 2022 | Association for Computing Machinery

Type: Thesis | 2022 | University of Southampton

Type: Dataset | 2022 | University of Southampton

F

Type: Dataset | 2022 | University of Southampton

G

Solid-phase Mn speciation in suspended particles along meltwater-influenced fjords of West Greenland - C.M. van Genuchten, M.J. Hopwood, T. Liu, J. Krause, E.P. Achterberg, M.T. Rosing and L. Meire
Type: Article | 2022 | Item not available on this server.

K

Type: Article | 2022 | Item not available on this server.

L

Type: Article | 2022

M

Type: Dataset | 2022 | University of Southampton

Type: Dataset | 2022 | University of Southampton

P

Work After Lockdown: No Going Back: What we have learned working from home through the COVID-19 pandemic - Jane Parry, Zoe Young, Stephen Bevan, Michail Veliziotis, Yehuda Baruch, Mina Beigi, Zofia Bajorek, Sarah Richards and Chira Tochia
Type: Monograph | 2022 | University of Southampton

Type: Article | 2022

R

Type: Dataset | 2022 | University of Southampton

S

Type: Dataset | 2022 | University of Southampton

Type: Thesis | 2022 | University of Southampton

T

Type: Dataset | 2022 | University of Southampton

Z

Ethnicity and risks of severe COVID‐19 outcomes associated with glucose‐lowering medications: A cohort study - Francesco Zaccardi, Pui San Tan, Carol Coupland, Baiju R. Shah, Ash Kieran Clift, Defne Saatci, Martina Patone, Simon J. Griffin, Hajira Dambha-Miller, Kamlesh Khunti and Julia Hippisley-Cox
Type: Letter | 2022

This list was generated on Tue Dec 17 02:09:48 2024 GMT.
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