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Twitter 1 – SCPHRP

https://blogs.ed.ac.uk/scphrp/bulletin-8-twitter-1/

Scottish Collaboration for Public Health Research & Policy.

Bulletin 9 Twitter 1 – SCPHRP

https://blogs.ed.ac.uk/scphrp/bulletin-9-twitter-1/

Scottish Collaboration for Public Health Research & Policy.

Courses | Short Courses | University of Edinburgh

https://www.shortcourses.ed.ac.uk/courses?subject=Literature%2C+Writing+and+Film

Short courses at the University of Edinburgh

IDCORE People | EPSRC Industrial CDT in Offshore Renewable Energy (IDCORE)

https://idcore.eng.ed.ac.uk/our-people/all?field_research_theme_tags_tid=6

Wave Venture. Wood Group. Xodus. Zyba Renewables. Research Area. - Any -. Civil/Structural (CS). Computational Modelling (CM). Control Engineering (CE). Electrical Engineering (EE). ... Member type. Research Area. Programme Partner. Industrial Partner.

ResiliencebyDesign Research Innovation Lab – Making Scotland an ACE informed nation

https://blogs.ed.ac.uk/CRFRresilience/2019/02/22/resiliencebydesign-research-innovation-lab/

Photovoice: Use of a participatory action research method to explore the chronic pain experience in older adults. ... British educational research journal, 33(6), 927-942. Mezirow, J. (1997). Transformative learning: Theory to practice.

E_WP4: Context-driven Behaviour Monitoring & Anomaly Detection | University Defence Research Collaboration (UDRC)

https://udrc.eng.ed.ac.uk/archive/phase-2/research/edinburgh-consortium/E_WP4-Context-driven-Behaviour-Monitoring-Anomaly-Detection

The large variability of agreement is striking and in itself highlights one of the great challenges for anomaly detection research : obtaining agreement about what constitutes an anomaly. ... Main menu. The University Defence Research Collaboration (UDRC)

L_WP1: Automated statistical anomaly detection and classification in high dimensions for the networked battlespace | University Defence Research Collaboration (UDRC)

https://udrc.eng.ed.ac.uk/archive/phase-2/research/lssc-consortium/L_WP1-automated-statistical-anomaly-detection-and-classification

Lead Project Partner: Thales. Research Themes: T1,T2,T7 and T10. To develop algorithms for the automatic detection of anomalies from multidimensional, undersampled, non-complete datasets and unreliable sources. ... View all LSSC Consortium Research ».

L_WP2: Handling uncertainty and incorporating domain knowledge | University Defence Research Collaboration (UDRC)

https://udrc.eng.ed.ac.uk/archive/phase-2/research/lssc-consortium/L_WP1-handling-uncertainty-and-incorporating-domain-knowledge

Work Package Leader:Other Academics involved: Research Associate:PhD:Lead Project Partner:Thales. Research Themes: T3 and T5. ... View all LSSC Consortium Research ». Main menu. The University Defence Research Collaboration (UDRC) in Signal Processing is

L_WP3: Signal separation and broadband distributed beamforming | University Defence Research Collaboration (UDRC)

https://udrc.eng.ed.ac.uk/archive/phase-2/research/lssc-consortium/L_WP3-signal-separation-and-broadband-distributed-beamforming

PhD:Lead Project Partner: QinetiQ. Research Themes: T1, T2, T4, T5, T6 and T8. ... View all LSSC Consortium Research ». Main menu. The University Defence Research Collaboration (UDRC) in Signal Processing is delivered in partnership betweenandUnless

L_WP5: Low complexity algorithms and efficient implementation | University Defence Research Collaboration (UDRC)

https://udrc.eng.ed.ac.uk/archive/phase-2/research/lssc-consortium/L_WP5-low-complexity-algorithms-and-efficient-implementation

and application-specific low-cost implementations through collaborative research and active engagement with all other WPs. ... Main menu. The University Defence Research Collaboration (UDRC) in Signal Processing is delivered in partnership