GSSS 2019-Projects & Working Groups: Difference between revisions
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==POSSIBLE PROJECT TOPICS== | ==POSSIBLE PROJECT TOPICS== | ||
# Numbered list item Seen a city as a network graph, correlations of components (descriptors) as weight connections. Low flow components may appear as cluster patterns in the graph, fast flow components should have a high degree of connection. | # Numbered list item Seen a city as a network graph, correlations of components (descriptors) as weight connections. Low flow components may appear as cluster patterns in the graph, fast flow components should have a high degree of connection. | ||
# Numbered list item How effective are Civic behaviour characterization using small data. In order of doing these we have to measure quality of data (using some of the common dimensions). A diagrammatic framework could be formulated to understand in a common basis small data set. | |||
How effective are Civic behaviour characterization using small data. In order of doing these we have to measure quality of data (using some of the common dimensions). A diagrammatic framework could be formulated to understand in a common basis small data set. | |||
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[[Media:SFI GSSS Protect Themes.xlsx | GSSS Project Themes from Slack Posts]] | [[Media:SFI GSSS Protect Themes.xlsx | GSSS Project Themes from Slack Posts]] | ||
Revision as of 16:21, 16 July 2019
| GSSS 2019 |
POSSIBLE PROJECT TOPICS
- Numbered list item Seen a city as a network graph, correlations of components (descriptors) as weight connections. Low flow components may appear as cluster patterns in the graph, fast flow components should have a high degree of connection.
- Numbered list item How effective are Civic behaviour characterization using small data. In order of doing these we have to measure quality of data (using some of the common dimensions). A diagrammatic framework could be formulated to understand in a common basis small data set.
GSSS Project Themes from Slack Posts
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