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www.si.umich.edu/about-SI/news-detail.htm?NewsItemID=623
Notes
Discovering Salience in Textual Elements Using Graph Mutual Reinforcement → Ahmed Hassan → Ahmed came up with an elegant idea: sentences that provide the best summary of a piece of text have important words. And important words are those that are contained in important sentences. Sounds like a job for the HITS algorithm, and Ahmed takes it for a spin.
Tiger is full of hidden little apps that could make life easier (as well as getting rid of iPhoto completely, to make life harder).
The graphing program looks pretty hardcore.
MDsuite.EMR provides flexible graphing capabilities. For any patient that has data, you can graph the following:
- Vital Signs
- Lab Results
- Growth Charts
- Custom Watch Lists
Within the above categories you can even be more specific as to which vitals you want to see on the graph. Is there a common set of Vitals you want to see graphed? Or a standard set of Labs and Vitals that relate to each other? You can save Custom Watch Lists so they can easily be selected and graphed the next time you are accessing that patient or any other patient.
Contact Data Strategies, Inc. for more information at 800-875-0480 or Email Us
Someone call Edward Tufte, this is the single worst graph ever. Neither the X or Y axis have any meaning whatsoever.
From:
images.creative.com/iss/images/inline/products/xmod/fe_an...
There's a cluster with very low turnout (<43%) and a yes vote at or just above the national average. These were electorates that (from memory) have a history of low engagement with the electoral process in general: Maori seats, Mangere, Manukau East and Manurewa.
Then it suddenly jumps to a high yes vote, followed by a strong decline as the turnout increases. Might this indicate that the "no" vote was focussed and single-minded, whereas those who wanted to keep the current law were divided between voting "yes" and abstaining on principle? Discussions on Public Address System prior to the referendum would seem to indicate that.