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Viva apartments visualizations created for Adele Bates' interior design project in Brighton.
Software used: 3ds Max, Corona and Photoshop
JSMath is a JavaScript library that allows the display of complex mathematical expressions. LaTeX is a popular mathematical typesetting tool. Sage is compatible with both of them.
Maps of racial and ethnic divisions in US cities, inspired by Bill Rankin's map of Chicago, updated for Census 2010.
Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Yellow is Other, and each dot is 25 residents.
Data from Census 2010. Base map © OpenStreetMap, CC-BY-SA
I was astounded by Bill Rankin's map of Chicago's racial and ethnic divides and wanted to see what other cities looked like mapped the same way. To match his map, Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Gray is Other, and each dot is 25 people. Data from Census 2000. Base map © OpenStreetMap, CC-BY-SA
I was astounded by Bill Rankin's map of Chicago's racial and ethnic divides and wanted to see what other cities looked like mapped the same way. To match his map, Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Gray is Other, and each dot is 25 people. Data from Census 2000. Base map © OpenStreetMap, CC-BY-SA
Patrick van der Pijl: On January 4th 2011 Alex Osterwalder reinversed the business model of Facebook. On his blog he reconstructed together with his smart and loyal followers the model of Facebook. We thought it would be great to build on the work that has been done by visualizing this business model. More on www.businessmodelsinc.com - Illustration: Joeri Lefevre
I can't see
I can't walk alone
I lack some physical skills
But, I won't knee to blindess
I won't be completely depedent on the others
I won't stay without any work
I have the heart to visualize the feelings
I have the mind to comprehend the life
I have the soul to be a free human
[Abraaj. January 2007]
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Series of Kuwait's portraits (winter 06-2007)
I saw this blind old man at Al-Mubarakiah Market in Kuwait City
Canon EF 70-200mm f/2.8L
editing: RAW processing and Photoshop editing
I was astounded by Bill Rankin's map of Chicago's racial and ethnic divides and wanted to see what other cities looked like mapped the same way. To match his map, Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Gray is Other, and each dot is 25 people. Data from Census 2000. Base map © OpenStreetMap, CC-BY-SA
Freestyle. Center is a pysanky design found in Zenon Elyjiw's Sixty Score of Easter Eggs: A Comprehensive Album of Ukrainian Easter Eggs. Love that book. Around the egg are my doodles, which turned out to look vaguely pea-pod-ish. This piece is completely covered with stitches and is roughly the size of the palm of my hand.
CGI exterior visualization: good fairy by day and wicked witch by night??? Perhaps it is just Photoshop ;)
I was astounded by Bill Rankin's map of Chicago's racial and ethnic divides and wanted to see what other cities looked like mapped the same way. To match his map, Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Gray is Other, and each dot is 25 people. Data from Census 2000. Base map © OpenStreetMap, CC-BY-SA
I just started an excellent online class via Coursera titled Exploring Neural Data Exploring Neural Data that started 29 September 2014. Monica Linden and David Sheinberg of Brown University are teaching this class. Our first assignment was to detect spikes (action potentials) in a few seconds of recorded data from a neuron. The assignment was to modify some Python code to plot the data, and then detect and plot the spike activity, and plot all the detected spikes. This plot shows voltage versus time, there are about 88,000 samples in this data. To figure out the "spikes", a threshold is applied (in voltage and time) to separate the spike from the noise. The red lines were drawn for every spike detected.
It was very satisfying to work with this data, and to learn a bit more about neuroscience (and Python). We are using the Spyder environment, which is quite a nice development environment. This assignment took me a little longer than I thought it would (finished about 530 am Sunday morning).
www.luzinterruptus.com/ is a Spanish collective of artists specialized in Interventions. This time they draw attention to public urinating. By installing “public toilets” in places they chose by their noses, easy to find places where the smell tells, they hope to remind people to abstain from this anti social behavior.
Probably inappropriately used from:
Visualisation of emails received in a subfolder using the Java based Processing toolkit.
The long lines separate years, each row is a separate email address, the length of the green is the size of the email.
Email data exported from Outlook into Access then filtered into text doc for reading by Processing. Contact me if you want the script.
If you look deep in to the image, you can visualize alot of funny stuff from this image...give it a try! :)
What you see from distance in the image is a sand bank with small trees which is eventually going to be an island.
Paper at www.stat.columbia.edu/~gelman/research/published/signif4.pdf (PDF)
Let's say that a country, Lagutrop, wants to increase its PISA results and, before deciding on policy, the decision-makers want to know what works by running experiments or studies of intervention effectiveness. These studies compare two variables with similar intervention scales, say expenditure in computer-assisted learning (U) and expenditure in teacher selection and incentive systems (V).
In Study 1, data is collected measuring the effect of U and V (possibly with a lot of covariates). The parameter estimates for the effect of U and V are given by the two bell-curve-like curves on the left above.
Conclusion (as is traditionally presented): Lagutrop should invest in teacher selection and incentive systems, since computer-aided education has no significant effect.
Gelman and Stern problem 1: but the difference between the effects is itself non-significant! If significance is the criterion for disposing of U, then it should also be explained to the decision-makers that significance cannot be used to separate U from V. Specifically, policy-makers in Lagutrop should be told that the rejection of computer-aided education is based on a criterion that also suggests that computer-based education is as effective as teacher recruitment and incentives.
Meanwhile, another group of researchers run a single-variable study (Study 2) considering only the effects of spending money on teachers (in Lagutrop this study would probably have been done by teachers :-).
The results of Study 2 are then presented as supporting the conclusions of Study one, phrased as "Expenditure on teachers shows a significant effect on PISA scores in both studies."
Gelman and Stern problem 2: Studies 1 and 2 predict very different effect sizes for variable V; why the discrepancy? How can two parameter estimates that are significantly different from each other be considered corroboration?
My own take on this problem 2 is the following: suppose the policy-makers in Lagutrop have to decide how much to allocate to this PISA-improvement project, out of a budget that includes other considerations (national defense, jobs for the families and friends of the politicians, police, fire-fighters, etc.). Budgeting will require forecasting. Which of the parameter estimates for effect size will they use to build a forecasting model? Since the two estimates are significantly different, any attempt at aggregation would violate the basic meaning of that significance.
That's what we engineers call a serious execution problem.
(Reblogged at my personal blog.)
"In the beginning, there was Cal."
Recommended background music: serious, or silly.
A visualization of commits to the flickr.com codebase. Colors represent different types of file extensions: .txt templates, .gne (PHP) files, JS, images, CSS and so on.
One day is one frame, and the video was created at 60 fps - then sped up somewhat to make the 3-minute video limit.
This video does not include commits to the new node.js codebase, which drives things like photo books and the new photo page. Someone else needs to make a video of that one at some point.
Someone else should re-do this in the future, and make a note to scale up all the font sizes, circle radii and so on. I didn't have time to do a third rendering. ;)
The last four years of my data from Facebook: gadgetwise.blogs.nytimes.com/2010/10/06/facebook-now-lets...
Visualized with GrandPerspective: grandperspectiv.sourceforge.net/
Maps of racial and ethnic divisions in US cities, inspired by Bill Rankin's map of Chicago, updated for Census 2010.
Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Yellow is Other, and each dot is 25 residents.
Data from Census 2010. Base map © OpenStreetMap, CC-BY-SA
Maps of racial and ethnic divisions in US cities, inspired by Bill Rankin's map of Chicago, updated for Census 2010.
Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Yellow is Other, and each dot is 25 residents.
Data from Census 2010. Base map © OpenStreetMap, CC-BY-SA
Part of a 5 house visualization project for ARCHIPOD.
Furniture models in this image are part of the model supplied in the latest 3dallusions - Charette#15 - Quinta House
I was astounded by Bill Rankin's map of Chicago's racial and ethnic divides and wanted to see what other cities looked like mapped the same way. To match his map, Red is White, Blue is Black, Green is Asian, Orange is Hispanic, Gray is Other, and each dot is 25 people. Data from Census 2000. Base map © OpenStreetMap, CC-BY-SA