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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
CGI exterior visualization: good fairy by day and wicked witch by night??? Perhaps it is just Photoshop ;)
Try to visualize a beautiful woman. Give it some seconds serious consideration. I shall wait patiently as long...
Now the woman you picture in you head, not only has form and shape, she most likely even have mannerisms and perhaps are wearing clothes. If so we can even with wisdom assume that the clothes she is wearing is consistent with, and thus reflect, the person she is and here is my point. She is to the mental effect almost a person, as your imagination is a VERY powerfull tool. - Mind you not even the Tihane-2 (The Chinese supercomputer) would be able to create in memory what you just did in seconds. (Further more, the Tihane-2 would probably answer that beauty is subjective and continue in long explanations to explain the beauty of binary simplicity, but be quite indifferent as in regard to the beauty of women.)
In your head, from the quest was launched, you started drawing upon your feminine resources of data in your eyes putting together a pretty much ”perfect” women ;o) But make no mistake, in a way she is VERY real, as she is created only and alone from YOUR subconscious imaginative spectrum of what a ”beautiful women” consist of. Those perceptions are not only VERY real, to you it is the whole world and thus, the very definition of beauty.
If you are a crossdresser, transvestite or transexual, you know very well what powers are to be drawn from within that imaginative spectrum, but make no mistake. When ordinary macho heterosexual men watch Expendables 1 (Macho hetero classic - 5 stars from my male side, Lisa says ”No comment!” shaking her head) they very much identify them self, with being amongst such group of battle scarred veterans, knowing each others weaknesses and strengths, using them in unison, like a team, working like clockwork and on backbone alone beating odds no sane person would bet a single dime on.
Women as well have their own visual identification spectrum and I stand accused making following statement without statistic documentation, but I have notion practically all women at some time, have imagined them self walking into a crowded room drawing all attention, dazzling everyone with the mere presence of their radiant beauty. But again, I might be mistaken and women not only may, but trust me will rightfully claim ”What the hell do I REALLY know about women.” and it is in fact quite true.
Never the less there is still much to be obtained from within, the almost magical imaginative spectrum.
You see, something happens to macho heterosexual men, watching not ONLY Expendables 1, but every film made in modern times that has to do with war, fighting, death, violence and murder (several times). Slowly, we find, such identification change such individuals. The same thing happens to T-girls who spend much time in the imaginative female spectrum, they change slowly, becoming more like that in reality as well, changing slowly.
Thus watching many movies on war identifying with being a vengeful warmachine, might actually in a stressfull situation, combined with a life crisis, trigger the hidden imaginative being nurtured by such imagination, making that person pick up a riffle going into warmode showing the world a thing or two. Where as a T-girl in same stressfull life crisis, very well might say ”Fuck it all.” pick up a pair of stilettos and wearing a tight skirt ”showing” (though in a more practical sense) the world a thing or two as well.
I have so many connections on LinkedIn it became almost unusable and started becoming a repository of business contacts. This visualization, though mesmerizing to me at first and to others as well, is interesting though the groups are spread around time, location, profession and education.
The top and left is more related to my design expertise, the lower right is more my personal life.
Also the edges are filled with people I barely know. Then again in the center it is often the same.
Visualizing the various features of the SwiftRiver distributed reputation and veracity functionality.
Things like Time, Location, Activeness as well as Global and Local interaction, are all considered in scoring. Time (green) and Location (dark grey) are optional, for scenarios like a conflict or war. The content producer’s location, or proximity to ‘ground zero’ tells the system to factor this in to its score. Also the length of time that content is produced after the initial event may also tell us a lot. Things like ‘time’ and ‘location’ are optional because if your Swift instance is tracking something like a political scandal, time and proximity may not actually add any value to authority calculations.
Purple represents how active Users 1 and 2 are. In and of itself how much someone uses a Swift instance is irrelevants. It could mean that they are an eager member providing valuable assistance, or it could mean they are attempting a brute force attack on the system similar to the Figure 1 scenario. However, when coupled with other factors, frequency of interaction is considered and can positively or negatively weight the score for a user.
Illustrative Visualization of a german climate change adaption research network – using processing and a metaball force field fpr moving agents
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
The Ars Electronica Futurelab made a high-profile guest appearance in Los Angeles. As part of the Walt Disney Concert Hall’s IN/SIGHT series, Esa Pekka Salonen conducted the L.A. Philharmonic Orchestra in a performance of Ravel’s “Mother Goose” that featured impressive visualizations designed by the Linz-based media art lab.
Credit: Ars Electronica Futurelab
This is a visualization of a blog community. It's one of the end results of our project. In the visualization, thicker lines suggest a stronger connection between the two blogs. If you want to know more, or play with it, hop over to www.blogslikethis.com/
Hydrogen accounts for about 74 percent of the normal matter in the Universe. This visualization shows the electron clouds of hydrogen through the probability density function when the principal quantum number, N, is 1 and 2. The probability density illustrates where the electron is most likely to be found if measured, red indicates high probability, blue indicates low probability.
Update: 2020/06/22: A 16k version is now available.
Update: 2020/07/06: A visualization showing all electron orbitals for N=1 to 6 is also available on Youtube: youtu.be/HyRHT4yOvms
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
Ascent Penthouse
Client: Mr Dung - IAM Architecture
---
@ Long Nguyen & Thu Nguyen
Architecture - Interior Design & 3D Visualization
0979 962 864, Ho Chi Minh City
advlongnguyen@gmail.com
This visualization shows the wave functions of hydrogen when the principal quantum number, N, is between 1 and 2. The wave function is the solution of the Schrödinger equation and describes the electron in its wave form. Yellow and red colors show positive, while blue and purple denote negative values. Its complex square is the probability density, which actually shows where the electron might be found in the atom when measured.
That visualization can be found here: www.flickr.com/photos/188522613@N05/49924325132/in/datepo...
Update: 2020/06/22: A 16k version is now available.
Here's a quick and dirty attempt to automatically determine arterial streets without any prior knowledge about the arterial status of a street. The idea is: a shortest path tree is taken for a bunch of random points, and the trunkyness of each branch was determined. The trunkynesses of the roads are summed, and this is the resulting map. It sort of works.
Ascent Penthouse
Client: Mr Dung - IAM Architecture
---
@ Long Nguyen & Thu Nguyen
Architecture - Interior Design & 3D Visualization
0979 962 864, Ho Chi Minh City
advlongnguyen@gmail.com
Money plays a central role to life in EVE. What does 200B ISK in damage actually look like? When I lose a Battleship, how much is that setting me back? How many Logistics ships could you buy instead of one Dreadnaught?
More details on how I collected the data, and why, in my post on this visualization.
You'll need to zoom in on this to see the details.
This image is part my new blog about EVE Online that tries to explain and document the world, with a focus on making it accessible for non-players and new players.
Visualization of ragas based on 1000+ features derived from:
- vadi and samvadi
- which notes are included
- bigram and tetragrams in the raga
- distinction of all the above features wrt aaroha vs avaroha
- distinction of all the above features wrt extended notes
- distinction of all the above features wrt second-octave notes
Raw data is available as json and csv:
github.com/kylemcdonald/ragaDB/blob/master/ragasdb/ragas....
github.com/kylemcdonald/ragaDB/blob/master/ragasdb/ragas.csv
And a script is available for generating the derived features: github.com/kylemcdonald/ragaDB/blob/master/ragasdb/make-t...
Layout and coloring was found using t-sne, with scripts in this repository github.com/kylemcdonald/EmbeddingScripts
There are more variations on the visualization above with different parameters (and varying accuracy in representing the space) here: github.com/kylemcdonald/ragaDB/tree/master/tsne
Centered on my photos page :)
This is a map of the Flickr site, where they grey circles represent URLs that end in a slash, and the blue circles are (I think) images.
Based on Sala's Web Sites As Graphs, this is a crawler that visualizes the validation profile of the pages in a Web site. As it traverses links, it also draws a clear image of the IA (the "site map"). It's hard to think of another free tool that gives this kind of immediate, visual insight into how a site is organized. Definitely not production-ready. And, of course (its a tree graph), it doesn't show all the links between pages.
June 18, 2013 - NREL Senior Scientists Ross Larsen and Travis Kemper examine a molecular model of Polymeric organic nitroxide radical (PTMA) film for battery applications using a 3D model at the Insight Collaboration Laboratory during a tour of the Energy Systems Integration Facility (ESIF) at the National Renewable Energy Laboratory (NREL) in Golden, Colorado. (Photo by Dennis Schroeder / NREL)
visualization in-progress - this is a dataset of twitter messages taken from the #140conf that jeff pulver organized in Tel Aviv last December.
Mike Moradi, Founder and Chief Executive Officer, Sensulin, USA; Young Global Leader capture during the Session: "Visualizing Disease" at the World Economic Forum - Annual Meeting of the New Champions in Dalian, People's Republic of China 2017. Copyright by World Economic Forum / Sikarin Fon Thanachaiary