Shrivelling world
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| License | CC Attribution 2.0 Belgium: You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor. | |
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Visualization (computer graphics)SpacetimeAtomic nucleusOpen setRow (database)Cartesian coordinate systemSpacetimeProjective planeGroup actionComputer animation
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Visualization (computer graphics)SpacetimeMultiplication signProjective planeInformationSpacetimeDemo (music)Computer animation
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Visualization (computer graphics)SpacetimeDistanceFingerprintDistanceResultantCoefficient of determinationObject (grammar)Video gameSpacetimeProjective planeMultiplication signComputer animation
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BitTable (information)Reflection (mathematics)Line (geometry)Computer animation
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HomothetieAsynchronous Transfer ModeRepresentation (politics)Computer networkSpring (hydrology)SoftwareBitMultiplication signWave packetString (computer science)HypothesisLevel (video gaming)Asynchronous Transfer ModeRepresentation (politics)Goodness of fitAnamorphosisPlane (geometry)Process (computing)WordArithmetic meanFrequencyTransportation theory (mathematics)Office suiteSpring (hydrology)Projective planeInformation technology consultingComputer animation
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Computer networkAsynchronous Transfer ModeWordLevel (video gaming)Line (geometry)Different (Kate Ryan album)Projective planePlane (geometry)Position operatorCone penetration testAsynchronous Transfer ModeDirection (geometry)Computer animation
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Position operatorCone penetration testConcordance (publishing)Point (geometry)BitMultiplication signDistanceMereologySoftwareLevel (video gaming)Line (geometry)Greatest elementDevice driverPower (physics)Plane (geometry)Decision theoryCAN busForcing (mathematics)Computer animation
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FingerprintReal numberProjective planeBitMachine visionTransportation theory (mathematics)Cartesian coordinate systemShooting methodComputer graphics (computer science)Torus
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SpacetimeComplex (psychology)Visualization (computer graphics)Representation (politics)FingerprintOpen sourceNeuroinformatikCartesian coordinate systemMachine visionMachine codeFreewareComputer animation
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Software developerVisualization (computer graphics)HypothesisOpen setSoftwareGame controllerBlogTransportation theory (mathematics)SpacetimeComputer animation
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Asynchronous Transfer ModeCartesian coordinate systemPosition operatorPairwise comparisonQuicksortTerm (mathematics)Set (mathematics)Computer animation
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SpacetimeForcing (mathematics)Projective planeDifferent (Kate Ryan album)Cycle (graph theory)Computer animation
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Point cloudFacebookOpen source
Transcript: English(auto-generated)
00:05
OK. Thank you. I will be speaking today about Shaving World. Sorry, third French in a row, so it should be accustomate to the accent. I will be speaking about three-dimensional
00:26
application for representing geographical time space. On behalf of Alan Rustis, who is the main researcher in this project, who can be here today, I will speak about what
00:41
is the problem with time space. I will show some examples of geographical time space representation, and I will give you some information about the project. I cannot make you a demo because it's too short in time. So what's the problem with time space? In geography, this is a geography
01:09
project, there are two major concepts, issues, where is something, where is it, and at what
01:21
is something else. But in the daily life movement, we thought about time. When I go to work, I don't say, oh, it's 15 kilometers. I say, oh, I go to work in 15 minutes. OK? So
01:40
we thought in time. So there are two concepts in this, the geographical distance, we have to go to somewhere, and the geographical time space. So how can we represent those two objects, the geographical time space and the geographical distance? So I will show you some examples,
02:03
and then I will show you a little bit of Schrodinger. We'll try to mitigate the issues. So it's an old question. This is the Schrodinger table, which is a medieval document about
02:21
a Roman iterarium. And if you saw the orange line with steps on it, it's believed that one step is one day travel by horse. So it's very old data, and with that, a merchant wants to say, OK, to go to where, to where, I have maybe many, many days of travel.
02:45
So this is actually a solution. It's not very perfect. And we have some modern reflection on it. So this is a famous Mach-L representation. It's an homotect. So the world is shrinking
03:03
when the transportation modes became faster. For example, before the industrial revolution, you go there by horse carriage or by foot, so the world was very big. The next village was already far. Nowadays, the world is very narrow. You can go to New York in a bunch
03:35
of hours. So it's a very great representation to show the acceleration of transportation
03:43
modes. But you can't compare different modes, but not in the same period. So modes can't exactly coexist. Modes, I mean, train, cars, foot, and so on, transportation modes.
04:02
And there is no representation of networks. So the networks are different on those. This one from Shimizu in the 80s used an anamorphosis and makes a cartography of it. It's from
04:21
Japan. And try to show how the Japan is shrinking with the arrival of fast train and airplanes. So it's great to show acceleration. We have from the 60s to project after the
04:42
80s. You can mix a little bit the modes, but it's not represent. So it's not easy to see if it's by train or by plane. And you can maybe thought about the networks,
05:01
but they're not really unfazed. This map was made by Tobler, who is a famous geographer. And he keeps the cities at their place, made networks in it, and tried to make strings
05:25
in the networks. So the edges are springs, sorry. So good things, networks are preserved. And represented, modes can partially coexist also, but it doesn't show acceleration. So
05:44
you are stuck in, it's a picture of one time. So the streaming mode hypothesis is to show in a 3D map, you keep all the summit of each cone is actual city. It's in a 3D
06:06
direction. And we have two travel modes. The fastest one is the red line, always the red line. It doesn't move. And we apply a ratio from the fastest to the slowest. And
06:23
the slowest is represented by the blue line. And actually, the blue cone, which is a cone, it's in 3D, so it's a cone. The blue cone summit is moving from the ratio between the fastest and the slowest. So for example, with jet planes and cars, we
06:45
have this kind of cones, but if you have supersonic planes, the cone is steeper. Because the ratio, the difference between a car going at 100 kilometers is very much bigger. So
07:05
it gives things like that. So maybe in the early 30s, you can go to London, to Berlin. This is the blue line. This is actual position of the city. This is a worldwide map. So each summit is an airport, actually. So in eight hours, maybe you can do that
07:26
distance with a propeller airplane. It's pretty much like 2,060 kilometers, London to Bucharest, if you have an airplane who is able to do an eight-hour flight.
07:43
In the 60s, we have airplanes with jet engines, so we can do a little bit farther and faster. So maybe we can still do London-Berlin, but you can do London-New York or London-Paris to New York as well, and we have a little bit more network. So we can go a little bit
08:07
in the eight-hour farther. And you can see the cones start to be a little bit shapen and steeper. In the 80s, in the last half of the last part of the 20th century,
08:29
we have the supersonic airplanes, the Concorde, and a little bit at the time the FFF, one you can watch farther. In eight hours, you can make a very big travel, but the Concorde
08:44
was only six hours autonomy. And there was only two destinations from New York. It was Paris or London, and we were warned, but that's it. So the network was very narrow at the time. So you can see the cones are very steeper and sharp. And after the end
09:12
of the commercial use of Concorde, we are back at the same point in the 60s with jet airplanes.
09:21
The autonomy is a little bit better. They can go a little bit faster, but not so much. But the airport network is much more dense. So you say, oh, you speak about acceleration. If you combine things, you can make an acceleration. So we have the same
09:47
vision like Mach-Air, and we have something like Sabie. And you see that it's acceleration, the transportation modes can accelerate, but
10:05
they now get slower. So this is the capabilities and the main goal of the Shriving World project. I will be talking a little bit more of this project.
10:20
Okay, this means to represent a complexity. It's for research application. There is no practical use, but it tackles things from cartography, computer graphics, and scientific vision. It's free open-source software, mostly in JavaScript. You can find the code on GitHub
10:47
and find the research blog on time-space.epotespot.org. And we have a small team,
11:00
feel free to join. And if you have any questions, I'm here for you. Thank you. Have you used this into comparing sub-modes, transportations between cities,
11:26
and walkability indexes? Actually, no. So you asked me if we used it for slow modes actually in cities. Yeah, actually, no.
11:41
The only application we use it, the only data set we use are airport's position and comparison between flight mode and terrestrial transportation modes. Maybe you can do that, but you need the data for that. In terms of city planning, sometimes we want to see,
12:09
can we create more spaces for certain sub-modes, cycling and others? And so what is the difference which could make it? Maybe this project could help visualizing this.
12:23
Yeah, maybe it can be helpful for city planning, but we don't have any data set, and it's not subjective. But maybe you can contact us and try to work with us. It might be interesting. Yeah. Thank you. Thank you very much.