Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature • Hacker News Board

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#101

Post by Angostura » Thu, Oct 18, 2018, 1:14 PM UTC

dleslie wrote: post #49

strainer wrote: post #33

""" """ "" ^v^ "" "" ^v^ "" "" ^v^ "" ... low pressure """...""" held by vortex ######### ### dandelion falling """"""""" """ rising air I wonder about the chances of creating this kind of toroidal vortex above a duct for lift. It seems necessary for the air to pass in the same direction as the lift, yet lift is normally created by throwing air in the opposite direction.

Excuse me, I'm going to go launch SyncTerm now and browse some Mystic and SynchroNet boards.

I'm going to dig through the alt.fan.warlord archives

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#102

Post by taneq » Thu, Oct 18, 2018, 1:20 PM UTC

mclehman wrote: post #72

taneq wrote: post #46

Earlier quoted context omitted.

Also: > When some animals, aeroplanes or seeds fly, rings of circulating air called vortices form in contact with their wings or wing-like surfaces. > Researchers thought that an unattached vortex would be too unstable to persist in nature. I guess those animals and seeds aren't natural then?

Aren't those two sections contrasting "in contact" with "unattached"?

Huh, looks like I misread that bit. Good catch!

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#103

Post by [deleted] » Thu, Oct 18, 2018, 2:17 PM UTC

TeMPOraL wrote: post #91

nl wrote: post #70

Earlier quoted context omitted.

That would 100% be possible with image recognition. Segment using UNet, then measure the remaining joined pixels. (Well thanks for the downvotes. I do this as my job, so I guess I'm doing the impossible or something)

Hm. Are NNs reliable enough to be sure you're getting a correct result? I'd imagine this kind of task would lend itself to some old-school image recognition techniques - photograph against uniform background, threshold, mask the middle part and count contiguous regions.

[deleted]

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#104

Post by kbenson » Thu, Oct 18, 2018, 3:39 PM UTC

nl wrote: post #70

seandavidfisher wrote: post #67

> Previous studies have found that dandelion seeds always have between 90 and 110 bristles, says Nakayama Those poor research assistants. Imagine counting hundreds of dandelion bristles every day. Probably still not possible with AI/image recognition either.

That would 100% be possible with image recognition. Segment using UNet, then measure the remaining joined pixels. (Well thanks for the downvotes. I do this as my job, so I guess I'm doing the impossible or something)

I think the real question is, which is more cost/time efficient:

a) Hire someone or a company skilled enough to whip up some classifier that can count these from some accuracy, level, which entails paying a developer, and probably 5-10 graduate students to sit around and count dandelion bristles on a good number of dandelion seeds to create a training set.

or

b) Just have 5-10 graduate students sit around and count dandelion bristles on a good number of dandelion seeds

Given that a is a super set of b, and the extra portions of a are likely much more expensive than all of b, I think the answer is fairly clear...

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#105

Post by jayd16 » Thu, Oct 18, 2018, 3:50 PM UTC

seandavidfisher wrote: post #67

> Previous studies have found that dandelion seeds always have between 90 and 110 bristles, says Nakayama Those poor research assistants. Imagine counting hundreds of dandelion bristles every day. Probably still not possible with AI/image recognition either.

The bristles seem long enough. You could cut them, separate them, take a well contrasted photo, repeat. The image recognition task would be pretty easy at that point I think as you're just counting separated bristles.

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#106

Post by dj-wonk » Thu, Oct 18, 2018, 4:11 PM UTC

btrettel wrote: post #66

dj-wonk wrote: post #56

Earlier quoted context omitted.

Please clarify what you mean by ‘accurately’ ... without reducing this discussion to a coarse dichotomy between ‘accurate’ or ‘not accurate’ —- which would miss a main point of what models do and why they are useful. My very rough understanding is that computer simulations of air flow are sufficently accurate for a high percentage of predictions for many kinds of objects. Fair? If not, under what cases does their acc…

Fluid dynamicist here. Short version: Scale models (like wind tunnels) are useful because the most accurate simulations are extremely computationally expensive or computationally intractable, and the faster less accurate simulations are often so inaccurate that they are untrustworthy. Scale models are not 100% trustworthy themselves, and to construct and use them you need to understand similarity theory. Long version…

Wow, thanks for your well-written response. I didn't quite follow all the details; in any case, I have a slightly better idea of what is going on. Next, I look forward to learning a bit more about laminar versus turbulent flow.

I can relate to your comment: "Some people lately have proposed that machine learning could construct a particularly accurate turbulence model, but that seems unlikely to me". A healthy skepticism is important. Different inductive biases in various machine learning algorithms will have a significant effect here, I'd expect.

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#107

Post by creep » Thu, Oct 18, 2018, 4:35 PM UTC

onion2k wrote: post #71

creep wrote: post #62

Earlier quoted context omitted.

I don't think worship is an "animistic" quality. I think the tendency to worship is very much a refined trait in highly intelligent organisms.

You're right in the sense that ritualised, repeated behaviour performed for no obvious gain is something very unusual. Most animals don't waste energy on things that don't have a material impact on their life. I'd disagree with your point about intelligence though. It's simply that we have more resources than we need. Even the stupidest animals would develop rituals if they could afford to.

You can't say that ritual and worship doesn't have material impact. You have no way to prove or disprove that.

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#108

Post by sova » Thu, Oct 18, 2018, 5:24 PM UTC

anigbrowl wrote: post #22

sova wrote: post #16

Does anybody have a link to a video of the lasers creating small vortices just above the dandelion surface?

Click through to the paper and you can view the figures and supplementary information for free. Protip: while it's frustrating to find a paywalled paper if you just want to know how it works the supplementary materials are usually unrestricted, better written, and easier to understand than the paper itself.

Thanks ! That is a good pro tip. Did not think about supplemental papers and resources.

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#109

Post by dang » Thu, Oct 18, 2018, 6:38 PM UTC

hasahmed wrote: post #93

im3w1l wrote: post #64

If you find this interesting I highly recommend you to look at some vape-trick videos. Smoke/steam is great at visualizing vortices, and it's absolutely astonishing how much aerodynamically control some people can achieve. Creating lots of small vortices in rapid succession, merging vortices, splitting vortices, letting vortices "suck in" other vortices. https://www.youtube.com/watch?v=Tmv228G8R4o&time_continue=1m

I feel like I could have enjoyed that if those dudes weren't such giant fuck boys

Please don't do this here.

Re: Dandelion Seeds Fly Using ‘Impossible’ Method Never Before Seen in Nature

#110

Post by btrettel » Thu, Oct 18, 2018, 7:59 PM UTC

dj-wonk wrote: post #106

btrettel wrote: post #66

Earlier quoted context omitted.

Fluid dynamicist here. Short version: Scale models (like wind tunnels) are useful because the most accurate simulations are extremely computationally expensive or computationally intractable, and the faster less accurate simulations are often so inaccurate that they are untrustworthy. Scale models are not 100% trustworthy themselves, and to construct and use them you need to understand similarity theory. Long version…

Wow, thanks for your well-written response. I didn't quite follow all the details; in any case, I have a slightly better idea of what is going on. Next, I look forward to learning a bit more about laminar versus turbulent flow. I can relate to your comment: "Some people lately have proposed that machine learning could construct a particularly accurate turbulence model, but that seems unlikely to me". A healthy skepti…

Glad to help.

Here's some additional comments you or some other reader might find useful:

Dimensional homogeneity is the most important constraint I think most machine learning folks would miss. It's not really an "inductive bias", rather something which everyone agrees models need to satisfy, so it should be baked in from the start. This is trivial to meet, actually; just make sure all of the variables are dimensionless and it's automatically satisfied. (Depending on the larger model, you might have to convert back to physical variables.)

https://en.wikipedia.org/wiki/Dimensional_analysis#Dimension...

In terms of "inductive biases", I'm not certain what that would entail in terms of turbulence, but I'll think about it. Might be something to figure out empirically.

Turbulence models which satisfy certain physical constraints are called "realizable". Some of these constraints are seemingly trivial, but not necessarily satisfied, like requiring that a standard deviation be greater than zero. (Yes, some turbulence models might get that wrong!) The "Lumley triangle" is a more advanced example of a physical constraint that a (RANS) model needs to satisfy that often is not satisfied.

I'd be interested in applying machine learning type methods (combined with the model order reduction approaches to include information from the Navier-Stokes equations), but I'm not knowledgeable about them. My impression is that most people applying machine learning to turbulence are novices at machine learning. And I imagine most machine learning people applying machine learning to turbulence are novices in turbulence and wouldn't know much anything about the realizability constraints I mentioned.

Another issue worth mentioning is experimental design. I think the volume of data needed to make a truly good turbulence model is probably several orders of magnitude higher than anything done today for turbulence. Experimental design could make this more efficient. I don't think most machine learning people worry much about this. They seem to focus on problems which can be run many times without much trouble. Acquiring data for turbulence is slow and hard, so it's outside their typical experience.