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Space Launches and Deterrents

SpaceX has recently purchased their new floating oil rigs to transform them it into offshore spaceport. One of the potential drawbacks, that people might miss, is impact of sound waves during the rocket launches on marine life. Enormous levels of noise during spacecraft launch are typically up to 180db. Remind you that noise levels in our daily life are about 30db (whispering) to 110db (disco close to a speaker). Levels above 150db are physically harming organic tissues, while 180db is x1000 higher power due to logarithmic scaling. Speed of sound propagation in water is about 3 times higher than in the air (~1,480 vs 343 meters per second). All this means that space launches are not only going to stress and harm animal habitat but expected to be lethal for underwater life over a wide area. Obviously this is not as close as underwater nuke explosions that were banned at 1963, but considering the persistence of events and times that we live in, something must be done here…

Proposal is use of Acoustic Fish Deterrents to withdraw as much marine life as possible from the location and time of launch. There are two main types of acoustic waves used as deterrents – continuous and pulsed. Based on studies, pulsed sound waves are not very much efficient for use for fish withdrawal, but continuous wave can be used for this cause. The signal should start at the location and according to the rocket launch schedule with growing amplitude and act effectively as a moving wall, distancing and saving the marine life.


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COVID-19 (Coronavirus) post-incubation

[October’20 update at the bottom. Hint – really good prediction so far: Israel Covid Dead[+14days] = 0.82% of Confirmed (rsq = 0.9236)].

Those days, when you have to stay (and work from) home, you realize how interconnected our world is – because someone in China distant province eaten something bad, you and all around you (regardless where you are from) stay at home with all kids for weeks or months, gather food, cancel flights, loose savings… in best case, or life in worst. How can we say after all, that this is not a unified world we are leaving in. Enough philosophy – let’s get to the data.

There is an ambiguity about incubation period of COVID-19 and it is defined between 2 and 24 days. Definition of incubation period is “the time elapsed between exposure… and when symptoms and signs are first apparent“. There is however another important index – the duration of disease. Based on the data we can get the duration after exposure till critical period. Assuming “Total Cases” index is captured (on daily basis) after incubation period in most cases and after latent period (the time from infection to infectiousness) in some, we can run correlation between the “Total Cases” [from here: TC] signal and to “Total Dead” [from here: TD] index signal, capturing Rsq while changing time shift between them. The peak of Rsq would expose the Time-to-critical-point of the disease.

Dataset source: Johns Hopkins University Center for Systems Science and Engineering (GitHub; HDX) captured at 16/3/20

Since China has changed on the way the metrics, therefore the dependency between the TC and DC got duality in behavior as we will see, so I have split the data for analysis.

Here is correlation coefficient between TC[day] and DC[day-i] and how correlation looks at peak for all the world except China:

Total Death [after 12 days] ~ 0.248*Total Cases
Total Death [after 6 days] ~ 0.09*Total cases
Total Death [after 0 days] ~ 0.03*Total cases

You can see that as we go towards peak of death index at 12 days after incubation among captured cases, the multiplier becomes scary-high – almost quarter. Really hope that is not the case and just a transitional distortion…

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Fractals and neural adaptation

For my followers, sorry for a delay – I was overloaded by exciting projects at work (Intel Electronics), but recently got some time to get back to my hobby of modeling and concepts, so more posts to come soon ūüôā

Meanwhile here is a small visual cortex experiment you can do to experience the neural adaptation in a cool way.

For those that are not familiar with the term, this is actually a set of adjustments of neural system to stimuli. The effect is, that once stimuli is removed, the adjustment continues for some time.

There is a lot of info in the web about various effects of visual neural adaptation, like image inversion that we all experience in our childhood, afterimage effect when you continue to see the light object after you close the eyes or motion effect during which the objects continue to move after they actually stop.

The subset effect of the latter I would like to show you here is radial visual adaptation. Have not seen works/material on this particular way, so here it comes ūüôā

Attention! Can cause headache and nausea. Not for those that suffer from neural disorders, especially epilepsy!

Experiment: take a look at fractals zoom (e.g. Manderblot set or any other fractal long zoom animation) for couple minutes and then (if you succeed to move your gaze from this beauty) take a look at static screen/picture. You will see that it continues to “squeeze”. The reason for that is visual neural adaptation to radial motion of the fractal zoom, so our cortex is trying to proceed with the same visual transformation on static picture.

You can play with time of exposure to the zooming stimuli and see that there is a non-linear saturating dependency on duration of after-effect. Interesting to do some mass experiment and see wither the tau of saturation varies a lot cross population.

You can also play with the speed (in youtube – right bottom side settings) and experience non-linear correlation to speed. The after-effect magnitude is accelerating with increased stimuli speed, but if it is too fast, then there is a reduction in impact for given exposure time.

You can play with reverse speed (“zoom out”) of the stimuli and experience opposite effect of “expansion” of static picture.

Leave a comment if you have found any other interesting effects and enjoyed the infinite beauty of fractals.

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Language-driven opportunities – Internet

Merging W3Techs and InternetWorldStats numbers for 2019 Language content dominance and users statistics together, easy to see that there is a lot of potential for Arabic, Spanish and especially Chinese languages content development.

Internet content vs users by panguageOther languages are a long tail of sub-2% users and content availability. Very stable Lingual users breakdown with strong dominance of English (changing from 58% to 55% over almost the last decade).

Salable and convenient language transformation tools and methods could close the shown gaps and leverage potential for the barely English-speaking countries.

Even though Wikipedia is also dominant by English articles, the distribution of languages there is slightly less polarized.

Internet content vs Wiki by languageHere you can see that Swedish articles got outstanding 7.3% [2019] share  for very small amount of users, generated by automatic translation bot, developed by Sverker Johansson, that received a lot of criticism, thanks to poor translation abilities of Google Translate. Something to think about…

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Touch 5 control

Nice implementation of Microsoft Surface Studio had two main innovations at least from external visual perspective. One is the Hinge, which put a focus on a mechanical part, that from TRIZ theory and its laws of system evolution was “screaming” to be a next part to evolve. I put several times this system component at the frontier of next changes. The law is that every system is evolving heterogeneously, so¬†you can take a look at old legacy components to¬†bring a next breakthrough.

Another component that has been added is a Surface Dial. Nice idea to increase the control ability and improve interaction design.¬†While, what MSFT¬†did, is good from margin aspect (addition to a BOM/sales), from system evolution perspective they have added another component to the super-system. It makes new functionalities, but adding complexity. Thinking TRIZ, you can tell that the next phase would be “trimming” by “changing dimension”. For example you can remove this component by determining the touch of 5 fingers altogether to call for the same functionality. Something like this:


To make the interaction design of the feature more convenient I would add the functionality of next action once the “Touch 5” is triggered. It can be a single finger left to rotate the wheel or finger taps to choose the next action.

Makes sense?

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YouTube Identity sharing


From time to time I realize,¬†that I am logged out of Google account and then interesting thing are happening¬†– I’ve¬†got¬†totally different response at¬†all Google services. This is exceptionally visible when I go to YouTube, where I discover¬†a whole new world of content.

Similar¬†thing is obviously happening when my wife is logged in. Then , the content is very predictable, as I know her, and¬†I realize how much predictable for myself my own content is. This over-fitting from time to time is driving¬†me to go out and spend time in trying to¬†dig some new type of content, but over and over again I understand how¬†hard is to expend the boundaries of personality… Eventually I come to a similar content, which is a part of my “YouTube identity”. And no – Google are not doing good enough job to expend boundaries of my identity, even though they know exactly how it looks like (maybe because they do not want to).

This “YouTube identity” is a YouTube-dimension of myself and¬†the simplistic representation of the world as I see it, while¬†to understand someone better, I would want to¬†look at¬†the world through his/her eyes (at least virtual ones).

So I thought – can we do something to share this insight into “YouTube identity” of ourselves, like if someone would login to my Google account without impacting it. That would be totally different from sharing a particular video – something I want to share and not something I am.

Something that is less visible, but much more impacting on a global scale, is Google searches and social pages. The impact of the¬†algorithm of content fitting is causing clustering of similar people¬†and growing informational walls around ourselves. That negative feedback is driving us away from intrinsic diversity and global stability to the word of narrow-mindedness¬†and global extremism. That is another topic for discussion¬†and there is a lot of data out there¬†that supports it…

Can we get to a better understanding of each other by sharing our virtual identities and swapping to other points of view? I think it would make our development more efficient and at same time the world more stable.

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Skills network

Anything related can be a network. Any network got a hidden magic inside. Building a network is unleashing another part of the beauty of this world. And when you do this, when you find the secret clusters, when you connect the lonely entities of existence Рthen this magic is flowing though this network, enlightening and reviving nodes, breaking out over the invisible strings into the life, connecting everything and everyone.

Our skills are shaped by the templates of education and jobs, by human behaviors and to get a glimpse of this bias we can do a simple experiment.

Let’s build s crawler that is getting LinkedIn skills from many people, connect those skills based on cross-correlation and build a network that is based on highly correlated skills.

Even small amount of people I took (about 150), is giving a network of over 400 correlated skills, connected by 3500 links and lots of interesting insights.


So…¬†Mainly pics and less words.

Parts of the network, related to declared programming language-based networks (per language). Pay attention on differences:languages

Design (Since this is a small network, it is biased by my occupation, so the design is mainly represented by word of semiconductors – doing it widely would expose other meanings of design):

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