Newsgroups: alt.ufo.reports
From: MrPostingRobot@kymhorsell.com
Subject: sector 21 (1/n)

[uploaded 4 times; last 08/09/2024]

Another update on the analysis of TESS telescope images.

The programs I'm using are starting to become moderately complicated.
The latest effort involves building a model that will combine the
efforts of all the major components I've put together over the past
few years. The backbone of the original effort was an AI-based
software originally used to look at climate data. It managed to pick
out -- a couple years before others published the same result -- that
certain regions of the world (the Congo and Amazon) had flipped from
net carbon storage to carbon emitters. That program involved some
fairly standard stats packages with a general problem solving front
end that decided what needed to be analysed and then used the results
of one or more trial runs to decide what data to look at next and how
to analyse it.

That software has now been fleshed out a lot more, with many bits and
pieces I've used in other "data science" type projects over the past
few years as well as some new ideas from a current growth area in AI
-- "automated science". A mental model is a robot that uses its
experience to decide what to study and how to go about forming
hypotheses, testing them, combining them into theories and justifying
what it thinks it's learned about the world.

This stuff has now been expanded to include various models I've
developed to analyse different aspects of UFO behaviour.  I have a
model that tries to track UFO flights around planet earth --
particularly across the Pacific and near the poles in key regions of
the world.  Another model tries to predict UFO behaviour from the
movements of key groups of asteroids, planets and comets to find a set
of asteroids and flight characteristics that can predict when an UFO
that may be moving around "out there" in the solar system will decide
to take a trip to earth and match up with sightings as e.g. reported
to the NUFORC.

And now I've added in another major model that looks at sequences of
telescope images and tries to detect sometimes very small objects down
at the pixel size moving in a consistent way across a sequence of
usually hourly telescope images.

The combined software can use information of past sightings to predict
fairly well when other "visitors" may be inclined to come our way,
where in the sky they may appear during their journey from there to
here, and where on the planet they may park the truck for subsequent
day-trips until they decide to leave.

And in coming posts we'll look at the results of the first significant
end-to-end run of the program including the final stage of looking at
the telescope images to see what there is to see in the part of the
sky at the specified time the relevant objects were expected to appear there.

The program used historical hour by hour data from 2020 to determine
what set of "hang out" asteroids may have been involved, how fast the
objects would have to move when they decided to depart from one of
those asteroids to travel to earth, where in the sky they would appear
to be during their trip, and what part of the relevant telescope
record we need to look at to see them.

With several years of experience no big surprise the AI's seem to have
found something.

Part of the deal in the past few months has been the experimental part
of the software developing a "pipeline" -- essentially a sequence of
operations to apply to a sequence of images -- that best brings up the
features they are hoping to find. The big problem in the past has been
finding things the human eye can actually see. Computers are great at
playing with numbers and testing statistical hypotheses, but
understanding in some way what it is people are convinced by as visual
evidence has been a bit of a problem. Essentially the AI's have to
build a model of human visual perception and decide whether an image
sequence they prepare with their pipeline will knock its socks off
rather than appearing to be noise.

At an early stage of this work the programs I was using then had
managed to present movies of parts of the sky they deduced would have
something interesting to see using averaged light curves of regions of
the sky.  The movies posted at my web-site at the time showed some
interesting things -- I liken some to "ant farms" -- with bright and
dark dots moving around some part of the sky seemingly at random. It
looked like ants foraging around but despite the various stats saying
it was interesting it was hard to see if the software was finding
something real or just filtering out some noise that just seemed to be
something real.

But by combining the image processing with the predictions from what I
have called the "nav model" should put that worry to rest.  The nav
model finds which asteroids and flight parameters predict the arrival
of certain objects over the skies of mostly N America.  The model is
validated using standard data science methods -- 1/2 the data is used
to tune up the model, then that model is run against the other 1/2 of
the data to ensure it predicts it rather than simply has memorised the
first 1/2 of the data.

That program can be used to find the position in the sky the relevant
objects should be visible in on their journey to Planet Dirt (in a
past post we looked at things moving around a well-known region of the
sky that were predicted to be there from UFO sightings reported in
Florida), then it locates some appropriate telescope images and
creates a pipeline that finds features that people should find
convincing, and determines whether in fact those images contain those
convincing features.

It's still not a lock on "proving" anything, but it certainly
encourages me to fiddle some more with the approach. :)

With the prospect of large chunks of movies showing things moving as
they were predicted to move at the times they were predicted to show
up, I've started re-organising the <kym.massbus.org/TESS/SECTORS>
directories.  Each sub-directory sNNN -- where NNN currently goes from
1 to 77 -- will eventually contain some images and series of short
movies.  Most sectors already show where in the sky the telescope
images were taken, some detailed pix of how the telescope lined up in
that part of the sky (because with a line of 4 cameras containing a
2x2 grid of ccds where each ccd is pointing is a non-trivial thing :)
and some images showing what is normally seen in that part of the sky,
and maybe a few images showing planets, asteroids and comets that may
have been seen by the telescope in that part of the sky in the past
10+ years.

Plus, of course, a few movies run through the AI's image pipeline
showing bright and dark dots moving around that somehow were predicted
by the movement of relevant asteroids &ct and line up statistically
close to NUFORC UFO reports dated usually 5-40 hours after the dates
on the images. It seems at this point we can "see them coming" up to
40 hours out. And also apparently see some departing again on average
around 20 hours after the UFO sighting.

--
Welcome to the very first official UFO hearing in American history
It's a historic day for everybody who has always wondered if we are alone in
the universe. Although there have already been multiple hearings on UFOs or
UAPs, this is the first hearing in which credible witnesses will testify
under oath in front of Congress. All representatives already offered their
initial remarks and gave all three witnesses the chance to make their oath
before the hearing starts. These witnesses are former Commander David Fravor,
former fighter jet operator Ryan Graves, and former Intelligence Official
David Grusch.
-- Marca.com, Wed Jul 26 10:48:24 EDT 2023

There is something there -- measurable light, multiple instruments -- and
yet it seems to move in directions inconsistent with what we know of physics
or science more broadly. And that, to me, poses questions of tremendous
interest, as well as potential national security significance.
-- Rep. Adam Schiff, D-Calif., 2022 House Intelligence Committee hearing
   on UAPs.

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