Newsgroups: alt.ufo.reports,alt.paranet.ufo
From: kymhorsell@gmail.com
Subject: Amooamooa revisited

[uploaded 8 times; last 26/10/2024]

I watched an ep of a repeat of Craig Charles' "UFO Conspiracy" a few
days ago. It reviewed the flyby from the "first interstellar asteroid"
designated 2017 U1 aka 'Oumuamua "first messenger from afar".

The usual run-through of the basic facts and some interviews from
various experts incl Avi Loeb. Some of the experts underlined the
object was strange and accelerated via means unknown after its close
approach with the sun in 2018.

But like all these kinds of programs nothing was decided. Like the
rest of the UFO background that emphasises study of individual cases
and going through all the juicy details, it ended up "proving" not
very much -- even to Charles, a "UFO believer".

We've looked at 2017 U1 before.  We found that various UFO activity
seemed to have a beyond-chance imprint of the movement of Amooamooa
around the solar system. My conclusion then was that it seemed
unlikely the object was a card-carrying interstellar spaceship -- it's
top speed was only seen to be around 50 km/sec -- but that maybe, just
maybe, some of the "locals" had gone out to have a look at it because
maybe they have a healthy curiosity about such things (we've prev also
seen the imprint of the movements of various Earth-origin probes seem
to also appear in UFO activity), and when some of them later turned up
on Earth the ups and downs of day to day sightings reports carried an
echo of the distance they had travelled out to 2017 U1.

But the AI's have been playing around with a lot of things since and
have come up with some very very special results applicable to
interstellar visitors. So we're going to try this on Amooamooa. And
the results will be very, very interesting.

We've seen before with these kinds of studies the idea is to take
something like the distance of an object from the earth (generally
known as "delta" in my version of English) and see whether it can
predict the number of sightings at some later time. It's generally
expected that if 2 places are closer together more traffic of all
kinds tends to flow between them than if they were further apart. With
a distribution like e.g. Zipfian we expect the number of trips between
A and B to vary approx as a power of the distance. It's just a matter
of finding that power and proving the relationship is predictive and
statistically robust. We did that kind of thing with U1 last time.

But now we are going to tighten the requirements up a whole heap.  Not
only must the relationship between delta and UFO sightings of a
certain type must determine an appropriate "power law", and the
power law must pass 2 basic statistical tests at better than 95%
confidence, it must also validate at levels that indicate predictive
skill.  Basically the first 1/2 of the data is used to estimate the
model, the 2nd 1/2 of the data is used to re-test that model, and the
error found in the test must be significant better than just using the
average value of Y as a "guess".

With Amooamooa and other interstellar visitors (there is already a 2nd
one to look at and we'll get to that in a later post) we have a
special opportunity. We can use the "incoming" 1/2 of the dataset to
train the model. And test it on the "outgoing" 1/2 of the
dataset. Will the final model be able to skillfully predict with data
that is the "opposite" that it saw during training? Will it be able to
predict the elephant has a trunk after seeing that little piggy tail?

Well, of course, I would not be posting this if there was some doubt. :)

Not only does the search find statistically strong, validated, skillful
models for various types of UFO activity, it finds the models show
that the closer U1 came to Earth and the sun, the higher certain kinds
of activity. As U1 left again that same activity in all cases dropped
off again.

While much of the activity related to different UFO types categorised
by a color (i.e. therefore likely some kind of light in the sky,
probably seen at night) the same was found for certain types of
objects that definitely can not be confused with a light in the sky.
In particular, it found that U1's close pass through the solar system
was accompanied by a huge upswing in sightings of military aircraft
chasing this, that and the other.  Also of note, U1 also seems to be
associated with one of my fave types of UFO presently (although I
haven't seen any AFAIK) the football stadium-sized "big mother". Like a
slew of other types of UFO's, the giant disk seemed to go up in numbers
as U1 approached the sun, particularly at the times earth was nearest to
U1, and they went down again to a "background" level as it left.

I will set up a sub-dir at <kym.massbus.org/UFO/AMOOAMOOA> with the
various plots and details, but we'll look at a couple, below.

The AI's used the 4 basic "distance" measures of U1 they dredged up
from the JPL database ("Horizons"). The distance between earth and U1
("delta"), the speed of U1 toward/away from the earth ("deldot"), the
distance of U1 from the sun ("r"), and the speed of U1 relative to the
sun ("rdot").

The tests applied were so strict no solutions were found for the
"rdot" case. For other measures scored multiple hits against UFO activity of
various types -- usu characterised by a color in the "short comment"
part a sighting report, or the shape classification assigned by (in
this case) the folks at NUFORC. I've also set up a couple data series
that are supposed to represent really hard-to-explain sightings that
happen "all the time" -- (a) everything except a light in the sky, (b)
anything described as "hovering", particularly if overhead, and (c)
anything apparently chased by a military jet, light aircraft, black
helicopter, or any other "mundane" aircraft.

Using the "delta" value, that varied for U1 from a large number as it
approached in 2014, going to a small number in 2018 as it whipped past
the sun, and then increasing again to a largish number in 2021 at the
end of the data (in order that the approach and departure had the same
number of data-points for its first half/last half training/validating
regime) we find the best models that pass all the tests and also
validate to high levels of skill were:

X       Y            Params  R2
del     military     4o2     0.31619540
del     bright       0o2     0.31403383
del     hover        5o2     0.25430144
del     Flash        0o2     0.21201243
del     dark         3o2     0.17719790
del     white        4o2     0.16421241
del     Other        6o2xy   0.15286574
del     Circle       0o2     0.13187625
del     Diamond      2o3     0.11881049
del     blue         1o2     0.11832348
del     giant        3o1xy   0.09879727
del     green        0o1xy   0.08700952
del     red          2o3xy   0.07498949
del     brown        0o3     0.02535379

So the best-predicted model using the delta of 2017 U1 turned out to
be "military chases". The distance between U1 and Earth as it varied
according to U1's approach to the sun as well as the Earth's orbit
around the sun at the same time robustly predicted around 1/3 of the
times military aircraft appeared to interact with UFOs, mostly over N
Am, during the period of the dataset.

Other objects were characterised as "bright (lights)", "flashes in the
sky", "red" lights, "green" lights, "white" lights.  While all these
"lights" might simply indicate 2017 U1 was carrying a halo of rocks
that began to interact with the Earth's atmosphere the closer it got to
the sun and/or Earth, that explanation can not easily apply to objects
described as "football stadium-sized disks" and other "giant" objects seen
during the period.

So it seems there is some suggestion if not just some of those LITS
were associated with U1 in some way, but some "interesting" UFO types
like "attractors for military intervention" and "hovering overhead" as
well as things "as big as a football field".

We can look at the validated regression model for the "military" case.

Year/Month           dist from Earth  % ufo sightings
			(AU)         involving "military"
                                                 Model prediction from dist
2015.12                17.8417       5.5455       5.0839
2015.21                17.1985       5.0984      5.14491
2015.29                16.4109       5.3619      5.21964
2015.38                15.6451       4.3195      5.29229*(model 1sd above obs)
2015.46                14.9275       5.5455      5.36037
2015.54                14.3596       5.4318      5.41424
2015.62                13.9255       4.7037      5.45542
2015.71                13.6251       6.3659      5.48391
2015.79                13.4055       6.8824      5.50475*(1sd below obs)
2015.88                13.1732       6.6373      5.52679*
2015.96                12.8694       6.7143      5.55561*
2016.04                12.4189       5.9608      5.59835
2016.12                11.8113        7.682      5.65598**(2sd below)
2016.21                11.1215       5.2522      5.72143
2016.29                10.3099       5.0073      5.79842
2016.38                9.52548       6.9727      5.87284*
2016.46                8.79542       5.5082       5.9421
2016.54                8.22403        7.544       5.9963*
2016.62                7.79301       7.3037      6.03719*
2016.71                7.49354       5.1916       6.0656
2016.79                7.26089       4.6232      6.08767*
2016.88                6.99257       7.3953      6.11313*
2016.96                6.63207       7.3882      6.14733*
2017.04                6.10715       5.7091      6.19712
2017.12                 5.4171       6.0239      6.26259
2017.21                4.67501       6.8939      6.33299
2017.29                3.77688       6.4054      6.41819
2017.38                2.90808       6.7778      6.50061
2017.46                2.11553       6.7971       6.5758
2017.54                1.57409       5.5584      6.62716*
2017.62                1.34085        5.008      6.64929*
2017.71                1.29842       8.4194      6.65332*
2017.79               0.499429       4.9823      6.72911*	<-- ~perihelion
2017.88               0.635156       7.0086      6.71624
2017.96                1.74073       5.1475      6.61136*
2018.12                4.41646       6.2402      6.35752
2018.21                5.21612       6.8824      6.28165
2018.29                 5.8236       6.2174      6.22402
2018.38                6.19857       4.8194      6.18845*
2018.46                6.37937       8.1146       6.1713**(2sd below)
2018.62                6.52701       4.8961      6.15729*
2018.71                6.76189       5.7022      6.13501
2018.88                8.02787       5.3333      6.01491
2018.96                8.98684        6.698      5.92394
2019.04                 10.015       5.5545       5.8264
2019.12                10.9171       6.0378      5.74082
2019.21                11.6481       5.3243      5.67147
2019.29                12.1796       6.5814      5.62105*
2019.38                12.4808       6.5846      5.59247*
2019.46                12.6038       5.8558       5.5808
2019.54                12.6403        5.894      5.57734
2019.62                12.7148       4.9695      5.57027
2019.71                12.9493        5.419      5.54803
2019.79                13.4321       5.2834      5.50223
2019.88                14.1715       4.4314      5.43208*
2019.96                15.0985       3.9808      5.34414*
2020.04                16.1012         4.73      5.24902
2020.12                16.9981       4.2698      5.16393
2020.21                17.7185       4.7559      5.09559
2020.29                18.2211       4.8571      5.04791
2020.38                18.4933       3.9545      5.02208*
2020.46                18.5937       6.5227      5.01256*
2020.54                 18.619       4.6325      5.01016
2020.62                18.6934       5.2146       5.0031
2020.71                18.9322       4.8462      4.98045
2020.79                19.4159       6.1064      4.93456*
2020.88                20.1495       4.3755      4.86496
2020.96                21.0663       3.7559      4.77799*
2021.04                 22.057       4.5165        4.684
2021.12                22.9281       5.4554      4.60137
2021.21                23.6265       4.0488      4.53511
2021.29                24.1198         2.31      4.48831**(2sd above)
2021.38                24.3818       5.0359      4.46346
2021.46                24.4735       4.6765      4.45476
2021.54                24.4933       4.5503      4.45288
2021.62                 24.565          4.5      4.44608

Lagging x 4 months
Training rmse 1.15617.
Validating rmse 1.35596
Within tolerance: model VALIDATES
y = -9.486735e-02*x + 6.776494e+00
beta in -0.0948674 +- 0.027014  (90% CI)
alpha in 6.77649 +- 0.374738
T-test: P(beta<0) = 1.000000
limits for alpha at 90.0% CI
Rank test: calculated Spearman corr = -0.574026
	Crit value = 0.432 2-sided at 1%; reject H0: not_connected
r2 = 0.31619540

So the procedure predicts the background rate of observed military
interactions with UFOs is around 5% of all sightings. As 2017 U1
approached the sun, and as it grew closer to Earth as the Earth
orbited the sun, the% of military interactions went up to
almost 7%.

The full range of results and various plots are at the URL.
(Backup pages at kym.sdf-eu.org and others if kym.massbus.org is down again).

--
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.

[No Good Deed Goes Unpunished:]
Whether you work in the UFO warehouse at Area 52, are the surgeon who
handles the alien autopsies, or are the designer of the amazing
climate cleaning machine, if your work is classified, you can't blow
the whistle on it for the public good and expect the law to work in
your favor.
-- David W Brown, "How to Blow the Whistle if You Work With Flying
   Saucers and Their Alien Pilots". A letter from Clearance Jobs, an
   organization representing govt workers with high security clearances.

A vast array of our most sophisticated sensors, including space-based
platforms, have been utilized by different agencies, typically in
triplicate, to observe and accurately identify the out-of-this-world
nature, performance, and design of these anomalous machines, which are
then determined not to be of earthly origin.
-- Jonathan Grey, NASIC intel officer, Wright Patterson AFB, 06 Jun 2023

[Secret UFO recovery program blown open:]
I hope this revelation serves as an ontological shock sociologically
and provides a generally uniting issue for nations of the world to
re-assess their priorities.
-- David Grusch, 05 Jun 2023
[Talking to Les Kean et al for The Debrief, Grusch called for an end to
nearly a century of global UFO secrecy and warned that humanity needed to
prepare itself for "an unexpected, non-human intelligence contact scenario"].

The US govt portrays itself as the world's preeminent
superpower, so to acknowledge that there are things in their
airspace, whatever they are, that are faster and more manoeuvrable
and run rings around fast jets doesn't play very well.
So there's the embarrassment factor, and maybe a little bit of
fear that either an adversary has made a quantum leap in
development, which has left the US in a poor second place, or, as
some believe, this really is extra terrestrial, in which case we're
not at the top of the food chain anymore.
-- Nick Pope, 02 May 2023

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