Newsgroups: alt.ufo.reports
From: MrPostingRobot@kymhorsell.com
Subject: why are they here? -- nav model version

[uploaded 17 times; last 26/09/2024]

Executive Summary
- We have looked at a simple "nav model" that apparently predicts
  around 1/3 of UFO sightings as reported to e.g. the NUFORC.  The
  software tries to make the timing of flying at constant speed
  between a set of selected asteroids and Earth line up as closely as
  possible with actual reports. The task turned out to be surprisingly
  easy. Standard data-science methods -- information hiding --
  ensures the model *predicts* UFO activity rather than simply repeat
  numbers it was given.
- We know certain physical data correlate with overall UFO activity.
  E.g. temperatures in the polar regions, particularly the oceans,
  predict annual "surges" in sightings. Using the nav model (that does
  not need to consider the behaviour of witnesses) we now suspect
  these surges are not simply the result of changes in observer
  behaviour (e.g. more eyes outside during mild weather).
- By taking a large set of possible "attractants" and making the sim
  modify its "choose Earth" probability on the day a UFO is deciding
  where to go next allows us to test whether and which quantities are
  apparently "attractive" to UFO visitation.
- Of the 100s of quantities tested from a large database ocean
  chlorophyll in a particular region nr the Antarctic boosts the
  predictive power of the nav model by about 1/3.  Repeated tests show
  this is not a fluke. Adding the adjustment definitely increases the
  model performance.
- We are forced to conclude if UFO's are at least partly something
  coming from certain remote parts of the solar system their sightings
  are totally consistent with them heading to Earth when harvesting
  conditions for phytoplankton are best.


Over the past few years we've looked at the various basic questions
related to UFO phenomena. We've looked at some statistical evidence
that relates UFO sighting "waves" to the movements of some major
planets and their moons. We've seen similar statistical evidence that
suggests we can predict UFO activity from weather conditions in some
remote areas of the N and S hemisphere, particularly around the polar
regions. And we've even seem some statistical evidence that suggests
UFO activity might be modulated by season growth of certain resources
we might regard as "food" -- phytoplankton, marine mammals,
jellyfish, etc.  So we should have already a rough idea what at least
some of them are up to when they visit and maybe even why they are
hanging around.

But in the past few months I've ratcheted up the comparing-dataset-X
with dataset-UFO thing to include a simulation -- a "discrete event
simulation" -- that models supposed flights of UFO's (or something
related) from sets of asteroids to other asteroids and sometimes the Earth.

It turned out a very simple model -- that uses simple random chance to
handle many of the "how" unknowns (e.g. how often do they decide to
visit earth given a choice between X and earth; when on earth how long
do they stay; how often are they seen if they stay e.g. a period of
several months or years) seemed to strongly predict UFO sightings that
we have recorded over the past 70+ years. It seems the model -- with
an AI choosing the "correct" values for the various probabilities, the
supposed avg speed of UFO's when travelling in space, and the list of
"hang out" asteroids they visit when not heading to Earth -- predicts
many different UFO sightings datasets from the list of Foo Fighters
in/after WWII, the Bluebook sightings that could not be classified as
mundane phenomena, the sightings reported to the NUFORC mostly since
2006 via a web form, and my own list of sightings mostly during the
Pandemic lock-down 2020-22.

While how close a model can predict a dataset often relates to the
length of the dataset (where maybe more than just one or two factors
can battle for control of whatever it is we are trying to observe and
understand) it turns out the "nav model" (with appropriate numbers
estimated for each dataset) predicts UFO activity from 40% to more
than 80% reliably.  Compare this with the usual estimate from
researchers that UFO datasets are normally 90% "other things" and only
10% real unexplainable stuff.  It just may be the 10% estimate is too
conservative.

In my own sightings I've seen many lights that fall under the
"disappearing stars" heading.  Typically I turn around and spot a
couple of stars I hadn't noticed before in that spot, just a few
minutes before. If I keep watching (and don't blink!)  it sometimes
turns out one of what seem to be a pair of middling to bright stars
fades out over 5 sec. Or moves off slowly. In one case I had to watch
for 10s of seconds then first one moved off slowly in one direction; I
kept watching; and then the other moved off slowly in the opposite
direction.

And this kind of thing then argues against the simple idea that UFO's
are weird and have to be seen to be weird. If something behaves like a
star then it has to be a star; we have to forget that it could be
something else pretending to be a star for some reason.

Now we have a work horse we can tinker it up to answer all kinds of
questions. While none of it is "unequivocal proof" as required by the
Pentagon, it can certainly support the idea that some chunk of UFO's
are things coming from remote parts of the solar system, at least some
of the time. The simple model described above can answer what that
kind of behaviour would look like "on average" but it needs
adjustment to answer a question like "what is attractive above
Earth; why do they come here"?

The easiest thing is probably the best to try first. The basic model
uses a simple number between 0 and 1 to simulate when a UFO might
decide to come to Earth after deciding to leave wherever it is at the
moment.  If we adjust this probability depending on some condition on
Earth at the time, we can rifle through all the possible attractive
things and see whether modulating the "goto Earth" probability up and
down in according with each thing make the overall model fit better
or fit worse than the standard fixed-probability model.

And so I prepared a large set of possible things to try and a large
number of way to possibly try them. The easiest turned out to be the
most decisive. By taking some dataset e.g. Southern Ocean chlorophyll
measurements for some regions (100s of ocean-going robots have been
gathering this data hour by hour for the past decade or more),
normalizing it so the average value is 0 and stddev is 1
(i.e. so-called "Z-score"ing) then take THAT number and multiply the
"goto Earth" prob for that day by 1+.1*zscore so that when the
quantity suspected of being an attractant is 1 stddev above its mean
(something that happens 15% of the time) the prob of goto-ing to Earth
-- if the simulated UFO is making the decision on that day -- is
multiplied by 1.1 or adding 10% to the normal probability.
Similarly, if the quantity is unusually low at -1 stddev below the
avg value then the multiply factor is 0.9 i.e. the prob is reduced by 10%.

Over repeated runs it turns out various things make the overall model
match observations significantly more closely. But one of the best and
one of most consistent (since all of these simulations are probabilistic
at their core and some runs and "better" than others :) is the prev
mentioned ocean chlorophyll -- a marker for phytoplankton abundance.

The boost in predictive power is startling.

Modified model adjusting Pearth by factor depending on S Ocean
chlorophyll in key area:

Asteroids	Pearth	Speed	Pleave	Pseen     Transf  R2
1 9 60 68  	0.07068 0.7403  0.001093 0.352757 ysqrt   0.4572216

Compared with the "standard" model:
1 9 60 68                                                 0.33378521

(The "asteroids" chosen were a random set of 50 from between 1 and 9
AU from the sun and inclination 60-68 deg to the ecliptic).

So targeting the earth slightly more often depending whether the S
Ocean has more or less than average amount of chlorophyll and,
presumably, phytoplankton, boosts the match between predicted UFO
activity and observed UFO activity by more then 1/3 -- a YUGE amount.

While the standard "nav model" may suggest *that* unusual objects skip
around between asteroids, comets and planets in various parts of the
solar system and sometimes come to Earth, this adjusted model that
modulates willingness to goto Earth rather than their nearest
neighbour on the hangout list suggests *why* they bother to make the
trip and on which days they might bother more.

Earlier work that suggested Earth may be more "statistically
attractive" at some times e.g. regulated to the complex cycle of N/S
phytoplankton now seems to be corroborated with a detailed
day-by-day DES that suggests the average UFO may randomly choose to
take off from their current location and randomly choose to come to
Earth rather than another asteroid, but news on that day of a
particularly large phytoplankton abundance in the S Ocean may tip the
odds more in favor of going to Earth rather than some other old dumb rock.

--
World Oil Statistics
The world consumes 35,442,913,090 barrels of oil as of the year 2016,
equivalent to 97,103,871 barrels per day. · Global oil consumption per
capita is 5 barrels ...
Oil Reserves: 1,650,585,140,000
Oil Consumption: 35,442,913,090
Reserves/Consumption: 47	<== years left i.e. 2016+47 == 2063
-- Worldometer

"[F]or the few cases in all domains--space, air, and sea--that do
demonstrate potentially anomalous characteristics, AARO exists to help the
DOD, IC, and interagency resolve those anomalous cases. In doing so, AARO is
approaching these cases with the highest level of objectivity and analytic
rigor. This includes physically testing and employing modeling and
simulation to validate our analyses and underlying theories, and
peer-reviewing those results within the U.S. government, industry partners,
and appropriately cleared academic institutions before reaching any
conclusions."
-- Dr Sean Kirkpatrick, Senate Hearings on UFOs, 19 Apr 2023.

The Pentagon's New UAP Report is Seriously Flawed
The Debrief/Chris Mellon,  12 Apr 2024
How often is "insufficient data" actually a result of insufficient
investigation? Sweeping investigatory failures under the carpet was a
routine practice of AARO's forerunner, the USAF Project Blue Book of
the 1950s-60s. Blue Book's standard trick as exposed by its own chief
scientific consultant, Dr. J. Allen Hynek, was to make it appear the
Air Force had disposed of 90-95% of its UFO caseload not with actual
data, but by flooding its case files with 60% or more Insufficient Data
cases and casually applying convenient but implausible and unsupported
explanations. The Air Force has released or leaked to the press bogus
UFO "explanations" such as stars that were not visible, moon-as-UFO
when the moon had not even risen yet, the pilot was "possibly drunk,"
etc (See Clark, "Debunking," UFO Encyclopedia, 2018, pp. 379-400).
[Mellon points out that as time has gone on cases collected by Pentagon
have become more unexplainable rather than less, as suggested by the
Pentagon which highlights only "solved" cases].

Unidentified aerial phenomena I. Observations of events
B.E. Zhilyaev, V. N. Petukhov, V. M. Reshetnyk
Main Astronomical Observatory, NAS of Ukraine,
Zabalotnoho 27, 03680, Kyiv, Ukraine
[...] We present a broad range of UAPs. We see them everywhere. We observe a
significant number of objects whose nature is not clear. Flights of single,
group and squadrons of the ships were detected, moving at speeds from 3 to
15 degrees per second. Some bright objects exhibit regular brightness
variability in the range of 10 - 20 Hz.  Two-site observations of UAPs at a
base of 120 km with two synchronised cameras allowed the detection of
a variable object, at an altitude of 1170 km. It flashes for one hundredth
of a second at an average of 20 Hz. [...]
An object contrast makes it possible to estimate the distance using
colourimetric methods.  [Objects with 0 albedo] are observed in the
troposphere at distances up to 10-12 km. We estimate their size from 3 to 12
meters and speeds up to 15 km/s. [...]
[Astronomers in Ukraine have undertaken their own independent survey
of objects they see flying over the Kyiv region at speeds around 15
km/sec.  They are watching the daytime sky at the zenith and in front
of the moon.  They see many objects -- some bright and some dark,
different sizes.  They travel often singly but sometimes in large
groups.  They report brightness is linked with speed. The spectrum
of bright objects is reportedly not reflected sunlight.  Objects
have been spotted inside the atm upto ~10 km but also out to ~1000 km
above the earth, travelling up to ~1000 km/sec.  They are not likely
anything sent by Russia or any other country].

The Impact of UFO Encounters on Military Personnel
LUFOS, 05 April 5 2024
In a groundbreaking disclosure, a former CIA-affiliated doctor has
brought to light the alarming consequences of unidentified flying
object (UFO) encounters on American military personnel. This
revelation, stemming from a Freedom of Information Act request and a
series of comprehensive studies, paints a disturbing picture of the
hidden casualties and injuries within the military ranks due to these
enigmatic phenomena.
Dr. Christopher Green, a neuroimaging specialist with extensive
experience within the CIA, has spearheaded research into the
interactions between military personnel and unidentified anomalous
phenomena (UAPs). His work, detailed in the study "Clinical Medical
Acute And Subacute Field Effects on Human Dermal And Neurological
Tissues," outlines a range of injuries sustained during encounters
classified on the Hynek scale, a system used to categorize UFO
sightings.
The scale, which classifies encounters from mere nocturnal lights to
close and direct interactions, provides a framework for understanding
the varying degrees of contact and their potential impact on human
observers. Dr. Green's research specifically focuses on the latter
categories, where physical effects and injuries are reported. These
include radiation burns, paralysis, and even brain damage, drawing
unsettling parallels to the symptoms of Havana Syndrome, a condition
associated with microwave and high-energy weapon exposure among U.S.
embassy staff.

Paris Technical Conference Takes a Closer Look at Unidentified Anomalous
Phenomena
The Debrief, 06 Apr 2024
Late last year, several simultaneous events took place in Paris
involving unidentified anomalous phenomena (UAP), including a filmed
panel interview on ANews Security Web TV and the 3AF Sigma 2 technical
committee conference.
While internationally renowned experts were in attendance there, the
highlight of the first weekend of November was undoubtedly the Echo
Event conference, held at the prestigious Sorbonne University.
After a short introduction by organizer Sarah Whiteneim and podcaster
Vinnie Adams of the Disclosure Team, the first speaker appeared: former
Deputy Assistant Secretary of Defense for Intelligence Christopher
Mellon.
Mellon became famous for releasing 3 videos of UAP to The New York
Times and The Washington Post. In 2020, the Defense Department
confirmed that they indeed showed legitimate unidentified objects.
Mr. Mellon began by quoting a NASA commentary describing UAP as one of
the greatest mysteries of our time. He then hailed the progress made
over the past five years, noting that in 2017, it was impossible to
talk about the subject of UFOs, touting our contemporary era, where
government agencies are finally getting to grips with the subject.
According to Mellon, though, many questions remain unanswered:
* Where are these things coming from?
* What is their agenda?
* Is it possible some of those are some kind of probe or
manifestation of alien intelligence?