Myriad Security Diagnostic Testing (Important!)

@Tezu pointed it out to me as well. :wink: Thanks Tezu!

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My numbers match yours exactly.
Bleh, it looks I can get electroencephalography out of all the servers, except 88014

I’m awake again… :wink:

THIS (aligned, gridded) layout of the data is what I was looking for…
Great stuff, @Espilonarge, thank you.

INITIAL OBSERVATIONS & THOUGHTS:

PAIRING
This finding seems to make much sense, but let’s try to “make sure”.
(P1)
I recommend if someone can lay the datasets out in a CLOCKWISE fashion, and DRAW PAIR LINES ONLY between what we believe are “paired” servers, to see if any “visual pattern” emerges – ie, a “regular” star, or just a jumbled set of crossed lines.
(P2)
If anyone has “more time”, to borrow some simple WORLD MAP IMAGE and overlay FASTEST PING datasets over that (section of) country which has that fastest ping…

We “know” that PING time is signal turnaround time, between 2 ends of any connection, so it would make most sense that shortest PING indicates “proximity”.

DATASET LENGTH:
I have a nagging feeling that there is a MASSIVE SIGNIFICANCE to the differences in dataset lengths…
++ Whether or not they “ought” to be paired up, according to their numerical coincidences;
++ What the Significance is of the Periods and Colons (frequency, placement)

I think @Espilonarge makes a great point re QUADS of characters – it would FIT with “NEXT” and 4^2=16 → Loop16 … .(and Next being 1.4) — so, lots of 4s to consider.

I’m inclined to find a way to “make the data fit” into EQUAL LENGTHS,
then “line them up”,
then “rotate” them, somehow… but needing to know where to start and stop.

I’m playing with Espi’s image, and adding a bit of colour / highlights . . .
Gonna try something…

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Following up on my earlier thoughts about possible “data corruption”;

If it is CONCLUSIVE & agreed across the board (across the globe?!) that the DATASETS ARE ALL EXACTLY THE SAME – and it would take a most patient person (or someone with a convenient comparison app) to TRIPLE-CHECK that there are NO SUBTLE DIFFERENCES between ANY datasets (ie between countries where they’re downloaded) – then I would conclude that:

The PING times are “only relevant” to Triangulating WHERE (or at least, which country or world segment) any particular Server is LOCATED – the smaller the PING, the nearer the server is to the downloader.

(S)LOW Upload / Download speed MIGHT suggest “noise on the line” as well as a measure of potential Contention Ratio… though why this would be relevant AT ALL to this puzzle, escapes me…

I remain concerned if there might be One or Two “subtle differences” in datasets depending on which country (ie nearest vs farther away from a source server).

If we know UNEQUIVOCALLY that ALL the data is IDENTICAL WORLDWIDE,
then the issue now is ONLY “decoding” it.

In which case, I’d recommend re-considering the data in QUADS (and even OCTALS, since the part-word OCTA appears near the start (chars 2-5) of one dataset…

3 Likes

For giggles, here is the byte count from each servers FetchData
31422 - 137
91247 - 131
11986 - 137
67240 - 138
85671 - 138
88014 - 141
73195 - 130
40144 - 133
55197 - 133
60206 - 134

Paired -

  1. 137 - 138
  2. 131 - 130
  3. 137 - 134
  4. 138 - 133
  5. 141 - 133
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I don’t like one seen from Europe:
60206
Upload: 25 mbps
Download: 24 mbps
Ping: 25 ms

More in up than down is clearly weird for a connection. (Not for a Symmetric Digital line but since the other seem to be in Assymetric…)

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We might look at your data this way, @kerdorin:

To have such rubbish U/D speeds & Ping time, then Server 60206 should NOT be relied upon by CSD Europe Division, and that 60206 must be “better used / accessed” from elsewhere in the World.

Therefore, for “future data analysis”, Europe CSD should (probably) “ignore” 60206 as “unreliable”…

1 Like

Thanks, @SingularGleam – this is what I wanted / needed just now.

BBL, gonna apply these numbers…

Forgive me, @SingularGleam

… but these totals (near 250 per pair) don’t seem to match up with the 260-270 of your most recent counts…?

What have I missed? :frowning:

Someone flat out counted characters, I slapped the FetchData into this
https://lingojam.com/ByteCounter

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Why would anyone want to manually count them lol.

Better them than me lol

POSSIBLE BREAKTHROUGH??

In @SingularGleam’s per-character counts post earlier,
I’ve JUST noticed there are NO Zs, NO Qs, and NO Js.

I note – thanks to Scrabble – that Q / Z are worth 10 points apiece.
… and that J / X are worth 8 points each.

ABSENCE of those letters MAY suggest that we “don’t need such high values” (with the exception of the MANY Xs, at 8pts).

Please may I NOTE that the INVENTOR of SCRABBLE is named ALFRED BUTTS.
A.B.
The only two CAPITAL LETTERS we have in ALL the datasets.

Coincidence?

Someone please use the Link provided above, grab the POINTS values (1 through 5 for the other letters, and 8 for X) and see if we might TRANSLATE the LETTER DATA into NUMERICAL DATA

… and then take it into QUADS (or OCTALS) and see if we can’t get some COORDINATES of some kind, out of them…

We will need to remove the A and B,
NOTE the locations of Periods and Colons,
… and see where it takes us.

5 Likes

2 blank tiles (scoring 0 points)
1 point: E ×12, A ×9, I ×9, O ×8, N ×6, R ×6, T ×6, L ×4, S ×4, U ×4
2 points: D ×4, G ×3
3 points: B ×2, C ×2, M ×2, P ×2
4 points: F ×2, H ×2, V ×2, W ×2, Y ×2
5 points: K ×1
8 points: J ×1, X ×1
10 points: Q ×1, Z ×1

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Has anyone tried putting these in a ceasar’s square?

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With what shift?

wouldn’t know, but I’d try incremental shifts to see if anything sensible comes out. Can’t rn because I’m at the office and I SHOULD be working

2 Likes

Everything seems to be so spread out. So, here’s my attempt to pull all the information together in one post.

Servers:

31422
91247
11986
67240
85671
88014
73195
40144
55197
60206
Note: There are 10 servers and 10 active dreamers. We all have the same list of servers.

Connection Test:

(31422) Upload: 16 mbps Download: 49 mbps Ping: 21 ms
(91247) Upload: 31 mbps Download: 66 mbps Ping: 2 ms
(11986) Upload: 20 mbps Download: 41 mbps Ping: 18 ms
(67240) Upload: 25 mbps Download: 38 mbps Ping: 19ms
(85671) Upload: 16 mbps Download: 41 mbps Ping: 22 ms
(88014) Upload: 16 mbps Download: 59 mbps Ping: 25 ms
(73195) Upload: 35 mbps Download: 66 mbps Ping: 4 ms
(40144) Upload: 8 mbps Download: 21 mbps Ping: 12 ms
(55197) Upload: 15 mbps Download: 59 mbps Ping: 25 ms
(60206) Upload: 10 mbps Download: 31 mbps Ping: 17ms

Connect%20Quality%20Values
Note: Connections vary across the globe making connection different. Here in N. America it looks like the data could possibly vary according to time zones. Thus, I’m not sure the spreadsheet is accurate.

Data:

(31422)
ihnelucdss1dxve8d
ecx5i.egioehrtg.de
hnaftdnco.drss
oc7nche6aes.dmswtk
yvalusaxeaeievb
essaepermorxvysnet
xlrcrop:gencsd
tdxsd.eeccoi.

(91247)
p.mm.gtoepoxvrxce
cieslsecdtre9asd.1r
eneraxdcnha.dnes
ldumelsiotecnscxh
resyestodaeah
aBeatvkss.euyneldm
oxti:cenprh
co7iosg3f.ux5

(11986)
gxdeoneiss2sesgu
sveeeoacmyuiyhe6e
xd.pyheeectaysi.a
td0mcxvxsmeappenxm
rvmlxdisttad.aok
roanbsohipned.c6re
leieccrarssesncr
oc0atllces.d.

(67240)
gryxenxcht0u.dec
saxdgopptnchy
cxsresonasem4lesxprt
ahauedca4dxneuse
mseraaaeiwm.o4ef.a
lpesevr.sasddsicb
emen.ned.ksoraecpp
ltneoec1lccei

(85671)
g.scenciei4ncteis
ltmepevsvaei.kysmo
belaa.neged2dx
neuucdvy3desxp
rtasacceptnad.r1:h
cexsdsrgoe.anrsssmd
mooheesxplrxcdeiha
xa2i.xtcsdefo

(88014)
pxcxa9ceoheededei
tdvy5smxtcnoateis
gefogesei1vyi.
kactmesd.anrcrneu:
ssrgocccensdsmdsva
a.n.n.r5oxmobeaxplr
eaed7measacshsvuhi
sxpt.cexsiept

(73195)
usoxmn.nednetmhr
aseevstvbdeds4c
cla7ssltixdycner
rpgavi.sthaeelodxs
helu:ocopic.e
acoencenxtkieux1ax
ne2mssgiytd.dr
.re9rd.crsfeo

(40144)
iccennxnevnesxer
.dem0nyca6ept
sasseoesaAlbcsep
egdcalom.s.pchroro
eegnsawtued.erene
iseseudxdxpsplv
ceyxoxlaho4drat7li
cc2umssdc.a.k

(55197)
nocta1s.xmdtac.ks
deneercrgsi.e.reg
etitdvercxnr8ohmxp
ssalasaereomsw
ln.d.vuhesi0meaeia
ctlcedxuxcyvao
geieepxaxnnsssd4ve
iy8ccoeu:nsdb

(60206)
rhypa8mesmdcplxp
tpteuaaa.ksyxsaec
hleosasgrccaopes
llcdcd.gxntti.deen
taxvnsieeo.ae
issetceseobsm.he
soelxnedanuor.d6cm
ci9vehr1sxdy1
Note: There are 8 lines of data. We all have the same data. This data has been paired. However, I don’t understand how the pairing could come into play.

5 Likes

Here is 31422 - scrabblefied

1411132111284182
13851.121114112.21
211412131.2111
13713416111.231415
44111118111143
111113113118441111
81113:211312
12812.113311.

5 Likes

The pair theory is supposing they are talking to each other.
Edit - out of likes, shocker :frowning:

1 Like