Icons: System States

I had a very interesting discussion regarding Aristotlean Drama, Linear Programming and Transactional Analysis today and it lead me to reevaluate my own thoughts on these concepts.

First I reevaluated my thoughts on States:

states-aristotle-drama

states-linear-program

states-transact-analysis

Aristotlean Drama is simple because it only involves the state of one character following a linear path.

However, when you begin to think about the outcomes for two characters the dynamic becomes tabular which brings us to game theory and the famous prisoner’s dilemma and game theory payoff matrixes:

prisoner-aristotle-diad

prisoner-linear-diad

prisoner-transact-diad

However, it immediately becomes apparent that the Prisoner’s Dilemma does not account for all of the States.

prisoner-aristotle-triad

prisoner-linear-triad

prisoner-transact-triad

Here we have the States of Transactional Analysis, however this state model is not complete either.

prisoner-aristotle-pentad

prisoner-linear-pentad

prisoner-transact-pentad

Even with a pentad the States are incomplete.  This is where my epiphany came in.  There has to be a begin state and an end state.

prisoner-aristotle-heptad

prisoner-linear-heptad

prisoner-transact-heptad

Now with a heptad, we have all seven States and a complete tabular model.

However, we are learning tabular models are not adequate.  We are learning network models are necessary.  And network models require an alternate portrayal.

prisioner-aristotle-hex

prisoner-linear-hex

prisoner-transact-hex

Here we have a network presentation of the seven States.  And each of these States have seven states of their own.  There is no magic here.  The correlation to the week I do not think is coincidental, but cultural, however I do not think that astronomical phenomena have any causation.

prisoner-score-hex

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Universe: The Fabrics of Perception

https://i2.wp.com/www.historyforkids.org/learn/greeks/clothing/pictures/weaving.jpg

I am working with the Latin language and it is helping me to classify my thoughts more effectively by understanding historical correlations in meaning. For example matter was considered a fabric. The term for light, “lume”, comes from the term loom which alludes to textile manufacture. In fact all of the textile terms merge with geometry where they were practically applied.

WEAVE: a fabric
POINT: a intersection
LINE: a line
ANG: a cut
HEIR: an area
VOL: layers
QUAL: a bundle

These terms have influenced our thinking for literally thousands of years. We still talk of the “fabric” of space, the fabric of time and “material” or whatever. We are unintentionally applying a metaphor. Yet it is a metaphor that has served us well.

At this point I present a scale that I have arrived at for human sensory perception.

outsideness

– 8 , – 2 , – 1 , 0 , + 1 , + 2 , + 8

where

8 is infinity

2 is two

1 is one

0 is zero

+ is positive

– is negative

– 8 : WEAVE below perception: Datrice
– 2 : POINT: below acception: Sortrice
– 1 : LINE: below exception: Matrice
0 : ANGE: exception: Natrice
+ 1 : HEIR above exception: Patrice
+ 2 : VOL: above acception: Fratrice
+ 8 : QUAL: above perception: Satrice

1. WHO: Eyes: Occipital Lobe: Speciatation of Matter.

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root ASTR for the night sky:

– 8 : WEAVISTER: below perception
– 2 : POINTISTER: below acception
– 1 : LINISTER: below exception
0 : ANGISTER: exception
+ 1 : HEIRISTER above exception
+ 2 : VOLISTER: above acception
+ 8 : QUALESTER: above perception

PhotonicPhotons, PhotonicElectrons, PhotoincIons, PhotonicGases, PhotonicLiquids, PhotonicSolids, PhotonicMolecules

2. WHAT: Ears: Temporal Lobe: Association of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root FUL for Electricity or “Lightning” which is interesting because it means we hear events.

– 8 : WEAVIFUL: below perception
– 2 : POINTIFUL: below acception
– 1 : LINIFUL: below exception
0 : ANGIFUL: exception
+ 1 : HEIRIFUL: above exception
+ 2 : VOLIFUL: above acception
+ 8 : QUALIFUL: above perception

ElectronicPhotons, ElectronicElectons, ElectronicIons, ElectronicGases, ElectronicLiquids, ElectronicSolids, ElectronicMolecules

3. WHEN: Nose: Brainstem: Attibution of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root FIED for Ions or burn which is interesting because it means we smell ions or things that are reactive.

– 8 : WEAVEFIED: below perception
– 2 : POINTFIED: below acception
– 1 : LINEFIED: below exception
0 : ANGFIED: exception
+ 1 : HEIRFIED: above exception
+ 2 : VOLFIED: above acception
+ 8 : QUALIFIED: above perception

IonicPhotons, IonicElectrons, IonicIons, IonicGases, IonicLiquids, IonicSolids, IonicMolecules

4. WHERE: Throat: Parietal Lobe: Domination of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root AER for Gases

– 8 : WEAVIER: below perception
– 2 : POINTIER: below acception
– 1 : LINIER: below exception
0 : ANGIER: exception
+ 1 : HEIRIER: above exception
+ 2 : VOLIER: above acception
+ 8 : QUALIER: above perception

GasicPhotons, GasicElectrons, GasicIons, GasicGases, GasicLiquids, GasicSolids, GasicMolecules

5. WHY: Mouth: Frontal Lobe: Ingestion of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root AEST for Liquids or “Sea” which is interesting because it means that the Sea is the surface of the water.

– 8 : WEAVIEST: below perception
– 2 : POINTIEST: below acception
– 1 : LINIEST: below exception
0 : ANGIEST: exception
+ 1 : HEIRIEST: above exception
+ 2 : VOLIEST: above acception
+ 8 : QUALIEST: above perception

LiquidicPhotons, LiquidicElectons, LiquidicIons, LiquidicGases, LiquidicLiquids, LiquiidicSolids, LiquidicMolecules

6. HOW: Body: Cerebellum: Deduction of Matter

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root TER for Liquids or “Earth” because it means that the creators of the word Earth meant “water”.

– 8 : WEAVITER: below perception
– 2 : POINITER: below acception
– 1 : LINITER: below exception
0 : ANGITER: exception
+ 1 : HEIRITER: above exception
+ 2 : VOLITER: above acception
+ 8 : QUALITER: above perception

SolidicPhotons,  SolidicElectons, SolidicIons, SolidicGases, SolidicLiquids, SolidicSolidsSolidic, Molecules

HOW MUCH: Gut: brain region unknown

+ 8 , + 2 , + 1 , 0 , – 1 , – 2 , – 8

Standard prefixes with root DUCT for Counting which is interesting because this involves the digestive process.  Molecule literally means “soft stone”.  Another word for dung.

– 8 : WEAVIDUCT: below perception
– 2 : POINTIDUCT: below acception
– 1 : LINIDUCT: below exception
0 : ANGIDUCT: exception
+ 1 : HEIRIDUCT above exception
+ 2 : VOLIDUCT: above acception
+ 8 : QUALIDUCT: above perception

MoleculicPhotons, MoleculicElectrons, MoleculicIons, MoleculicGases, MoleculicLiquids, MoleculicSolids, MoleculicMolecules.

Note: The seven International System Units are:

– 8 : WEAVE: below perception: Candela
– 2 : POINT: below acception: Ampere
– 1 : LINE: below exception: Kelvin
0 : ANG: exception: Metre
+ 1 : HEIRabove exception: Second
+ 2 : VOL: above acception: Kilogram
+ 8 : QUAL: above perception: Mole

I posted all of the above, because I believe that classification is underrated. If we spent more time thinking about the aesthetics of our classification language, which is presently total crap, we might make more discoveries.

How much do we conceal from ourselves because we deceive ourselves into thinkng a dogmatic classification system won’t bear fruit.

Have you ever seen this guy?

https://relationary.files.wordpress.com/2007/11/mendeleevphoto.jpg

He beat his brains out letting the data talk to him and came up with this:

Periodic Table

When Dmitri Mendeleev created this table to describe periodic behaviour of the elements, many of the elements had not been discovered. However, the table projected what the properties of those elements would be making the search much easier.  Dmitri also was very good at making Vodka.

As I have discussed there are Satrice, Fratrice, Patrice, Natrice, Matrice, Sortrice and Datrice networks.  Each of them classify in different ways.  Understanding these networks and their classification are the road to new discoveries.  Networks are classification systems.

I just saw this in the New York Times:

knowledgemap

It is called a “Knowledge Map”.  It is a plot of the link clicking behaviour of a scientific community.  Not what they say is important, but where they are going that they think is important.  From this information it may be possible to reorganize knowledge to make it more accessible to everyone.

And that is what we are all here for getting and giving access.

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