# Female 1000 System

The first question is: Why have an image for each number from 000 to 999 (one thousand images)?

It is so that one imagined image can represent a three digit number - and that might be helpful for memorising most of a 4 digit history date; or for learning some kind of numeric password.

The next question is: If I am going to go to all that effort, is there any bonus benefit to learning so many images:numbers?

It is generally claimed that, when learning a foreign language, the most frequently used 2000 words are a good investment of a student's time. I was thinking that, if I could have two 1000 image systems then the images could not just represent 000-999 but also represent common vocabulary meanings;

then, if I am learning a tricky foreign word (that sits within the 2000 list), I could imagine its representative image in a story which involces another memory image to do with how to spell the word. Eg. 'T.h.i.n.k' and the 'PE' of 'Pe.n.s.e.r' if learning French. It is just a small prompt but the mind is pretty good at using a small prompt and recalling the whole thing.

Where the method is weak is when a language has a prefix used so often that many many words all start with the same letters: the two letter prompt is not specific enough. Then, you have to think about a bespoke image for a prefix like 'prze'.

Also, the prompt can be a one letter image (see the Alphabet-related article) or a 3 letter image (see the Robots article later in the course).

There is a less and less taught maths technique called logarithms. As a curiosity, I wanted to embed some logarithm table data in the image of each person. But I think you can largely ignore that fact since nobody cares about logarithms nowadays. A log table would typically let you look up a 3 digit number and discover a 4 digit+ number by running your finger down a reference table. I wanted to record the 4 digit number appropriate for a 000-999 number, if any.

The idea was that the eyes, nose, etc. of a face each indicate a digit. So, a face could be 'translated' into a 4 digit number based on choice of eye, nose, etc..

The 1000 women images are in this article. There is a separate 1000 men article.

Below are how cartoon women are described by their features.

The clothes 0-9 choice is just the colour of the person's clothes. Any three digit number beginning with 0 uses the 0 colour on the clothing.

The clothes consist of a top half and a bottom half. The 2nd and 3rd digits of the 3 digit number represent the top half clothing choice and the bottom half clothing choice.

Facial features: wrinkles beside eyes, straight eyebrows, eye bags, angled eyebrows, nose mark, red cheeks, arched eyebrows, bowed eyebrows, freckles, reverse direction brows.

In this way, the first digit of the 4 digit 'answer' number is represented by one of 10 facial features.

Hair / hat is not a random decision by me. I developed a shorthand abbreviation for each word in the 1000 word vocabulary. The shorthand is either a letter and a digit or two letters followed by a digit. There are 26 hair / hat types to represent the first letter of that shorthand.

The colour of the hair represents the second letter of the shorthand or, if the shorthand is a letter and a digit, the colour represents the digit.

Eye colour can create variety in the 1000 people. I have decided to use blue, brown, green, light blue eyes - in a looping sequence from 000 upwards.

I used an antilog table to get 4 digits that are represented as facial effect, eyes choice, nose choice, mouth choice.

Skin colour follows a loop of 7 colours.

The name of the person is the vocabulary meaning. If an image represents the word 'lid' then Lid is that person's name - a bit unusual!.

Women 1000 Table

There are 1001 rows in the table from 000 to 1000 but row 1000 is an additional row in case a 1000 integer item needs representing. It is not log related.

Video of the Women 1000 images (generated using software - but good enough!))

Women 000 to 099

Women 100 to 199

Women 200 to 299

Women 300 to 399

Women 400 to 499

Women 500 to 599

Women 600 to 699

Women 700 to 799

Women 800 to 899

Women 900 to 1000