Spam is goooooood :)
Published on November 6, 2007 By BX In WinCustomize Talk

Hi fellows,
As you know that we are going through A WC Subscription/Chairity Drive). To help a noble cause and return a bit to the community I love, I have decided to put a little contest thingie. Just post what-ever you want (Provided not against ethics/WC Policy) and the 100th poster will get a shiny new WC Subscription or An extension if you are a current subscriber.



SO here we go .... !!!!!



(If somone wants to upsize the package ----- doors are open)

Edit: Modified topic so everyone would know what the thread was about - Zoomba

Post # Donated By Won By  
100 BX ilsabav92 *
200 Fuzzy Logic BookChick *
300 Anon NautilusIT *
400 Anon HAPTORK *
500 Anon killajosh *
600 Anon Cheated, cycled to 1000  
700 ----- -----  
800 ----- -----  
900 NightTrain Bobbyhundreds  
1000 Anon Carguy1 *
1100 Lantec sAARGe *
1200 Anon Uma11 *
1300   Jason Carver  
1400   webby85  
1500 Quentin94 2of3 *

* - Subscription added to account.


Comments (Page 18)
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on Nov 07, 2007

Fuzzy logic is a superset of conventional (Boolean) logic that has been
extended to handle the concept of partial truth -- truth values between
"completely true" and "completely false".  It was introduced by Dr. Lotfi
Zadeh of UC/Berkeley in the 1960's as a means to model the uncertainty
of natural language. (Note: Lotfi, not Lofti, is the correct spelling
of his name.)

Zadeh says that rather than regarding fuzzy theory as a single theory, we
should regard the process of ``fuzzification'' as a methodology to
generalize ANY specific theory from a crisp (discrete) to a continuous
(fuzzy) form (see "extension principle" in [2]). Thus recently researchers
have also introduced "fuzzy calculus", "fuzzy differential equations",
and so on (see [7]).

Fuzzy Subsets:

Just as there is a strong relationship between Boolean logic and the
concept of a subset, there is a similar strong relationship between fuzzy
logic and fuzzy subset theory.

In classical set theory, a subset U of a set S can be defined as a
mapping from the elements of S to the elements of the set {0, 1},

   U: S --> {0, 1}

This mapping may be represented as a set of ordered pairs, with exactly
one ordered pair present for each element of S. The first element of the
ordered pair is an element of the set S, and the second element is an
element of the set {0, 1}.  The value zero is used to represent
non-membership, and the value one is used to represent membership.  The
truth or falsity of the statement

    x is in U

is determined by finding the ordered pair whose first element is x.  The
statement is true if the second element of the ordered pair is 1, and the
statement is false if it is 0.

Similarly, a fuzzy subset F of a set S can be defined as a set of ordered
pairs, each with the first element from S, and the second element from
the interval [0,1], with exactly one ordered pair present for each
element of S. This defines a mapping between elements of the set S and
values in the interval [0,1].  The value zero is used to represent
complete non-membership, the value one is used to represent complete
membership, and values in between are used to represent intermediate
DEGREES OF MEMBERSHIP.  The set S is referred to as the UNIVERSE OF
DISCOURSE for the fuzzy subset F.  Frequently, the mapping is described
as a function, the MEMBERSHIP FUNCTION of F. The degree to which the
statement

    x is in F

is true is determined by finding the ordered pair whose first element is
x.  The DEGREE OF TRUTH of the statement is the second element of the
ordered pair.

In practice, the terms "membership function" and fuzzy subset get used
interchangeably.

That's a lot of mathematical baggage, so here's an example.  Let's
talk about people and "tallness".  In this case the set S (the
universe of discourse) is the set of people.  Let's define a fuzzy
subset TALL, which will answer the question "to what degree is person
x tall?" Zadeh describes TALL as a LINGUISTIC VARIABLE, which
represents our cognitive category of "tallness". To each person in the
universe of discourse, we have to assign a degree of membership in the
fuzzy subset TALL.  The easiest way to do this is with a membership
function based on the person's height.

    tall(x) = { 0,                     if height(x) < 5 ft.,
                (height(x)-5ft.)/2ft., if 5 ft. <= height (x) <= 7 ft.,
                1,                     if height(x) > 7 ft. }

A graph of this looks like:

1.0 +                   +-------------------
    |                  /
    |                 /
0.5 +                /
    |               /
    |              /
0.0 +-------------+-----+-------------------
                  |     |
                 5.0   7.0

                height, ft. ->

Given this definition, here are some example values:

Person    Height    degree of tallness
--------------------------------------
Billy     3' 2"     0.00 [I think]
Yoke      5' 5"     0.21
Drew      5' 9"     0.38
Erik      5' 10"    0.42
Mark      6' 1"     0.54
Kareem    7' 2"     1.00 [depends on who you ask]

Expressions like "A is X" can be interpreted as degrees of truth,
e.g., "Drew is TALL" = 0.38.

Note: Membership functions used in most applications almost never have as
simple a shape as tall(x). At minimum, they tend to be triangles pointing
up, and they can be much more complex than that.  Also, the discussion
characterizes membership functions as if they always are based on a
single criterion, but this isn't always the case, although it is quite
common.  One could, for example, want to have the membership function for
TALL depend on both a person's height and their age (he's tall for his
age).  This is perfectly legitimate, and occasionally used in practice.
It's referred to as a two-dimensional membership function, or a "fuzzy
relation".  It's also possible to have even more criteria, or to have the
membership function depend on elements from two completely different
universes of discourse.

Logic Operations:

Now that we know what a statement like "X is LOW" means in fuzzy logic,
how do we interpret a statement like

    X is LOW and Y is HIGH or (not Z is MEDIUM)

The standard definitions in fuzzy logic are:

    truth (not x)   = 1.0 - truth (x)
    truth (x and y) = minimum (truth(x), truth(y))
    truth (x or y)  = maximum (truth(x), truth(y))

Some researchers in fuzzy logic have explored the use of other
interpretations of the AND and OR operations, but the definition for the
NOT operation seems to be safe.

Note that if you plug just the values zero and one into these
definitions, you get the same truth tables as you would expect from
conventional Boolean logic. This is known as the EXTENSION PRINCIPLE,
which states that the classical results of Boolean logic are recovered
from fuzzy logic operations when all fuzzy membership grades are
restricted to the traditional set {0, 1}. This effectively establishes
fuzzy subsets and logic as a true generalization of classical set theory
and logic. In fact, by this reasoning all crisp (traditional) subsets ARE
fuzzy subsets of this very special type; and there is no conflict between
fuzzy and crisp methods.

Some examples -- assume the same definition of TALL as above, and in addition,
assume that we have a fuzzy subset OLD defined by the membership function:

    old (x) = { 0,                      if age(x) < 18 yr.
                (age(x)-18 yr.)/42 yr., if 18 yr. <= age(x) <= 60 yr.
                1,                      if age(x) > 60 yr. }

And for compactness, let

    a = X is TALL and X is OLD
    b = X is TALL or X is OLD
    c = not (X is TALL)

Then we can compute the following values.

height  age     X is TALL       X is OLD        a       b       c
------------------------------------------------------------------------
3' 2"   65      0.00            1.00            0.00    1.00    1.00
5' 5"   30      0.21            0.29            0.21    0.29    0.79
5' 9"   27      0.38            0.21            0.21    0.38    0.62
5' 10"  32      0.42            0.33            0.33    0.42    0.58
6' 1"   31      0.54            0.31            0.31    0.54    0.46
7' 2"   45      1.00            0.64            0.64    1.00    0.00
3' 4"   4       0.00            0.00            0.00    0.00    1.00

For those of you who only grok the metric system, here's a dandy
little conversion table:

  Feet+Inches = Meters
  --------------------
    3'   2"     0.9652
    3'   4"     1.0160
    5'   5"     1.6510
    5'   9"     1.7526
    5'  10"     1.7780
    6'   1"     1.8542
    7'   2"     2.1844

on Nov 07, 2007

Bookchick: Fuzzy logic is derived from fuzzy set theory dealing with reasoning that is approximate rather than precisely deduced from classical predicate logic. It can be thought of as the application side of fuzzy set theory dealing with well thought out real world expert values for a complex problem (Klir 1997).


Love the name.
on Nov 07, 2007
Damn...reading that gave me a fuzzy logic headache.  
on Nov 07, 2007
Wow! This is the real thesis! I'm admire!
on Nov 07, 2007
Will there be a test on this?
on Nov 07, 2007
On this day...

November 7:

* 1665 – The London Gazette, the oldest surviving English newspaper, was first published as the Oxford Gazette.
* 1811 – American forces led by Indiana Territory Governor William Henry Harrison defeated the forces of Shawnee leader Tecumseh's growing American Indian confederation at the Battle of Tippecanoe near present-day Battle Ground, Indiana.
* 1885 – Construction of the Canadian Pacific Railway, the first transcontinental railroad across Canada, concluded with financier and politician Sir Donald Smith driving in the "last spike" (pictured) in Craigellachie, British Columbia.
* 1917 – Vladimir Lenin led a Bolshevik insurrection against the Provisional Government of Alexander Kerensky, starting the Bolshevik Revolution, the second phase of the overall Russian Revolution.
* 1987 – Zine El Abidine Ben Ali deposed and replaced Habib Bourguiba as President of Tunisia, declaring him medically unfit for the duties of the office.

More events on this day...
on Nov 07, 2007
The day after tomorrow is the third day of the rest of your life.
George Carlin
on Nov 07, 2007
The future isn't what it used to be...
on Nov 07, 2007
If all the world's a stage, I want to operate the trap door.
-- Paul Beatty

on Nov 07, 2007
* William Shakespeare - baptized April 26, 1564- April 23, 1616

"Good friend, for Jesus sake forbeare
To dig the dust enclosèd here.
Blessed be ye man that spares these stones,
And curst be he that moves my bones."

It was not unusual, at the time of Shakespeare's death, for corpses to be removed from graves and burnt allowing for the reuse of the grave site. Shakespeare's grave remains undisturbed.

on Nov 07, 2007
A man was sent to Hell for his sins. As he was being taken to his place of eternal torment, he passed a room where a lawyer was having an intimate encounter with a beautiful young woman.

"What a ripoff," the man muttered. "I have to roast for all eternity, and that lawyer gets to spend it with a beautiful woman."

Jabbing the man with his pitchfork, the escorting demon snarled, "Who are you to question that woman's punishment?"
on Nov 07, 2007
Oh I'm too late.
Hey means if the 300th post will be of mine then I will win I year subscription.    
on Nov 07, 2007
Hey means if the 300th post will be of mine then I will win I year subscription.


That's right. You may be 300th or 400th or 500th etc... You will win 1 year subscription in any of these cases!

Hope it will be already on on 300th post. Good luck!

on Nov 07, 2007
The Lord of the Rings: The Return of the King

Battle of Pelennor Fields


King of the Dead: Release us!
Gimli: Bad idea! Very handy in a tight spot, these lads, despite the fact they're dead.
King of the Dead: You gave us your word!
Aragorn: I hold your oaths fulfilled. Go, be at peace
on Nov 07, 2007
Encyclopaedia Britannica
Seen in my local paper's "readers sales" section.

FOR SALE BY OWNER

Complete set of encyclopaedia Britannica.
45 Volumes. Excellent condition.
£1000 pounds or best offer.

Reason for sale:- No longer required.
Got married last weekend.
Wife knows everything.
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