Advice

Do u need help? anything........anything u want to ask for help on.....even homework! (no cheating!) i will answer any questions u have to offer

I need help with everything!

Ok I admit I'm not a math wiz.......but I am good with computers and can do a bunch of reasearch. I found this possible answer on thescienceforum.com (by serpicojr)

I don't know a lot about it myself, but let me take a stab. Consider a yes-or-no problem which takes n inputs. For example, given a set S of n distinct, positive integers and another integer k, can you write k as the sum of distinct elements of S? Suppose that the answer to our problem is yes. There are two main things we'd like to do in the context of this problem:

1. decide whether potential solutions are correct;
2. produce solutions

The former is an easier thing than the latter: when you produce a potential solution, you have to be able to decide whether it's true!

Suppose we have some algorithms to do 1. and 2. Oftentimes you can describe the time it takes to perform these algorithms as a function of the number of inputs n. (By "time" I really mean "how many calculations you have to perform".) For each problem, there are good algorithms (fast ones) and bad algorithms (slow ones). We can speak of the minimal amount of time it takes to complete 1. or 2. as being the running times of the best algorithms that exist, and we consider this minimal time to be the complexity of the problem. We can then break problems into "classes" based upon the complexity of 1. and 2.

Two important notions of speed of algorithms we're interested in are polynomial and non-polynomial time. An algorithm is polynomial time if the number of steps it takes is (less than or equal to) a polynomial in the number of inputs n, e.g. n, n², n²⁰+3n⁷, etc. An algorithm is polynomial time if it runs much faster, too--for example, log(n) is much faster, so this is polynomial time. An algorithm which is not polynomial time is... non-polynomial time. In other words, the number of steps grows faster than any polynomial as the number of inputs increases.

Now we define P and NP. NP is the set of problems where 1. has polynomial time complexity. P is the subset of NP where 2. also has polynomial time complexity. The question, then, is whether P is all of NP or whether there exist "hard" problems for which 2. is non-polynomial time. The traveling salesman problem (TSP) is an example of such.

So our poster was claiming that he had shown P = NP by finding solutions to TSP in polynomial time.

2. I think when people regret stuff its because when they did it they might not have had time to think over it. Even in chess you must think about the move you will make or you will end up regreting it soon!

cool

good point but to aviod regreting something u should think

Okay...I need some ideas for a way to make extra money on a part time basis with my computer.

It must involve a low initial investment...no more than $500

I only have about 10 or so extra hours a week to put into it at first(if I start making money I will cut back on the OT at work and put more time in it)

I am open to just about everything

I am a very organized person (when it comes to work) 

I am also not into these "Internet overnight success scams"

I am a realist and I know there is no such thing as an overnight millionaire except in very rare cases which I doubt  will happen to me

So...any ideas?