As the heroes in the well-known TV series ‘The Big Bang Theory’, geeks are generally defined as the guys who are obsessed with computer technology and science. Most of them are incredibly intelligent on academic stuff, but not able to create good strong relationship with the world. In other words, so-called ‘common people’ cannot understand their lives. They regard them as the smart rebarbative geniuses who indulge themselves in the virtual world. We can see the dislike from the public to the geeks from the word ‘geeky’.
That’s why geeks should know how to write. For a common person, the contents of books or articles are the most acceptable knowledge, which means, they are willing to believe the words they read. If a geek manages to write, he will gain opportunities to let the world know his thoughts, the technologies he is interested and the happiness he wants to share with people about the virtual world.
Another advantage of the geeks who can write is that writing is the most efficient tool to spread their idea. With writing skills, for instance, they can spend 1 hour on writing down their ideas, and let thousands of people know what they are doing. Compared with the usual communicating methods such as chatting and making speeches, writing is absolutely a better way to express, especially with the help of the internet.
Writing can also help geek field develop and obtain fresh blood. Some teenagers who are not clear with their futures may find their interests in this field and join them after reading the stuff geeks write. That’s related to the prospect of computer science, to some level.
Above all, writing ability is important for geeks, and they have to make efforts to let the world comprehend why their virtual world is so appealing.
2015年1月25日星期日
2014年11月28日星期五
SLOG 11
This week we had our last
three lessons, and it is still a little bit tough for me to understand them.
The content we learned this
week is about halt, and it is related to another lesson I am taking, which is
programming.
Halt, which means ‘stop’, is opposite to the
computing method ‘loop ’. If a code runs, and it can finally return a result (sometimes
maybe more results), then the function halts; on the other hand, if it keeps
looping, the function does not halt.
Then the ‘halt’ problem leads to
another important topic, ‘computable’ and ‘non-computable’.
To comprehend ‘computable’, we have to firstly comprehend the concept
of ‘well-defined’. A function is
well-defined if and only if we can tell what f(x) is for every x in some
domain. A function is computable if and only if it is well-defined and we can
tell how to compute f(x) for every x in the domain. Here is another definition.
If function f(n) can be implemented by extending another function g(n), then we
say f reduces to g.
Now we can combine and simplify these two definitions: ‘f reduces to g’ means
‘g computable⇒ f computable’. It is an important
transformation because we can solve the problems about ‘computing’ by using the knowledge on proof. It is also
remarkable that ‘g computable⇒ f computable’ can be written as ‘f non-computable⇒ g computable’.
Above are what we learn this week, and next week we may learn more interesting
theories on computing.
2014年11月14日星期五
2014年11月7日星期五
2014年10月31日星期五
2014年10月24日星期五
SLOG 6
This week is the week for us to learn the proof methods, and we finished the method ‘proof by cases’. And then professor introduced the concept of counting steps, which includes the worst case and the best case. Let us talk about proof by cases firstly.
Sometimes we have to prove some claims that have conclusive antecedents. For example, if we now have a claim with an antecedent like this: | x - y | = e, we have to consider it by cases, for we know few ways to prove directly by absolute value. So we split | x - y | = e into two cases:
x - y = e and | x - y | = -e. Then we prove in this structure:
Case 1： x - y = e
......
Case 2： x - y = -e
......
Then we have a lot of ways to figure out the claim, since we are familiar to the equation
x - y = e and x - y = -e, and we know plenty of ways to do transformation on them.
After that, we learned how to count steps. It is a tough part because we need to be careful or we will easily go on a wrong way. Counting the worst case is the most representative case of counting steps because it includes all the possibilities. Worst case is the situation that the algorithm has to run the largest times that it can run. For example, the worst case ①of the algorithm
def LS(A, x):
’’’
Return index i, x == A[i].
Otherwise, return -1
’’’
i = 0 ①
while i < len(A): ②
if A[i] == x: ③
return i
i = i + 1 ④
return -1 ⑤
If it is in the worst case:
It has to run once at step ①, twice at step ②, once at step ③, once at step ④, and once at step ⑤ if len(A) = 1.
It has to run once at step ①, three times at step ②, twice at step ③, twice at step ④, and once at step ⑤ if len(A) = 2.
It has to run once at step ①, four times at step ②, three times at step ③, three times at step ④, and once at step ⑤ if len(A) = 3.
......
So when len(A) = n, it has to run 1+( n + 1) + n + n +1 = 3n + 3 times.
Next week we are supposed to enter a new world of logic. Although until now I have no idea about how that world is, I cannot be more excited on exploring it!
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