Whale Box

任意一个类型与字符串相加自动转化成字符串

2011-09-28T18:12:00.001+08:00

I was doing code review, someone wrote something as the following.

It can totally build and it's the first time I know this.

int i = 1;

string s = i+""; //任意一个类型与字符串相加自动转化成字符串。没有直接调用C#类库，隐含间接调用的。

powershell script to replace strings in a file

2011-08-31T14:16:00.001+08:00

ReplaceStringInFile.bat

----------------

echo off

powershell.exe -command "Get-Content %1 | ForEach-Object {$_ -replace \"%3\", \"%4\"} | Set-Content %2"

timeout 5

----------------

托管与非托管的区别

2011-07-28T18:30:00.001+08:00

1.托管代码 (managed code)

由公共语言运行库环境（而不是直接由操作系统）执行的代码。托管代码应用程序可以获得公共语言运行库服务，例如自动垃圾回收、运行库类型检查和安全支持等。这些服务帮助提供独立于平台和语言的、统一的托管代码应用程序行为。

托管代码是可以使用20多种支持Microsoft .NET Framework的高级语言编写的代码，它们包括：C#, J#, Microsoft Visual Basic .NET, Microsoft JScript .NET, 以及C++。所有的语言共享统一的类库集合，并能被编码成为中间语言(IL)。运行库编译器（runtime-aware ompiler）在托管执行环境下编译中间语言（IL）使之成为本地可执行的代码，并使用数组边界和索引检查，异常处理，垃圾回收等手段确保类型的安全。

在托管执行环境中使用托管代码及其编译，可以避免许多典型的导致安全黑洞和不稳定程序的编程错误。同样，许多不可靠的设计也自动的被增强了安全性，例如类型安全检查，内存管理和释放无效对象。程序员可以花更多的精力关注程序的应用逻辑设计并可以减少代码的编写量。这就意味着更短的开发时间和更健壮的程序。

2.非托管代码 (unmanaged code)

在公共语言运行库环境的外部，由操作系统直接执行的代码。非托管代码必须提供自己的垃圾回收、类型检查、安全支持等服务；它与托管代码不同，后者从公共语言运行库中获得这些服务。

3.托管代码和非托管代码的区别

非托管代码：一般是直接与OS打交道.
托管代码：一般是委托中介（如.net framework 等）

所谓托管代码:

是指.Net下面编译为msil的一种字节码, 而非传统的编译语言编译入C,C++之流, 直接编译成二进制的可执行机器码.
就是说, 需要一个额外的解释器, 才能执行这种假的奇迹码. 在.net里面, 就是一个jit的编译器, 在执行的时候, 才编译成可执行的目标机器码, 才能真正执行起来.

这个概念类似于, java里面的那些.class文件, 需要jdk虚拟机才能执行起来是一个意思.

同样, 这个特性, 造成了一个很好的效果, 就是平台无关的特性.

Difference between Heap and Stack

2011-04-26T13:37:00.001+08:00

堆(heap)和栈(stack)有什么区别??

简单的可以理解为：
heap：是由malloc之类函数分配的空间所在地。地址是由低向高增长的。
stack：是自动分配变量，以及函数调用的时候所使用的一些空间。地址是由高向低减少的。

预备知识—程序的内存分配

一个由c/C++编译的程序占用的内存分为以下几个部分
1、栈区（stack）—   由编译器自动分配释放   ，存放函数的参数值，局部变量的值等。其操作方式类似于数据结构中的栈。
2、堆区（heap）   —   一般由程序员分配释放，   若程序员不释放，程序结束时可能由OS回收   。注意它与数据结构中的堆是两回事，分配方式倒是类似于链表，呵呵。
3、全局区（静态区）（static）—，全局变量和静态变量的存储是放在一块的，初始化的全局变量和静态变量在一块区域，   未初始化的全局变量和未初始化的静态变量在相邻的另一块区域。   -   程序结束后有系统释放
4、文字常量区   —常量字符串就是放在这里的。   程序结束后由系统释放
5、程序代码区—存放函数体的二进制代码。

二、例子程序
这是一个前辈写的，非常详细
//main.cpp
int   a   =   0;   全局初始化区
char   *p1;   全局未初始化区
main()
{
int   b;   栈
char   s[]   =   "abc ";   栈
char   *p2;   栈
char   *p3   =   "123456 ";   123456在常量区，p3在栈上。
static   int   c   =0；   全局（静态）初始化区
p1   =   (char   *)malloc(10);
p2   =   (char   *)malloc(20);
分配得来得10和20字节的区域就在堆区。
strcpy(p1,   "123456 ");   123456放在常量区，编译器可能会将它与p3所指向的 "123456 "优化成一个地方。
}
二、栈的理论知识
2.1申请方式
stack:
由系统自动分配。   例如，声明在函数中一个局部变量   int   b;   系统自动在栈中为b开辟空间
heap:
需要程序员自己申请，并指明大小，在c中malloc函数
如p1   =   (char   *)malloc(10);
在C++中用new运算符
如p2   =   (char   *)malloc(10);
但是注意p1、p2本身是在栈中的。
2.2
申请后系统的响应
栈：只要栈的剩余空间大于所申请空间，系统将为程序提供内存，否则将报异常提示栈溢出。
堆：首先应该知道操作系统有一个记录空闲内存地址的链表，当系统收到程序的申请时，
会遍历该链表，寻找第一个空间大于所申请空间的堆结点，然后将该结点从空闲结点链表中删除，并将该结点的空间分配给程序，另外，对于大多数系统，会在这块内存空间中的首地址处记录本次分配的大小，这样，代码中的delete语句才能正确的释放本内存空间。另外，由于找到的堆结点的大小不一定正好等于申请的大小，系统会自动的将多余的那部分重新放入空闲链表中。
2.3申请大小的限制
栈：在Windows下,栈是向低地址扩展的数据结构，是一块连续的内存的区域。这句话的意思是栈顶的地址和栈的最大容量是系统预先规定好的，在   WINDOWS下，栈的大小是2M（也有的说是1M，总之是一个编译时就确定的常数），如果申请的空间超过栈的剩余空间时，将提示overflow。因此，能从栈获得的空间较小。
堆：堆是向高地址扩展的数据结构，是不连续的内存区域。这是由于系统是用链表来存储的空闲内存地址的，自然是不连续的，而链表的遍历方向是由低地址向高地址。堆的大小受限于计算机系统中有效的虚拟内存。由此可见，堆获得的空间比较灵活，也比较大。
2.4申请效率的比较：
栈由系统自动分配，速度较快。但程序员是无法控制的。
堆是由new分配的内存，一般速度比较慢，而且容易产生内存碎片,不过用起来最方便.
另外，在WINDOWS下，最好的方式是用VirtualAlloc分配内存，他不是在堆，也不是在栈是直接在进程的地址空间中保留一快内存，虽然用起来最不方便。但是速度

也最灵活
2.5堆和栈中的存储内容
栈：在函数调用时，第一个进栈的是主函数中后的下一条指令（函数调用语句的下一条可执行语句）的地址，然后是函数的各个参数，在大多数的C编译器中，参数是由右往左入栈的，然后是函数中的局部变量。注意静态变量是不入栈的。
当本次函数调用结束后，局部变量先出栈，然后是参数，最后栈顶指针指向最开始存的地址，也就是主函数中的下一条指令，程序由该点继续运行。
堆：一般是在堆的头部用一个字节存放堆的大小。堆中的具体内容有程序员安排。
2.6存取效率的比较

char   s1[]   =   "aaaaaaaaaaaaaaa ";
char   *s2   =   "bbbbbbbbbbbbbbbbb ";
aaaaaaaaaaa是在运行时刻赋值的；
而bbbbbbbbbbb是在编译时就确定的；
但是，在以后的存取中，在栈上的数组比指针所指向的字符串(例如堆)快。
比如：
#include
void   main()
{
char   a   =   1;
char   c[]   =   "1234567890 ";
char   *p   = "1234567890 ";
a   =   c[1];
a   =   p[1];
return;
}
对应的汇编代码
10:   a   =   c[1];
00401067   8A   4D   F1   mov   cl,byte   ptr   [ebp-0Fh]
0040106A   88   4D   FC   mov   byte   ptr   [ebp-4],cl
11:   a   =   p[1];
0040106D   8B   55   EC   mov   edx,dword   ptr   [ebp-14h]
00401070   8A   42   01   mov   al,byte   ptr   [edx+1]
00401073   88   45   FC   mov   byte   ptr   [ebp-4],al
第一种在读取时直接就把字符串中的元素读到寄存器cl中，而第二种则要先把指针值读

edx中，在根据edx读取字符，显然慢了。

2.7小结：
堆和栈的区别可以用如下的比喻来看出：
使用栈就象我们去饭馆里吃饭，只管点菜（发出申请）、付钱、和吃（使用），吃饱了就走，不必理会切菜、洗菜等准备工作和洗碗、刷锅等扫尾工作，他的好处是快捷，但是自由度小。
使用堆就象是自己动手做喜欢吃的菜肴，比较麻烦，但是比较符合自己的口味，而且自由度大。

堆和栈的区别主要分：
操作系统方面的堆和栈，如上面说的那些，不多说了。
还有就是数据结构方面的堆和栈，这些都是不同的概念。这里的堆实际上指的就是（满足堆性质的）优先队列的一种数据结构，第1个元素有最高的优先权；栈实际上就是满足先进后出的性质的数学或数据结构。
虽然堆栈，堆栈的说法是连起来叫，但是他们还是有很大区别的，连着叫只是由于历史的原因。

双程计

2011-03-25T18:08:00.001+08:00

从google reader上看到的，挺逗的一篇

http://jacquesmattheij.com/A+tale+of+two+programmers

A tale of two programmers

Submitted by administrator on Wed, 03/09/2011 - 17:21.

When MSX and Atari ST were still 'hot', I contracted for a short while for a game company in the Netherlands, called Aackosoft, in Leiderdorp, a small town near The Hague. The reason it was only short was because the company failed spectacularly (the financial director came in one night and started shredding documents, I just packed my bag and left). Other than the management, the people working there were great.

We wrote interesting programs, the pay was OK (assuming you got paid), and the amount of knowledge floating around there was amazing. The designers were as good as I've ever seen, given the limited display capabilities of the various platforms available. For me, two people stood out: Steve and Chris, both from the UK. Because most of us had a very long commute, we slept 'on campus', one section of the building was something that is best described as a college dorm. After work we'd get together, order pizza or Thai food, talk shop and play games, sometimes our own games (Indy500, FlightDeck), sometimes those by competitors (does anybody even remember Gauntlet?).

Steve and Chris were as unalike as I've ever seen. Steve would toss out reams of code, sometimes creating the skeleton of a game in a few manic nights of coding and then he'd run out of steam to become slow as molasses. At roughly this point in time, Chris would enter the picture. He'd take the pile of work that Steve had done, and bit by bit, he'd clean it up and make it reliable and efficient. They knew each other so well that they didn't actually discuss the code much, it just got passed back and forth in this fashion until the job was done, usually in record time.

Their secret was obviously their complimentary characters and the fact that they'd grown up together, and had gotten to rely on the other guy 'having your back', as opposed to spending endless hours on transferring the knowledge Chris had been through this so many times that he knew quite well what to expect.

Today we'd probably call this 'pair programming', but it was pair programming in a way that was far more than the sum of its parts. Chris wouldn't be able to come up with an original work if his life depended on it. Steve would not be able to finish a job if you threatened to fire him. But as a team, they worked out splendid. They typically had their releases based on the same storyboards ready before we'd had the skeleton fleshed out.

Over the years, Steve had collected a whole encyclopedia of useful chunks of assembly code and he would beat these in shape just long enough for Chris to find his way.

Co-dependency amongst programmers. I've never seen it afterwards, and I don't really expect to see it ever again, it was one of those small things that remain as unique on the day that I first came across it as it is today.

But what I have seen is 'halves'. I've seen Steve's (I'm fairly strongly in his 'camp' when it comes to personality, when the engine works, I usually find it very hard to motivate myself to continue, that was the interesting bit for me), and I've seen Chris's.

Typically they wander around big companies looking for their soulmate, but they never ever run into them in a way that they recognize each other, or manage to hit it off on a personal level. But it makes me wonder if there isn't a use for a 'programmer dating service', where the Steve's and the Chris's of this world can meet up and achieve miracles that they alone would not be able to realize.

中文原文地址

http://www.aqee.net/2011/03/22/a-tale-of-two-programmers/

当MSX和Atari ST还很‘火’的时候，我在荷兰的一家叫做Aackosoft的游戏公司里短暂的就职过一段时间，这个公司位于Leiderdorp —— 离海牙不远的一个小镇。之所以短暂，原因是这个公司神奇的倒闭了(一天晚上财务主管一进来就开始粉碎各种文件，我只好拿起公文包离开了)。除了管理方面的问题外，这里工作的人都很不错。

要开发的程序非常有趣，这里的薪水还行(假如你是拿薪水过日子的)，开发过程伴随着大量的知识学问，让我惊叹不已。这里的设计人员都非常的优秀，他们让这不通用的显示效果能够在各种平台上使用。对于我，有两个人格外的吸引我：Steve 和 Chris，他们都是英国人。我们大部分人下班后都会一起坐一段很长的路程，我们住在“校园宿舍”里 —— 因为对这栋建筑的这个部分最好的描述就是校园宿舍。下班后我们就待在一起，我们叫了匹萨或泰国食品，聊天、玩游戏，有时是我们自己的游戏(Indy500, FlightDeck)，有时是竞争对手的(是否还有人记得Gauntlet？)。

Steve 和 Chris 这两个人极不相似。Steve 讨厌大量的编码工作，他有时会疯狂的花上几个昼夜的时间把一个游戏的框架搭建起来，之后他就会像泄漏气的脾气，行动慢慢腾腾，像个蜗牛。而大概就在这个节骨眼上，Chris入场了。他捡起Steve已经完成的那一大堆代码，一个字节一个字节的，规整清理，使之可靠、高效。他们之间是如此了解，根本不需要讨论哪段代码是干什么、为什么这样写，只是用这种方式来回交替的进行，直到任务完成，通常都是迅速顺利的搞定。

这其中的奥秘显然是得益于他们值得称赞的性格，长期共处培养出来的融洽，以及形成的一种依赖于对方的习惯，而不是相反的用大量的时间来相互传授自己的知识和用意。Chris 已经无数次的这样配合Steve，已经十分清楚的知道Steve想干什么。

如今我们也许可以称这为“结对编程”，而这种结对的方式产生的效果远超了他们两个作为单独个体的总和。Chris 如果一直依赖于这种工作方式，那他将不会有自己的原创作品。而Steve一旦失去了Chris，将不能完整的完成任何一个工作。可作为一个团队，他们做出了出色的东西。就像是他们在搭起骨架，填充内容之前，脑海中有了共同的图纸，这是他们能成功完成任务的基础。

数年里，Steve已经积攒了犹如大百科全书那样丰富的有用的程序代码，这些足够Chris用来发现他的思维轨迹。

这是程序员中的合作依赖。之后我再也没有遇到这种情况，我也并不是真的想盼望看到这样的组合出现，这只是那些日子里能让我感到独特、至今回忆的一件小事，就像发生在昨天。

我所看到的是一种‘热情’。我看到了Steve的 (从个性上来讲，我更喜欢他，但当我发现有趣的事情时，我却不能像他那样富有激情的工作)。我看到了Chris的。

他们曾徘徊在各大公司里寻找他们的精神伙伴，但从来没有遇到这样能够相知、能超出工作范畴、从个人角度上相互接受的人。这让我产生奇想，也许应该有个“程序员约会服务系统”，像Steve和Chris这样的人能够遇到一起，一起合作创造出他们各自独自根本无法想到的奇迹来。

求最大公约数（欧几里德算法）

2011-01-30T14:07:00.002+08:00

求最大公约数的欧几里德算法，也称作辗转相除法，如下：

int GetGCD(int m, int n)
{
if (n = 0)
{
return m;
}
return GetGCD(n, m % n);
}
(GCD = Greatest Common Divisor)

比如
GetGCD(18, 24)
-> GetGCD(24, 18)
-> GetGCD(18, 6);
-> GetGCD(6, 0);
-> return 6;

----------------------------------------

另外，最小公倍数 = 两数之积 / 最大公约数
所以 GetLCM(m, n) = m * n / GetGCD(m, n)
(LCM = Least Common Multiple)

比如
GetLCM(18, 24) = 18 * 24 / 6 = 72

The two egg problem solution (copy-pasted from http://classic-puzzles.blogspot.com)

2011-01-24T18:59:00.001+08:00

Google Interview Puzzle : 2 Egg Problem

My intention here is not to trouble Google interviewers. I was just collecting some classic puzzles and found this one and a small Google search showed me that this is a Google interview puzzle to my pleasant surprise. But many of the answers I found were either wrong or totally twisted. I am making no surety of the answer I give and I am open to your remarks or suggestion or corrections.

The Standard Problem in simple writing goes like this:

* You are given 2 eggs.
* You have access to a 100-storey building.
* Eggs can be very hard or very fragile means it may break if dropped from the first floor or may not even break if dropped from 100 th floor.Both eggs are identical.
* You need to figure out the highest floor of a 100-storey building an egg can be dropped without breaking.
* Now the question is how many drops you need to make. You are allowed to break 2 eggs in the process

If you are one of the people who likes to solve a puzzle before seeing the answer you must quit the blog now and come back later for checking the answer.

Now that this is a Google interview question I am taking the normal "Interview-Style" of solving a problem. Simply saying thinking aloud through the solution from worst to the best correcting the flows optimizing the solution or taking the 5-minute hard thinking acting pause to a problem, which you know already and just want to make your interviewer think that you are a challenge lover.

Solution

Drop the first egg from 50.If it breaks you can try the same approach for a 50-storey building (1 to 49) and try it from 25th floor. If it did not break try at 75th floor. And use linear search with the remaining portion of storey we need to test. For example if the first egg breaks at 50 we need to try all possibilities from 1 to 49.

Now this looks a feasible solution. In computer student's jargon do a binary search with first egg and linear search with the second one. Best case is log (100) and worst is 50.

Now the optimal solution for the problem is that you figure out that you will eventually end up with a linear search because you have no way of deciding the highest floor with only one egg (If you broke one egg and you have to find the answer among 10 all you can do is start from the lowest to the highest and the worst is the total number of floors). So the whole question grinds up to how to make use of the first egg to reduce the linear testing of the egg.

(For strict computer science students, well this problem can be solved using binary search on the number of drops needed to find the highest floor.)

Now let x be the answer we want, the number of drops required.

So if the first egg breaks maximum we can have x-1 drops and so we must always put the first egg from height x. So we have determined that for a given x we must drop the first ball from x height. And now if the first drop of the first egg doesn't breaks we can have x-2 drops for the second egg if the first egg breaks in the second drop.

Taking an example, lets say 16 is my answer. That I need 16 drops to find out the answer. Lets see whether we can find out the height in 16 drops. First we drop from height 16,and if it breaks we try all floors from 1 to 15.If the egg don't break then we have left 15 drops, so we will drop it from 16+15+1 =32nd floor. The reason being if it breaks at 32nd floor we can try all the floors from 17 to 31 in 14 drops (total of 16 drops). Now if it did not break then we have left 13 drops. and we can figure out whether we can find out whether we can figure out the floor in 16 drops.

Lets take the case with 16 as the answer

1 + 15 16 if breaks at 16 checks from 1 to 15 in 15 drops
1 + 14 31 if breaks at 31 checks from 17 to 30 in 14 drops
1 + 13 45 .....
1 + 12 58
1 + 11 70
1 + 10 81
1 + 9 91
1 + 8 100 We can easily do in the end as we have enough drops to accomplish the task

Now finding out the optimal one we can see that we could have done it in either 15 or 14 drops only but how can we find the optimal one. From the above table we can see that the optimal one will be needing 0 linear trials in the last step.

So we could write it as

(1+p) + (1+(p-1))+ (1+(p-2)) + .........+ (1+0) >= 100.

Let 1+p=q which is the answer we are looking for

q (q+1)/2 >=100

Solving for 100 you get q=14.
So the answer is: 14
Drop first orb from floors 14, 27, 39, 50, 60, 69, 77, 84, 90, 95, 99, 100... (i.e. move up 14 then 13, then 12 floors, etc) until it breaks (or doesn't at 100).

Please feel free to correct or post any comment on the solution or the answer.

0/1 KnapSack problem in C#

2011-01-24T17:14:00.001+08:00

The following program find a best solution in 0/1 KnapSack problem, but it does not pick all the best solutions.

public static int CalculateBagProblem(int BagVolumn, List<int> items, out List<int> chosenItems)

{

chosenItems = new List<int>();

if (items.Count == 0)

{

return 0;

}

else if (items.Count == 1)

{

if (items[0] <= BagVolumn)

{

chosenItems.Add(items[0]);

return items[0];

}

else

{

return 0;

}

else

{

// without the first item

List<int> remainItems = items.GetRange(1, items.Count - 1);

List<int> chosenItemsInRemainItems = new List<int>();

int withoutFirstItemResult = CalculateBagProblem(BagVolumn, remainItems, out chosenItemsInRemainItems);

// with all the items

int withFirstItemResult = 0;

List<int> chosenItemsInItems = new List<int>();

if (BagVolumn >= items[0])

{

withFirstItemResult = CalculateBagProblem(BagVolumn - items[0], remainItems, out chosenItemsInItems) + items[0];

chosenItemsInItems.Add(items[0]);

}

// select max from the two results

if (withoutFirstItemResult >= withFirstItemResult)

{

chosenItems = chosenItemsInRemainItems;

return withoutFirstItemResult;

}

else

{

chosenItems = chosenItemsInItems;

return withFirstItemResult;

}

Example of the Locus Control Test

2010-12-30T17:07:00.001+08:00

Locus of control refers to how a person perceives the cause of life events. Someone with an internal locus of control would generally perceive himself or herself as responsible for certain occurrences (his or her actions would have a direct bearing on the result). On the other hand, a person with an external locus of control would most often blame (or thank) fate, destiny, luck, society, or some other force beyond his or her control.

Snapshot Report

Success Orientation

You have a mixed attribution style when it comes to success. Sometimes you interpret your success as a result of your skills, intelligence, nice personality, etc. Other times, you attribute it to external factors, such as luck, ease of task, or other people's help. As a consequence, you don't always take the credit you deserve. Your self-esteem, motivation, and general well-being would most likely be improved if you realized that you actively influence positive events in your life.

How to hide Thinking at Work so that the Non-Programmers don't suspect Slacking?

2010-12-29T13:50:00.001+08:00

222 down vote favorite

116

Better programmers than me can write in essays about walking around with a coffee mug and call it programming. And it's perfectly accepted at a place that knows the business. Or see what Gregory House (TV show "House M.D.") does when he is thinking.

But what about the other places where you are the only programmer?

If you don't stare at boring stuff on the monitor for 8 hours straight, co-workers suspect you being a slacker. Yes, not the managers who see the output. Only the co-workers who see the process and can't relate to this kind of work.

Yesterday I had to explain to a trainee of some other profession that software development is like flying. The explanation from the Hitchhiker's Guide to the Galaxy. I don't think she bought it.

edited Mar 31 at 20:02

community wiki

10 revs, 6 users 85%
stesch

Seriously? Why the 3 close requests? At the moment there are 9 answers, with most of them upvoted. People are interested in this question/topic. – stesch May 1 '09 at 13:39

This might be better as a community wiki question? – James McMahon May 1 '09 at 15:25

If it gets closed it's an automatic reopen vote from me. – cletus May 1 '09 at 23:50

Note: according to Jeff this is programming related blog.stackoverflow.com/2009/04/… "What is a programming related question? Here's a solid set of guidelines generated by the SO community itself: ... Questions about social engineering, management, or career building, ergonomics, or other "soft" topics related to development work." – cletus May 2 '09 at 17:28

rofl, to paraphrase the question "how do I hide thinking at work, because thinking is discouraged by my employer" – STW May 2 '09 at 19:24

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locked by Michael Myers♦ 12 hours ago

35 Answers

active newest votes

up vote 145 down vote accepted

It's funny you ask this question because just yesterday I had a client blow up at a colleague and I who were discussing Google Analytics and Macbooks. Now this client gets charged for our time and we both exclude such time from our timesheets but such breaks are actually important: you can mentally recharge and it can help to work through problems and so on.

Now I put people into two categories:

Process-oriented: these people are concerned with how you do things. Do you turn up for work on time? Is your desk neat? Have you filled out your weekly status report? And so on; and
Results-oriented: within reason, these people don't care how you do something, they just care that you do it.

I am firmly in the second category and I have a real problem with people in the first. In my experience, people in the first category seem to suffer from insecurity. It's a fundamental psychological principle that controlling your environment makes you happy and such people, who are faced with something where they feel out of control or don't know how to achieve the best results, resort to controlling their environment by dictating how you do things.

You're right in that this is particularly problematic for non-programmers when dealing with programmers. They often just don't understand what we do and how we do it, like how things can take longer than estimated and so on.

Yesterday's case was even worse because this same guy would sit with a colleague and discuss the house she's buying and other things in the middle of doing his own work (and he's charging his clients for his time and I'm sure he's not charging for such downtime), which I found particularly galling as a real double standard on downtime.

So how do you deal with it? Preventively. Try and associate with results-oriented people by choosing the right job, staying in a good job, leaving a bad one, hiring the right people and so on. There will be a point where you'll simply have to put up with such nitpicking however. You can try and explain how the process doesn't work where you just sit there and stuff happens in some linear fashion but in my experience more often than not non-programmers just don't get it and you're wasting your breath and it'll sound like you're just trying to make excuses for slacking off.

In my case, as a consultant, I'm simply going to finish the current project (which is soon thankfully) and then respectfully decline any future work as I've already got more in the pipeline than I can already do.

answered May 1 '09 at 13:21

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cletus

I completely agree. I used to work for one client that would complain about the amount of times I showed up an hour or two after everyone else, but wouldn't consider the fact that I leave four or five hours after everyone else and that I produced more results in less time than the permanent staff. Results-Oriented people tend to be a joy to work with, process-oriented people [in my experience] tend to nit pick and micro-manage and drive me crazy. If you want the job done exactly your way, by all means go ahead and do it, otherwise go away and let me do what you hired me for. – BenAlabaster May 1 '09 at 13:30

I'm with you both. Also had a month ago a quarrel about me arriving an hour or so after everyone else. When I said I stay correspondingly longer in the evenings they told me that nobody actually sees me do that. Between the lines I got they don't trust me. Suggestions to check out Windows logs or introduce any other kind of observation were declined however. And yes, I'm also basically the only developer there. – User May 1 '09 at 15:38

Fair points, but it smells of a bit of a rant to me. You also exhibit the classic programmer need to divide everything into black/white, 1/0... when talking about Process/Results oriented. If you're dealing with anyone of average or better intelligence, it often becomes very obvious to them that they've been "pigeon holed" and is a sure fire way of degrading a working relationship. In fact, the act of pigoen holing is itself a way of reducing the complexity of human interaction, ie "controlling your environment". Hmmm... Does that make you Process or Results oriented? ;) – Ash May 2 '09 at 6:36

I think it's fine if results-oriented boss leans toward being process-oriented one if results are dissapointing. – Arnis L. Jul 21 '09 at 18:22

while i would lean more towards the second category, i cannot see this as an either-or, mutually-exclusive grouping. yes, granting folks the autonomy and freedom they need to achieve the results is very important as it liberates people. But at the same time, caring on about results alone can lead to compromises to mandatory standards, ethics, security, or safety requirements, etc. Those items belong to the process-oriented category. And i have seen such compromises happen. There has to be a balance for these work practices. – icelava Jul 28 '09 at 6:35

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up vote 211 down vote

One solution could be this:

During their lunch break get them to do a simple task like as a crossword. Ask them to be conscious of the amount of time they spend reading/writing vs. the amount of time they spend thinking [or looking up the answer]. Tell them that this is exactly the same as the time you spend reading/typing vs. the amount of time you spend thinking and looking up answers.

Better still Sudoku because it can involve hours of trying to figure out where you went wrong and why none of your numbers add up. So while the task itself seems relatively easy, after all, it's just numbers in boxes it can take time. Get them to predict how long it'll take them before they start and see if their prediction is right - guaranteed it won't be. You can hit them with a double whammy for why your time expectations never quite add up either.

This is the only way I can really think of to get them to understand the way engineers work. I see lots of "those types just don't get us types" - people are adaptable, people can understand things if presented in a fashion they can understand, it's just that nobody's ever taken the time to present them with an argument they get.

edited Jul 22 '09 at 17:54

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5 revs
BenAlabaster

I really like this explanation. I'm going to use it when needed. – Sandor Davidhazi May 6 '09 at 22:35

Wicked analogy! +1 – John MacIntyre May 7 '09 at 18:23

That is a fantastic analogy. I'm going to have to remember that. – Colin Cochrane Jul 21 '09 at 17:41

The real question should be: How should non programmers in the office hide gossipping about American Idol and other such crap so that us programmers don't suspect slacking! – BenAlabaster Aug 10 '09 at 16:33

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up vote 164 down vote

Just let your build scripts run, see lots of command lines spewing thousands of useless trace messages, and you're all good...

answered May 1 '09 at 14:52

community wiki

Yuval A

Must... resist... urge... to... upvote... – Michael Myers♦ May 1 '09 at 15:09

@mmyers - don't worry, I've got ya covered +1 :P – BenAlabaster May 1 '09 at 15:15

BRB- building screensaver of never-ending compiler output – Graphics Noob Aug 26 '09 at 20:53

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up vote 113 down vote

Years ago I had a gig writing some "Business Basic" stuffs. I was teamed up with a rather "brilliant" programmer with a strange work flow..

He would sit at his computer.. for half to 3/4's of the day.. and play doom / quake / wolfenstine 3D (he was really into the FPS). when he had enough, He'd fire up the editor and just type. At the end of the day, whatever he wrote.. was gold.

We had a new account manager start with the company that walked in on him playing one morning and in dealing with her, was not very polite.

She complained to the CEO that "one of those programmers isn't doing any work at all but playing those violent video games". To which the CEO replied to her "YOU DIDN'T DISTURB HIM DID YOU!?!?".

The games helped him think. He designed, wrote, tested and debugged all of the code in his head while he was playing. Once he was done, it was just a matter of brain dumping and getting it all out.

answered May 1 '09 at 14:15

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datacop

That's ridiculous and unprofessional. – Tim May 1 '09 at 14:18

Upvote not because I agree with the attitude, but just because I love the story. :-) – T.E.D. May 1 '09 at 14:19

@Tim - Maybe he gets paid to produce good code (rather than to strictly 'think and code'). If he produces enough golden material, then he's doing his job. – StuffMaster May 1 '09 at 21:40

Thinking isn't something you can do for eight hours straight and still be productive. Downtime is a vital part of the cognitive process -- it's when your brain gets a chance to rearrange what it already knows and spot correlations it couldn't while under load. How many of us have come up with some of our best ideas in the shower? If this programmer knows how and when to take their downtime, more power to them. Sounds like it works. – Joe White May 2 '09 at 19:38

Was this programmer's surname Carmack? – Arec Barrwin Oct 16 '09 at 15:40

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up vote 44 down vote

Why, leave something verbose running on the terminal, of course.

answered May 1 '09 at 13:23

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kch

I've actually had my boss walk by my desk while doing some SVN dumps and he said "That's what a programmers screen is supposed to look like" It hurt a bit, but now I have an easy "I'm busy!" sign. – Wally Lawless May 1 '09 at 13:41

@Power-coder: You mean a programmer's secondary screen isn't supposed to be permanently etched with a browser window displaying the StackOverflow website? – BenAlabaster May 1 '09 at 14:01

One well written line of code can replace a thousand bad ones. – Sneakyness Jul 26 '09 at 16:16

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up vote 38 down vote

Take a walk

I've found that it's more the appearance of not "working" than anything else. If I leave my desk for a few minutes and walk around outside no one thinks anything of it. Much different than sitting at your desk looking idle.

answered May 1 '09 at 14:48

community wiki

Alan Jackson

I agree. It's a perception thing. Just sitting is always lazy. But moving either fingers or legs convinces people you're /really/ working. – Matthew Flaschen May 2 '09 at 0:46

Out of sight, out of mind. – Walt Gordon Jones May 2 '09 at 20:22

ps walking around with a piece of paper in your hand = working in most places. – Martin Beckett Jul 8 '09 at 20:30

MGB is right. I got away with wandering the halls in High School for a very large amount of time by simply walking around with paper. – Sneakyness Jul 26 '09 at 16:17

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up vote 36 down vote

Here's a solution from commandlinefu.com:

cat /dev/urandom | hexdump -C | grep "ca fe"

It will make some data scrolling off the terminal.

edited 20 hours ago

community wiki

2 revs
Olivier Lalonde

That's what I appreciate, a command-line solution to any programmer's problem! – thrashr888 23 hours ago

Did you mean hexdump -C < /dev/urandom | grep "ca fe" – Sam 18 hours ago

Add | pv -q --rate-limit 75 for some extra slowness. – Cristian Ciupitu 18 hours ago

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up vote 32 down vote

How about thinking on the lav (the john)?! Of course it limits you to one thought session a day unless you don't mind people thinking you have diarrhea

edited May 1 '09 at 22:20

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3 revs, 2 users 78%
Chris S

lol +1, I do some of my best thinking on the loo. It's the only time I'm not constantly interrupted by coworkers asking retarded questions I don't have time to answer. – BenAlabaster May 1 '09 at 13:37

Works at home, too. Unless you have toddlers constantly banging on the door. – Even Mien May 1 '09 at 13:40

My office is noisy. I use this technique surprisingly frequently during the daily, shouted political argument going on one aisle over. The important thing is finding the lavatory in the basement or up a floor that's less-frequented. (Fewer distractions.) – Greg D May 1 '09 at 14:21

I had one place where I'd do that multiple times a day, because the handicapped stall was bigger than my cubicle. :-) – T.E.D. May 1 '09 at 14:21

The paper in the lavatory isn't so good for taking notes ... and let's not talk about the pen. – JeeBee May 1 '09 at 15:30

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up vote 30 down vote

Think on paper, i.e., make a note of your mental thoughts. I find diagrams make things a lot clearer for me when thinking anyway, so it's a win-win.

answered May 1 '09 at 13:04

community wiki

JeeBee

Paper is so passé, get a whiteboard... – BenAlabaster May 1 '09 at 13:52

@balabaster, ii actually prefer paper for it is much more portable and scaleable (On a whiteboard you have to erase everything when it's full, on paper you just get a new paper) – Pim Jager May 1 '09 at 14:30

@Pim Jager - Understandably - I think in this day and age, I think we need to come up with electronic white boards that just dump the contents to file and then sync with the computer when you connect it up. Something lightweight enough to carry to the board room if necessary. – BenAlabaster May 1 '09 at 14:39

That's it, now I want one of these: e-beam.com/products/whiteboard.html – BenAlabaster May 1 '09 at 14:43

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up vote 25 down vote

Pull out some paper and scribble technical-looking stuff on it. Then when you're thinking, hold your pen and have one hand on the paper. Occasionally add something to the paper.

If you're working on hard problems, you'll probably need a pen and paper to assist your train of thought anyway.

answered May 1 '09 at 13:05

community wiki

Nathan Ridley

This "pen and paper" you speak of -- can you explain what it is and how it works? – Gabe yesterday

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up vote 15 down vote

Pretending you're working on something that's physical, not mental, is a short term solution, I think.

You'd better teach your co-workers that thinking takes most part of the process of programming. Of course, it's a long term solution that may show no value on the first few weeks - or months - but it will surely pay off.

They'll even leave you alone when they see you're quiet, with a mug of coffee in your hand.

Leave him there, they'll say, he's doing his best.

answered May 1 '09 at 13:19

community wiki

Mario Marinato -br-

+1 Exactly, why try to pretend you're working. That's generally the stance someone who isn't working takes. Just do what you do! – Robin Day May 1 '09 at 13:24

up vote 13 down vote

I honestly don't think you can. Sure, you can "pretend" you're working by scribbling, having technical websites open. But if you're doing that, you're not doing the actual "thinking" bit that gets the work done.

I'd stick to worrying about how you get your work done best and not trying to appear to be working to others. If it matters to them they will know the truth.

answered May 1 '09 at 13:16

community wiki

Robin Day

up vote 13 down vote

Why do you even think you need to hide the fundamental part of your job as a programmer, ie thinking, from co-workers?

If a co-worker says "Wow! You really don't seem to do much each day, do you?", just explain, in a good natured way, what you are actually doing when they notice you staring off into the distance.

If they continue to have a problem, WHO CARES! Just let the responsible manager deal with it. Of course this relies on the fact that your output is actually acceptable.

This is exactly how I have dealt with this sitaution myself in the past. If someone just doesn't like you, you are not change their views, but most people are simply curious.

A programmer that believes hiding and being deceptive to colleagues about what it they do, will always have difficulty dealing with non-programmers.

edited May 2 '09 at 12:09

community wiki

2 revs
Ash

up vote 12 down vote

Have your eyes closed and when someone walks up to you, say "Amen".

answered May 1 '09 at 13:36

community wiki

Even Mien

and put a crucifix on your wall and get a prayer mat too... or whatever your religion dictates. A sure fire way never to be pestered by anyone ever again. Especially if your religion is of a non-mainstream nature :P – BenAlabaster May 1 '09 at 14:05

May the sauce of the FSM lead you to enlightenment. – nilamo Aug 27 '09 at 5:32

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up vote 12 down vote

I recall the movie The Firm when Gene Hackman tells Tom Cruise that if he is even thinking about a client, it's billable time. If it's good enough for a lawyer...

answered Aug 26 '09 at 20:29

community wiki

Jeff O

My employer couldn't pay me enough if we would handle it the same way. Programmers are constantly trying to learn and improve themselves. I've ideas in the shower before work, but can't put shower time on the time sheet. – stesch Oct 31 '09 at 13:18

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up vote 12 down vote

Do you really have to do this (I mean explanations)? I know it's tough times, etc. but think of finding some place else when you can.

According to your question several things are wrong with your place of work:

Other people (including peers) should have implicit respect to what you do;
Other people should not be able to observe you all the time;
You being concerned with what other people think of you is counter-productive;
"Flow" is a critical process for software development and you are clearly in environment that doesn't embrace this process.

Pick up Peopleware by DeMarco and Lister to read about these and other things that define and explain right teams and places to work.

edited Aug 10 at 3:21

community wiki

3 revs
grigory

up vote 10 down vote

I worked for a couple years for a small company as the sole developer. I know for a fact that they thought I was just slacking off when they'd pass by my door and see me on the internet looking something up, or reading a book like Pragmatic Programmer; and even when I was actually writing diagrams related to the current workload.

In short, I don't think it is possible for someone unfamiliar with programming practices to understand what we do. Anymore than it is possible for someone unfamiliar with engines to see a mechanic just standing there staring under the hood, and understand that the guy is actually working.

answered May 1 '09 at 18:33

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hmcclungiii

Yes, I had negative comments in a job once because coworkers saw me sitting around reading "magazines". Like Dr. Dobbs, Programmer's Journal, Proceedings of the ACM. – Cyberherbalist May 1 '09 at 18:51

@Cyberherbalist: The kind of coworkers who can't learn anything by themselves? – stesch May 2 '09 at 0:30

About reading Pragmatic Programmer at work: it's like an automechanic reading "Basic car care" at work instead of fixing cars. – simon Oct 7 '09 at 17:17

The OP didn't mention reading Pragmatic Programmer, so your comment is a straw man argument. A more appropriate analogy is that of an automechanic reading a reference manual about car engines at work when stumped, and I think it's a very good thing. – Seun Osewa 22 hours ago

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up vote 9 down vote

What I hate is when people see you browsing the internet and think you're slacking off. A key part of expectations or perception management is to not have your monitor facing a busy thoroughfare. I hate people walking behind me as a general rule anyway.

answered May 2 '09 at 19:20

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Jordie

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up vote 8 down vote

Program in Java. Then you'll have to do a lot more typing. Or, if you're already programming in Java, well, hmmm...COBOL, maybe?

answered Jun 7 '09 at 0:18

community wiki

Curt Sampson

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up vote 7 down vote

Get a whiteboard and scribble some ideas on it while you're thinking. I find it helps me structure my ideas better than just walking around while thinking.

answered May 1 '09 at 13:29

community wiki

hammar

I don't have a whiteboard in my cubicle at this client, but I've been pestering them for one for ages. Having a whiteboard is great for diagramming random ideas - a great thought processor. – BenAlabaster May 1 '09 at 13:38

Absolutely. The same managers who demand you work also get very excited when they see people writing things on whiteboards viewing it as a sign of creativity, planning and communication. I once had a manager who when we had clients in demanded that the team sit around a whiteboard pretending to discuss stuff so the environment would seem dynamic... Terrifying but true. Still, in her defence she was generally a pretty good manager other than that. – Jon Hopkins May 1 '09 at 13:45

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up vote 6 down vote

I always come running back from the toilet, and say I got a great idea while I was thinking there.

The worst part: it is even true, I just make a show out of it. Do the same with coffee break, just break of mid-phrase if you get an idea etc.

answered May 1 '09 at 22:34

community wiki

Marco van de Voort

up vote 6 down vote

I've seen this one. We have an internal IM system where I work. Last year, word came to us (from our boss, as a friendly warning) that people in other departments were looking at the IM client to see our status (if we were "away" or not) and using that to determine that we were slacking off.

So we set our away timeouts to be very high, so it looks like we're always busy, which we usually are.

Between watching programs run that may take time, reading stuff on screen, talking to other programmers next to you, etc... it can look that way.

I don't worry about, really. That's how I work (and the others around me too). That just the way things work in our department. That metric can work with some jobs (i.e. % of time in a call for a call center employee), but it doesn't work for everyone.

What can you do about it? I wouldn't do much. I like the crossword suggestion above. If you are worried about others opinions, I wouldn't be. If they are complaining/making remarks, you can try being nice (the crossword thing) but if it continues you could simply talk to you manager asking for people to basically be informed "he's doing his job, let him be". It's not the job of the clerk 3 desks over to monitor how hard you're working.

The people who watch this kind of thing are usually the same people who are slacking themselves (or at least worried they are, such as a workaholic).

As long as your boss knows you're doing a good job and doesn't think you're wasting the company's money, you should be fine.

answered Aug 26 '09 at 20:45

community wiki

MBCook

up vote 5 down vote

Write your thoughts on a paper, so they see that you are working !

answered May 16 '09 at 9:58

community wiki

Adinochestva

up vote 4 down vote

Usually what I do is I'll leave something on my computer screen (query in progress, report, data table, etc.) and i'll play with my rubik's cube while periodaclly looking at the screen.

answered May 1 '09 at 14:44

community wiki

DForck42

yes...gotta have screen full of windows with things so complex it always looks like your working. Until they notice web browser and you're typing a comment on SO...ohhh shit. – dotjoe May 1 '09 at 15:26

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up vote 4 down vote

Sometimes when I have a difficult problem, like everything I've tried just isn't working, I lean back in my chair and close my eyes. Guess what that looks like.

answered May 1 '09 at 14:54

community wiki

Robert S.

Some times I do that and wake up slightly alarmed when a co-worker wakes me up with some random question. Closing your eyes is dangerous business. – kch May 1 '09 at 15:01

The last job I worked at, I had the same thing - I was leaned back, eyes closed, thinking. Boss walks into my cube, quietly. She says my name and I jump a little - wasn't expecting the interruption. Later that day, my supervisor calls me over and tells me the boss is going to have her "eyes on me" because of the situation. And she was a programmer in the past. Apparently, she's able to think just fine while coding - different strokes for different folks, I guess. – Knobloch May 1 '09 at 18:30

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up vote 4 down vote

I think it's important to distinguish between accepted forms of "thinking" and less conventional methods like some of the ones above (playing FPS games etc). Most workplaces expect some degree of professionalism, and while playing games might be the most effective method for you, society doesn't generally accept that as professional behaviour (yet ;) ).

Usually I just leave the CLI for a linux server open on one screen - most people see that and run.

answered May 1 '09 at 15:22

community wiki

Matt

If you can't do even that, take a few screenshots of the command line on your home computer and bring them in to work. :) – Barry Brown May 2 '09 at 1:08

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up vote 4 down vote

If they don't affect your getting a paycheck, what does it matter what they think?

answered May 1 '09 at 15:34

community wiki

johnny

If enough people think you are slacking off, eventually management would be forced to do something, which could affect you paycheck. – Rob Z May 1 '09 at 17:14

Even if management knows you're not slacking, it's often easier for them to force you to change your behavior than force everyone else to mind their own business. – patros May 28 '09 at 16:04

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up vote 3 down vote

If you're the only programmer in your division, it's a pity. Otherwise you could write mini-documents like a model overview - anything high-level - to help you with your implementation thougts.

revise your own thoughts
provide a written document as basis for possible "stand-up" reviews with fellow developers
aggregate artefacts for later detailed documentation purposes (which mostly are required in not-so agile companies)

answered May 1 '09 at 14:49

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msiemeri

up vote 3 down vote

You can run your test cases in selenium IDE. x 100

answered May 1 '09 at 14:51

community wiki

drikoda

up vote 2 down vote

My strategies:

Bring up some gnarly code in Emacs, and stare in the general direction of the screen.
Take a walk.

The problem with the second approach is that if a thought strikes that requires looking something up, you are often a minute or more away from your workstation. Also, I often bump into someone on the walk I need to talk to. That isn't nessecarily a bad thing, but it doesn't help with the task at hand. Still, you end up learning something that you needed to learn. Consider it a holistic development technique. :-)

answered May 1 '09 at 14:16

community wiki

T.E.D.

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不合时尚的追求- Freeman J.Dyson (转载自水木)

2009-05-11T20:11:00.001+08:00

发信人: happyzhe (good boy), 信区: AI
标题: 转文：不时兴的人和不时兴的思想，常常对科学的进步有决定性的意义
发信站: 水木社区 (Sun Apr 5 16:50:47 2009), 站内

不合时尚的追求

Freeman J.Dyson

   一、引言今天，我很高兴以高等研究所代表的身份，向Ｈumboldt基金会的会友讲话，因为高等研究所和Humboldt基金会都在努力支持国际范围的科学研究，又都面临着同样的困境和难处。我们正试图坚持150年前von Humboldt所开创的传统。为了对von Humboldt有所了解，我查阅了1910年版的不列颠百科全书，看到科学史家Ａgnes Clerke写的极漂亮的文章，如果你查以后的版本，则只能读到Clerke文章的片断。Clerke在文中描述了von Humboldt建立第一个国际气象和磁力观测网的工作，结尾铿锵有力："国际间的科学协作，乃是现代文明最富丽的硕果，而正是Humboldt的努力，成功地促成了第一次合作。"高等研究所和Humboldt基金会正以von Humboldt为榜样，尽力在我们自己的时代，加深和扩大国际间的科学协作。

   二、科学研究的时尚我决定谈谈科学中的时尚问题，因为对于科学，特别是对于高等研究所和Humboldt基金会，这是个严肃而日趋重要的问题，我首先谈在高等研究所里看到的时尚；然后讲我们能从跨越漫长时期的科学史中吸取的教训；最后，就今后如何更明智地对待时尚说几句话。

   有种说法总是对的，而且在今天比以往任何时候都更加真切，即：对于能力一般的年轻科学家，最聪明的办法是追随占优势的时尚。任何一名青年科学家，要是没有杰出的才华，也没交上难得的好运，他首先关心的是找到一项工作并保有它。为此，他必须涉足于某个科学领域--它是控制着职业市场的、占据高位和有影响的权威们感兴趣的，并从事一项自己能胜任的工作。这些权威认为重要的科学问题，几乎就可以定为合时尚的问题。当然，给予工作的权力，在今天一般不由单个权威掌握，而由一个权威组成的委员会控制。但是，跟个人相比，委员会更难从一个时代的潮流中解脱出来。所以，关心自己生存的的青年科学家倾向于顺着踏就的路前进，这是毫不奇怪的。那些第一流的高级学术机构，向能轻车熟路跟随时尚的人提供保证，给予升职晋级，对不追随时尚者则只提供极少的机会。

   我们研究所也不例外，三十四年前，我首次来这里作访问成员。当时主要的权威是Robert Oppenheimer。他决定物理学中的哪些领域值得搞，他的口味总是跟当时最时兴的方向吻合。我那时年纪轻轻、雄心勃勃，拿着一篇讨论时髦问题的急就篇找到他，很快得到了一个永久的职位。这是那时的状况，今天也依旧如故。有些了解研究所历史的人可能反对上述看法，他们会说，研究所毕竟也给了Kurt Gödel 一个永久职位，情况确是如此。Gödel乃是本世纪少有的几个名不虚传的天才之一。在我们的同事中，他是唯一能跟Einstein以平等地位一起散步、聊天的人。Gödel从事非常深刻但不合时尚的一个数学领域的研究。随着年龄的增加，他显得更加赶不上潮流。我们研究所有理由为给他在教授会提供席位而骄傲。只有一个事实使这和光荣减色：Gödel自来研究所生活和工作，从普通成员升到教授竟花了十四年时间。Gödel有如此的独立和潮流精神，才使得我觉得，研究所在经历十四年的踌躇之后，终于使他成为一名教授，总算也是值得一提的一点功劳吧。晚做总比不做强！

   今天来研究所工作的青年物理学家，比起三十年前的我，受到更大的压力。首先，他们多半是靠跟政府的合同得到钱的，合同约束他们在确定的时间内从事指定科学领域的研究。当然，我们不必过份从字面上理解“合同”这个措词。管理合同的国家科学基金会和能源部的官员都是理智的，允许我们对所承担的义务作带点伸缩性的解释。如果研究所内某些靠合同挣钱的成员，打算搞跟合同无关的课题，那时没有人会强迫我们把这些人赶到大街上去。有些人的兴趣所在不适于签入合同，他们的工作一般就由研究所基金会支持。但不管怎么说，合同仍是严肃的，具有约束力，它从总体上规定了研究所物理部的访问成员应积极从事的工作领域。合同确定了物理学的主流应该是什么。我们对邀请来工作的成员，必然要求他们的工作能容易地纳入这一项或那一项合同之中。

   三十年后的今天，我也成了权威中的一份子。我努力鼓励年轻的物理学家在非时尚的领域搞研究，但只能以一种既不道明又十分无力的方式进行。我试图让很少几个没有合同支持的研究领域保持生气。我力图让研究所的大门向具有独立思想和逆潮流的人物敞开。我要始终开着一扇门，以待另一个Kurt Gödel找上门来。不过我不得不承认，我企图阻挡时兴潮流的努力，其效果跟杰出的前辈Ｃanute王[注１]阻止大西洋潮汐的结果差不多。今天的年轻人，被一种比合同或权威更强的力所驱赶，追求着时兴的玩意儿。这股驾驭年轻人时髦的力量就是同辈的压力，就是追赶时髦本身的刺激。他们知道舞台在那儿，并想登台表演。他们知道只有短暂的时间来证明自己是个科学家。他们知道在配给他们使用的短时间内做出有价值成就的最好办法是随大流，尽快地在已成熟的领域摘取科学果实。

   年轻的科学家们力争尽快获得成功、力争尽快取得报偿，这本身并非坏事。他们的努力集中在一些时兴的专门领域，也不一定有害。毕竟，时尚问题之所以成为时尚，并非由于象某些时装设计师那样的灵机一动所致，而是大部分科学家认为它们重要。有一条普遍法则，大多数人的判断总是有根据的。时兴的领域常常都是些在其中获得了极其重要发现的领域。年轻科学家拥向这些领域，以期作出轰动世间的发现，这是无可非议的。确实，在时兴领域中许多人同时研究一些课题，大大增加了研究所日常生活中乐趣和激情。对于你在时兴领域开发宝藏进的每一次小的成功、每一回短暂的凯旋，朋友们都会在饭桌上或讨论班里谈起它。如果失去对时兴问题的共同旨趣，如果没有这种对新鲜消息和传闻的关心，我们研究所的生活将变得十分乏味。

   那么，我为什么还不满足呢？我为什么要为那些年轻人--他们正做着我自己在那种年龄时做的事--鸣不平呢？我之所以有牢骚，因为我认为我们的工作不应该百分之百都是合潮流的。时尚的研究是有用的、重要的和激动人心的。我们可以为年轻一代搞时髦课题并有所建树而骄傲。出于我能理解并尊重的理由，我们将看到他们中的大多数人会永远乐于搞时尚课题。我的意思只是说，必须为少数不搞时尚研究的人留下位置。我们应该发现那些不适于纳入流行款式的少数人，并对他们加以鼓励。在为研究所选人时，必须稍微偏向一点非正统和不从习俗的人。如果连我们这里都不给搞非时尚科学家的从业者一席工作之地，那么还有谁会给呢？！

   三、以往的历史由于存在许多非时尚的科学，支持它们的主要困难之一是选择问题。非时尚的科学千姿百态，没有任何统一的结构。上星期，我穿过批Princeton 大学的Forrestsl Cumpus (一处校园)时，遇到两个研究生静静地坐在草地中间，起初，我以为他们正在享受阳光和八月午后的静谧。可是走近时，我看到他们正全神贯注地做什么精巧的操作，手一点不能颤动，精神不得丝毫分散。当走到跟前时，我才弄清他们正忙着把一小块铅粘在蜜蜂背上。我静静地在旁观看，等他们做完全部工作，便跟着来到他们的实验蜂箱，箱上装备有照相机和录相机。这两个人正在更精确地做Karl von Frisch 的经典实验，并进一步扩充实验内容：原实验用于研究蜜蜂用舞蹈传递信息的系统。他们已发现，当蜜蜂发现蜜源离巢相当远时，它们的舞蹈更明显、更有力、了更精确。不幸，大多数蜜蜂只在蜂巢附近找蜜，返巢时只是简单地、马马虎虎地跳一阵。这两个学生想观察高精度的舞态，便设计一套办法让蜂表演更明显的舞姿。当一只蜜蜂负重45毫克铅时，只要飞一小段距离它就以为飞了很长时间。蜜蜂以所费的气力来感知飞行的距离。所以，负重的蜜蜂每次采蜜回巢后，都跳出精细的舞蹈。

   上面说的是典型的非时兴科学的例子。事情发生的地点就在我们Princeton大学的门口，我并非提议高等研究所应支持某个昆虫学学派。但蜜蜂实验说明，一切这类非时兴研究的特点，使得支持它们变得困难。它们的规模很小，研究对象各式各样，风格特异，看起来缺乏严肃性。

   为了说清非时尚科学具有真正的和持久的重要性，我来谈我擅长的领域：数学物理。数学物理是这样的人从事的学科，他们力图用严格的方式和纯数学的方法，达到对物理现象的深刻理解。这门学科处于物理和数学的交界处。数学物理学家的目标不是对现象进行数量方面的计算，而是从质的方面去理解。他们提出定理，加以证明，但不依赖数学和计算机。他们的目标在于用数学的精确性，阐明物理理论赖以确立的概念的含义。

   数学物理有三个性质使它跟眼下的讨论有特殊的关系。第一，它为更实际的物理领域提供基本思想和专门语汇，它从大的范围阐明事物的性质，因而很重要；第二，它的进展缓慢，一个新概念从创生到能有效的使用，基本上经历五十到一百年之久；第三，它几乎总是非时兴的，因为它的周期比科学浪潮的周期大约慢车10倍。由于它不时髦，所以在欧洲对它的关注与支持，总比在美国强得多。

   有一位伟大的数学物理家的工作，对今日的物理学仍然无比重要，我指的是Sophus Lie,他已去世八十年了。他的伟大工作完成于十九世纪七十至八十年代，但只是在刚过去的二十年间，才支配了研究粒子的物理学家的思想。 Lie第一个理解并清晰地陈述了群理论可作为物理原理的起点。他几乎靠单枪匹马构造了浩大而漂亮的连续群理论，并预见到有朝一日它将成为物理学的一个基础。一百年后的今天，每个按照破缺或无破缺对称性研究粒子分类的物理学家，都自觉或不自觉地使用Sophus Lie的语言。可是当Lie在世时，他的思想并不合时尚，几乎没几个数学家理解它，更不用说物理学家了。Felix Klein 是为数很少的能理解和支持他的大数学家之一。

   Lie属于这样一种人，他们似乎承受着不公平的厄运， 1870年普法战争爆发时，年轻的Lie正在法国漂泊。他是挪威人操着带普鲁士口音的法语。枫丹白露的爱国者认定他是普鲁士奸细，把他投入监狱，由于法国战败，形势一片混乱，当Lie的法国朋友最终找到关他的牢房并成功地使他获释时，他正静居囚笼，搞出了新的数学发现（Lie, 1877）。在世纪交替之际，Rouse Ball出版的数学史中，以悲怆的语调结束对Lie工作的评述（Rouse Ball, 1908）： “看来，Lie一直很失望，因他的工作价值没得到普遍承认，他为此而苦恼……。在他生命的最后十年，他常陷入沉思，想着他被过份忽视了的过去，使他心情不快。”

   另一位伟大的数学物理天才是Hermann Grassmann, 他在世时比Sophus Lie更不合时尚。 1844年在Stettin当预科学校的教员时，他发表了题为Die Lineale Ausdehnungslehre（扩张演算）的著作，首次引入了向量、向量空间和反交换代数的基本概念。它们在二十世纪的物理学中极其重要，但在十九世纪时却不然。在他生活的世纪，Grassmann一直在那所不知名的预科学校当教员，科学院的权威对他不闻不问。不过，他比Sophus Lie 有更强的适应性。他不是老想着得不到数学家们的承认这件事，而是开辟第二战场，去学习梵文。他把Rig-Veda（印度古经典四吠陀之一）译成了德文，因而有了不小的名气。也许，如果命运安排你成了不被承认的数学天才，为了健康起见，去当个预科学校的老师比当大学教授要好一些。

   为准备这次讲演，我到研究所图书馆查过资料，我高兴地发现了一本1878年版的Ausdehnungslehre(维数理论)，标题页上用铅笔写的Minkowski的名字 --他是Einstein的老师，第一个理解相对论的数学家。1878年出的这本书中有Grassmann写的序言（仍是在Stettin写的），他兴奋的表达了如下希望：新版本将比三十四年前的头一版受到学术界更多注意。序言之后有一行脚注："Der Verfasser ist während des Druckes gesorben"(本书付印时作者已去世)。只是到了十九世纪九十年代，Felix Klein--一位在为非时尚的事业战斗时总是毫不吝啬气力的人，才促成了对Grassmann的正式承认，并出版了他的全集（Grassmann, 1844, 1878, 1894）。

   数学物理在更近期的一个伟大发现，是Hermann Weyl于1918年提出的规范场的思想。这一思想仅过了五十年就在现代基本粒子物理学中获得了地位。量子色动力学是1981年粒子物理学家最时髦的理论，从概念上看，它就是Lie的群论代数和Weyl的规范的综合。Weyl提出规范场时的情况，跟Lie群和Grassmann 代数发现时遭遇完全不同。Weyl既有名气，工作也得到了承认。他在1918年搞的正是物理学中最时兴的领域：新诞生的广义相对论。他创立规范场是为了解决将重力和电磁力统一起来的时尚课题。几个月内，他的规范场变成最时髦的玩意儿。然后Weyl和其他人发现，规范场的提出并没达到预期的效果，即他们在事实上并不适于Weyl原来创立它们的目标。它们很快又不时兴了，甚至几乎被人忘却。又经过五十年漫长岁月之后，规范场在一个完全不同的方向上--量子电动力学及其在近期引出的量子色动力学方面的推广，清楚地显示出它的重要性。为规范恢复名誉的关键一步，是由我们Princeton的同事Frank Yang和他的学生Bob Mills于1954年迈出的，那是在Hermann Weyl 去世前一年的事（Yang和Mills，1954）。没有证据说明Weyl知道或注意到Yang和Mills使用从他脑袋里蹦出来的娃娃所从事的研究。

   规范场的故事充满了讽刺意味。一个时髦的思想，本想用来解决某个问题，但这个问题本身是短命的。经受长期的冷落之后，规范场最终以物理学里程碑的雄姿屹立于世。在漫长的数学物理发展史上，不乏这种反复的例证。Hamilton发明的四元数，曾被欢呼为解决十九世纪物理问题的灵丹妙药。可是在世纪转折之际，因无用而被弃置。到本世纪二十年代，它有以量子力学中自旋矩阵的形式恢复了青春，现在，它又光荣地跃入了夸克场理论。 Gauss发明的微分几何，起初只是他从事测地学和绘制地图等实际工作的副产品，经天才的Riemamn之手，它被改造成一个具有抽象一般性的新天地；五十年后，又作为Einstein重力理论的基础立于世人面前。这些历史有一个共同点，它们都经经历一个漫长的时期，从发生到结束通常超过单个人的生命期，而最终的结果完全无法预知，发明具有决定性意义的概念的人中，没有一个能对最终使用这种概念的物理领域有些微的感知。

   往事讲得不少了，我想，我已经给各位充分的历史见证以证明我的论点：不时兴的人和不时兴的思想，常常对科学的进步有决定性的意义。现在该讲讲现实和未来我没有理由期待今后科学思想的发展格式跟过去不同。我们能够期待，在未来的岁月，非时兴的思想显示其重要性的机会跟过去一样频繁，当然，这要经过漫长的孕育期，并在人们所不熟悉的领域崭露头角。作为科学进步的卫士，我们面临着如何识别有前途但不合时尚的思想以及如何支持它们的问题。

   四、魔怪和教训首先，让我们环顾数学世界，看看能否鉴别出在二十一世纪可能成为物理学基本构件的非时髦的思想。要是走运，我们说不定能挑出未来杰作的侯选者。当然，不能奢望在我们的有生之年，就弄清这种挑选是否正确。

   粗略地讲，非时尚的数学就是Bourbaki的权威们宣布为不属于数学的那部分数学，许多非常漂亮的数学发现属于这一范畴。据Bourbaki的观点，一种思想要称得上是数学，应该是一般的、抽象的、统一的，并跟数学的其余部分有清晰的逻辑关系。被排除在数学之外的是特殊的事实和具体的对象，它们的存在缺乏相应的理由，数学农称之为偶然或散在的事物。非时尚的数学主要跟具有意想不到的妙处的对象有关，如特殊函数、特殊的数域、异常的代数、散在有限群。我劝诸君到数学中这些尚未系统化、尚未形成学科的部分，去寻找物理学下一次革命的火种。它们具备奇异性和意外性的品质。它们不容易纳入漂亮的Bourbaki的逻辑结构。正是基于上述理由，我们应该珍爱它们，去开发它们。请记住两年前我们的所长Harry Woolf在一次讲演中的基调，那是他在研究所纪念Einstein诞辰白周年纪念会上引用的Francis Bacon的一句话： "没有奇特的奇异性，也就不存在于不同的美丽"（Woolf,1980）。

   我将简要地谈谈散在有限群（Conway, 1980）的特殊的奇异性。散在有限群的历史始于法国数学家Emile Mathieu，他在1861年发现了第一个这种群， 1873年又发现第二个。跟通常获得这类发现的情形一样，Mathieu并不知道自己发明了散在群，事实上，他的文章的标题中没有"群"这个词（Mathieu, 1861, 1873）。但是，他清楚的知道已找到某种非常漂亮和重要的东西。用几何语言讲，我们可以说他已经发现在12和24维空间中，存在一种具有奇特对称性的结构，但在任何维数不是12或24的空间中，不存在这种结构，他的工作发表了，但在其后的一百年里并不时兴。正如被公认的数学家喜欢说的那样，这是珍奇的孤品，没有开辟任何前进的道路。

   大约七十五年后，Mathieu群在编码业务中表现出某种实用的重要性。每个Mathieu群都给一种特别有效的纠错码提供了基础。当然，Mathieu群在实际中的应用并未招致数学家的青眯，他们的口味让Bourbaki给限制住了。

   接着的二十年间，风云突变，各方面的数学家用各种方法发现了新的散在群组成的宏大的"动物园"。他们之中有的是按照Mathieu的思想找到的；另一些是通过研究一个非时尚的问题引出的：把24维的台球尽可能紧地装进24维欧几里得空间（Leech, 1967）；还有的是在大计算机上试算排列组合问题时创造的。

这些发现有一些共同点：具体性、经验性、实验性和偶然性。这跟Bourbaki的精神正好相违。包括Mathieu的结果在内，总共发现了25个散在群。与此同时，群论专家的团体，用更一般和抽象的方法，成功地证明了散在群的总数不能大于26，所以，两年前的形势是还剩下一个散在群可寻。当时知道，如果着最后一个群存在，它将是所有散在群中最大和最漂亮的（Conway和Norton, 1979）。正在猎取它的人给它起了绰号叫"魔怪"或"亲密的巨兽"。

   去年，当Bob Griess从Michigan大学来高等研究所访问时，上面的故事终于有了结尾，他找到了构造这个魔怪的方法（Griess, 1981）。正巧在昨天，我收到从Michigan几来的长篇论文的最后部分，其中包括对他的研究的完全和肯定的评价(Griess, 1982)。对于那些不辞辛劳地从细节上弄清Bob Griess构造的人来说，魔怪的面目已暴露无遗，他们可以感到满足和快意。现在，这最后的也是最大的散在群已无懈可击地独立于世，成为一座不朽的纪念碑。

   这一切对物理学有什么意义呢？也许，一无所有。也许，散在群只是数学史上一弯可爱的滞水，远离浩荡主流的奇妙的插曲。我们绝没发现一点儿迹象，说明物理世界中的对称以任何方式跟散在群的对称发生联系。迄今，我们所知道的是，不管有无散在群存在，物理世界的面貌和功能依然如故。但是，我们不应过分地肯定它们之间无关。缺乏证据跟不存在证据到底不是一回事。在物理学史上，有过比意想不到的散在群的出现更奇怪的事。我们应该永远准备好迎接意外的事情。我必须坦白地招认，我内心存着希望，没有任何事实和证据支持的希望：有朝一日，在二十一世纪，物理学家将与魔群邂逅，以某种出人意料的方式将其纳入物理世界的结构。这只是一种莽撞的推测，几乎肯定是错的。有利于这一推断的唯一证据来自神学。这个强有力的证据是：宇宙的创造者喜爱对称。如果他喜爱对称，那么还有什么别的对称?quot;魔怪"的对称更可爱呢？

   散在群只是不合潮流的数学家创造的怪异而奇妙的思想宝库中的一例。我还能举出许多例证。你能想象一个正面体，--由完美的对称元构成的物体，--排列成完美的对称结构，总共有11个面吗？去年，我的朋友Donald Coxeter（在Toronto）找到了这个多面体（Coxeter, 1981）。有朝一日，会不会发现Zeta函数的零点（Riemann在120年前猜测它们具有某些性质，现今仍是数学中重要的秘密之一）跟物理世界有隐秘的联系呢？去年，Andrew Odlyzko(Bell实验室使用Cray计算机的数学家) 发现了Zeta函数零点的某些新的和出人意料的性质。 Kurt Gödel的不完全性定理（证明纯数学中存在这类问题，任意给定一组有限个公理和推理规则，都无法解答它），是否有一天会使我们对物理知识的限度有更深入的理解？不管你在哪个思想的王国游历，总会发现各种奥秘的暗示，听到有关藏匿着的各种事物间联系的传闻。
时间不多了。我必须践约讲讲对支持科学研究的具体意见。我是针对高等研究所和Humboldt基金会讲的。这既是我们的义务，也是我们这两个比政府更具慧眼的独立组织的殊荣。我们应能采取一种比政治家和博士后的学生看的更远的科学观。目光远大的科学观教我们怎么做呢？从上面讲过的许多故事应引出什么教训呢？教训只有一条，很简单：应该更多地注意、更有力地支持非时尚的研究。在科学史上任一特定时期，最重要和最重要和最富成果的思想往往潜伏着不被利用，原因仅仅是它不合时尚。具体到数学物理领域，从新思想的孕育到它成为科学思想的主流，通常要磨蹭五十或一百年。如果这是衡量基础性进展的尺度，那么结论必然是：在数学物理领域从事基本研究的任何人几乎肯定是不合时尚的。

   当然，我们不应该停止支持使大多数年轻科学家忙碌和高兴的时尚研究。但我们应拨出一部分经费，也许是十分之一或四分之一，以支持从事非时尚工作的不合潮流的人。我们不应该害怕看到做傻事，或是看到一堆破烂；我们不应该害怕支持可能完全失败的冒险事业。因为我们是独立的、我们有权利冒险和犯错误。那些仅仅支持搞无危险、无犯错误机会的研究的机构，实际上只是支持了平凡的人。如果我们靠良知和勇气，支持不时兴的人，去做正统观念认为是不对题和冒险的事，这就提供一种好的机会，为科学拯救很难得到的Sophus Lie或是Hermann Grassmann。当我们时代的所有时髦动人的成果早被人遗忘之后，他们的思想仍将驰名于世。

参考文献

Conway, J. H. (1980) Monsters and Moonshine, Then Mathematical Intelligencer, 2, No. 4, 165-171.
Conway, J. H. and S. P. Norton (1979) Monstrous Moonshine, Bull. London Math. Soc. 11, 308-339.
Coxeter, H. S. M. (1981) "A Symmetric Arrangement of Eleven Hemi-Icosahedron", to be published.
Grassmann, H. (1844, 1878, 1894) Die Lineale Ausdehnugslehre, 1st ed. (ott Wigand, Leipzig) 1844, 2nd ed. (Otto Wigand, Leipzig) 1878, 3rd ed. in Grassmann's collected works edited by F. Engel (Teubner, Leipzig) 1894.
Griess, R. L. (1981) A Construction of F_1 as Automorphisms of a 196883-dimensional Algebra, Proc. Nat. Acad. Sci USA, 78, 689-691.
Griess, R. L. (1982) The Friendly Giant, Invent. Math. 69, 1-102.
Leech, J. (1967) Notes on Sphere Packings, Can. J. Math. 19, 251-267.
Lie, S. (1877) letter to A. Meyer, published in Sophus Lie, Gesammelte Abhandlunger, ed. F. Engel (Leipzig, Teubner, 1922), Vol. 3, Anmerkungern, p. 691.
Mathieu E. L. (861, 1873) Mémoire sur l' éstude des functions de plusieurs quantities, J. de Math. Pures et Appliquées, 6, 241-323, "Sur la foncion cinq fois transitive de 24 qunatités", J. de Math. Pures et Appliquées, 18, 25-46.
Rouse, Ball, W. W. (108) A Short Account of the History of Mathematics, 4th ed. (MacMillan, London), p. 478.
Woolf, H., ed. (1980) Some Strangeness in the Proportion: A centennial Symposium to Celebrate the Achievments of Albert Einstein (Addison-Wesley, Reading, Mass.)
Yang, C. N. and R. L. Mills (1954) Conservation of Isotopic Spin and Isotopic Gauge Invariance, Phys. Rev. 96, 191-195.

译注1： Canute王：英格兰及丹麦的王（995-1035）。

原题：Unfashionable Pursuits。译自The Mathematical Intelligencer 5:3 (1983), 此报告是1981年８月２４日在Princeton高等研究所做的。
中文翻译：袁向东译，吴允增较。原载于《数学译林》。

The Business of Mining the Twitter Stream

2009-05-08T17:56:00.000+08:00

The Business of Mining the Twitter Stream

(http://datamining.typepad.com/data_mining/2009/02/the-business-of-mining-the-twitter-stream.html )

February 19, 2009

While mining Twitter data for business and marketing intelligence (trend/buzz analysis, sentiment/opinion mining, authority/influence analysis) looks like a compelling path to explore for a business model, it is important to consider the proposition from the point of view of the customer. Enterprises have been working with vendors in this space (mining social media content for BI) for well over 5 years and already have expectations regarding the features and quality of reports that these analytics needs to deliver to be useful (actionable).

Domain coverage: how broad is the topical space available in the solution? Crawling all data sources is the way to win here.
Demographic coverage: the broader the demographic coverage (and the accuracy with which the demographic features of the content authors can be determined) the better.
Content Analysis/Text Mining: how well does the solution take all the unstructured content and deliver structured interpretations that can then act as the input for further data mining. This is generally a matter of applied research (taking the current state of the art in text mining and making it work with the greater variety and complexity of social media content).
Timeliness: how timely is the analysis. This is generally a function of how timely the data is collected. Blog data, for example, can be gathered in a very timely manner thanks to the ping/feed mechanism. However, the reality of real time mining is that the consumer of the data is the real calibrator - real time may mean 4 hourly, not second by second.

If the business model for Twitter is going to be mining the Twitter stream for BI/MI, then they will be competing with companies that gather very large data sets (weblogs, usenet, message boards, reviews, groups, mailing lists, etc.). Seth Grimes suggested that the short texts of the Twitter stream may make hard problems like sentiment mining simpler as the limited space requires the author to be concise. However, this is a double edges sword as it means that the depth of analysis will be far shallower.

I believe that mining Twitter data will be a very exciting experiment, but I think that if Twitter goes down this path, it will have to either provide analytics over the other data sets, or partner with an existing company (say Visible Technologies). In fact, such a partnership would take the burden of building out an analytics engine away from the small Twitter team allowing them to continue to focus on infrastructure and ensuring the flow of this valuable data stream.

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Comments

Matthew, thanks for the mention. I'd venture that tweet mineability is also easier because short messages cover a single topic.

Short messages are easy to post so they folks can post more frequently. So maybe the more interesting thing to mine from twitter is message propagation. Then from propagation threads and connectedness patterns, one could infer influence networks and knowledge about the types & topics & forms of messages that travel farthest and fastest.

Posted by: Seth Grimes | February 19, 2009 at 05:12 PM

I don't get it, anyone can mine twitter for sentiment (using the search API)... why would twitter reinvent the wheel?

Posted by: Roddy | February 19, 2009 at 07:14 PM

Nice analysis, Matthew - I'd also say that as part of the way that people use Twitter is to share links to interesting content/conversations elsewhere, the need to be analysing the networks around the Twitter streams is very important indeed.

Posted by: Antony Mayfield | February 20, 2009 at 03:16 AM

There's a reality of the value of the raw data to the marketplace, which I'll get to in a minute. Regardless, short messages may very well be harder to search, not easier. Here's some reasons why:

* For indexing purposes, it's not only the corpus of the text that matters, it's the number of objects. So a search architecture has to take that into account. It's a non-trivial problem; especially with the kind of volumes involved here. Not to mention that servers are going to be thrashed with reading/writing if anything is meant to be done real time. (Perhaps less so for batch analysis of course.)

* Next we have the nature of the messages themselves. Due to the 140 character nature, there's an increase in odd acronyms even beyond the brb, lol, etc. Perhaps synonym dictionaries could be produced, but the variability here seems extreme just based on anecdotal experience.

* Regarding sentiment mining, that's difficult enough in larger text, but may be harder in small text. Not for raw sentiment where the phrases are obvious. But sentiment analysis lags with regards to humor and sarcasm, which may need more markers to divine actual meaning.

These are solvable problems. And in the latter case, it might not matter that terribly much if some stuff gets missed as general trends can still be spotted easily enough. Personally, I feel confident someone(s) will work this out to some reasonable degree of satisfaction.

Next, as to the dollars. I can tell you from experience the industry does not value the raw data terribly highly for specific social media data streams. The value added analysis? Yes. The actual data? Not so much. This is because it's easy enough for a variety of people to crawl blogs, forums and so forth. And several do, though in some cases there's really only a couple of providers feeding data to the 60+ reputation monitoring companies.

Unless Twitter made itself the sole availability for the full data stream, they wouldn't be able to command that great a price. I'm just guesstimating based on past experience with other data types here, but MAYBE 1M / month if they sold to every rep services company out there. (Who would in turn add analysis and re-sell for much more.) That's decent money, but it's not 'to the moon' money. I could be wrong here. People are valuing this stuff more highly. But to really capitalize on it, there's no way they could just let anyone suck down all they could eat off the stream. Which means less open. Which is fine. They're entitled to do so.

We'll see!

Posted by: Scott Germaise | February 20, 2009 at 02:06 PM

Nice post. I have included this blog into my rss subscriptions. Very nicely put on data mining using social media. I honestly have not thought about it in this much detail but it makes sense and could be used as a great competitor intelligence tool!

Posted by: video Promotion | February 20, 2009 at 07:39 PM

I'm still working on it but Twitter data sure is tasty.. Lots of goodies !

Thanks for the run down'

Mike

www.wannadevelop.com

Posted by: wannadevelop.com | February 24, 2009 at 05:30 AM

There is a lot of potential in analyzing Tweets : Segmentation of users, Sentiment Analysis to name a few. In my experience, the fact that tweets are maximum 140 characters makes things easier in catching emerging trends but also in Text analysis.

Combining Information Extraction and Ontologies (using IE to mark Text and using NLP to insert information to an Ontological Setting) is the way to go although it requires considerable effort.

Posted by: Themos Kalafatis | March 03, 2009 at 05:12 PM

Comments on Face Recognition (zz from newsmth)

2009-04-24T10:21:00.001+08:00

发信人: cbir (Fighting for honor), 信区: AI
标题: dodo：人脸识别方法个人见解(zz from prfans)
发信站: 水木社区 (Tue Jul 10 14:00:00 2007), 站内

http://prfans.com/forum/redirect.php?tid=97&goto=lastpost#lastpost

注：这个帖子很精彩，应该是prfans的震坛之宝:)，没有经过作者同意转载到这里，猜测转载到这里应该不违背作者初衷，呵呵。

dodo：人脸识别方法个人见解

看到j.liu关于人脸识别的帖子，萌发写这个帖子的念头。没有别的意思，就是想抛砖引玉，把问题说的全面一点，希望j.liu和回其帖子的兄弟姐妹们不要介意。如有兴趣，欢迎继续讨论。在以下讨论中，

TPAMI = IEEE Transactions on PAMI 这个杂志
PAMI 是指 pattern analysis and machine intelligence这两个领域

1）PCA和LDA及其相关方法

Eigenfaces和Fisherfaces无疑是人脸识别中里程碑式的工作。就使用的方法而言，PCA和LDA都不是新方法，但是他们都是被第一次十分明确的用在人脸识别中的方法。之所以说"十分明确"，是因为就发表的时间来看，这两个论文都不是首次把这两个方法用在PAMI相关的分类识别中。这给我们一个小小的启示：一个新的方法专注于解决一个具体的问题可能会带来更大的影响，虽然这个方法具有一般性。

在现在人脸识别的方法中，这两个方法也是follow的人最多的。究其原因，除了其有效性之外，简单是其最大的特点。纵观PAMI历史风云，能经受住时间考验而流传下来的方法，除了有效之外一般都有两个特点其一：1）简单（PCA, LDA, K-Means, Normalized Cuts etc.）；2）复杂，但是解决一个具有一般性而且很难被解决的问题 (在AAM、3d morphable model有深刻影响的Lucas-Kanade算法)。所以如果你的方法一般人都有能力做得到，那就尽量把你的方法做的简单明确。这就是外国人推崇备至的所谓的Ockham's Razor原理（就个人情感而言，我十分讨厌这个名词）。在这里我要强调一点是，这里说的简单并不是说原理简单，Normalized Cuts就方法本身来说简单，但是原理并不简单；微分几何中的Gauss-Bonnet定理形式非常简单，内涵何其丰富。

在此我想多提两句。由于国内有诸多发论文的方法论，其中一个流传下来的一句话就是：系统做的越简单越好，理论做的越复杂越好。不可否认，这句话有它有道理的地方，但是如果用这句话教育后人，误人子弟矣。

后来出现了许多新的与之类似的方法，就TPAMI上发表的来看，比较有代表性就是 HE Xiaofei 的LPP和 YAN Shuicheng 的MFA。关于这两个方法的评论大家可参看j.liu贴中knato的回帖。
在这里我想谈谈我的个人见解。首先这两个方法的出现有它们的意义。LPP是流形学习中Laplacian Eigenmaps线性化，这样无疑会带动其它流形学习方法在识别问题中的尝试，一个为解决问题找到一个思路，二个为进入寒冬的流形学习找到新的用武之地，虽然这两个都不是上档次的思路，但是潜在影响还是有的。后来 YANG Jian 的UDP就是在LPP号召下在TPAMI上的产物。LPP是非监督方法，所以它的识别性能比LDA好的概率极其微弱。
MFA是基于局部数据关系的监督鉴别方法。它有两个最近临近点数量的参数要调。这两个参数是这个方法双刃剑。参数调的好，MFA会比LDA效果好，调的不好则不行。这样MFA用起来比LDA复杂，这样如果MFA的性能比LDA好的有限，而用起来复杂得多的话，它终将被历史所抛弃。
另外就像j.Liu在他的帖子中说出的一样，这些方法有一定的投机性，比如这两篇文章的试验，他们都把Fisherfaces(PCA+LDA)设为c-1，虽然这是按照原始论文的取法，但是是做过这方面工作的人都知道PCA的主元数目如果取得太大，PCA+LDA的性能会显著降低，在WANG Xiaogang的IJCV上的Random sampling LDA中清楚地给出了图形说明。所以他们论文中给出的实验比较不具可信性。

LPP, UDP, MFA都是我们中国人（至少这些方法发表时还都是）为第一作者发表的方法，个人认为其存在有一定的价值，但它们将是PAMI研究发展中的过眼烟云，无法与PCA,LDA相媲美。

2）LDA奇异性问题

众所周知，LDA是基于求解广义特征值问题（Sb*u=Alpha*Sw*u），所以在实际应用时遇到奇异性的问题，就是Sw矩阵不可逆。在人脸识别中解决这一问题的论文“浩如烟海”。这也说明了LDA的影响力之大。在这一类方法中，也有风格之分。

o. PCA 降维
在Fisherfaces中采用的就是先用PCA降维，再用LDA，这也是现在处理这一问题的一般方法。这里有个比较讽刺的事情。Belhumeur在他的论文里说：PCA actually smears the classes together。那末既然smears the classes together，既然PCA破坏类的结构，那为什莫还要用PCA降维？而且事实证明，即使在Sw可逆的情况下，用PCA features也会增强LDA在人脸识别中的性能。这里只能说明，PCA的作用或是PCA features并不是Belhumeur和其以后follow这样说法的人叙述的那样。PCA虽然简单，但是人们应该对它有个正确的认识，这个以后如果有机会再谈。

a. RDA
至今影响最大最实用的还是基于regularization思想的RDA。其实这个问题不仅仅在人脸识别中才被注意到。很早在统计中就被解决过，RDA发表于1989的Journal of the Americal Statistical Association杂志上，可见其久远。在Sw上加一个扰动项也是解决这一问题的最简单方法。

b.子空间投影
论文最多的也就在这一块。应用knato类似的排列组合方法，令image(Sw)和null(Sw)分别表示Sw的列（像）空间和零空间，则我们可很容易的就列出如下组合方法（强调：这里却不是提供给大家发论文的方法论，而是以较形象的方式叙述！）
把样本投影到
aa. image(Sb), bb. null(Sw), cc. image(Sw), dd. image(Sw)+null(Sw), ee. image(Sb)+null(Sw) 可并列可串行, ff. image(St)+null(Sw)
以上每一种组合就代表不止一篇论文，在此就不详细列举了。另外，你还可以把random sampling技术加进来，这样就可以不止翻倍。还有，你还可以把同样的技术用到KPCA KLDA (kFA)上，这样又可翻倍。更进一步，你还可以把ICA,LBP, Gabor features等诸如此类的东西和以上子空间混合，...，子子孙孙无穷尽焉。
把这个东西做到极致的是国内的 YANG Jian。另外香港中文大学的 TANG Xiaoou 和他以前的学生 WANG Xiaogang 也做这相关的工作，但是他们做一个idea就是一个，没有灌水之嫌。YANG Jian的工作可以用他在TPAMI上的 KPCA plus LDA 这篇文章来概括，虽然他灌水无数，但就子空间方法而言，他这篇文章还有他发表在国内自动化学报上的那篇长文还是有东西的。如果你想做这一块的工作，值得看一看，是个较为全面的总结。TANG Xiaoou在子空间方面的代表工作（开山之作）就是dual spaces LDA, random sampling (and bagging) LDA, unified subspaces。（在此之后他还有学生一直在做，就不详细列举了。）

我建议想做这一块工作的同学们，要把TANG and YANG的工作烂熟于心，取长补短，相互学习，取其精华，这样可以较为快速而全面地掌握。

c. QR分解
矩阵和数值功底比较好的人，能做得更像模像样。Cheong Hee Park 和 YE Jieping 无疑是这方面的高手。去看看他们在TPAMI,JMLR, 和SIAM的J. Matrix Anal. & Appl上发表的论文可知一二。

d. 相关性
如果Sw可逆，则Sb*u=Alpha*Sw*u可以转化为 inv(Sw)*Sb*u=Alpha*u。那末就可以考察Sw的子空间和Sb子空间的相关性。这方面的代表工作就是Aleix M. Martinez在TPAMI上长文的那个工作。

e. 变商为差
变u'*Sb*u/(u'*Sw*u)为u'*(Sb-Sw)*u。

3）基于图像局部结构的方法

这一类获得广泛认可的方法有Gabor和LBP，另外还有可能有用的SIFT和differential features。
Gabor应用比较早有影响力的代表作就是EBGM。Gabor也是提取用来识别的visual feature的最常用手段。
有无数人因为LBP的极其简单而怀疑它的性能，但是有趣的是最近Ahonen在TPAMI上的短文，就是把LBP应用在人脸识别上，没有任何新的改进，这也说明Reviewer们和editor对这类方法的肯定和鼓励。在非监督feature extraction中，LBP有明显的优势，但是绝对没有达到作者在论文显示的那个水平。在他的论文中，LBP特别weighted LBP效果非常好，这和他们应用的FERET人脸库的人脸crop形式有关。他们应用CSU的椭圆模板来crop人脸，如果应用正方形的模板weighted LBP提高很有限。特别在FRGC Version 2上测试，LBP绝对没有一般监督性的识别方法好。另外这也给我们一个小小启示，就是加个weight其识别性能就能大大提高，这说明什莫问题呢？

另外我不敢苟同j.liu在他文章说的LBP对image blocks大小不敏感是个美丽谎言的说法。首先，有一定的敏感性，这个是要承认的。但是LBP有一个性能稳定的image blocks，并不是人们认为的histogram要符合一定的统计性等等。这个block size的选取比最优的PCA主元数目的选取要容易得多。当然这些都是小问题。

国内有人做Gabor和LBP的结合。当然是值得探索的，但是我个人认为不应该在这两种方法结合上花费太多精力。完全可以用类似形式考虑别的思路。

4) Sparse representation

NMF和NTF都属于sparse representation的方法，都曾被应用在人脸识别中，但效果都非常有限。特别是NTF，属于数学理论上非常优美，但是实际效果很勉强的典型。

另外，Sparse representation (coding) 是一个很有趣也是很有前途的方法，Sparse representation 有很多方式，关键要看你怎莫用、解决怎样的问题。过段时间我们还有机会再谈。

5）Tensor方法

Tensor在人脸识别中至少到现在为止，还非常得不成功。最典型的就是M. Alex O.Vasilescu在ECCV'02上的tensorfaces。他们对于问题的分析和tensor的对应天衣无缝，非常有道理，数学实现上也同样简单，但是自从那个方法发表出来以后基本无人follow。究其原因，个人认为就是把本来简单的问题复杂化，最重要的就是复杂化以后并没有带来该有的益处。

Alex对tensor的应用是flattening high-way tensor。这是一种常见的处理tensor的方法，这样做的好处就是使tensor好处理易于计算。two-way tensorfaces就是我们理解的Eigenfaces。但是同样是tensor，这种tensor和Amnon Shashua的NTF有着本质的区别。NTF是纯正的tensor思想。但是它实现起来过于复杂，又加上原理比Alex的tensor更复杂，所以无人问津。但是不可否认，它们都是数学上十分优美的方法。如果你想学习tensor而又不想枯燥，我推荐你去看这三篇论文（Shashua两篇）。

6）参数模型
参数模型的应用也多种多样，比如HMM, GMM等。这两个都是一般性的建模方法，所以应用也很庞杂，而且在人脸识别中的应用大多是从speech recognition中的方法转化而来，在此就不多谈。有兴趣的同学们可以参看H. Othman在PAMI上的论文和Conrad Sanderson在PR上的论文。

但是在此其中，最简单的是Baback Moghaddam在TPAMI上那个Probabilistic Subspaces的文章，这个文章也是WANG Xiaogang的unified spaces的参考原本。

7) 3D 模型

代表作是Volker Blanz在TPAMI上的那个文章。不过个人十分不看好。

8）Personal Perspectives

a. 基于子空间的方法很难在实际应用中有所用处

b. 基于找图像局部结构的方法更有希望。像EBGM, LBP, SIFT之类可以给我们很多有益的启示。这点和j.liu的观点一致。

c. 把人脸识别中的方法推广开来，应用到一般的分类和统计问题中，这也是人脸识别衍生出来的一大作用。

d. 由于我们国内的特殊研究环境，大家一般都喜欢做简易快的工作，所以人脸识别这一领域出现有华人名字的论文为数可观。其实在某些压力之下这也无可厚非，但是还是希望我们国人在有条件的情况下，不要以发论文为主，多关注于解决问题本身、尽量向推动理论发展的方向努力。我们绝对有这个能力。君不见，NIPS‘06两篇Best student paper被在国外留学的中国人获得，CVPR'07更是又传来喜讯：Best student paper由清华学生获得，这些都是迹象。我们正处于一个意气风发、大有可为的时代。就本人学术水平和资历来说，绝没有资格来说这些话，这只不过是个人的一点心愿和号召而已，同时更是勉励自己。

以上均是dodo个人拙见，囿于本人才疏学浅，难免出现挂一漏万和观点偏颇的情况，还请大家及时批评指正，以免曲彼误人。谢谢

--
Enjoy the world around you. This is life.

※ 修改:・cbir 于 Jul 10 14:00:09 修改本文・[FROM: 211.99.222.*]
※ 来源:・水木社区 newsmth.net・[FROM: 211.99.222.*]

[dahua lin] 我的PhD生活 (转载自水木)

2009-03-09T22:38:00.001+08:00

【以下文字转载自 NLP 讨论区】
发信人: zibuyu (得之我幸), 信区: NLP
标题: [dahua lin] 我的PhD生活
发信站: 水木社区 (Sun Mar 8 01:05:06 2009), 站内

一直以来，我在这个blog上写的都是偏重学术的文章。这一期就换一下口味吧，在这里聊聊我日常的生活。

在外面的人看来，MIT这所理工科的殿堂，或多或少有一点神秘的色彩。网上流传着很多关于这个学校的故事，包括Hacker，超负荷的课业，还有各种怪才。这些东西确实真实地存在着，却不是这里校园生活的主流。对于研究生来说，这里的日常生活是相当单调的，这种平凡得乏善可陈的生活和他们特别强调创新的研究工作形成了一种有趣的对比。

PhD的生活方式在很大程度上会受到导师的指导风格的影响。在这里，你问100个不同的PhD，他们会告诉你100种不同的生活方式——但是有一点是共同的，大家的工作都很繁忙。还是说说我自己的吧。在读master的时候，我只需要每过相当长的时间向汤老师汇报一次就行了；而在这里，我必须与三位不同的指导者讨论我的研究。

首先是Eric Grimson，他是我的正式的supervisor。但是，他有另外一重身份——MIT EECS的head，由于管理方面的事务极为繁忙，他在学术界上已经不太活跃了。我一般每个学期会和他有一到两次meeting，对自己的工作做一般性的汇报并且听他的建议，时间不长，通常是30到40分钟。向他做的报告，必须非常简明扼要，再复杂的topic，必须在5分钟内说完，并且要把要点说清楚，这对我来说是一个不小的挑战。然后他会向提出一些问题，并且对以后的大方向提出一些建议。对我来说，我并不期待这个简短的交流过程对我具体的 research有多大的帮助，最主要的是要获得他对我的研究方向的持续支持。

然后是John Fisher，这里的一位Principal Scientist，他是我直接work with的人。和他的接触是相当频繁的，每周会有一次reading group，还有一次一对一的research meeting。在research meeting上，我会很具体的和他讨论我的研究，包括很多细节上的东西。一般来说。他会有很多建议，但是，仅仅是建议，没有要求我必须这样做——事实上有起码50%的建议，会被我当场驳回。不过，这并不影响我和他之间良好的合作，我们都认为这些是正常学术讨论中很自然的事情。

还有就是 Alan Willsky了，LIDS的co-director。他是一个非常渊博的学者，对非常多的学科（信号处理，控制论，统计学习，数学）都着广泛而深刻的了解。每个星期，他和与他有关的学生进行分组讨论，我在其中的一组。我的研究涉及的相当重要的部分——李代数和微分方程，正是他非常熟悉的领域。一方面，我能够从和他的讨论中学到很多东西，事实上，我研究过程中的很多进展都得益于他的启发。另外一方面，他对这个领域太熟悉了，要让这方面的工作得到他的欣赏，是非常困难的。

在这里进行的研究，和我在MSRA或者CUHK做的研究有一个很不一样的地方，我的导师们非常强调一个工作是不是具有开创性的学术价值，而一个算法在实际中work不work，虽然也很重要，但不是放在最核心的地位的。我和他们讨论的绝大部分时间都是理论和方法论上的探讨，至于算法怎么在实验中更好的performance，他们assume是学生自己在实验过程通过各种方式中达到，这些东西如果和理论核心没有特别关系就不会是讨论的主要议题了。这不代表MIT或者CSAIL的全部，不过在我所在的“小环境”里，理论倾向是非常明显的。

在这里，不会有特别的paper或者project的压力，研究是自然地推进的，受会议deadline的影响会有一些（deadline前，如果刚好有一项工作差不多成熟了，需要多花点时间整理成paper），但不是特别明显。研究的最终目标是形成一份有重要影响的PhD thesis，因此，我们不会特别围着CVPR/ICCV/ICML/NIPS之类的会议转。如果留心统计的话，MIT在这些会议上发的文章不会比一个普通的学校多，但是在这里所完成的工作的长远影响远大于一般的学校。

能来到这里的学生，多多少少都希望能在学术上有自己的价值，而不仅仅是毕业后有一份还说得过去的工作——如果仅仅为了这点，用不着来这里，花那么长的时间（在我身边的同学里，5年甚至更长的很普遍的）读一个PhD。不过，现实中总是有着很多的压力和诱惑一点一点地消磨着学术上的理想。一方面，不是在paper-driven的氛围中工作，publication list的增长变得不那么迅速和激动人心；而对于高impact的研究的追求则时常会陷入挫折，推进缓慢。另一方面，faculty的opening逐渐减少和竞争日趋激烈，让前景变得不再是那么明朗。

与之相对比的是来自学术界以外的诱惑，比如工业界，华尔街，和管理咨询公司，它们一直以来都相当青睐从这里出去的学生（无论何种专业），而且有着极富竞争力的待遇。MIT统计了去年的top 5 employer: McKinsey, MIT, Google, Booz Allen, 和Boston Consulting Group，其中三家是顶尖的咨询公司；此外，虽然现在处在金融危机的时代，Morgan Stanley等的著名金融公司的校园招聘还在如常进行，仍旧吸引着很多的学生——而这个学校的学生里面，真正读管理和金融的是比例很小的——这说明了，很多理工科专业的同学去做consultant或者trader了。

这是一种令人困惑或者迷惘的对比。一部分人一直坚持自己的学术理想并取得成功（按照去年的统一，MIT的博士毕业生进入Education的占30%，我相信这里面大部分人并不是去教中学或者小学:-) ），而另外一部分人走进了商业的世界。这没有谁好谁不好的比较，每一次的人生选择都是一种choice——没有标准答案的choice。但是，一旦做出了选择，就意味着你在享受这种选择带给你的一切好的东西的同时，也必须承担所伴随的责任。

直到今天，我依然很执着地认为我会选择学术的道路，这是我内心中觉得最有价值的事情。如果到华尔街去，在为自己创造了财富的同时给世界上的其他人留下了什么——我想今天的局势或多或少表明了这个问题的答案。如果在科学上做出了真正的贡献，那么将给这个世界（至少是所工作的领域）带来进步和改变。一个人一生的价值，不在于他拥有了什么，而在于他创造了什么。

--

※ 修改:・zibuyu 于 Mar 8 01:05:10 2009 修改本文・[FROM: 166.111.135.*]
※ 来源:・水木社区 newsmth.net・[FROM: 166.111.135.*]

what was stumbled upon today

2009-02-26T23:57:00.001+08:00

Mainly photos:

http://prometheus.med.utah.edu/~bwjones/

http://www.flickr.com/photos/ethanhein/

Flickr果然是宝藏

Story of Subrahmanyan Chandrasekhar [转载]

2009-02-16T21:39:00.001+08:00

转载自：【杨建邺　发布时间： 2007-03-15 15:09　科学时报】

钱德拉塞卡由于第一次突然遭到严重打击而转变研究领域，这一转变居然使他感到受益匪浅，形成了以后不断转变研究领域的特殊风格。虽然不免孤独，却因为每

到一个新的领域它都不可避免的是"新手"，不可能有"傲慢"的可能，只能老老实实从虚心当学生开始。这样倒使得他一生谦逊地对待大自然。这岂不是"塞翁失马，焉知非福"吗？

     我们很少看到印度科学家的传记。这本书使我们有机会了解20世纪30年代前后印度科学家经历的人生历程。所以这本书的翻译出版，可以说填补了一个空白，因此很有价值。仔细看了这本书以后，它给我的震撼和对于科学界曾经发生过的一些不公正事件，有了深入肺腑的了解，而让我感到惊心动魄的是发生在1935年的事件。这件事情几乎可以说决定了钱德拉塞卡将走上"孤独的科学之路"，而且妙不可言的是，它居然塞翁失马得到了一个伟大的启示！要弄清楚其中一些事情和奥妙，还得从1930年讲起。

    1930年，钱德拉塞卡带着两篇论文来到了英国剑桥大学。一篇论述的是非相对论性的简并结构，另一篇则论述了相对论简并机制和恒星临界质量的出现。福勒看了这两篇文章，对第一篇他没有什么意见，赞同钱德拉塞卡已取得进展；然而第二篇所说的相对论简并以及由此而生的临界质量，福勒持怀疑态度。福勒把第二篇论文给著名天体物理学家米尔恩看，征求他的意见。米尔恩同福勒一样，也持怀疑态度。

    虽然两位教授对钱德拉塞卡的结论持强烈怀疑态度，但钱德拉塞卡通过与他们的讨论和争辩，愈加相信临界质量是狭义相对论和量子统计结合的必然产物。1932年，钱德拉塞卡在《天文物理学杂志》上发表了一篇论文，公开宣布了自己的观点。

    1933年，钱德拉塞卡在剑桥大学三一学院获得了哲学博士学位，并被推举为三一学院的研究员。几年来，他与米尔恩已经建立了密切的工作联系和深厚的友谊，他也逐渐熟悉了英国著名的天文学家和物理学家爱丁顿。爱丁顿经常到三一学院来，与钱德拉塞卡一起吃饭，一起讨论问题，爱丁顿几乎了解钱德拉塞卡每天在干什么。

    到1934年底，钱德拉塞卡关于白矮星的研究终于顺利完成。他相信他的研究一定具有重大意义，是恒星演化理论中的一个重大突破。他把他的研究成果写成两篇论文，交给了英国皇家天文学会。皇家天文学会作出决定，邀请他在1935年1月的会议上，简单说明自己的研究成果。

    会议定于1935年1月11日星期五举行，钱德拉塞卡踌躇满志，自信在星期五下午的发言中，他宣布的重要发现将一鸣惊人。在下午会议上，钱德拉塞卡简短介绍了自己的研究：一颗恒星在烧完了它所有的核燃料之后，将会发生什么情形？如果不考虑相对论性简并，恒星最终都塌缩为白矮星。这正是爱丁顿同意的理论。但是，当人们考虑到相对论简并的时候，任何一颗质量大于1.44M⊙（太阳质量）的恒星在塌缩时，由于巨大的引力超过恒星物质在压缩时产生的简并压力，这颗恒星将经过白矮星阶段继续塌缩，它的直径越变越小，物质密度也越来越大，直到……

   "啊，那可是一个很有趣的问题。"他明确地宣称："一颗大质量的恒星不会停留在白矮星阶段，人们应该推测其他的可能性。"

    接着，大会主席请爱丁顿讲"相对论性简并"，爱丁顿开始发言了。钱德拉塞卡怀着异常紧张的心情，等待着这位权威的裁定。爱丁顿说：

    钱德拉塞卡博士谈到了简并。就此而论，通常使用两种表达："普通的"简并和"相对论性"简并。……我不知道我是否应该逃离这次正在召开的会议，不过我的论文的论点是并不存在像相对论性简并这样的东西！……恒星不得不继续辐射、再辐射和收缩、再收缩，我推测，这样直到它达到几千米的半径为止，此时重力变大，足以抑制住辐射，从而恒星最终能归于平静。……

    各种不同的偶然事件也许会介入以拯救恒星，但我希望有比这更多的保护。我认为应有一条自然定律阻止恒星以这种荒谬的方式行动!

    钱德拉塞卡惊呆了！怎么爱丁顿从来没有同他讨论过这一点呢？！在那么多的相互讨论中，爱丁顿至少应该表白一下他的观点才对呀！但是，爱丁顿并没有办法驳倒钱德拉塞卡的逻辑和计算，他只是声称，钱德拉塞卡的结果过于"稀奇古怪和荒诞"。这哪里是科学的反驳！

    钱德拉塞卡说的这种恒星的最终结局（"直径越变越小，物质密度也越来越大，直到……"），实际上就是现在已被广泛承认的黑洞（black hole），这个名称是30多年后于1969年由美国科学家惠勒正式定下的。但1935年1月11日的那天下午，爱丁顿断然宣布它是绝不可能存在的。他的理由只不过是一种直觉："我认为应有一条自然定律阻止恒星以这种荒谬的方式行动!"

    可以想象，1935年1月11日的下午对于钱德拉塞卡来说，真是一个惨淡得可怕的下午。他曾经心疼地回忆过那天下午会议结束后的惨况，他写道：

    在会议结束后，每个人走到我面前说"太糟糕了，钱德拉，太糟糕了"。我来参加会议时，本以为我将宣布一个十分重要的发现，结果呢，爱丁顿使我出够了洋相。我心里乱极了。我甚至不知道我是否还要继续我的研究。那天深夜大约1点钟左右我才回到剑桥，我记得我走进了教员休息室，那是人们经常聚会的场所。那时当然空无一人，但炉火仍然在燃烧。我记得我站在炉火前，不断地自言自语地说："世界就是这样结束的，不是砰的一声巨响，而是一声呜咽。"

    钱德拉塞卡原本想通过玻尔、泡利等的介入，把这个争论继续下去，但是由于当时物理学家们正忙于建立量子力学而无心介入，钱德拉塞卡的处境变得十分不利，他几乎失去了在英国寻找一个职位的任何机会，人们对爱丁顿的嘲笑记忆极深。没有办法，他只得于1937年来到美国，很幸运的是他在芝加哥大学找到了一个教职。与此同时，钱德拉塞卡决定不与爱丁顿争论，暂时放弃恒星演化的研究，但他坚信他的理论总有出头露面的一天。于是他把他的整个理论推导、计算、公式等统统写进了一本书中，这本书的书名是《恒星结构研究导论》。

    写完了这本书以后，他改弦更张，开始研究星体在星系中的几率分布，后来又转而研究天空为什么是蓝颜色的。有趣的是，钱德拉塞卡后来似乎十分满意这种不断转换研究领域的做法，以致他后来又全面地研究了磁场中热流体的行为、旋转物体的稳定性，广义相对论，最后他又从一种全然不同的角度回到了黑洞理论。1983年，他终于因为"对恒星结构和演化过程的研究，特别是因为对白矮星的结构和变化的精确预言"，获得了诺贝尔物理学奖。但这已是他最初提出这种理论后的48年了！

    法国著名作家蒙田曾意味隽永地说过：

    命运对于我们并无所谓利害，它只供给我们利害的原料和种子，任那比它更强的灵魂随意变转和利用，因为灵魂才是自己的幸与不幸的唯一主宰。

    钱德拉塞卡后来的经历，可以说是蒙田说法的一个佐证。1935年1月11日那天下午突然落到钱德拉塞卡头上的严重打击，有可能毁掉一个人的人生；但对于具有"更强的灵魂"的钱德拉塞卡，这一严重的打击却给了他一个千载难逢的机会，使他悟出了一个深刻的道理：为什么科学家到了50岁以后（甚至更早），就基本上不再会有什么创造性了。科学家为什么不能像伟大的文学家、艺术家那样不断地具有创新精神呢？钱德拉塞卡通过自己奇特的经历，找到一个答案，那就是：

    "由于没有更恰当的词，我只能说这似乎是有一些科学家对大自然产生某种傲慢的态度。这些科学家有过伟大的洞见，作出过伟大的发现，但他们此后就以为他们的成就，足以说明他们看待科学的特殊方法必然是最正确的。但是科学并不承认这种看法，大自然一次又一次地表明，构成大自然基础的各种真理超越了最强有力的科学家。"

钱德拉塞卡举爱丁顿和爱因斯坦为例：

    以爱丁顿为例，他是一位科学伟人，但他却认为，必然有一条自然定律阻止一个恒星变为一个黑洞。他为什么会这么说呢？无非是他不喜欢黑洞的想法。但他有什么理由认为自然规律应该是怎样的呢？同样，人们都十分熟悉爱因斯坦的那句不赞成量子力学的话："上帝是不会掷骰子的。"他怎么知道上帝喜欢做什么呢？

    而钱德拉塞卡由于第一次突然遭到严重打击而转变研究领域，这一转变居然使他感到受益匪浅，形成了以后不断转变研究领域的特殊风格。虽然不免孤独，却因为每到一个新的领域它都不可避免的是"新手"，不可能有"傲慢"的可能，只能老老实实从虚心当学生开始。这样倒使得他一生谦逊地对待大自然。这岂不是"塞翁失马，焉知非福"吗？这一事例大约会使我们得到很多很多的感受吧？

2007 news report about Emotiv Corp

2009-02-13T22:21:00.001+08:00

Emotiv Ushers New Era of Gaming; Enables Players to Control Games with Their Brains
Posted by: Kevin Hawkins at March 7, 2007 11:50:04 AM

Game Developers Conference, San Francisco, CA - March 7, 2007 - Emotiv Systems, the pioneer in brain computer interface technology, today launched the Emotiv Development Kit (EDK) for the electronic games industry. With the EDK, developers will be able to create games that respond to a player's emotions and allow players to control their characters' expressions and manipulate objects using only the power of their brain.

Emotiv's technology represents a scientific breakthrough: it is the only brain computer interface solution that can detect and process both human conscious thoughts and non-conscious emotions, including those represented by brain activity patterns unique to a particular individual. Unlike earlier brain computer interfaces, which only detect a limited number of mental 'states' such as concentration (by identifying when the user is focusing on the screen), Emotiv can process dozens of expressions, gestures and emotions. For the first time, computers will be able to differentiate between thoughts of pushing an object or lifting it; detect a user's smile or win; and respond to emotions such as excitement and calmness.

The EDK is the first product offering from Emotiv, which publicly launched today. It enables game developers to attach dozens of specific thoughts and emotions to many different actions in their game. For example, they can enable players to move an object in a game without the use of a keyboard or joystick, make their character smile when they smile, or require that a player stays calm in order to ensure his or her character remains undiscovered in a stealth game. As a result, developers can create a more interactive, immersive, personal experience than is currently possible.

"The games industry is ripe for a revolution in the way players interact with a game. Current interfaces, such as keyboards and controllers, are relatively basic and non-intuitive and are out-of-keeping with the sophistication levels of today's games and the movement towards more immersive environments," said Nam Do, CEO and co-founder at Emotiv Systems. "Brain computer interfaces dramatically change the way players interact with a game and, as such, have a profound effect on the gaming experience. Developers are looking to this technology to take their games to another level, to differentiate their products and to retain their fans."

Emotiv Development Kit (EDK)
The EDK comprises a headset with multiple sensors for detecting brain activity and a series of application development suites:

_ The Expressiv(tm) suite can identify facial expressions in real-time, allowing developers to create characters that respond to the expressions of the player, such as smiles and winks.

_ The Affectiv(tm) suite measures players' discreet emotional states, allowing a game to respond to the player's emotions, such as excitement or calmness.

_ The Cognitiv(tm) suite detects players' conscious thoughts, enabling them to move or manipulate objects just by thinking about an action, such as push, pull, lift or rotate.

How brain computer interface technology works
The brain is made up of approximately 100 billion nerve cells, which are called neurons. These active neurons cause electrical activity, which can be observed using non-invasive electroencephalography (EEG).

Brain computer interface technology works by observing an individual's electrical brain activity and processing it so that computers can take inputs from the human brain. Human thoughts and emotions can therefore control and influence an application.

About Emotiv Systems
Emotiv Systems is a pioneer in brain computer interface technology. Its focus is on leveraging neuro-technology to create the ultimate interface for the next-generation of man-machine interaction. It does this by evolving the interaction between human beings and electronic devices beyond the limits of conscious interface. Emotiv creates technologies that allow machines to take both conscious and non-conscious inputs directly from your brain. These technologies include a hardware and software platform that can be licensed to commercial software developers and other third parties, as well as a suite of products for consumer applications.

Today, Emotiv is developing solutions specifically for the electronic games industry. In the future, Emotiv's technology has the potential to be applied to numerous industries, including interactive television, accessibility design, market research, medicine, and security.

Founded by four award-winning scientists and technology entrepreneurs, Emotiv is headquartered in San Francisco, CA, and has offices in Sydney, Australia. Investors include Technology Venture Partners, Epicure Capital Partners and the Australian Federal Government. More information is available at www.emotiv.com.

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"Emotiv Ushers New Era of Gaming; Enables Players to Control Games with Their Brains" Discussion

shengshwi Member since: 1/16/2007 From: Woodland Hills, CA

Posted - 3/7/2007 3:54:24 PM
This is really interesting. I can definitely see it being a huge market in the future.

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Tolo Member since: 3/3/2007 From: Lassa hang, Louangphrabang

Posted - 3/7/2007 10:27:42 PM
cool era! :)

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Dwiff Member since: 12/9/2006 From: Eugene, OR

Posted - 3/8/2007 12:24:50 AM
I have been excited about this technology for years, I think it will be a while before a game will outright benefit for the technology though. None-the-less I think it will be one step closer to the next real generation of gaming.

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Elektordi Member since: 5/10/2003 From: France

Posted - 3/9/2007 9:54:17 AM
I want one... ;)

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Rolando Member since: 6/1/2008 From: Santiago, Santiago de Cuba

Posted - 6/1/2008 1:00:27 PM
It looks really very interesting. Unfortunately the public (or at least the available) demonstrations of Emotiv have the following weak points:
- The available choices on each scene seem to be usually YES or NO (do it or not). A more interesting situation must include several possibilities and show that the user can freely select one of them.
- All the scenes implies the use of hands, arms or face muscles then it is hard to believe that Emotiv is really using brain activity instead of electromyogram.
- The claim of an optimal electrode position is really hard to justify without additional theoretical elements, at least if the goal is brain activity and not electromyogram.
www.electrical-neuroimaging.ch

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[URL: http://www.gamedev.net/community/forums/topic.asp?topic_id=438376&whichpage=1&#2907682]

Article by Professor Allan Snyder FRS

2009-02-13T06:02:00.001+08:00

OWNING INNOVATION: From Idea to Delivery

Home › Publications › Symposia Proceedings › 2002 › Snyder

Academy Symposium, November 2002

Dinner Address

Genius, Madness and Innovation

Professor Allan Snyder FRS
Director, Centre for the Mind/

You know, when you think about it, creativity is an act of rebellion! It is downright subversive! Creativity must, by its very nature, confront conventional wisdom.

Distinguished guests, ladies and gentlemen. Creativity, this wondrous expression of our minds, underpins innovation, underpins real genius and even underpins the world's economic growth. And yet, and yet creativity remains largely illusive. We don't really know how it can be nurtured. We don't really know how it manifests itself in some and not in others. Why in some and not in others?

I want you to recall "A Beautiful Mind". The recent film about Nobel Prize winner John Nash. John Nash's extraordinary mathematical genius, by his very own admission, came NOT from his conventional training, but rather from his particular form of schizophrenia. Quite simply, John Nash could 'see' patterns and relationships that normal people could not. And, this revelation, resonates with other expressions of genius, from the impressionist artist Gaugin to the Russian novelist Dostoyevsky, and possibly even onto the great Newton. Madness, bi-polar disorder, schizophrenia or whatever, somehow facilitate creativity.

Ladies and gentlemen - Why is this so? Why do altered mental states facilitate genius? Answer this question and we will have unlocked one of the mysteries of creativity. Answer this question and we may even allow ordinary people greater access to genius.

To be really creative, you must see the world in a new light. Sounds easy, but it is virtually impossible. The disturbing reality is that we don't see what is out there. What we do see is based largely on what we expect to see. What we do see is based largely on what we know. Two people looking at the very same cloud formation can see radically different images. The portrait painter sees a face of dignity, the ultrasound sonographer sees a diseased gall bladder.

To me, this says it all. We project out what we know onto everything. Nothing we see is looked at afresh. We are blinded by what we know. We are blinded by our expertise. We are blinded by our mindsets.

Have you ever wondered why you can't draw? I mean of course draw without being shown the tricks of how to do so. This really is deeply mysterious, because our brains already possess the information necessary to draw, otherwise we couldn't see at all! For example our brains have algorithms for calculating the shape of an object from subtle shading across its surface. Yet, we are not conscious of this shading. Because, if we were, we would be able to draw without training.

When you think about it, when you think about it, this is rather an extraordinary state of affairs. Why does our brain have secret information? But when you think about it, why should we be conscious of subtle shading? Why should we be conscious of any so called backroom deliberations? Isn't it the final decision, the executive decision, and not the intermediate details leading to that decision that is of ultimate importance to us? No wonder subtle details are a secret of the nonconscious mind.

But the frightening consequences of this strategy is that we don't see what is actually out there. And, here is the fundamental block to creativity.

Is it possible to extricate ourselves from this intrinsic block? Is it possible to access the secrets of the nonconscious mind and see the world the way it really is? Just think of the rich applications if we could actually do that! Now, surprisingly, our approach to accessing the nonconscious is inspired by severely brain damaged people known as autistic savants. You know, like the character Dustin Hoffman played in the Hollywood film, Rain Man. Autistic savants are peculiarly literal. They lack the big picture. They lack executive decision making. Autistic savants would appear to be the exact opposite of the creative mind. But, they display extraordinary skills. Skills which demonstrate that they, unlike us, can access the nonconscious mind.

Nadia, a severely mentally retarded girl could draw like Leonardo da Vinci. She did so without any training and from memory. And yet, Nadia was only three years old. She had no language ability and could not even recognise her mother from the nurse. Somehow Nadia could access the mechanisms for vision directly from the raw data of the nonconscious mind. Somehow she could access what is in all of our nonconscious minds.

So, a peculiar brain damage affords autistic savants privileged access to the secrets of the nonconscious mind. Privileged access to something that exists in us all but is normally not accessible.

Now here's the big idea! Although we do not have access to the nonconscious mind as do savants, is there nonetheless some artificial means to promote this access? Wouldn't it be amazing if, on command, we could switch off the part of the brain that is damaged in savants and allow ordinary people this privileged access to the nonconscious mind? Wouldn't it be amazing if we could just momentarily see the world as it really is? Incredibly, we can! We have actually been able to turn on savant like skills in people by shutting off part of their left brain with magnetic pulses.

Incredibly, we can allow anyone access to the unprocessed raw information about the world, information that is normally a secret of the nonconscious mind. And, we do so not by stimulating the brain but rather by turning part of it off!

Now this could really have some truly extraordinary applications, especially to learning and problem solving. Because, if we can, through artificial means, allow ordinary people a glimpse of the nonconscious mind, then they too would have an opportunity to see a novel interpretation - a novel way to join up the dots. Then they too would have a greater opportunity for innovation. And, this is precisely what we are attempting right now at our Centre for the Mind. Technological ways to enhance learning and creativity.

But how does all this relate to John Nash. How does this relate to mental illness and genius? Well, I wonder if our results with magnetic pulses could help explain why so many geniuses suffer mental disorders? I wonder if, for example, bi-polar disorders, intermittently switch off the left side of the brain, allowing privileged access to raw sensory data of the nonconscious right-brain. This would lead to alternating views of the world. One view that driven by the left brain is consistent with past experience, consistent with what we know. The other view that dictated by the right brain sees the world anew and hence is devoid of familiarity and meaning. Taken together, these alternating views are deeply unsettling because they are unexpected. But, taken together they provide the fertile ingredients for creativity.

I am sure you are thinking that there must be other ways than magnetic pulses or mental abnormalities to seeing the world unfiltered through our mindsets. Now, it is very hard to obliterate mindsets, and you need them anyway, so the way to see more of the world is to take on more mindsets. Because the more mindsets you imbue, the more different views you have of the world. So, after mastering one situation, you should go on and master something completely different. And, this strategy emulates the very effects of switching off the left side of the brain because it plunges you into unfamiliar territory.

Take Picasso, arguably the most innovative painter of the 20th century. Picasso's four major stylistic shifts were precipitated, in every instance, by an upheaval in his life. He changed everything. He changed his woman. He changed his circle of friends. He changed his house. And, he even changed his dog!!! In every instance, the radical transformations of Picasso's styles, were reflected in the radical transformations of his private life.

Take Steven Jobs, the co-founder of Apple computers. After Apple, he started Pixar digital animated films. Animated films? Yes! Returning to Apple years later, he revolutionised the appearance of computers and saved Apple industries.

Take my career. My insights about optical fibres for telecommunication were inspired, not from engineering physics, but amazingly from insect eyes. Insect eyes! Working in completely different fields facilitates creativity. Somehow our minds link seemingly disparate concepts into a new synthesis.

And, I emphasise, I emphasise the nonconscious nature of this process. Because in the final analysis, true genius is about making nonconscious leaps! Making leaps that explode upon you, seemingly from nowhere.

Take the brilliant mathematician Poincare. Poincare's breakthrough solution leaped into his mind, unexpectedly, as he stepped onto a bus, and most importantly, after a lengthy holiday. The problem had incubated in his nonconscious mind.

It's this crucial incubation period, the 'let me sleep on it' phenomenon, which links seemingly disparate concepts into a new synthesis. It's this crucial incubation period which facilitates the uprush of innovation and genius. And, it's this crucial incubation period which I believe can be enhanced by new technologies.

Ultimately, creativity, this driving force of innovation, is the process of destroying ones own gestalt to build a completely new picture. But as I said, creativity is an act of rebellion! And to initiate a rebellion you must have courage. So, in conclusion remember what the celebrated Sigmund Freud said about his ability to innovate: "I am not really a man of science, I am not an observer, I am not an experimenter, I am not even a thinker. I am nothing but an adventurer - a conquistador - with all the boldness, and the tenacity of that type of being." In other words, in other words, from his own assessment, Freud was not especially skilled or talented. Rather, he had the courage to break the rules and to confront conventional wisdom.

Thank you.

Professor Allan Snyder FRS
Director Centre for the Mind
http://www.centreforthemind.com

Centre for the Mind:
A joint venture between Australian National University and University of Sydney
__________________________________
Centre for the Mind
University of Sydney Main Quadrangle (A14)
Sydney NSW 2006 Australia
Phone: 61 (2) 9351 8531
Fax: 61 (2) 9351 8534
________________________________
Centre for the Mind (Bdg 59)
Australian National University
Canberra ACT 0200 Australia
Phone: 61 (2) 6125 2626
Fax: 61 (2) 6125 5184

The views expressed in the above article are those of the author(s) and do not necessarily represent the views of the Academy.

Polly Matzinger 从会问问题的女招待到世界闻名的科学家 [转载]

2009-02-12T18:24:00.001+08:00

【以下文字转载自 square 讨论区】
【原文由 pico 于 Fri Mar 28 13:02:58 2008 发表】

◇◇新语丝(www.xys.org)(xys.dxiong.com)(xys.dropin.org)(xys-reader.org)◇◇

Polly Matzinger，从会问问题的女招待到世界闻名的科学家

mdoctor

　　第一次听说Polly的故事，是在研一时免疫学的课堂上。何维老师在讲授
"危险模式"理论时，特意卖了个官子："大家知道提出这个理论的是谁吗？在
国际免疫学界可是一位传奇人物啊！"

　　Polly是一位极具个人魅力的女人。每次学术会议，只要有她的演讲，会场
总是爆满。而且，她曾经为Playboy工作过。当年她做学生时曾向JEM（国际权威
的免疫学杂志）投稿，只署了自己的名字。编辑认为这篇论文只有一个作者并不
可靠，怎么也得把老板的名字也属上吧！文章修回后，增加了一个作者。不久，
论文发表了。后来，Polly的一位同学，也是JEM主编的女儿拿着这篇论文，去找
她老爸说："您知道Polly后边的那个名字是谁吗？"主编说："不是她老板
吗？"女儿哈哈大笑："那是Polly养的小狗（一只阿富汗猎犬）的名字！"此
后，Polly被禁止作为主要作者在JEM上发表文章，直到那位编辑去世。

　　那篇发表在JEM上的论文：Polly Matzinger and Galadriel Mirkwood.
(1978). In a fully H-2 incompatible chimera, T cells of donor origin
can respond to minor histocompatibility antigens in association with
either donor or host H-2 type. Journal of Experimental Medicine, 148,
84-92.

　　就是这么一位传奇的女科学家，在1994年时提出了"危险模式"理论，引发
了免疫学界一场新的"革命"，堪称近10来免疫学最重要的理论突破。随着网络
的不断发展，能从网上搜集到的有关Polly的资料也越来越多。

　　Polly的经历非常特殊，在成为一名科学家之前，做过各种各样的工作，包
括爵士乐手、实验室技术员、训狗员以及Playboy俱乐部的"兔女郎"（Playboy
bunny）等。在她看来，"兔女郎"是一项"伟大的"工作（a great job）。而
在Playboy俱乐部的网站中，Polly也被列入著名的前兔女郎名录：

http://mysite.wanadoo-members.co.uk/explayboybunnies/information/faq2.html
Dr. Polly Matzinger - world renowned immunologist.
Denver Playboy Club, 1969

　　不过，Polly的这些工作都干不了多久，她很快就会感到乏味。1972年她来
到加州Davis做酒吧服务生，同时也使自己有些时间来阅读、写作和从事动物工
作。

　　一天，Davis加州大学的两位教授来到这个酒吧。和往常一样，他们喝着啤
酒，讨论着动物拟态的问题。Polly问："为什么没有动物模仿过臭鼬呢？"
Robert Swampy Schwab教授，也是野生动植物、鱼类、菌类学系主任，竟然被问
得哑口无言。Schwab教授断言，这个"会问问题的女招待"应该成为一个科学家。
于是，他花了9个月的时间，到酒吧给Polly送去各种科学著作，使她相信科学是
永不令人厌倦的工作。1974年，Polly回到了学校，这年她已经27岁。2年后，
Polly获得了迟来学士学位。1979年，获得博士学位，终于开始了她永不觉得厌
倦的科学研究工作。她说，她终生感激那个（引导她走上科学道路的）人（I
owe that man my life）。

　　Polly目前在NIH（国立卫生研究院）的NIAID（国家过敏和传染病研究所）
领导着细胞和分子免疫学实验室的T细胞耐受和记忆研究部门。Polly给自己的实
验室取了一个奇怪的名字："幽灵（GHOST）"。
　　
http://www3.niaid.nih.gov/labs/aboutlabs/lcmi/tCellToleranceMemorySect
ion/matzinger.htm

　　作为一名国际知名的科学家，Polly的文章并不算多，迄今为止在PubMed上
只能检索到不足70篇，但大部分发表在Nature系列（23篇）、Science（4篇）、
JEM（10篇）、Annu Rev（1篇）等顶级学术杂志上。Polly的研究性论文不多，
而大都是综述、评论、讨论，这也是理论免疫学家的一个特点。
　　
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=search&db=pubmed&ter
m=(matzinger%20p[auth])

　　Polly的传奇经历，给我们太多的启示和思考。我们可以赞扬Schwab教授的
伯乐识马，也可以感叹Polly的的特立独行，还可以赞扬那个自由、平等、开放
的学术风气。如果没有Schwab教授，Polly恐怕永远只是芸芸众生中的一员，唯
一值得骄傲的，恐怕就只是曾经做赤戴着可爱的大耳朵和小尾巴的兔女郎。

　　其实，通过网络，我也有幸与Matzinger教授有过几次交流。研究生时，曾
将自己的实验与"危险模式"理论结合，用Email与Matzinger教授讨论过中其中
一些问题，很快就收到了她的详尽的解答和有关实验方向的指导。可惜，由于时
间和条件有限，我没能继续相关研究。

　　前不久，看到Matzinger教授在Nat Immunol上最新的一篇关于"危险模式"
理论的文章，于是再次向她去信，希望获得这篇文章的reprint。第二天，
Matzinger教授便给予了回复。显然，Polly已经不记得我这位3年前曾向她求教
的学生。她说："我对一位外科住院医师能对免疫感兴趣觉得非常惊讶。"同时，
她还附上另一篇几年前发表在Science上的相关的文献，供我参考。虽然实际上
我已经读过阐述"危险模式"理论的大部分文献，包括Science上的那篇，但是，
Matzinger教授此举，着实让我感动。她在用自己的行动，影响着每一个正在或
尚未走上科学之路的渴望科学的年轻人，就像当年Schwab教授带她走上科学之路。

　　Matzinger教授给我的回复：

From: "polly matzinger" <pcm@helix.nih.gov>
To: "**" <**@hotmail.com>
Subject: Re: a reprint (or pdf) of your paper
Date: 2007年8月28日 18:22
hi
i am also sending you another paper about the danger model of immunity
(and the web supplement that went with it), just in case you have not
seen it. i am surprised that a surgery resident is interested in
immunity. good work!i hope you enjoy these, let me know if you can't open
them.
cheers polly

　　科学，对某些人来说，可能只是枯燥乏味的工作，而对另一些人来说，则可
能是永不令人厌倦的快乐的源泉。

　　我想，不管从事什么工作，只要能从中获得快乐，那便是成功。

说明：本文最早于2007-11-03发表于我的博客
http://blog.sina.com.cn/u/1401213573
http://xinguancha.blog.tianya.cn/

(XYS20080327)

◇◇新语丝(www.xys.org)(xys.dxiong.com)(xys.dropin.org)(xys-reader.org)◇◇

Tan Le 报道中所提到的竞争对手 OCZ 公司生产的脑电波信号游戏控制器

2009-02-12T05:35:00.001+08:00

脑电波游戏控制器将上市定价159美元

作者：大文轱辘 2008-03-11

　　【IT168 资讯】再强的游戏鼠标，再好的游戏手柄，恐怕都不能与人脑电波直接控制游戏操作更加吸引人吧，OCZ公司展示过的脑电波系统并不是一项科学发明，而是一种真真切切即将上市的产品！

　　OCZ的"神经脉冲激励者"（NIA）利用一个头带探测脑电波活动，并将其转换为游戏中的各种动作，通过驱动程序定义，可将某种脑电波信号定义为具体的键盘按键或鼠标动作。玩家使用它，不需要动一根指头，就可以在游戏中完成跑、跳、开火的动作。

　　近日OCZ的首席执行官Ryan Petersen在接收采访时说，这套系统的定价为159美元："我们希望每个用户都来使用它，而不是那种高不可攀的概念型产品"。

Tan Le on the Cover of Inc. Magazine

2009-02-12T05:31:00.000+08:00

Tan Le on the Cover of Inc. Magazine
December 1, 2008

The scientists at Emotiv have done the impossible: created a brain-wave-reading headset that lets you conjure entire worlds using nothing but your mind -- a breakthrough that could be worth billions. Now comes the hard part.

I'm sitting in a darkened room, attempting to move a large block with nothing but my thoughts. I stare at it intently and imagine myself physically tugging on it, trying to flood my mind with a sense of strain and determination. But the block doesn't budge. I try again, concentrating, concentrating: Move, damn you; I am your master. After a long moment, the block trembles a bit, then slowly skids toward me a few feet before stopping. Encouraged, I mentally bear down until the block resumes its sliding, and this time it keeps going. I'm gripped by the immensity of what I have just accomplished: effecting a change in the world around me without moving a muscle. Well, that's not entirely true. I may have squinted a bit.

This isn't a dream; it's science -- and soon, maybe, a big business. OK, the block was only a virtual one on a computer screen, but that's a nit. The same technology that converted my thoughts into action on the screen someday could be hooked up to a real-life backhoe, robot surgeon, or microwave oven, placing any of those objects at my mental whim. This thought-conversion technology is composed of some extremely sophisticated software and a piece of headgear that looks like a cross between a telephone headset and a skeletal bike helmet. Embedded in the headset are 16 electrodes that press lightly on my scalp, monitoring the electrical signals generated by the 3 pounds of toothpaste-like goo sealed in my skull. The signals are my brain waves, the stuff of thought and emotion. The headset passes the signals to the software, which extracts patterns that can be used to control anything that's run by electronics.

Brain waves usually are monitored in hospitals or research labs, but I'm in a conference room at a company called Emotiv, where a few dozen scientists have developed the gear and software that quite literally read my mind, allowing me to play a sort of video game with nothing but sheer thought. This is not a rough, spare-no-expense research and development prototype of some distant-futuristic product, but rather an upcoming stocking stuffer. For $299, you and yours will very soon be able to vaporize onscreen enemies with an angry thought, have your online characters smile when you smile, and see video games react to your level of excitement.

And that's just for starters. Backed by some impressive partners, Emotiv has a long-range strategy that sounds like a business-school case study from the 22nd century. After enabling us to control video games with our minds, Emotiv intends to let us control most everything else we do on our computers and, after that, what's around our homes. In 10 years or so, according to the company's co-founder Tan Le, we will all go around in a world that will respond to our mental commands. Fed by data wirelessly streaming in from a few freckle-size sensors embedded in your scalp, your stereo will know when you are feeling blue and what sort of music cheers you up. Movies will know when you are getting bored and cut to the action. Car advertisers will know when you are feeling the need for speed. Your doctor will know when you are depressed. Doors will open at your mental command.

Given all this, you might expect that Emotiv would be sitting pretty. But if you think building a mind-reading device is tough, try marketing one. It turns out the old saw about building a better mousetrap doesn't hold in the context of a product most people hesitate to believe is possible and aren't sure they want anything to do with if it is. And that has left Emotiv with a challenge every bit as big as conquering mind reading: figuring out how to present its breakthrough device to the world in a way that will transform it from a slightly scary gadget to the next must-have consumer technology. And Emotiv has to do it while taming persistent hiccups in the system, herding video-game producers into tailoring games to the device, and trying to halt a skidding launch date before competitors -- yes, there are other companies making mind-reading devices -- pick off pieces of the market. "Emotiv faces some crucial decisions it absolutely has to get right," says Stephen Prentice, an analyst at Gartner (NYSE:IT) who has sampled the company's device.

Le admits that such challenges are real. But once consumers give the headset a try, she predicts, a lot of the doubts will themselves be vaporized, and demand will snowball. "We see it becoming a totally ubiquitous device, allowing you to interact in a seamless way with everything else in the world," she says.

That grandiose strategy reflects the intensity and outsize ambitions of Emotiv's founders, and especially of Le. Her entire life has been a string of hard-won, improbable triumphs, and she is loath to lower her standards to anything less than spectacular. Going all in with Emotiv doesn't scare her. "When you start with nothing," she says, "you don't get attached to a lot of things. You end up unafraid to push outside your comfort zone."

It's not entirely true that Le started with nothing. She had a bottle of poison. Her mother kept the bottle and little else on the small, calamitously overcrowded boat on which she, 4-year-old Tan, and Tan's younger sister, grandmother, aunt, and uncle fled the Communist government in South Vietnam in 1981. At first, they had felt lucky to have avoided being captured and jailed. But floating in the South China Sea, they weren't so sure. Pirates were chasing the hapless vessels and picking them off one by one. Hence, the bottle of poison: Tan's mother was determined to grant her children a swift and relatively painless chemical end if their boat should be overtaken. "She didn't tell us about any of the horrible stuff, but she didn't have to," says Le. "You see the fear on people's faces, and you know."

The women and girls were kept in the stifling lower deck all day to make the boat a less appealing target, but they were allowed some fresh air late at night. On the fifth night, when the boat was out of fuel and passengers were down to their final rations, Tan, though she had been warned not to speak while above deck, couldn't resist remarking to her mother on the sudden appearance through the clouds of a wide patch of brilliant stars. "Those aren't stars," her mother gasped. "Those are lights." It was a British tanker steaming alongside. They were rescued and taken to a refugee camp in Malaysia. Three months later, they were given a choice of countries that were accepting refugees. Tan's mother had heard that Australia was a young country with a big future, so that's where the family ended up.

They settled outside of Melbourne, where Le's mother, still in her early 20s, picked vegetables and struggled to learn English in night school while raising her daughters. It's not hard to see why Le grew up with an unshakable belief in her ability to accomplish anything. Her mother, who went on to get a bachelor's and then a master's degree, started a cosmetics business and then a consultancy aimed at facilitating Australian-Vietnamese trade. In 1997, she became mayor of Maribyrnong, a suburb of Melbourne, becoming the first Vietnamese woman to be elected mayor anywhere outside of Vietnam.

Grateful that her family had been able to find a comfortable place in Australian society, Le grew up wanting to help others do the same. At 15, she joined an organization that aids Vietnamese immigrants. Smart, ambitious, and disciplined, she was elected the group's president at 18. Somehow, she also found time to complete her schoolwork and entered Australia's prestigious Monash University at 16. In 1998, Le, then 20, was named Young Australian of the Year, a highly publicized government honor that made her a national celebrity and put her on a speaking circuit, where she hobnobbed with prime ministers, scientists, and international captains of industry. That same year, she graduated with a combined degree in business and law.

Le took a job at one of Melbourne's most prestigious law firms, seeing it as a natural extension of her community service work. But by the time she was 22 and a full-fledged lawyer, she found she couldn't stop thinking about the successful entrepreneurs she had met. In particular, she was captivated by the high-tech moguls, some not much older than herself, who had the ability to forge new types of electronic ties that left people better connected to one another and to the world. "There was a technology revolution going on, and I didn't want to just be a facilitator," Le says. "I wanted to be part of the creating."

In 2000, as her restlessness was peaking, she delivered a speech at the University of Melbourne. Afterward, she was approached by a young Vietnamese student who was studying business and information technology on a scholarship at the nearby Royal Melbourne Institute of Technology. This was Nam Do, like Le newly aspiring to high-tech entrepreneurship. The two hit it off so well that they decided to try to start a company, one that would give Le a chance to make her contribution to the connectivity revolution.

Their idea was for small bar-code scanners that could be built into cell phones so that consumers could aim their phones at products and get a text message back with product information and price comparisons. Telcos weren't interested in the bar-code part but were impressed with the high-speed text-messaging capabilities -- these were pre-American Idol-voting days, and mass text messaging seemed a novel idea. Le and Do sold licenses for the software and stuck in a clause that would allot them a modest-sounding five cents for every message handled by the system. Within a few years, their software was handling 150 million messages a month; you do the math. In 2003, Le and Do sold the company, which they had owned outright. They were 26, rich, and looking for a new -- and bigger -- idea.

Le knew where the pair could grab a little inspiration. A few years earlier on the speaking circuit, she had been at yet another dinner event, feeling a bit overwhelmed as a young Asian woman in a sea of suits, when she spotted another misfit -- a middle-aged man in cargo pants, with wildish hair tucked under a sideways baseball cap. This turned out to be the scientist Allan Snyder, who had a prestigious award of his own to boast about: the Marconi Prize, a near-Nobel-level honor he had been awarded for his role in the development of fiber optics. Snyder and Le got on well and stayed in touch. Le and Do went to dinner at Snyder's home, where he enthralled them with his work on using magnetic fields to stimulate human brains. He went on to bemoan the fact that the computer revolution had shut out emotions, which are, after all, what drive us. The industry had thrived on digital signal processors -- chips and software that could handle images and sounds. What was needed, insisted Snyder, was an emotional signal processor.

The notion rang every bell in Le's head. Snyder was describing a technology breakthrough, an entrepreneurial adventure, and a way to form an entirely new, world-changing type of connection. "We stayed up until 4 in the morning talking about it," Le recalls. "By the time we got together again a few months later, we realized none of us had been able to get the idea out of our heads."

In fact, Snyder had been approached by larger companies about developing his idea. But he liked the idea of starting a company with Le and Do. "There are magical qualities to both of them," he says. "I just had a strong intuition this could work with them in charge." Le brought in another friend: Neil Weste, a prominent Australian chip designer who had sold his last company to Cisco (NASDAQ:CSCO) in 2000 for several billion dollars. Among these four very successful partners, start-up capital would not be a problem for the new company, which they dubbed Emotiv. There was no shortage of strategic vision, either. "We wanted to bring to computers and the Internet all the facial expressions and emotions that are so important in our interactions with each other," Le says.

Emotiv's headquarters looks like that of any Web 2.0 start-up, which is to say it is a cluttered warren with mostly twentysomethings hunched over multiple monitors in San Francisco's South of Market neighborhood. But you have to meet only a few of these laptop lizards to realize that something unusual is going on here. One is an expert on facial expressions. Another has designed high-powered communications software. Yet another has produced best-selling video games. Smoke from a soldering iron wafts from a side room teeming with custom circuit boards. The payroll includes mathematicians as well as an evolutionary biologist.

And then there's the charismatic Le, now 31, who is a bit harder to characterize. She is comfortable shooting the breeze about the fine points of intellectual-property protection, the structure of the human cortex, and the future of the music industry, punctuating all of it frequently with an infectious laugh. But there are also flashes of a less easygoing, sharper-edged Le -- flaring, for example, at the suggestion that Emotiv can be compared with any of the countless start-ups that have set up shop nearby. "They may take on some technology risk in their development, but they know what they want to do is doable," she says. "Here, we're pushing the boundaries of what's possible."

Measuring brain waves, of course, isn't such a big deal. Electroencephalography, or EEG, machines that track the brain's electrical activity at the scalp have been around for the better part of a century. But the best EEG machines cost tens or even hundreds of thousands of dollars -- and for all that, they generally haven't been used for much more than measuring relaxation levels or detecting signs of life.

When they launched Emotiv, the partners figured there was no point in hiring established EEG experts, since the state of the art in EEG machines wasn't even close to what they needed. "We decided that we'd look at the whole landscape of science," says Do, "because there had to be something out there traditional researchers were missing." Ultimately, Emotiv decided to treat emotional signal processing as a sort of math problem that could be solved with clever software. Emotiv opened an office in Sydney and staffed it with mathematicians, digital signal processing experts, and artificial intelligence whizzes. To help keep R&D costs manageable, Emotiv leaned heavily on graduate students willing to work for free in exchange for having some exciting, cutting-edge research on their resumé.

The result was a software program that broke brain waves down into 90,000 components. It was so complex that running a single 10-second brain-wave reading through the program took six computers two days. And sometimes the two-day crunching session would be for naught: The brain-wave readings were so faint that just the electrical activity generated in an eye blink was enough to swamp them. To work well, the software had to learn to filter out the noise. "It was like listening to all the phone conversations in New York at once and trying to pull a few of them out," says Snyder. But the researchers made steady progress, and as they did, Le was quick to file patents; she eventually claimed some 25 that covered a range of processes.

In late 2004, after a day of particularly good progress, the group sensed it was close to being able to read a person's level of excitement in real time. No one went home that evening. Le, Do, and the research team pulled an all nighter; they took turns wearing a standard electrode cap -- sort of like a bathing cap coated inside with gel to improve electrical conductivity -- while watching movies, listening to jokes, arguing, and more, all while a graph on the screen tracked excitement. "By morning, we knew we had it," says Le. "We knew we were going to succeed." Without any champagne on hand and with the bars closed, the team members went to a coffee shop to celebrate, their hair glistening with conductive gel.

By now, I can move that block with ease. I'm ready for a new challenge: making something happen onscreen that has no real-life analog. In this case, I'm to make that same damn block vanish into thin air. What am I supposed to think and feel? Disappear isn't part of my mental repertoire. It's suggested that I stare at the background scene and visualize it without the block. I conjure the image in my mind and focus on making it vivid. The block flickers. I sear the blockless image into my brain, and just like that, the block is gone. Who knew I had the ability to concentrate in such deadly ways? Now for some easier fun. An animated face comes up on the screen, and I'm told to make faces. As I grin, the face grins; it matches my frown, blink, wink, and eyebrow arching. I'm a cartoon! I feel as if the headset is helping me realize fantasies I didn't even know I harbored.

Le and her colleagues were just as tickled when they found they could perform similar feats. But they soon realized they now had a serious decision to make, one they had been putting off while the very feasibility of the project was in play: What do we do with this? Hit the market with an expensive device that would sell in low volume? License the technology to one or more big companies? Or somehow figure out how to bring the costs down enough to sell to a mass audience? The co-founders had been dreamily discussing the possibilities all along, but now they met to formally choose their future. "Nam and I were very excited about the opportunities around licensing, but then Allan said to us, 'We don't want to make money doing this,' " recalls Le. "Nam and I rolled our eyes, thinking that this was typical scientist talk. Then Allan added, 'We want to make a lot of money.' " They all laughed, but the point was clear: They had all seen success in past exploits. Why bother to do this if they weren't going to go for the jackpot? They decided to shoot for the mass market.

The strategy is counterintuitive, to say the least. "The best beachhead strategy for a new technology is one that demonstrates that the technology works, is highly valued by the customer, and gives you a high margin," says Jerome Engel, executive director of the Lester Center for Entrepreneurship and Innovation at the University of California, Berkeley. The transistor, for example, was first brought to market in 1952, when it was used in hearing aids. Customers were grateful rather than finicky, marketing was fairly simple, and the revenue funded expansion into bigger markets. Emotiv, in fact, is working with a wheelchair company to develop a thought-controllable device for those who can't move their body. But that's a sideline. The company's biggest bet remains squarely on consumers -- which Engel finds risky. "If you go for a consumer market first," he says, "you're racing against limited resources, you need to get a lot of partners, and you need to have a very sexy product that delivers exactly what unforgiving customers are looking for. These guys made a choice that carries a huge risk."

The decision to shoot for a mass market immediately led to another: The one market that seemed ripe for a large-scale invasion of innovative interface technology was the video-game industry. "Better and better graphics had reached a point of diminishing returns, while there had been almost no innovation in controllers," Le says. "And gamers tend to be early adopters, making them a good incubator for a new technology." Emotiv opened a new headquarters in San Francisco, placing it close to the heart of the gaming industry, while keeping an R&D team in Sydney.

With a market in mind, Emotiv could now pin down the details of its device. Gamers weren't going to wear a gooey bathing cap, so the team came up with a rigid, relatively unobtrusive, even cool-looking headset able to get an accurate brain-wave reading with 16 gel-free sensors instead of the 128 sticky ones in a standard EEG cap. The headset was augmented with a tiny gyroscope to track head motions and a wireless transmitter to free the wearer of wires. More important, the software's brain-wave-interpreting capabilities were improving by leaps and bounds. The software would eventually be able to differentiate among 30 of what the company characterizes as mental states, roughly divided into three categories -- emotions, facial expressions, and actions. All three types of mental states would be critical: Actions would allow controlling what a character does, facial expressions would convey feelings and intentions to fellow online players, and emotions would allow a game to respond to how a player was feeling. A plot could change when you were bored, a virtual character could appear more often if you found him engaging or threatening, music or lighting could shift to complement your mood.

The technology worked, but it didn't work perfectly for everyone. Some users had more trouble than others sending out consistent, identifiable signals, even after running through a training session. And that, says Le, was a shadow hanging over the future of Emotiv. "If we let something seen as half baked get onto the market, it would be a disaster," she says. "We have an opportunity to revolutionize the way people interact with technology. But we won't get a chance to do that unless we provide the right experience in the beginning."

To make the device easier and more fun to use, Emotiv's team worked furiously with a small video-game-development company called Demiurge Studios in Cambridge, Massachusetts, to embed the technology in a gamelike context. Instead of a boring training session, an Asian sensei walks you through an exotic introduction to your new powers. He gets you to grimace at annoying flying creatures to make them flee, to lift heavy objects, and more. This acclimation process gives the software a chance to record your brain waves and trains you to use them consistently before it throws a series of increasingly difficult challenges at you, such as reconstructing simply via thought a fallen bridge needed for a mystical journey while a fiery sky changes hue in response to your emotional state. Another mini game teaches you to hurl thunderbolts.

The market seemed to break in Emotiv's favor with the success of the Nintendo Wii, which lets users wield game controllers like rackets or steering wheels; the Wii's popularity suggested a real thirst for new sorts of interfaces.

And so, buoyed by early results with test subjects, Emotiv decided to take a chance and unveil a prototype in February 2008, at the closely watched Game Developers Conference in San Francisco. There, new video games and accessories can pick up buzz or sink under the gaming community's disdain.

On the show's opening night, with thousands of attendees and reporters in the audience and video cameras rolling, an Emotiv team member named Zachary Drake attempted to move a cube and more, which by this point was something anyone at Emotiv could do in his or her sleep. But for the first time since the team's big breakthrough, the device, which the team had named the Epoc, simply stopped working. Clearly rattled, Drake gamely tried again and again to work his will on the screen, his face a knot of concentration, his arms reaching out plaintively. For a moment, the crowd was silent. "I think people cringed for us," says Le. Then, the murmuring and snickering began. "Welcome to demo hell, folks," Drake said.

The Emotiv team later learned that a powerful wireless network at the facility had wiped out the connection between the headset and the PC. That the demo might fail had never entered Le's mind, and she just stood there, stunned: "We had done so many dry runs and had never had a problem. I was so shocked. I was speechless." The debacle led to widespread ridicule of the company -- "The Force Is Not Strong With Emotiv's Epoc," "Watch Emotiv's Performance Anxiety," and "The Trade Show and Demo Hall of Shame" were among the headlines on gaming sites.

On the other hand, more than 300 people gave the device a shot at the company's booth, and by almost all accounts, it was a big hit and worked well for virtually everyone who tried it. The company was encouraged enough to set a product launch time frame of the 2008 holiday season. The plan was to sell the headsets through game and electronics retailers, as well as online. Meanwhile, competitors were massing. CyberLearning Technology in San Marcos and OCZ Technology in Sunnyvale, for example, have both developed neural headsets. Hitachi in Japan has poured money into potential mind-reading products, and dozens of universities have made efforts to develop better, cheaper thought processors, any of which could lead to spinoffs. There's even an ambitious project funded by the U.S. military, which hopes to have patrolling soldiers communicating by thought within two decades.

But most notably, there's NeuroSky in San Jose, which has developed a single-electrode game-control headband. NeuroSky's device can detect only two mental states -- attention and meditation. But at a projected $50 or so, it is about one-sixth the price of Emotiv's. And for games, at least, keeping it simple could turn out to be an advantage. "People can use ours right away without training," says Greg Hyver, NeuroSky's vice president of marketing. "You can add on all the features you want to a headset, but if people can't use it right out of the box, they won't use it at all." At a conference in October, Square Enix demonstrated a zombie game that uses the NeuroSky device, and Sega is considering releasing a toy sword or a game based on the technology.

Meanwhile, a company called EmSense is making inroads into the corporate market with a headset that measures the reactions of consumers to games, ads, and other entertainment and marketing creations. EmSense hopes to provide its clients with a detailed, high-tech analysis of what flies with what types of consumers. Coca-Cola used EmSense last year to help fine-tune its Super Bowl advertising decisions. That's a business Emotiv wants to be in on as it moves beyond gaming, and no wonder. Says EmSense CEO Keith Winter: "The market research business is worth billions. It's an ocean. Gaming is a pond."

Le and her teammates have tried these rival systems and remain confident they don't come close to the Epoc's capabilities. Still, Emotiv decided in September to postpone the rollout. Why? Because it can, Le says. She insists Emotiv's technology edge is insurmountable. She also says funding isn't a problem, at least in the near term; the company raised $13.4 million in a round of financing in 2007 -- the Australian government chipped in, along with three venture capital firms. "Trying to make the Christmas time frame just wasn't necessary," she says. "We don't have to risk the whole business trying to meet an early delivery date." Le even suggests that delaying the product could prove to be a smart marketing move. "We want pent-up demand," she says. "We've already got 5,000 preordered through our website. After we deliver a good experience to those early customers, we can talk about making tons of them for next Christmas." The company hasn't announced a new launch date, but Le says the headset will be out in 2009.

Meanwhile, the team continues to think beyond games. The headset already can be used to control most ordinary functions in common software, such as word processing and spreadsheet programs, by taking the place of a mouse -- the cursor simply follows your gaze, and you can think your way into triggering the equivalent of a left or right mouse click. Not only might that be a critical tool for people who may have trouble working a mouse, but it might end up feeling a lot more natural for the rest of us. The technology could be applied to entertainment, Le says, noting that wearing a headset while listening to music or watching a video would allow your computer to track what you like and dislike down to individual choruses or scenes, and start automatically tailoring what it serves you, perhaps via a website -- a sort of brain-powered iTunes that Le hints she would like to see Emotiv own. The headset could help educators who work with children who have autism or attention deficit disorder. Social networking sites could use emotional feedback from the headset to create compatible online gatherings or even assist in matchmaking. Well, maybe. "Love is tricky to identify in brain signals," Le allows. "I'm not sure we know how to tell it apart from lust."

Some powerful partners have come on board. IBM (NYSE:IBM) is working with Emotiv to develop a corporate version of the headset that would allow, for example, virtual conferencing with avatars that represent people's expressions and feelings -- so you would know who was engaged, who was bored, who was laughing at your jokes, and, maybe, who was pretending to laugh. Ketan Paranjape, chief of technical staff at Intel, says the chip giant is interested in enlisting Emotiv's headset to navigate via thought three-dimensional representations of corporate data -- the company featured Emotiv prominently at its annual conference for developers. "We think neural devices will be the next interface," he says.

And that brings us, hypothetically, to the day when we are all wearing Emotiv hair plugs, our thoughts and feelings productively ricocheting through our homes, offices, and, through the Internet, the whole world. That's Le's vision, anyway, and she is almost dismissive of lesser goals. "We don't want to be some niche company providing a specific solution to a specific problem," she says. "We have an opportunity to create an industry that will revolutionize the whole framework of technology."

That may well happen. But first, she has to give the world a chance to move that block mentally, before someone beats her to it.

Contributing editor David H. Freedman is a Boston-based freelance writer.

[URL: http://www.allianceofceos.com/press/member_news/2008/the_scientists_at_emotiv_have.php]

Difference Between Asperger's Syndrome and High Functioning Autism - Dr Tony Attwood's View

2009-02-08T06:06:00.000+08:00

Is There a Difference Between Asperger's Syndrome and High Functioning Autism?

Dr Tony Attwood

We have been exploring the nature of autism, as described by Leo Kanner, for nearly 60
years. He described a severe form of autism, typified by the silent and aloof child. We
have only been exploring the profile of autism described by Hans Asperger for about 15
years. The children he described had speech and were active participants in social
interactions. There is currently some debate in the academic literature and between
clinicians as to whether Asperger's syndrome is a unique disorder with a profile of
abilities that does not occur in any other syndrome or simply a form of autism with a
higher intelligence quotient.

There is general agreement that autism as defined by Leo Kanner and 'autistic
psychopathy' (the original descriptive term of Hans Asperger which was later changed
to the term Asperger's syndrome by Lorna Wing) are two conditions within the range of
disorders known as Pervasive Developmental Disorders or Autistic Spectrum Disorders.
In 1994 the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) provided
diagnostic criteria for Asperger's syndrome. The opinion of the authors of the manual,
which was revised in 2000 (DSM-IV-TR) was that Asperger's syndrome could be
differentiated from autism by an examination of the child's early development and the
existence of some characteristics that were rare in children with autism. They considered
that early language and cognitive skills are not delayed significantly in children with
Asperger's syndrome. There is also no clinically significant delay in age-appropriate selfhelp
skills, adaptive behaviour and curiosity about the environment in childhood. The
clinical profile of a child with Asperger's syndrome is also less likely to include motor
mannerisms and preoccupation with parts of objects as occurs in autism but the child
can have a circumscribed interest that consumes a great deal of their time amassing
information and facts. They also noted that the profile of social skills in children with
autism includes self-isolation or rigid social approaches, while in Asperger's syndrome
there can be a motivation to socialise but this is achieved in a highly eccentric, one-sided,
verbose and insensitive manner. Should the child's profile of abilities and developmental
history be consistent with the criteria for both autism and Asperger's syndrome, the
authors of the DSM state that a diagnosis of autism should take precedence.

The diagnostic criteria in the DSM, which provide a differentiation between autism and
Asperger's syndrome, have been examined by several research studies over the last five
years. There has been some criticism from clinicians and research that the criteria do not
identify the disorder Hans Asperger originally described. The four cases he described in
his original paper would be diagnosed, according to DSM criteria, as having autism not
Asperger's syndrome. (Miller and Ozonoff 1997). If one was to use the DSM criteria,
Asperger's syndrome would be a very rare condition.

Research has also been conducted on whether delayed language in children with autism
can accurately predict later clinical symptoms. Three studies have cast considerable
doubt over the use of early language delay as a differential criterion between autism and
Asperger's syndrome (Eisenmajer, Prior, Leekam, Wing, Ong, Gould and Welham 1998,
Dickerson Mayes and Calhoun 2001 Manjiviona and Prior 1999). Any differences in
language ability that are apparent in the pre-school years between children with autism
and Asperger's syndrome has largely disappeared by early adolescence (Eisenmajer,
Prior, Leekam, Wing, Ong, Gould and Welham 1998, Ozonoff, South and Miller 2000).
There is general agreement that children with Asperger's syndrome may not show any
conspicuous cognitive delay in early childhood. Indeed, some can be quite precocious or
talented in terms of learning to read, numerical abilities and in some aspects of their
constructive play and memory. Children with autism can be recognised as having
developmental delay in their cognitive abilities from infancy and diagnosed as young as
18 months of age with a mean age of diagnosis of five years. Children with Asperger's
syndrome are often not diagnosed until after they start school with a mean age of
diagnosis of eleven years (Howlin and Asgharian 1999). However, the signs of
Asperger's syndrome in very young children may be more subtle and easily
camouflaged at home and school. On reflection, parents (especially mothers) and
teachers have often been concerned about some aspects of the child's cognitive
development, in particular their social reasoning, but their concerns may have been
intuitive, and difficult to describe to clinicians. It is not until the child is expected to
show more advanced cognitive abilities that formal assessments indicate significant
delay or an unusual profile in cognitive development.

There has been research comparing the cognitive profile of adolescents with autism and
Asperger's syndrome. The studies have examined the cognitive profile of what may be
called 'High Functioning Autism', that is children with a diagnosis of autism with an
Intelligence Quotient in the normal range, i.e. above 70. The term High Functioning
Autism has been used in the past to describe children who had the classic signs of
autism in early childhood but as they developed, formal testing of their cognitive skills
indicated a greater degree of intellectual ability with greater social and adaptive
behaviour skills than are usual with children with autism. Their clinical outcome was
better than expected. The cognitive abilities of this group of children were then
compared to the cognitive profile of children with Asperger's syndrome, who did not
have a history of early cognitive or language delay. The results of the research has not
established a distinct and consistent profile for each group. Ehlers, Nyden, Gillberg,
Dahlgren Sanberg, Dahlgren, Hjelmquist and Oden (1997) found that only a minority of
each diagnostic group showed a characteristic profile.

One group of researchers, based at Yale University in the United States have suggested,
on the basis of their research studies, that the neuropsychological profiles of children
with Asperger's syndrome and High Functioning Autism are different. (Klin, Volkmar,
Sparrow, Cicchetti and Rourke 1995). However, research by other scientists examining
diagnostic differentiation using neuropsychological testing has not identified a distinct
profile that discriminates between the two groups. (Manjiviona and Prior 1999, Miller
and Ozonoff 2000 Ozonoff South and Miller 2000).

The DSM criteria refer to children with Asperger's syndrome as having, in comparison
to children with autism, no clinically significant delay in age-appropriate self-help skills
and adaptive behaviour. Clinical experience indicates that parents, especially mothers of
children and adolescents with Asperger's syndrome, often have to provide verbal
reminders and advice regarding self-help and daily living skills. This can range from
problems with dexterity affecting activities such as learning to tie shoelaces to reminders
regarding personal hygiene, dress sense and time management. Clinicians have also
recognised significant problems with adaptive behaviour, especially with regard to
anger management, anxiety and mood. (Attwood 2002). Clinical experience and research
has confirmed that in terms of the child's behavioural profile, children and adults with
High Functioning Autism and Asperger's syndrome have a very similar presentation
(Ozonoff, South, and Miller 2000). Both groups benefit from the same behavioural
treatment programs.

The academic may decide whether a particular subject in a research study has a
diagnosis of autism or Asperger's syndrome to ensure that their research examines the
same clinical populations as in other studies. The clinician has other considerations and
decides whether the child has a diagnosis of autism or Asperger's syndrome to help
define and understand their differences to other children. However their
recommendations for treatment for both High Functioning Autism and Asperger's
syndrome are the same.

Clinicians have noted that as the clinical picture of Pervasive Developmental Disorders
or Autistic Spectrum Disorders changes over time, a child may receive a diagnosis of
severe autism or High Functioning Autism at one point in their developmental history
and Asperger's syndrome at a later stage. (Attwood 1998, Gillberg 1998). There is also
the opinion among clinicians that, contrary to DSM, if a child meets criteria for both
autism and Asperger's syndrome, the child is given a diagnosis of Asperger's syndrome
(Mahoney, Szatmari, MacLean, Bryson, Bartolucci, Walter, Jones and Zwaigenbaum
1998)

A dilemma for the clinician is whether a particular diagnosis enables the child to have
access to the government services that they need. In some countries, a child may only
have support in the classroom or the parents receive government allowances or medical
insurance coverage if the child has a diagnosis of autism. Clinicians may write reports
with a diagnosis of autism rather than the more accurate diagnosis of Asperger's
syndrome. This is particularly relevant when one considers the epidemiological research
suggests that one person in 250 has Asperger's syndrome, using the criteria being
adopted by clinicians (Kadesjo Gillberg and Hagberg 1999). Government and nongovernment
agencies, especially Education and Health departments, have usually not
been funded for such an incidence and are reluctant to 'open the floodgates'.

Conclusion

Having reviewed the literature, we may be able to answer the question, is there a
difference between Asperger's syndrome and High Functioning Autism? The reply is
that the research and clinical experience would suggest that there is no clear evidence
that they are different disorders. Their similarities are greater than their differences. We
appear to be taking, particularly in Europe and Australia, a dimensional view of autism
and Asperger' syndrome rather than a categorical approach. (Leekam, Libby, Wing
Gould and Gillberg 2000). At present both terms can be used interchangeably in clinical
practice.

References

Attwood T. Asperger's syndrome: A guide for parents and professionals. London Jessica
Kingsley Publications. 1998.
Attwood T. (2002) Frameworks for behavioural interventions. Child and Adolescent
Psychiatric Clinics of North America. 12 (in press).
Dickerson Mayes, S. and Calhoun, S.L. (2001) Non-significance of early speech delay in
children with autism and normal intelligence and implications for DSM-IV Asperger's
Disorder. Autism. 5, 81-94.
Ehler, S., Nyden A., Gillberg C. Dahlgren Sandberg A., Dahlgren S.O., Hjelmquist, E.,
and Oden A. (1997) Asperger syndrome, autism and attention disorders: A comparative
study of the cognitive profiles of 120 children. Journal of Child Psychology and
Psychiatry, 38 207-217.
Eisenmajer, R., Prior, M., Leekam, S., Wing L., Ong, B., Gould, J., and Welham M. (1998)
Delayed language onset as a predictor of clinical symptoms in Pervasive Developmental
Disorders. Journal of Autism and developmental Disorders, 28, 527-533.
Gillberg C. Asperger syndrome and High Functioning Autism. British Journal of
Psychiatry, 171, 200-209.
Howlin P. and Asgharian A. (1999) The diagnosis of autism and Asperger syndrome:
findings from a survey of 770 families. Developmental Medicine and Child Neurology,
41, 834-839.
Klin A., Volkmar F.R., , Sparrow S.S., , Cicchetti D. V., and Rourke B.P. (1995) Validity
and neuropsychological characterization of Asperger Syndrome: Convergence with
Nonverbal Learning Disabilities Syndrome. Journal of Child psychology and Psychiatry
36, 1127-40.
Kadesjo B., Gillberg C., and Hagberg B. (1999) Autism and Asperger syndrome in sevenyear-
old children: a total population study. Journal of Autism and Developmental
Disorders, 29, 327-331.
Leekam S., Libby S., Wing L., Gould J., and Gillberg C. (2000) Comparison of ICD-10 and
Gillberg's criteria for Asperger syndrome. Autism 4, 11-28.
Mahoney W. J., Szatmari P., , MacLean J.E., Bryson S. E., Bartolucci G., Walter S.D., Jones
M.B. and Zwaigenbaum L. (1998) Reliability and accuracy of differentiating Pervasive
Developmental Disorder subtypes. Journal of the American Academy of Child and
adolescent Psychiatry, 37, 278-285.
Manjiviona, J. and Prior M. (1999) Neuropsychological profiles of children with
Asperger syndrome and autism. Autism 3, 327-356.
Miller, J.N. and Ozonoff, S. (1997) Did Asperger's cases have Asperger Disorder? A
research note. Journal of Child Psychology and Psychiatry. 38. 247-251.
Miller, J.N. and Ozonoff,S. (2000) The external validity of Asperger Disorder: Lack of
evidence from the domain of Neuropsychology. Journal of Abnormal Psychology 109,
227-238.
Ozonoff S., South M., and Miller J.N. (2000) DSM-IV defined Asperger syndrome:
Cognitive, behavioural and early history differentiation from High Functioning Autism.
Autism 4, 29-46.

Copywrite 2003 Tony Attwood

[URL: http://www.sacramentoasis.com/docs/8-22-03/as_&_hfa.pdf]

Difference between Asperger's Syndrome and High-functioning Autism

2009-02-08T05:47:00.001+08:00

1) About Asperger's Syndrom
一九四四年，在维也纳执业的小儿科医师汉斯"亚斯伯格，率先提出关于亚斯伯格症的案例报告。但是他的文章以德文发表，语言本身即造成藩篱；加上他研究的个案数目，又比肯纳医师在一九四三年发表的研究个案少；而且亚斯伯格医师描绘患者时的精确性以及概念性的陈述，均不及肯纳医生。以上种种原因，让亚斯伯格医师的报告，并未如肯纳医生类似的研究，获得学界广泛的关注。事实上，直至一九八一年，才有人陆续开始整理、发表其临床个案，并引用"亚斯伯格症"这个名词表述这些个案的临床特征，西方世界才真正开始关注这一群患者。

　　相关文献从此逐渐累积，但研究文章大量出现，则是一九九○年以后的事。这个障碍被列入自闭症的亚型，至今已有超过十年的历史；然而学界对这个障碍的界定，却不断有纷云的讨论。大多数学者同意将亚斯伯格症归纳在自闭症的诊断之下，但对于是否应将其独立为一个亚型，或应将之视为高功能自闭症的变异状况，至今仍有争议。争议的主因是高功能自闭症患者与亚斯伯格症的分界并不明确，即使长程追踪研究的结果，也无法清楚显现两者之间的差异。

2) Difference between Asperger's Syndrome and High-functioning Autism

区分亚斯伯格症和婴幼儿自闭症（肯纳症），主要关键点为患者三岁前的语言发展与智能，是否均在正常的范围内。但是对于智力正常的高功能自闭症患者而言，若无法澄清早年的语言发展史，便会产生辨认上的困难。而且由于大部分亚斯伯格症患者发现、就医或接受诊断的时间较晚，因此这个亚型出现后，许多临床工作者便将某些语言发展出现轻度障碍、在临界接近正常范围的患者，或者智能轻度障碍、临界接近正常范围，但是有人际关系问题的患者，或者行为局限、固执与怪异的患者，甚至许多不明的人际、社交或社会情境学习困难的患者，通通归类在亚斯伯格症之下，导致亚斯伯格症的诊断，更不容易被人所了解。不过由于目前通用的诊断手册中，并无关于高功能自闭症操作定义的描述，因此亚斯伯格症也可以被视为目前唯一被界定的高功能自闭症。

　　亚斯博格症估计盛行率约在万分之二到二点五之间；美国一项对新泽西洲及特定小区的研究，则显示此症的盛行率约为万分之三左右。该症常见于男生，出现率约为女生的八倍。Safra指出瑞典的盛行率约为千分之七，而Neil指出在美国的出现率约为千分之二，近年的研究显示，每千名7-16岁的儿童中，约有3.6至7.1位为亚斯博格症，较自闭症患者多（大约每一万名出生的新生儿中，有7-16位为自闭症患者）。亚斯博格症病患的男女比例约在10-15：1，以男性居多。

　　一般而言，亚斯博格症儿童和高功能自闭症儿童的差异性很小，通常被称为自闭症的延续或是变异的自闭症因此有些亚斯博格症儿童，也常被误认为是自闭症，但其和自闭症之间仍存在着差异性。

　　语文智商是判断的标准

　　一般在定义亚斯博格症和高功能自闭症，通常以智商七十以上来作为范围。一九九八年，调查三百三十个个案研究发现，高功能自闭症儿童在语文智商方面，普遍低于亚斯博格症儿童，高功能自闭症儿童语文智商平均为七十七，亚斯博格症儿童则为九十八；在操作智商方面，亚斯博格症儿童为九十，高功能自闭症儿童为八十六。研究结论显示，语文智商是可以做为诊断亚斯博格症儿童和高功能自闭症儿童的标准。

　　自闭症儿童对于某些事情大多有特殊的兴趣或特殊的天赋，例如机械性计数的能力、机械性音乐的能力、机械性的判断能力，比较不属于思考性能力，而亚斯博格症儿童则不同，亚斯博格症儿童可能一直会思考诸如"美国应该有一州是没有空气的"。

　　国内有个典型的亚斯博格症儿童，他就是一直在专研印度橡树，连叶脉偏向几度时受风会比较大的问题都会去思考。

　　另外，在语言的流畅性方面，对亚斯博格症儿童没有困难，两岁前即会出现单字，三岁就会说整个句子，但四岁前，你、我、他还是会混淆，而且会有反复和重复对方话语的情况。相对于高功能自闭症所特有的机械性特殊能力，亚斯博格症儿童在特殊能力方面则属思考性的，例如曾有个国外知名的心脏科专家，即是亚斯博格症患者，他就是对于心脏特别感兴趣。

　　亚斯博格症者的鉴定方法

　　在语言方面，亚斯博格症和高功能自闭症最大的差异在，高功能自闭症的自发性语言非常少，不会流畅的表达，亚斯博格症儿童则在自发性语言和对谈上并没有问题，问题则在于对谈时，亚斯博格症儿童会有"冗长的对谈"，不管对方有没有兴趣，会和对话者一直谈同一件事情（例如印度橡树），而引起对方的反感，进而影响到其人际关系的互动。

　　在动作方面，高功能自闭症儿童的大肌肉动作没有问题，亚斯博格症儿童则动作非常笨拙，他们一般的标准有四项：一、模仿肢体动作有困难，二、无法顺利的接球，三、单脚站立有困难，四、两手无名指弯曲有困难。

　　在社会互动能力方面，和自闭症儿童不同的是，亚斯伯格症儿童是具有能力、有兴趣，且会去参与，但因为他的社会直觉和一般人有差异，所以无法了解人际互动的意义。例如请他举右手，他会举左手，原因是他面对着施令者，会以模仿的方式，跟着施令者举相同的手。

　　所以在教导亚斯博格症儿童时，应注意其"参考点"的问题，以教写字为例，不要面对着他写，而是到他身旁教导他，以免写出来的字左右上下相反，造成家长又要担心孩子是否还有视觉知觉统合的问题。

　　在攻击暴力行为方面，亚斯博格症儿童因有满高的道德标准，因此也会引发互动上的冲突。例如过马路时，看到有人闯红灯，他们会马上义正严词的制止："不行，叫警察来抓你喔！"也曾有一个亚斯博格症儿童常扬言："我要拿刀子来杀那些坏人。"像是发生类似的情况，就很容易和其它人发生冲突，而被误解有攻击暴力行为。有时候，他们是因为被"逼急"了，才会产生攻击暴力行为。

　　此外，有些过动儿也曾被误判为亚斯博格症儿童，一般正常儿童出现过动的机率为百分之四到百分之六。

　　根据国际精神医学会的鉴定标准，亚斯博格症儿童鉴定的标准有：一、语言发展问题，二、社会互动，三、行为问题，四、非精神症状况的行为问题。前三项和自闭症的鉴定标准是相同的，主要是以第四项来作为判别的不同。利用视觉线索来解决问题。

　　亚斯博格症儿童的情感相当丰沛、敏感，很在意别人的看法、嘲弄或挑剔，有时候一个嘲弄或挑剔，会使其产生低自尊，甚至有忧郁症、焦虑症的症状；在教育上必须使其了解别人的意向、行动、态度有时并非是负面的。例如，曾经有一个亚斯博格症女童在过生日时，因看到蛋糕上的小裂痕，使得原本高兴的情绪，顿时转为嚎啕大哭，原来她从蛋糕上的裂痕，联想到山川河流的切割，以及自己的身世背景和不被他人接受的人际关系。

　　如何为亚斯博格症的孩子选择适当的治疗？

　　当父母首次由医师的口中得知，孩子罹患的是亚斯伯格症(以下简称AS)时，脑中闪过的第一道问题常是"接下来怎么办呢？"。真正的答案，其实还是在孩子身上。各种专家及医师都有满腹经典要协助你的AS孩子，但世界上真的没有某种治疗是放诸四海皆准，适合每一位病童的。父母的重责在于为自己的孩子找到最适合他的治疗策略。

　　截至目前，已发展出许多AS的治疗模式。但受限于研究对象的数目太少，父母将会发现许多治疗方案在执行时未必实用。最重要的是，至目前为止，世界各地的精神医学专家对AS的诊断标准仍未有一致的看法，治疗方式也因而五花八门。有的父母因而转向"有经验的父母"求助。总而言之，父母必须多方收集信息，先行筛选掉对孩子无帮助的治疗方式。在配合治疗师或医师治疗时，父母不必对于疗效过于惊慌或计较。记住，只要治疗方式是正确的，孩子的行为或情绪就会出现你所期望的转变。反之亦然。

　　当然，有些治疗需要数周以上才会出现疗效。如果在耐心等待一段时间，或问题没有改善、甚至是恶化时，父母就必须立即再与治疗师或医师讨论。休息一阵后，你可以选择另一种治疗方法，也可以再给旧方法一次机会。

　　在惊慌无助中，许多父母会选择性的注意到一些"治愈"的AS个案报导。父母满心期盼地打听，他们怎么"好的"？是什么神秘的治疗？维他命或稀有矿物质的补充？其实，AS的症状、轻重程度相差极大。某一位个案"痊愈"了，但他（或她）可能是症状与你的孩子完全不同的一位AS病童，或甚至是被误认为是AS的孩子。

　　因此，我们强烈建议父母们多看、多听、多比较，也多搜集讯息来协助自己及其它无助的家长。有时，治疗一般情障、智障、或正常儿童情绪问题的方法也都适用AS孩子。

　　［如何选择适合孩子的治疗？］

　　在开始任何一种治疗时，父母不妨先思考下列数个问题：

　　1）我选择的这种治疗是要针对孩子的什么问题，要改善什么问题？没有一种治疗是全方位的。不妨与治疗师或医师讨论即将进行的治疗（不论是行为治疗、感统治疗、职能治疗或语言治疗）对孩子的帮助及治疗极限。如果治疗师告诉你这种治疗可以改善孩子一切问题时，一定要请他详细说明改善症状的原因。如果他在解释时使用太多专有名词，就要进一步请他「翻译」成你听得懂的语句！

　　在与治疗师谈话时，最好可以做笔记。把你的疑问、你得到的解答及新的发现等都记好，才可有效率地利用每一项及每一次的治疗及治疗时间。最重要的是千万不要不好意思问问题。

　　举个例子，如治疗师告知你孩子有「精细动作障碍」时，你必须弄清楚，这个毛病会使孩子出现书写的困难，或不会自己扣扣子。因此，如果你不能体会「精细动作」对孩子的影响，就要问个明白！

　　2）治疗到底要进行多久？

　　大部分针对AS的治疗都没有「结束」的时刻表。孩子的各种问题常纠缠不清（如：社交技巧不好导致情绪困扰；协调能力不好使得学习及写字能力变差）。因而许多治疗时间都是以月或年来计算。目前受限于保险制度，有的治疗会在进行一段时间后停止。这时如果孩子的进步仍有限，父母自己必须持续协助训练孩子。

　　3）除了到医院治疗外，老师在学校及父母在家中还有什么协助孩子的方法吗？

　　一旦孩子在治疗中学到某些技能，父母不妨立即在生活中或学校教室内强化他的印象。譬如孩子在职能治疗中学会分辨外形一样，但触感完全不同的物体时，我们就可以在超市与他一起进行同样的辨识练习。如治疗师以隔离法（time out）来处理孩子的情绪时，我们可以同时告知老师，当孩子在教室中有不当行为时，也可以time out方式来使他冷静下来。

　　4）在家中治疗孩子时，父母要注意什么？

　　许多父母在"旁观"孩子治疗一段时间后，就会跃跃一试，在家中为孩子进行治疗的工作。其实许多治疗项目，尤其是牵扯到心理层面的治疗时（如：行为处理、情绪治疗），技巧常只是工具而已。好的治疗师还必须可以客观地观察孩子的改变，冷静地维持自己中立但坚定的态度。但父母在"治疗"孩子时，往往无法像治疗师一样，因为经过完整的训练，有能力审思自己的情绪，而在不知不觉中带给自己及孩子更多压力。有的父母则认为与AS孩子相处已够令人心烦了，就把治疗工作交给治疗师，自己只努力做好"父母"的角色。

　　不管你决定如何面对AS孩子的各种治疗选择，记着：

　　1.这是一场长期抗战，要随时保持客观，不要吝于寻找资源及发问，但也不要累坏自己。有时候你会对某一种治疗"意兴阑珊"或"忍无可忍"时。这时，至少先与治疗师谈一谈再中止治疗。因为往往是孩子或你最无法解决的问题，在治疗上最困难，带给父母的挫折也最大。记住！保持客观！

　　2 .孩子才是治疗的重心。孩子在成长过程中，会逐渐了解到，他一定是"有问题"的，才需要定期至某处"治疗"。想想看，他的压力有多大！？我们其它的人都只是在敲边鼓，他却必须在正确时间做出正确反应。所以，请常常用力称赞孩子既有的优点（记性好、会帮忙作家事…）、他对治疗的耐心及勇于改变的气魄。

Asperger Syndrome - A CNN Manager's View (转载)

2009-02-08T05:39:00.001+08:00

Asperger's: My life as an Earthbound alien

One CNN manager, who asked to remain anonymous, recently learned -- at 48 -- that she has Asperger's syndrome, a form of autism. Today she shares an inside view of life with the condition.

ATLANTA, Georgia (CNN) -- Recently, at 48 years of age, I was diagnosed with Asperger's syndrome. For most of my life, I knew that I was "other," not quite like everyone else. I searched for years for answers and found none, until an assignment at work required me to research autism. During that research, I found in the lives of other people with Asperger's threads of similarity that led to the diagnosis. Although having the diagnosis has been cathartic, it does not change the "otherness." It only confirms it.

When I talk to people about this aspect of myself, they always want to know what it means to be an "Aspie," as opposed to a "Neurotypical" (NT). Oh, dear, where to start . ...

The one thing people seem to know about Asperger's, if they know anything at all, is the geek factor. Bill Gates is rumored to be an Aspie. We tend to have specialized interests, and we will talk about them, ad infinitum, whether you are interested or not. Recognizing my tendency to soliloquize, I often choose silence, although perhaps not often enough. Due to our extensive vocabularies and uninflected manner of speaking, we are called "little professors," or arrogant.

I don't quite understand small talk, and early in my adult life, solecisms were frequent. At meetings, I launch into business without the expected social acknowledgments. It's not that I don't care about people, I am just very focused on task. Do you have to rehearse greeting people to reinforce that you should do it? I do.

I am lucky to have a very dear friend who savors my eccentricities. She laughs, lovingly, about one particular evening at a restaurant. Before she could get seated, I asked her what she knew about the golden ratio and began to spew everything I know about it. I re-emphasize how lucky I am to have her as a friend, because this incident occurred long before I was diagnosed.

A misconception is that Aspies do not have a sense of humor. It is true that we can be very literal, so we often miss the humor in everyday banter, but we can and do enjoy even subtle humor. Our literal interpretations, however, can be problematic.

In first grade, whenever someone made a mess in the classroom, the teacher would ask a student to get the janitor. The student would come back with Mr. Jones (not really his name), who carried a broom and large folding dustpan. When I was asked to get the janitor, I looked all over the school and reported back to the teacher that I could not find it. After all, the person was Mr. Jones, so the janitor must be the object, right?

I lack the ability to see emotion in most facial expressions. I compensate for this deficiency by listening to the inflections in people's voices and using logic to determine emotional context. The words people choose, their movements, or even how quickly they exit a meeting can provide clues to emotion.

I also have intensified senses -- touch, taste, smell, sight, and sound -- so I am attuned to lights, noise, textures, and smells. In a "busy" environment, I will eventually go into sensory overload and my mind will go blank. When this happens, I have to "go away" mentally for a brief period to regain focus. When I "return," I have to piece together what occurred while I was "away." The additional mental processing I must do to function every day is fatiguing, and I don't handle "ad hoc" very well. Being asked to respond quickly in the midst of all this other processing is difficult, sometimes impossible.

I am so sensitive to touch that a tickle hurts me. This is the hardest concept for most people to understand. How can a tickle hurt? All I can tell you is that it does, so I avoid being touched except by those who have learned how to touch me.

Hugs are dispensed infrequently, but if I do hug someone, I resemble Frankenstein's monster, arms extended to control contact. When my dad (who I suspect is an Aspie, too) and I hug, we both have "the approach." We sometimes miss and have to re-approach a couple of times until a brief, awkward hug is achieved.

In school, other children noted my differences, and I was bullied (and tickled into fits of despair) for years. Already needing extended periods of time alone, my response was to become even more of a loner. Uh oh. When you are weird, you are a joke. When you are a loner, you frighten people. It's always the quiet ones. ...

I am married (wow!), and my brilliant husband is an absolute sweetheart. I don't know any other man who has the self-confidence to be pushed away (sometimes sharply), both physically and mentally, as often as he has been. He has been gentle and patient (and, yes, frequently emotionally depleted) as we both worked through my need for space, tendency to go so deep into my own world that the real world and everyone in it cease to exist, and sensitivity to touch during the 26 (soon to be 27) years of our marriage.

I live with anxiety, because the world can be overwhelming and people have expectations that I always, sooner or later, fail to meet. I cannot begin to tell you how many times I have been told that I am rude, inaccessible or cold, yet I have never purposely tried to harm anyone, nor do I mean to be, well, mean.

I could tell you so much more, but instead let me share one last insight. Don't pity me or try to cure or change me. If you could live in my head for just one day, you might weep at how much beauty I perceive in the world with my exquisite senses. I would not trade one small bit of that beauty, as overwhelming and powerful as it can be, for "normalcy."

[URL: http://www.cnn.com/2008/HEALTH/conditions/03/28/autism.essay/index.html]

(zz) about advanced edu in the states

2009-01-13T22:45:00.001+08:00

(转载)

本人在学校里呆的时间比较长，在美国的大学里先是念书，再是教书，呆了不少年，几个学校，行话叫，'Been at both sides of the desk'。今天就谈谈我所了解的美国大学，希望能给有志于留学美国的青年才俊提供一点参考。

美国的高等院校一共有三千多所，可以分为三类。最多的是社区学院（Community College），它们一般是两年制学校，毕业时给一个副学士学位（Associate Degree），毕业生可以转到四年制大学继续深造，学过的课程学分也可以转过去。社区学院一般由州政府出资，学费很低，兼具成人教育的功能。第二类是教学型四年制大学（Teaching University），它们以教学为主，一般可以授予学士（和硕士）学位，这类大学中公立的和私立的都有。

最后一类叫做研究型大学（Research University），它们是研究和教学并重，可以授予博士学位。这类大学在美国有两百多所，最著名的大学绝大多数属于这一类，它们自然也就是中国学生留学深造的目标。这类大学有私立的，更多是公立的。私立大学的经费主要来自捐款和学费，所以学费要高一些。公立大学的一部分经费来自各州政府，学费就会低一点儿，但因为州政府出钱，州内学生的学费和州外的学费差距可能会很大。来自中国的学生要按州外学生付费，所以学费也不会比私立学校低多少。

如果按"US News"的排名，研究型大学的前二十名都是私立大学，例如哈佛、耶鲁、普林斯顿等常春藤名校等，公立大学中排名最前的伯克利（UC Berkeley）只能排到二十一、二名。这一排名更是注重于本科教育的比较，对于研究生、博士生教育来说并不一定准确。常春藤学校注重综合素质的培养，很多校友都身居高位，可能会给后辈同学提供一些帮助，所以，本科去那里确实很好。研究生却不一样，例如，伯克利几乎所有的博士专业都可以排在前十名，可以媲美任何其他学校，它的博士学位也可以说是含金量最高的。而且，还要看不同的专业，甚至不同的实验室。例如，哈佛的法学院和医学院很好，耶鲁的法学院很好，但如果说工科专业，哈佛不一定比得过排名五十以外的普渡大学。计算机（CS）、电子工程专业（EE）最好的是MIT，斯坦福，伯克利，CMU等等。

美国大学综合排名的好坏，主要看三大学院，法学院（Law School），医学院（Medical School），和商学院（Business School）。美国最好的学生多集中在这三个学院，不像中国的好学生多在工学院（Engineering School）。所以，工科的学生选择院校时，不用太看重大学的综合排名，更应注重本专业的排名。美国综合排名前五十（或前一百）的大学都相当不错，一般每个州都有一、两所不错的大学。每个州都有至少一所某州大学（University of X)和某州立大学（X State University），这些学校的主校区都不错（有的学校会有多个校区，不一定都好），前者一般好于后者（也有例外，如 Ohio State要好于Ohio University）。某州大学中比较好的有 University of California，University of Texas(Austin), University of Virginia，University of Michigan，University of Illinois 等，州立大学中好的有Pen State，Ohio State等。

美国是一个联邦制国家，其权利和财富不是集中在某个地方，而是分散在各地。好的大学也是分散在全国各地，基本上每个州都有一两所不错的、有全国性影响的大学，相互之间的差距也并不太大。由于公立大学学费低于私立大学，州内大学低于州外大学，所以，很多最优秀的学生会选择一个本州的州立大学，而不是去排名最高的大学。结果是最优秀的美国学生是分散在各个大学，而不是集中在某一两所大学内。

前面说每个州都有一、两所好的大学，但有两个州的好大学却远远超过两所，就是麻州和加州。麻州是美国最先发展的地方，号称"The Spirit of America"，大学有两百多所，波士顿地区最集中，如哈佛，MIT，东北，Boston College等等。加州也是美国经济、文化最发达的地区之一，好大学也很多。兄弟在美十多年，大多数时间出没于加州南北各地，这疙瘩咱比较熟，下面就专门介绍一下位于加州的大学。

1. 加州的大学
加州的大学中，能排在全美前五十名的有九所，私立的有三所(加上公立的加大系统（UC System）六所)，北加州湾区的斯坦福大学（Stanford University），和南加州洛杉矶地区的加州理工学院（CalTech）和南加大（USC）。斯坦福大学称得上世界上最好的大学之一，各科都很强，足以抗衡东部的常春藤学校。斯坦福的工科很不错，大批斯坦福的毕业生在湾区开公司，才形成了硅谷这一世界级的高科技公司集中地。斯坦福人开的公司有惠普，思科，谷歌，雅虎，升阳（SUN）等等。
     CalTech 是一个小而精的学校，学生数少于两千，理科和工科都很好。按比例计算，CalTech的诺贝尔奖获得者世界最多。CalTech同时还管理着同在 Pasadena市的喷气推进实验室（JPL）。世界著名的JPL其实比CalTech还大，有五、六千研究人员，由CalTech的教授们创建，最初为军方研究火箭技术，现属于美国宇航局（NASA）。
     USC位于洛杉矶市中心地区，该地区治安不太好（USC是我见过的唯一有围墙的美国大学）。因为靠近好莱坞，USC的媒体专业非常好，工学院也不错。USC中的富家子弟很多，所以有人称之为 USC（University of Spoiled Children)。USC的死敌，同城的UCLA的学生们也把ＵＳＣ称为 University of Second Choice，其实两校的综合实力相当，体育都很强（USC是橄榄球的老大，UCLA是篮球的老大）。
    加州的公立大学包括社区学院，加州州立大学系统（Cal State System)和加州大学系统（UC System）。州大系统属于教学型大学，可以授予学士和硕士学位，有二十多所校区遍布加州各地（一所例外，圣迭戈州大（SDSU）属于研究型大学）。加大系统属于研究型大学，可以授予博士学位，有十所校区，北加州五所，南加州五所。一般认为，加大系统的学校分三个档次，第一档包括UC Berkeley，UCLA和UC San Diego；第二档包括UC Davis，UC Irvine和UC Santa Babara，这六所都可以排在全美前五十名；第三档包括 UC Riverside，UC Santa Cruz和UC Merced。其中Merced校区刚开张两三年，还有一个 UC San Francisco只有医学院，声誉很好，排名可居全美前十。
     亚裔家庭一般重视教育，小孩们也比较好学，所以加大系统中亚裔学生的比例很高，一般可以达到30%-40%（加州的亚裔人口低于总人口的10%）。亚裔比例最高的是尔湾加大（UC Irvine），将近 60%，所以UCI又有一个外号叫"中国移民大学"（UCI，University of Chinese Immigrants)。UCLA中亚裔也近半数，被称为"University of Chinese and Lots of Asians"。不光是加大系统，在美国各大名校中的亚裔学生都偏高，所以美国高等教育照顾少数民族的政策中从不包括亚裔，只照顾西裔和非裔学生。
      加州的学生中间流传着有一种说法，如果你又聪明家里又有钱，那你应该上斯坦福或CalTech；如果你只聪明但没钱，就去Berkeley或UCLA；如果你不太聪明但有钱，你就去USC；不太聪明也没钱，你去其他加大各校；如果你又不聪明又没钱，那你只好去州大或社区学院好了。

2.教授治校
    美国大学中实行所谓的" 教授治校"的政策，说的是大学中重大决策的权利大都掌握在教授们的手中，确切的说，是掌握在由教授组成的各种委员会的手中。校长的主要职责是筹款，系主任多为兼职，一般由资深教授们轮流担任，在管理系里的日常事务外，还需要担任一定的教学任务（我呆过的一个系，系主任的管理工作算30%工作量，也就是说，他还需要承担我们其他教授70%的教学任务）。换句话说，校长和系主任并非教授们的领导，一个教授的前途也不掌握在他们手中（这一点很重要）。
     美国大学一个系的教授并不太多，一般有二、三十个，这些教授有权成为终身教授，这叫"Tenure-Track Faculty"。教授有助理教授（Assistant Professor），副教授（Associate Professor）和正教授（Full Professor）。助理教授是还没有得到终身教职的教授，而大多数副教授和正教授都有终身教职（Tenured Professor）。一个教授的职责有三方面，教学（Teaching），科研（Research）和服务（Service）。教学好懂，每人必须教一定的课时，再大牌的教授也不能逃脱。科研就是申请研究经费，带研究生、博士生，发学术论文。服务指的是参加学校里的各种委员会，参加学生的指导答辩组，和参与组织学术会议等。一个助教授要评Tenure，这三方面都要做得比较好。
      教授中工作最勤奋的是助理教授（多为新毕业的博士），他们一般需要工作五、六年才能评Tenure。从第二年起，每年都要准备一份完整的材料，总结一年各方面的工作成果，上交给由资深教授组成的提升评审委员会（Tenure and Promotion Committee，权力很大的一个教授委员会）。如果到第五年还不能达到终身教授的标准，该同志就只能再呆一年，同时开始找工作，一年后走人。大多数学校还好，只要达到一定标准的助教授都可以晋升Tenure，不用和别人争位子。有些变态的学校，如MIT的工学院，一个Tenure的位置可能会招三个助理教授，让他们血拼几年，最后留下一个最好的（好像大家都喜欢拿MIT做反面典型，不过有一次我和一位 MIT机械系的助理教授聊起这事儿，他说，我们还好吧，你不知道，哈佛……）。
     当然，评为终身教授后也不能太松懈，要想有所作为，还是得不断努力。Tenure是铁饭碗，但犯了重大错误也会被开除，例如，论文剽窃、造假等。从助理教授开始，基本上每位教授都是自成一体（没有像中国那样的教研组），带一帮学生艰苦奋斗。一个教授干得好不好，不在于他和系主任或校长的关系，而在于学生们喜不喜欢他（每门课都有学生评语），他申请到了多少科研经费，发了多少高水平的论文。也就是说，他的前途由学生（教学评审），本系其他教授（晋升评审），和其他学校的同行（科研经费的评审）来共同决定。
     一个系的好坏，关键是看你能不能招到好的教授。所以，招聘教授是最重要的工作。决定聘请谁的权力，由所有教授共同掌握。美国的研究型大学只有两百多所，一个系平均一年也就有一个空缺，加上不是每个学校都有这个系，以计算机系为例，一年的教授空缺也就有大概一百个。所以，这种位置的竞争非常激烈，只要是有计算机博士学位的人都可以申请，竞争者往往来自世界各地，经常是一个位置有上百人申请。系里的招聘委员会进行第一次筛选，选出最优秀的几位，邀请他们来学校访问，做一场学术报告，与系里的各个教授单独进行半小时的面谈。最后，系里的所有教授投票，一人一票，决定聘请人选。
      以上说的都是教授，除他们外，高校教师中还有一些讲师（Lecture）。他们属于临时聘请（non-tenure track)，只负责讲课，不用承担教授们的其他责任，不能评Tenure，报酬也比较低。系里还会聘请一些助教（Teaching Assistant），大多由研究生，博士生担任，他们的工作是协助教授教学，例如批改作业，带本科生实验课等。

3.研究生入学申请
     研究生的录取由学院或系里的录取委员会决定（Application Committee），这个委员会由教授们轮流担任。通过这个委员会审查，获取录取通知书一般不太难，中国学生更关心的是怎样拿到奖学金。奖学金有三种，一种叫Fellowship，这是真正的奖学金，不需要干活，这种机会不多；还有一种叫TA（助教，Teaching Assistant），这是要帮助教授教学，基本每门课都有一个，这些位置由录取委员奖给最合格的申请学生；还有一种叫助研（RA，Research Assistant），帮助教授做科研，经费来自教授的科研基金，RA由各个教授自己决定。
     所谓全额奖学金，就是说包括学费和生活费（tuition and living expense)，一年大概有两、三万美元。听起来不少，但去掉学费后，也就是勉强温饱。美国大学倾向于把奖学金给博士研究生而不是硕士研究生，因为硕士在美国是一个中间学位，要求不高，很多人一年就可以毕业。而博士生要呆四、五年以上，这样才有时间做一点像样的研究。所以，要想拿奖学金，最好是申请读博士（本科毕业也可以申请直接读博士）。
     各种奖学金中，Fellowship的机会比较少，不干活只拿钱的事儿在哪都不多。TA和RA的位置多一些，RA更受学生们的欢迎，因为TA主要是干一些重复性的杂事，不太长本事，RA是科研工作，可以学功夫，发论文，有助于尽快拿到学位。所以，要想拿到RA的位置，在通过正常渠道申请的同时，还要记着和你感兴趣的教授套磁，这非常重要，也是一门需要掌握的艺术。
     给教授发信时，一定不要简单的"Copy and Paste"，只把第一行的 "Dr. A"换成"Dr. B"，然后发给所有的教授。美国的教授们每天都会受到大量的套磁Email，一眼就能识破这类信件。还有就是不要给系里的每个教授都发一份，因为几个教授中午一起吃饭时一聊天，发现人手一份同样的Email，您老马上就没戏了。某些好事的教授还会给所有的教授发一封信，警告不要再理会这个学生（我就收到过这种信）。
      所以，正确的做法是：上、中、下各个档次各选几个学校，每个学校选两、三个你最感兴趣的，与你的方向最接近的教授，仔细研究一下他的网页，下载他几篇论文，好好读一读，然后花功夫写一篇情深意切的Email，一定要提一提你对他的研究、论文的看法，观点对不对没关系，还有你曾经有的，和他的研究领域相关的经历。一定要下工夫，要精耕细作，而不是广种薄收。我认识的一位教授，他专门做了一个网页给申请的学生，在网页的最后有一个密码，写给他的申请信的标题中必须含有这个密码，否则他根本不看。你不仔细读他网页，辛辛苦苦准备的Email就会被他直接给删掉了。
    还有，有些教授要等你被录取后才会考虑给你RA，所以，一定要和系里多联系，查看你申请的当前状态，注意备齐所有的材料，该交申请费也就交了吧，不要因为一个小的细节而误了大事。通过录取关并不太难，国内学校成绩不错，材料齐备大概就行了，除非是排名前三的学校（例如，CS专业，MIT，Berkeley，Stanford的录取不太容易，可能需要下点儿功夫）。难点在于争取奖学金，这方面竞争相当激烈。

4.结论
从总体国力来看，美国可能是在走下坡路，但在高等教育方面，美国的大学的质量至今还是无与伦比，尤其是研究生教育。所以美国大学吸引了来自世界各地最优秀的有志青年，竞争自然也就激烈，但物超所值。几分耕耘，几分收获，No Pains，No Gains。在美国大学里几年的良好教育，加上一、两个含金量高的学位，一定会帮你在以后的人生中打开几扇门，但进门后能走多远，就要看你本身的实力了.

转载Xi Tan同学去年写的一篇文章

2008-12-28T17:15:00.001+08:00

在计算机领域做研究的一些想法（转载）

# 前言 #

1. 讨论一下计算机领域的牛圈和'带头大哥'；

2. 讨论一下科研方法；

3. 讨论一下计算机领域的学术论文（会议、期刊）；

# 第一章 #

计算机的大牛90%以上都在美国，所以只讲讲美国的CS。别的国家没什么太大的参考意义（英国、法国、匈牙利、日本、香港、新加坡、大陆、加拿大），不过还是说两句：第一句是，美国以外的地方CS和美国有差距，主要是没钱；第二句是，搞科研也讲'近亲繁殖'，美国以外的其他地方很明显'人手不够'。没钱的问题看大陆就知道，高性能计算、硬件、网络。。统统没办法干。当年人家Stanford跑一个粒子加速器就几百万美金，中国哪个高校有这资金。人手问题也很明显，像Stanford的Dan同学，以前在Cololado Boulder，后来不也被挖走了？像以前呆在加拿大一个人闷做研究的Han Jiawei老大，不也被UIUC挖走了？为什么呢。说白了还是资源。Han Jiawei 02年被UIUC从加拿大的SFU拎到UIUC，转年就成了IEEE的FELLOW。为什么。说白了就是'近亲繁殖'。直到现在美国相当数量的大学（就不说全部了）都非常认可同行的推荐。学校要各个同行评分，发paper也是同行review，nominate也要同行，甚至PhD的application也相当依赖reference letter。另外呢，就是这些资源相当丰富的地方容易产'奶牛'。当年吴健雄也才第九名考进的中央大学，可是人家一跑美国去就成了实验物理大牛，还当了美国协会的会长。物以类聚，人以群分。你说90%的老大都在美国，你呆在印度做CS，有啥意思。不管是Science还是Engineering，还得靠inspiration。Inspiration靠什么？显然是要以Group为研究的基本单位，像Dan Jurafsky和Jiawei Han那样的人毕竟是少数。最好不还是被几个牛棚给挖走了？这玩意真没办法，是趋势。不说废话了，来扯美国的CS。

美国CS首当其冲的就是"五大牛棚"：MIT，Stanford，Berkeley，UIUC，和CMU。其他的牛校像Washington，Princeton，Cornell，Wisconsin等等都是非常不错的，只不过可能光芒还不够。而且还有很重要的一点，就是这些学校的faculty好多都是'五大牛棚'出来的，自然地位也就低一些。尤其是Princeton和Cornell这类学校（其他还包括JHU，Maryland，Duke，甚至综合排名非常靠后的Amhest），好多Professor都是牛棚混出来然后过来独当一面的。特殊点的就是Washington和Wisconsin，还有诸如Caltech这类学校，他们的Alumni也出过不少人才。

首先是MIT。我脑子里（或者说几乎所有工科学生的脑子里）可能下意识地定死了MIT是工科最牛查查的学校。甚至我一直认为（至今仍然），MIT的脑袋都是畸形，整个MIT不是牛棚，而是一个ZOO。MIT简直就是发了战争财。开始做雷达，整的它的无线电啊，EE什么的巨牛无比。然后就是冷战，国防部投了好多美金做乱七八糟的东西。CSAIL还没有合并的时候，MIT的计算机实验室叫AI实验室。就是这个实验室，早期做了很多开拓性的工作。主要是冷战的时候（90年代以前），美国国防部投资了无数的资金，狂搞AI的项目。很多学校在那个时候得到了很大的发展，譬如Texas Austin，譬如UMass Amherst，他们的CS系便是那个时代的产物。可是后来AI的投入没有打到预期的产出，糟蹋了好多国防部美好的愿景，项目一个接一个的流产，大师也一个接一个的归隐。看看MIT那些早年毕业的大牛（50-60年代左右），基本都有深厚的物理背景，这就意味着他们不仅数学知识扎实，而且具有深厚的电子电气的背景。这些"牛群"在冷战后奔向各个其他的institution，自然就成了领军人物。好多人说，MIT虽然没有做什么牛哄哄的东西，可是任何一个人都可以证明，其他institution都是他在学术上的孙子的孙子。Orz. （麻教主千秋万代，一统江湖！！ o(∩_∩)o...）事实上的确，比较一下MIT的PHD毕业生，在学术上是其他学校无法超越的。至少去年我在港中文'打杂工'的时候，我们组的'带头大哥'Professor Helen M. Meng就是在MIT拿的BS,MS和PHD；然后中大做Vision的老大Professor Xiaoou Tang，也是MIT的PHD。这两人明显带有MIT培养出来的严谨风格，而且学术嗅觉非常之好。记得我给Helen做presentation的时候，她问过我好些问题，都是一语中的的。而且她还鼓励我做Vision和Speech的数据融合，事实证明也是很好的思路。Helen在MIT是Stephanie和Victor的学生，Stephanie又和我们剑桥的Steve有很好的合作项目和官方渠道（例如CAM-MIT）。这两个组一直都在联合做Spoken Language Dialog System的项目。又一次雄伟而彪悍无比地证明了我说的'近亲繁殖'理论。。。娃哈哈~ MIT的老师我只接触过CSAIL的老大Professor Victor Zue，语音组的老大Professor Stephanie和Vision组的几个Professor。首先感觉是都很NICE，说话都很客气。尤其是Victor，记得去年在上海参加MIT面试的时候和Victor聊天，他老是笑呵呵的，想来脾气应该很好。虽然去年没有去成MIT的Vision组，可是总能感觉到MIT那种技术的金属质感给我带来的吸引和震撼。希望今年能去MIT念Stephanie的PHD啊~~ Bless...

然后扯一下Stanford。其实我原来对Stanford感觉蛮好的（现在感觉也不错），我在LA认识的朋友也应该是最多的（最多又是Stanford，然后才是Berkeley，UCLA和Caltech。SYF小朋友啊~ 嗯，我在Stanford最好的几个朋友之一了。SYF，看到这个帖子给师傅留个Message哈。嘿嘿）。可是因为种种原因，以前就压根没有打算过去斯坦福念书（主要是MWJ小朋友不让我去。我又乖又听话，所以就没申请了）。Stanford给我的感觉就是超级大，而且几乎没有什么软肋。历数美国诸多CS高校中，唯一能在AI方面和MIT抗衡的就数斯坦福了。而MIT现在AI仿佛有走下坡路的趋势，而斯坦福倚其地理优势和财政强势，迅速崛起。Sorry，不应该是崛起，是第二波浪潮~~ 斯坦福的AI，诸如视觉，语音和自然语言，机器人等等，都有大牛撑腰。然后在体系结构和数据库方面又依赖硅谷的强大应用平台，有着得天独厚的发展资源。AI作为CS的灵魂，斯坦福已经有了；体系结构和数据库这些应用背景很强的领域，硅谷也给斯坦福与生俱来的优势。当然，那帮学生也不是省油的灯，好多PHD没念完就跑了。什么GOOGLE啊，YAHOO啊，通通都迅速崛起了。另一方面也反应了斯坦福的学生商业头脑很好，很灵活，不像书呆子（譬如MIT，譬如Caltech。哈哈）。真没什么说的，牛哄哄的。对了，补充一点，斯坦福坐拥硅谷的土地，真是巨有钱啊。。。望尘莫及。

第三头大牛要数Berkeley。好多人和我讨论，和我争辩，到底是Berkeley厉害还是MIT厉害。我觉得没什么好比较的。因为每个学校发展的方向都不太一样，CS和CS没法比，可以比的只是某个组，譬如MIT的AI就比Berkeley的好，Berkeley的网络就比MIT好。Berkeley的传统优势就是网络，操作系统等等。早期Berkeley的CS毕业生好多去各个高校当教授，大多也做的是网络和操作系统这一块的东西。现在Berkeley的AI也发展了起来，诸如图形图像，语音语言都有了很大的发展。Berkeley作为公立学校的老大，收费低，又地处LA，开个什么国际会议啊，养个老啊，都挺好的。UC系统又联系广泛，而且Berkeley还和诸如Stanford，UCLA和Caltech这样的牛校贴得这么近，不做点东西出来真是对不起这地理位置。想想我本科毕业的学校'西北工业大学'，其实计算机在中西部应该是最强的，在全国我觉得某些领域也能在前五（譬如计算机应用）。可是相比起同是国防科工委的北航，就没有了地理优势。西安显然没有北京有钱，地理位置显然没有北京好，而且显然也没有清华北大这样的学校和他交流，甚至连北邮北理北工大这样的学校在西安都没有。哦，对了，有个西电。Sorry，西电也是巨牛无比的。我甚至觉得在很多领域西电比西工大牛多了。记得我在CUHK的时候，看过几篇文章都是西电的老师和港中文的老师一起写的（譬如那篇影响我很大的Xiaou文章，就是和西电的老大一起写的）。然而，西工大的老师是和蔼可亲的。以前给予我诸多帮助的WQ老师，ZYN老师我感觉在学术上都是可以独树一帜的人。事实上也的确给了我很多启发和思考的灵感。当然还有我们更加和蔼可亲的XL老师。真是又是老师又是朋友。想起在清华-港中文做RA的那段日子，的确教会了我很多东西。北航的老师我只和LW校长聊过天。LW老师做的好像是软件理论，也是英国毕业的（好像是爱丁堡）。虽然LW老师都是校长了，可是那时候和我聊天一点都没有什么架子（5年前了），和蔼可亲的很。哎，大凡大牛都是和蔼可亲型的啊。扯着这么远，无非就是要说Berkeley有多么好的地理优势，把UC其他几个学校远远抛在了脑后（至少CS是这样）。譬如UCSD，譬如UCI，甚至UCLA也远不及Berkeley。去年我给UCSD的Alon做presentation，人家好像才40岁，就已经是IEEE的FELLOW了，这样下去怎么得了。Alon虽然是做Information Theory的，但是却为我的project提了一个非常好的建议，取得了很大的突破。这才让我感觉到IEEE Fellow的威力。我那时就想，要是Alon也跑到berkeley去，那该有多猛啊。。。。（插播广告：英语语法）'Had Professor Alon joined Berkeley, he would have already made far greater contribution to the information industry.' EAP没白来。。o(∩_∩)o...哈哈~ Berkeley的教授我就不认识几个，不过有几位朋友在那，传说没有Stanford漂亮。呵呵~

第四头大牛是UIUC。我对UIUC的印象最开始来自高我几级的SZ。SZ和我一样都是做OI出身，然后保送到了清华。据说在清华学习十分猛，老是系里前5名，后来又考了老高的GT，结果就去UIUC了。我当时十分郁闷，因为我那时候不是很清楚UIUC在CS领域里是个什么地位。我说怎么这么好一孩子不去Stanford和Berkeley，非跑到'玉米地'去了？不过这以后UIUC这个名字我就记下来了，这是第一印象。然后一个比较深刻的印象就是Jiawei han。我当年读Jiawei Han的书时，他还在加拿大。我也纳闷，我说怎么写了这么牛哄哄的书的人，倒喜欢做武林蒙面大侠了？莫非又是一'隐藏关卡的BOSS'？没想到Han老爷子02年的时候果真就被UIUC挖走了。这时候我才念起UIUC的好，觉得实属牛棚一个了。以前那些虚幻的带有主观臆断的想法通通成了幼稚的偏见。UIUC是干嘛的？回答其实很明确，如果说MIT是为AI而生的话，UIUC就是为硬件和超级计算机而生的。It is UIUC that 当年改良了计算机中的晶体管、集成电路和ALU的好多东西。Intel和AMD，还有早期做chip的Motorola等等，我想都大多受惠于UICU的faculty。自然，这些老faculty拿这些技术继续做硬件和超级计算机便有如鱼得水之势了。所以，包括硬件逻辑电路设计、计算机算术、机器结构和数值分析领域，UIUC都是独执牛耳的领军人物。UIUC的CS相来比较扎实，生源和师资都非常好，自然声誉也很高。尤其是硬件。早期的超级计算机大多出自UIUC之手，譬如ILLIAC的1、2、3、4代以及后来的一些超级计算机，都是这一领域的大手笔。UIUC的这些理论和工业成果和成功，对并行计算机的发展历程做出了不可磨灭的贡献。UIUC的老教授David Kuck就是并行处理的先驱，原来是NASA第一部超级计算机的首席设计师。属于在并行处理这个领域挖了一个坑然后等着后人来'建设社会主义美好家园式'的人物。UIUC早期的发展有很多历史佐证，譬如美国国家超级计算及应用中心(NCSA)在UICU的建立，譬如Marc Andreessen在UIUC读本科大四的时候在NCSA主持编写的Mosaic。无一不是一个又一个翔实的历史介绍。可惜，后来（85年-2000年左右），UIUC的硬件学术队伍老化，没有形成良好的学术梯队，硬件队伍失去了很多元老级的人物，新的professor呢，又无心做这些东西，大多又开始弄软件去了。把UIUC的传统和家业整个换了个门面。不过，正式由于这个原因，UIUC的CS系以拥有众多充满活力的世界级青年学者。例如Josep Torrellas (其弟子有在Cornell ECE，Georgia Tech CS任教的)，Klara Nahrstedt (其弟子有在Cornell ECE，Purdue CS，Toronto ECE任教的)，还有稍老一些的Gerald DeJong (其弟子有在UW-Madison，UT-Austin任教的)等等。前几年刚被Duke挖走的Herbert Edelsbrunner，由于对计算几何的根本性贡献，1991年拿了个Waterman Award，成为历史上第一位获此殊荣的计算机科学家。UIUC的校友也有很多有名的，譬如写了Mosaic并成立了netscape的marc Andreessen，譬如David Kuck的学生陈世卿(Steve Chen)，譬如Lotus Notes的老大Ray Ozzie等等。UIUC CS 的学生毕业后去学术界的不少，Stanford，Princeton，Cornell，UT-Austin。。。都有UIUC的博士挑大梁。在U Michigan CS和UCLA CS，UIUC CS出身的教授更随处可见。在仅有的18名华裔ACM Fellow中，就有6名是UIUC的。另外一个不得不讲得人当然是我们可亲可爱的'刘爷爷'。当年我拿到'蒋震海外研究生奖学金'的时候，还是刘爷爷给我面试的，还要我背唐诗宋词。吓得我当时很紧张，竟然把沁园春雪给背错了几句，刘爷爷还很机敏地当即纠正了我的错误。哎，仍然记忆犹新啊。刘爷爷的确是个非常（N次幂，N > 3）的人，至少一点架子都没有，和蔼可亲得很。连我当年去MIT的推荐信也是刘爷爷亲手执笔的。可恨的是当年没有申Princeton，要不然panel一看是刘爷爷的亲笔推荐信，肯定就把我给收了。。。哈哈哈~ Professor C.L.Liu是属于桃李满天下的那种人。在国内最有名的当然要数Professor Andrew Yao了，人家在哈佛念完物理就跑到UIUC去念计算机了，当年的导师就是我们可爱的'刘爷爷'。后来姚老大成了世界上第一位拿过图灵奖的华人，当然，现在还是唯一一人。可以想象，当时我和图灵奖的导师聊天的时候有多紧张。。。可惜本人实在愚钝，在CS领域也毫无建树，刘爷爷把Victor从美国请过来给我面试去MIT我最后都没有如他老爷子的愿，跑到剑桥这地方天天骑自行车看康河来了。。。哎~ 真是惭愧。另外关于UIUC不得不说当然是他的发展'现象'。为什么说是'现象'呢？因为UIUC是有名的'玉米地'，常年面临加州等地名校的"挖人"威胁。尽管不少教授在成名以后离开，UIUC计算机系仍然凭借着为中青年人才的成长营造最好氛围，在小地方办成了世界一流的研究重镇。我想，UIUC可能是惟一几个不靠地理位置发财的CS牛棚吧。这个'现象'值得很多学校借鉴，譬如西工大，西电，譬如中科大等等。

最后呢，当然是牛哄哄的CMU了。事实上，CMU的CS应该比UIUC要稍微好一些。因为CMU貌似就只有一个CS在撑门面，所以它的CS硕大无比，几乎没有弱项。尤其厉害的是它的vision和robotics，当然还有software。CMU的Robotics实在是名气太响了，'附送'的Vision也沾了很大的光，导致CMU在AI领域的大哥地位也无人能撼。我的本科学校去年就走了一个师兄去CMU，貌似就是做ROBOTICS的。什么FIFA CUP之类的足球机器人啦，CMU最喜欢招这些人了。其实我当年准备去CMU的VISION组的，可惜我当年实在是迷恋MIT，就没有申请CMU，现在想起来，如果当年能去CMU也是个不错的选择。对了，我一位很好的朋友现在就在CMU。可爱的CX小朋友。这哥们是少年班的天才，在CMU跟随图灵奖大师做'玄学'（他自己如是说的），哈哈哈。CX绝对属于天才型的，几十位图灵奖的逸闻趣事他都知道。引用我们JK同学的话叫'简直太神奇了'。我们漂亮的JK小同学如今在MIT做EE，所以高智商夸赞高智商总是很有分量。CX做事很踏实，也很有目的性，他就只跟图灵奖做理论计算机的研究。当时把我佩服得直咂舌。不过，现在终于如愿以偿了，人家以后可是图灵奖的弟子啊。。。哎~~ 和我的Professor Steve Young不是一个级别的。可爱的Steve，您啥时候也拿个图灵奖让俺们沾沾光啊。CX同学，过几年回西安的时候记得再吃饭聚一聚~（看到这个给我留言哈）。CMU不仅Robotics好，Software也是技术一流。据说现在微软招得最多的软件开发员工都是CMU毕业的。某种程度上说，CMU的老大们挣了我们不少钱。哼哼~ 另据CX小朋友介绍，CMU的CS系实在是过于庞大了。。。巨多教授。哥们，这还真够挤的~~ 好了，牛棚都介绍完了。都是我印象中的东西，肯定有很多不准确的数据和理解。不过应该大致差不多。够了~

# 第二章 #

我思考后的结果告诉我，其实做科研的步骤，或者说写科技文献的步骤，不是很复杂（当年我做了4年的数模果真没白费，哈）。我总结了一下，大概就一下几点：

1.Introduction

选好一个学术方向后，对此方向上的已有成果进行阅读，分析，分类, 搞清楚已解决的问题是什么，现存的难点是什么，热点是什么, 写出综述报告。其实就是literature review啦。在CUHK LAB的时候，XL老师和Helen老师老是和我提这个词，我已经比较熟悉了。另外呢，刚入门的人应该看看Journal上的东西，毕竟那是沉淀了之后的东西。然后才可以慢慢看看conference的东西练内功。

2. Problem formulation

把所要研究的具有实际工程背景的学术问题进行描述，并转化成数学问题。数学一直都是最强有力的描述工具，当然，也是最正统的科学工具。

3. Main contributions

找到适当的数学工具，给出上述问题的理论上的解决方案，得到理论上的结果, 并用定理的形式进行阐述。还是数学，科学家和工程师只相信数学和事实。

4. Simulations or experiments

通过计算机仿真或实验研究进行上述理论成果的验证。CS，计算机科学与技术，首先是科学，是理论；可是最后终归要转化成实际的产品，不像做Pure mathematics的人，整天只要YY就可以了。。。-_-

5. Conclusions

给出一般性的结论，以及需要进一步研究的问题。有头有尾的事情。一次不可能把问题都解决好，总有可以瞻望的地方，可以改进的嘎吱角落弯。

# 第三章 #

哎，扯期刊和会议。其实这是最没意思的东西了。想当年，我刚了解SCI和EI，整天琢磨着怎么在线看Nature和Science等等。其实，CS里面根本不是这么回事。CS是一个日新月异的领域，各种技术都在以不可预测的速度在发展和变化。这和基础科学有着太大的不同了。所以，什么物理化学生物一个实验做好多年，最后发到Nature和Science上面，真正上conference上发表的东西其实没有什么特别大的价值，都是只言片语，远远没有期刊的威力来得大。所以无聊的美国人加菲猫同学（哈哈~ Garfield有一个多好记的名字），弄了个SCI来做索引。弄了个IF把整个学术界搞得乌烟瘴气，尤其是大陆还有亚洲一些国家，整天就想着弄几篇高IF的牛paper。可是，CS压根就不是这个形式。CS的publication最大特点在于：极度重视会议，而期刊则通常只用来做re-publication。大部分期刊文章都是会议论文的扩展版，首发就在期刊上的相对较少。也正因为如此，计算机期刊的影响因子都低到惊人的程度，顶级刊物往往也只有1到2左右―-被引的通常都是会议版论文，而不是很久以后才出版的期刊版。因此，要讨论计算机科学的publication，首先就压根和IF无关。另外一个现象就是CS的会议规模都很有限，有时候只登十来篇甚至三四篇论文，有的还是季刊或双月刊。很多好的会议每年只录用三四十篇甚至二十篇左右的论文。所以，CS的几乎每个领域都有好几种顶级刊物和好几个顶级会议。

最牛哄哄的当然是'Journal of the ACM(JACM)'了，ACM的官方学刊。可是，这个鸟刊只刊登那些对计算机科学有长远影响的论文，因此其不可避免地具有理论歧视。事实上确实如此：尽管JACM征稿范围包括了计算机的绝大部分领域，然而其刊登的论文大部分都是算法、复杂度、图论、组合数学等纯粹理论的东西，其它领域的论文要想进入则难如登天。这让我想到了两件事情：一件是meritocracy；一件是GRE填空里面的一道讲专家如何鄙视layman的题目。哎~ 罢了。另外一个就是'Communications of the ACM (CACM)'了。从某种意义上来说，CACM比JACM要像Nature/Science很多。JACM上登的全是长篇大论，满纸的定义、定理和证明，别说一般读者没法看，就连很相近的领域的专家都未必能看懂。而CACM则是magazine，既登高水平的学术论文和综述，也登各种科普性质的文章和新闻。即便是论文，CACM也要求文章必须通俗易懂，不追求数学上的严格证明，而追求易于理解的直觉描述。在十几二十年前，CACM的文章几乎都是经典。但最近几年，由于CACM进一步通俗化，其学术质量稍有下降。

除了ACM老大的东西外，就是IEEE的了。'IEEE Transaction on Computers'是IEEE在计算机方面最好的刊物。但由于IEEE的特点，其更注重computer engineering而非computer science。换句话说，IEEE Transaction on Computers主要登载systems, architecture, hardware等领域的东西，尽管它的范围已经比大部分刊物要广泛。就刊物的质量而言，ACM Transactions系列总体来讲都高于IEEE Transactions系列，不过也不可一概而论。大部分ACM Transactions都是本领域最好的刊物或最好的刊物之一。大部分IEEE Transactions都是本领域很好的刊物，但也有最好的或者一般的。然而，非ACM/IEEE的刊物中，也有好的甚至最好的。例如，SIAM Journal on Computing被认为是理论方面最好的期刊之一。CS方面的会议论文事实上起着比刊物论文更大的作用。大部分会议都是每年一次，偶尔也有隔年一次的。正规的会议论文需要经过2-4个甚至更多个审稿人的双向或单向匿名评审，并且所有被接收的论文会被结集正式出版。大部分ACM的会议都是本领域顶级的或很好的会议。大部分IEEE的会议都是本领域很好的会议，但也有顶级的或者一般的。会议的档次通常可以通过论文录用率表现出来。顶级会议通常在20%左右或更低，有时能达到10%左右。我所知道的最低的录用率为7%。很好的会议通常在30%左右。达到40%以上时，会议的名声就很一般了。60%以上的会议通常很难受到尊敬。但也有例外。大名鼎鼎的STOC(ACM Symposium on Theory of Computing)录用率就达到30%以上，但它毫无疑问是理论方面最好的会议。造成这样的情形，主要是因为理论方面的工作者不多，而大部分人对STOC又有一种又敬又怕的心理。

下面列一些CS的顶级会议和期刊，有些是网上查到的，有些是某些人用SCI的IF排序做出来的：

Computer Vision

Conf.:

Best:

ICCV, Inter. Conf. on Computer Vision

CVPR, Inter. Conf. on Computer Vision and Pattern Recognition

Good:

ECCV, Euro. Conf. on Comp. Vision

ICIP, Inter. Conf. on Image Processing

ICPR, Inter. Conf. on Pattern Recognition

ACCV, Asia Conf. on Comp. Vision

Jour.:

Best:

PAMI, IEEE Trans. on Patt. Analysis and Machine Intelligence

IJCV, Inter. Jour. on Comp. Vision

Good:

CVIU, Computer Vision and Image Understanding PR, Pattern Reco.

Network

Conf.:

ACM/SigCOMM

ACM Special Interest Group of Communication

ACM/SigMetric Info Com Globe Com

Jour.:

ToN (ACM/IEEE Transaction on Network)

A.I.

Conf.:

AAAI: American Association for Artificial Intelligence

ACM/SigIR IJCAI: International Joint Conference on Artificial Intelligence

NIPS: Neural Information Processing Systems

ICML: International Conference on Machine Learning

Jour.:

Machine Learning

NEURAL COMPUTATION

ARTIFICIAL INTELLIGENCE

PAMI

IEEE TRANSACTIONS ON FUZZY SYSTEMS

IEEE TRANSACTIONS ON NEURAL NETWORKS

AI MAGAZINE

NEURAL NETWORKS

PATTERN RECOGNITION

IMAGE AND VISION COMPUTING

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

APPLIED INTELLIGENCE

OS,System

Conf.:

SOSP: The ACM Symposium on Operating Systems Principles

OSDI: USENIX Symposium on Operating Systems Design and Implementation

Database

Conf.:

ACM SIGMOD

VLDB:International Conference on Very Large Data Bases

ICDE:International Conference on Data Engineering

Security

Conf.:

IEEE Security and Privacy

CCS: ACM Computer and Communications Security NDSS (Network and Distributed Systems Security)

Web

Conf.:

WWW(International World Wide Web Conference)

Theory

Conf.:

STOC FOCS EDA Conf.: Best: DAC: IEEE/ACM Design Automation Conference

ICCAD: IEEE International Conference on Computer Aided Design

Good:

ISCAS: IEEE International Symposium on Circuits And Systems

ISPD: IEEE International Symposium on Physical Design

ICCD: IEEE International Conference on Computer Design

ASP-DAC: European Design Automation Conference

E-DAC: Asia and South Pacific Design Automation Conference

Graphics

Conf.:

Best:

Siggraph: ACM SigGraph

Good:

Euro Graph Jour.: IEEE(ACM) Trans. on Graphics

IEEE Trans. on Visualization and Computer Graphics

CAD

Jour.: CAD CAGD

conf.: ICSE The International Conference on Software Engineering

FSE The Foundations of Software Engineering Conferences

ICASE IEEE International Conference on Automated Software Engineering

COMPSAC International Computer Software and Applications Conferences

ESEC The European Software Engineering Conferences

Jour.:

SEN ACM SIGSOFT Software Engineering Notes

TSE IEEE Transactions on Software Engineering

ASE Automated Software Engineering SPE Software-Practice and Experience

呼呼呼~~ 终于写完了。弄了我1、2个小时~~ FT~

以上言论大多为个人关于CS的一些不成熟想法，并不代表本台观点。

通俗一点说就是：'纯属扯淡'。不要当真。

25岁以下的儿童须在女朋友的指导下完成阅读。钦此。

By Xi Tan. 2007.10.6 于英国剑桥大学三一学院绿野猪楼 R10 ~ :-)

美国大学计算机专业的排名 [zz]

2008-12-09T23:44:00.001+08:00

总的来说，前20的CS可以分成三波：

（1） 4 个最为优秀的CS Program: Stanford, UC. Berkeley, MIT, CMU

（2） 6 个其他前10的： UIUC， Cornell, U. of Washington,Princeton, U. of Texas-Austin 和 U. of Wisconsin-Madison，其中UIUC, Cornell, U. of Washington和UW-Madison几乎从未出过前10。

（3）其他非常非常优秀的CS：CalTech, U. of Maryland at CP, UCLA, Brown, Harvard, Yale, GIT, Purdue, Rice, 和 U. of Michigan.

约定：CS＝计算机科学（系）。

总的来说，前20的CS可以分成三类：

一、4个最为优秀的CS Program： Stanford斯坦福大学, UC.Berkeley加州大学（伯克利分校）, MIT, CMU 卡内基梅隆大学

二、6个其他前10的： UIUC诺伊大学－香槟分校，
Cornell康纳尔大学,
U. of Washington,Princeton,
U. of Texas-Austin 和
U. of Wisconsin-Madison，
其中UIUC, Cornell, U. of Washington和UW-Madison几乎从未出过前10。

三、其他非常非常优秀的CS： CalTech, U. of Maryland at CP, UCLA, Brown, Harvard , Yale, GIT, Purdue, Rice, 和 U. of Michigan.

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Stanford

Stanford URL: http://www.stanford.edu/

Stanford的CS是个很大个的CS，拥有40人以上的Faculty成员，其中不乏响当当硬梆梆的图灵奖得主(Edward A.Feigenbaum, John McCarthy) 和各个学科领域的大腕人物，比如理论方面的权威 Donald E. Knuth；

数据库方面的大牛Jeffrey D. Ullman（他还写过那本著名的编译原理，此人出自Princeton）；以及RISC技术挑头人之一的John Hennessy。相信CS的同学对此并不陌生。该系每年毕业30多名Ph.D.以及更多的Master。学生的出路自然是如鱼得水，无论学术界还是工业界，Stanford的学生倍受青睐。几乎所有前10的CS中都有Stanford的毕业生在充当教授。当然同样享有如此地位的还包括其他三头巨牛：UC.Berkeley, MIT 和 CMU.

毕业于U. of Utah(犹他州)的Jim Clark 曾经在Stanford CS当教授。后来就是这个人创办了高性能计算机和科学计算可视化方面巨牛的SGI公司。SUN公司名字的来历是：Stanford University Network.。顺便提一下，创办 YAHOO的华人杨致远曾在斯坦福的EE攻读博士，后来中途辍学办了YAHOO。

CS科研方面，斯坦福无论在理论，数据库，软件，硬件，AI 等各个领域都是实力强劲的顶级高手。斯坦福的RISC技术后来成为SGI/MIPS的 Rx000系列微处理器的核心技术； DASH，FLASH 项目更是多处理器并行计算机研究的前沿；SUIF并行化编译器成为国家资助的重点项目，在国际学术论文中SUIF编译器的提及似乎也为某些平庸的论文平添几分姿色。

Stanford有学生14000多，其中研究生7000多。CS有175人攻读博士， 350人攻读硕士，每年招的学生数不详，估计少不了，但不要忘了，每年申请CS的申请学生接近千人，申请费高达80$。

斯坦福大学位于信息世界的心脏地带――硅谷。加州宜人的气候，美丽的风景使得Stanford堪称CS的天堂。33.1平方公里的校园面积怕是够学子们翻江蹈海，叱诧风云的了。

申请斯坦福是很难成功的，但也并非不可为之。去斯坦福这样的牛校，运气很重要，牛人的推荐也很重要。

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MIT

MIT URL: http://www.mit.edu/

MIT招生好象不看GRE成绩。但MIT的CS是巨牛的，99年最新排名上它和斯坦福被打了5.0 的满分，并列第一。MIT的CS曾为CS的发展作出不可磨灭的贡献，数据流计算的思想和数据流计算机、人工智能方面的许多重大成就，以及影响了整个UNIX界的X-Window……MIT和斯坦福，CMU，UC. BERKELEY一样，都是几乎在CS界样样巨牛的学校。

MIT的Media Arts and Sciences其知名度不在Computer Department下。主要是多媒体技术，信息处理，人工智能……有一大批著名的教授，如Marvin Minsky(Turing Award)……

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UC.Berkeley

UC.Berkeley URL: http://www.berkeley.edu/

同样地处旧金山湾畔，硅谷地带，离Stanford只有大约 50公里的加州大学伯克利校区：UC.Berkeley是美国最激进的学校之一。60年代的嬉皮文化，反越战，东方神秘主义，回归自然文化都起源于此。诗人爱伦金斯堡是当年 Berkeley的代言人。

在当今高科技领域C. Berkeley在缔造新的神话，在文学、数学、化学、新闻等20多个大的学科领域中位居前3。16个诺贝尔奖得主，总数近200的科学院院士、工程院院士，连同众多在硅谷商战中成为亿万富翁的伯克利人撑起了一面汇集天下之英才的大旗。INTEL总裁AndrewGrove毕业于UC. Berkeley。

BSD版的UNIX影响了整个OS界，伯克利的RISC技术后来成为了SUN公司SPARC微处理器的核心技术，巨牛人物David Patterson接下了一个6亿美元的项目用于新型计算机体系结构，特别是IRAM的研究开发。

UC. Berkeley有学生30000多，研究生超过8500。申请费和其他加州大学的分校一样，40$。据一项最近的调查，伯克利已经成为美国大学生最向往的研究生院，高居榜首，其申请的难度可想而知。UC.Berkeley的 DEADLINE一般很早，12月中就截至了，其内部的实际DEADLINE其实要迟一些。

Berkeley的CS是个大系，Faculty中有图灵奖得主以及象 Patterson这样的巨牛。学生的出路同Stanford，MIT，CMU一样，光辉灿烂，前程锦绣，这里不再赘述。CS科研方面，Berkeley也是样样强，门门巨牛。

旧金山湛蓝起伏的海湾，苍翠绵延的山峦，舒心宜人的气候，以及近在咫尺的硅谷…… 这一切的一切不也使得UC.Berkeley 俨然一个CS 学子的世外桃源么？

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CMU

CMU URL: http://www.cmu.edu/

CMU是个位于匹兹堡的不大的学校，学生7000多，校园好象也不大。但这个学校在工程及其他一些领域却是顶尖的学堂。 CMU的CS不单单是个系，而是一个学院，其规模之大，可能只有Stanford, UIUC可比。教师学生的情况同前面3个类似，不再赘述。Mach操作系统，PVM，C.mmp等都有CMU的巨大贡献。

申请CMU的难度很大，因为尽管CMU的 CS Faculty很多，但每年只招不足30人的研究生队伍。

********************************
Cornell

URL: http://www.(cs.)cornell.edu

作为 IVY LEAGUE的成员和一所私立学校，Cornell有其独到的优势。在美国，私立学校一般比公立学校难进，其学生也是经过很严的选拔才录取的，Cornell的CS学生入校后多能享受FELLOW的待遇，其个人经济条件非公立学校可比，加上贵族式校友的提拔，私立学校的出路是很诱人的。

康乃尔在理论计算机方面一直是顶级高手，但在其他CS领域并不总能在前10。 Cornell学生18000多，研究生过5000。CS每年招攻读Ph.D.的学生25 人左右。

********************************
UIUC

URL: http://www.uiuc.edu/

UIUC的工程院在全美堪称至尊级的巨牛，其CS，ECE，EE在历史上都屡建战功。在CS方面，从早期的超级计算机ILLIAC I, II, III, IV到后来的 CEDAR，都是CS发展史上，特别是并行计算机发展史上的重要事件，影响，引导了很长时期的发展。 David Kuck曾是并行处理界的一代先驱。

超级计算机研究开发中心：CSRD，美国国家超级计算及应用中心：NCSA等众多的机构，使得UIUC的CS常常成为研发的领军头领。

大家可能还记得，Netscape-Navigator 的最初开发人员中有个Marc・ Anderssen。这位来自WISCONSIN的小伙在UIUC读本科，大四的时候在NCSA参与编写了MOSAIC，后来他去了硅谷，并在那里遇到了前面提到过的大牛: Jim Clark,SGI的前创始人，两人一见如故，联手创办了著名的网景，并一度在浏览器市场上独霸武林。

随着一代代至尊大师的离去，UIUC 的 Faculty看上去似乎并不引人注目。但得提醒你，UIUC的CS向来以实干著称。我期待着他们下一个惊世之举。

UIUC是个大学校，学生数过35000，研究生院的近万。UIUC的CS很大个，40余个Faculty提供了全面的CS教育和科研项目。每年30多个博士的毕业数目似乎只有斯坦福可以匹敌。

UIUC的Polaris并行化编译器是这个领域和斯坦福的SUIF直接叫板的拳头产品。清华开发并行编程环境时选用了这个系统。只是代码庞大，运作缓慢的Polaris搞的清华有那么一点点瘪西西……

UIUC 在计算机硬件，软件，AI，DB，等各个领域都相当巨牛。特别是硬件，前面提到的ILLIAC，CEDAR……事实上，UIUC在超级计算机系统的研究开发方面决不逊于CS四大天王中的任何一个，甚至有过之而无不及。NCSA建立在UIUC这一事实本身就是佐证。

UIUC-CS 的学生毕业后去学术界的不少，Stanford, Berkeley……都有UIUC的博士挑大梁。但更多UIUC-CS学人还是进入业界，成为业界实干的中坚。

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U. of Washington

U. of Washington URL: http://www.washington.edu/

位于 Seattle的 UW 得天独厚--计算机界的巨牛MS就在西雅图，而且更为要命的是，Bill Gates就是那里儿的人。这位Harvard 的辍学者给了哈佛许多MONEY，但同给UW的钱财相比，实在是小巫见大巫。

U. of Washington位于分光秀丽的WASHINGTON湖畔，气候四季如春。33000多学生中研究生有8000。Seattle最令人厌恶的地方可能就是一年有160天会降水。

UW的CS较大，30多名Faculty成员，每年近20个优质博士毕业，以及大量的Master。估计每年的招生数应该不低，UW的CS在各个方面比较均衡，最强的软件排名第5，而其他领域也一般都能位居前10，好象没有明显弱的地方。

图灵奖得主 Dick Karp从Berkeley告老还乡后又被返聘到了UW的CS。U. of Washington的 CS要求很高，Ph.D.学生入学的平均 GPA 高达 3.86，GRE2160+，加上一般较早的DEADLINE，申请UW是相当有难度的。

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Princeton

Princeton URL: http://www.princeton.edu/

Princeton是个令人神往的地方，这里曾经是科学的世界中心。Princeton的CS不大， 18个Faculty成员，学生数也不算多。科研上除了排名第5的理论，似乎俺还没注意到其他闪光点，望知情人补充。但是，Princeton无疑培养出了大量计算机界的优秀人物，Jeffrey D. Ullman, John McCarthy等巨牛人物均出自大名鼎鼎的Princeton. 在Princeton领受的教育是最好的教育熏陶。

Princeton学校不大，只有6000多学生，研究生不过1700。Princeton 的 CS录取很严，虽然已有不少华人学生就读 Princeton。

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UW-Madison

UW-Madison URL: http://www.(cs.)wisc.edu

UW-Madison的CS较大，35个Faculty，200多个研究生，每年招60-70 个新生。目前几乎 1/4 的 Faculty 来自Berkeley，博士生毕业后有去 Stanford，Berkeley等牛校挑大梁的，但和UIUC类似，似乎进入业界的更多些。然而要在这里拿到博士学位可不容易。超过7成的人，会在中途找到比较理想的工作后，拿着硕士文凭撒丫子就跑，免得被那些无穷无尽的科研项目给整瘪了。一位WISCONSIN的哥们在回答我关于 "该做些什么准备"的提问时说：尽情欢乐享受吧，这样可以 Bring A healthy and energetic you to Madison to survive those projects.

UW-Madison的数据库一直在前 3 位，经常是第1位。这里的数据库由于在设计实现DBMS系统上的传统优势，使得其在业界的声誉相当崇高， MicroSoft 里据说有一帮WISCONSIN的校友从中兴风作浪，Oracle也格外青睐WISCONSIN-Madison的学子。可惜，偶似乎对数据库并不是很感兴趣。

WISCONSIN的硬件，计算机体系结构实力巨牛，99排名第6，对业界相当有影响力。微处理器中的超标量技术（SuperScalar）源于此地；多处理机CACHE一致性的总线侦听SNOOPING协议，IEEE SCI协议等，都是源于此地。正在研究开发中的MultiScalar技术和DataScalar技术据吹可以把微处理器每个时钟周期的指令发射数提到10以上，大大地提高微处理器的计算能力。WISCONSIN的软件99排名第 7。主要是在系统软件方面做OS的设计与实现，WEB上的CACHE策略，支持共享主存和消息传递两种并行编程模式及其混合的并行程序设计语言和编译器，以及由MIDSHIP项目挑起的关于并行与分布式计算，OODB，科学数据库，支持图象查询的新型查询语言以及图象处理等方面的研究。由于美国有大量的卫星图象需要及时处理，加上迫切需要GIS系统的研究开发，这方面的研发使得UW-Madison 捞到了不少经费。

WISCONSIN和UIUC的CS理论都是10名左右。WISCONSIN的Carl de Boor 是逼近理论方面的大牛。

U. of Wisconsin-Madison是个大型综合性的学校，40000 学生中研究生院的超过10000，这万人中有博士生5000，硕士生3500，法学院、医学院、护院、兽医院的职业学生2000人。2200多 Faculty中有多位诺贝尔奖得主，52个院士，18个工程院院士。130个科系几乎涵盖了所有科研领域。科研经费常年位居全美前4。Wisconsin的研究生院稳居 TOP20，而且由于它的大而全，在科研排名上能进前10。UW-Madison在95年NRC 的41项评价中，16项位居TOP10，35项排进了TOP25。

U. of WISCONSIN-Madison的校园位于风景如画的湖畔林荫中. 现代化风格和古典欧美风格的建筑物在平缓起伏的湖岸上交相呼应。学校自吹拥为世界上最美的校园之一。偶不知道其他校园的场景，单从他们在网页上提供的照片来看，的确很美。WISCONSIN的冬天很冷，很长，而且大雪纷飞，寒风凛冽。

需要注意的是，WISCONSIN的CS有点不同于许多其他学校，它隶属于College of Letters & Science. 而不在College of Engineering下面，因此许多偏硬件的项目，比如嵌入式系统，网络硬件、路由，多媒体，通信，自控以及数字信号处理及等项目不在CS Dept，而是在工程院下的 Dept. of Electrical & ComputerEngineering 即 ECE系。那个系也挺大个，比CS还要大不少。98年在工程类排名的计算机工程一项上也排了第9。但偶将来怕跟他们没多少来往。伊拉的网址：

工程院：http://www.engr.wisc.edu

ECE系：http://www.ece.wisc.edu

********************************
URL: http://www.(cs.)utexas.edu/
UT-Austin的CS较大。Faculty中好象有个图灵奖得主。( Edsger Wybe Dijkstra，是那个搞算法的)。好象该系发展比较平衡，最好的AI 排第5，其他几个专业也多能挤进前十。

UT-Austin是个巨大的学校，5万学生，研究生院的可能有1.3万。但学校的主校区却好象面积不足，仅140公顷，按美国大学的标准，太不足了。偶曾见到一张照片，校园周围高楼林立，可能是位于市中心的缘故吧。

总的来说，前 10 的 CS由于在当前国际计算机行业普遍热门的情况下，很难申请，但决不是不可为之的！

********************************

CalTech

CalTech URL: http://www.caltech.edu/

CalTech的CS很小，只有大约5位教授，每年招很少的学生。虽然申请CalTech是免费的，但建议轻易不要尝试。（也别让我这话给吓趴下了）

由于系太小，CalTech 好象只是在计算机硬件，和科学计算的可视化方面很强。该系多年以来一直稳坐 NO.11,12几乎没动过窝, 类似的情况还有斯坦福、MIT，稳居NO.1,2, Cornell稳居NO.5, UW-Madison, 稳居 No.9,10.CalTech的CS和其他系，比如数学，物理，生物等需要大量科学计算的部门联系很紧密。

CalTech 学校也很小，2000名学生中研究生占1100人。 Faculty人数也不多，但几乎个个是巨牛，按平均水平看，CalTech 可能是世界上最牛的学校了。偶好象就没见到来自大陆的学子在该系，可能是偶孤陋寡闻吧。

这是一个实力相当强劲的CS，软件(8)，数据库(4)，AI(9) 三个专业都挤进了前10

********************************
URL: http://www.ucla.edu/

历史上UCLA的CS曾经一度辉煌，上到过第6 (NRC'82)，但近年来一直徘徊在13－15。而且CS的各个专业细目几乎没有一个能进前10。尽管如此，UCLA的CS还是十分强大的。

UCLA辉煌的历史可能在于它对Internet的发展，所作出的巨大贡献。六十年代美国的 ARPA在搞网络互连的开创性研究， ARPA网的四个节点是：UCLA，Stanford 的 SRI,UCSB 和 U. of Utah。此时一位来自美国新英格兰地区的青年: Vinton Cerf不去离家咫尺的 Yale大学，远涉千里，来到了加州。他先在Stanford获得数学学士，然后到UCLA拿下了CS 的硕士和博士。

毕业后Cerf一直在SRI从事ARPA网的研究，特别是如何让它无法正常工作。几年后，Cerf与MIT的一位到业界闯荡的数学教授Kyhn合作研发，搞出了一套软件系统用于网络互连(1973)。这就是TCP/IP协议的诞生。

UCLA 作为 INTERNET 的先驱，地处阳光灿烂的南加州，应当成为CS学生的乐土。加州的学校的确难申请，但也是可以一试的。

UCLA有学生33000人，其中研究院的占 9900人。地处落杉矶的 UCLA,周围几乎有玩不尽的地方，DISNEY，HOLLYWOOD……由于位于大城市，校园不是很大，但风景似乎非常美丽。UCLA的CS较大，规模应该和 U. of Washington 和 UW-Madison类似。

********************************
U. of Michigan

U. of Michigan URL: http://www.(eecs.)umich.edu

U. of Michigan是个非常了不起的学校。在BIG TEN里，从综合的角度上说它可算的上是领头羊了，当然UW-Madison，UIUC 也紧随其后。

这里的CS偏硬的更利害些，硬件排在第9，而计算机工程(7)，EE(5) 都是前10中的巨牛。 MICHIGAN 的 CS 和EE合在一起称为 EECS系。是个相当大个的系，每年招的学生当不在少数。

MICHIGAN的CS估计在历史上也相当牛，UW-Madison CS里的两位来自umich的教授都是院士，在其他CS系里，比如UIUC的，也大有UMICH的牛人在。如前述，UIUC的CS在硬件上极强，而UMICH的CS中有许多UIUC的哥们在那里当老师。

********************************
GIT

GIT URL：http://www.git.edu/

GIT是个较大的学校，具体数字记不清了。GIT的工程院很利害，研发经费仅次于MIT，和UIUC, Umich差不多。CS系的数据库第7，GUI第4。其他没有列在前10，偶也没有去仔细了解过，就一概的不清楚了。

********************************
Brown

Brown URL：http://www.brown.edu/

Brown的规模不大，具体数字记不清了。这所 IVY LEAGUE 的私立学校可能拥有一些类似于CORNELL的优势。CS的GUI可以列在NO.6，好象还有许多关于语音识别等偏人工智能方面的研发项目。

********************************
Harvard

Harvard URL: http://www.harvard.edu

在CS的早期发展史上，Harvard曾经是泰斗级的人物，毕竟CS和数学，物理的渊源太深太长了。可惜Harvard并不重视工程化的东西，现在伊的CS已不能和圈里的巨牛，甚至伊的当初相提并论了。好象王安是这里出来的，Bill Gates也是这里出来的，Harvard毕竟是Harvard，总是名人辈出。毕竟Harvard总是可以招到最优秀的人，甚至是在它很瘪的领域里。但千万别以为哈佛人人牛。据说美国人的调侃中，专门有一条是说哈佛的某些学生是如何令人叹为观止的愚蠢……偶还没有身在美国，不知是真是假。

Harvard不喜欢带工程色彩的东西，CS 是挂在Arts & Science学院下面的Division of Engineering and Applied Science,连独立的一个系好象都不是。除了理论可以排进前10，其他项目怕也拿不出多少货色了。

但是，如果给我一次机会的话，我一定申请Harvard。因为这里是Harvard，你可以学到许多在别的地方难以学到的东西。专业知识并不是全部，况且哈佛的教育是不会差的，虽然它在CS 的科研上没什么好吹的。哈佛的研究生每年超过 20000$ 的FELLOWSHIP是你安心寒窗苦读的强大后盾。

哈佛大学学生18000人，其中研究生院的11000人。Harvard大学拥有世界上最多的诺贝尔奖得主，150多个美国国家科学院院士……哈佛是个巨牛云集的超级牛圈。哈佛的 CS 估计不会是个大个子，招的学生可能也不会多，申请的难度应当很大。

********************************
Purdue

Purdue URL: http://www.purdue.edu/

可能许多人还不知道，Purdue 的计算机系是美国最早成立的计算机系。建系之初一直处于TOP10。在70年代由于本人不甚了解的原因，没落了。Purdue的排名也不太稳定从13到 30的排法偶似乎都见过。Purdue是个大个的学校，有35000学生。其工程院很出名。

********************************
Rice

Rice URL: http://www.rice.edu/

Rice是个位于休斯顿的小学校， 4000个学生，研究生有1600左右吧。CS也不大。优势在于软件，排在第9。别的情况偶不了解，但偶特别想告诉大家的是，该系的 KEN KENNEDY是个巨牛的人物。伊是美国 HPCC 常委的关键人物之一,好象还是总统在信息科学方面的特别顾问。KENNEDY是并行计算领域的大牛牛。前几年，伊义无反顾地承担起高性能 FORTRAN 语言(HPF)的编译器研制工作，项目之大，投入人力之巨，加上伊的权威地位，被人们普遍寄予厚望。可惜后来项目失败了。从此并行计算界陷入了一阵低潮。这几年 KENNEDY 好象转向去作针对特定处理器的后端优化技术了。Rice CS 学生的出路相当好。

********************************
YALE

YALE URL: http://www.yale.edu/

YALE 曾经也进过前 10，NRC'82 的排名上，是 YALE和 UCLA而不是 Princeton和UT-Austin 位于前 10 的榜上。YALE的 CS不大，十几个老师加上为数不多的学生，每年只招六个博士研究生。

和 Harvard这样很重文理的学校一样，YALE 的CS在理论上比较强。但不同于哈佛，YALE有独立的CS系，受到较高的重视。YALE-CS 在 AI，软件方面比较强。著名的 LINDA 并行编程模式是在这里提出并实现的。YALE 的毕业生中到学术界的比到业界的似乎要多，哈佛似乎也是这样。

这里只随便罗列了一些俺顺口拈来的东西，仅供参考。其实 CS其他很好的学校还有很多，比如： UCSD，USC，Columbia，UNC-CH，DUKE，U. of Penn等等。 Columbia在AI，语音识别，自然语言处理等方面颇有造诣，而北卡: U. of North Carolina at Chapel-Hill 和 U. of Utah方面则是顶级牛校。

小米的信

2008-12-09T13:42:00.001+08:00

"Twenty years from now you will be more disappointed by the things you didn't do than by the ones you did do. So throw off the bowlines.

Sail away from the safe harbor. Catch the trade winds in your sails.

Explore. Dream. Discover."

-- Mark Twain

Randy Pausch

2008-11-30T23:23:00.001+08:00

In Randy Pausch's Last Lecture at Carnegie Mellon University in the Fall of 2007, facing pancreatic cancer and the likelihood that he would only live a month or two, Randy summed up his life's wisdom for his kids (then 1,2, and 5). He gave his lecture to several hundred in a CMU auditorium, but it has now been viewed on YouTube by millions of Americans. It's enormously inspiring, tear-rendering and well worth your time if you haven't seen it.

His Last Lecture is now fleshed out in a book of the same name (co-written with Jeff Zaslow, the WSJ reporter that brought his lecture to widespread prominence) and he recently filmed an ABC News Special with Diane Sawyer. His comments are immensely wise for a 47 year old.

Randy Pausch alas died in his home last night (July 25, 2008) as reported by Diane Sawyer on GMA. Randy Pausch's home page is here.

He lived a vibrant life to the end, giving a charge to the graduating seniors at his beloved Carnegie Mellon University just in June 2008

and providing moving testimony to Congress on supporting pancreatic cancer research to help future innocent victims (3/13/08).

Notable quotes:

When there's an elephant in the room introduce him
Brick walls are there for a reason. The brick walls are not there to keep us out. The brick walls are there to show how badly we want something. Because the brick walls are there to stop the people who don't want something badly enough. They are there to keep out the other people.
If there's anything I want to do so badly, I should have already done it.
We can't change the cards we are dealt, just how we play the hand. If I'm not as depressed as you think I should be, I'm sorry to disappoint you.
Work and play well together.
- Tell The Truth. All The Time. No one is pure evil.
- Be willing to apologize. Proper apologies have three parts: 1) What I did was wrong. 2) I'm sorry that I hurt you. 3) How do I make it better? It's the third part that people tend to forget…. Apologize when you screw up and focus on other people, not on yourself.
- Show gratitude. Gratitude is a simple but powerful thing.
- Find the best in everybody…. Wait long enough, and people will surprise and impress you. It might even take years, but people will show you their good side. Just keep waiting.
- If you want to achieve your dreams, you better learn to work and play well with others…[you have] to live with integrity.
Collaboration, treating others with respect.
- Never found anger a way to make things better.
- How do you get people to help you? You can't get there alone. People have to help you and I do believe in karma. I believe in paybacks. You get people to help you by telling the truth. Being earnest. I'll take an earnest person over a hip person any day, because hip is short term. Earnest is long term.
- Loyalty is a two-way street.
- Get a feedback loop and listen to it. Your feedback loop can be this dorky spreadsheet thing I did, or it can just be one great man who tells you what you need to hear. The hard part is the listening to it.
Persistence and hard work.
- When you are doing something badly and no one's bothering to tell you anymore, that's a very bad place to be. Your critics are the ones still telling you they love you and care.
- Don't bail: the best gold is at the bottom of barrels of crap
- Don't complain, Just work harder. [showing picture on screen] That's a picture of Jackie Robinson. It was in his contract not to complain, even when the fans spit on him. You can spend it complaining or playing the game hard. The latter is likely to be more effective.
- Experience is what you get when you didn't get what you wanted…. I probably got more from that dream [of playing professional football] and not accomplishing it than I got from any of the ones that I did accomplish.
Fun, wonder, living your dream.
- Decide if you're a Tigger or an Eyeore. I'm a Tigger.
- It is not about achieving your dreams but living your life. If you lead your life the right way, the karma will take care of itself, the dreams will come to you.
- Never underestimate the importance of having fun. I'm dying and I'm having fun. And I'm going to keep having fun every day, because there's no other way to play it….Having fun for me is like a fish talking about the importance of water. I don't know how it is like not to have fun…
- Never lose the child-like wonder. It's just too important. It's what drives us. Help others.
Risk-taking.
- You can tell the pioneers by the arrows in their backs. But at the end of the day, a whole lot of people will have a whole lot of fun.
- Better to fail spectacularly than do something mediocre. [Randy Pausch gave out a First Penguin award each year when he was teaching to the biggest failure in trying something big and new because he thought this should be celebrated. First Penguins are the ones that risk that the water might be too cold.]
Parenting and kids.
- The best piece of parenting advice I've ever heard is from flight attendants. If things get really tough, grab your own oxygen mask first.
- About his pancreatic cancer: It's unlucky, but it not unfair. We all stand on a dartboard and some of us randomly get hit by pancreatic cancer. But my children won't have me for them and that's not fair.
- Someone's going to push my family off a cliff pretty soon and I won't be there to catch them and that breaks my heart. But I have some time to sew some nets to cushion the fall so that seems like the best and highest use of my time and I better get to work.
- I'm sorry I won't be around to raise my kids. It makes me very sad but I can't change that fact, so I did everything I could with the time I have and the time I had to help other people.
- Importance of people instead of things. Told story of buying new convertible that he was so proud of and taking niece and nephew for a ride. Randy's sister, the kid's mother was telling them how important it was to keep car pristine and kids were laughing because at the same time he was pouring a can of orange soda on the back seats. His sister asked what are you doing and he said "it's just a thing." And nephew Chris wound up being really grateful because he had flu and wound up throwing up on way home. "And I don't care how much joy you get out of owning a shiny new thing; it's not as good I felt from making sure that an 8 year old didn't have to feel guilty for having the flu."
- [not a direct quote] but Randy implores parents to always indulge your children's wild ideas (he talks about how important it was that his parents let him decorate his walls with math formulas, despite the negative impact on their house's resale value) He says: "If you're going to have childhood dreams you should have great parents who let you pursue them and express your creativity."
- It is Important to have specific childhood dreams. (For example, Randy wanted to play football in the NFL, write an article for the World Book Encyclopedia, experience the Weightlessness of Zero Gravity, be Captain Kirk from Star Trek, work for the Disney Company.)
Be good at something; it makes you valuable…. Have something to bring to the table, because that will make you more welcome.
I've never understood pity and self-pity as an emotion. We have a finite amount of time. Whether short or long, it doesn't matter. Life is to be lived.
To be cliché, death is a part of life and it's going to happen to all of us. I have the blessing of getting a little bit of advance notice and I am able to optimize my use of time down the home stretch.

[Original article: http://socialcapital.wordpress.com/2008/04/11/randy-pausch-notable-quotes/]

Whale Box

任意一个类型与字符串相加自动转化成字符串

powershell script to replace strings in a file

托管与非托管的区别

Difference between Heap and Stack

双程计

从google reader上看到的，挺逗的一篇

http://jacquesmattheij.com/A+tale+of+two+programmers

A tale of two programmers

求最大公约数（欧几里德算法）

The two egg problem solution (copy-pasted from http://classic-puzzles.blogspot.com)

Google Interview Puzzle : 2 Egg Problem

0/1 KnapSack problem in C#

Example of the Locus Control Test

How to hide Thinking at Work so that the Non-Programmers don't suspect Slacking?

locked by Michael Myers♦ 12 hours ago

35 Answers

不合时尚的追求- Freeman J.Dyson (转载自水木)

The Business of Mining the Twitter Stream

The Business of Mining the Twitter Stream

(http://datamining.typepad.com/data_mining/2009/02/the-business-of-mining-the-twitter-stream.html)

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小米的信

Randy Pausch

(http://datamining.typepad.com/data_mining/2009/02/the-business-of-mining-the-twitter-stream.html )

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