Shadow

Unicode Kanji/Kana tables (with ranges)
Shift-JIS tables
EUC-JP tables

I’d always thought the ancient Arabs could count …

The art of the calligrapher

‘The calligrapher needs five things: a fine temperament, understanding
of calligraphy, an endurance of pain and a perfect set of implements’Mir Ali of Herat (died AD 1556)

Alright, I’ve gone a little far today. But someone is obviously much more obsessed with RAID than I do. A link via http://ipod.hackaday.com/ which posted a RAID made of 4 iPod Shuffles (don’t ask me why).

USB FLOPPY DISK STRIPED
RAID UNDER OS X

Now I know this is now just
[…]

iPod Shuffle … hmmm… I am waiting for the price to drop to $60, AND somebody to hack the A-D converter and the FM radio (no, not to hack any iPod into a Shuffle). Interface would be a problem, but that makes the challenge fun.

How Much Should an IPod Shuffle Cost?
 
Analysts […]

G / 2005 (7)

February 18th, 2005
[…]

苧阪直行教授
〒606-8501京都市左京区吉田本町
Phone/FAX: 075-753-2796
[…]

Joh Harris at Number27, is featured in MIT Technology Review’s blog today.

10×10 
posted by Kestrell @ 2/27/2005 3:07:46 AM
TenByten
is a news site created by Jonathan Harris, 25, which uses the most
common words from major news outlets like BBC World Edition and New
York Times International and delivers images to accompany them,
allowing users to search […]

A walker, who rarely sees herself in the mirror, would recognize her
poit-light walking pattern. Not sure I will read it, but sounds
intriguing.

Journal of Experimental Psychology: Human Perception and Performance

Volume 31, Issue 1
,
February 2005,
Pages […]

Senior Lecturing Fellow
ggopen@duke.edu
Tel: 919-641-1122
Fax: 919-613-7231
06A Social Sciences
Durham, NC 27708-0360
Original URL
The Science of Scientific Writing
If the […]

Is it an coincidence that the
identified gene on chromosome 3 is related the Phonological awareness,
rapid serial naming, and verbal short term memory, or were these simply
what they could measure? What if they had defined/measured dyslexia in
a slightly different way — for example, being a slower-than-normal
reader (reading speed, not learning). Given the enormous parameter
space they […]

蒋严   
男，1984年获复旦大学英美语言文学学士学位，1987年获复旦大学现代英语语言学硕士学位。1986至1989年在复旦大学外文系任教。1995年获
伦敦大学哲学博士学位，1993年秋至今在香港理工大学中文及双语学系任教，研究专项为语义学和语用学。

Welcome to my personal page. I am a linguist interested in the study of
meaning [semantics] and use [pragmatics], from both formal and non-formal
viewpoints. My other interests include translation, English grammar, natural
language logic, computational linguistics, literature, and philosophy. I am a
native speaker of Shanghainese, a fluent speaker of English and Mandarin
Chinese. Besides, I have learnt […]

roses are #FF0000
violets are #0000FF
all my base
are belong to you

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After updating some software NewsGator stopped working with my Outlook.
Had to search hard to find the solution. The trick is to go
Outlook->Help->About->Disabled Items->enable NewsGator, and
restart.
I reinstalled NewsGator in the mist of trying to figure out the
problem. This meant I had to re-activate NewsGator, and go through the setup
wizard. I was scared that I’d lost […]

There are some unsual papers in the latest issue of J of Research in Reading. As said in the Editorial:
In this issue, to celebrate the contribution Tony Pugh
and Greg Brooks have made to educational and scientific research, we
present five papers by members of the current editorial board. Each
paper takes as its starting point […]

Naive Bayesian is probably a better alternative. But that defeats the entertainment purpose.

February 10, 2005
关于中国人姓名的算法说明::[Source]
这个事情本来是不原意提起的，只是很多人认为我做到姓名的搜索误差太大，这里也就说明一下，以免让大家认为蒙在鼓里。
1. 查查全中国有多少人的名字和你一模一样 是纯粹的娱乐性产品。
2. 计算机非人口普查部门和公安部门，因此任何输入的词语都将给予解释。
下面介绍本系统的算法，如果你系高中毕业，对概率统计有一定的认识，可以继续：
算法A ：
前文已经声明，我通过网络采集了大约40多万人的姓名，这期间大约有20万的姓名是独立的，现在这个数据库还在变大，今天已经大约有100万的姓名了。
我们假设在这100万的姓名分布和全国13亿人的姓名的分布相近，那么当你搜索“张三”这样一个姓名的话，如果我的数据库
里有70个张三的话，那么全国按照样本的分布就应该是 70*1300000000/1000000 = 91000
就是说全国有91000个人都叫张三。
误差分析 Sigma = f_sigma(70) + f_sigma(1300000000) + f_sigma(1000000) =
11050 就是说，全国张三最多是 91000+11050 = 102050 个张三，最少91000-11050 = 79950
个张三，以上为70％左右的置信区间。
算法B：
根据姓名的概率 ＝ 姓的概率＊名的概率
建立在姓和名的概率分布是独立的分布，P(姓, 名) = P(姓) * P(名)
在100万的数据里，我大约收集到2800个姓，和24000个名，这样关于姓和名的分布就很合理的建立起来了。例如当我们输入“张三
”的时候，算法将是先计算“张”作为姓的概率，然后计算“三”作为名的概率，然后将两者相
乘，再乘以全国的总人数就得到多少个张三。
P(张) = 0.602% ， "三"作为名的概率为 P(三) = 0.4%，因此 […]

Take the monkey quiz, see if you can count. Thanks, Liz.

Of course, I should have thought of it … Chomsky’s classic, the foundation of cognitive psychology, should be on-line, fully and freely accessible, and from nowhere other than CogPrint. Thanks, CogPrint/ePrints.
But wait a minute, what is the Bad News about Noam Chomsky?

A Review of B. F. Skinner’s Verbal Behavior
Chomsky, Noam (1959) A […]