📄 8.htm

📁 美国出国申请所需资料大全
💻 HTM
字号:
<html><head><meta http-equiv="Content-Type" content="text/html; charset=gb2312"><title>CTerm非常精华下载</title></head><body bgcolor="#FFFFFF"><table border="0" width="100%" cellspacing="0" cellpadding="0" height="577"><tr><td width="32%" rowspan="3" height="123"><img src="DDl_back.jpg" width="300" height="129" alt="DDl_back.jpg"></td><td width="30%" background="DDl_back2.jpg" height="35"><p align="center"><a href="http://10.13.21.88"><font face="黑体"><big><big>88</big></big></font></a></td></tr><tr><td width="68%" background="DDl_back2.jpg" height="44"><big><big><font face="黑体"><p align="center">                     陶瓷大全                                                   </font></big></big></td></tr><tr><td width="68%" height="44" bgcolor="#000000"><font face="黑体"><big><big><p   align="center"></big></big><a href="http://cterm.163.net"><img src="banner.gif" width="400" height="60" alt="banner.gif"border="0"></a></font></td></tr><tr><td width="100%" colspan="2" height="100" align="center" valign="top"><br><p align="center">[<a href="陶瓷大全.htm">回到开始</a>][<a href="陶瓷大全.htm">上一层</a>][<a href="9.htm">下一篇</a>]<hr><p align="left"><small>发信人: cntiger (UPENN是我的梦), 信区: Oversea <br>
标  题: 一封 沾 信评论 <br>
发信站: 飘渺水云间 (Wed Apr 14 07:51:34 1999), 站内信件 <br>
  <br>
看你发了半天,也没有人回答,将就写两句吧. <br>
偶也不是大虾,不过想起也算是套中过一个教授的 <br>
(成功率低了点:(  ),俺也就说两句. <br>
为什么没有人reply,主要是这封信太长.我看完第一段就 <br>
气喘不已.教授虽然英文比我好,不过大概不如我有闲工夫, <br>
所以也不见得会看完. <br>
我觉得陶瓷信比较好的方法是尽量写短一些,但是把很长的 <br>
背景材料附在信后.在信里简单的介绍完以后,把附的材料 <br>
的目录列出来,尽量简洁明了.教授对你那段感兴趣能够迅速 <br>
地查到,有不必看完每一个细节. <br>
仅供参考. <br>
  <br>
  <br>
  <br>
【 在 wcia (黑色的眼睛看着你) 的大作中提到: 】 <br>
:  本人发一文,无人RE. <br>
:  可否有大哥大姐再看看: <br>
:  我友,仅收到UMICH,UW的ADMISSION, <br>
:  UMICH的小秘让其与教授套瓷: <br>

:  以下是套瓷文本: <br>
:  请诸位大虾不吝赐教: <br>
:  他的想法是，老美一般比较坦率，绕来绕去人家反而会烦，而且此信的核 <br>
:  心部分应该是介绍研究情况，所以其它段落应该尽量简洁。 <br>
:  Dear Prof. XXX: <br>
:  I am applying for admission to your department. The Admission Committee has <br>
  <br>
:  forwarded my application to the Rackham Graduate School with recommendation <br>
for <br>
:  admission. But Linda Cox told me that financial aid is not available at this <br>
  <br>
:  time. I feel that means I should contact some professor directly for financi <br>
al <br>
:  support. <br>
:  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ <br>
:  作者担心是否第一段就提出FINACIAL AID的问题是不是不太好. <br>
:  I was a member of XXX Class, the top class here at XXX(还不错的) University, <br>
  <br>
:  which is an honor only given to the top 5% excellentstudents. <br>
:  My exceptional GRE(2220) and TOEFL(657) scores can prove this. <br>
:  Moreover,my GPA rank is among top 5% because of the very strict standard of <br>
  <br>
  <br>
:  XXX Class. As a graduate student now, I'm unquestionably the top 1 man <br>
:  in my class. <br>
:  I focused my research on image reconstruction from projections, such as <br>
:  PET (positron emission tomography) and MRI. You must know that image <br>
:  reconstruction is something involving statistical signal processing because <br>
  <br>
:  the projection data is stochastic itself. And tomography is a typical invers <br>
e <br>
:  problem. The subject I'm studying now is spotlight-mode SAR. It can also be <br>
  <br>
:  regarded as a tomographic problem because these two subjects share the same <br>
  <br>
:  principle to a great extent. Thus it is an inverse problem too. Because of t <br>
he <br>
:  ill-posedness inherent in inverse problems, the directly reconstructed image <br>
s <br>
:  contain much noise. Sometimes the noise is even greater than the signal so t <br>
hat <br>
:  the images are of poor quality. What I do in solving these inverse problems <br>
is <br>
:  try to eliminate or at least restrain their ill-posedness. One important met <br>
hod <br>
hod <br>
:  is Tikhonov regularization method. I once presented the maximum entropy <br>
:  regularization theory for MRI based on regularization methods for solving <br>
:  ill-posed problems. I studied an iterative maximum entropy regularization <br>
:  reconstruction algorithm using the generalized Shannon entropy as the <br>
:  regularizer. I also studied an AR (autoregressive) model-based maximum entro <br>
py <br>
:  regularization reconstruction technique using the Burg entropy as the <br>
:  regularizer. Since the projection data in image reconstruction is always <br>
:  incomplete and random, we often use statistical methods, such as the Bayesia <br>
n <br>
:  method, to reconstruct images. I have shown in my personal statement that my <br>
  <br>
:  research interests include inverse problems in image processing. I think my <br>
  <br>
:  research experience and ability makes me eligible to join your group. <br>
:  （这一部分是介绍自己的研究经历和能力，若有行家的宝贵建议则更好。 <br>
:  另外，他打算针对不同教授重点介绍自己不同方面的研究情况） <br>
:  After you consider my application carefully, I'm sure you'll find out that <br>
:  I'm worth your resources. :) Are you willing to give me such a chance? <br>
:  Thank you very much. <br>
:  Best wishes. <br>
:  Sincerely yours, <br>

:  XXX <br>
  <br>
  <br>
  <br>
-- <br>
鼠DDMM们，今日已杀了你们195个同胞,，小的罪过.但小的上有老板在逼，下有DDMM在催, <br>
小的也要把你们换成数据混毕业，所以我还得杀你们。我会尽量把刀磨的快一些， <br>
你们也不要在临刑前对我越来越凶。小的实在无奈，阿弥陀佛！ <br>
  <br>
  午夜梦回，肠寸断， <br>
  无它，杀孽深重耳！ <br>
  <br>
  <br>
※ 来源:．飘渺水云间 FreeCity.ml.org．[FROM: 210.32.148.91] <br>
</small><hr><p align="center">[<a href="陶瓷大全.htm">回到开始</a>][<a href="陶瓷大全.htm">上一层</a>][<a href="9.htm">下一篇</a>]<p align="center"><a href="http://cterm.163.net">欢迎访问Cterm主页</a></p></table></body></html>
⌨️ 快捷键说明

复制代码 Ctrl + C
搜索代码 Ctrl + F
全屏模式 F11
切换主题 Ctrl + Shift + D
显示快捷键 ?
增大字号 Ctrl + =
减小字号 Ctrl + -