# Editing-taolu

Some tips about the paper editing. 一些自己在editing的时候容易犯的小错误。

### singular plural

Third person

Check this one to get more details. When using the modal verbs. Do not use this thirs person sigular.

A and B 并列的时候，单复数的使用

http://www.gaosan.com/gaokao/332134.html

### 关于公式后面的标点符号

https://blog.csdn.net/weixin_46309254/article/details/122541026

### Shrink the paper

paper似乎就像是一个含着水的海绵，只要想办法挤，总是能使它越来越dry并且越来越tight. 常用的方式有以下一些：

\setlength{\textfloatsep}{0pt} 这个会减少一些图片与文字之间的距离，要是还有的距离比较大，就使用\vspace{-10pt} 一般是图片的caption部分和图片之间，总有一些可以缩小的空隙。

### Remove the “there be” or “it is”

Here are several examples:

it is necessary to use A to do sth -> using A to do sth is necessary

when there is a fixed number of processes -> when the number of processes is fixed

when there are arbitrary combinations of A and B -> When the combination of A and B is arbitrary.

### Online vs Real time

real time 更强调的是data processing 的 delay。这个文章解释的比较好。这些相关的term更多的是强调不同的delay， 一般比较常见的用法就是real time processing 这种。

Another scenario is the model learning or parameter prediction, we use the online prediction or offline prediction to emphasize the approach, refer to this to get more ideas

https://www.mathworks.com/help/ident/ug/what-is-online-estimation.html

and this

### Tools

Grammaly professional version can reduce most of the typos or the general expression.

https://ludwig.guru/ Can help to find how a particular pharase is adopted in other related articles.

If you do not sure how to translate a particular meaning in an accurate way, just use the the google translate. Or if you not sure if a particular english paragraph can express things in an accurate manner, just use google translate to translate the english version into the native language to see if everything is correct. Sometimes, I translate english into the Chinese by google translate, and find that the meaning is not what I want to expressed.

### Other concrete examples and tips

logic flow

There is one paper to discuss the elasticity, we did not provide enough information at the beginning to discuss details of the elasticity, the reviewer provides a good logic flow to reorganize it.

Write one sentence explaining what elasticity is, then one sentence with the fact that it was identified as a key research challenge, and finally one sentence to explain what the present work focuses on.

Originally, we start with the sentence such as our works focuse on A, B, C and then use several sentences to explain the A B C in detail.

When listing the structure of the framework, we tend to use the overarching method and then the specific point. But when we try to argue sth, do not hurry to give out a specific conclusion quickly and directly. We need to get to that point step by step. Explain the reason clearly and then move to the results, instead of explaining that in a inverse way, other people might not catch the main point in this way.

Try to put the adv after the verb as much as possible. 习惯上adv是放在verb的后面的，尤其是only further之类的，这个和中文的顺序有些相反。

fianlly vs at last

from vs in

There is a expression such like “Z is a PhD student from CS department”, 之后被老师改成了 “Z is a PhD student in CS department”. 这里到底是in还是from自己之前也弄的比较模糊，这个文章 列了几个常见的from的用法，后面加表示具体地方的名词才是那种来自哪里的表述。一般都是一个地名，而CS department是机构的名称，这里使用in表示自己在这个机构里面，这样更合适一些。

others

### Online vs Offline

For the parameter estimation of the model, there are online approach and the offline approach. This article explains a lot of details. From the paper’s perspective, do not too persist into the online method. Since from the research perspective, the accuracy of the model is more important and have more research value. You could always try to update the model and use it into an online scenarios which can recursively update the model parameters.

If there are some certainties of the system or the source data, you can always start with the offline model estimation approach (which is easier for most cases). Just collect a bounch of input data and the output results, and then train the model based on these data. That’s how it works in general.

The online approach might be only suitable for the reinforcement learning scenarios or the case that you can not store the large amounut of data.

This is also a good insight for the in-situ or post-processing approach. In most of the cases, the real-time manner (in-situ processing) is not the necessary one. It is just a way to do the things, but it is not the necessary one. So if you focuse too much on this specific way to do things, you may lose some key points. For instance of ML, the key point is develop the model that works as expected instead of doing the parameter in an online or offline manner.

### Reference

This is a really good one for Chinese students

https://arxiv.org/pdf/1011.5973.pdf

Some writting style references

https://www.computer.org/publications/author-resources/peer-review/magazines#writing