使用latex编写文档
1) latex file
2) pdf file

\documentclass[12pt]{article}
\usepackage[colorlinks,linkcolor=blue,anchorcolor=red,citecolor=green,CJKbookmarks=true]{hyperref}
\usepackage{CJK}

\begin{document}
\begin{CJK}{GBK}{song}

\title{LaTeX 文档}
\author{shi~Cheng\\
shi.cheng@live.com}
\date{\today}
\maketitle
\tableofcontents

\begin{abstract}
  LateX文档中 公式, 中文, 摄氏度, 角度, 定理, 定义, 目录, 链接, 书签, 分数, 开方, 摘要, references
\end{abstract}

\section{公式}
\begin{enumerate}
    \item 无序号公式 使用$\backslash$begin\{displaymath\}与$\backslash$end\{displaymath\}
    \item 有序号公式 使用$\backslash$begin\{equation\} 与 $\backslash$end\{equation\}.
    \item 在段落中直接使用公式, 公式需写在\$ \$或者$\backslash$[ 与$\backslash$]之间
    \item 公式在$\backslash$begin\{displaymath\}与$\backslash$end\{displaymath\} 或者$\backslash$begin\{equation\} 与 $\backslash$end\{equation\}时, $\sum$ 的上下标将自动位于$\sum$的上下方居中. 对于段落中的公式, $\backslash$sum默认上下标是写在右上角和右下角, 如在上下方居中,则须加入$\backslash$limits命令. 例如: $\sum\limits_{i=1}^n a_i$ 的命令为: \$$\backslash$sum$\backslash$limits\_\{i=1\}$\,\hat{}\,$n a\_\{i\}\$
    \item 在公式中插入文本, 使用$\backslash$text\{文本\}, 或者$\backslash$mbox\{文本\}
    \item 公式换行:
    \begin{eqnarray*}
      \cos 2\theta & = & \cos^2 \theta - \sin^2 \theta \\
      & = & 2 \cos^2 \theta - 1.
    \end{eqnarray*}
    code:\\
    $\backslash$begin\{eqnarray*\}\\
      $\backslash$cos 2$\backslash$theta \& = \& $\backslash$cos$\,\hat{}\,$2 $\backslash$theta - $\backslash$sin$\,\hat{}\,$2 $\backslash$theta \\
      $\&$ = $\&$ 2 $\backslash$cos$\,\hat{}\,$2 $\backslash$theta - 1.\\
    $\backslash$end\{eqnarray*\}\\
    其中\&是对其点，表示在此对齐。*使LaTeX不自动显示序号，如果让latex自动标序号，则去掉*
\end{enumerate}

\section{中文}
\begin{enumerate}
  \item 在$\backslash$begin\{document\}后加入$\backslash$begin\{CJK\}\{GBK\}\{song\}
  \item 在$\backslash$end\{document\}前加入$\backslash$end\{CJK\}
\end{enumerate}

\section{摄氏度, 角度}
\begin{enumerate}
    \item 摄氏度 $30\,^{\circ}\mathrm{C}$ code: \$30$\backslash$,$\,\hat{}\,$\{$\backslash$circ\}$\backslash$mathrm\{C\}\$
    \item 角度 $30^{\circ}$ code: \$30$\,\hat{}\,$\{$\backslash$circ\}\$
\end{enumerate}

\section{定理, 定义}
定义环境, 使用 $\backslash$newtheorem\{defineName\}\{Definition\}[section]\\
defineName (可更改) 是定义的短关键字，用于标识“定理/定义”。Definition (可更改)是“定理/定义”的真实名称, 显示在最终文件. 方括号选项可选, 用于指定``定理''的标号。
\newtheorem{defineName}{Definition}[section]
\begin{defineName}[text]
  This is a definition
\end{defineName}
code:\\
$\backslash$newtheorem\{defineName\}\{Definition\}[section]\\
$\backslash$begin\{defineName\}[text]\\
  This is a definition\\
$\backslash$end\{defineName\}\\

\section{目录, 链接, 书签}
\begin{enumerate}
  \item 目录 在添加目录处使用 $\backslash$tableofcontents 命令
  \item 链接 使用 $\backslash$usepackage\{hyperref\} 命令, 此命令自动产生pdf文件书签
  \item 链接支持中文 使用$\backslash$usepackage[CJKbookmarks=true]\{hyperref\}命令
  \item LaTeX 默认链接为方框, 修改方框链接为彩色, 使用命令 $\backslash$usepackage[ colorlinks,linkcolor=blue,anchorcolor=red,citecolor=green]\{hyperref\}
  \item 中文彩色链接 $\backslash$usepackage[colorlinks,linkcolor=blue,anchorcolor=red, citecolor=green,CJKbookmarks=true]\{hyperref\}
\end{enumerate}

\section{分数, 开方}
\begin{enumerate}
  \item 分数: $\frac{numerator}{denominator}$ code: \$$\backslash$frac\{numerator\}\{denominator\}\$
  \item 开方: $\sqrt{expression}$ code: \$$\backslash$sqrt\{expression\}\$
  \item 开 n 次方 $\sqrt[n]{expression}$ code: \$$\backslash$sqrt[n]\{expression\}\$, [n]为开方参数
\end{enumerate}

\section{摘要}
\begin{enumerate}
  \item 在 article 环境中, 使用在$\backslash$begin\{abstract\} 和 $\backslash$end\{abstract\}
  \item 在 book 环境中, 使用$\backslash$chapter*\{Abstract\}
  \item $\backslash$chapter* 表示此chapter不编号.
\end{enumerate}

\section{references}
\begin{enumerate}
  \item 使用 $\backslash$begin\{thebibliography\} 与 $\backslash$end\{thebibliography\}\\
    $\backslash$begin\{thebibliography\}\{100\}\\
    \{$\backslash$small\\
    $\backslash$bibitem\{Kennedy\} James\,\~{}\,Kennedy, Russell\,\~{}\,C.\,\~{}\,Eberhart, Yuhui\,\~{}\,Shi. \{$\backslash$it Swarm Intelligence\}. Morgan Kaufmann Publishers 2001\\
    \}\\
    $\backslash$end\{thebibliography\}
  \item 使用bibtex
\end{enumerate}
\end{CJK}
\end{document}

在LaTeX中插入矩阵和行列式
1. tex file
2. pdf file
% usepackage
\usepackage{amssymb}
\usepackage{amsmath}
\usepackage{amsthm}

% code
The \emph{characteristic polynomial} $\chi(\lambda)$ of the $3 \times 3$ ~matrix
\[ \left(
\begin{array}{ccc}
    a & b & c \\
    d & e & f \\
    g & h & i
\end{array} \right)\]

is given by the formula
\[ \chi(\lambda) = \left|
\begin{array}{ccc}
    \lambda - a & -b          & -c \\
    -d          & \lambda - e & -f \\
    -g          & -h          & \lambda - i
\end{array} \right| \]

$ \Psi(\mathbf{x}_1, \mathbf{x}_2, \ldots, \mathbf{x}_N) =
\frac{1}{\sqrt{N!}} \left|
\begin{matrix}
    \chi_1(\mathbf{x}_1) & \chi_2(\mathbf{x}_1) & \cdots & \chi_N(\mathbf{x}_1) \\
    \chi_1(\mathbf{x}_2) & \chi_2(\mathbf{x}_2) & \cdots & \chi_N(\mathbf{x}_2) \\
    \vdots               & \vdots               &        & \vdots               \\
    \chi_1(\mathbf{x}_N) & \chi_2(\mathbf{x}_N) & \cdots & \chi_N(\mathbf{x}_N)
\end{matrix} \right| $

\begin{displaymath}
    x = \left[
        \begin{matrix} x_{1}   \\
                       x_{2}   \\
                       \vdots  \\
                       x_{n}
        \end{matrix}   \right]
\end{displaymath}
 

$$
\bordermatrix{
              & A_1     & A_2     & \cdots & A_n     \cr
    C_1     & w_1     & w_2     & \ldots & w_1     \cr
    C_2     & w_2     & w_2     & \ldots & w_2     \cr
    \vdots & \vdots & \vdots & \ddots & \vdots \cr
    C_n     & w_n     & w_n     & \ldots  & w_n     \cr
            }
\bordermatrix{
    &        \cr
    & w_1    \cr
    & w_2    \cr
    & \vdots \cr
    & w_n    \cr
} =n \bordermatrix {
    &        \cr
    & w_1    \cr
    & w_2    \cr
    & \vdots \cr
    & w_n    \cr
}
$$
$$
\bordermatrix{
     & A_1    & A_2    & \ldots & A_3    \cr
     & w1/w1  & w1/w1  & \ldots & w1/w1  \cr
     & w2     & w2     & \ldots & w2     \cr
     & \vdots & \vdots & \vdots & \vdots \cr
     & w3     & w3     & \ldots & w3     \cr
}
$$

windows系统中, 编译boost_1_40_0, jam为 boost-jam-3.1.17. C++编译器为 visual studio 2005

1. download the source of Boost and Boost Jam from http://www.boost.org/.

2. release the Boost source files to folder, e.g. d:\shi\boost. release Boost Jam to the subfolder of the Boost sourced:\shi\boost\jam.

3. open Visual Studio e.g. .NET 2005, 工具 -> 选项 -> 项目 ->VC++目录(Tools -> Options -> Projects and Solutions -> VC++ Directories), 在"包含文件目录 (Include files) "里，增加一行，如：D:\shi\boost 这样就可以使用大多数的Boost类库. 使用 test code 1 来验证include files

-----------------test code 1 -------------------------------
#include <vector>
#include <iostream>
#include <boost/lexical_cast.hpp>

using namespace boost ;
using namespace std ;

int main(int argc, char * argv[])
{
  vector<int> v1;
  vector<int>::const_iterator ci_v1 ;
  int iLength = 0 ;

  while( iLength < 10 )
  {
    try
    {
      if ( iLength == 5 )
        v1.push_back(lexical_cast<int>("chengshi")) ;
      else
        v1.push_back(lexical_cast<int>(iLength));
      }
      catch(bad_lexical_cast &ex)
      {
        cout << ex.what()<< endl ;
        v1.push_back(-1);
      }
      iLength++ ;
    }

    cout << "vector --> " ;
    for ( ci_v1 = v1.begin() ; ci_v1 != v1.end() ; ci_v1++ )
    {
      cout << *ci_v1 << " " ;
    }
    cout << endl ;

    system("pause");
    return 0 ;
}
--------------------------test code 1 ---------------------

4. 少数的类库需要额外再生成对应操作系统的动态库, 才可以使用以Windows+VS2005为环境, 以regex类库举例说明. regex为我们提供了正则表达式功能, 其中boost的regex支持perl语法, 更极大的提升了使用正则表达式所产生的效果. 但要想使用regex, 需要生成相关的lib文件才可以. 生成的步骤如下: 开始(Start) -> Microsoft Visual Studio.NET 2005 -> Visual Studio.NET 工具(Tools) -> Visual Studio.NET 2005 命令提示(Command Prompt). 使用这个命令提示符之后, VS就会为我们自动配置好VC环境. 打开命令提示符之后, 我们进入目录 D:\shi\boost\libs\regex\build, 现在我们敲入 nmake /fvc8.mak 生成lib文件. 生成lib文件之后, 单独建一个文件夹, 例如建立的是d:\boost_libs, 然后把所有的*.lib文件拷贝到这个目录. 然后我们打开VS2005，选择菜单工具-->选项-->项目-->VC++目录(Tools -> Options -> Projects and Solutions -> VC++ Directories), 在"库文件(Library files)"里加入目录d:\boost_libs, 这样VS2005在链接时, 就会搜索这个目录

--------------------- test code 2 -------------------------
#include <iostream>
#include <string>
#include <iterator>
#include <boost/regex.hpp>

using namespace boost;
using namespace std;

int main(int argc, const char** argv)
{
    wchar_t * strSample = L"[测试]cheng 2007-05-15 测试 " ;
    wregex rgExpression(L"(\\[(\\S*)\\])((\\S|\\s)*)(\\d{4,}-\\d{2,}-\\d{2,})((\\S|\\s)*)", boost::regex::perl) ;
    wcmatch what ;

    wcout.imbue(locale("chs"));
    try
    {
        if(regex_match(strSample, what, rgExpression))
        {
        wcout << L"match!" << endl ;
            for (unsigned int i = 0 ; i < what.size() - 1 ; i++ )
            {
                wcout << L"what[" << i << L"] --> " << what[i] << endl ;
            }
        }
        else
        wcout << L"not match!" << endl ;
    }
    catch(...)
    {
        return -1;
    }
    system("pause");
    return 0;
}
---------------------test code 2 ---------------------------
如果编译上面的程序, 在链接时没有报错, 就是正确链接了lib库文件.
* gcc 不支持宽字符串
 
5. 使用Boost.Jam来Build所有的库. 首先, 打开VC.NET 2005的命令提示符(Command Prompt), 然后进入D:\shi\boost\jam目录, 运行build.bat. 这时会生成 bjam的可执行程序并且在jam下生成bin.ntx86这个子目录。
6. 配置环境变量PATH, 以便用 bjam来build boost. 配置步骤如下：右键我的电脑 -> 属性 -> 高级 -> 环境变量, 在PATH这个变量后面加入bin.ntx86所在的绝对路径。e.g. ";D:\shi\boost\jam\bin.ntx86". 注意: 每个绝对路径要用分号隔开. 同时要重新打开命令提示符, 因为环境变量只在打开命令提示符的时候读取一次.
7. 进入D:\shi\boost目录, 直接敲bjam, Build就会自动开始, 并生成Boost库.

8.前面工作都是把整个boost的安装过程分解，其实下面的内容如果不做，也可以正常的使用Boost。现在介绍是标准的 Boost 建立和安装过程. 这部分将使用上面所介绍过的一些知识来做一下标准Boost的Build和Install过程. Boost的安装过程其实很简单: 建立一个d:\boost目录，然后解压zip 文件到d:\boost。首先用上文中介绍的方法Build bjam的可执行文件（参与上面的步骤），然后进入d:\boost。 在命令行执行bjam --prefix=d:\boost install 执行后，会在d:\boost生成所需要的所有库和头文件。然后你用上面介绍的配置Visual Studio.NET 2005的方法配置include目录为 D:\boost, lib目录为D:\boost\lib.

bjam的参数含义:
--build-dir=<builddir>      编译的临时文件会放在builddir里(这样比较好管理，编译完就可以把它删除了)
--stagedir=<stagedir>     存放编译后库文件的路径，默认是stage
--build-type=complete     编译所有版本，不然只会编译一小部分版本（确切地说是相当于:variant=release, threading=multi;link=shared|static;runtime-link=shared）
variant=debug|release     决定编译什么版本(Debug or Release?)
link=static|shared     决定使用静态库还是动态库。
threading=single|multi     决定使用单线程还是多线程库。
runtime-link=static|shared     决定是静态还是动态链接C/C++标准库。
--show-libraries     显示需要编译的库名称
命令行的install的意思是指要安装库文件和头文件
--prefix的意思是说安装独立文件的路径. 上面使用的是d:\shi\boost.
--exec-prefix的意思是安装依赖文件的路径. 上面我们没有输入. 默认prefix提供的目录, 在本例中, 是d:\boost
--libdir的意思是指安装库文件的路径. 上面也没有输入. 默认是exec-prefix提供的目录加lib, 本例中exec-prefix使用的是prefix的目录, libdir为d:\boost\lib
另外还有一些比较常用的参数如：
--includedir 这个参数是头文件所在的目录.
--with 指Build或Install单独的库, 如果使用这个参数，可自动完成指定库的Build和Install。例如：bjam --prefix=d:\boost install --with-regex

編譯好的lib，所代表意義:
gd -- Debug
mt -- Multi Thread
sgd-- Runtime-link-static的debug
s -- 在Runtime-link-的時候，是用static的方式
serialization == ansi
wserialization == Unicode

9. Dev-C++, 使用 Tools -> Compiler Options -> Directories -> C++ includes 来include Boost的head files.

在LaTeX文档中, 插入代码, 使用 listings 宏包

用法：

\usepackage{listings}

\lstset{breaklines}  %LaTeX自动将长的代码行换行排版

1. 直接把代码写入TEX文本中

\begin{lstlisting}[language=***]

source

\end{lstlsting}

2. 调用并嵌入源文件

\lstinputlisting{filename.*}

a)  file default extension: tex. 如果仅用 ilename 不加后缀名 .*, CTex会自动寻找 filename.tex文件

b) filename.*,  .* 可以为任意纯文本文件

c)  使用 \usepackage{CJK}后, \begin｛lstlisting｝和 end{lstlsting}间可以使用中文, 但 \lstinputlisting{filename.*}, finaname.* 不能包含中文 (会出现乱码, 或编译错误)

latex file

pdf file

code file

---------------------- latex file ---------------------

\documentclass[12pt]{article}
\usepackage{listings}
\usepackage{CJK}

\lstset{breaklines}
\lstset{extendedchars=false}

\begin{document}
\begin{CJK}{GBK}{song}

\title{algorithm}
\author{shi~Cheng}
\maketitle

\section{algorithm}
\begin{lstlisting}[language=C]
int main(int argc, char ** argv)
{
/* print a string "Hello world! 测试" */
printf("Hello world!\n");
return 0;
}
\end{lstlisting}
测试
\begin{lstlisting}[language=Python]
print("tset")

\end{lstlisting}
\lstinputlisting{hello.cpp}
\end{CJK}

\end{document}

latex文件中, 在表格中插入公式

文件地址:

a) formulaInTable.tex

b) formulaInTable.pdf

 

\documentclass[12pt]{article}
\usepackage{amsmath}
\begin{document}
\title{formula in table}
\author{Shi~Cheng\\
shi.cheng@live.com}
\date{September~10,~2009}
\maketitle

\begin{abstract}
set formula in table
\end{abstract} 
\section{section}
\begin{tabular}{|c|c|} \hline
Formula & Explanation \\ \hline
      $h_\sigma(a,B)=
            \left\{
            \begin{array}{rl}
                1 & \mbox{if }d(a,B) \leq \sigma  \\
                0 & \mbox{if }d(a,B)> \sigma
            \end{array}\right.
            \label{pan}$
          Explain something here.& your explanation\\ \hline
\end{tabular}
\end{document}

說明:

1) 這是一篇 latex 練手之作, 寫成之后發現latex生成的pdf文件無法被復制到 word中, 源代碼也無法復制到word中, 復制

后變成亂碼. ultraEdit可以自動改變編碼, 只能源代碼復制到 ultraEdit, 但將ultraEdit轉碼后的文件保存為tex, 

latex卻也不能編輯. 復雜的編碼問題…

2) .jpg 不能生成 .dvi文件, 使用' latex filename '命令, 會提示' !Latex Error: File 'figureName.bb' not found.'

應使用'pdflatex filename' 將tex文件轉換為pdf文件查看

3) 排版問題

a) 圖片粘貼在latex文件中,緊隨 \includegraphics{fig.jpg}

b) 長句子顯示在網頁中, 會自動截斷文字, 需手動換行

4) 文件地址:

a) tex 文件

b) 編譯完成的 pdf 文件

\documentclass[12pt]{article} 
\usepackage{CJK}
\usepackage{graphicx}
\usepackage{color}

\begin{document}
\begin{CJK}{GBK}{song}
\title{\Large {\CJKfamily{hei} excel~畫折線圖}}
\author{Shi~Cheng}
\date{2009/05/22}
\maketitle

\begin{abstract}
使用~excel~來對一些點進行擬合, 得到這些點構成的折線圖
\end{abstract}

\section{要求和原始數據}
曲線圖的要求:\\
1) 取表格~Table\ref{tab:data}~第二列數據~Number of Items~作為~$X$~軸\\
2) 表格第三到六列數據~method A - D~ 表示四種不同~method~完成排序所花費的~step~數目, 這構成折線圖的~$Y$~軸\\
3) 將四種~Method~隨~Number of Items~增加后, ~step~數目趨勢表示在折線圖上\\
原始數據如下表格~Table\ref{tab:data}~所示:
\begin{center}
\begin{table}[htp]
\centering
    \caption{original~data}
    \begin{tabular}{|c|c|c|c|c|c|}\hline\\
serial & NumOfItem & methodA & methodB & methodC & methodD\\ \hline\\
1 & 100 & 653 & 541 & 9166 & 4900\\ \hline\\
2 & 150 & 1091 & 897 & 18809 & 11089\\ \hline\\
3 & 200 & 1495 & 1276 & 33546 & 19766\\ \hline\\
4 & 250 & 2011 & 1679 & 52369 & 30922\\ \hline\\
5 & 300 & 2647 & 2100 & 75431 & 44479\\ \hline\\
6 & 350 & 3061 & 2524 & 102760 & 60662\\ \hline\\
7 & 400 & 3712 & 2963 & 134624 & 79606\\ \hline\\
8 & 450 & 4246 & 3396 & 158549 & 100627\\ \hline\\
9 & 500 & 4693 & 3857 & 195896 & 124258\\ \hline\\
10 & 550 & 5203 & 4321 & 237301 & 150630\\ \hline\\
11 & 600 & 6121 & 4788 & 282181 & 179124\\ \hline\\
12 & 650 & 6759 & 5265 & 331622 & 210561\\ \hline\\
13 & 700 & 7231 & 5745 & 384261 & 244038\\ \hline\\
14 & 750 & 7698 & 6226 & 441366 & 280243\\ \hline\\
15 & 800 & 8384 & 6722 & 502153 & 318852\\ \hline\\
16 & 850 & 9141 & 7213 & 566964 & 360035\\ \hline\\
17 & 900 & 9734 & 7711 & 635202 & 403345\\ \hline\\
18 & 950 & 10519 & 8212 & 708426 & 450002\\ \hline
    \end{tabular}
    \label{tab:data}
\end{table}
\end{center}
\pagebreak
\section{繪制折線圖步驟}
折線圖繪制步驟:\\
1) 將數據填入~excel~單元格中, 如~Figure\ref{fig:data}~所示:
\begin{figure}[htp]
    \centering
    \includegraphics{graphics/data.jpg}
     
    \caption{copy data into excel}
    \label{fig:data}
\end{figure}
\newpage
2) 首先繪制四種方法的對比圖, 選擇需要生成的四組數據, 鼠標左鍵依次點擊 菜單欄 {\textcolor{blue}{\bf 插入}}

 ~$\rightarrow$~{\textcolor{blue}{\bf 折線圖}}~$\rightarrow$~{\textcolor{blue}{\bf 二維折線圖}}, 如

~Figure\ref{fig:insert}~所示:
\begin{figure}[htp]
    \centering
    \includegraphics{graphics/insert.jpg}
     
    \caption{choose a type of line chart}
    \label{fig:insert}
\end{figure}
\newpage
3) 鼠標左鍵點擊折線圖, ~excel~自動生成折線圖如~Figure\ref{fig:fourM}~所示:
\begin{figure}[htp]
    \centering
    \includegraphics{graphics/fourM.jpg}
     
    \caption{create a line chart for four method}
    \label{fig:fourM}
\end{figure}
\newpage
4) 鼠標左鍵點擊工具欄{\textcolor{blue}{\bf 選擇數據}}, 出現圖例項和水平軸的編輯框, 如~Figure\ref{fig:edit}~所示:
\begin{figure}[htp]
    \centering
    \includegraphics{graphics/edit.jpg}
      
    \caption{edit the line chart}
    \label{fig:edit}
\end{figure}
\newpage
或在折線圖上, 點擊鼠標右鍵, 再點擊{\textcolor{blue}{\bf 選擇數據}}, 進入編輯框, 如~Figure\ref{fig:edit2}~所示:

\begin{figure}[htp]
    \centering
    \includegraphics{graphics/edit2.jpg}
     
    \caption{edit the line chart in other way}
    \label{fig:edit2}
\end{figure}
\newpage
5) 點擊 ~{\textcolor{blue}{\bf 水平(分類)軸標簽}}~ 的 ~{\textcolor{blue}{\bf 編輯}}~, 選擇

~{\textcolor{blue}{\bf 軸標簽區域}}, 點擊~{\textcolor{blue}{\bf 確定}}, 如~Figure\ref{fig:editx}~所示:
\begin{figure}[htp]
    \centering
    \includegraphics{graphics/editx.jpg}
     
    \caption{choose the x coordinate axes}
    \label{fig:editx}
\end{figure}
\newpage
對系列進行~{\textcolor{blue}{\bf 添加}}~, ~{\textcolor{blue}{\bf 編輯}}~, ~{\textcolor{blue}{\bf 刪除}}~

操作. 選擇任意系列, 點擊~{\textcolor{blue}{\bf 編輯}}~, 為各個系列添加系列名, 如~Figure\ref{fig:editi}~所示:
\begin{figure}[htp]
    \centering
    \includegraphics{graphics/editi.jpg}
     
    \caption{change item's name}
    \label{fig:editi}
\end{figure}
\section{折線圖}
最終形成的圖形如~Figure\ref{fig:fourF}~所示:
\begin{figure}[htp]
    \centering
    \includegraphics{graphics/fourF.jpg}
     
    \caption{the final figure}
    \label{fig:fourF}
\end{figure}
\newpage
{\textcolor{red}{\bf method A}}~與~{\textcolor{red}{\bf method B}}幾乎重合, 單獨作圖將這兩個method

區分開, 如~Figure\ref{fig:twoM}~所示:
\begin{figure}[htp]
    \centering
    \includegraphics{graphics/twoM.jpg}
     
    \caption{create a line chart for four method}
    \label{fig:twoM}
\end{figure}
\section{conclusion}
excel可以做出 {\textcolor{blue}{柱形圖 折線圖 餅圖 條形圖 面積圖 散點圖}} 等圖形, 單獨對于折線圖也可以有

不同的~{\textcolor{blue}{圖表布局}}~方式, 折線圖可以分為~{\textcolor{blue}{二維折線圖 三維折線圖}}, 又可

分為~{\textcolor{blue}{堆積折線圖 百分比折線圖}}等.\\
{\textcolor{red}{\bf \it Practice make perfect}}
\end{CJK}
\end{document}

Original Passage

Finally, how can astronauts ‘let off stream’ when interpersonal conflicts develop? Even best friends can irritate each other when forced to spend weeks together in isolation. Space stations are small, cramped, busy workspaces and there is little privacy. Also, space exploration is dangerous, which adds to the stress aboard a spaceship.

Paraphrase

NASA physician Patrick Clinton states that the way <of> astronauts release <releases> their resentment when disagreement happen <happened> is a problem. Close friends may annoy each other when they have to stay together in a tiny space for a long time. Astronauts cannot be alone as the space is tiny and insufficient. The dangers <dangerous> of space exploration also make astronauts nervous. [18].

The original passage is from <A HISTORY OF WESTERN PHILOSOPHY And Its Connection with Political and Social Circumstances from the Earliest Times to the Present Day> by Bertrand Russell.

Original Passage

Philosophy, as I shall understand the word, is something intermediate between theology and science. Like theology, it consists of speculations on matters as to which definite knowledge has, so far, been unascertainable; but like science, it appeals to human reason rather than to authority, whether that of tradition or that of revelation. All definite knowledge--so I should contend--belongs to science; all dogma as to what surpasses definite knowledge belongs to theology. But between theology and science there is a No Man's Land, exposed to attack from both sides; this No Man's Land is philosophy. Almost all the questions of most interest to speculative minds are such as science cannot answer, and the confident answers of theologians no longer seem so convincing as they did in former centuries. Is the world divided into mind and matter, and, if so, what is mind and what is matter? …

Paraphrase

The philosopher Bertrand Russell states that philosophy is something between theology and science in his <[his]> understanding of the word <vocabulary>. Similar to <Like> theology, philosophy composes <hypothesis> hypotheses on the area of universe about which knowledge is <, for example, the definition of knowledge are> still uncertain. However, similar to <like> science, Philosophy is more logical <reasonable> than obedient to some higher power/being, either that of a king or a god <from in all ages>. All the certain <definition of> knowledge is part of science and the beliefs beyond the certain <definition of> knowledge is part of theology in his <[his]> opinions. However, the empty area between theology and science is criticized from both sides and this area, he maintains is philosophy. For most philosophical questions, <the> science cannot give certain answers to thinking and analytical persons <persons who like think and analysis>, and <the> theology cannot make people deeply believe <believes them> like in centuries gone by / previously centuries <former centuries>. Can the world be separated <separate> as mind and matter? If the answer is yes, how to define <definition> mind and matter? ...[10]

<The> Artificial Intelligence

<The> Intelligence <has> created great temptation for <to> the researcher who wants to know the secret of the universal. Researchers hoped to build artificial intelligence on the computer to simulate <the> real intelligence. However, Different researchers have different definitions of artificial Intelligence (AI). From ‘Artificial Intelligence system is the study of how to make computers do things at which, at the moment, people are better’ by Rich [1] to ‘An intelligence system is one whose expected utility is the highest that can be achieved by any system with the same computational limitations’ by Russell [2], numerous researchers have contributed to the field of artificial intelligence. This brief history of this field will be reviewed in this essay.

智能對于想探索宇宙奧秘的研究者擁有巨大的誘惑力. 研究者希望在計算機算建立人工智能以模仿真實的智能. 但是, 不同的研究者對於人工智能有不同的定義, Rich在1983年定義為: 人工智能是研究如何讓計算機做在現階段人做的更好的事情[1]. Russell定義為智能系統是相同的計算局限下, 系統可以獲得最大的功效[2]. 無數研究者對人工智能做出了貢獻, 本文將簡單描述人工智能研究的歷史.

With the idea ‘The world can be represented as a physical symbol system’, the traditional AI researchers used the symbol system to simulate the relationship in the world. For instance, If A is B’s parent, then B is A’s child. This can be represented as (equal (parent A B) (Child B A)) in lisp.

整個世界可以表示為一個物理符號系統，帶著這樣的想法，早期的研究者使用符號系統來表示世界上存在的關係，例如，如果A是B的parent, B就是A的child，這個在lisp中就可以表示為(equal (parent A B) (child B A))。

The traditional AI researchers wanted to have ‘an explanation of can, cause, and knows in terms of a representation of the world by a system of interacting automata’ [6]. The researchers hoped the programs would have common sense, which would means the computer becoming <became> a ‘Logic Theory Machine’ [5]. The AI researchers need to know the structure of human’s knowledge first: what is knowledge? How to represent knowledge? The problems need to be solved by Philosophy. However, like Wittgenstein has written, Logic cannot deduce any new information; knowledge is too complicated to represent. This approach <has> lost favor over <last> the three decades after it begin.

傳統AI研究者希望擁有”通過自動影響機器來用 ‘能夠’, ‘原因’, 和 ‘知道’的解釋來表示真實世界”[6]. 研究者希望程序能夠擁有’常識’, 也就是說, 計算機成為’邏輯理論機器’[5]. AI研究者首先需要知道人類知識的結構: 什么是知識? 怎樣表示知識? 這些問題需要哲學來解決. 但是，如同維特根斯坦所言：邏輯不能演繹出新的知識。知識本身過於複雜，難以被符號表示。在持續了三十年後，這種研究方法逐漸淡化。

Modern AI research was termed machine learning, which was based on <the> probability and statistical learning. Machine Learning is concerned with the design and development of algorithms that allow computers to improve their performance over time based on data, such as from sensor data or databases. Machine Learning divided into supervised Learning and unsupervised Learning <depend>depending on whether it has the measurement of the outcome or not. Machine Learning <Choosing> chooses the features of data, then <classifying> classifies or regressing the data to one or two dimensional space. Through the analysis of training data, a model can be found to predict behaviors of new objects and describe group tendency. The problem was first represented in high dimensional space, and then dimensions <was reduces> were reduce after mathematical transformation. However, these advantages are not without drawback. It is difficult to find the proper mathematical transformation function.

現代人工智能研究被稱為機器學習，其基礎是概率和統計學習. 機器學習在于設計和發展算法譲計算機通過在長時間處理來自傳感器或者數據庫的數據,以增強性能. 根據輸出有無衡量目標, 機器學習可以分為有監督學習和無監督學習. 機器學習選擇數據的特征, 將數據分類或回歸到一維或二維空間. 通過對訓練集的分析，可以建立一個模型來分析新的對象的行為或整個群體的趨勢。問題先被表述在高維空間，在經過數學變換後，再降低維度。但是，優點往往也是缺點，這種方法的困難之處是難以找到適合的數學變換方程。

The researchers also are learning from the real world and society. This approach of AI research is termed computational intelligence. The neural network (NN) learning from the human brain, the genetic algorithm (GA) simulating human evolution, the swarm intelligence learning (SI) from ants or birds; to sum up, computational research learning from natural life. For example, The Particle swarm Optimization (PSO) is <one> a type of the swarm intelligence. It was <firstly> first introduced by Eberhart and Kennedy in 1995 [3, 4]. The PSO was first designed to simulate birds seeking food which is defined as a “Cornfield vector”. The bird would <found> find food through social cooperation with other birds around it (within its neighborhood). In other words, when a flock of birds go to seek some food, the single bird<, when a flock of birds going to seek some food,> <did> does not know the entire group’s position. The bird knows only a few of bird’s <position> positions which around it. This bird’s position changed quickly, and it was determined by its neighborhood’s position. Every bird goes <going> to find their <his> local best position, then the entire group finds the global best. However, this approach also has <have> its drawback, insufficient mathematical analysis is the deficiency of this approach.

智能研究者也模仿真實世界和人類社會，這種研究思路稱為計算智能。神經網絡學習人腦細胞運作，遺傳算法模擬人類進化，群體智能從螞蟻或鳥群中學習；總而言之，計算智能從自然生物中學習。例如, 粒子群優化算法就是一種群智能.這種方法在1995年首次由Eberhart 和Kennedy介紹[3, 4].粒子群優化最早被設計用來模擬鳥群尋找食物的行為, 這被稱為’麥田向量’. 鳥通過與它周圍的鳥群的社會合作來尋找食物. 換而言之, 單一的小鳥, 在一群鳥都尋找食物時,并不知道整個群體的位置.這只鳥只知道它周圍鳥群的位置, 這只鳥迅速變換它的位置,這些鳥都去尋找它們的單個最優位置,整個群體得到他們的群體最優位置.但是這種方式也有缺陷, 缺乏數學分析是這種方法的不足之處。

Different problems need different methods, like the ‘no free lunch theory’ suggests. Further research is needed in the AI field to determine good solutions for problems and represent the physical world.

如‘no free lunch theory’所證明的，不同的問題需要不同的解決辦法。在人工智能領域，取得問題的最優解，使用智能來表示物理世界，還需要進一步的研究。

References

[1] Rich, E. (1983). Artificial Intelligence. New York: McGraw-Hill

[2] Fogel, David B. Evolutionary Computation. IEEE Press

[3] Eberhart, R. C., Kennedy, J. (1995). A New Optimizer Using Particle Swarm Theory. Proc. Sixth International Symposium on Micro Machine and Human Science (Nagoya, Japan), IEEE Service Center, Piscataway, NJ, 39-43

[4] Eberhart, R. C., Kennedy, J. (1995). Particle Swarm Optimization. Proc. IEEE International Conference on Neural Networks (Perth, Australia), IEEE Service Center, Piscataway, NJ, pp. IV: 1942 - 1948

[5] John McCarthy. Programs with Common Sense.

[6] John McCarthy, Patrick J. Hayes. Some Philosophical Problems from the standpoint of Artificial Intelligence.

Different researchers have different definitions of artificial Intelligence (AI). From ‘Artificial Intelligence system is the study of how to make computers do <thing> things at which, at the moment, people are better’ by Rich (1983, p.1) to ‘An intelligence system is one whose expected utility is the highest that can be achieved by any system with the same computational limitations’ by Russell (quoted in Ubiquity, 2004), numerous researchers have contributed to <in> the field of artificial intelligence. This brief <briefly> history of this field will be reviewed in this essay.

不同的研究者對於人工智能有不同的定義，Rich在1983年定義為：人工智能是研究如何讓計算機做在現階段人做的更好的事情。Russell定義為智能系統是相同的計算局限下，系統可以獲得最大的功效。無數研究者對人工智能做出了貢獻，本文將簡單描述人工智能研究的歷史。

With the <ideas> idea ‘The world can be represented as a physical symbol system’, the AI researchers used <using> the symbol system to simulate <simulation> the relationship in the world. For instance, If A is B’s parent, then B is <A is> A’s child. This can be represented <represents> as (equal (parent A B) (Child B A)) in lisp. However, <But> like Wittgenstein has written <writing>, Logic cannot deduce any new information <‘Logic and deduction cannot bring any new information’>; <the> knowledge is too complicated to represent. This approach <method> has lost favour over last <was decayed after consistent> three decades <decade>.

整個世界可以表示為一個物理符號系統，帶著這樣的想法，早期的研究者使用符號系統來表示世界上存在的關係，例如，如果A是B的parent, B就是A的child，這個在lisp中就可以表示為(equal (parent A B) (child B A))。但是，如同維特根斯坦所言：邏輯不能演繹出新的知識。知識本身過於複雜，難以被符號表示。在持續了三十年後，這種研究方法逐漸淡化。

Modern <The modern> AI research was termed <named as> machine learning, which was based on the probability and statistical learning. Through the analysis of <the> training data, <the> A model can be found to predict behaviors of new objects <object> and describe group tendency. The problem was first <firstly> represented in high dimensional space, and then dimensions was reduces <reduces some dimension> after mathematical transformation <mathematic transform>. However, these advantages are not without drawback <But the advantage is the deficiency in some way>. It is difficult to find the proper mathematical <mathematic> transformation <transform> function.

現代人工智能研究被稱為機器學習，基礎是概率和統計學習，通過對訓練集的分析，可以建立一個模型來分析新的對象的行為或整個群體的趨勢。問題先被表述在高維空間，在經過數學變換後，再降低維度。但是，優點往往也是缺點，這種方法的困難之處是難以找到適合的數學變換方程。

The researchers also are learning from <form> the real world and society <social>. This approach of AI research is termed <named as> computational intelligence. The neuron network learning from the human <human’s> brain, the genetic algorithm simulating <simulate the> human evolution, the swarm learning from ants or birds; to sum up <, in a word>, <the> computational research learning from natural life <nature>. Insufficient <The insufficient> mathematical <mathematic> analysis is the deficiency of this approach.

智能研究者也模仿真實世界和人類社會，這種研究思路稱為計算智能。神經網絡學習人腦細胞運作，遺傳算法模擬人類進化，群體智能從螞蟻或鳥群中學習；總而言之，計算智能從自然生物中學習。缺乏數學分析是這種方法的不足之處。

Different problems need <problem needs> different methods, like the ‘no free lunch theory’ suggests <suggestion>. Further research is needed in <on> the AI field <fields> to determine <the> good solutions <solution> for <of> problems and represent the physical world.

如‘no free lunch theory’所證明的，不同的問題需要不同的解決辦法。在人工智能領域，取得問題的最優解，使用智能來表示物理世界，還需要進一步的研究。

References

Rich, E. (1983). Artificial Intelligence. New York: McGraw-Hill

Fogel, David B. Evolutionary Computation. IEEE Press