当我使用 WindEdt 10.3 编译以下代码时，我得到了以下结果。为了清晰起见，我将代码分为三部分（代码 A、代码 B 和代码 C）。我希望中文写成英文：第一章简介 . ...
\documentclass{UJS-PhD-thesis}
%\usepackage[english]{babel}
\title{ONLINE ANOMALY DETECTION}
\usepackage{subfiles}
\usepackage{ulem}
\newtheorem{theorem}{\indent 定理}[chapter]
\newtheorem{proof}{\indent 证明}[chapter]
\usepackage{mhchem}
\author{Kuku Didier} % 论文作者
\major{Computer Science} % 学院
\advisor[Prof.]{Chi Chi} % [职称]指导老师
\ReplyDate{2023年 月} % 答辩日期
\SubmitDate{2023年 月} % 论文提交日期
\GrantDate{} % 学位授予日期
\chairman{} % 答辩委员会主席
\referee{} % 评阅人
\date{\today}
\info{TP393.0}{公开}{004.7}{55643191303}
% \info{<分类号>}{<密级>}{<UDC>}{<编号>}
% 密级： 内部 秘密 机密 公开 等
% -------------
% 以下为英文标题、作者、[职称]导师、日期的相关信息
\entitle{ONLINE ANOMALY DETECTION}
\enauthor{Kuku Didier}
\enmajor{Computer Science}
\enadvisor[Prof.]{Chi Chi}
\enDate{September, 2023}
\begin{document}
\makecninnertitle
%\myemptypage % 添加空白页方便双面打印
\makeauthorization{figures/authorization}
%\myemptypage
\frontmatter
% -----------------------------------------------------------
% 摘要书写区
% -----------------------------------------------------------
\subfile{chapters/abstract}
\tableofcontents % 目录生成
\listoffigures % 图目录生成
\listoftables % 表目录生成
\mainmatter
% -----------------------------------------------------------
% 正文书写区
% -----------------------------------------------------------
\subfile{chapters/c1}
\subfile{chapters/chapter2}
\subfile{chapters/chapter3}
\subfile{chapters/chapter4}
\subfile{chapters/chapter5}
\subfile{chapters/chapter6}
\subfile{chapters/chapter7}
%\subfile{chapters/chapter8}
\bibliographystyle{gbt7714-unsrt}
\addcontentsline{toc}{chapter}{参考文献}
\bibliography{ujs-PhD-thesis}
\subfile{chapters/acknowledgement}
\subfile{chapters/biographic}
\end{document}
代码 B
\NeedsTeXFormat{LaTeX2e}[1995/12/01]
\ProvidesClass{UJS-PhD-thesis}[02/02/2021 UJS-PhD-thesis thesis class]
\PassOptionsToClass{23pt}{ctexbook} \ProcessOptions
\LoadClass[openany,twoside,a4paper,12pt]{ctexbook}
\RequirePackage{xeCJK}
\RequirePackage{zhnumber}
\RequirePackage{graphicx}
\RequirePackage{subfigure}
\RequirePackage[labelsep=quad]{caption}
\RequirePackage[list=off]{bicaption}
\RequirePackage{mwe}
\RequirePackage{amsmath}
\RequirePackage{multirow}
\RequirePackage{enumitem}
\RequirePackage{newtxtext}
\RequirePackage{latexsym}
\RequirePackage{fancyhdr}
\RequirePackage{zhlipsum}
\RequirePackage{lipsum}
\RequirePackage{ifthen}
\RequirePackage[sort&compress,numbers]{natbib}
\RequirePackage[explicit,clearempty,newparttoc]{titlesec}
\RequirePackage{titletoc}
\RequirePackage{algorithm}
\RequirePackage{algorithmic}
\RequirePackage{enumitem,amssymb}
\RequirePackage{indentfirst}
\RequirePackage{threeparttable}
\RequirePackage{soul,color,xcolor}
\RequirePackage[justification=centering]{caption}
\RequirePackage{array,booktabs}
\RequirePackage{afterpage}
\RequirePackage{tikz}
\RequirePackage{adjustbox}
% 表中所需强调的数据加深显示
\definecolor{hl}{rgb}{0.75,0.75,0.75}
\sethlcolor{hl}
\newcommand{\blankline}[2][7.5em]{\uline{\makebox[#1]{#2}}}
% 设置页边距，参数asymmetric表示页边距不会随奇偶页进行翻转，若需要翻转则删去
\RequirePackage[top=25mm,left=25mm,right=25mm,bottom=25mm, asymmetric]{geometry}
\setlength{\bibsep}{0pt plus 0.3ex}
% 各种图标的定义
\RequirePackage{pifont}
\newcommand{\cmark}{\ding{51}}%
\newcommand{\xmark}{\ding{55}}%
\newcommand{\done}{\rlap{$\square$}{\raisebox{2pt}{\large\hspace{1pt}\cmark}}\hspace{-1pt}}
\newcommand{\wontfix}{\rlap{$\square$}{\large\hspace{1pt}\xmark}}
% 章的目录样式定义
\titlecontents{chapter}[0pt]{\vspace*{.4em}\normalfont}
{\thecontentslabel \hskip.5em}{}
{\bfseries\zihao{-4}\dotfill\contentspage}
% 节的目录样式定义
\titlecontents{section}[15pt]{\zihao{-4}\hspace{\ccwd}}
{\thecontentslabel \hskip.5em}{}{\dotfill\contentspage}
% 节的目录样式定义
\titlecontents{subsection}[35pt]{\zihao{-4}\hspace{\ccwd}}
{\thecontentslabel \hskip.5em}{}{\dotfill\contentspage}
% 章的样式定义
\titlespacing*{\chapter}{0pt}{-1.5em}{1.5em}
\titleformat{\chapter}{\centering\bfseries\zihao{3}}
{Chapter~{\thechapter}~ #1}
{.8em}{}
% 节的样式定义
\titlespacing*{\section}{0pt}{.5em plus 1ex minus .2ex}{.5em plus .2ex}
\titleformat{\section}{\raggedright\bfseries\zihao{4}}
{\thesection}
{.8em}{#1}
% 节的样式定义
\titlespacing*{\subsection}{0pt}{.5em plus 1ex minus .2ex}{.5em plus .2ex}
\titleformat{\subsection}{\raggedright\bfseries\zihao{-4}}
{\hspace{1em}\thesubsection}
{.8em}{#1}
% 页面与页码的样式定义
\fancypagestyle{main}{
\fancyhf{}
\fancyfoot[CO,CE]{\thepage}
\fancyhead[CO]{\normalfont Doctoral thesis of Jiangsu University}
\fancyhead[CE]{\normalfont\@title}
}
\fancypagestyle{plain}{
\fancyhf{}
\fancyfoot[CO,CE]{\thepage}
\fancyhead[CO]{\normalfont Doctoral thesis of Jiangsu University}
\fancyhead[CE]{\normalfont \@title}
}
% 目录、图目录与表目录的样式定义
\renewcommand{\contentsname}{Table of Contents}
\renewcommand{\listfigurename}{List of Figures}
\renewcommand{\listtablename}{List of Tables}
% 目录、图目录与表目录的样式定义
% 定义的样式定义
\newtheorem{definition}{\hspace{2em}定义}[chapter]{\normalfont}
\numberwithin{algorithm}{chapter}
\floatname{algorithm}{算法}
%\renewcommand{\algorithmicrequire}{ \textbf{Input:}}
%\renewcommand{\algorithmicensure}{ \textbf{Output:}}
\renewcommand{\algorithmicrequire}{ \textbf{输入:}}
\renewcommand{\algorithmicensure}{ \textbf{输出:}}
%原来的
% 算法的样式定义
%\numberwithin{algorithm}{chapter}
%\renewcommand{\algorithmicrequire}{ \textbf{Input:}}
%\renewcommand{\algorithmicensure}{ \textbf{Output:}}
%\renewcommand{\algorithmicrequire}{ \textbf{输入:}}
%\renewcommand{\algorithmicensure}{ \textbf{输出:}}
%图表的样式定义
\captionsetup[figure][bi-second]{name=Figure} %设置图的英文编号前缀
\captionsetup[table][bi-second]{name=Table} %设置表的英文编号前缀
\renewcommand{\captionfont}{\normalfont\small}%设置图表中文标题的字体样式
\titlecontents{figure}[0.5cm]{\normalfont}
{\figurename~\thecontentslabel\quad}{\hspace*{-1.5cm}}
{\titlerule*[.5em]{.}\contentspage}[\addvspace{6pt}]
\titlecontents{table}[0.5cm]{\normalfont}
{\tablename~\thecontentslabel\quad}
{\hspace*{-1.5cm}}{\titlerule*[.5em]{.}\contentspage}[\addvspace{6pt}]
%段落间距，和word有所不同
\linespread{1.65}\selectfont
\def\@en@title{}
\def\@en@author{}
\def\@en@advisor{}
\def\@en@jobtitle{}
\def\@en@major{}
\def\@en@date{}
\newcommand{\enadvisor}[2][]{\def\@en@jobtitle{#1}\def\@en@advisor{#2}}
\newcommand{\entitle}[1]{\def\@en@title{#1}}
\newcommand{\enauthor}[1]{\def\@en@author{#1}}
\newcommand{\enmajor}[1]{\def\@en@major{#1}}
\newcommand{\enDate}[1]{\def\@en@date{#1}}
\def\@major{}
\def\@title{}
\def\@advisor{}
\def\@chairman{}
\def\@referee{}
\def\@SubmitDate{}
\def\@ReplyDate{}
\def\@GrantDate{}
\def\@jobtitle{}
\renewcommand{\title}[2][1]{\def\@titlerownum{#1}\def\@title{#2}}
\newcommand{\major}[1]{\def\@major{#1}}
\newcommand{\advisor}[2][]{\def\@jobtitle{#1}\def\@advisor{#2}}
\newcommand{\chairman}[1]{\def\@chairman{#1}}
\newcommand{\referee}[1]{\def\@referee{#1}}
\newcommand{\ReplyDate}[1]{\def\@ReplyDate{#1}}
\newcommand{\SubmitDate}[1]{\def\@SubmitDate{#1}}
\newcommand{\GrantDate}[1]{\def\@GrantDate{#1}}
\def\@CID{}
\def\@SCF{}
\def\@UDC{}
\def\@no{}
\def\@info{}
\newcommand{\info}[4]{
\def\@CID{#1}
\def\@SCF{#2}
\def\@UDC{#3}
\def\@no{#4}
}
%% 封面页
\AtBeginDocument{
\thispagestyle{empty}
\newcommand{\makecninnertitle}{
\setlength{\parindent}{0pt}
\parbox{4\ccwd}{\textbf{分~类~号：}} \blankline{\@CID} \hfill \parbox{3\ccwd}{\textbf{密~级：}} \blankline{\sffamily \@SCF} \par
\parbox{4\ccwd}{\textbf{U~~D~~C~：}} \blankline{\@UDC} \hfill \parbox{3\ccwd}{\textbf{编~号：}} \blankline{\@no} \par
\vspace*{1.2cm}
\begin{center}
\includegraphics[width=.12\linewidth]{logo/ujslogo.pdf} \hspace*{0.8cm}
\includegraphics[width=.45\linewidth]{logo/ujs.pdf} \par
\vspace*{1cm}
\zihao{1}
\textbf{博~~士~~学~~位~~论~~文} \par
\vspace*{1cm}
\parbox{.86\linewidth}{\centering\bfseries\zihao{3} \@title} \par
{
\linespread{1.2} \normalfont
\textbf{\zihao{3}\@en@title} \par
}
\vspace*{1.2cm}
\end{center} \par
\zihao{-3}
\makebox[6\ccwd][s]{指导老师} \uline{\hfill\@advisor\ \ \ \ \@jobtitle\hfill} \par
\makebox[6\ccwd][s]{作者姓名} \uline{\hfill\@author \hfill} \par
申请学位级别 \blankline[.28\linewidth]{工学博士} 专业名称 \uline{\hfill\@major\hfill} \par
论文提交日期 \blankline[.28\linewidth]{\@SubmitDate} 论文答辩日期 \uline{\hfill \@ReplyDate \hfill} \par
学位授予单位和日期 \uline{\hfill 江苏大学\@GrantDate \hfill} \par
\vspace*{1.5cm}
\hfill\textbf{答辩委员会主席} \blankline{\@chairman} \par
\hfill\textbf{评阅人} \blankline{\@referee} \par
\clearpage
}}
%% 空页，方便双面打印
\newcommand\myemptypage{
\null
\pagestyle{empty}
\addtocounter{page}{-1}
\newpage
}
%% 独创性声明与授权书扫描
\newcommand\makeauthorization[2][]{
\pagestyle{empty}
\begin{tikzpicture}[remember picture, overlay, inner sep=0pt]
\node at (current page.center)
{\includegraphics[width=\paperwidth, height=\paperheight, keepaspectratio=false,#1]{#2}};
\end{tikzpicture}
\clearpage }
\renewcommand\frontmatter{%
\cleardoublepage
\@mainmatterfalse
\pagenumbering{Roman}
\normalfont\normalsize
\setlength{\parindent}{2\ccwd}
\pagestyle{main}}
\newcommand{\cnkeywords}[1]{
\bigskip
\noindent
\textbf{关键词}：#1}
\newcommand{\enkeywords}[1]{
\bigskip
\noindent
\textbf{Keywords}: #1}
% Link
\RequirePackage{hyperref}
\hypersetup{
colorlinks=false,
pdfborder={0 0 0},
}
\graphicspath{{figures/}} % 设置图片引用路径
\allowdisplaybreaks % 公式可断页显示
\newcommand{\upcite}[1]{\textsuperscript{\textsuperscript{\cite{#1}}}}%参考文献引用
\endinput
代码C
\contentsline {chapter}{\numberline {第一章\hspace {.3em}}Introduction}{1}{chapter.1}%
\contentsline {section}{\numberline {1.1}Research Question}{2}{section.1.1}%
\contentsline {section}{\numberline {1.2}Main Dissertation Contributions Summary}{4}{section.1.2}%
\contentsline {subsection}{\numberline {1.2.1}Detection of compromised online social network account with enhanced Knn}{4}{subsection.1.2.1}%
\contentsline {subsection}{\numberline {1.2.2}Network anomaly detection in a controlled environment with enhanced PSOGSARF}{5}{subsection.1.2.2}%
\contentsline {subsection}{\numberline {1.2.3}A deep learning approach to online social network account compromisation}{5}{subsection.1.2.3}%
\contentsline {subsection}{\numberline {1.2.4}Intrusion Detection in Online Social Networks: Leveraging Deep Reinforcement Learning and Salp Swarm Algorithm}{5}{subsection.1.2.4}%
\contentsline {section}{\numberline {1.3}Organization of the Dissertation}{6}{section.1.3}%
\contentsline {chapter}{\numberline {第二章\hspace {.3em}}Background}{10}{chapter.2}%
\contentsline {section}{\numberline {2.1}Overview of OSN Intrusion Detection Systems}{10}{section.2.1}%
\contentsline {section}{\numberline {2.2}Threats under OSN}{11}{section.2.2}%
\contentsline {subsection}{\numberline {2.2.1}Classic Threats}{12}{subsection.2.2.1}%
\contentsline {subsubsection}{Malware}{13}{subsubsection*.8}%
\contentsline {subsubsection}{Phishing Attacks}{15}{subsubsection*.9}%
\contentsline {subsubsection}{Spammers}{15}{subsubsection*.10}%
\contentsline {subsubsection}{Cross-Site Scripting (XSS)}{17}{subsubsection*.11}%
\contentsline {subsubsection}{Internet Fraud}{18}{subsubsection*.12}%
\contentsline {subsection}{\numberline {2.2.2}Modern Threats}{18}{subsection.2.2.2}%
\contentsline {subsubsection}{Clickjacking}{19}{subsubsection*.13}%
\contentsline {subsubsection}{De-Anonymization Attacks}{20}{subsubsection*.14}%
\contentsline {subsubsection}{Face Recognition}{20}{subsubsection*.15}%
\contentsline {subsubsection}{Fake Profiles}{21}{subsubsection*.16}%
\contentsline {subsubsection}{Identity Clone Attacks}{22}{subsubsection*.17}%
\contentsline {subsubsection}{Attacks Based on Inference}{22}{subsubsection*.18}%
\contentsline {subsubsection}{Information Leakage}{23}{subsubsection*.19}%
\contentsline {subsubsection}{Sybil Attack}{23}{subsubsection*.20}%
\contentsline {subsubsection}{Online Predators}{24}{subsubsection*.21}%
\contentsline {subsubsection}{Cyberbullying}{24}{subsubsection*.22}%
\contentsline {section}{\numberline {2.3}Methods of detecting intrusion on OSN}{24}{section.2.3}%
\contentsline {subsection}{\numberline {2.3.1}Categories of the Algorithms Used on OSN IDS}{25}{subsection.2.3.1}%
\contentsline {subsection}{\numberline {2.3.2}Machine Learning}{25}{subsection.2.3.2}%
\contentsline {subsubsection}{Supervised Learning}{26}{subsubsection*.23}%
\contentsline {subsubsection}{Unsupervised Learning}{26}{subsubsection*.24}%
\contentsline {subsubsection}{Deep Learning Algorithms}{27}{subsubsection*.25}%
\contentsline {subsection}{\numberline {2.3.3}Mathematical Tools}{27}{subsection.2.3.3}%
\contentsline {subsubsection}{Particle Swarm Optimization}{27}{subsubsection*.26}%
\contentsline {subsubsection}{Gravitational Search Algorithm}{29}{subsubsection*.27}%
\contentsline {subsubsection}{Non-Symmetric Auto-encoder (NDAE)}{31}{subsubsection*.28}%
\contentsline {subsubsection}{Convolutional Neural Network}{31}{subsubsection*.29}%
\contentsline {subsection}{\numberline {2.3.4}The Limitations of the known Methods for OSN Intrusion Detection}{32}{subsection.2.3.4}%
\contentsline {section}{\numberline {2.4}Chapter Summary}{33}{section.2.4}%
\contentsline {chapter}{\numberline {第三章\hspace {.3em}}Detection of compromised OSN account with an enhanced WE-KNN}{34}{chapter.3}%
\contentsline {section}{\numberline {3.1}Preliminaries}{34}{section.3.1}%
\contentsline {subsection}{\numberline {3.1.1}Machine Learning Approaches}{35}{subsection.3.1.1}%
\contentsline {subsection}{\numberline {3.1.2}Discrete-Time Stochastic Control And Probabilistic Graphical Model Approach}{40}{subsection.3.1.2}%
\contentsline {section}{\numberline {3.2}Word Embedding \& Tuning}{41}{section.3.2}%
\contentsline {subsection}{\numberline {3.2.1}Word Embedding}{42}{subsection.3.2.1}%
\contentsline {subsection}{\numberline {3.2.2}Tuning}{43}{subsection.3.2.2}%
\contentsline {section}{\numberline {3.3}Datasets}{43}{section.3.3}%
\contentsline {subsection}{\numberline {3.3.1}KDD CUP '99}{43}{subsection.3.3.1}%
\contentsline {subsection}{\numberline {3.3.2}NSL-KDD}{44}{subsection.3.3.2}%
\contentsline {section}{\numberline {3.4}The Proposed Methodology}{44}{section.3.4}%
\contentsline {section}{\numberline {3.5}Experimental Results}{49}{section.3.5}%
\contentsline {subsection}{\numberline {3.5.1}Comparison on the Mainstream Social Media Datasets}{54}{subsection.3.5.1}%
\contentsline {subsection}{\numberline {3.5.2}Comparison with Related Works}{56}{subsection.3.5.2}%
\contentsline {section}{\numberline {3.6}Chapter Summary}{57}{section.3.6}%
\contentsline {chapter}{\numberline {第四章\hspace {.3em}}Detection of compromised OSN account with an enhanced PSOGSARFC}{59}{chapter.4}%
\contentsline {section}{\numberline {4.1}Preliminaries}{59}{section.4.1}%
\contentsline {subsection}{\numberline {4.1.1}Adaptive Partcile Swarm Optimization}{60}{subsection.4.1.1}%
\contentsline {subsection}{\numberline {4.1.2}Gravitational Search Algorithm}{61}{subsection.4.1.2}%
\contentsline {subsection}{\numberline {4.1.3}Random Forest Classifier}{64}{subsection.4.1.3}%
\contentsline {section}{\numberline {4.2}The Proposed Approach}{65}{section.4.2}%
\contentsline {section}{\numberline {4.3}Results and Experiment Discussion}{70}{section.4.3}%
\contentsline {subsection}{\numberline {4.3.1}Dataset Description}{70}{subsection.4.3.1}%
\contentsline {subsection}{\numberline {4.3.2}Evaluation Metrics}{71}{subsection.4.3.2}%
\contentsline {subsection}{\numberline {4.3.3}Features Selection and Classification Accuracy}{72}{subsection.4.3.3}%
\contentsline {section}{\numberline {4.4}Results and Experiment Discussion}{72}{section.4.4}%
\contentsline {subsection}{\numberline {4.4.1}Dataset Description}{72}{subsection.4.4.1}%
\contentsline {subsection}{\numberline {4.4.2}Evaluation Metrics}{73}{subsection.4.4.2}%
\contentsline {subsection}{\numberline {4.4.3}Features Selection and Classification Accuracy}{74}{subsection.4.4.3}%
\contentsline {subsection}{\numberline {4.4.4}Comparison on the Mainstream Social Media Datasets}{80}{subsection.4.4.4}%
\contentsline {subsection}{\numberline {4.4.5}Comparison with Related Works}{82}{subsection.4.4.5}%
\contentsline {section}{\numberline {4.5}Chapter Summary}{83}{section.4.5}%
\contentsline {chapter}{\numberline {第五章\hspace {.3em}}A Deep Learning Approach to OSN Account Compromisation}{85}{chapter.5}%
\contentsline {section}{\numberline {5.1}Preliminaries}{85}{section.5.1}%
\contentsline {section}{\numberline {5.2}Proposed Method}{86}{section.5.2}%
\contentsline {subsection}{\numberline {5.2.1} NDAE Optimization}{86}{subsection.5.2.1}%
\contentsline {subsection}{\numberline {5.2.2}Features Selection \& Classification}{89}{subsection.5.2.2}%
\contentsline {section}{\numberline {5.3}Experiments and Discussions}{90}{section.5.3}%
\contentsline {subsection}{\numberline {5.3.1}Data Preprocessing}{91}{subsection.5.3.1}%
\contentsline {subsection}{\numberline {5.3.2}Comparison on the Mainstream Social Media Datasets}{91}{subsection.5.3.2}%
\contentsline {subsection}{\numberline {5.3.3}Performance Comparison with NSL-KDD AND KDD CUP`99}{92}{subsection.5.3.3}%
\contentsline {subsection}{\numberline {5.3.4}Comparisons Between 13 AND 5-Class Performance Over NSL-KDD}{95}{subsection.5.3.4}%
\contentsline {subsection}{\numberline {5.3.5}Comparison Between 13 AND 5-Class Performance Over KDD CUP'99}{97}{subsection.5.3.5}%
\contentsline {subsection}{\numberline {5.3.6}Comparison With the Related Works}{98}{subsection.5.3.6}%
\contentsline {section}{\numberline {5.4}Chapter Summary}{102}{section.5.4}%
\contentsline {chapter}{\numberline {第六章\hspace {.3em}}Intrusion Detection in Online Social Networks: Leveraging Deep Reinforcement Learning and Salp Swarm Algorithm}{104}{chapter.6}%
\contentsline {section}{\numberline {6.1}Preliminaries}{104}{section.6.1}%
\contentsline {section}{\numberline {6.2}Proposed Methodology}{106}{section.6.2}%
\contentsline {subsection}{\numberline {6.2.1}Memory Module}{107}{subsection.6.2.1}%
\contentsline {subsection}{\numberline {6.2.2}Data Pre-processing}{108}{subsection.6.2.2}%
\contentsline {subsection}{\numberline {6.2.3}Feature selection}{110}{subsection.6.2.3}%
\contentsline {subsection}{\numberline {6.2.4}Classification}{113}{subsection.6.2.4}%
\contentsline {section}{\numberline {6.3}Experiments and Discussions}{116}{section.6.3}%
\contentsline {subsection}{\numberline {6.3.1}Experimental Setup}{117}{subsection.6.3.1}%
\contentsline {subsection}{\numberline {6.3.2}Performance Comparison Metrics of the proposed model on 60\% training data }{120}{subsection.6.3.2}%
\contentsline {subsection}{\numberline {6.3.3}Performance Comparison Metrics of the proposed model on 75\% training data}{122}{subsection.6.3.3}%
\contentsline {subsection}{\numberline {6.3.4}Performance Comparison Metrics of the proposed model on 90\% training data}{123}{subsection.6.3.4}%
\contentsline {subsection}{\numberline {6.3.5}Comparison with related works}{125}{subsection.6.3.5}%
\contentsline {subsection}{\numberline {6.3.6}Ablation experiment}{126}{subsection.6.3.6}%
\contentsline {subsection}{\numberline {6.3.7}Threats to Validity concerning this research}{129}{subsection.6.3.7}%
\contentsline {section}{\numberline {6.4}Chapter Summary}{130}{section.6.4}%
\contentsline {chapter}{\numberline {第七章\hspace {.3em}}Conclusions and Future Works}{131}{chapter.7}%
\contentsline {section}{\numberline {7.1}Conclusions}{131}{section.7.1}%
\contentsline {section}{\numberline {7.2}The Future Works}{133}{section.7.2}%
\contentsline {chapter}{参考文献}{134}{section.7.2}%
\contentsline {chapter}{致谢}{135}{chapter*.96}%
\contentsline {chapter}{攻读博士学位期间发表的学术论文及参与的科研项目}{136}{chapter*.97}%
\contentsfinish