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美赛论文LaTeX模板

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%% 本论文的排版主要参考了LaTeX2e插图指南(王磊), LaTeX2e用户手册, media的中文学位%% 论文宏包(CDT), happaytex的ORmain1.tex等文件以及ChinaTeX, CTeX论坛上的诸多贴子. %%% 本论文采用了Miktex2.2的方式在ChinaTeX.iso系统下得到了实现,其编译方式为%% latex(得到DVI文件)+dvips(得到PS文件)+ps2pdf(可得PDF文件).%%\documentclass[12pt]{article}%需要的一些宏包\usepackage{CJK} % 中文输入环境宏包\usepackage{titlesec,titletoc} % 配合命令在后面, 章节标题设置\usepackage{indentfirst} % 使首段首行缩进\usepackage{graphicx} % 插图宏包\usepackage{caption2} % 可以更改插图, 表格的标题样式\usepackage{subfigure} % 产生并列的子图或子表, 命令\subfigure, \subtable\usepackage{longtable} % 如果表格太长, 超过了一页时, 就可以试试longtable 宏包所定义的longtable 环境\usepackage{slashbox} % 在表格中绘制斜线\usepackage{fancyhdr} % 更改页眉的宏包, 并可在页眉插入图片\usepackage{times} % Times Roman + Helvetica + Courier\usepackage{amsmath} % 数学符号宏包AMS-LaTeX, 如下面的\overset需要此宏包%页面的设置\special{papersize=21cm,29.7cm} \setlength{\textwidth}{15cm}\setlength{\textheight}{23cm} \setlength{\evensidemargin}{0.46cm}\setlength{\oddsidemargin}{0.46cm} \setlength{\topmargin}{-1.84cm}\setlength{\headheight}{2.9cm} \setlength{\headsep}{0.4cm}%字号设置\newcommand{\chuhao}{\fontsize{42pt}{\baselineskip}\selectfont}\newcommand{\xiaochuhao}{\fontsize{36pt}{\baselineskip}\selectfont}\newcommand{\yihao}{\fontsize{26pt}{\baselineskip}\selectfont}\newcommand{\xiyihao}{\fontsize{24pt}{\baselineskip}\selectfont}\newcommand{\erhao}{\fontsize{22pt}{\baselineskip}\selectfont}\newcommand{\xiaoerhao}{\fontsize{18pt}{\baselineskip}\selectfont}\newcommand{\sanhao}{\fontsize{16pt}{\baselineskip}\selectfont}\newcommand{\xiaosanhao}{\fontsize{15pt}{\baselineskip}\selectfont}\newcommand{\sihao}{\fontsize{14pt}{\baselineskip}\selectfont}\newcommand{\xiaosihao}{\fontsize{12pt}{\baselineskip}\selectfont}\newcommand{\wuhao}{\fontsize{10.5pt}{\baselineskip}\selectfont}\newcommand{\xiaowuhao}{\fontsize{9pt}{\baselineskip}\selectfont}\newcommand{\liuhao}{\fontsize{7.5pt}{\baselineskip}\selectfont}\newcommand{\xiaoliuhao}{\fontsize{6.5pt}{\baselineskip}\selectfont}\newcommand{\qihao}{\fontsize{5.5pt}{\baselineskip}\selectfont}\newcommand{\bahao}{\fontsize{5pt}{\baselineskip}\selectfont}%页眉的设置, 要用到fancyhdr宏包\pagestyle{fancy} \fancyhead{} \fancyfoot{}\fancyhead[L]{\footnotesize Team \# 189}\fancyhead[R]{\footnotesize Page\ \thepage\ of\ 42}\fancypagestyle{plain}{%\fancyhead[L]{\footnotesize Team \# 189}\fancyhead[R]{\footnotesize Page\ \thepage\ of\ 42}}\setcounter{secnumdepth}{4}%更改\theparagraph的编号样式\makeatletter\renewcommand{\theparagraph}{\@arabic\c@paragraph}\makeatother%章节格式的设置\titleformat{\section}{\erhao\bf}{}{0em}{}[]\titleformat{\subsection}{\xiaoerhao\bf}{}{0em}{}[]\titleformat{\subsubsection}{\sanhao\bf}{}{0em}{}[]\titleformat{\paragraph}[hang]{\vspace*{0.5ex}\sihao\bf}{\hspace*{1em}\theparagraph)}{0.5em }{}[\vspace*{-0.5ex}]%更改插图的标题\renewcommand{\figurename}{\wuhao\bf\sf Figure}\renewcommand{\captionlabeldelim}{\ }%更改表格的标题\renewcommand{\tablename}{\wuhao\bf\sf Table}%更改图形或表格与其标题的间距\setlength{\abovecaptionskip}{10pt}\setlength{\belowcaptionskip}{10pt}%定义产生不浮动图形和表格的标题的命令\figcaption和\tabcaption\makeatletter\newcommand\figcaption{\def\@captype{figure}\caption}\newcommand\tabcaption{\def\@captype{table}\caption}\makeatother%自定义的可以调整粗细的水平线命令, 用于绘制表格, 调用格式\myhline{0.5mm}. \makeatletter\def\myhline#1{%\noalign{\ifnum0=`}\fi\hrule \@height #1 \futurelet\reserved@a\@xhline}\makeatother%第一层列表序号为带圈的阿拉伯数字\renewcommand{\labelenumi}{\textcircled{\arabic{enumi}}}%更改脚注设置\renewcommand{\thefootnote}{\fnsymbol{footnote}}\begin{document}\begin{CJK*}{GBK}{song}\CJKtilde\title{\bf\yihao Aviation Baggage Screening\\{\&} Flight Schedule}\author{}\date{}\maketitle\section{Introduction}Following the terrorist attacks on September 11, 2001, there isintense interest in improving the security screening process forairline passengers and their baggage. Airlines and airports areconsidered high-threat targets for terrorism, so aviation securityis crucial to the safety of the air-travelling public. Bombs andexplosives have been known to be introduced to aircraft by holdbaggage and cargo, carried on by passengers, and hidden withinaircraft supplies.At present To Screen or Not to Screen, that is a Hobson's choice.US Current laws mandate 100{\%} screening of all checked bags at the 429 passenger airports throughout the nation by explosive detection systems(EDS) by the end of the Dec 31 2003. However, because the manufacturers arenot able to produce the expected number of EDS required to meet the federal mandate, so it is significant to determine the correct number of devicesdeploy at each airport, and to take advantage of them effectively.The Transportation Security Administration (TSA) needs a complicatedanalysis on how to allocate limited device and how to best use them.Our paper contains the mathematical models to determine the number of EDSsand flight schedules for all airports in Midwest Region. We also discuss theETD devices as the additional security measures and the future developmentof the security systems.\section{Assumption and Hypothesis}\begin{itemize}\item The passengers who will get on the same airplane will arrive uniformly, namely the distribution is flat.\item The detection systems, both EDS and ETD, operate all the time during peak hour, except downtime.\item The airline checks the passengers randomly, according to its claim.\item The passengers, who are just landing and leave out, do not have to be checked through EDS or ETD.\item According to the literature, the aircraft loads approximately equal among the sets of departing flight during the peak hour.\item The landing flight did not affect the departure of the plane.\item Once a passenger arrives, he can go to EDS to be checked, except he has to wait in line.\item Once passengers finish screening, they can broad on the plane in no time.\item During peak hours, a set of flights departs at the same time every the same minutes.\item All the runways are used as much as possible during peak hours.\item The maximum number of the baggage is two, which a passenger can carry on plane. []\item The detection machine examines the bags at the same speed.\item EDS cannot make mistakes that it detect a normal object as an explosive.\end{itemize}\section{Variable and Definition}\begin{longtable}{p{100pt}p{280pt}}\caption{Variables}\\ %第一页表头的标题\endfirsthead %第一页的标题结束\caption{(continued)}\\ %第二页的标题\endhead %第二页的标题结束\hline\hline\textbf{Symbol}&\textbf{Description}\\\hline$n_{ij}$&The airplane number of the $i^{\mathrm{th}}$ type in the $j^{\mathrm{th}}$ flight set\\\hline${NP}_i\:(i=1,2,\ldots)$&The number of passengers on each airplanes of the same type.\\\hline$\xi_{ij}\:(i,j = 1,2,\cdots)$&The number of baggage on each airplane of the $j^{\mathrm{th}}$ flights\\\hline$a$&The maximal number of airplanes type\\\hline$B_j^{set}$&The total baggage number of each set of flight\\\hline${NF}_i$&Number of airplanes of each type\\\hline$\bar{\rho}$&The mean value of passengers' baggage coming per minute in every flight set\\ \hline$N_{set}$&The number of flight sets\\\hline$B_{total}$&The total number of checked baggage during the peak hour\\\hline$H_{peak}$&The length of the peak hour\\\hline$T_{set}$&The time length during which each flight set's passengers wait to be checked\\\hline$\Delta t$&The time interval between two consecutive flight set\\\hline$N_{EDS}$&The number of all the EDSs\\\hline$N_{shadow}$&The number of flight sets whose passengers will be mixed up before being checked\\\hline$v_{EDS}$&The number of baggage checking by one EDS per minute\\\hline$\rho_j$&The number of passengers' baggage coming per minute in one flight set\\\hline$N_{runway}$&The number of an airport's runway\\\hline\\*[-2.2ex]${\bar{B}}^{set}$&The mean value of checked baggage number of every flight set\\\hline$M$&The security cost\\\hline\hline\label{tab1}\end{longtable}\subsubsection{Definition:}\begin{description}\item[Flight set] A group of flights take off at the same time\item[The length of peak hour] The time between the first set of flight and the last set\end{description}\section{Basic Model}During a peak hour, many planes and many passengers would departfrom airports. Therefore, It is difficult to arrange for thepassengers to enter airports. If there are not enough EDSs forpassengers' baggage to check, it will take too long time for themto enter. That would result in the delay of airplanes. On thecontrary, if there are too many EDSs, it will be a waste. It isour task to find a suitable number of EDSs for airport. In orderto reach this objective, we use the linear programming method tosolve it.\subsection{Base analysis}The airplanes are occupied at least partly. The passengers'baggage would be checked by EDSs before they get on the airplanes.We have assumed that every passenger carry two baggages. Thisassumption would simplify the problem. According to the data fromthe problem sheet, we can obtain the useful information thatairlines claim 20{\%} of the passengers do not check any luggage,20{\%} check one bag, and the remaining passengers check two bags.Therefore, we can gain the total number of passengers' baggagethat should be carried on one plane: $\xi_{ij}$. Moreover, we canget the equation that calculate $\xi_{ij}$:\[\xi_{ij}={NP}_i\times 20\%+{NP}_i\times 60\%\times 2\]We define the matrix below as airplane baggage number matrix:\[\overset{\rightharpoonup}{\xi}_j=\left[\xi_{1j}\quad\xi_{2j}\quad\cdots\quad\xi_{ij}\quad\cdots\ right]\]We define the matrix below as flight schedule matrix:\[\left[\begin{array}{llcl}n_{11}&n_{12}&\cdots&n_{1N_{set}}\\n_{21}&n_{22}&\cdots&n_{2N_{set}}\\\multicolumn{4}{c}\dotfill\\n_{a1}&n_{a2}&\cdots&n_{aN_{set}}\end{array}\right]\]In this matrix, $n_{ij}$ is the airplane number of the$i^{\mathrm{th}}$ type in the $j^{\mathrm{th}}$ flight set whichwill take off. Apparently, this value is an integer.We define the matrix below as flight set baggage number matrix:\[\left[B_1^{set}\quad B_2^{set}\quad\cdots\quad B_j^{set}\quad\cdots\quad B_a^{set}\right] \]It is clear that they meet the relation below:\begin{equation}\begin{array}{cl}&\left[\xi_{1j}\quad\xi_{2j}\quad\cdots\quad\xi_{ij}\quad\cdots\right]\cdot\left[\begin{array}{llcl}n_{11}&n_{12}&\cdots&n_{1N_{set}}\\n_{21}&n_{22}&\cdots&n_{2N_{set}}\\\multicolumn{4}{c}\dotfill\\n_{a1}&n_{a2}&\cdots&n_{aN_{set}}\end{array}\right]\\=&\left[B_1^{set}\quad B_2^{set}\quad\cdots\quad B_j^{set}\quad\cdots\quad B_a^{set}\right]\end{array}\label{Flight:baggage}\end{equation}Then, we know:\[B_j^{set}=\sum\limits_{i=1}^a\xi_{ij}\times n_{ij}\]There are some constraints to the equation (\ref{Flight:baggage}).First, for each set of flight, the total number of airplanesshould be less than the number of runways. Second, the totalairplane number of the same type listed in the equation(\ref{Flight:baggage}) from every set of flight should be equal tothe actual airplane number of the same type during the peak hour.We can express them like these:\[\sum\limits_{i=1}^a n_{ij}\le N_{runway}\quad\quad\sum\limits_{j=1}^b n_{ij}={NF}_i \]We should resolve the number of flight sets. According to our assumptions,during the peak hour, the airlines should make the best use of the runways.Then get the number of flight sets approximately based on the number of allthe airplanes during the peak hour and that of the runways. We use anequation below to express this relation:\begin{equation}N_{set}=\left\lceil\frac{\sum\limits_{j=1}^{N_{set}}\sum\limits_{i=1}^an_{ij}}{N_{runway}}\right\rceil\label{sets:number}\end{equation}The checked baggage numbers of each flight set are equal to eachother according to our assumption. We make it based on literature.It can also simplify our model. We define $\bar{B}^{set}$ as themean value of checked baggage number of every flight set.Moreover, We define $\bar{\rho}$ as the mean value of checkedbaggage number of every flight set per minute:\[\bar{B}^{set}=\frac{B_{total}}{N_{set}}\]\[\bar{\rho}=\frac{\bar{B}^{set}}{T_{set}}=\frac{B_{total}}{T_{set}N_{set}}=\frac{B_{total}\ Delta t}{T_{set}H_{peak}}\]The course of passengers' arrival and entering airport isimportant for us to decide the number of EDSs and to make theflights schedule. Therefore, we should analyze this processcarefully. Passengers will arrive between forty-five minutes andtwo hours prior to the departure time, and the passengers who willget on the same airplane will arrive uniformly. Then we can getthe flow density of all checked baggage at any time duringpassengers' entering. This value is the sum of numbers ofpassengers' checked baggage coming per minute. To calculate thisvalue, firstly, we should obtain flow density of each flight set'schecked baggage. We define $\rho_j $, namely the number of checkedbaggage per minute of one flight set:\[\rho_j=\frac{B_j^{set}}{T_{set}}\]Secondly, we draw graphic to help us to understand. We userectangle to express the time length for all the passengers of oneflight set to come and check bags. In the graphic, the black partis the period for them to come. During the white part, nopassengers for this flight set come. According to the problemsheet, the former is 75 minute, and the latter is 45 minute. Thelength of rectangle is 120 minute. $T_{set}$ is the period duringwhich all passengers of one flight set wait to be checked. Sincewe have assumed that each time interval between two consecutiveflight set is same value, we define $\Delta t$ as it. Observe thesection that value we want to solve is $\sum\limits_j\rho_j$. Moreover, we can get another important equation from the graphic below:\begin{equation}N_{set}=\frac{H_{peak}}{\Delta t}\label{PeakHour}\end{equation}\begin{figure}[hbtp]\centering\includegraphics[width=298.2pt,totalheight=141.6pt]{fig01.eps}\caption{}\label{fig1}\end{figure}Each EDS has certain capacity. If the number of EDSs is $N_{EDS}$ and one EDS can check certain number of baggage per minute (Thatis checking velocity, marked by $v_{EDS}$), the total checking capacity is $N_{EDS}\cdot\frac{v_{EDS}}{60}$. $v_{EDS}$ is between 160 and 210.Now we can easily decide in what condition the passengers can be checked without delay:\[\sum\limits_j\rho_j\le v_{EDS}\]The passengers have to queue before being checked:$\sum\limits_j\rho_j>v_{EDS}$Well then, how can we decide how many $\rho_j$? It depends on how many flight sets whose passengers will be mixed up before being checked. We note it as $N_{shadow} $. Return to the Figure\ref{fig1}, we can know:\[N_{shadow}=\left\lfloor\frac{T_{set}}{\Delta t}\right\rfloor\]\begin{figure}%[htbp]\centering\includegraphics[width=240pt,totalheight=131.4pt]{fig02.eps}\caption{}\label{fig2}\end{figure}From Figure \ref{fig1} and Figure \ref{fig2}, we can get theresult as follows:\begin{enumerate}\item If $N_{shadow}\le N_{set}$, namely $H_{peak}>T_{set}$, then $\sum\limits_{j=1}^{N_{shadow}}\rho _j\le N_{EDS}\frac{v_{EDS}}{60}$\renewcommand{\theequation}{\arabic{equation}a}That is:\begin{equation}N_{EDS}\ge\frac{60}{v_{EDS}}\sum\limits_{j=1}^{N_{shadow}}\rho_j\approx\frac{60}{v_{ EDS}}N_{shadow}\bar{\rho}=\frac{60B_{total}\Deltat}{v_{EDS}T_{set}H_{peak}}N_{shadow}\label{EDS:number:a}\end{equation}\item If $N_{shadow}>N_{set}$, namely $H_{peak}\le T_{set}$, then $\sum\limits_{j=1}^{N_{set}}\rho_j\le N_{EDS}\frac{v_{EDS}}{60}$\setcounter{equation}{3}\renewcommand{\theequation}{\arabic{equation}b}That is:\begin{equation}N_{EDS}\ge\frac{60}{v_{EDS}}\sum\limits_{j=1}^{N_{set}}\rho_j\approx\frac{60}{v_{EDS} }N_{set}\bar{\rho}=\frac{60B_{total}\Delta t}{v_{EDS}T_{set}H_{peak}}N_{set}\label{EDS:number:b}\end{equation}\end{enumerate}\subsection{The number of EDSs}Then we begin to resolve the number of EDSs assisted by the linearprogramming method.EDS is operational about 92{\%} of the time. That is to say, whenever it isduring a peak hour, there are some EDSs stopping working. Then the workingefficiency of all the EDSs is less than the level we have expected.Therefore, the airline has to add more EDSs to do the work, which can bedone with less EDSs without downtime.We use binomial distribution to solve this problem. $N$ is the number ofactual EDSs with downtime and $k$ is the number of EDSs without downtime. Ifprobability is $P$, we can get the equation below:\[\left(\begin{array}{c}N\\k\end{array}\right)\cdot98\%^k\cdot(1-98\%)^{N-k}=P\]We can obtain $N$ when we give $P$ a certain value. In this paper,$P$ is 95{\%}. The $N_{EDS}$ is the actual number we obtainthrough the equation above.Now we have assumed that passengers can be checked unless be delayed by the people before him once he arrives at airport. Apparently, if the time length between two sets of flight is short, the density of passengers will begreat. It will bring great stress to security check and may even make some passengers miss their flight. To resolve this question, the airline has toinstall more EDSs to meet the demand. However, this measure will cost much more money. Consequently, we have to set a suitable time interval between two set of flight.Based on the base analysis above. We can use the equation(\ref{sets:number}) to decide the number of flight sets $N_{set}$assuming we know the number of runways of a certain airport. Thenbased on the equation (\ref{PeakHour}), we can decide the peakhour length $H_{peak}$ when we assume a time interval between two consecutive flight sets. Then we use \textcircled{1} and\textcircled{2} to decide which to choose between equation(\ref{EDS:number:a}) and equation (\ref{EDS:number:b}). In consequence, we can obtain the minimum of EDSs number.If we choose different numbers of runways and the time intervalsbetween two flight sets, we can get different EDSs numbers. Inthis paper that followed, we gain a table of some value of$N_{runway}$ and $\Delta t$ with the corresponding EDSs numbers. Moreover, we draw some figure to reflect their relation.For a certain airport, its number of runway is known. Givencertain time interval ($\Delta t$), we can get the length of thepeak hour ($H_{peak}$). When the $N_{runway}$ is few enough,perhaps $H_{peak}$ is too long to be adopted. However, for acertain airline, they can decide the time interval of their ownpeak hour. In this given time interval, they could find theminimum of $N_{runway}$ through the Figure \ref{fig3}. We draw asketch map to describe our steps.\begin{figure}[hbtp]\centering\includegraphics[width=352.8pt,totalheight=214.2pt]{fig03.eps}\caption{}\label{fig3}\end{figure}\subsection{The Flight Schedule }According to the base analysis, we can know that the flightschedule matrix and $\Delta t$ is one form of flight timetable. In``The number of EDSs'', we can get suitable $\Delta t$. Then weshould resolve the flight schedule matrix.Because we have assumed that the checked baggage numbers of each flight setare equal to each other. It can be described as follows:\[\left\{\begin{array}{l}\rho_j\approx\bar{\rho}\\B_j^{set}\approx\bar{B}^{set}\end{array}\right.\begin{array}{*{20}c}\hfill&{j=1,2,\cdots,N_{set}}\hfill\end{array}\]The flight schedule matrix subject to this group:\[\left\{\begin{array}{ll}\sum\limits_{j=1}^{N_{set}}n_{ij}={NF}_i&i=1,2,\cdots\\\sum\limits_{i=1}^a n_{ij}\le N_{runway}&j=1,2,\cdots,N_{set}\\n_{ij}\ge0,&\mathrm{and}\:n_{ij}\:\mathrm{is}\:\mathrm{a}\:\mathrm{Integer} \end{array}\right.\]In order to make the best use of runway, we should make$\sum\limits_{i=1}^a n_{ij}$ as great as we can unless it exceed$N_{runway}$.Then we can see that how to resolve the flight schedule matrix is a problemof divide among a group of integers. This group is all the numbers of eachflight passengers' baggage in one flight set. We program for this problemusing MA TLAB and we get at least one solution in the end. However, thematrix elements we have obtained are not integer, we have to adjust them tobe integers manually.\subsection{Results and Interpretation for Airport A and B}The number of passengers in a certain flight (${NP}_i$), the timelength of security checking ($T_{set}$), the checking velocity ofEDS ($v_{EDS}$), and the number of baggage carried by onepassenger are random.\subsubsection{Data Assumption:}\begin{itemize}\item $T_{set}$ is 110 minutes, which is reasonable for airline.\item To simplify the problem, we assume that every passenger carry 2 baggage. If some of thepassengers carry one baggage, the solution based on 2 baggages per passenger meets therequirement.\item The number of runways in airport A and airport B is 5.\end{itemize}\subsubsection{Airport A:}Once the number of runway and the number of the flights aredecided, the flight schedule matrix is decided, too. We producethis matrix using MATLAB. This matrix companied by $\Delta t$ isthe flight schedule for airport A. $\Delta t$ will be calculatedin (\ref{Flight:baggage}), (\ref{sets:number}) and(\ref{PeakHour}).We calculate $N_{EDS}$ and make the flight timetable in threeconditions. The three conditions and the solution are listed asfollowed:\paragraph{Every flight are fully occupied}The checking speed of EDS is 160 bags/hour.\begin{table}[htbp]\centering\caption{}\begin{tabular}{*{11}c}\myhline{0.4mm}$\mathbf{\Deltat(\min)}$&\textbf{2}&\textbf{4}&\textbf{6}&\textbf{8}&\textbf{10}&\textbf{12}&\textbf{14} &\textbf{16}&\textbf{18}&\textbf{20}\\\myhline{0.4mm}$N_{EDS}(\ge)$&31&31&31&31&31&29&24&22&20&17\\\hline$H_{peak}(\min)$&20&40&60&80&100&120&140&160&180&200\\\myhline{0.4mm}\end{tabular}\label{tab2}\end{table}We assume that the suitable value of $H_{peak}$ is 120 minutes.Then the suitable value of $\Delta t$ is about 12 minutes, and$N_{EDS}$ is 29 judged from Figure \ref{fig4}. Certainly, we canwork $\Delta t$ and $N_{EDS}$ out through equation.\begin{figure}[htbp]\centering\includegraphics[width=294.6pt,totalheight=253.2pt]{fig04.eps}\caption{}\label{fig4}\end{figure}\paragraph{Every flight is occupied by the minimal number of passengers onstatistics in the long run.}The checking speed of EDS is 210 bags/hour.\begin{table}[htbp]\centering\caption{}\begin{tabular}{*{11}c}\myhline{0.4mm}$\mathbf{\Deltat(\min)}$&\textbf{2}&\textbf{4}&\textbf{6}&\textbf{8}&\textbf{10}&\textbf{12}&\textbf{14} &\textbf{16}&\textbf{18}&\textbf{20}\\\myhline{0.4mm}$N_{EDS}(\ge)$&15&15&15&15&15&14&13&12&10&7\\\hline$H_{peak}(\min)$&20&40&60&80&100&120&140&160&180&200\\\myhline{0.4mm}\end{tabular}\label{tab3}\end{table}We assume that the suitable value of $H_{peak}$ is 120 minutes.Then the suitable value of $\Delta t$ is about 12 minutes, and$N_{EDS}$ is 14 judging from Figure \ref{fig5}. Certainly, we canwork $\Delta t$ and $N_{EDS}$ out through equation.\begin{figure}[htbp]\centering\includegraphics[width=294.6pt,totalheight=253.2pt]{fig05.eps}\caption{}\label{fig5}\end{figure}\paragraph{${NP}_i$ and $v_{EDS}$ are random value produced by MATLAB.}\begin{table}[htbp]\centering\caption{}\begin{tabular}{*{11}c}\myhline{0.4mm}$\mathbf{\Deltat(\min)}$&\textbf{2}&\textbf{4}&\textbf{6}&\textbf{8}&\textbf{10}&\textbf{12}&\textbf{14} &\textbf{16}&\textbf{18}&\textbf{20}\\\myhline{0.4mm}$N_{EDS}(\ge)$&15&22&21&21&15&17&21&16&13&14\\\hline$H_{peak}(\min)$&20&40&60&80&100&120&140&160&180&200\\\myhline{0.4mm}\end{tabular}\label{tab4}\end{table}We assume that the suitable value of $H_{peak}$ is 120 minutes.Then the suitable value of $\Delta t$ is about 12 minutes, and$N_{EDS}$ is 17 judging from Figure \ref{fig6}. Certainly, we canwork $\Delta t$ and $N_{EDS}$ out through equation.\begin{figure}[htbp]\centering\includegraphics[width=294.6pt,totalheight=249.6pt]{fig06.eps}\caption{}\label{fig6}\end{figure}\subsubsection{Interpretation:}By analyzing the results above, we can conclude that when$N_{EDS}$ is 29, and $\Delta t$ is 12, the flight schedule willmeet requirement at any time. The flight schedule is:\\[\intextsep]\begin{minipage}{\textwidth}\centering\tabcaption{}\begin{tabular}{c|*{8}c|c|c}\myhline{0.4mm}\backslashbox{\textbf{Set}}{\textbf{Type}}&\textbf{1}&\textbf{2}&\textbf{3}&\textbf{4}&\te xtbf{5}&\textbf{6}&\textbf{7}&\textbf{8}&\textbf{Numbers of Bags}&\textbf{Numbers of Flights}\\\myhline{0.4mm}1&2&0&0&0&2&1&0&0&766&5\\\hline2&2&0&2&0&2&0&0&0&732&4\\\hline3&0&1&1&1&2&0&0&0&762&4\\\hline4&0&1&0&0&2&1&0&0&735&4\\\hline5&0&1&0&0&2&1&0&0&735&5\\\hline6&2&0&0&0&1&0&0&1&785&5\\\hline7&2&0&0&0&2&0&1&0&795&5\\\hline8&0&1&0&0&2&1&0&0&735&4\\\hline9&2&0&0&0&2&1&0&0&766&5\\\hline10&0&0&0&2&2&0&0&0&758&5\\\hlineTotal&10&4&3&3&19&5&1&1&7569&46\\\myhline{0.4mm}\end{tabular}\label{tab5}\end{minipage}\\[\intextsep]We have produced random value for ${NP}_i$ and $v_{EDS}$. On thiscondition, the number of EDSs is 17, which is less than 29 that wedecide for the airport A. That is to say our solution can meet thereal requirement.\subsubsection{Airport B:}\paragraph{The passenger load is 100{\%}}The checking speed of EDS is 160 bags/hour.\begin{table}[htbp]\centering。

用latex软件撰写科技议论文模板.

用latex软件撰写科技议论文模板.

Latex 实用例子通过实验本例子可以基本掌握科技排版的方法:\documentclass[twocolumn]{article}\usepackage{amsmath}\renewcommand{\rmdefault}{ptm}\begin{document}\title{Physical Model Order Reduction}\author{Qiang Wang and Guo-Hua Li\\Department of Electronic Engineering,the East University of China}\date{December 17, 2009}\maketitle\begin{abstract}This paper presents a novelapproach for model order reduction for multilayer lossy RFembedded passives.\end{abstract}\section{Introduction}As the Radiofrequency modules having been designed more compactthan ever before, the parasitic effects due to the tightly coupledinter-connections on the circuit layout are inevitable. Therefore,an efficient method that can derive a circuit model of such circuitlayout is highly desirable. A few techniques such as PEEC were developed to extract equivalent circuits from an electromagnetic model.Classic PEEC solver converts the layout into lumped RLCinterconnection networks, including mutual couplings. Once a circuit model is generated, any circuit solver, such as SPICE, can manage the rest of the job. Unfortunately, the numbers of nodes and elements in the circuits are excessive. Therefore, researchers have been searching for an effective measure that can reduce the model order for accelerating the analysis of the circuit model.Although exploited Krylovsubspace methods and provided ways to speed up the simulation; they all lack the physical insight. In fact, they are mathematics-based MOR. Several realizable model order reduction approaches are also proposed. However, can only handle RC networks. Besides, they both concern with matching the first two or three moments of the system via Taylor's expansion. Thus, these methods can not provide a clear physical explanation to the reduced circuit either. It is worth mentioning that has showed some insight fordealing with coupled inductances, even though the complexity of the scheme itself might have already limited its practical use.The work presented in this paper is an extension to,in which a derived physically realizable lossless expressive circuit model reduction method is introduced. In this paper, a lossy modelis the major concern. The passivity of the resultant circuit modelby the new reduction scheme is guaranteed.\section{Theory}The circuit model generated by traditional quasi-static PEEC model for a multi-layer circuit layout with very thin conducting stripscan easily incorporate the conducting loss, which is a major origin of the circuit loss.Since the meshes used in solving MPIE (Mixed Potential Integrated Equations of the PEEC algorithm are all in regular shapes, thus we could first evaluate their losses piecewisely and then superimpose this pre-calculated loss model to the generated circuit model to represent the conductor loss of the circuit. Therefore reasonable and time-saving approaches to calculate the loss for different meshing geometries are investigated.Since the conductor loss is generally determined by the skin depth effect at RF frequency, a coarse but rapid approximation to this type of loss is to find out the skin depth and other shape factorsof the mesh. Then the equivalent surface impedance can be easily calculated by $R_{L} = l / 2\delta S$, where $l$ is the mesh length, along which the current flows, $S$ is the area of the equivalent crossing section where the current goes through, $\delta$ is the skin depth:\begin{align}\delta=\frac{1}{\sqrt{\smash[b]{\pi f \mu \sigma}}},\label{Equ1}\end{align}in which $f$ is the frequency, $\mu$ is the magnetic permeability, and $\sigma$ is the conductivity of the metal. In addition to this, various other empirical formulas, such as those incould also be used todetermine the conducting loss.Capacitor's loss is mainly due to bypassing leak-age current. Considering the basic relationship be-tween the current and the charge stored in the capacitor, its losscontribution could be computed by $G_{C} = \sigma C / \varepsilon$, where $G_{C}$ is the bypassing conductance, $C$ is the capacitance, $\varepsilon$ and $\sigma$ are the dielectric constant and the conductivity of the substrate, respectively....\end{document}形成的PDF效果图:。

latex的论文格式模板

latex的论文格式模板

latex的论文格式模板LaTeX是一种基于ΤΕΧ的排版系统即使使用者没有排版和程序设计的知识也可以充分发挥由TeX所提供的强大功能,那它的论文格式是怎么样的呢?下面是小编精心推荐的一些latex的论文格式模板,希望你能有所感触!latex的论文格式模板1、题目:应简洁、明确、有概括性,字数不宜超过20个字。

2、摘要:要有高度的概括力,语言精练、明确,中文摘要约100—200字;3、关键词:从论文标题或正文中挑选3~5个最能表达主要内容的词作为关键词。

4、目录:写出目录,标明页码。

5、正文:论文正文字数一般应在3000字以上。

论文正文:包括前言、本论、结论三个部分。

前言(引言)是论文的开头部分,主要说明论文写作的目的、现实意义、对所研究问题的认识,并提出论文的中心论点等。

前言要写得简明扼要,篇幅不要太长。

本论是论文的主体,包括研究内容与方法、实验材料、实验结果与分析(讨论)等。

在本部分要运用各方面的研究方法和实验结果,分析问题,论证观点,尽量反映出自己的科研能力和学术水平。

结论是论文的收尾部分,是围绕本论所作的结束语。

其基本的要点就是总结全文,加深题意。

6、谢辞:简述自己通过做论文的体会,并应对指导教师和协助完成论文的有关人员表示谢意。

7、参考文献:在论文末尾要列出在论文中参考过的专著、论文及其他资料,所列参考文献应按文中参考或引证的先后顺序排列。

8、注释:在论文写作过程中,有些问题需要在正文之外加以阐述和说明。

9、附录:对于一些不宜放在正文中,但有参考价值的内容,可编入附录中。

关于养生的论文范文浅析中医养生智慧摘要:《黄帝内经》讲道:"法于阴阳,和于术数,食饮有节,起居有常,不妄作劳,故能形与神俱,而尽终其天年,度百岁乃去。

"只有在平时养成良好的生活习惯,并以"经典"养生方法,点滴积累,持之以恒,才能令体质强健,年过百而动作不衰也,真正达到益寿延年的目的。

latex英文作业模板

latex英文作业模板

latex英文作业模板英文回答:Introduction.In this essay, I will discuss the various factors that influence the popularity of online games, including game design, marketing, and social aspects.Game Design.One of the most important factors that influence the popularity of online games is the game design itself. Games that are well-designed are more likely to be enjoyed by players and to keep them coming back for more. There are a number of elements that go into good game design, including:Gameplay: The gameplay is the core of any game, and it is what keeps players engaged. Games that are challenging and rewarding are more likely to be popular than games thatare too easy or too difficult.Graphics: The graphics of a game can also play a role in its popularity. Games with high-quality graphics are more likely to attract players than games with poor graphics.Story: The story of a game can also be a factor in its popularity. Games with engaging stories are more likely to keep players invested in the game world.Marketing.Marketing is another important factor that can influence the popularity of online games. Games that are marketed well are more likely to reach a wider audience and to generate interest in the game. There are a number of different marketing strategies that can be used to promote online games, including:Advertising: Advertising is one of the most common ways to market online games. Games can be advertised on avariety of platforms, including television, radio, and the internet.Social media: Social media can also be a powerful tool for marketing online games. Games can be promoted on social media platforms by creating engaging content and by interacting with potential players.Influencer marketing: Influencer marketing is another effective way to market online games. Influencers are people who have a large following on social media and who can help to promote games to their followers.Social Aspects.The social aspects of online games can also play a role in their popularity. Games that allow players to interact with each other are more likely to be popular than games that are played solo. There are a number of different ways that players can interact in online games, including:Chat: Chat is one of the most common ways for playersto interact in online games. Players can chat with each other in real-time, which can help to build relationships and create a sense of community.Clans and guilds: Clans and guilds are groups of players who band together to play together and achieve common goals. Clans and guilds can provide players with a sense of belonging and support.Player-versus-player (PvP) PvP is a type of online game in which players compete against each other. PvP can be a lot of fun, and it can also help to build rivalries and create a sense of competition.Conclusion.The popularity of online games is influenced by a number of factors, including game design, marketing, and social aspects. By understanding these factors, game developers can create games that are more likely to be popular with players.中文回答:简介。

MCM美赛论文集

MCM美赛论文集

高教社杯全国大学生数学建模竞赛承诺书我们仔细阅读了中国大学生数学建模竞赛的竞赛规则。

我们完全明白,在竞赛开始后参赛队员不能以任何方式(包括电话、电子邮件、网上咨询等)与队外的任何人(包括指导教师)研究、讨论与赛题有关的问题。

我们知道,抄袭别人的成果是违反竞赛规则的,如果引用别人的成果或其他公开的资料(包括网上查到的资料),必须按照规定的参考文献的表述方式在正文引用处和参考文献中明确列出。

我们郑重承诺,严格遵守竞赛规则,以保证竞赛的公正、公平性。

如有违反竞赛规则的行为,我们将受到严肃处理。

我们参赛选择的题号是(从A/B/C/D中选择一项填写):A我们的参赛报名号为(如果赛区设置报名号的话):99999所属学校(请填写完整的全名):西安交通大学参赛队员(打印并签名):1.一作者2.二作者3.三作者指导教师或指导教师组负责人(打印并签名):导师日期:2011年8月1日赛区评阅编号(由赛区组委会评阅前进行编号):2011高教社杯全国大学生数学建模竞赛编号专用页赛区评阅编号(由赛区组委会评阅前进行编号):赛区评阅记录(可供赛区评阅时使用):评阅人评分备注全国统一编号(由赛区组委会送交全国前编号):全国评阅编号(由全国组委会评阅前进行编号):全国大学生数学建模竞赛L A T E X2ε模板摘要这是数学建模论文模板mcmthesis的示例文件。

特别地,这篇文档是“全国大学生数学建模竞赛(CUMCM)”模板的示例文件。

这个模板使用于参加高教社杯全国大学生数学竞赛的同学准备他们的建模论文,帮助他们更多的关注于论文内容而非论文的排版。

这个模板的设计是根据2010年修订的《全国大学生数学建模竞赛论文格式规范》[1]制作,完全符合该论文格式规范,但是该模板未得到官方认可,请使用者自己斟酌使用。

这个示例文档逐条展示其对[1]的实现效果,并对所有自定义命令进行说明。

这个示例文件还包含了一些对公示、插图、表格、交叉引用、参考文献、代码等的测试部分,以展示其效果,并作简要的使用说明。

latex数学模板样例

latex数学模板样例

当您在撰写数学论文或报告时,使用LaTeX数学模板可以帮助您更轻松地组织和格式化数学内容。

以下是一个简单的LaTeX数学模板样例,用于演示如何使用LaTeX编写数学公式和符号。

首先,确保您已经安装了LaTeX软件包和相应的数学包。

然后,按照以下步骤创建数学模板文档:1. 创建一个新的LaTeX文档,并使用适合您的模板或新建一个空白文档。

2. 在文档中添加一个环境来包含您的数学公式和符号。

常用的环境是`equation`、`align`或`gather`等。

3. 在环境中,使用LaTeX数学命令来创建公式和符号。

以下是一些常用的命令示例:* `\frac{分子}{分母}`:用于分数。

* `\sqrt{x}`:用于平方根。

* `\lim_{x \rightarrow ∞}`:用于极限符号。

* `\oint_{x=a到b}`:用于积分符号。

* `\pm`、` \times`、` \div`等:基本的运算符。

4. 添加必要的上下文和说明。

例如,如果您要写一个数学定理的证明过程,请提供相关的定义、前提和结论。

5. 使用LaTeX文档类和数学包来正确显示公式和符号。

通常,LaTeX文档类提供了一些预设的样式和符号,而数学包提供了更多的符号和格式选项。

6. 在编译LaTeX文档时,确保正确设置了排版选项和格式化参数。

下面是一个简单的LaTeX数学模板样例,其中包含一些常见的数学公式和符号:```latex\documentclass{article} % 选择适合您的文档类,例如report或book\usepackage{amsmath} % 添加数学包以提供额外的符号和格式选项\begin{document}\begin{equation}\lim_{x \rightarrow \infty} \frac{x}{e^x} = 1\end{equation}\begin{align}a +b &=c \\x^2 + y^2 &= z^2 \\\frac{d}{dx} f(x) &= g(x)\end{align}\end{document}```这个样例包含了一个极限公式、一个加法公式和一个微分公式。

latex论文模板

latex论文模板

latex论文模板
在LaTeX中,有许多可以用于撰写论文的模板。

以下是一些
常用的LaTeX论文模板:
1. `\documentclass{article}`:这是LaTeX的基本模板类别之一,可用于撰写一般论文。

你可以根据需要随意添加其他包和自定义设置。

2. `elsevier`:这是适用于撰写科技领域论文(如工程、计算机
科学等)的模板。

这个模板提供了相应的论文格式和引用风格。

3. `IEEEtran`:这是适用于撰写电气工程和计算机科学领域论
文的模板。

它符合IEEE期刊论文的格式要求。

4. `acmart`:这是适用于计算机科学和信息技术领域的模板,
符合ACM期刊和会议论文的格式要求。

5. `memoir`:这是一个全功能的文档类,可以用于撰写各种类
型的论文,包括书籍、学位论文等。

它提供了丰富的布局和样式选项。

这只是一小部分可以用于LaTeX论文撰写的模板示例。

你可
以根据自己的需求选择相应的模板,并按照模板提供的文档结构和命令进行撰写。

latex中文文稿模板

latex中文文稿模板

latex中文文稿模板以下是一个基本的 LaTeX 中文文稿模板,你可以根据自己的需求进行修改和扩展。

```latex\documentclass[UTF8]{ctexart}\usepackage{ctex}\usepackage{graphicx}\usepackage{geometry}\usepackage{hyperref}\usepackage{caption}\usepackage{subcaption}\usepackage{float}\usepackage{enumitem}\usepackage{makeidx}\makeindex\geometry{a4paper, left=3.18cm, right=3.18cm, top=2.54cm, bottom=2.54cm} \title{中文文稿标题}\author{作者姓名}\date{\today}\begin{document}\maketitle\section{引言}在此处插入引言。

\section{正文}在此处插入正文内容。

\section{结论}在此处插入结论。

\appendix\section{附录}在此处插入附录内容。

\end{document}```此模板使用 `ctexart` 文档类,并采用了 `UTF8` 编码以支持中文字符。

它包含了常用的 LaTeX 包,如 `ctex` 用于中文排版,`graphicx` 用于插入图片,`geometry` 用于页面布局,`hyperref` 用于生成超链接,`caption` 和 `subcaption` 用于图片标题和子标题,`float` 用于浮动图形和表格,`enumitem` 用于定制列表环境,以及 `makeidx` 用于生成索引。

你可以根据自己的需求修改和扩展这个模板,例如添加章节、图表、引用等内容。

如果你有特定的要求或需要进一步的帮助,请提供更多细节。

分享我的Latex模板(数学建模论文通用,附下载链接)

分享我的Latex模板(数学建模论文通用,附下载链接)

分享我的Latex模板(数学建模论⽂通⽤,附下载链接)前⾔去年数模国赛⽤Latex排的论⽂,算是⼊了Latex的坑,⾃此⼀边说着Latex也不是那么好⽤(危)⼀边真⾹了,⼀个学期不管是平时的⼩项⽬⽂档、实验报告、案例分析还是期末论⽂,都是在数模那个.tex⽂件的基础上修改形成的。

于是我把这些七改⼋改的⽂件提炼了⼀下,弄了个模板。

(其实就是把⼏个常⽤的环境堆到⼀起了)直接给⼤家上图!实⽤的很!⼀、编译选项打开.tex⽂件后,点击XeLaTeX编译:就可以看到同⼀路径的⽂件夹中形成了⼀个.pdf⽂件,也就是排版好的⽂章。

⼆、效果⼀览第⼀页,标题+作者+⽬录:Latex代码:1. 数模竞赛要求第⼀页是题⽬、摘要和关键词,不能有作者姓名,把导⾔区的\author{\bf ⼩⼩的灰⾊脑细胞}删掉即可。

2. 如果想要显⽰时间,把\date{}删掉即可。

3. 如果不想要⽬录,把\tableofcontents以及摘要部分的\addcontentsline{toc}{section}{摘要}、参考⽂献部分的\addcontentsline{toc}{section}{参考⽂献}这三⾏删掉即可。

4. 如果不想另起⼀页,把\newpage删掉即可。

5. 导⾔区已设置⾃动⾸⾏缩进,段落写完打两个enter(空⼀⾏)即可实现⾸⾏两个字缩进。

第⼆页,摘要和关键词:第三页,第四页,正⽂:这⾥涉及到⽆序编号、有序编号、三线表绘制、普通表格绘制、插⼊图⽚等知识&环境,简单说⼀下:1. ⽆序编号环境itemize,begin和end成对出现,必须搭配\item。

\begin{itemize} % 这是⼀个⽆序枚举\item\item\end{itemize}2. 有序编号环境enumerate,label=(\arabic*)的意思是排出来是(1)(2)这样形式的编号。

\begin{enumerate}[itemsep=0pt, parsep=0pt, label=(\arabic*)] % 这是⼀个带标签的枚举\item\item\item\end{enumerate}3. 画表格我就不说了,模板⾥⾯填空空嘛。

美赛备忘录latex模板

美赛备忘录latex模板

美赛备忘录latex模板As a participant in the Mathematical Contest inModeling (MCM) or Interdisciplinary Contest in Modeling (ICM), you may be looking for a LaTeX template for your memo. The memo is a crucial component of your submission,as it is the primary method through which you will communicate your findings and recommendations to the judges. Therefore, it is essential that you use a well-designed and professional-looking template to ensure that your memo is clear, organized, and visually appealing.One of the key benefits of using a LaTeX template for your memo is the ability to create a professional and polished document with minimal effort. LaTeX is atypesetting system that is widely used in the academic and scientific communities for its ability to produce high-quality documents with complex formatting requirements. By using a LaTeX template, you can take advantage of thesystem's powerful features to create a memo that is well-structured, visually appealing, and easy to read.In addition to its aesthetic benefits, using a LaTeX template can also help you save time and effort in the memo-writing process. The template provides a pre-designed layout and formatting, which means that you can focus on the content of your memo without having to worry about the technical details of document design. This can beespecially helpful if you are working under a tight deadline and need to produce a high-quality memo quickly.Furthermore, using a LaTeX template can also help you ensure the consistency and professionalism of your memo. The template provides a standardized format for your document, which can help you maintain a cohesive style and structure throughout. This is important for creating a professional and polished impression on the judges who will be evaluating your submission.Finally, using a LaTeX template for your memo can also provide you with the flexibility to customize and personalize your document to meet your specific needs. While the template provides a basic structure andformatting, you can easily modify and customize it to include your own branding, graphics, and other design elements. This can help you create a memo that is not only professional and well-organized but also unique and reflective of your team's identity and style.In conclusion, using a LaTeX template for your memo can offer a range of benefits, including professional design, time savings, consistency, and flexibility. By taking advantage of the powerful features of LaTeX, you can create a memo that effectively communicates your findings and recommendations in a clear, organized, and visually appealing manner. Whether you are participating in the MCM or ICM, using a LaTeX template for your memo can help you make a strong impression on the judges and increase the overall impact of your submission.。

latex 课程论文模板

latex 课程论文模板

在网上有很多LATEX模板,但大多是重量级的,主要用于写毕业论文,对于写课程论文不太方便。

我搜集了网上的一些方法,自己写了一个配置文件,虽然很简单,但对于写一般的课程论文已经足够了。

我的配置文件包含以下功能:1、增加页眉2、设定段与段之间的距离3、增加 \makeak 命令用于产生摘要和关键字部分=====包文件 package.tex =========\usepackage{indentfirst}\usepackage{CJK}\usepackage[%paper=a4paper,vmargin={3.8cm, 3.8cm}body={14.6true cm, 22true cm}]{geometry}\usepackage{fancyhdr}\usepackage{color}\usepackage{CJKpunct}\usepackage{listings}======配置文件 format.tex =========\newcommand{\chuhao}{\fontsize{42pt}{\baselineskip}\selectfont}\newcommand{\yihao}{\fontsize{28pt}{\baselineskip}\selectfont}\newcommand{\erhao}{\fontsize{21pt}{\baselineskip}\selectfont}\newcommand{\sanhao}{\fontsize{15.75pt}{\baselineskip}\selectfont}\newcommand{\sihao}{\fontsize{14pt}{\baselineskip}\selectfont} \newcommand{\wuhao}{\fontsize{10pt}{\baselineskip}\selectfont}\newcommand{\song}{\CJKfamily{song}}\newcommand{\zhuan}{\CJKfamily{zhuan}}\newcommand{\li}{\CJKfamily{li}}\newcommand{\hei}{\CJKfamily{hei}}\setlength{\parskip}{1.5ex plus 0.3ex minus 0.2ex}\pagestyle{fancy}\fancyhead{}\chead{\wuhao\textnormal\leftmark}\cfoot{--\thepage--}% \renewcommand{\headrulewidth}{0.4pt}% \renewcommand{\footrulewidth}{0.4pt}\renewcommand{\sectionmark}[1]{%\markboth{#1}{}}\makeatletter\def\cabs#1{\def\@cabs{#1}}\def\@cabs{}\def\ckey#1{\def\@ckey{#1}}\def\@ckey{}\def\makeak{%\noindent{摘要:}\@cabs\\[0.5em] \noindent{关键字:}\@ckey}\makeatother========例子 test.tex ========\documentclass[a4paper, 12pt]{article} \input{package.tex}\input{format.tex}\begin{document}\begin{CJK*}{UTF8}{song}\title{A test document}\author{abc}\maketitle\cabs{这是摘要}\ckey{这是关键字}\makeak %生成摘要、关键字。

美赛数学建模比赛论文实用模板

美赛数学建模比赛论文实用模板

The Keep-Right-Except-To-Pass RuleSummaryAs for the first question, it provides a traffic rule of keep right except to pass, requiring us to verify its effectiveness. Firstly, we define one kind of traffic rule different from the rule of the keep right in order to solve the problem clearly; then, we build a Cellular automaton model and a Nasch model by collecting massive data; next, we make full use of the numerical simulation according to several influence factors of traffic flow; At last, by lots of analysis of graph we obtain, we indicate a conclusion as follow: when vehicle density is lower than 0.15, the rule of lane speed control is more effective in terms of the factor of safe in the light traffic; when vehicle density is greater than 0.15, so the rule of keep right except passing is more effective In the heavy traffic.As for the second question, it requires us to testify that whether the conclusion we obtain in the first question is the same apply to the keep left rule. First of all, we build a stochastic multi-lane traffic model; from the view of the vehicle flow stress, we propose that the probability of moving to the right is 0.7and to the left otherwise by making full use of the Bernoulli process from the view of the ping-pong effect, the conclusion is that the choice of the changing lane is random. On the whole, the fundamental reason is the formation of the driving habit, so the conclusion is effective under the rule of keep left.As for the third question, it requires us to demonstrate the effectiveness of the result advised in the first question under the intelligent vehicle control system. Firstly, taking the speed limits into consideration, we build a microscopic traffic simulator model for traffic simulation purposes. Then, we implement a METANET model for prediction state with the use of the MPC traffic controller. Afterwards, we certify that the dynamic speed control measure can improve the traffic flow .Lastly neglecting the safe factor, combining the rule of keep right with the rule of dynamical speed control is the best solution to accelerate the traffic flow overall.Key words:Cellular automaton model Bernoulli process Microscopic traffic simulator model The MPC traffic controlContentContent (2)1. Introduction (3)2. Analysis of the problem (3)3. Assumption (3)4. Symbol Definition (3)5. Models (4)5.1 Building of the Cellular automaton model (4)5.1.1 Verify the effectiveness of the keep right except to pass rule (4)5.1.2 Numerical simulation results and discussion (5)5.1.3 Conclusion (8)5.2 The solving of second question (8)5.2.1 The building of the stochastic multi-lane traffic model (9)5.2.2 Conclusion (9)5.3 Taking the an intelligent vehicle system into a account (9)5.3.1 Introduction of the Intelligent Vehicle Highway Systems (9)5.3.2 Control problem (9)5.3.3 Results and analysis (9)5.3.4 The comprehensive analysis of the result (10)6. Improvement of the model (11)6.1 strength and weakness (11)6.1.1 Strength (11)6.1.2 Weakness (11)6.2 Improvement of the model (11)7. Reference (13)1. IntroductionAs is known to all, it’s essential for us to drive automobiles, thus the driving rules is crucial important. In many countries like USA, China, drivers obey the rules which called “The Keep-Right-Except-To-Pass (that is, when driving automobiles, the rule requires drivers to drive in the right-most unless theyare passing another vehicle)”.2. Analysis of the problemFor the first question, we decide to use the Cellular automaton to build models,then analyze the performance of this rule in light and heavy traffic. Firstly,we mainly use the vehicle density to distinguish the light and heavy traffic; secondly, we consider the traffic flow and safe as the represent variable which denotes the light or heavy traffic; thirdly, we build and analyze a Cellular automaton model; finally, we judge the rule through two different driving rules,and then draw conclusions.3. AssumptionIn order to streamline our model we have made several key assumptions●The highway of double row three lanes that we study can representmulti-lane freeways.●The data that we refer to has certain representativeness and descriptive●Operation condition of the highway not be influenced by blizzard oraccidental factors●Ignore the driver's own abnormal factors, such as drunk driving andfatigue driving●The operation form of highway intelligent system that our analysis canreflect intelligent system●In the intelligent vehicle system, the result of the sampling data hashigh accuracy.4. Symbol Definitioni The number of vehiclest The time5. ModelsBy analyzing the problem, we decided to propose a solution with building a cellular automaton model.5.1 Building of the Cellular automaton modelThanks to its simple rules and convenience for computer simulation, cellular automaton model has been widely used in the study of traffic flow in recent years. Let )(t x i be the position of vehicle i at time t , )(t v i be the speed of vehicle i at time t , p be the random slowing down probability, and R be the proportion of trucks and buses, the distance between vehicle i and the front vehicle at time t is:1)()(1--=-t x t x gap i i i , if the front vehicle is a small vehicle.3)()(1--=-t x t x gap i i i , if the front vehicle is a truck or bus.5.1.1 Verify the effectiveness of the keep right except to pass ruleIn addition, according to the keep right except to pass rule, we define a new rule called: Control rules based on lane speed. The concrete explanation of the new rule as follow:There is no special passing lane under this rule. The speed of the first lane (the far left lane) is 120–100km/h (including 100 km/h);the speed of the second lane (the middle lane) is 100–80km8/h (including80km/h);the speed of the third lane (the far right lane) is below 80km/ h. The speeds of lanes decrease from left to right.● Lane changing rules based lane speed controlIf vehicle on the high-speed lane meets control v v <, ),1)(min()(max v t v t gap i f i +≥, safe b i gap t gap ≥)(, the vehicle will turn into the adjacent right lane, and the speed of the vehicle after lane changing remains unchanged, where control v is the minimum speed of the corresponding lane.● The application of the Nasch model evolutionLet d P be the lane changing probability (taking into account the actual situation that some drivers like driving in a certain lane, and will not takethe initiative to change lanes), )(t gap f i indicates the distance between the vehicle and the nearest front vehicle, )(t gap b i indicates the distance between the vehicle and the nearest following vehicle. In this article, we assume that the minimum safe distance gap safe of lane changing equals to the maximum speed of the following vehicle in the adjacent lanes.Lane changing rules based on keeping right except to passIn general, traffic flow going through a passing zone (Fig. 5.1.1) involves three processes: the diverging process (one traffic flow diverging into two flows), interacting process (interacting between the two flows), and merging process (the two flows merging into one) [4].Fig.5.1.1 Control plan of overtaking process(1) If vehicle on the first lane (passing lane) meets ),1)(min()(max v t v t gap i f i +≥ and safe b i gap t gap ≥)(, the vehicle will turn into the second lane, the speed of the vehicle after lane changing remains unchanged.5.1.2 Numerical simulation results and discussionIn order to facilitate the subsequent discussions, we define the space occupation rate as L N N p truck CAR ⨯⨯+=3/)3(, where CAR N indicates the number ofsmall vehicles on the driveway,truck N indicates the number of trucks and buses on the driveway, and L indicates the total length of the road. The vehicle flow volume Q is the number of vehicles passing a fixed point per unit time,T N Q T /=, where T N is the number of vehicles observed in time duration T .The average speed ∑∑⨯=T it i a v T N V 11)/1(, t i v is the speed of vehicle i at time t . Take overtaking ratio f p as the evaluation indicator of the safety of traffic flow, which is the ratio of the total number of overtaking and the number of vehicles observed. After 20,000 evolution steps, and averaging the last 2000 steps based on time, we have obtained the following experimental results. In order to eliminate the effect of randomicity, we take the systemic average of 20 samples [5].Overtaking ratio of different control rule conditionsBecause different control conditions of road will produce different overtaking ratio, so we first observe relationships among vehicle density, proportion of large vehicles and overtaking ratio under different control conditions.(a) Based on passing lane control (b) Based on speed control Fig.5.1.3Fig.5.1.3 Relationships among vehicle density, proportion of large vehicles and overtaking ratio under different control conditions.It can be seen from Fig. 5.1.3:(1) when the vehicle density is less than 0.05, the overtaking ratio will continue to rise with the increase of vehicle density; when the vehicle density is larger than 0.05, the overtaking ratio will decrease with the increase of vehicle density; when density is greater than 0.12, due to the crowding, it willbecome difficult to overtake, so the overtaking ratio is almost 0.(2) when the proportion of large vehicles is less than 0.5, the overtaking ratio will rise with the increase of large vehicles; when the proportion of large vehicles is about 0.5, the overtaking ratio will reach its peak value; when the proportion of large vehicles is larger than 0.5, the overtaking ratio will decrease with the increase of large vehicles, especially under lane-based control condition s the decline is very clear.● Concrete impact of under different control rules on overtaking ratioFig.5.1.4Fig.5.1.4 Relationships among vehicle density, proportion of large vehicles and overtaking ratio under different control conditions. (Figures in left-hand indicate the passing lane control, figures in right-hand indicate the speed control. 1f P is the overtaking ratio of small vehicles over large vehicles, 2f P is the overtaking ratio of small vehicles over small vehicles, 3f P is the overtaking ratio of large vehicles over small vehicles, 4f P is the overtaking ratio of large vehicles over large vehicles.). It can be seen from Fig. 5.1.4:(1) The overtaking ratio of small vehicles over large vehicles under passing lane control is much higher than that under speed control condition, which is because, under passing lane control condition, high-speed small vehicles have to surpass low-speed large vehicles by the passing lane, while under speed control condition, small vehicles are designed to travel on the high-speed lane, there is no low- speed vehicle in front, thus there is no need to overtake.● Impact of different control rules on vehicle speedFig. 5.1.5 Relationships among vehicle density, proportion of large vehicles and average speed under different control conditions. (Figures in left-hand indicates passing lane control, figures in right-hand indicates speed control.a X is the average speed of all the vehicles, 1a X is the average speed of all the small vehicles, 2a X is the average speed of all the buses and trucks.).It can be seen from Fig. 5.1.5:(1) The average speed will reduce with the increase of vehicle density and proportion of large vehicles.(2) When vehicle density is less than 0.15,a X ,1a X and 2a X are almost the same under both control conditions.Effect of different control conditions on traffic flowFig.5.1.6Fig. 5.1.6 Relationships among vehicle density, proportion of large vehicles and traffic flow under different control conditions. (Figure a1 indicates passing lane control, figure a2 indicates speed control, and figure b indicates the traffic flow difference between the two conditions.It can be seen from Fig. 5.1.6:(1) When vehicle density is lower than 0.15 and the proportion of large vehicles is from 0.4 to 1, the traffic flow of the two control conditions are basically the same.(2) Except that, the traffic flow under passing lane control condition is slightly larger than that of speed control condition.5.1.3 ConclusionIn this paper, we have established three-lane model of different control conditions, studied the overtaking ratio, speed and traffic flow under different control conditions, vehicle density and proportion of large vehicles.5.2 The solving of second question5.2.1 The building of the stochastic multi-lane traffic model5.2.2 ConclusionOn one hand, from the analysis of the model, in the case the stress is positive, we also consider the jam situation while making the decision. More specifically, if a driver is in a jam situation, applying ))(,2(x P B R results with a tendency of moving to the right lane for this driver. However in reality, drivers tend to find an emptier lane in a jam situation. For this reason, we apply a Bernoulli process )7.0,2(B where the probability of moving to the right is 0.7and to the left otherwise, and the conclusion is under the rule of keep left except to pass, So, the fundamental reason is the formation of the driving habit.5.3 Taking the an intelligent vehicle system into a accountFor the third question, if vehicle transportation on the same roadway was fully under the control of an intelligent system, we make some improvements for the solution proposed by us to perfect the performance of the freeway by lots of analysis.5.3.1 Introduction of the Intelligent Vehicle Highway SystemsWe will use the microscopic traffic simulator model for traffic simulation purposes. The MPC traffic controller that is implemented in the Matlab needs a traffic model to predict the states when the speed limits are applied in Fig.5.3.1. We implement a METANET model for prediction purpose[14].5.3.2 Control problemAs a constraint, the dynamic speed limits are given a maximum and minimum allowed value. The upper bound for the speed limits is 120 km/h, and the lower bound value is 40 km/h. For the calculation of the optimal control values, all speed limits are constrained to this range. When the optimal values are found, they are rounded to a multiplicity of 10 km/h, since this is more clear for human drivers, and also technically feasible without large investments.5.3.3 Results and analysisWhen the density is high, it is more difficult to control the traffic, since the mean speed might already be below the control speed. Therefore, simulations are done using densities at which the shock wave can dissolve without using control, and at densities where the shock wave remains. For each scenario, five simulations for three different cases are done, each with a duration of one hour. The results of the simulations are reported in Table 5.1, 5.2, 5.3. Table.5.1 measured results for the unenforced speed limit scenariodem q case#1 #2 #3 #4 #5 TTS:mean(std ) TPN 4700no shock 494.7452.1435.9414.8428.3445.21(6.9%) 5:4wave 3 5 8 8 0 14700nocontrolled520.42517.48536.13475.98539.58517.92(4.9%)6:364700 controlled 513.45488.43521.35479.75-486.5500.75(4.0%)6:244700 no shockwave493.9472.6492.78521.1489.43493.96(3.5%)6:034700 uncontrolled635.1584.92643.72571.85588.63604.84(5.3%)7:244700 controlled 575.3654.12589.77572.15586.46597.84(6.4%)7:19●Enforced speed limits●Intelligent speed adaptationFor the ISA scenario, the desired free-flow speed is about 100% of the speed limit. The desired free-flow speed is modeled as a Gaussian distribution, with a mean value of 100% of the speed limit, and a standard deviation of 5% of the speed limit. Based on this percentage, the influence of the dynamic speed limits is expected to be good[19].5.3.4 The comprehensive analysis of the resultFrom the analysis above, we indicate that adopting the intelligent speed control system can effectively decrease the travel times under the control of an intelligent system, in other words, the measures of dynamic speed control can improve the traffic flow.Evidently, under the intelligent speed control system, the effect of the dynamic speed control measure is better than that under the lane speed control mentioned in the first problem. Because of the application of the intelligent speed control system, it can provide the optimal speed limit in time. In addition, it can guarantee the safe condition with all kinds of detection device and the sensor under the intelligent speed system.On the whole, taking all the analysis from the first problem to the end into a account, when it is in light traffic, we can neglect the factor of safe with the help of the intelligent speed control system.Thus, under the state of the light traffic, we propose a new conclusion different from that in the first problem: the rule of keep right except to pass is more effective than that of lane speed control.And when it is in the heavy traffic, for sparing no effort to improve the operation efficiency of the freeway, we combine the dynamical speed control measure with the rule of keep right except to pass, drawing a conclusion that the application of the dynamical speed control can improve the performance ofthe freeway.What we should highlight is that we can make some different speed limit as for different section of road or different size of vehicle with the application of the Intelligent Vehicle Highway Systems.In fact, that how the freeway traffic operate is extremely complex, thereby, with the application of the Intelligent Vehicle Highway Systems, by adjusting our solution originally, we make it still effective to freeway traffic.6. Improvement of the model6.1 strength and weakness6.1.1 Strength●it is easy for computer simulating and can be modified flexibly to consideractual traffic conditions ,moreover a large number of images make the model more visual.●The result is effectively achieved all of the goals we set initially, meantimethe conclusion is more persuasive because of we used the Bernoulli equation.●We can get more accurate result as we apply Matlab.6.1.2 Weakness●The relationship between traffic flow and safety is not comprehensivelyanalysis.●Due to there are many traffic factors, we are only studied some of the factors,thus our model need further improved.6.2 Improvement of the modelWhile we compare models under two kinds of traffic rules, thereby we come to the efficiency of driving on the right to improve traffic flow in some circumstance. Due to the rules of comparing is too less, the conclusion is inadequate. In order to improve the accuracy, We further put forward a kinds of traffic rules: speed limit on different type of cars.The possibility of happening traffic accident for some vehicles is larger, and it also brings hidden safe troubles. So we need to consider separately about different or specific vehicle types from the angle of the speed limiting in order to reduce the occurrence of traffic accidents, the highway speed limit signs is in Fig.6.1.Fig .6.1Advantages of the improving model are that it is useful to improve the running condition safety of specific type of vehicle while considering the difference of different types of vehicles. However, we found that the rules may be reduce the road traffic flow through the analysis. In the implementation it should be at the 85V speed of each model as the main reference basis. In recent years, the 85V of some researchers for the typical countries from Table 6.1[ 21]: Table 6.1 Operating speed prediction modeAuthorCountry Model Ottesen andKrammes2000America LC DC L DC V C ⨯---=01.0012.057.144.10285Andueza2000Venezuel a ].[308.9486.7)/894()/2795(25.9885curve horizontal L DC Ra R V T ++--= ].[tan 819.27)/3032(69.10085gent L R V T +-= Jessen2001 America ][00239.0614.0279.080.86185LSD ADT G V V P --+=][00212.0432.010.7285NLSD ADT V V P -+=Donnell2001 America 22)2(8500724.040.10140.04.78T L G R V --+=22)3(85008369.048.10176.01.75T L G R V --+= 22)4(8500810.069.10176.05.74T L G R V --+=22)5(8500934.008.21.83T L G V --=BucchiA.BiasuzziK.And SimoneA.2005Italy DC V 124.0164.6685-= DC E V 4.046.3366.5585--= 2855.035.1119.0745.65DC E DC V ---= Fitzpatrick America KV 98.17507.11185-= Meanwhile, there are other vehicles driving rules such as speed limit in adverseweather conditions. This rule can improve the safety factor of the vehicle to some extent. At the same time, it limits the speed at the different levels.7. Reference[1] M. Rickert, K. Nagel, M. Schreckenberg, A. Latour, Two lane traffi csimulations using cellular automata, Physica A 231 (1996) 534–550.[20] J.T. Fokkema, Lakshmi Dhevi, Tamil Nadu Traffi c Management and Control inIntelligent Vehicle Highway Systems,18(2009).[21] Yang Li, New Variable Speed Control Approach for Freeway. (2011) 1-66。

美赛论文模板

美赛论文模板

T eam Control NumberFor office use only0000For office use onlyT1 F1T2 F2T3 Problem Chosen F3T4 A F42014 Mathematical Contest in Modeling (MCM) Summary Sheet(Attach a copy of this page to each copy of your solution paper.)Repeaters Coordination And DistributionFebruary 6,2015AbstractIn this paper, it aims to computing problem on Relay Strategy (repeaters coordination and distribution). According to advanced radio cellular coverage technology, usage of frequency attenuation and geometric mapping methods, Hata model, cellular coverage solution and FDM (Frequency Division Multiplexing) model were established. The algorithms used MATLAB to simulate, with the final modeling results of sensitivity analysis and improvement & promotion on models.Question one : For a circular flat area of radius 40 miles radius, determine the minimum number of repeaters necessary to accommodate 1,000 simultaneous users. Assume that the spectrum available is 145 to 148 MHz, the transmitter frequency in a repeater is either 600 kHz above or 600 kHz below the receiver frequency, and there are 54 different PL tones available.Answer:1. Based on Frequency attenuation expression and calculation with MATLAB, it figuredout the eligible coverage radiuses, which are 30km for BS (base station), and 14.9km for repeater.2. Assuming the users in a given area under uniform distribution, using advancedcellular coverage solution, we can calculate that minimum number of required repeater is 36 under cellular features.3. Based on the US VHF spectrum allocation standard, the minimum spacing for adjacentchannels is 30kHz. And with up to 54 different PL tones, maximum 4320 channels can be allocated to provide 1000 simultaneous users to use at the same time. Conclusion:The minimum number of repeaters necessary to accommodate 1,000 simultaneous users is 36.Question Two : How does your solution change if there are 10,000 users?Answer:1. Since the given spectrum is in a fixed range, even if 54 different PL tones can not be allocated enough channels for 10,000 simultaneous users. So the number of repeaters will be increased, meanwhile, the given area will be divided into different parts.2. On the assumption that uniform distribution of the population in the given area, it will be divided into 3 sub-regions equally by analyzing the binding domain, frequency spectrum and PL tones three independent factors. And then the number of repeaters within each sub-region will be classified discussion.3. The FDM (Frequency Division Multiplexing) model is established here to improve channel efficiency to accommodate up to 10,000 simultaneous users Conclusion:The minimum number of repeaters necessary to accommodate 10,000 simultaneous users is 126.Question Three : Discuss the case where there might be defects in line-of-sight propagation caused by mountainous areas. Answer:Basically, under the same condition for question 1&2, the mountainous area will be analyzed as following:1. The function for relationship between radio attenuation x caused by obstacles and the eligible coverage radius d for repeater is 2249.354371.4110x d -=, which is to analyze the impact on the number of repeaters under full signal coverage. 2. For the mountain barrier, based on the different situation of mountains, the addition of repeaters on the suitable location will be discussed to achieve full coverage. This paper describes model established by using of cellular coverage technology and frequency attenuation expression, to achieve simple, fast, accurate algorithm. And also illustrated the effect takes the entire article. In the end, the sensitivity analysis and error calculation are applied for modeling, making the model practically.Key words: Cellular Coverage technology, frequency attenuation expression, channel allocation, MatlabRepeaters coordination and distributionContent1 Restatement of the Problem (1)1.1 Introduction (1)1.2 The Problem (1)2 Simplifying Assumption (1)3 Phrase explain (1)4 Model (2)4.1 Model I (2)4.1.1 Analysis of the Problem (2)4.1.2 Model Design (2)5 Sensitivity analysis (2)6 Model extension (2)7 Evaluating our model (2)7.1 The strengths of model (2)7.2 The weaknesses of model (2)References (3)1 Restatement of the Problem1.1 IntroductionThe VHF radio spectrum involves line-of-sight transmission and reception. This limitation can be overcome by “repeaters,” which pick up weak signals, amplify them, and retransmit them on a different frequency. Thus, using a repeater, low-power users (such as mobile stations) can communicate with one another in situations where direct user-to-user contact would not be possible. However, repeaters can interfere with one another unless they are far enough apart or transmit on sufficiently separated frequencies.1.2 The ProblemYour job is to:◆Design a scheme that determines the minimum number of repeaters necessaryto accommodate 1,000 simultaneous users in a circular flat area of radius40 miles radius.And assume that the spectrum available is 145 to 148 MHz,the transmitter frequency in a repeater is either 600 kHz above or 600 kHz below the receiver frequency, and there are 54 different PL tones available.◆Change your scheme to accommodate 1,0000 simultaneous users base on yourmodel.◆Discuss the case where there might be defects in line-of-sight propagationcaused by mountainous areas.2 Simplifying Assumption3 Phrase explain4 Model4.1 Model I4.1.1 Analysis of the Problem4.1.2 Model Design5 Sensitivity analysisSymbol◆N: the number of total repeaters in the circle area ◆Q: the number of the users in the circle area◆k: the number of the red circle in figure 2最前面最好有一个Symbol List6 Model extension7 Evaluating our model7.1 The strengths of model7.2 The weaknesses of modelReferences参考文献不要引用非常差的期刊的论文,要引用比较厉害的英文期刊,证明你有足够的阅读文献量。

美国大学生数学建模比赛的论文格式

美国大学生数学建模比赛的论文格式

ContentsⅠIntroduction (1)1.1Problem Background (1)1.2Previous Research (2)1.3Our Work (2)ⅡGeneral Assumptions (3)ⅢNotations and Symbol Description (3)3.1 Notations (4)3.2 Symbol Description (4)ⅣSpread of Ebola (5)4.1 Traditional Epidemic Model (5)4.1.1.The SEIR Model (5)4.1.2 (6)4.1.3 (6)4.2 Improved Model (7)4.2.1.The SEIHCR Model (8)4.2.2 (9)ⅤPharmaceutical Intervention (9)5.1 Total Quantity of the Medicine (10)5.1.1.Results from WHO Statistics (10)5.1.2.Results from SEIHCR Model (11)5.2 Delivery System (12)5.2.1.Locations of Delivery (13)5.2.2 (14)5.3 Speed of Manufacturing (15)ⅥOther Important Interventions (16)6.1 Safer Treatment of Corpses (17)6.2 Conclusion (18)ⅦControl and Eradication of Ebola (19)7.1 How Ebola Can Be Controlled (20)7.2 When Ebola Will Be Eradicated (21)ⅧSensitivity Analysis (22)8.1 Impact of Transmission Rate (23)8.2 Impact of the Incubation Priod (24)ⅨStrengths and Weaknesses (25)9.1 Strengths (26)9.2 Weaknesses (27)9.3 Future Work (28)Letter to the World Medical Association (30)References (31)ⅠIntroduction1.1.Promblem Background1.2.Previous Research1.3.Our WorkⅡGeneral Assumptions●●ⅢNotations and Symbol Description3.1. Notataions3.2. Symbol DescriptionSymbol DescriptionⅣSpread of Ebola4.1. Traditional Epidemic Model4.1.1. The SEIR Model4.1.2. Outbreak Data4.1.3. Reslts of the SEIR Model4.2. Improved Model4.2.1. The SEIHCR Model4.2.2. Choosing paametersⅤPharmaceutical Intervention 5.1. Total Quantity of the Medicine 5.1.1. Results from WHO Statistics5.2. Delivery System5.2.1. Locations of Delivery5.2.2. Amount of Delivery5.3. Speed of Manufacturong5.4. Medicine EfficacyⅥOther Important Interventions 6.1. Safer Treatment of Corpses6.2. ConclusionⅦControl and Eradication of Ebola 7.1. How Ebola Can Be Controlled7.2. When Ebola Will Be EradicatedⅧSensitivity Analysis8.1. Impact of Transmission Rate8.2. Impact of Incubation PeriodⅨStrengths and Weaknesses 9.1. Strengths●●●9.2. Weaknesses●●●9.3.Future WorkLetter to the World Medical AssociationTo whom it may concern,Best regards,Team #32150References [1][2][3][4]。

latex,中文论文模板

latex,中文论文模板

竭诚为您提供优质文档/双击可除latex,中文论文模板篇一:一个简单的latexcjk论文模板一个简单的latex+cjk论文模板作者:于江生(北京大学计算机系)声明:允许未经作者的同意进行非商业目的的转载,但必须保持原文的完整性。

--------------------------------------------------------------------------------中文tex使用者一般的选择是在windows下用ctex,在unix下用tetex+latex-cjk。

cjk是德国人wernerlemberg 研发的,和几乎所有的宏包都能“和平相处”。

下面介绍一个简单的latex+cjk论文模板。

唯一要说明的是,命令\cjkcaption{gb}是实现章节标题的中文化,但是在Freebsd下用tetex编译通不过。

感谢aloft的贡献,他修改的gb.cpx真正实现了章节标题的中文化,使得\cjkcaption{gb}在unix和windows下都没有问题。

unix用户可以用aloft的gb.cpx替换/usr/local/share/texmf/tex/latex/cjk/gb/gb.cpx文件。

从一个简单的latex+cjk论文模板出发,你会发现用tex 写作是一件非常令人愉悦的事情。

以下模板在Freebsd下用tetex编译通过,在windows下用ctex也编译通过。

欢迎测试和使用,任何方面的改进都是鼓励的。

你可以对照本模板生成的pdf文件。

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%目的:latex+cjk中文论文模板%%%%文件:template4cjk.tex%%%%日期:10-01-20xx%%%%整理:于江生%%%%系统:Freebsd+tetex%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\iffalse%块注释如果要注释一块文字,用\iffalse...\fi界定住要注释的文字。

美赛论文模版(非常实用)

美赛论文模版(非常实用)

Title Abstract:Key words:Contents1. Introduction (3)1.1 Why does toll way collects toll? (3)1.2 Toll modes (3)1.3 Toll collection methods (3)1.4 Annoyance in toll plazas (3)1.5 The origin of the toll way problem (3)1.6 Queuing theory (4)2. The Description of Problem (5)2.1 How do we approximate the whole course of paying toll? (5)2.2 How do we define the optimal configuration? (5)2.2.1 From the perspective of motorist (5)2.2.2 From the perspective of the toll plaza (6)2.2.3 Compromise (6)2.3 Overall optimization and local optimization (6)2.4 The differences in weights and sizes of vehicles (7)2.5 What if there is no data available? (7)3. Models (7)3.1 Basic Model (7)3.1.1 Symbols and Definitions (7)3.1.2 Assumptions (8)3.1.3 The Foundation of Model (9)3.1.4 Solution and Result (11)3.1.5 Analysis of the Result (11)3.1.6 Strength and Weakness (13)3.2 Improved Model (14)3.2.1 Extra Symbols (14)3.2.2 Additional Assumptions (14)3.2.3 The Foundation of Model (14)3.2.4 Solution and Result (15)3.2.5 Analysis of the Result (18)3.2.6 Strength and Weakness (19)4. Conclusions (19)4.1 Conclusions of the problem (19)4.2 Methods used in our models (19)4.3 Application of our models (19)5. Future Work (19)5.1 Another model (19)5.2 Another layout of toll plaza (23)5.3 The newly- adopted charging methods (23)6.References (23)7.Appendix (23)Programs and codes (24)I. IntroductionIn order to indicate the origin of the toll way problems, the following background is worth mentioning.1.11.21.31.41.51.6II. The Description of the Problem2.1 How do we approximate the whole course of paying toll?●●●●2.2 How do we define the optimal configuration?1) From the perspective of motorist:2) From the perspective of the toll plaza:3) Compromise:2.3 The local optimization and the overall optimization●●●Virtually:2.4 The differences in weights and sizes of vehicles2.5 What if there is no data available?III. Models3.1 Basic Model3.1.1 Terms, Definitions and SymbolsThe signs and definitions are mostly generated from queuing theory.●●●●●3.1.2 Assumptions●●●●●3.1.3 The Foundation of Model1) The utility function●The cost of toll plaza:●The loss of motorist:●The weight of each aspect:●Compromise:2) The integer programmingAccording to queuing theory, we can calculate the statistical properties as follows.3)The overall optimization and the local optimization●The overall optimization:●The local optimization:●The optimal number of tollbooths:3.1.4 Solution and Result1) The solution of the integer programming:2) Results:3.1.5 Analysis of the Result●Local optimization and overall optimization:●Sensitivity: The result is quite sensitive to the change of the threeparameters●Trend:●Comparison:3.1.6 Strength and Weakness●Strength: In despite of this, the model has proved that . Moreover, wehave drawn some useful conclusions about . T he model is fit for, such as●Weakness: This model just applies to . As we have stated, .That’sjust what we should do in the improved model.3.2 Improved Model3.2.1 Extra SymbolsSigns and definitions indicated above are still valid. Here are some extra signs and definitions.●●●●3.2.2 Additional Assumptions●●●Assumptions concerning the anterior process are the same as the Basic Model.3.2.3 The Foundation of Model1) How do we determine the optimal number?As we have concluded from the Basic Model,3.2.4 Solution and Result1) Simulation algorithmBased on the analysis above, we design our simulation arithmetic as follows.●Step1:●Step2:●Step3:●Step4:●Step5:●Step6:●Step7:●Step8:●Step9:2) Flow chartThe figure below is the flow chart of the simulation.3) Solution3.2.5 Analysis of the Result3.2.6 Strength and Weakness●Strength: The Improved Model aims to make up for the neglect of .The result seems to declare that this model is more reasonable than the Basic Model and much more effective than the existing design.●Weakness: . Thus the model is still an approximate on a large scale. Thishas doomed to limit the applications of it.IV. Conclusions4.1 Conclusions of the problem●●●4.2 Methods used in our models●●●4.3 Applications of our models●●●V. Future Work5.1 Another model5.1.1The limitations of queuing theory 5.1.25.1.35.1.41)●●●●2)●●●3)●●●4)5.2 Another layout of toll plaza5.3 The newly- adopted charging methodsVI. References[1][2][3][4]VII. Appendix。

美赛论某文LaTeX实用模板82728

美赛论某文LaTeX实用模板82728

\documentclass{icmmcm}\usepackage{url} % For formatting URLs and other web or % file references.\usepackage{mflogo} % Provides the METAFONT logo; you% won't need it for your report.\usepackage{graphicx} % For importing graphics.\usepackage{natbib}%%% Sample ICM/MCM Contest Submission%%%%%% Based on sample senior thesis document%%% Last modified by Jeremy Rouse%%% Summer 2000%%%%%% and on the LaTeX Hints document%%% created by C.M. Connelly <cmc@>%%% Copyright 2002-2012%%% ---------------%%% Local Command and Environment Definitions%%% If you have any local command or environment definitions, put them %%% here or in a separate style file that you load with \usepackage.% \newtheorem declarations\newtheorem{Theo1}{Theorem}\newtheorem{Theo2}{Theorem}[section]\newtheorem{Lemma}[Theo2]{Lemma}% Each of the above defines a new theorem environment.% Multiple theorems can be done in the same environment.% Theo2's number is defined by the subsection it's in.% Theo3 uses the same numbering counter and numbering system as% Theo2 (that's the meaning of [Theo2]).%%% You probably won't want any of the following commands, which are %%% here to allow various the names of commands, make examples typeset %%% properly, and so on. You can, of course, use them as examples for %%% your own user-defined commands.\newcommand{\bslash}{\symbol{'134}}%backslash\newcommand{\bsl}{{\texttt{\bslash}}}\newcommand{\com}[1]{\bsl\texttt{#1}\xspace}\newcommand{\file}[1]{\texttt{#1}\xspace}\newcommand{\pdftex}{PDF\tex}\newcommand{\pdflatex}{PDF\latex}\newcommand{\acronym}[1]{\textsc{#1}\xspace}\newcommand{\key}[1]{\textsf{\emph{#1}}\xspace}\newcommand{\class}[1]{\textsf{#1}\xspace}\newcommand{\package}[1]{\textsf{#1}\xspace}\newcommand{\env}[1]{\texttt{#1}\xspace}\newcommand{\prog}[1]{\texttt{#1}\xspace}\newcommand{\command}[1]{\texttt{\bsl{}#1}\xspace}\newcommand{\ctt}{\texttt{comp.text.tex}\xspace}\newcommand{\tex}{\TeX\xspace}\newcommand{\latex}{\LaTeX\xspace}%%% Note that the \xspace command comes from the xspace package. It %%% allows you type a command that inserts text without having to %%% worry about how you ``end'' that command.%%%%%% Without \xspace, you would need to end a command with a backslash %%% followed by a space or with an empty set of braces if you followed %%% the command with a space. For example,%%%%%% \foo is a very important algorithm.%%%%%% might produce%%%%%% The foobarbaz algorithmis a very important algorithm.%%%%%% whereas with the \xspace command, the same code would produce %%%%%% The foobarbaz algorithm is a very important algorithm.%%%%%% If you need to butt a command that produces text against a letter %%% of some sort -- say, to pluralize it -- you need to tell TeX %%% where your command name ends so that it expands the correct %%% macro. So you might do%%%%%% \bar{}s are very busy creatures.%%% TeX has an amazingly good hyphenation algorithm, but sometimes it %%% gets confused and needs some help.%%%%%% For words that only occur once or twice, you can insert hints%%% directly into your text, as in%%%%%% our data\-base system is one of the most complex ever devised %%%%%% For words that you use a lot, and that seem to keep ending up at %%% the end of a line, however, inserting the hints each time gets to %%% be a drag. You can use the \hyphenation command to globally tell %%% TeX where to hyphenate words it can't figure out on its own.\hyphenation{white-space}%%% End Local Command and Environment Definitions%%% ---------------%%% ---------------%%% Title Block\title{\latex Hints for ICM/MCM Contest Reports}%%% Which contest are you taking part in? (Just one!)\contest{ICM/MCM}%%% The question you answered. (Again, just the one.)\question{Report Sample}%%% Your Contest Team Control Number\team{21247}%%% A normal document would specify the author's name (and possibly %%% their affiliation or other information) in an \author command. %%% Because the ICM/MCM Contest rules specify that the names of the %%% team members, their advisor, and their institution should not %%% appear anywhere in the report, do *not* define an \author command.%%% Defining the \date command is optional. If you leave it blank, %%% your document will include the date that the file is typeset, in %%% the form ``Month dd, yyyy''.% \date{}%%% End Title Block%%% ---------------\begin{document}%%% ---------------%%% Summary\begin{summary}This document is meant to give you a quick introduction to \TeX\ and \LaTeX. It covers a lot of material, but still barely manages toscratch the surface. It should provide you with some inspirationand, I hope, with some useful code you can copy, modify, and use in your report.You should use the \file{blank-template.tex} file as a basis foryour report rather than this file. Be sure to change its name tosomething sensible (maybe your team control number), and to set the values of the \com{title}, \com{question}, and \com{team} commands to appropriate values.Good luck!\hfill{}-- Claire\end{summary}%%% End Summary%%% ---------------%%% ---------------%%% Print Title Block, Contents, et al.\maketitle\tableofcontents%%% Uncomment the following lines if you have figures or tables in %%% your report:\listoffigures\listoftables%%% End Print Title Block, Contents, et al.%%% ---------------\section{Introduction: What Is \latex?}%\label{sec:introduction}\latex is a tool that allows you to concentrate on your writing while taking advantage of the \tex typesetting system to producehigh-quality typeset documents.\latex's benefits include\begin{enumerate}\item Standardized document classes\item Structural frameworks for organizing documents\item Automatic numbering and cross-referencing of structural elements \item ``Floating'' figures and tables\item High-level programming interface for accessing \tex'stypesetting capabilities\item Access to \latex extensions through loading ``packages''\end{enumerate}\section{Structured Writing}%\label{sec:structured-writing}Like HTML,\footnote{HyperText Markup Language} \latex is a markup language rather than a \acronym{Wysiwyg}{}\footnote{What You See IsWhat You Get.} system. You write plain text files that use special \key{commands} and \key{environments} that govern the appearance and function of parts of your text in your final typeset document.\subsection{Document Classes}%\label{sec:document-classes}The general appearance of your document is determined by your choice of \key{document class}. Document classes also load \latex packages to provide additional functionality.\latex provides a number of basic classes, including \class{article}, \class{letter}, \class{report}, and \class{book}. There are also a large number of other document classes available, including\class{amsart} and \class{amsbook}, created by the American Mathematical Society and providing some additional mathematically useful structures and commands; \class{foils}, \class{prosper}, and\class{seminar}, which allow you to create ``slides'' for presentations; the math department's \class{thesis} class, for formatting senior theses; and many journal- or company-specificclasses that format your document to match the ``house style'' of a particular periodical or publisher.\subsection{Packages}%\label{sec:packages}%\label{sec:ctan}\latex packages, or \key{style files}, define additional commands and environments, or change the way that previously defined commands and environments work. By loading packages, you can change the fonts used in your document, write your document in a non-English language with a non-\acronym{Ascii} font encoding, include graphics, format program listings, add custom headers and footers to your document, and much more.A typical \tex installation includes hundreds of style files, and hundreds more are available from the Comprehensive \tex ArchiveNetwork (CTAN), at \url{/}.\subsection{Structural Commands}%\label{sec:structural-commands}\begin{table}\centering\begin{tabular}{ll}\topruleCommand & Notes \\\midrule\com{part} & \class{book} \& \class{report} only \\\com{chapter} &\class{book} \& \class{report} only \\\com{section} \\\com{subsection} \\\com{subsubsection} \\\com{paragraph} \\\com{subparagraph} \\\bottomrule\end{tabular}\caption[Structural commands in \latex]{Structural commands in \latex.}% \label{tab:structural-commands}\end{table}\latex provides a set of structural commands for defining sections of your document, as shown in Table~\ref{tab:structural-commands}.Note that the argument to structural commands are moving arguments (see Section~\ref{sec:fragile-commands}) because they can be reused in the table of contents or in page headers or footers. Structural commands can take an optional argument in which you specify nonfragile commands or a shorter version of the actual section title that fits. You'll generally know when you need to provide an optional argument by \TeX's behavior.\subsection{Labels and References}%\label{sec:labels-and-references}Sections are numbered automatically by \latex during typesetting. If you change your mind and decide that a subsection should be promoted to a section, or moved to the end of your document, the sections will be renumbered so that the numbers are consistent.Sections can also be \command{label}{}ed with a tag such as\begin{quote}\begin{verbatim}\section{Our Complicated Equations}%\label{sec:complicated-eqs}\end{verbatim}\end{quote}and referred to with a \command{ref} or \command{pageref} command, as in\begin{quote}\begin{verbatim}In Section~\ref{sec:complicated-eqs}, we pointed out...\end{verbatim}\end{quote}or\begin{quote}\begin{verbatim}On page~\pageref{fig:gordian-knot}, we illustrated...\end{verbatim}\end{quote}\latex substitutes the correct section number when typesetting yourdocument.The same commands can be used with numbered environments such as\env{equation}, \env{theorem}, and so forth.Use \emph{meaningful} labels---labeling a section as \texttt{sec12} may seem useful, but it will be confusing if you end up moving it to a different place in the document and its number changes to Section~34. It's also easier to remember what reference you want if you use a meaningful name.You may also want to impose some additional organization through the use of \emph{namespaces}, as I've done in this document. Rather than give different types of objects undistinguished labels, I precede section labels with \texttt{sec:}, equations with \texttt{eq:},figures with \texttt{fig:}, tables with \texttt{tab:}, and so on.Emacs with Aux\tex and Ref\tex gives you easy access to these labels, as do many other editors with \tex-specific features. It's much easier to find the particular label you're looking for if you have some additional information to help you. Adding the prefixes also reminds you of what text should precede the \com{ref} command.\subsection{Commands}\latex uses commands for changes that are very limited in scope (a few words) or are unlimited in scope (the rest of a document). For example, the commands\begin{quote}\begin{verbatim}\textbf{bold}\emph{italic (emphasized)}\textsf{sans serif}\end{verbatim}\end{quote}produce the following output in a typeset document:\begin{quote}\textbf{bold} \emph{italic (emphasized)} \textsf{sans serif}\end{quote}These are ``commands with arguments''---the command itself starts with a backslash (\bsl), and its \key{argument} appears inside braces{\verb+{ }+). Some commands may also have \key{optional arguments},which are typed inside brackets (\verb+[ ]+).There are also commands that take no arguments, such as\command{noindent}, \command{raggedright}, and \command{pagebreak}.You can define your own commands, as discussed inSection~\ref{sec:customization}.\subsection{Environments}%\label{sec:environments}\latex provides a number of \key{environments} that affect the appearance of text, and are generally used for more structurally significant purposes. For example, the commands listed above are typeset inside a \env{verbatim} environment typed inside a \env{quote} environment. Their results were typeset inside a \env{quote} environment.Environments use special commands to start and close---\command{begin} and \command{end}, followed by the name of the environment in braces, as in\begin{quote}\begin{verbatim}\begin{quote}``This is disgusting---I can't eat this. That arugala is sobitter\ldots{} It's like my algebra teacher on bread.''\flushright -- Julia Roberts in \emph{Full Frontal}\end{quote}\end{verbatim}\end{quote}producing\begin{quote}``This is disgusting---I can't eat this. That arugala is sobitter\ldots{} It's like my algebra teacher on bread.''\flushright -- Julia Roberts in \emph{Full Frontal}\end{quote}Some environments may take additional arguments in braces (required) or brackets (optional).Note that the order in which environments nest is extremely important. If you type an environment inside another environment, the inner environment must be \command{end}{}ed \emph{before} the secondenvironment is closed. It's also vitally important that you have an \command{end} line for each \command{begin} line, or \latex will complain.\subsubsection{The \env{document} Environment and the Preamble}%\label{sec:document-environment}The most important environment is the \env{document} environment, which encloses the \key{body} of your document. The code before the \command{begin}\verb+{document}+ line is called the \key{preamble}, and includes the all-powerful \command{documentclass} command, which loads a particular document class (seeSection~\ref{sec:document-classes}); optional \command{usepackage} commands, which load in additional \latex packages (seeSection~\ref{sec:packages}); and other setup commands, such asuser-defined commands and environments, counter settings, and so forth.I generally also include the commands defining the title, author, and date in my preambles, but other people include them just after\command{begin}\verb+{document}+, before the \command{maketitle} command, which creates the title block of your document.\subsubsection{Math Environments}%\label{sec:math-environments}One of the major hallmarks of \tex is its ability to typeset mathematical equations.The two primary ways of doing so are with the use of \key{inline} and \key{display math environments}. These environments are used sooften that there are shorthands provided for typing them. Inline math environments, such as $a^2 + b^2 = c^2$, can be typed as\begin{quote}\begin{verbatim}\begin{math}a^{2} + b^{2} = c^{2}\end{math}\end{verbatim}\end{quote}or\begin{quote}\begin{verbatim}$a^{2} + b^{2} = c^{2}$.\end{verbatim}\end{quote}Display math environments set your equation apart from your running text. They're generally used for more complicated expressions, such as\[f(x) = \int \left( \frac{x^2 + x^3}{1} \right)dx\]which can be typed as\begin{quote}\begin{verbatim}\begin{displaymath}f(x) = \int \left( \frac{x^2 + x^3}{1} \right)dx\end{displaymath}\end{verbatim}\end{quote}or\begin{quote}\begin{verbatim}\[f(x) = \int \left( \frac{x^2 + x^3}{1} \right)dx\]\end{verbatim}\end{quote}Generally, you'll want to use the \verb+$+ %$ <- fool font-lock-modedelimited form for inline math, and the \com{[} \com{]} form for display math environments. [Besides being easy to type, these forms are \key{robust}, which means that they can be used in \key{movingarguments}, elements that \tex may need to typeset in more than one place (such as a table of contents) or adjust (such as footnotes).]\paragraph{The \env{equation} Environment}%\label{sec:equation-environment}You'll probably want to use the \env{equation} environment for any formula you plan to refer to. \latex not only typesets the contents of an \env{equation} environment in display mode, it also numbers it, as in\begin{equation}\label{eq:myequation}f(x) = \int \left( \frac{x^2 + x^3}{1} \right)dx\end{equation}written as\begin{quote}\begin{verbatim}\begin{equation}\label{eq:myequation}f(x) = \int \left( \frac{x^2 + x^3}{1} \right)dx\end{equation}\end{verbatim}\end{quote}Note that you can refer to this formula asEquation~\ref{eq:myequation} with\begin{verbatim}\ref{eq:myequation}.\end{verbatim}\subsection{Fonts}%\label{sec:fonts}Generally you'll want to let \latex handle the fonts for you---Knuth's Computer Modern fonts are used by default, and include a wide range of variations that can cover most any use you can think of.If you want to get fancy (and portable; seeSection~\ref{sec:fuzzy-fonts}), you can use Type~1 PostScript fonts, such as Times, Palatino, Utopia, and so forth. These font sets are accessible with packages with names like \package{times},\package{palatino}, and \package{utopia}. There are others, aswell---a command such as \com{locate psnfss | grep sty} will find most of them.You can also get fonts from CTAN (see Section~\ref{sec:ctan}), both bitmap and Type 1. There's even support for TrueType fonts in some\TeX\ systems.\subsubsection{Font Commands}%\label{sec:font-commands}Most of your concern about fonts is probably related to what you're writing. You might want some \emph{emphasized} or \textbf{bold} textto stress a point or highlight a key term. Filenames might be set in \texttt{typewriter text} (although you should consider using the\package{url} package to help you out---by default, text set in typewriter text isn't hyphenated, which can lead to some unattractive line breaks).You can also set text in \textsf{sans serif} or \textsc{small caps}. Table~\ref{tab:font-commands} shows you some of the most commonly used font commands provided by \latex.\begin{table}[htbp]\centering\begin{tabular}{ll}\topruleCommand & Result\\\midrule\com{emph} & \emph{emphasized text}\\\com{textsf} & \textsf{sans-serif text}\\\com{texttt} & \texttt{typewriter text}\\\com{textbf} & \textbf{bold text}\\\com{textsc} & \textsc{small caps text}\\\com{textsl} & \textsl{slanted text}\\\com{textit} & \textit{italic text}\\\bottomrule\end{tabular}\caption[Commonly used font commands]{Commonly used font commands.} \label{tab:font-commands}\end{table}I recommend that you use \com{emph} in preference to \com{textit}, and use \com{textbf} sparingly. \com{emph} is a smarter command than\com{textit}---it switches back to the roman font when necessary. For example, \emph{She loved \emph{Scooby Doo}.} versus \textit{He loved \textit{Titanic}.}For complicated font changes, or for special font usages that you're typing a lot, creating a macro (Section~\ref{sec:customization}) is the way to go. I often just write, tossing in custom commands as I go, and waiting to define them until just before I compile the document.\subsection{Customization}%\label{sec:customization}The main advantage of using commands and environments is that they allow you to organize your writing. A useful side-effect is that you can change your mind about the way an element is typeset, and change all the appearances of that element in document by editing one piece of code. For example, in this document the names of environments have been set in ``typewriter text'', using a command I created called\command{env}, which is defined as\begin{quote}\begin{verbatim}\newcommand{\env}[1]{\texttt{#1}\xspace}\end{verbatim}\end{quote}All I have to do to make the names of all the environments in the document appear in sans-serif type instead is to change that one line to\begin{quote}\begin{verbatim}\newcommand{\env}[1]{\textsf{#1}\xspace}\end{verbatim}\end{quote}You can do the same with almost anything you can conceptualize---key terms, people's names (especially names of people fromnon-English-speaking countries), files, functions, and so on.\section{Mathematical Notation}%\label{sec:mathematical-notation}As we saw in Section~\ref{sec:math-environments}, math is typed into one of several kinds of math environments. Choose your environment based on the context and importance of the content. Any formula you plan to refer to should be typed in an \env{equation} environment (or a similar environment that supports labels).You should punctuate your mathematics as if the formulae were normal parts of English sentences. Reading them aloud is often a useful method for ensuring that you have all the commas in the right places. Where appropriate, you should also follow a displayed formula at the end of a sentence with a period.\subsection{Sums and Products}%\label{sec:sums-n-products}It's easy to typeset sums and products. For example,\begin{equation}f(n) = \sqrt[n]{\sum_{k=1}^{n} {n \choose k} f \left( n - k \right)},~\prod_{n=2}^{\infty} \frac{n^{3}-1}{n^{3}+1} = \frac{2}{3}.\end{equation}%%% The ~ in the equation puts a nonbreaking space (equivalent to an%%% interword space in text mode) between the two halves of the equation. %%%%%% Also, note that the use of the \choose command here causes the%%% amsmath package to issue the warning%%%%%% Package amsmath Warning: Foreign command \atopwithdelims;%%% (amsmath) \frac or \genfrac should be used instead %%% (amsmath) on input line 557.%%%%%% amsmath would prefer the use of the \binom command it supplies.\subsection{Matrices}%\label{sec:matrices}It's a little more difficult to create matrices, but not too bad:%%% In LaTeX, & is the alignment tab, and separates columns. \\ is the end of %%% line marker, and separates rows. The ccc denotes that there are three %%% columns. The array environment and the tabular environment are%%% more or less identical, so what goes here also applies to a table.%%%\begin{equation}\left[ \begin{array}{ccc}2 & 1 & 2\\1 & 0 & 2\\2 & 1 & 1\end{array} \right]\left[ \begin{array}{ccc}-2 & 1 & 2\\3 & -2 & -2\\1 & 0 & -1\end{array} \right] =\left[ \begin{array}{ccc}1 & 0 & 0\\0 & 1 & 0\\0 & 0 & 1\end{array} \right].\end{equation}\subsection{Symbols}%\label{sec:symbols}\LaTeX provides an enormous number of symbols. Additional packages (loaded with \com{usepackage}) may provide additional symbols and fonts.For example, $\mathbb{N}$, $\mathbb{Z}$, $\mathbb{Q}$, $\mathbb{R}$, and $\mathbb{C}$ require you to load the \package{amsfonts} package (which is automatically loaded by the \texttt{icmmcm} class). These symbols are generated by \com{mathbb}, which only works in math mode.Subscripts and superscripts are easy---\verb!$a_n$! produces $a_n$, and \verb!$x^2$! produces $x^2$. Ordinal numbers, such as$3^{\textrm{rd}}$, $n^{\textrm{th}}$, and so forth,\footnote{Somefonts may include their own ordinals that can be accessed withspecial commands.} can be produced with code like\verb!$3^{\textrm{rd}}$!, \verb!$n^{\textrm{th}}$!.Equation~\ref{eq:superscript} shows a formula with a superscript.\begin{equation}\label{eq:superscript}\int_{0}^{\pi} \, \cos^{2n+1} x \, {\rm d} x = 0 \qquad\forall \, n \in \mathbb{N}.\end{equation}Notice that \com{cos} produces a nice roman ``$\cos$'' within math mode. There are similar commands for common functions like \com{log}, \com{exp}, and so forth. More can be defined with the\com{DeclareMathOperator} command provided by the \package{amsmath} package.You can stack symbols over other symbols. In math formulas,\begin{equation}m\ddot{x} + \gamma\dot{x} + kx = 0,\end{equation}or to produce diacritical accents, as in\begin{quote}Paul Erd\H{o}s s'est reveill\'{e} t\^{o}t pour enseigner lefran\c{c}ais \`{a} son fr\`{e}re et sa s\oe{}ur.\end{quote}\LaTeX{} has lots of Greek letters and ellipses too, some of which are shown in Figure~\ref{fig:greek-symbols}.\begin{figure}\begin{center}\begin{equation}\sqrt{\left[\begin{array}{cccccc}\alpha & \beta & \gamma & \delta & \epsilon & \zeta \\\eta & \theta & \iota & \kappa & \lambda & \mu \\\nu & \xi & o & \rho & \pi & \sigma \\\tau & \upsilon & \phi & \chi & \psi & \omega \\\Gamma & \Delta & \Theta & \Lambda & \Xi & \Pi \\\Sigma & \Upsilon & \Phi & \Psi & \Omega & \varphi\\\cdots & \ldots & \vdots & \ddots & : & \cdot\end{array}\right ] }.\end{equation}\end{center}\caption[Greek letters and some symbols]{Greek letters and some symbols.}% \label{fig:greek-symbols}\end{figure}See \cite{gratzer-mil}, pp.~455--474, or \cite{kopka-daly-guide},pp.~123--127, for lists of the symbols available. Intext, you mightsee some of these symbols used as\begin{quote}The Strong Induction Principle asserts that if a statement holds forthe integers $1$,~$2$,\dots,~$n$, and if whenever it holds for $n =1$, \dots,~$k$ then it also holds for $n = k+1$, then the statementholds for the integers $1$,~$2$,~$3$, $\ldots\,$ Using thisPrinciple, it can be shown that $1+2+\cdots+n = n(n+1)/2$ for allpositive integers~$n$.\end{quote}Notice that in the lists of integers, the ellipsis was made using the\com{ldots} command, and that the periods were nicely spaced betweenthe commas. In the sum, the dots were made with \com{cdots} and were centered on the line. The \package{amsmath} package provides a``smart'' \com{dots} command that can generally get things right basedon the context.So, with \com{dots} alone, the previous examples come out as\begin{quote}$1$,~$2$,~\dots,~$n$\\$n = 1$, \dots,~$k$\\$1$,~$2$,~$3$, $\dots\,$\\$1+2+\dots+n = n(n+1)/2$\end{quote}The general $n \times n$ matrix can be typeset as follows:\begin{equation}\left[\begin{array}{cccc}a_{11} & a_{12} & \ldots & a_{1n}\\a_{21} & a_{22} & \ldots & a_{2n}\\\vdots & \vdots & \ddots & \vdots\\a_{n1} & a_{n2} & \ldots & a_{nn}\\\end{array}\right].\end{equation}A fine point: lists of numbers that you're using in a mathematical sense (as opposed to dates, numbers of objects, etc.) should be typed in math mode. For example, $341$, $541$, $561$, and $641$. The same numbers without math mode are 341, 541, 561, and 641. Depending on the fonts and packages that you're using, you may notice a little bit more space around the first set than the second. With some packages, numbers intext may be set using old-style figures by default, as in \oldstylenums{341}, \oldstylenums{541}, \oldstylenums{561}, and\oldstylenums{641}. %%% But without the \oldstylenums commands!\subsection{More Math}In Fourier analysis, we talk about the $z$-domain.If $a$ is an even number, then\[ a + \phi(a) < \frac{3 a}{2}, \]and\[ \sigma(a) > \frac{2^{\alpha+1}-1}{2^{\alpha}} \, a \geq \frac{3a}{2}, \]where $\alpha$ is the greatest power of 2 that divides $a$, $\phi(a)$ is the number of integers less than $a$ and relatively primeto $a$, and $\sigma(a)$ is the sum of the divisors of $a$ (including $1$ and $a$).。

american statistical latex模板

american statistical latex模板

american statistical latex模板以下是一个美国统计学会(American Statistical Association,ASA)使用的LaTeX模板的示例:```\documentclass[12pt]{article}% 导入所需的LaTeX宏包\usepackage{amsmath}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{graphicx}% 设置页面布局\usepackage[top=1in, bottom=1in, left=1in, right=1in]{geometry}% 设置页眉页脚\usepackage{fancyhdr}\pagestyle{fancy}\fancyhf{}\fancyhead[C]{American Statistical Association}\fancyfoot[C]{Page \thepage}% 设置标题格式\usepackage{titlesec}\titleformat{\section}{\normalfont\bfseries}{\thesection}{1em}{} \titleformat{\subsection}{\normalfont\bfseries}{\thesubsection}{1 em}{}% 设置参考文献格式\usepackage[round]{natbib}\bibliographystyle{plainnat}% 文档正文\begin{document}\title{Example Document Using the ASA LaTeX Template}\author{Author Name}\date{\today}\maketitle\section{Introduction}This is an example document using the American Statistical Association (ASA) LaTeX template. The template provides a basic structure for statistical papers, including sections for introduction, methods, results, and conclusions.\section{Methods}In this section, we describe the methods used in our study. We collected data from a random sample of individuals and performed a regression analysis to investigate the relationship between variables A and B.\section{Results}Our results show a significant positive correlation between variables A and B (p < 0.05). Figure \ref{fig:scatterplot} displays the scatterplot of the data.\begin{figure}[h]\centering\includegraphics[scale=0.5]{scatterplot.png}\caption{Scatterplot of variables A and B}\label{fig:scatterplot}\end{figure}\section{Conclusions}Based on our analysis, we conclude that there is a strong positive relationship between variables A and B. These findings have important implications for future research in this field.\section{References}\bibliography{references}\end{document}```这是一个基本的ASA模板,你可以根据自己的需要进行修改和定制。

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%% 本论文的排版主要参考了LaTeX2e插图指南(王磊), LaTeX2e用户手册, media的中文学位%% 论文宏包(CDT), happaytex的ORmain1.tex等文件以及ChinaTeX, CTeX论坛上的诸多贴子. %%% 本论文采用了Miktex2.2的方式在ChinaTeX.iso系统下得到了实现,其编译方式为%% latex(得到DVI文件)+dvips(得到PS文件)+ps2pdf(可得PDF文件).%%\documentclass[12pt]{article}%需要的一些宏包\usepackage{CJK} % 中文输入环境宏包\usepackage{titlesec,titletoc} % 配合命令在后面, 章节标题设置\usepackage{indentfirst} % 使首段首行缩进\usepackage{graphicx} % 插图宏包\usepackage{caption2} % 可以更改插图, 表格的标题样式\usepackage{subfigure} % 产生并列的子图或子表, 命令\subfigure, \subtable\usepackage{longtable} % 如果表格太长, 超过了一页时, 就可以试试longtable 宏包所定义的longtable 环境\usepackage{slashbox} % 在表格中绘制斜线\usepackage{fancyhdr} % 更改页眉的宏包, 并可在页眉插入图片\usepackage{times} % Times Roman + Helvetica + Courier\usepackage{amsmath} % 数学符号宏包AMS-LaTeX, 如下面的\overset需要此宏包%页面的设置\special{papersize=21cm,29.7cm} \setlength{\textwidth}{15cm}\setlength{\textheight}{23cm} \setlength{\evensidemargin}{0.46cm}\setlength{\oddsidemargin}{0.46cm} \setlength{\topmargin}{-1.84cm}\setlength{\headheight}{2.9cm} \setlength{\headsep}{0.4cm}%字号设置\newcommand{\chuhao}{\fontsize{42pt}{\baselineskip}\selectfont}\newcommand{\xiaochuhao}{\fontsize{36pt}{\baselineskip}\selectfont}\newcommand{\yihao}{\fontsize{26pt}{\baselineskip}\selectfont}\newcommand{\xiyihao}{\fontsize{24pt}{\baselineskip}\selectfont}\newcommand{\erhao}{\fontsize{22pt}{\baselineskip}\selectfont}\newcommand{\xiaoerhao}{\fontsize{18pt}{\baselineskip}\selectfont}\newcommand{\sanhao}{\fontsize{16pt}{\baselineskip}\selectfont}\newcommand{\xiaosanhao}{\fontsize{15pt}{\baselineskip}\selectfont}\newcommand{\sihao}{\fontsize{14pt}{\baselineskip}\selectfont}\newcommand{\xiaosihao}{\fontsize{12pt}{\baselineskip}\selectfont}\newcommand{\wuhao}{\fontsize{10.5pt}{\baselineskip}\selectfont}\newcommand{\xiaowuhao}{\fontsize{9pt}{\baselineskip}\selectfont}\newcommand{\liuhao}{\fontsize{7.5pt}{\baselineskip}\selectfont}\newcommand{\xiaoliuhao}{\fontsize{6.5pt}{\baselineskip}\selectfont}\newcommand{\qihao}{\fontsize{5.5pt}{\baselineskip}\selectfont}\newcommand{\bahao}{\fontsize{5pt}{\baselineskip}\selectfont}%页眉的设置, 要用到fancyhdr宏包\pagestyle{fancy} \fancyhead{} \fancyfoot{}\fancyhead[L]{\footnotesize Team \# 189}\fancyhead[R]{\footnotesize Page\ \thepage\ of\ 42}\fancypagestyle{plain}{%\fancyhead[L]{\footnotesize Team \# 189}\fancyhead[R]{\footnotesize Page\ \thepage\ of\ 42}}\setcounter{secnumdepth}{4}%更改\theparagraph的编号样式\makeatletter\renewcommand{\theparagraph}{\@arabic\c@paragraph}\makeatother%章节格式的设置\titleformat{\section}{\erhao\bf}{}{0em}{}[]\titleformat{\subsection}{\xiaoerhao\bf}{}{0em}{}[]\titleformat{\subsubsection}{\sanhao\bf}{}{0em}{}[]\titleformat{\paragraph}[hang]{\vspace*{0.5ex}\sihao\bf}{\hspace*{1em}\theparagraph)}{0.5em }{}[\vspace*{-0.5ex}]%更改插图的标题\renewcommand{\figurename}{\wuhao\bf\sf Figure}\renewcommand{\captionlabeldelim}{\ }%更改表格的标题\renewcommand{\tablename}{\wuhao\bf\sf Table}%更改图形或表格与其标题的间距\setlength{\abovecaptionskip}{10pt}\setlength{\belowcaptionskip}{10pt}%定义产生不浮动图形和表格的标题的命令\figcaption和\tabcaption\makeatletter\newcommand\figcaption{\def\@captype{figure}\caption}\newcommand\tabcaption{\def\@captype{table}\caption}\makeatother%自定义的可以调整粗细的水平线命令, 用于绘制表格, 调用格式\myhline{0.5mm}. \makeatletter\def\myhline#1{%\noalign{\ifnum0=`}\fi\hrule \@height #1 \futurelet\reserved@a\@xhline}\makeatother%第一层列表序号为带圈的阿拉伯数字\renewcommand{\labelenumi}{\textcircled{\arabic{enumi}}}%更改脚注设置\renewcommand{\thefootnote}{\fnsymbol{footnote}}\begin{document}\begin{CJK*}{GBK}{song}\CJKtilde\title{\bf\yihao Aviation Baggage Screening\\{\&} Flight Schedule}\author{}\date{}\maketitle\section{Introduction}Following the terrorist attacks on September 11, 2001, there isintense interest in improving the security screening process forairline passengers and their baggage. Airlines and airports areconsidered high-threat targets for terrorism, so aviation securityis crucial to the safety of the air-travelling public. Bombs andexplosives have been known to be introduced to aircraft by holdbaggage and cargo, carried on by passengers, and hidden withinaircraft supplies.At present To Screen or Not to Screen, that is a Hobson's choice.US Current laws mandate 100{\%} screening of all checked bags at the 429 passenger airports throughout the nation by explosive detection systems(EDS) by the end of the Dec 31 2003. However, because the manufacturers arenot able to produce the expected number of EDS required to meet the federal mandate, so it is significant to determine the correct number of devicesdeploy at each airport, and to take advantage of them effectively.The Transportation Security Administration (TSA) needs a complicatedanalysis on how to allocate limited device and how to best use them.Our paper contains the mathematical models to determine the number of EDSsand flight schedules for all airports in Midwest Region. We also discuss theETD devices as the additional security measures and the future developmentof the security systems.\section{Assumption and Hypothesis}\begin{itemize}\item The passengers who will get on the same airplane will arrive uniformly, namely the distribution is flat.\item The detection systems, both EDS and ETD, operate all the time during peak hour, except downtime.\item The airline checks the passengers randomly, according to its claim.\item The passengers, who are just landing and leave out, do not have to be checked through EDS or ETD.\item According to the literature, the aircraft loads approximately equal among the sets of departing flight during the peak hour.\item The landing flight did not affect the departure of the plane.\item Once a passenger arrives, he can go to EDS to be checked, except he has to wait in line.\item Once passengers finish screening, they can broad on the plane in no time.\item During peak hours, a set of flights departs at the same time every the same minutes.\item All the runways are used as much as possible during peak hours.\item The maximum number of the baggage is two, which a passenger can carry on plane. []\item The detection machine examines the bags at the same speed.\item EDS cannot make mistakes that it detect a normal object as an explosive.\end{itemize}\section{Variable and Definition}\begin{longtable}{p{100pt}p{280pt}}\caption{Variables}\\ %第一页表头的标题\endfirsthead %第一页的标题结束\caption{(continued)}\\ %第二页的标题\endhead %第二页的标题结束\hline\hline\textbf{Symbol}&\textbf{Description}\\\hline$n_{ij}$&The airplane number of the $i^{\mathrm{th}}$ type in the $j^{\mathrm{th}}$ flight set\\\hline${NP}_i\:(i=1,2,\ldots)$&The number of passengers on each airplanes of the same type.\\\hline$\xi_{ij}\:(i,j = 1,2,\cdots)$&The number of baggage on each airplane of the $j^{\mathrm{th}}$ flights\\\hline$a$&The maximal number of airplanes type\\\hline$B_j^{set}$&The total baggage number of each set of flight\\\hline${NF}_i$&Number of airplanes of each type\\\hline$\bar{\rho}$&The mean value of passengers' baggage coming per minute in every flight set\\ \hline$N_{set}$&The number of flight sets\\\hline$B_{total}$&The total number of checked baggage during the peak hour\\\hline$H_{peak}$&The length of the peak hour\\\hline$T_{set}$&The time length during which each flight set's passengers wait to be checked\\\hline$\Delta t$&The time interval between two consecutive flight set\\\hline$N_{EDS}$&The number of all the EDSs\\\hline$N_{shadow}$&The number of flight sets whose passengers will be mixed up before being checked\\\hline$v_{EDS}$&The number of baggage checking by one EDS per minute\\\hline$\rho_j$&The number of passengers' baggage coming per minute in one flight set\\\hline$N_{runway}$&The number of an airport's runway\\\hline\\*[-2.2ex]${\bar{B}}^{set}$&The mean value of checked baggage number of every flight set\\\hline$M$&The security cost\\\hline\hline\label{tab1}\end{longtable}\subsubsection{Definition:}\begin{description}\item[Flight set] A group of flights take off at the same time\item[The length of peak hour] The time between the first set of flight and the last set\end{description}\section{Basic Model}During a peak hour, many planes and many passengers would departfrom airports. Therefore, It is difficult to arrange for thepassengers to enter airports. If there are not enough EDSs forpassengers' baggage to check, it will take too long time for themto enter. That would result in the delay of airplanes. On thecontrary, if there are too many EDSs, it will be a waste. It isour task to find a suitable number of EDSs for airport. In orderto reach this objective, we use the linear programming method tosolve it.\subsection{Base analysis}The airplanes are occupied at least partly. The passengers'baggage would be checked by EDSs before they get on the airplanes.We have assumed that every passenger carry two baggages. Thisassumption would simplify the problem. According to the data fromthe problem sheet, we can obtain the useful information thatairlines claim 20{\%} of the passengers do not check any luggage,20{\%} check one bag, and the remaining passengers check two bags.Therefore, we can gain the total number of passengers' baggagethat should be carried on one plane: $\xi_{ij}$. Moreover, we canget the equation that calculate $\xi_{ij}$:\[\xi_{ij}={NP}_i\times 20\%+{NP}_i\times 60\%\times 2\]We define the matrix below as airplane baggage number matrix:\[\overset{\rightharpoonup}{\xi}_j=\left[\xi_{1j}\quad\xi_{2j}\quad\cdots\quad\xi_{ij}\quad\cdots\ right]\]We define the matrix below as flight schedule matrix:\[\left[\begin{array}{llcl}n_{11}&n_{12}&\cdots&n_{1N_{set}}\\n_{21}&n_{22}&\cdots&n_{2N_{set}}\\\multicolumn{4}{c}\dotfill\\n_{a1}&n_{a2}&\cdots&n_{aN_{set}}\end{array}\right]\]In this matrix, $n_{ij}$ is the airplane number of the$i^{\mathrm{th}}$ type in the $j^{\mathrm{th}}$ flight set whichwill take off. Apparently, this value is an integer.We define the matrix below as flight set baggage number matrix:\[\left[B_1^{set}\quad B_2^{set}\quad\cdots\quad B_j^{set}\quad\cdots\quad B_a^{set}\right] \]It is clear that they meet the relation below:\begin{equation}\begin{array}{cl}&\left[\xi_{1j}\quad\xi_{2j}\quad\cdots\quad\xi_{ij}\quad\cdots\right]\cdot\left[\begin{array}{llcl}n_{11}&n_{12}&\cdots&n_{1N_{set}}\\n_{21}&n_{22}&\cdots&n_{2N_{set}}\\\multicolumn{4}{c}\dotfill\\n_{a1}&n_{a2}&\cdots&n_{aN_{set}}\end{array}\right]\\=&\left[B_1^{set}\quad B_2^{set}\quad\cdots\quad B_j^{set}\quad\cdots\quad B_a^{set}\right]\end{array}\label{Flight:baggage}\end{equation}Then, we know:\[B_j^{set}=\sum\limits_{i=1}^a\xi_{ij}\times n_{ij}\]There are some constraints to the equation (\ref{Flight:baggage}).First, for each set of flight, the total number of airplanesshould be less than the number of runways. Second, the totalairplane number of the same type listed in the equation(\ref{Flight:baggage}) from every set of flight should be equal tothe actual airplane number of the same type during the peak hour.We can express them like these:\[\sum\limits_{i=1}^a n_{ij}\le N_{runway}\quad\quad\sum\limits_{j=1}^b n_{ij}={NF}_i \]We should resolve the number of flight sets. According to our assumptions,during the peak hour, the airlines should make the best use of the runways.Then get the number of flight sets approximately based on the number of allthe airplanes during the peak hour and that of the runways. We use anequation below to express this relation:\begin{equation}N_{set}=\left\lceil\frac{\sum\limits_{j=1}^{N_{set}}\sum\limits_{i=1}^an_{ij}}{N_{runway}}\right\rceil\label{sets:number}\end{equation}The checked baggage numbers of each flight set are equal to eachother according to our assumption. We make it based on literature.It can also simplify our model. We define $\bar{B}^{set}$ as themean value of checked baggage number of every flight set.Moreover, We define $\bar{\rho}$ as the mean value of checkedbaggage number of every flight set per minute:\[\bar{B}^{set}=\frac{B_{total}}{N_{set}}\]\[\bar{\rho}=\frac{\bar{B}^{set}}{T_{set}}=\frac{B_{total}}{T_{set}N_{set}}=\frac{B_{total}\ Delta t}{T_{set}H_{peak}}\]The course of passengers' arrival and entering airport isimportant for us to decide the number of EDSs and to make theflights schedule. Therefore, we should analyze this processcarefully. Passengers will arrive between forty-five minutes andtwo hours prior to the departure time, and the passengers who willget on the same airplane will arrive uniformly. Then we can getthe flow density of all checked baggage at any time duringpassengers' entering. This value is the sum of numbers ofpassengers' checked baggage coming per minute. To calculate thisvalue, firstly, we should obtain flow density of each flight set'schecked baggage. We define $\rho_j $, namely the number of checkedbaggage per minute of one flight set:\[\rho_j=\frac{B_j^{set}}{T_{set}}\]Secondly, we draw graphic to help us to understand. We userectangle to express the time length for all the passengers of oneflight set to come and check bags. In the graphic, the black partis the period for them to come. During the white part, nopassengers for this flight set come. According to the problemsheet, the former is 75 minute, and the latter is 45 minute. Thelength of rectangle is 120 minute. $T_{set}$ is the period duringwhich all passengers of one flight set wait to be checked. Sincewe have assumed that each time interval between two consecutiveflight set is same value, we define $\Delta t$ as it. Observe thesection that value we want to solve is $\sum\limits_j\rho_j$. Moreover, we can get another important equation from the graphic below:\begin{equation}N_{set}=\frac{H_{peak}}{\Delta t}\label{PeakHour}\end{equation}\begin{figure}[hbtp]\centering\includegraphics[width=298.2pt,totalheight=141.6pt]{fig01.eps}\caption{}\label{fig1}\end{figure}Each EDS has certain capacity. If the number of EDSs is $N_{EDS}$ and one EDS can check certain number of baggage per minute (Thatis checking velocity, marked by $v_{EDS}$), the total checking capacity is $N_{EDS}\cdot\frac{v_{EDS}}{60}$. $v_{EDS}$ is between 160 and 210.Now we can easily decide in what condition the passengers can be checked without delay:\[\sum\limits_j\rho_j\le v_{EDS}\]The passengers have to queue before being checked:$\sum\limits_j\rho_j>v_{EDS}$Well then, how can we decide how many $\rho_j$? It depends on how many flight sets whose passengers will be mixed up before being checked. We note it as $N_{shadow} $. Return to the Figure\ref{fig1}, we can know:\[N_{shadow}=\left\lfloor\frac{T_{set}}{\Delta t}\right\rfloor\]\begin{figure}%[htbp]\centering\includegraphics[width=240pt,totalheight=131.4pt]{fig02.eps}\caption{}\label{fig2}\end{figure}From Figure \ref{fig1} and Figure \ref{fig2}, we can get theresult as follows:\begin{enumerate}\item If $N_{shadow}\le N_{set}$, namely $H_{peak}>T_{set}$, then $\sum\limits_{j=1}^{N_{shadow}}\rho _j\le N_{EDS}\frac{v_{EDS}}{60}$\renewcommand{\theequation}{\arabic{equation}a}That is:\begin{equation}N_{EDS}\ge\frac{60}{v_{EDS}}\sum\limits_{j=1}^{N_{shadow}}\rho_j\approx\frac{60}{v_{ EDS}}N_{shadow}\bar{\rho}=\frac{60B_{total}\Deltat}{v_{EDS}T_{set}H_{peak}}N_{shadow}\label{EDS:number:a}\end{equation}\item If $N_{shadow}>N_{set}$, namely $H_{peak}\le T_{set}$, then $\sum\limits_{j=1}^{N_{set}}\rho_j\le N_{EDS}\frac{v_{EDS}}{60}$\setcounter{equation}{3}\renewcommand{\theequation}{\arabic{equation}b}That is:\begin{equation}N_{EDS}\ge\frac{60}{v_{EDS}}\sum\limits_{j=1}^{N_{set}}\rho_j\approx\frac{60}{v_{EDS} }N_{set}\bar{\rho}=\frac{60B_{total}\Delta t}{v_{EDS}T_{set}H_{peak}}N_{set}\label{EDS:number:b}\end{equation}\end{enumerate}\subsection{The number of EDSs}Then we begin to resolve the number of EDSs assisted by the linearprogramming method.EDS is operational about 92{\%} of the time. That is to say, whenever it isduring a peak hour, there are some EDSs stopping working. Then the workingefficiency of all the EDSs is less than the level we have expected.Therefore, the airline has to add more EDSs to do the work, which can bedone with less EDSs without downtime.We use binomial distribution to solve this problem. $N$ is the number ofactual EDSs with downtime and $k$ is the number of EDSs without downtime. Ifprobability is $P$, we can get the equation below:\[\left(\begin{array}{c}N\\k\end{array}\right)\cdot98\%^k\cdot(1-98\%)^{N-k}=P\]We can obtain $N$ when we give $P$ a certain value. In this paper,$P$ is 95{\%}. The $N_{EDS}$ is the actual number we obtainthrough the equation above.Now we have assumed that passengers can be checked unless be delayed by the people before him once he arrives at airport. Apparently, if the time length between two sets of flight is short, the density of passengers will begreat. It will bring great stress to security check and may even make some passengers miss their flight. To resolve this question, the airline has toinstall more EDSs to meet the demand. However, this measure will cost much more money. Consequently, we have to set a suitable time interval between two set of flight.Based on the base analysis above. We can use the equation(\ref{sets:number}) to decide the number of flight sets $N_{set}$assuming we know the number of runways of a certain airport. Thenbased on the equation (\ref{PeakHour}), we can decide the peakhour length $H_{peak}$ when we assume a time interval between two consecutive flight sets. Then we use \textcircled{1} and\textcircled{2} to decide which to choose between equation(\ref{EDS:number:a}) and equation (\ref{EDS:number:b}). In consequence, we can obtain the minimum of EDSs number.If we choose different numbers of runways and the time intervalsbetween two flight sets, we can get different EDSs numbers. Inthis paper that followed, we gain a table of some value of$N_{runway}$ and $\Delta t$ with the corresponding EDSs numbers. Moreover, we draw some figure to reflect their relation.For a certain airport, its number of runway is known. Givencertain time interval ($\Delta t$), we can get the length of thepeak hour ($H_{peak}$). When the $N_{runway}$ is few enough,perhaps $H_{peak}$ is too long to be adopted. However, for acertain airline, they can decide the time interval of their ownpeak hour. In this given time interval, they could find theminimum of $N_{runway}$ through the Figure \ref{fig3}. We draw asketch map to describe our steps.\begin{figure}[hbtp]\centering\includegraphics[width=352.8pt,totalheight=214.2pt]{fig03.eps}\caption{}\label{fig3}\end{figure}\subsection{The Flight Schedule }According to the base analysis, we can know that the flightschedule matrix and $\Delta t$ is one form of flight timetable. In``The number of EDSs'', we can get suitable $\Delta t$. Then weshould resolve the flight schedule matrix.Because we have assumed that the checked baggage numbers of each flight setare equal to each other. It can be described as follows:\[\left\{\begin{array}{l}\rho_j\approx\bar{\rho}\\B_j^{set}\approx\bar{B}^{set}\end{array}\right.\begin{array}{*{20}c}\hfill&{j=1,2,\cdots,N_{set}}\hfill\end{array}\]The flight schedule matrix subject to this group:\[\left\{\begin{array}{ll}\sum\limits_{j=1}^{N_{set}}n_{ij}={NF}_i&i=1,2,\cdots\\\sum\limits_{i=1}^a n_{ij}\le N_{runway}&j=1,2,\cdots,N_{set}\\n_{ij}\ge0,&\mathrm{and}\:n_{ij}\:\mathrm{is}\:\mathrm{a}\:\mathrm{Integer} \end{array}\right.\]In order to make the best use of runway, we should make$\sum\limits_{i=1}^a n_{ij}$ as great as we can unless it exceed$N_{runway}$.Then we can see that how to resolve the flight schedule matrix is a problemof divide among a group of integers. This group is all the numbers of eachflight passengers' baggage in one flight set. We program for this problemusing MA TLAB and we get at least one solution in the end. However, thematrix elements we have obtained are not integer, we have to adjust them tobe integers manually.\subsection{Results and Interpretation for Airport A and B}The number of passengers in a certain flight (${NP}_i$), the timelength of security checking ($T_{set}$), the checking velocity ofEDS ($v_{EDS}$), and the number of baggage carried by onepassenger are random.\subsubsection{Data Assumption:}\begin{itemize}\item $T_{set}$ is 110 minutes, which is reasonable for airline.\item To simplify the problem, we assume that every passenger carry 2 baggage. If some of thepassengers carry one baggage, the solution based on 2 baggages per passenger meets therequirement.\item The number of runways in airport A and airport B is 5.\end{itemize}\subsubsection{Airport A:}Once the number of runway and the number of the flights aredecided, the flight schedule matrix is decided, too. We producethis matrix using MATLAB. This matrix companied by $\Delta t$ isthe flight schedule for airport A. $\Delta t$ will be calculatedin (\ref{Flight:baggage}), (\ref{sets:number}) and(\ref{PeakHour}).We calculate $N_{EDS}$ and make the flight timetable in threeconditions. The three conditions and the solution are listed asfollowed:\paragraph{Every flight are fully occupied}The checking speed of EDS is 160 bags/hour.\begin{table}[htbp]\centering\caption{}\begin{tabular}{*{11}c}\myhline{0.4mm}$\mathbf{\Deltat(\min)}$&\textbf{2}&\textbf{4}&\textbf{6}&\textbf{8}&\textbf{10}&\textbf{12}&\textbf{14} &\textbf{16}&\textbf{18}&\textbf{20}\\\myhline{0.4mm}$N_{EDS}(\ge)$&31&31&31&31&31&29&24&22&20&17\\\hline$H_{peak}(\min)$&20&40&60&80&100&120&140&160&180&200\\\myhline{0.4mm}\end{tabular}\label{tab2}\end{table}We assume that the suitable value of $H_{peak}$ is 120 minutes.Then the suitable value of $\Delta t$ is about 12 minutes, and$N_{EDS}$ is 29 judged from Figure \ref{fig4}. Certainly, we canwork $\Delta t$ and $N_{EDS}$ out through equation.\begin{figure}[htbp]\centering\includegraphics[width=294.6pt,totalheight=253.2pt]{fig04.eps}\caption{}\label{fig4}\end{figure}\paragraph{Every flight is occupied by the minimal number of passengers onstatistics in the long run.}The checking speed of EDS is 210 bags/hour.\begin{table}[htbp]\centering\caption{}\begin{tabular}{*{11}c}\myhline{0.4mm}$\mathbf{\Deltat(\min)}$&\textbf{2}&\textbf{4}&\textbf{6}&\textbf{8}&\textbf{10}&\textbf{12}&\textbf{14} &\textbf{16}&\textbf{18}&\textbf{20}\\\myhline{0.4mm}$N_{EDS}(\ge)$&15&15&15&15&15&14&13&12&10&7\\\hline$H_{peak}(\min)$&20&40&60&80&100&120&140&160&180&200\\\myhline{0.4mm}\end{tabular}\label{tab3}\end{table}We assume that the suitable value of $H_{peak}$ is 120 minutes.Then the suitable value of $\Delta t$ is about 12 minutes, and$N_{EDS}$ is 14 judging from Figure \ref{fig5}. Certainly, we canwork $\Delta t$ and $N_{EDS}$ out through equation.\begin{figure}[htbp]\centering\includegraphics[width=294.6pt,totalheight=253.2pt]{fig05.eps}\caption{}\label{fig5}\end{figure}\paragraph{${NP}_i$ and $v_{EDS}$ are random value produced by MATLAB.}\begin{table}[htbp]\centering\caption{}\begin{tabular}{*{11}c}\myhline{0.4mm}$\mathbf{\Deltat(\min)}$&\textbf{2}&\textbf{4}&\textbf{6}&\textbf{8}&\textbf{10}&\textbf{12}&\textbf{14} &\textbf{16}&\textbf{18}&\textbf{20}\\\myhline{0.4mm}$N_{EDS}(\ge)$&15&22&21&21&15&17&21&16&13&14\\\hline$H_{peak}(\min)$&20&40&60&80&100&120&140&160&180&200\\\myhline{0.4mm}\end{tabular}\label{tab4}\end{table}We assume that the suitable value of $H_{peak}$ is 120 minutes.Then the suitable value of $\Delta t$ is about 12 minutes, and$N_{EDS}$ is 17 judging from Figure \ref{fig6}. Certainly, we canwork $\Delta t$ and $N_{EDS}$ out through equation.\begin{figure}[htbp]\centering\includegraphics[width=294.6pt,totalheight=249.6pt]{fig06.eps}\caption{}\label{fig6}\end{figure}\subsubsection{Interpretation:}By analyzing the results above, we can conclude that when$N_{EDS}$ is 29, and $\Delta t$ is 12, the flight schedule willmeet requirement at any time. The flight schedule is:\\[\intextsep]\begin{minipage}{\textwidth}\centering\tabcaption{}\begin{tabular}{c|*{8}c|c|c}\myhline{0.4mm}\backslashbox{\textbf{Set}}{\textbf{Type}}&\textbf{1}&\textbf{2}&\textbf{3}&\textbf{4}&\te xtbf{5}&\textbf{6}&\textbf{7}&\textbf{8}&\textbf{Numbers of Bags}&\textbf{Numbers of Flights}\\\myhline{0.4mm}1&2&0&0&0&2&1&0&0&766&5\\\hline2&2&0&2&0&2&0&0&0&732&4\\\hline3&0&1&1&1&2&0&0&0&762&4\\\hline4&0&1&0&0&2&1&0&0&735&4\\\hline5&0&1&0&0&2&1&0&0&735&5\\\hline6&2&0&0&0&1&0&0&1&785&5\\\hline7&2&0&0&0&2&0&1&0&795&5\\\hline8&0&1&0&0&2&1&0&0&735&4\\\hline9&2&0&0&0&2&1&0&0&766&5\\\hline10&0&0&0&2&2&0&0&0&758&5\\\hlineTotal&10&4&3&3&19&5&1&1&7569&46\\\myhline{0.4mm}\end{tabular}\label{tab5}\end{minipage}\\[\intextsep]We have produced random value for ${NP}_i$ and $v_{EDS}$. On thiscondition, the number of EDSs is 17, which is less than 29 that wedecide for the airport A. That is to say our solution can meet thereal requirement.\subsubsection{Airport B:}\paragraph{The passenger load is 100{\%}}The checking speed of EDS is 160 bags/hour.\begin{table}[htbp]\centering。

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