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如何仅将最后一条记录跨越两列

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如何仅将最后一条记录跨越两列

我使用的是横向表格，其中最后一条记录需要跨越两列（合并）。下面给出了 MWC、观察到的输出和期望的输出。

世界移动通信大会

\documentclass[twocolumn]{svjour3}
\usepackage[english]{babel}
\usepackage{tabularx}
\usepackage{booktabs}
\usepackage{rotating}
\setlength{\rotFPtop}{0pt plus 1fil}
\usepackage{makecell}
\renewcommand{\theadfont}{\bfseries}
\begin{document}
\begin{sidewaystable*}

\caption{Comparison among state of the art designs}
\label{tab:1}       % Give a unique label
\begin{tabularx}{\linewidth}{c
                             >{\raggedright\arraybackslash}p{0.85in}
                             >{\raggedright\arraybackslash}p{0.65in}
                             c
                             >{\raggedright\arraybackslash}p{0.75in}
                             c
                             c
                             >{\raggedright\arraybackslash}p{1.5in}
                             X}
\toprule
\thead{Reference}&\thead{Sensor\\type}&\thead{Sensor\\location}&\thead{No. of\\ sensors}&\thead{Processing\\location}&\thead{Method}&\thead{Accuracy\\in \%}&\thead{Features}&\thead{Limitations}\\
\midrule\\

[1]
  & Accelerometer, Gyroscope

    & External & $>1$ & On board & TB & Unknown
      & Fine grained fall detection with good accuracy.
        & No text based location, Fall and break of device aspect not considered.
\\
\addlinespace

[2]
  & Triaxial Accelerometer
    & External & 1 & On board and Remote
 & TB & Unknown
      &Fine grained fall detection with good accuracy. Reduced false alarm.
        &Device location in pocket of pant. No real life implementation case study. Fall and break aspect not considered.
\\
\addlinespace

[3]
  & Triaxial Accelerometer
    & External & $>1$ & On board and remote
 & ML & 91.83
      &Fall detection and ADL based on KNN classifier with accuracy  of 91.83\%
        &Store \& analyse, no live data, device fall is not considered. \\
\addlinespace

[4]
  &Camera
    & External & $>1$ & Remote
 & ML & Unknown
  & Image information is used for fall classification.
        &Slow, multiple image capturing device may be required, privacy issues.\\
\addlinespace

[5]
  & Triaxial Accelerometer
    & External & $>1$ & Remote
 & TB + ML & Unknown
      & Threshold analysis, reminder analysis and decision tree algorithm .
        & The non-functional aspect of the device after a fall is not considered.\\
\addlinespace

[6]
  & Pressure Sensor
    &Integrated in the operator's shoe & $>1$ & remote
 & TB & Unknown
      & Good result accuracy and can be implemented in IOT platform.
        & The nature of walking surface has a direct impact on accuracy.\\
\addlinespace

[7]
 & Accelerometer, Gyroscope
 &Smartphone in chest pocket & $>1$ & On board and remote
 & TB & Unknown
 & Smartphone Google API (location), Good accuracy.
 & Device location is not suitable for heart patient, Google API is not accurate in remote locations.\\
\addlinespace
[8]
 & MEMS tri-axis accelerometer
 &Upper trunk of the body & 1 & Remote
 & ML & Unknown
 & Fall detection and prediction using hidden Markov chain.
 & Location information as well as fall alike cases are not considered.\\
\addlinespace
[9]
 & UHF-RFID
 &Different locations inside the room & $>1$ & Remote
 &TB + ML & Unknown
 & Device and location independent fine grained fall detection.
 & Not suitable for outdoor monitoring.\\
\addlinespace
Proposed system
 & Smartphone accelerometer
 &Gender and garment independent, easy to wear phone holder & 1 & Remote
 &TB & Unknown
 & Text based location + SMS, Indoor and outdoor monitoring , Ineffectual device consideration, Non ambulatory, Non self-recovery warning only so number of warnings are less,  Simple fast and accurate.
 \\
\bottomrule
\end{tabularx}
\end{sidewaystable*}
\end{document}

观察到的输出 观察到的输出 和期望的输出 所需输出（来自 MS Word）

请帮忙。

答案1

只是tabular和multicolumn..

应收账款

\documentclass[twocolumn]{svjour3}

\usepackage[english]{babel}
%   \usepackage{tabularx}
\usepackage{booktabs}
\usepackage{rotating}
\setlength{\rotFPtop}{0pt plus 1fil}
\usepackage{makecell}
\renewcommand{\theadfont}{\bfseries}
\begin{document}
\begin{sidewaystable*}
\small

\caption{Comparison among state of the art designs}
\label{tab:1}       % Give a unique label
\begin{tabular}{>{\raggedright\arraybackslash}p{0.60in}  % changed to tabular and first column
        >{\raggedright\arraybackslash}p{0.85in}
        >{\raggedright\arraybackslash}p{0.95in} % increase width
        c
        >{\raggedright\arraybackslash}p{0.65in}
        c
        c
        >{\raggedright\arraybackslash}p{1.5in}
        >{\raggedright\arraybackslash}p{1.5in}} %changed from X
    \toprule
    \thead{Reference}&\thead{Sensor\\type}&\thead{Sensor\\location}&\thead{No. of\\ sensors}&\thead{Processing\\location}&\thead{Method}&\thead{Accuracy\\in \%}&\thead{Features}&\thead{Limitations}\\
    \midrule\\
    
    [1]
    & Accelerometer, Gyroscope
    
    & External & $>1$ & On board & TB & Unknown
    & Fine grained fall detection with good accuracy.
    & No text based location, Fall and break of device aspect not considered.
    \\
    \addlinespace
    
    [2]
    & Triaxial Accelerometer
    & External & 1 & On board and Remote
    & TB & Unknown
    &Fine grained fall detection with good accuracy. Reduced false alarm.
    &Device location in pocket of pant. No real life implementation case study. Fall and break aspect not considered.
    \\
    \addlinespace
    
    [3]
    & Triaxial Accelerometer
    & External & $>1$ & On board and remote
    & ML & 91.83
    &Fall detection and ADL based on KNN classifier with accuracy  of 91.83\%
    &Store \& analyse, no live data, device fall is not considered. \\
    \addlinespace
    
    [4]
    &Camera
    & External & $>1$ & Remote
    & ML & Unknown
    & Image information is used for fall classification.
    &Slow, multiple image capturing device may be required, privacy issues.\\
    \addlinespace
    
    [5]
    & Triaxial Accelerometer
    & External & $>1$ & Remote
    & TB + ML & Unknown
    & Threshold analysis, reminder analysis and decision tree algorithm .
    & The non-functional aspect of the device after a fall is not considered.\\
    \addlinespace
    
    [6]
    & Pressure Sensor
    &Integrated in the operator's shoe & $>1$ & remote
    & TB & Unknown
    & Good result accuracy and can be implemented in IOT platform.
    & The nature of walking surface has a direct impact on accuracy.\\
    \addlinespace
    
    [7]
    & Accelerometer, Gyroscope
    &Smartphone in chest pocket & $>1$ & On board and remote
    & TB & Unknown
    & Smartphone Google API (location), Good accuracy.
    & Device location is not suitable for heart patient, Google API is not accurate in remote locations.\\
    \addlinespace
    
    [8]
    & MEMS tri-axis accelerometer
    &Upper trunk of the body & 1 & Remote
    & ML & Unknown
    & Fall detection and prediction using hidden Markov chain.
    & Location information as well as fall alike cases are not considered.\\
    \addlinespace
    
    [9]
    & UHF-RFID
    &Different locations inside the room & $>1$ & Remote
    &TB + ML & Unknown
    & Device and location independent fine grained fall detection.
    & Not suitable for outdoor monitoring.\\
    \addlinespace
    
    Proposed system
    & Smartphone accelerometer
    &Gender and garment independent, easy to wear phone holder & 1 & Remote
    &TB & Unknown
    & \multicolumn{2}{p{\dimexpr1.5in+1.5in+2\tabcolsep+\arrayrulewidth}}{% <<<< changed
        Text based location + SMS, Indoor and outdoor monitoring, Ineffectual device consideration, Non ambulatory, Non self-recovery warning only so number of warnings are less,  Simple fast and accurate.}
    \\
    \bottomrule
\end{tabular}
\end{sidewaystable*}
\end{document}

与问题无关：我减小了第一列的宽度并扩大了第三列的宽度，以减少该列的换行符。

更新

第三列标题可能看起来“有点偏离中心”，但实际上是居中的。

在此处输入图片描述

为了消除这种视觉错觉，请将标题行中的替换 \thead{Sensor\\location}为\bfseries Sensor location，并增加宽度以容纳更长的线条。

西

这是最终的外观和完整的代码。您可以对第二列的标题使用相同的方法。（\bfseries Sensor type）

F

\documentclass[twocolumn]{svjour3}

\usepackage[english]{babel}
%   \usepackage{tabularx}
\usepackage{booktabs}
\usepackage{rotating}
\setlength{\rotFPtop}{0pt plus 1fil}
\usepackage{makecell}
\renewcommand{\theadfont}{\bfseries}
\begin{document}
\begin{sidewaystable*}
\small

\caption{Comparison among state of the art designs}
\label{tab:1}       % Give a unique label
\begin{tabular}{>{\raggedright\arraybackslash}p{0.60in}  % changed to tabular and first column
        >{\raggedright\arraybackslash}p{0.85in}
        >{\raggedright\arraybackslash}p{1.1in} % increase width
        c
        >{\raggedright\arraybackslash}p{0.65in}
        c
        c
        >{\raggedright\arraybackslash}p{1.5in}
        >{\arraybackslash}p{1.5in}} %changed from X
    \toprule
    \thead{Reference}&\thead{Sensor\\type}& \bfseries Sensor location&\thead{No. of\\ sensors}&\thead{Processing\\location}&\thead{Method}&\thead{Accuracy\\in \%}&\thead{Features}&\thead{Limitations}\\
    \midrule\\
    
    [1]
    & Accelerometer, Gyroscope
    
    & External & $>1$ & On board & TB & Unknown
    & Fine grained fall detection with good accuracy.
    & No text based location, Fall and break of device aspect not considered.
    \\
    \addlinespace
    
    [2]
    & Triaxial Accelerometer
    & External & 1 & On board and Remote
    & TB & Unknown
    &Fine grained fall detection with good accuracy. Reduced false alarm.
    &Device location in pocket of pant. No real life implementation case study. Fall and break aspect not considered.
    \\
    \addlinespace
    
    [3]
    & Triaxial Accelerometer
    & External & $>1$ & On board and remote
    & ML & 91.83
    &Fall detection and ADL based on KNN classifier with accuracy  of 91.83\%
    &Store \& analyse, no live data, device fall is not considered. \\
    \addlinespace
    
    [4]
    &Camera
    & External & $>1$ & Remote
    & ML & Unknown
    & Image information is used for fall classification.
    &Slow, multiple image capturing device may be required, privacy issues.\\
    \addlinespace
    
    [5]
    & Triaxial Accelerometer
    & External & $>1$ & Remote
    & TB + ML & Unknown
    & Threshold analysis, reminder analysis and decision tree algorithm .
    & The non-functional aspect of the device after a fall is not considered.\\
    \addlinespace
    
    [6]
    & Pressure Sensor
    &Integrated in the operator's shoe & $>1$ & remote
    & TB & Unknown
    & Good result accuracy and can be implemented in IOT platform.
    & The nature of walking surface has a direct impact on accuracy.\\
    \addlinespace
    
    [7]
    & Accelerometer, Gyroscope
    &Smartphone in chest pocket & $>1$ & On board and remote
    & TB & Unknown
    & Smartphone Google API (location), Good accuracy.
    & Device location is not suitable for heart patient, Google API is not accurate in remote locations.\\
    \addlinespace
    
    [8]
    & MEMS tri-axis accelerometer
    &Upper trunk of the body & 1 & Remote
    & ML & Unknown
    & Fall detection and prediction using hidden Markov chain.
    & Location information as well as fall alike cases are not considered.\\
    \addlinespace
    
    [9]
    & UHF-RFID
    &Different locations inside the room & $>1$ & Remote
    &TB + ML & Unknown
    & Device and location independent fine grained fall detection.
    & Not suitable for outdoor monitoring.\\
    \addlinespace
    
    Proposed system
    & Smartphone accelerometer
    &Gender and garment independent, easy to wear phone holder & 1 & Remote
    &TB & Unknown
    & \multicolumn{2}{p{\dimexpr1.5in+1.5in+2\tabcolsep+\arrayrulewidth\relax}}{% <<<< changed
        Text based location + SMS, Indoor and outdoor monitoring, Ineffectual device consideration, Non ambulatory, Non self-recovery warning only so number of warnings are less,  Simple fast and accurate.}
    \\
    \bottomrule
\end{tabular}
\end{sidewaystable*}
\end{document

答案2

您可以使用修改后的 X 列进行跨越

在此处输入图片描述

我没有上课所以页面大小有点不对，但是

 &\multicolumn{2}{X}{%
\hsize=\dimexpr\hsize+1.5in+2\tabcolsep\relax

做你想做的事

\documentclass[twocolumn]{article}
\usepackage[english]{babel}
\usepackage{tabularx}
\usepackage{booktabs}
\usepackage{rotating}
\setlength{\rotFPtop}{0pt plus 1fil}
\usepackage{makecell}
\renewcommand{\theadfont}{\bfseries}
\advance\textheight 2in
\advance\textwidth 2in
\begin{document}
\begin{sidewaystable*}

\caption{Comparison among state of the art designs}
\label{tab:1}       % Give a unique label
\begin{tabularx}{\linewidth}{c
                             >{\raggedright\arraybackslash}p{0.85in}
                             >{\raggedright\arraybackslash}p{0.65in}
                             c
                             >{\raggedright\arraybackslash}p{0.75in}
                             c
                             c
                             >{\raggedright\arraybackslash}p{1.5in}
                             X}
\toprule
\thead{Reference}&\thead{Sensor\\type}&\thead{Sensor\\location}&\thead{No. of\\ sensors}&\thead{Processing\\location}&\thead{Method}&\thead{Accuracy\\in \%}&\thead{Features}&\thead{Limitations}\\
\midrule\\
{[}1]
  & Accelerometer, Gyroscope

    & External & $>1$ & On board & TB & Unknown
      & Fine grained fall detection with good accuracy.
        & No text based location, Fall and break of device aspect not considered.
\\
\addlinespace

{[}2]
  & Triaxial Accelerometer
    & External & 1 & On board and Remote
 & TB & Unknown
      &Fine grained fall detection with good accuracy. Reduced false alarm.
        &Device location in pocket of pant. No real life implementation case study. Fall and break aspect not considered.
\\
\addlinespace

{[}3]
  & Triaxial Accelerometer
    & External & $>1$ & On board and remote
 & ML & 91.83
      &Fall detection and ADL based on KNN classifier with accuracy  of 91.83\%
        &Store \& analyse, no live data, device fall is not considered. \\
\addlinespace

{[}4]
  &Camera
    & External & $>1$ & Remote
 & ML & Unknown
  & Image information is used for fall classification.
        &Slow, multiple image capturing device may be required, privacy issues.\\
\addlinespace

{[}5]
  & Triaxial Accelerometer
    & External & $>1$ & Remote
 & TB + ML & Unknown
      & Threshold analysis, reminder analysis and decision tree algorithm .
        & The non-functional aspect of the device after a fall is not considered.\\
\addlinespace

{[}6]
  & Pressure Sensor
    &Integrated in the operator's shoe & $>1$ & remote
 & TB & Unknown
      & Good result accuracy and can be implemented in IOT platform.
        & The nature of walking surface has a direct impact on accuracy.\\
\addlinespace

{[}7]
 & Accelerometer, Gyroscope
 &Smartphone in chest pocket & $>1$ & On board and remote
 & TB & Unknown
 & Smartphone Google API (location), Good accuracy.
 & Device location is not suitable for heart patient, Google API is not accurate in remote locations.\\
\addlinespace
{[}8]
 & MEMS tri-axis accelerometer
 &Upper trunk of the body & 1 & Remote
 & ML & Unknown
 & Fall detection and prediction using hidden Markov chain.
 & Location information as well as fall alike cases are not considered.\\
\addlinespace
{[}9]
 & UHF-RFID
 &Different locations inside the room & $>1$ & Remote
 &TB + ML & Unknown
 & Device and location independent fine grained fall detection.
 & Not suitable for outdoor monitoring.\\
\addlinespace
Proposed system
 & Smartphone accelerometer
 &Gender and garment independent, easy to wear phone holder & 1 & Remote
 &TB & Unknown
 &\multicolumn{2}{X}{%
\hsize=\dimexpr\hsize+1.5in+2\tabcolsep\relax
 Text based location + SMS, Indoor and outdoor monitoring , Ineffectual device consideration, Non ambulatory, Non self-recovery warning only so number of warnings are less,  Simple fast and accurate.}
 \\
\bottomrule
\end{tabularx}
\end{sidewaystable*}
\end{document}

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