last section

Socksorting/mydefs.tex

@@ -8,6 +8,7 @@
 \usepackage{algorithmicx}
 \usepackage{algpseudocode}
 \usepackage{emoji}
+\usepackage{soul}
 
 
 \newcommand{\acronym}{HADES }

Socksorting/project.tex

@@ -146,38 +146,56 @@ As evident from the algorithm above, only one loop performing
 operations which are all in $\mathscr{O}(1)$ is required thus
 putting the algorithm in a $\mathscr{O}(n)$ runtime complexity
 class. Assuming that $\forall\mathscr{L}\in\Lambda\exists\mathscr{L}^{-1}|\mathscr{L}\cong\mathscr{L}^{-1}$
-the algorithm always yields a correct solution for the problem 
+the algorithm always yields a correct solution for the problem
 (proof is left as an exercise to the reader).
 \section{Discussion and Results}
-To evaluate the algorithms performance it has been executed 
+To evaluate the algorithms performance it has been executed
 on different platforms consisting of diverse hardware:\\
-\begin{tabular}[]{l||l|c}
-  \textbf{Hardware} & \textbf{Algorithm} & \textbf{Runtime [s]}\\
-  \hline
-  Myself & Conventional (n=20) & 352.7\\
-  Myself & \acronym (n=20) & 92.3\\
-  Myself & Conventional (n=100) & 42069\\
-  Myself & \acronym (n=100) & 420.69\\
-  \hline
-  My roommate & Conventional (n=10) & 91.7\\
-  My roommate & \acronym (n=10) & -2\\
-  \hline
-  Girlfriend & n.a. & n.a.
-\end{tabular}\\
+\resizebox*{\linewidth}{!}{
+  \begin{tabular}[]{l||l|c}
+    \textbf{Hardware} & \textbf{Algorithm}   & \textbf{Runtime [s]} \\
+    \hline
+    Myself            & Conventional (n=20)  & 352.7                \\
+    Myself            & \acronym (n=20)      & 92.3                 \\
+    Myself            & Conventional (n=100) & 42069                \\
+    Myself            & \acronym (n=100)     & 420.69               \\
+    \hline
+    My roommate       & Conventional (n=10)  & 91.7                 \\
+    My roommate       & \acronym (n=10)      & -2                   \\
+    \hline
+    Girlfriend        & n.a.                 & n.a.
+  \end{tabular}
+}\\
 \begin{figure}[h]
   \begin{center}
     \includegraphics[width=\linewidth]{figs/graph.png}
     \bigskip
-    \caption{Comparative statistical time analysis of both algorithms. \acronym in blue, conventional sock sorting in green.}
+    \caption{Comparative statistical time analysis of both algorithms.
+    The graph depicts algorithm runtime (y-axis) and graphs it against 
+    input size (x-axis). Data for 
+    \acronym in blue, for conventional sock sorting in green.}
   \end{center}
 \end{figure}\\
 From the above data it is evident that \acronym bears a clear advantage in comparison
 to the conventional algorithm when it comes to sock sorting. Utilizing advanced statistical modelling we calculated a
-speedup factor of about $2.57179072584935274050327\cdot n$. The data also illustrates
+speedup factor of about $3.1415926535897932384626433\cdot n$. The data also illustrates
 the scalability of the algorithm and its adaptability to different hardware.
 \section{Conclusion}
-
+It can be concluded that the algorithm presented in this paper is
+greatly superior to the conventional method of sorting socks.
+It will probably revolutionize not only the field of laundry science but
+also have great impact in the industry.\\
+The datastructures outlined above may become abundantly used and be the future
+industry standard. Although the field of laundry science is still rather new
+there are still a lot of open questions to be answered. However it is unlikely
+that a faster sock sorting algorithm than \acronym can be developed.
 \section{Acknowledgements}
+We shall use this historic opportunity to thank the Journal of immaterial science
+for publishing great \st{memes} research. We also want to thank our university
+for giving us this great opportunity for \st{depression and self loathing}
+research and personal advancement.\\
+It is also only appropriate to thank the air. Without it no laundry would be 
+dry and we would not have written this paper.\\
 
 \begingroup
 \setlength\bibitemsep{0pt}