feat: decided to add the additional, 11th slide

1 files changed, 27 insertions, 20 deletions

diff --git a/main.tex b/main.tex
index 1f0cf0d..c600fb7 100644
--- a/main.tex
+++ b/main.tex
@@ -173,7 +173,7 @@
 		\end{center}
 		\vspace{-0.3cm}
 		\tiny
-		\textbf{Figure 1.7:} Experiment 1a. In this experiment we use red and yellow alarms to notify datacenter operators of unexpected failures.
+		\textbf{Figure 1.7a:} Experiment 1a. In this experiment we use red and yellow alarms to notify datacenter operators of unexpected failures.
 		We use a threshold based on predictions done by the simulator and a statistical distribution.
 	\end{minipage}
 	\hspace{0.6cm}
@@ -183,28 +183,35 @@
 		\end{center}
 		\vspace{-0.3cm}
 		\tiny
-		\textbf{Figure 1.8:} Experiment 1b. The mean failure detection rate is around 15\%. Even though this seems low, if we look at \textbf{Fig. 1.9} (see Extra Slides), this simply means around 15\% of failures are unexpected.
+		\textbf{Figure 1.7b:} Experiment 1b. The mean failure detection rate is around 15\%. Even though this seems low, if we look at \textbf{Fig. E.1} (see Extra Slides), this simply means around 15\% of failures are unexpected.
 	\end{minipage}
 	% Explain what the axis are in the figure caption.
 	% Talk about the experimental setup in the figure.
 	% Give more reliable results than just numbers -- do statistical testing, i.e., standard deviation, confidence intervals.
 \end{frame}
 
-%\begin{frame}\frametitle{\textbf{RQ3}: Experimental Results II}
-%	\begin{tcolorbox}[title=Evaluation]
-%		Predictive analytics is core to digital twinning. We evaluate our system against the requirements (extra slides) by predicting an optimal scheduling policy.
-%		During runtime, we make dynamic adjustments to the physical twin, if the scheduling results differ.
-%	\end{tcolorbox}
-%	\hspace{0.2cm}
-%	\begin{minipage}[b]{0.32\linewidth}
-%		\begin{center}
-%			\includegraphics[width=1.1\textwidth]{images/23_Jun_2026_102028.pdf}
-%		\end{center}
-%		\vspace{-0.3cm}
-%		\tiny
-%		\textbf{Figure 1.9:} Experiment 1
-%	\end{minipage}
-%\end{frame}
+\begin{frame}\frametitle{\textbf{RQ3}: Experimental Results II}
+	\begin{tcolorbox}[title=Main Finding III]
+		\emph{Sunfish} is capable of dynamic adjustments to the physical twin at runtime, and can lower the mean number of failed tasks.
+	\end{tcolorbox}
+	\hspace{0.2cm}
+	\begin{minipage}[b]{0.45\linewidth}
+		\begin{center}
+			\includegraphics[width=1.1\textwidth]{images/23_Jun_2026_102028.pdf}
+		\end{center}
+		\vspace{-0.3cm}
+		\tiny
+		\textbf{Figure 1.8a:} Experiment 2a.
+	\end{minipage}
+	\begin{minipage}[b]{0.45\linewidth}
+		\begin{center}
+			\includegraphics[width=1.1\textwidth]{images/23_Jun_2026_102028.pdf}
+		\end{center}
+		\vspace{-0.3cm}
+		\tiny
+		\textbf{Figure 1.8b:} Experiment 2b.
+	\end{minipage}
+\end{frame}
 
 \begin{frame}\frametitle{Key Takeaways}
 	\begin{tcolorbox}[title=What is the societal context?]
@@ -246,11 +253,11 @@
 	\bibliography{main.bib}
 \end{frame}
 
-\begin{frame}\frametitle{Technical Setup }
+\begin{frame}\frametitle{Extra Slides: Technical Setup }
 	\begin{tcolorbox}[title=What is the simulation workload?]
 		The compute workload is BitBrainsSmall.
-		The failure traces include user reports from Gmail, WhatsApp and Twitter.
-
+		The failure traces include user reports from Gmail, WhatsApp, Facebook and Twitter.
+		For predictions we use \texttt{prefabs}~\cite{DBLP:journals/fgcs/VersluisCGLPCUI23}.
 	\end{tcolorbox}
 	\begin{tcolorbox}[title=What is the experiment environment?]    A commodity laptop: Framework Laptop 13, with 32GB of DDR5 RAM and an AMD Ryzen 7840U processor and an ArchLinux OS with Linux 7.0.13-arch1-1 kernel.