diff --git a/graphics/problem/lmdk-scenario.pdf b/graphics/problem/lmdk-scenario.pdf
index 1d1975d..83a5835 100644
Binary files a/graphics/problem/lmdk-scenario.pdf and b/graphics/problem/lmdk-scenario.pdf differ
diff --git a/text/problem/main.tex b/text/problem/main.tex
index 4311bf9..53d7af6 100644
--- a/text/problem/main.tex
+++ b/text/problem/main.tex
@@ -7,13 +7,13 @@ The plethora of sensors currently embedded in personal devices and other infrast
 % Continuously user-generated data
 User--service interactions gather personal event-like data, which are tuples of an identifying attribute of an individual and the---possibly sensitive---information with a timestamp 
 %(including contextual information), 
-e.g.,~(\emph{`Bob', `dining', `Canal Saint-Martin', $17{:}00$}).
+e.g.,~(\emph{`Quackmore', `dining', `Canal Saint-Martin', $17{:}00$}).
 When the interactions are performed in a continuous manner, we obtain ~\emph{time series} of events.
 Example~\ref{ex:scenario} is an example of a user--service interaction that results in retrieving location-based information or reporting user-state at various locations.
 
 \begin{example}
   \label{ex:scenario}
-  Figure~\ref{fig:lmdk-scenario} shows a finite sequence of spatiotemporal data, generated by Bob, during an interval of $8$ timestamps.
+  Figure~\ref{fig:lmdk-scenario} shows a finite sequence of spatiotemporal data, generated by Quackmore, during an interval of $8$ timestamps.
   Events in gray correspond to
   % privacy-sensitive 
   % \kat{You should not say that only significant events are privacy-sensitive, because then why put noise to the normal timestamps? Maybe say directly significant for the shaded events?}
diff --git a/text/problem/thething/main.tex b/text/problem/thething/main.tex
index 8c5b0b4..15cbfe1 100644
--- a/text/problem/thething/main.tex
+++ b/text/problem/thething/main.tex
@@ -36,7 +36,7 @@ Hence, at any timestamp we achieve an overall privacy protection bounded by $\va
 
 \begin{example}
   \label{ex:st-cont}
-  Continuing Example~\ref{ex:scenario}, Bob cares about protecting his {\thethings} ($p_1$, $p_3$, $p_5$, $p_8$) along with every release that he makes, however he is not equally interested for the other regular events in his trajectory.
+  Continuing Example~\ref{ex:scenario}, Quackmore cares about protecting his {\thethings} ($p_1$, $p_3$, $p_5$, $p_8$) along with every release that he makes, however he is not equally interested for the other regular events in his trajectory.
   More technically, he cares about allocating a total budget of $\varepsilon$ on any set of timestamps containing the {\thethings} and one regular event.
   Event-level protection is not suitable for this case, since it can only protect one event at a time.
   So, let us assume that we apply user-level privacy\footnote{In this scenario, in order to protect all the {\thethings} from timestamp $1$ to $8$, $w$ must be set to $8$, which makes $w$-event privacy equivalent to user-level.}, by distributing equal portions of $\varepsilon$ to all the events, i.e.,~$\frac{\varepsilon}{8}$ to each one (see Figure~\ref{fig:st-cont}).