diff --git a/paper/main.tex b/paper/main.tex
index e96e0c4da5cffd8a09c82ab6d9134935da23418a..a60216111a5bffdfe40f27686ba32dc86b0fdb97 100644
--- a/paper/main.tex
+++ b/paper/main.tex
@@ -65,7 +65,7 @@
 
 \begin{document}
 
-\title{Modeling of Power Consumption in GPS Receivers for Power Aware Localization Systems}
+\title{Modeling of Energy Consumption in GPS Receivers for Power Aware Localization Systems}
 \author{Claudio Mandrioli}
 \affiliation{%
   \institution{Department of Automatic Control,\\Lund University}
diff --git a/paper/sections/01-intro.tex b/paper/sections/01-intro.tex
index 615a3771b8214e4fc86e2da085fd579465a8654e..76a7acb619c60f50e486ad7458e08e4ed18b8e7a 100644
--- a/paper/sections/01-intro.tex
+++ b/paper/sections/01-intro.tex
@@ -61,7 +61,7 @@ merging algorithms) programmatically and to expose the characteristics
 of each solution.
 \end{itemize}
 
-\textcolor{red}{Even though the notions used to build the presented model are known in the litterature, their systematic study and integration has not been seen elsewhere by the authors. The development of this first-principle and simulable model allows, among the others, to: (i) perform at design phase a quantitative evaluaion of the energy cost of different sampling strategies, (ii) compare different sampling strategies without depending on the specific testing conditions.}
+\textcolor{red}{Even though the notions used to build the presented model are known in the litterature, their systematic study and integration has not been seen elsewhere by the authors. The development of this first-principle and simulable model enables the possiblity of (i) performing at design phase a quantitative evaluaion of the energy cost of different sampling strategies, (ii) comparing different sampling strategies without depending on the specific testing conditions.}
 
 %
 This paper is organized as follows. As much research has been done on
diff --git a/paper/sections/03-model.tex b/paper/sections/03-model.tex
index fbc268bee192a74c54eaa8ea727bf7861c1cf5e5..69211ef736ef687e96ccdc7fcdfc2fc074f12138 100644
--- a/paper/sections/03-model.tex
+++ b/paper/sections/03-model.tex
@@ -205,7 +205,7 @@ font=\footnotesize]
 The GPS receiver provides a position estimate when it has collected
 both the ephemeris and the ranging data for at least 4 satellites.
 Detecting data from more than 4 satellites can improve the positioning
-accuracy. \textcolor{red}{This depents on many factors which are hard to model, e.g. the relative position of the stellites in sapce and the geography of the environment around the sensor. Therefore, for the sake of keeping the model at a reasonable complexity, it is only required to set a minimum number of satellites to be tracked, depending on the specific application. This number has to be equal to or greater than 4 and it being higher represents the the constraint of higher accuracy in the given application.} As for power consumption, the receiver always consumes a
+accuracy. \textcolor{red}{This depents on many factors which are hard to model, like the relative position of the stellites in sapce and the geography of the environment around the sensor. Therefore, for the sake of keeping the model at a reasonable complexity, it is only required to set a minimum number of satellites to be tracked, depending on the specific application. This number has to be equal to or greater than 4 and it being higher represents the the constraint of higher accuracy in the given application.} As for power consumption, the receiver always consumes a
 (negligible) idle power. On top of that, the sensor consumes
 additional power when its radio is turned on, which is precisely the
 cause of battery draining. This power has been experimentally shown to
@@ -215,7 +215,9 @@ be constant in time~\cite{bib:enloc-smartphones, bib:microsoft-leap}
 %=======
 and usually between 20mW and 400mW. We use the latter for our model,
 but this is just a constant that can be changed depending on the
-device. The important states that our model needs to capture are:
+device. 
+
+The important states that our model needs to capture are:
 \begin{enumerate}
   \item \emph{ephemeris data} are available or not;
   \item \emph{ranging data} are available or not;
diff --git a/paper/sections/06-results.tex b/paper/sections/06-results.tex
index 0a8a1319de5e6876c59f6fc28ccab8bb8d6ac9f8..1b07cffe4d9b8d6e78b168db8b709909c9888027 100644
--- a/paper/sections/06-results.tex
+++ b/paper/sections/06-results.tex
@@ -368,7 +368,7 @@ show what the tracking would have been when the sensor fusion
 algorithm was live, compared to the continuous sampling of the GPS. We
 then use simulations to further analyze the trade-off between power
 (and therefore battery) consumption and performance (positioning
-accuracy).
+accuracy). \textcolor{red}{The sampling rate of the used traces is $1Hz$ but the localization information is of course made available only when the model is in the correct state.}
 
 Figures~\ref{fig:cycling-trace} and~\ref{fig:car-trace} respectively
 show traces for the tracking of the bike and the car. In each