english

diff --git a/article.tex b/article.tex
index 5e7bea7711b8cebaf28c726e523bb6823f5fbc77..31de4f0134740119495415eb690527d50768f853 100644 (file)
--- a/article.tex
+++ b/article.tex
@@ -877,7 +877,7 @@ scheduling based on optimization in  MuDiLCO maintains higher coverage ratios of
 the area of interest  for a larger number of rounds. It  also means that MuDiLCO
 saves more energy,  with less dead nodes,  at most for several  rounds, and thus
 should  extend the  network lifetime.  \textcolor{blue}{MuDiLCO-7 seems  to have
-  most of the  time the best coverage  ratio up to round~80,  after MuDiLCO-5 is
+  most of the  time the best coverage  ratio up to round~80,  after that MuDiLCO-5 is
   slightly better.}
 
 \begin{figure}[ht!]
@@ -950,7 +950,7 @@ consumed during the different status of the sensor node.
 
 \textcolor{blue}{Energy consumption increases with the  size of the networks and
   the  number  of  rounds.   The curve  Unlimited-MuDiLCO-7  shows  that  energy
-  consumption due to  the time spent to solve the  integer program to optimality
+  consumption due to  the time spent to  optimally solve the  integer program
   increases drastically with  the size of the network. When  the resolution time
   is limited for large network sizes, the energy consumption remains of the same
   order whatever the MuDiLCO version. As can be seen with MuDiLCO-7.}
@@ -1017,8 +1017,8 @@ lifetime for a coverage  over 95\%, and a network of  250~nodes, is greater than
   rather than limiting the execution time,  similar results might be obtained by
   replacing  the  computation of  the  exact  solution  with  the finding  of  a
   suboptimal  one using  a  heuristic  approach. For  our  simulation setup  and
-  considering  the different  metrics, MuDiLCO-5  seems  to be  the most  suited
-  method in comparison with MuDiLCO-7.}
+  considering  the different  metrics, MuDiLCO-5  seems  to be  the best  suited
+  method compared to MuDiLCO-7.}
 
 \begin{figure}[t!]
   \centering