diff --git a/inefficiency.tex b/inefficiency.tex
index 1aa46fd..cfa6fe3 100644
--- a/inefficiency.tex
+++ b/inefficiency.tex
@@ -53,7 +53,7 @@ minimum energy it requires.
 %
 We define the ratio of application's energy consumption ($E$) and the minimum
 energy the application could have consumed ($E_{min}$) on the same device as
-inefficiency: $I = \frac{E}{E_{min}}$ 
+inefficiency: $I = \frac{E}{E_{min}}$. 
 %
 An \textit{inefficiency} of $1$ represents an application's most efficient
 execution, while $1.5$ indicate the the application consumed $50\%$ more
@@ -78,19 +78,27 @@ constraints for real systems:
 \end{enumerate}
 
 We continue by addressing these questions.
-
 \subsection{Inefficiency Bounds and Inefficiency Budget}
-
 % 27 Apr 2015 : GWA : I didn't understand this.
 
 % We argue that absolute value of $I_{max}$ is irrelevant because, even when
 % energy is unconstrained, algorithms should focus on delivering the best
 % performance.
-
 Devices will operate between an inefficiency of 1 and $I_{max}$ which
 represents the unbounded energy constraint allowing the application to
 consume unbounded energy to deliver the best performance.
 %
+$I_{max}$ depends upon applications and devices.
+%
+We argue that absolute value of $I_{max}$ is irrelevant
+because, when energy is unconstrained, algorithms can burn unbounded energy and
+only focus on
+delivering the best performance.
+%
+The inefficiency budget matters the most when application has bounded energy
+constraints and it can be set by the user or the applications. 
+%For example, an inefficiency budget of 1.2 means that the user is willing to lose 20\% more energy to execute the application.
+%
 The OS can also set the inefficiency budget based on application's priority
 allowing the higher priority applications to burn more energy than lower
 priority applications. 
diff --git a/submitted/Submission_90.pdf b/submitted/Submission_90.pdf
new file mode 100644
index 0000000..95ad00d
--- /dev/null
+++ b/submitted/Submission_90.pdf