diff --git a/IV/mj-msc.tex b/IV/mj-msc.tex
index e2e0392..186e595 100644
--- a/IV/mj-msc.tex
+++ b/IV/mj-msc.tex
@@ -33,18 +33,15 @@
 \newcommand{\WM}{Wang--M{\"u}ller}
 
 \title{
+    \includegraphics[width=60mm]{vu.png}\\[8ex]
     Cartographic Generalization of Lines using free software \\
     (example of rivers) \\ \vspace{4mm}
 }
 
-\iffalse
-\fi
-
 \author{Motiejus Jakštys}
 
 \date{
-    \vspace{10mm}
-    Version: \VCDescribe
+    \VCDescribe
 }
 
 \begin{document}
@@ -55,7 +52,7 @@
 
 Current open-source line generalization solutions have their roots in
     mathematics and geometry, and are not fit for natural objects like rivers
-    and coastlines. This paper discusses our implementation of \WM algorithm
+    and coastlines. This paper discusses our implementation of {\WM} algorithm
     under and open-source license, explains things that we would had
     appreciated in the original paper and compares our results to different
     generalization algorithms.
@@ -71,16 +68,70 @@ Current open-source line generalization solutions have their roots in
 \section{Introduction}
 \label{sec:introduction}
 
-A number of cartographic line generalization algorithms have been researched,
-which claim to better process cartographic objects like lines. These fall into
-two rough categories:
+When creating small-scale maps, often the detail of the data source is greater
+than desired for the map. This becomes especially acute for natural features
+that have many bends, like coastlines, rivers and forest boundaries.
+
+To create a small-scale map from a large-scale data source, these features need
+to be generalized: detail should be reduced. However, while doing so, it is
+important to preserve the "defining" shape of the original feature, otherwise
+the result will look unrealistic.
+
+For example, if a river is nearly straight, it should be nearly straight after
+generalization, otherwise a too straightened river will look like a canal.
+Conversely, if the river is highly wiggly, the number of bends should be
+reduced, but not removed.
+
+Generalization problem for other objects can often be solved by other
+non-geometric means:
+
+\begin{itemize}
+    \item Towns and cities can be filtered and generalized by number of
+        inhabitants.
+    \item Roads can be eliminated by the road length, number of lanes, or
+        classification of the road (local, regional, international).
+\end{itemize}
+
+Natural line generalization problem can be viewed as having two competing
+goals:
+
+\begin{itemize}
+    \item Reduce detail by removing or simplifying "less important" features.
+    \item Retain enough detail, so the original is still recognize-able.
+\end{itemize}
+
+Given the discussed complexities, a fine line between under-generalization
+(leaving object as-is) and over-generalization (making a straight line) must be
+found. Therein lies the complexity of generalization algorithms: all have
+different trade-offs.
+
+\section{Literature review}
+\label{sec:literature-review}
+
+A number of cartographic line generalization algorithms have been researched.
+The "classical" ones are {\DP} and {\VW}.
+
+\subsection{{\DP} and {\VW}}
+
+\cite{douglas1973algorithms} and \cite{visvalingam1993line} are "classical"
+line generalization computer graphics algorithms. They are relatively simple to
+implement, require few runtime resources. Both of them accept only a single
+parameter, which makes them very simple to adjust for different scales.
+
+However, both of them are emitting insufficient 
+
+\subsection{Modern approaches}
+
+After {\DP} and {\VW} have been established, 
+
+These fall into two rough categories:
+
 \begin{itemize}
     \item Cartographic knowledge was encoded to an algorithm (bottom-up
         approach). One among these are \cite{wang1998line}.
-    \item Mathematical shape transformation which yields a more
-        cartographically suitable down-scaling. E.g. \cite{jiang2003line},
-        \cite{dyken2009simultaneous}, \cite{mustafa2006dynamic},
-        \cite{nollenburg2008morphing}.
+    \item Mathematical shape transformation which yields a more cartographic
+        result. E.g. \cite{jiang2003line}, \cite{dyken2009simultaneous},
+        \cite{mustafa2006dynamic}, \cite{nollenburg2008morphing}.
 \end{itemize}
 
 During research for the mentioned articles, prototype code has been written for
@@ -113,10 +164,8 @@ those through a widely available \cite{chaikin1974algorithm} smoothing
 algorithm via \href{https://postgis.net/docs/ST_ChaikinSmoothing.html}{PostGIS
 ChaikinSmoothing}.
 
-\section{Visual comparison}
-
-\subsection{Comparison algorithms and parameters}
-\subsection{Combining bends}
+\section{Methodology}
+\label{sec:methodology}
 
 \section{Conclusions}
 \label{sec:conclusions}
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