From 12353956881c2e97f48bf1686871afabb03a85ff Mon Sep 17 00:00:00 2001 From: "hannes.kuchelmeister" Date: Sat, 9 May 2020 10:56:15 +0200 Subject: [PATCH] move placement of example box --- 30_Thesis/sections/40_concept.tex | 78 +++++++++++++++---------------- 1 file changed, 39 insertions(+), 39 deletions(-) diff --git a/30_Thesis/sections/40_concept.tex b/30_Thesis/sections/40_concept.tex index 5bbe4e4..5565dea 100644 --- a/30_Thesis/sections/40_concept.tex +++ b/30_Thesis/sections/40_concept.tex @@ -149,45 +149,6 @@ They select the current state at the beginning of the process. Then users repeat The case study used in this thesis is a simplified version from forestry \todo[]{hier evtl ergänzen: wo kommt der Use Case her / aus welchem Forschungsprojekt / warum ist er interessant?}. The used characteristics and attributes are shown in \autoref{fig:Concept:ForestExample}. Additionally, as examples preferences, a configuration state and a finished configuration are given. -\begin{figure} - \begin{mdframed}[ - nobreak=true, - frametitle={Example for Forestry Use Case}, - linecolor=black, - frametitlerulecolor=black, - frametitlebackgroundcolor=gray!5 - ] - In this example there is a small group of users. The use case is a piece of forest and variables are for example harvesting activity, which trees to grow and accessibility for people. - \begin{align} - \begin{split} - V = \{ & \textit{indigenous}, \textit{resilient}, \textit{usable}, \textit{effort}, \textit{quantity}, \textit{price}, \textit{accessibility} \}, - \end{split} \notag \\ - \mathfrak{D}(\textit{indigenous}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag \\ - \mathfrak{D}(\textit{resilient}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag \\ - \mathfrak{D}(\textit{usable}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag \\ - \mathfrak{D}(\textit{effort}) = \{ & \text{manual}, \text{harvester}, \text{autonomous}\}, \notag \\ - \mathfrak{D}(\textit{quantity}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag \\ - \mathfrak{D}(\textit{price}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag\\ - \mathfrak{D}(\textit{accessibility}) = \{ & \text{low}, \text{moderate}, \text{high}\},\notag \\ - U = \{ & 1,2\} \notag\\ - P = \{ & P_1, P_2\} \notag\\ - \begin{split} - P_1 = \{ & (\text{manual}, 0.8), (\text{harvester}, 0.3) \} \\ - & \cup \{ (d,0.5)\ |\ d \in \mathfrak{D}(i),\ i \in V,\ i \notin \{ \text{manual}, \text{harvester}\} \ \} \ - \end{split} \notag \\ - P_2 = \{ & (d,0.5)\ |\ d \in \mathfrak{D}(i),\ i \in V \} \notag \\ - S = \{ & (\textit{indigenous}, \text{low}), (\textit{quantity}, \text{moderate}) \} \notag \\ - \begin{split} - S_F = \{ & (\textit{indigenous}, \text{low}), (\textit{resilient}, \text{low}), (\textit{usable},\text{low}), (\textit{effort}, \text{manual}), \\ - & (\textit{quantity}, \text{low}), (\textit{price},\text{high}),(\textit{accessibility}, \text{low}) \} - \end{split} \notag - \end{align} - \end{mdframed} - \caption[Forestry Use Case]{An example of use case in forestry that includes two people.} - \label{fig:Concept:ForestExample} -\end{figure} - - \section{Recommendation Generation} \label{sec:Concept:SolutionGeneration} @@ -234,6 +195,45 @@ where $aggr$ is the aggregation function and $score_{user}(P_i, s)$ is the confi score_{user}(P_i, s) = average(\{x \ | \ (characteristic, x) \in P_i \land characteristic \in s \}) \notag . \end{equation} + +\begin{figure}[htb] + \begin{mdframed}[ + nobreak=true, + frametitle={Example for Forestry Use Case}, + linecolor=black, + frametitlerulecolor=black, + frametitlebackgroundcolor=gray!5 + ] + In this example there is a small group of users. The use case is a piece of forest and variables are for example harvesting activity, which trees to grow and accessibility for people. + \begin{align} + \begin{split} + V = \{ & \textit{indigenous}, \textit{resilient}, \textit{usable}, \textit{effort}, \textit{quantity}, \textit{price}, \textit{accessibility} \}, + \end{split} \notag \\ + \mathfrak{D}(\textit{indigenous}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag \\ + \mathfrak{D}(\textit{resilient}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag \\ + \mathfrak{D}(\textit{usable}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag \\ + \mathfrak{D}(\textit{effort}) = \{ & \text{manual}, \text{harvester}, \text{autonomous}\}, \notag \\ + \mathfrak{D}(\textit{quantity}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag \\ + \mathfrak{D}(\textit{price}) = \{ & \text{low}, \text{moderate}, \text{high}\}, \notag\\ + \mathfrak{D}(\textit{accessibility}) = \{ & \text{low}, \text{moderate}, \text{high}\},\notag \\ + U = \{ & 1,2\} \notag\\ + P = \{ & P_1, P_2\} \notag\\ + \begin{split} + P_1 = \{ & (\text{manual}, 0.8), (\text{harvester}, 0.3) \} \\ + & \cup \{ (d,0.5)\ |\ d \in \mathfrak{D}(i),\ i \in V,\ i \notin \{ \text{manual}, \text{harvester}\} \ \} \ + \end{split} \notag \\ + P_2 = \{ & (d,0.5)\ |\ d \in \mathfrak{D}(i),\ i \in V \} \notag \\ + S = \{ & (\textit{indigenous}, \text{low}), (\textit{quantity}, \text{moderate}) \} \notag \\ + \begin{split} + S_F = \{ & (\textit{indigenous}, \text{low}), (\textit{resilient}, \text{low}), (\textit{usable},\text{low}), (\textit{effort}, \text{manual}), \\ + & (\textit{quantity}, \text{low}), (\textit{price},\text{high}),(\textit{accessibility}, \text{low}) \} + \end{split} \notag + \end{align} + \end{mdframed} + \caption[Forestry Use Case]{An example of use case in forestry that includes two people.} + \label{fig:Concept:ForestExample} +\end{figure} + The example in \autoref{fig:Concept:ForestExample} contains two users. The first user has preferences for the characteristic \emph{manual} of the feature with $0.8$ and the characteristic \emph{harvester} of the same feature with $0.3$. All other characteristics have a preference of $0.5$. The second user's preferences are $0.5$ for all characteristics. The finished configuration that is supposed to be rated in this example contains the characteristics \emph{low} for each feature except for \emph{effort} and \emph{quantity} which are set to \emph{manual} and \emph{high}. The score fore the finished configuration $S_F$ of user one is $0.54$. This score is the average of all seven features. User one rates all characteristics of all features as $0.5$ except two characteristics for \emph{effort}. Thus, all feature scores for this user are $0.5$ except the score for \emph{effort} is $0.8$ because of the user's preference of $0.8$ for the characteristic \emph{manual}. The resulting average score per feature of $0.54$ is the user's score for this configuration. User two rates all characteristics with $0.5$ therefore the resulting average is $0.5$. The group configuration score is dependent on the used aggregation strategy. Multiplication results in a score of $0.54 \cdot 0.5 = 0.27$. The score for average is $\frac{1}{2}(0.54 + 0.5) = 0.52$ and for least misery $\min \{0.54, 0.5\} = 0.5$.