This master thesis investigates the possibilities of using GPS-information from trains to create a model of a railway system, register the routes of the the trains and predict how the trains will travel in the railway system.The thesis work was done at Icomera AB which is a company that specializes in internet connected vehicle solutions.We describe how the GPS-information is sent from the trains in the form of samples and investigate limitations and possibilities with the available information. About three million samples from 83 SJ-trains were analysed and the samples were filtered with the intent of removing erroneous information. We here found that about 30 % of the samples from the trains were unreliable.A solution for how the samples from the trains can be used to create a model of the railway system traveled by the trains is presented. We use a large set of historical samples and use cluster nodes and Hermite curves to generate a graph that represent the railway system with stations, nodes and the railway itself. A fully automatic solution is not presented since it did not fit into the time frame of the thesis; instead we created a simple tool which can be used to manually finish the model of the railway system.Furthermore, we describe how the railway system and the samples from the train can be used to register the routes the trains travel.

This master thesis investigates the possibilities of using GPS-information from trains to create a model of a railway system, register the routes of the the trains and predict how the trains will travel in the railway system.The thesis work was done at Icomera AB which is a company that specializes in internet connected vehicle solutions.We describe how the GPS-information is sent from the trains in the form of samples and investigate limitations and possibilities with the available information. About three million samples from 83 SJ-trains were analysed and the samples were filtered with the intent of removing erroneous information. We here found that about 30 % of the samples from the trains were unreliable.A solution for how the samples from the trains can be used to create a model of the railway system traveled by the trains is presented. We use a large set of historical samples and use cluster nodes and Hermite curves to generate a graph that represent the railway system with stations, nodes and the railway itself. A fully automatic solution is not presented since it did not fit into the time frame of the thesis; instead we created a simple tool which can be used to manually finish the model of the railway system.Furthermore, we describe how the railway system and the samples from the train can be used to register the routes the trains travel.

This master thesis investigates the possibilities of using GPS-information from trains to create a model of a railway system, register the routes of the the trains and predict how the trains will travel in the railway system.The thesis work was done at Icomera AB which is a company that specializes in internet connected vehicle solutions.We describe how the GPS-information is sent from the trains in the form of samples and investigate limitations and possibilities with the available information. About three million samples from 83 SJ-trains were analysed and the samples were filtered with the intent of removing erroneous information. We here found that about 30 % of the samples from the trains were unreliable.A solution for how the samples from the trains can be used to create a model of the railway system traveled by the trains is presented. We use a large set of historical samples and use cluster nodes and Hermite curves to generate a graph that represent the railway system with stations, nodes and the railway itself. A fully automatic solution is not presented since it did not fit into the time frame of the thesis; instead we created a simple tool which can be used to manually finish the model of the railway system.Furthermore, we describe how the railway system and the samples from the train can be used to register the routes the trains travel.

This master thesis investigates the possibilities of using GPS-information from trains to create a model of a railway system, register the routes of the the trains and predict how the trains will travel in the railway system.The thesis work was done at Icomera AB which is a company that specializes in internet connected vehicle solutions.We describe how the GPS-information is sent from the trains in the form of samples and investigate limitations and possibilities with the available information. About three million samples from 83 SJ-trains were analysed and the samples were filtered with the intent of removing erroneous information. We here found that about 30 % of the samples from the trains were unreliable.A solution for how the samples from the trains can be used to create a model of the railway system traveled by the trains is presented. We use a large set of historical samples and use cluster nodes and Hermite curves to generate a graph that represent the railway system with stations, nodes and the railway itself. A fully automatic solution is not presented since it did not fit into the time frame of the thesis; instead we created a simple tool which can be used to manually finish the model of the railway system.Furthermore, we describe how the railway system and the samples from the train can be used to register the routes the trains travel.

This master thesis investigates the possibilities of using GPS-information from trains to create a model of a railway system, register the routes of the the trains and predict how the trains will travel in the railway system.The thesis work was done at Icomera AB which is a company that specializes in internet connected vehicle solutions.We describe how the GPS-information is sent from the trains in the form of samples and investigate limitations and possibilities with the available information. About three million samples from 83 SJ-trains were analysed and the samples were filtered with the intent of removing erroneous information. We here found that about 30 % of the samples from the trains were unreliable.A solution for how the samples from the trains can be used to create a model of the railway system traveled by the trains is presented. We use a large set of historical samples and use cluster nodes and Hermite curves to generate a graph that represent the railway system with stations, nodes and the railway itself. A fully automatic solution is not presented since it did not fit into the time frame of the thesis; instead we created a simple tool which can be used to manually finish the model of the railway system.Furthermore, we describe how the railway system and the samples from the train can be used to register the routes the trains travel.

This master thesis investigates the possibilities of using GPS-information from trains to create a model of a railway system, register the routes of the the trains and predict how the trains will travel in the railway system.The thesis work was done at Icomera AB which is a company that specializes in internet connected vehicle solutions.We describe how the GPS-information is sent from the trains in the form of samples and investigate limitations and possibilities with the available information. About three million samples from 83 SJ-trains were analysed and the samples were filtered with the intent of removing erroneous information. We here found that about 30 % of the samples from the trains were unreliable.A solution for how the samples from the trains can be used to create a model of the railway system traveled by the trains is presented. We use a large set of historical samples and use cluster nodes and Hermite curves to generate a graph that represent the railway system with stations, nodes and the railway itself. A fully automatic solution is not presented since it did not fit into the time frame of the thesis; instead we created a simple tool which can be used to manually finish the model of the railway system.Furthermore, we describe how the railway system and the samples from the train can be used to register the routes the trains travel.

This master thesis investigates the possibilities of using GPS-information from trains to create a model of a railway system, register the routes of the the trains and predict how the trains will travel in the railway system.The thesis work was done at Icomera AB which is a company that specializes in internet connected vehicle solutions.We describe how the GPS-information is sent from the trains in the form of samples and investigate limitations and possibilities with the available information. About three million samples from 83 SJ-trains were analysed and the samples were filtered with the intent of removing erroneous information. We here found that about 30 % of the samples from the trains were unreliable.A solution for how the samples from the trains can be used to create a model of the railway system traveled by the trains is presented. We use a large set of historical samples and use cluster nodes and Hermite curves to generate a graph that represent the railway system with stations, nodes and the railway itself. A fully automatic solution is not presented since it did not fit into the time frame of the thesis; instead we created a simple tool which can be used to manually finish the model of the railway system.Furthermore, we describe how the railway system and the samples from the train can be used to register the routes the trains travel.

The study was performed for the Swedish Regional Forestry Board in Södra Götaland. The study examines broadleaf plantations on former farmland that were planted between 1991 and 1996 with subsidy payments for conversion of farmland into forest. In particular, the study reviews forests planted in 1991-92 and 1994-96. In the early 1990s, Swedish agriculture was deregulated and direct subsides to farmers ended. The Swedish state instead granted farmers financial support and offered incentives for conversion of farmland and investments in order to make their unproductive land productive. The state supported conversion of farmland to broadleaf forest, forest for energy biomass production, or establishment of wetlands on former farmland. The County Administrative Boards and Regional Forestry Boards together monitored the planting of broadleaf forests.

Föreliggande studies syfte är att utifrån ett diskursanalytiskt perspektiv undersöka hur företagande kvinnor, som själva beskriver sig som framgångsrika, konstruerar identitet. Detta sker med en kombination av analytiska verktyg från narrativ metod, kategoriseringsanalys och diskursiv psykologi vilka appliceras på data i form av företagande kvinnors blogginlägg. Resultatet visar att respondenterna tenderar att berätta om sig själva genom tre generella berättelser: berättelsen om företagsamheten, berättelsen om familjen och självbekännelseberättelsen och där gör de framför allt tre kategorier relevanta för den egna identiteten: den framgångsrika företagerskan, den goda modern och den moderna kvinnan. Berättelser och kategorier kan mötas och understödja varandra men framför allt kan de också konkurrera med varandra. Den spänning som skapas när berättelserna krockar och när de diskursiva stereotyper som styr kategorierna inte samstämmer kräver en retorisk finkänslighet och ett skickligt balanserande.