5 resultados para Steam Trains

em Dalarna University College Electronic Archive


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Wider economic benefits resulting from extended geographical mobility is one argument for investments in high-speed rail. More specifically, the argument for high-speed trains in Sweden has been that they can help to further spatially extend labor market regions which in turn has a positive effect on growth and development. In this paper the aim is to cartographically visualize the potential size of the labor markets in areas that could be affected by possible future high-speed trains. The visualization is based on the forecasts of labor mobility with public transport made by the Swedish national mobility transport forecasting tool, SAMPERS, for two alternative high-speed rail scenarios. The analysis, not surprisingly, suggests that the largest impact of high-speed trains results in the area where the future high speed rail tracks are planned to be built. This expected effect on local labor market regions of high-speed trains could mean that possible regional economic development effects also are to be expected in this area. However, the results, in general, from the SAMPERS forecasts indicaterelatively small increases in local labor market potentials.

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Banverket Trafik has a responsibility to make sure that the companies who traffic the Swedish railroad have the correct information about the status of the railroad. One of Banverket Trafiks information systems (Opera) presents the train’s actual position on a map and provides the user with physical information about the trains. Due to increasing demands on the information systems, Banverket Trafik needs to update the present system architecture in order to manage the increasing demands on map graphics and map functions. This paper analysis the information system Opera on the basis of theory and support of methods and discuss problems and demands for Opera. Further we investigate three GIS products to se if they meet the demands. Information about the products was gathered from both supplier and independent users to get a just picture of the products potentials. This paper comprises a suggestion of new system architecture that meet these needs. The suggested system architecture is capable of handling the map graphics and the map’s functions of more than one information system. Hopefully more than one information system will use the suggested system architecture as a map service.

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This paper used a qualitative technique from a social scientific perspective, a model based on Hewitt and his theory of the self-concept. The purpose of this study was to investigate why some elite athletes experience troublesome periods after their career ending. Interviews were performed with five elite athletes with varying experiences after career ending. The length of the elite athlete careers vary between 7 to 17 years. Two groups were made based upon experiences after career ending. Group 1 had experienced problems, for example suicide tendency, and group 2 had not. The result shows that a troublesome period can come up independently of career ending. The self-concept was investigated during the career and further different kind of variables which could affect the self as training and competition, social relations both before and after termination from sport. Result indicates that an individual in group 2 who has a high complexity in the self-concept based upon significant others outside the elite sport during the career copes with the new situation after career ending much better than group 1 who have not. To build up the self based only upon significant others in the elite sport seems to give expression in a strengthen self. Intensity in training and competition did not have a connection with a troublesome period after retirement from sport but it could prevent establishing contact with others outside the elite sport and reduce a high complexity in the self-concept. The result further shows that elite athletes who practise an individual sport trains in to a greater extent than elite athletes in a seasonal sport. Result also shows that practising a sport with one day off a week, contributes to better opportunities for developing a higher complexity in the self-concept. Suspicions has also rouse that practising an elite sport on the highest level can lead to extensive focusing that further leads to social isolation from individuals outside elite sport. To build up the self upon significant others outside elite sport during the career and keep in touch with significant others from elite sport after the career seems to be the key to avoid problems after the career ending. Suggestions about further investigations are made to see if medial exposure and status can affect the self.

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Train dispatchers faces lots of challenges due to conflicts which causes delays of trains as a result of solving possible dispatching problems the network faces. The major challenge is for the train dispatchers to make the right decision and have reliable, cost effective and much more faster approaches needed to solve dispatching problems. This thesis work provides detail information on the implementation of different heuristic algorithms for train dispatchers in solving train dispatching problems. The library data files used are in xml file format and deals with both single and double tracks between main stations. The main objective of this work is to build different heuristic algorithms to solve unexpected delays faced by train dispatchers and to help in making right decisions on steps to take to have reliable and cost effective solution to the problems. These heuristics algorithms proposed were able to help dispatchers in making right decisions when solving train dispatching problems.

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Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.