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  • 1.
    Lindberg, Rebecca
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Kranse, Mattias
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Tidsloggningssystem för ambulanshelikopterpiloter2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Active duty time is strictly regulated for ambulance helicopter pilots. Departures and arrivals are determined by incoming alarms, which can make active duty time calculations complicated. These calculations are currently done manually, which can generate uncertainty and unnecessary denial of incoming alarms as a result.

    In this work, a pilot study is made for a time management system for ambulance helicopter pilots, with the main purpose to decrease unnecessary denial of incoming alarms. An IT-system is created where a smartphone collects time data which in turn is presented in a web application.

    As a part of the system, the ability to automatically log flight time with a smartphone is explored. A smartphone application with the purpose of automatically logging flight time is made with its basis and ideas retrieved from previous research and data collection. The test result shows that the application logs the same flight time as the helicopter in 5 times out of 6, with the accuracy of one minute.

    For presenting the collected time data, a visualization model is made in the form of a web application based on previous research and established design principles. Testing of the visualization model shows, for the pilots, that it is easier to make an accurate decision under time pressure with the developed visualization model than with a numerical format of the same data. The result is analyzed with a t-test which concludes that the difference between the graphical and table presentation is statistically significant.

  • 2.
    Milutinovic, Goran
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Ahonen-Jonnarth, Ulla
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Decision, Risk and Policy Analysis.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science. Division of Visual Information and Interaction, Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Brandt, S. Anders
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.
    The impact of interactive visualization on trade-off-based geospatial decision-making2019In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 33, no 10, p. 2094-2123Article in journal (Refereed)
    Abstract [en]

    In a previous work we developed GISwaps, a novel method for geospatial decision-making based on Even Swaps. In this paper, we present the results of an evaluation of a visualization framework integrated with this method, implemented within a decision support system. This evaluation is based on two different studies. In the quantitative study, 15 student participants used GISwaps with no visual features, and 15 participants used GISwaps with the integrated visual framework, as the tool in a solar farm site location case study. The results of the quantitative evaluation show positive impact of the visualization in terms of increased coherency in trade-offs. The results also show a statistically significant difference in average trade-off values between the groups, with users from the non-visual group setting on average 20% higher trade-off values compared with the users in the visual group. In the qualitative study, we had one expert in GIS, two experts in decision-making and two experts in solar energy as a focus user group. Data in this study were obtained by observations and semi-structured interviews with the participants. The impact of the visualization framework was assessed positively by all participants in the expert group. 

  • 3.
    Olsson, Simon
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Ett sätt att formellt beskriva och mäta hälsotillståndet på en integrationsplattform2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    An integration platform is a platform that is used to integrate data between two incompatible systems. The architecture is fully adapted to the customers’ requirements and therefore looks different between systems. In order to be able to describe and judge the state of the health of an integration platform, there are many factors to consider. This research has been designed to find out which general factors that should be considered in the assessment and description of the health status of an integration platform. A thorough and detailed research and analysis has been made about the general factors that previous researches has highlighted as important. After that, a big analysis of the detected problems was made in comparison to the general factors to draw parallels, conclusions and common denominators if the detected errors depend on the general factors or not. The goal of this was to confirm the validity of the previous research and see if any new factors appear in this integration platform. Two prototypes have been produced to present an overall picture of the actual health status of the integration platform. These two prototypes are developed using assessment in the systems that using the integration platform. These two prototypes have used several factors and parameters in their assessment. A baseline was developed to represent a value that estimate the normal state of the investigated platform. The estimated baseline is an estimate of the normal state within which response time is assumed to be working. This was made to have a value to compare both current and historical health status in the integration platform. Percentiles were also developed to produce an average value. The 50th percentile was used as a general average value and the 90th percentile is used to illustrate and detect severe deviations. The result of the two prototypes is, respectively, an assessment of the actual health status of the integration platform. For more correctness and more detailed assessment of the actual health state, each subsystem in the researched system should be assessed individually because different subsystems affect each other and the health status different. This can lead to misleading picture of the actual health state of the integration platform. This research has combined all the subsystems in the research system in order to be able to describe and measure the actual state of the integration platform.

  • 4.
    Ren, Zheng
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.
    Jiang, Bin
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Capturing and characterizing human activities using building locations in America2019In: ISPRS International Journal of Geo-Information, ISSN 2220-9964, Vol. 8, no 5, article id 200Article in journal (Refereed)
    Abstract [en]

    Capturing and characterizing collective human activities in a geographic space have become much easier than ever before in the big era. In the past few decades it has been difficult to acquire the spatiotemporal information of human beings. Thanks to the boom in the use of mobile devices integrated with positioning systems and location-based social media data, we can easily acquire the spatial and temporal information of social media users. Previous studies have successfully used street nodes and geo-tagged social media such as Twitter to predict users’ activities. However, whether human activities can be well represented by social media data remains uncertain. On the other hand, buildings or architectures are permanent and reliable representations of human activities collectively through historical footprints. This study aims to use the big data of US building footprints to investigate the reliability of social media users for human activity prediction. We created spatial clusters from 125 million buildings and 1.48 million Twitter points in the US. We further examined and compared the spatial and statistical distribution of clusters at both country and city levels. The result of this study shows that both building and Twitter data spatial clusters show the scaling pattern measured by the scale of spatial clusters, respectively, characterized by the number points inside clusters and the area of clusters. More specifically, at the country level, the statistical distribution of the building spatial clusters fits power law distribution. Inside the four largest cities, the hotspots are power-law-distributed with the power law exponent around 2.0, meaning that they also follow the Zipf’s law. The correlations between the number of buildings and the number of tweets are very plausible, with the r square ranging from 0.53 to 0.74. The high correlation and the similarity of two datasets in terms of spatial and statistical distribution suggest that, although social media users are only a proportion of the entire population, the spatial clusters from geographical big data is a good and accurate representation of overall human activities. This study also indicates that using an improved method for spatial clustering is more suitable for big data analysis than the conventional clustering methods based on Euclidean geometry.

  • 5.
    Sundlöf, Krister
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Visualisering av referensstationsrörelser: En applikation för Swepos2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
  • 6.
    Veiret, Sebastian
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Integration av affärssystem och e-handelssystem2019Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The following study has been performed in association with Monitor ERP System AB, a company that develops an enterprise resource planning system (ERP). Monitor has developed an e-commerce system which is integrated with the ERP system so that articles in the ERP system can be sold from a web shop. When an order is placed in the web shop it is automatically added in the ERP system. A number of Monitor’s customers want to integrate the ERP system with a third-part e-commerce system instead of using the one developed by Monitor for B2C (business to customer) sales.

    In the study, the reasons for this is examined and a prototype and conceptual integration model is developed.

    Interviews with the customers have been performed that has shown that they consider the content management in Monitor’s e-commerce system far too limited. An e-commerce system that they showed interest in was WooCommerce which is a plugin for WordPress. It is for WooCommerce that the prototype and integration model has been created.

    A plugin for WooCommerce has been written that sends orders to the ERP system. To receive the order, a REST service has been developed that receives the order and creates it in the ERP system by using Monitor’s REST API.

  • 7.
    Åsberg, Philip
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Bohlins, Pontus
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Tidig detektering av skogsbränder med hjälp av högupplöst data: Automatisk identifiering med hjälp av bildbehandling2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    It is very difficult to discover forest fires in an early stage which can lead to devastat-ing consequences. Today, 30% of the total carbon dioxide that is released in the at-mosphere comes from forest fires. Thousands of human beings and animals are killed or forced to leave their homes every year. There are a variety of techniques today that is being used for discovering forest fires but whom lack in accuracy or has problems with a large amount of false alarms. This paper is an experimental study to try to solve this issue. The proposed method in this paper could be applied on UAV (Unmanned Arial Vehicles). This study will focus on identifying smoke regions from forest fires and removing fog objects which has similar characteristics as smoke. Two algorithms are tested, SDA (Statistical distributions algorithm) and KBA (Knowledge-based identification algorithm). The SDA uses statistic distribution al-gorithm where smoke and fogs characteristics are identified. The second algorithm, KBA, is a knowledge-based algorithm, where the shape, area and edges of the smoke’s characteristics are applied. The algorithm showed a 90 % accuracy for find-ing smoke in images with a false alarm rate of 20 % in images of fog.

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