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Inskrivningsprocessen av lagfart/tinglysing är en del av vad inskrivningsmyndigheterna arbetar med i Sverige och Norge. Lagfart/tinglysing finns till för att visa vem/vilka som är rättslig(a) ägare till en fastighet. Vilket är väldigt viktigt för att hålla koll vem som är ansvarig för fastigheten. Att ha en inskrivningsprocess som är säker, effektiv och som har en låg kostnad är viktigt för att ha fungerande system för både köpare, säljare, företag och myndigheter. Syftet med studien är att undersöka skillnaden mellan Sveriges och Norges inskrivningsprocess vid lagfart/tinglysings ansökan. Men även att jämföra fördelar och nackdelar med processen. De krav som krävs för att bevilja lagfart undersökts också för att den ska bli rättssäker eller om det finns behov att förändra dessa. Studien undersöker även om det går att effektivisera inskrivningsprocessen samt hur det skulle påverka rättssäkerheten. För att besvara frågeställningarna har en kvalitativ metod använts. Metoden utgörs av en enkätundersökning, intervjuer och en jämförelse. I jämförelsen har information från litteraturen inhämtats, medan intervjuer och enkäter har genomförts med sakkunniga i respektive land. Resultatet av studien visar att mer digitalisering av inskrivningsprocessen skulle innebära säkrare och effektivare inskrivningsprocess av lagfarter/tinglysingar för fastigheter. Studien visar även att lagändringar är det som behöver ändras för att möjliggöra mer digitalisering. Lagstiftningarna i bägge länder bygger på föråldrade lagar när det inte fanns elektroniska alternativ. / The registration process of lagfart/tinglysing is part of what the registration authorities working with in Sweden and Norway. Lagfart/tinglysing is available to show who/which is the legal owner of a property. Which is very important to keep track of who is responsible for the property. Having an enrollment process that is secure, efficient and has a low cost is important for having a functioning system for both buyers, sellers, companies and authorities. The purpose of the study is to investigate the difference between Sweden's and Norway's enrollment process in lagfart/tinglysings. But also, to compare the advantages and disadvantages of the process. The requirements required to grant lagfart/tinglysing have also been examined for it to be legally secure or if there is a need to change these. The study also examines whether it is possible to streamline the enrollment process and how it would affect legal certainty. A qualitative method has been used to answer the questions. The method consists of a survey, interviews and a comparison. In the comparison, information from the literature has been obtained, while interviews and questionnaires have been conducted with experts in each country. The results of the study show that more digitization of the registration process would mean a safer and more efficient registration process of legal deeds / registrations for properties. The study also shows that changes in the law are what need to be changed to enable more digitization. Legislation in both countries is based on outdated laws when there were no electronic alternatives.

Cancer is one of the leading causes of death in the world, but advances in research and development of treatment methods is constantly ongoing to reduce the number of deaths and the amount of suffering. One of many approaches is radiation therapy, which uses high doses of radiation to kill tumors. Radiation therapy requires advanced software in image analysis to create careful treatment plans, evaluate treatment responses and to perform dose accumulation, among other things. One important tool for this is deformable image registration (DIR) which is used to find a correspondence between the images. The aim with this master thesis is to improve the DIR method ANACONDA by automatically provide additional information to the algorithm before the registration is performed.This work focuses on the registration of internal tubular structures in lung and liver images (bronchial and vascular tree, respectively). Two challenges in registering lung images are the sliding motion of lung surfaces and large motion of small internal structures. Several DIR methods have been proposed for solving the challenging internal structures, however most of them do not take into account the alignment of surrounding tissues. DIR methods applied to the liver are published less frequently, but accurate registration of the liver is of high interest since, for example, knowledge of the anatomy of the vascular tree is essential when removing tumors through liver surgeries. In this work, corresponding (anatomical) points are automatically found in two images and added to the DIR algorithm. The points are found by extracting and comparing the tubular structures between the images, and with use of different distance requirements, nearby points are paired.The new method manages to achieve good registration of both internal structures and surrounding tissue. Mean target registration errors for the internal structures of lungs was 1.11 ± 0.75 and for liver 1.67 ± 1.15 mm.

Robot mapping is a major field of research in robotics. Its basic task is to combine (register) spatial data, usually gained from range devices, to a single data set. This data set is called global map and represents the environment, observed from different locations, usually without knowledge of their positions. Various approaches can be classified into groups based on the type of sensor, e.g. Lasers, Microsoft Kinect, Stereo Image Pair. A major disadvantage of current methods is the fact, that they are derived from hardly scalable 2D approaches that use a small amount of data. However, 3D sensing yields a large amount of data in each 3D scan. Autonomous mobile robots have limited computational power, which makes it harder to run 3D robot mapping algorithms in real-time. To remedy this limitation, the proposed research uses mid-level geometric features (lines and ellipses) to construct 3D geometric primitives (planar patches, cylinders, spheres and cones) from 3D point data. Such 3D primitives can serve as distinct features for faster registration, allowing real-time performance on a mobile robot. This approach works in real-time, e.g. using a Microsoft Kinect to detect planes with 30 frames per second. While previous approaches show insufficient performance, the proposed method operates in real-time. In its core, the algorithm performs a fast model fitting with a model update in constant time (O(1)) for each new data point added to the model using a three stage approach. The first step inspects 1.5D sub spaces, to find lines and ellipses. The next stage uses these lines and ellipses as input by examining their neighborhood structure to form sets of candidates for the 3D geometric primitives. Finally, candidates are fitted to the geometric primitives. The complexity for point processing is O(n); additional time of lower order is needed for working on significantly smaller amount of mid-level objects. The real-time performance suggests this approach as a pre-processing step for 3D real-time higher level tasks in robotics, like tracking or feature based mapping. In this thesis, I will show how these features are derived and used for scene registration. Optimal registration is determined by finding plane-feature correspondence based on mutual similarity and geometric constraints. Our approach determines the plane correspondence in three steps. First step computes the distance between all pairs of planes from the first scan to all pair of planes from the second scan. The distance function captures angular, distance and co-planarity differences. The resulting distances are accumulated in a distance matrix. The next step uses the distance matrix to compute the correlation matrix between planes from the first and second scan. Finally plane correspondence is found by finding the global optimal assignment from the correlation matrix. After finding the plane correspondence, an optimal pose registration is computed. In addition to that, I will provide a comparison to existing state-of-the-art algorithms. This work is part of an industry collaboration effort sponsored by the National Institute of Standards and Technology (NIST), aiming at performance evaluation and modeling of autonomous navigation in unstructured and dynamic environments. Additional field work, in the form of evaluation of real robotic systems in a robot test arena was performed. / Computer and Information Science / Accompanied by two .mp4 files.

In this thesis, multiple on-road vehicle tracking problem is explored, with greater consideration of road constraints and interactions between vehicles. A comprehensive method for tracking multiple on-road vehicles is proposed by making use of domain knowledge of on-road vehicle motion. Starting with raw measurements provided by sensors, bias correction methods for sensors commonly used in vehicle tracking are briefly introduced and a fast but effective bias correction method for airborne video sensor is proposed. In the proposed method, by assuming errors in sensor parameter measurements are close to zero, the bias is separately addressed in converted measurements of target position by a linear term of errors in sensor parameter measurements. Based on this model, the bias is efficiently estimated by addressing it while tracking or using measurements of targets that are observed by multiple airborne video sensors simultaneously. The proposed method is compared with other airborne video bias correction methods through simulations. The numerical results demonstrate the effectiveness of the proposed method for correcting bias as well as its high computational efficiency. Then, a novel tracking algorithm that utilizes domain knowledge of on-road vehicle motion, i.e., road-map information and interactions among vehicles, by integrating a car-following model into a road coordinate system, is proposed for tracking multiple vehicles on single-lane roads. This algorithm is extended for tracking multiple vehicles on multi-lane roads: The road coordinate system is extended to two-dimension to express lanes on roads and a lane-changing model is integrated for modeling lane-changing behavior of vehicles. Since the longitudinal and lateral motions are mutually dependent, the longitudinal and lateral states of vehicles are estimated sequentially in a recursive manner. Two estimation strategies are proposed: a) The unscented Kalman filter combined with the multiple hypothesis tracking framework to estimate longitudinal and lateral states of vehicles, respectively. b) A unified particle filter framework with a specifically designed computationally-efficient joint sampling method to estimate longitudinal and lateral states of vehicles jointly. Both of two estimation methods can handle unknown parameters in motion models. A posterior Cramer-Rao lower bound is derived for quantifying achievable estimation accuracy in both single-lane and multi-lane cases, respectively. Numerical results show that the proposed algorithms achieve better track accuracy and consistency than conventional multi-vehicle tracking algorithms, which assumes that vehicles move independently of one another. / Thesis / Doctor of Philosophy (PhD)

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Yes / In recent years, there has been a focus in social psychology on efforts to improve the robustness, rigour, transparency and openness of psychological research. This has led to a plethora of new tools, practices and initiatives that each aim to combat questionable research practices and improve the credibility of social psychological scholarship. However, the majority of these efforts derive from quantitative, deductive, hypothesis-testing methodologies, and there has been a notable lack of in-depth exploration about what the tools, practices and values may mean for research that uses qualitative methodologies. Here, we introduce a Special Section of BJSP: Open Science, Qualitative Methods and Social Psychology: Possibilities and Tensions. The authors critically discuss a range of issues, including authorship, data sharing and broader research practices. Taken together, these papers urge the discipline to carefully consider the ontological, epistemological and methodological underpinnings of efforts to improve psychological science, and advocate for a critical appreciation of how mainstream open science discourse may (or may not) be compatible with the goals of qualitative research.