The capability of the Swedish Armed Forces has been reduced to such an extent that the Armed Forces most likely cannot cope with health care within its own organization in the event of an armed attack on the country. The project Totalförsvarets sjukvårdssystem (The healthcare system of the total defence), initiated in 2015 by the Swedish Armed Forces and the National Board of Health and welfare, did a review of Sweden´s medical capacity, its limitations and needs at peace, crisis and armed conflict. However, the project did not profoundly review the conditions of military medicine for armed conflicts, the capacity of military medical planning and how the military medical capacity affects the planning and implementation of operations. This knowledge gap is not filled by available research or other source of information. The purpose of this work is to fill this gap through a qualitative method via interviews and text analysis. The work is supported by Moshe Kress's logistics theory of valuation of plans; macro- and micro-level subdivision in the planning process and need for information for medical planning. To adapt Moshe Kress's theory to the military medicine a theory development has been made. The result of the work shows that the capacity of military medicine is insufficient and that medical planners are not obvious partners in national military planning. This will probably effect both planning and execution through lack of credibility and fighting morale. This can also have a negative impact on the will to defend Sweden. Research in military medicine for the purpose of this work is limited. A probable cause may be that there is lack of basic research in the field of military medicine and that information about capacity, capabilities and limitations is mainly confidential.

This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. The literature review finds a notable gap in comprehensive image datasets addressing the image artefact spectrum of ADAS-equipped automotive cameras under real-world driving conditions. In this study, normal and fault scenarios for automotive cameras are defined leveraging published and company studies and a fault diagnosis model using unsupervised learning is proposed and examined. The types of image faults defined and included are Lens Flare, Gaussian Noise and Dead Pixels. Along with normal driving images, a balanced fault-injected image dataset is collected using real-time sensor simulation under driving scenario with industrially-recognised HIL setup. An AAE-based unsupervised automotive camera fault diagnosis system using VGG16 as encoder-decoder structure is proposed and experiments on its performance are conducted on both the selfcollected dataset and fault-injected KITTI raw images. For non-processed KITTI dataset, morphological operations are examined and are employed as preprocessing. The performance of the system is discussed in comparison to supervised and unsupervised image partition methods in related works. The research found that the AAE method outperforms popular VAE method, using VGG16 as encoder-decoder structure significantly using 3-layer Convolutional Neural Network (CNN) and ResNet18 and morphological preprocessings significantly ameliorate system performance. The best performing VGG16- AAE model achieves 62.7% accuracy to diagnosis on own dataset, and 86.4% accuracy on double-erosion-processed fault-injected KITTI dataset. In conclusion, this study introduced a novel scheme for collecting automotive sensor data using Hardware-in-Loop, utilised preprocessing techniques that enhance image partitioning and examined the application of unsupervised models for diagnosing faults in automotive cameras. / Denna avhandling syftar till att undersöka ett felupptäcknings- och diagnossystem för bilkameror med hjälp av oövervakad inlärning. De huvudsakliga forskningsfrågorna är om en bilduppsättning från en frontmonterad vidvinkelkamera kan skapas med hjälp av Hardware-in-Loop (HIL)-simulationer, om en Adversarial Autoencoder (AAE)-baserad metod för oövervakad felupptäckt och diagnos för SPA2 Vehicle Control Unit (VCU) kan utformas med en bilduppsättning skapad med Hardware-in-Loop, och om användningen av AAE skulle överträffa prestandan av att använda Variational Autoencoder (VAE) för den oövervakade modellen för felanalys i bilkameror. Befintliga studier om felanalys fokuserar på roterande maskiner, luftbehandlingsenheter och järnvägsfordon. Få studier undersöker definitionen av feltyper i bilkameror och klassificerar normala och felaktiga bilddata från kameror i kommersiella passagerarfordon. I denna studie definieras normala och felaktiga scenarier för bilkameror och en modell för felanalys med oövervakad inlärning föreslås och undersöks. De typer av bildfel som definieras är Lens Flare, Gaussiskt brus och Döda pixlar. Tillsammans med normala bilder samlas en balanserad uppsättning felinjicerade bilder in med hjälp av realtidssensor-simulering under körscenarier med industriellt erkänd HIL-uppsättning. Ett AAE-baserat system för oövervakad felanalys i bilkameror med VGG16 som kodaredekoderstruktur föreslås och experiment på dess prestanda genomförs både på den självinsamlade uppsättningen och felinjicerade KITTI-raw-bilder. För icke-behandlade KITTI-uppsättningar undersöks morfologiska operationer och används som förbehandling. Systemets prestanda diskuteras i jämförelse med övervakade och oövervakade bildpartitioneringsmetoder i relaterade arbeten. Forskningen fann att AAE-metoden överträffar den populära VAEmetoden, genom att använda VGG16 som kodare-dekoderstruktur signifikant med ett 3-lagers konvolutionellt neuralt nätverk (CNN) och ResNet18 och morfologiska förbehandlingar förbättrar systemets prestanda avsevärt. Den bäst presterande VGG16-AAE-modellen uppnår 62,7 % noggrannhet för diagnos på egen uppsättning, och 86,4 % noggrannhet på dubbelerosionsbehandlad felinjicerad KITTI-uppsättning. Sammanfattningsvis introducerade denna studie ett nytt system för insamling av data från bilsensorer med Hardware-in-Loop, utnyttjade förbehandlingstekniker som förbättrar bildpartitionering och undersökte tillämpningen av oövervakade modeller för att diagnostisera fel i bilkameror.

This study is based on the presumption that language is fundamental to the construction of knowledge. In addition, linguistic demands are incorporated in the policy documents of the upper secondary edu­cation of Sweden; students shall, during their education, be given the opportunity to appropriate certain linguistic tools. The purpose of this thesis is to investigate how teachers and students in upper secondary education manage and utilize the discourse of social science in both speech and writing. More specifically, two classes are studied during three terms. The teachers’ ability to organize and support the students vocally and in written is examined, so are the effects of the teaching on students’ writing. The origin of the study is constituted by a sociocultural stance provided by Vygotskij, Bakhtin and Halliday. A combination of a functional perspective on language and a cognitive is probed, where the study is comparative in nature consisting of an experimental class and a control class. The importance of language for the creation of knowledge has been communicated to the teachers of the experimen­tal class, with provided complementary subject didactic literature. This literature offers support for teachers to augment the use of explicit teaching and enhance student awareness of how conceptual structures mould social science. Qualitative analyses are performed on the basis of teacher-student dialogue and written tasks by a group of selected students. The ana­lytical tools object language – metalanguage, linguistic operations and knowledge structures are developed for the purpose of processing data, and have been combined with the tools activity analysis, subject-related concepts and text activity. The results from the analyses display no difference in the handling of the discourse of social science between the experimental class and the control class. The teachers of the experimental class, like the teacher of the control class, are primarily utilizing object language where knowledge structures are visible, as opposed to a combination of object language – metalanguage. Furthermore, they exhibit diminutive use of dialogue in their teaching. The students of both classes, on their hand, demon­strate an equal progress in textual development. This study concludes that the experimental class has not been provided with sufficiently explicit support to advance in the struc­turing of knowledge and in level of reasoning. A more efficient support to teachers to manage these analytical tools would, in all probability, give them, and through this the students, an increasingly profound insight into structuring of text activities, the meaning and signalling of linguistic operations, the construction of subject-related concepts and, most importantly, how these three tools are interrelated.

Historically 3D game environments have almost always been immutable. Mutable environments are a technical challenge that will affect performance. For games of the future to continue approaching realism, mutable environments are an essential step. Popularized by the game title Minecraft (2009), the use of voxel engines in games has become increasingly common. However, by the nature of the discrete position of voxels, the method is limited in representing arbitrary polyhedral shapes like angled slopes. It also prohibits smooth mutations including proper movement and rotation of objects within the voxelization. This is generally mitigable with more voxels. However, this paper proposes a more precise solution to the problem. A tetrahedral mesh engine (tetra engine). By altering tetrahedral topology, vertex positions, and material of individual tetrahedrons, tetras are intended to solve the issue of arbitrary polyhedral shapes for voxels. Additionally, the tetrahedral mesh shows other promises such as providing a robust collision detection method and as an acceleration structure for e.g. raycasting. The research question can be summarized as investigating the feasibility of a tetra engine as a mutable game environment. 3 sub-research questions are given: The first regarding performance, the second regarding robustness, and the third different types mutations. The research questions are addressed along with a proof of concept (POC). The POC intends to investigate a proposal for the most efficient robust solution possible for the most basic mutation type known as edits. Because of time constraints, it does not cover all parts of the research questions but works as a bottom-up approach to understand what is required to realize a full-fledged tetra engine. Thus, a large part of the research question is answered theoretically both hypothetically with grounds from the POC and through previous work. The result shows a much more critical robustness consideration than expected and suggests relying on slower but more robust algorithms that are known to work. In conclusion, nothing suggests that a scalable future-proof tetra engine is impossible, but the algorithms required are much less efficient than those for voxels and robustness is an issue to overcome. However, numerous hypothetical advantages particularly regarding deformation and fluid simulation are still recognized and it is not obvious that future mutable environments would not benefit from a tetra engine rather than voxels. / Historiskt sätt har 3D-datorspelmiljöer nästan uteslutande varit oföränderliga. Det finns goda anledningar till detta. Föränderliga miljöer är en teknisk utmaning som påverkar speleffektiviteten. Om man däremot vill fortsätta utveckla mer realistiska datorspel är föränderliga spelmiljöer ett naturligt steg. Spelet Minecraft (2009) populariserade användandet av voxlar i datorspel vars material kan ändras för att förändra miljön. Sedan dess har voxlar i datorspel blivit mer och mer populära. Dock, på grund av voxlars diskreta positioner har de begränsningar i dess förmåga att representera godtyckliga polyedriska former så som arbiträrt vinklade plan. Detta omöjliggör även mjuka rörelser inklusive rörelse och rotering inom voxeliseringen. Det här problemet kan generellt dämpas med hjälp av mindre och fler voxlar. Men, för att lösa problemet ordentligt föreslår den här rapporten en annan lösning, nämligen en tetrahedrisk-mesh-motor (tetramotor). Genom att ändra tetraedrisk topologi, hörn positioner, samt material av individuella tetraedrar ska tetrorna kunna forma arbiträra polyedriska former och lösa problemet med voxlar. Utöver detta visar en tetraedrisk mesh andra intressanta möjligheter likt en metod för robust kollisions hantering och som en accelereringsstruktur för till exempel ray-casting. Forskningsfrågan kan sammanfattas som att utforska tillämpbarheten av en tetramotor för föränderliga datorspelsmiljöer. Tre underfrågor ges: Den första handlar om beräkningseffektivitet, den andra angående robusthet och den tredje oliky typer av mutationer. Forskningsfrågorna angrips med hjälp av en proof of concept lösning (POC). POC:en är menad att utforska ett förslag på en effektiv och robust metod för direkta förändringar. På grund av tidsbegränsningar så täcker inte POC:en alla delar av frågeställningarna men är menad som en botten upp lösning för att inse och förstå kraven för en komplett tetramotor. På grund av detta är en stor del av forskningsfrågorna svarade teoretiskt, både hypotetiskt baserat på insikterna från POC:en och med grund från tidigare forskning. Resultatet visar en mycket mer kritisk hänsyn till robusthet än förväntat och föreslår att man använder sig av långsammare men fungerande existerande lösningar. Slutsatsen är att inget tyder på att en skalbar framtidssäker tetramotor är en omöjlighet, men att algoritmerna är mycket långsammare än de som krävs för voxlar. Däremot finns potentieally fördelar med en tetra motor, främst med hänsyn till deformering och flödessimulering. Det är därför inte självklart att framtida muterbara spelmijöer inte skulle ha fördelar av en tetramotor istället för voxlar.