This study investigates the diachronic shift of revised card texts in the tabletop collectible card game ‘Magic: The Gathering’.  The lexicogrammatical patterns found are compared to theories on comprehension and learning, and to the development of the game. To answer how the texts have changed, a sample of twenty cards with old and revised texts has been analysed according to systemic functional linguistics. The metafunctions used for the SFL analysis are interpersonal, ideational and textual. Additionally, a descriptive analysis has been conducted to answer how the changes in the linguistic metafunctions relate to comprehension and development. The analysis shows that there are general patterns within all the investigated metafunctions, which correspond to research on learning, language development and notions on text cohesion. Furthermore, the findings correlate to the game development and functions in the gameplay. While the sample size is limited in comparison to all available cards in the game, the diachronic shifts are distributed over a variety of card types matching the available cards overall, and with the initial interconnections found it is assumed that the patterns are generalisable. Further research could explore the findings in relation to general games development, games as a source of learning or genre and discourses.

Random walks on graphs are an essential base for crucial algorithms for solving problems, like the boolean satisfiability problem. A speedup of random walks could improve these algorithms. The quantum version of the random walk, quantum walk, is faster than random walks in specific cases, e.g., on some linear graphs. An analysis of when the quantum walk is faster than the random walk can be accomplished analytically or by simulating both the walks on the graph. The problem arises when the graphs grow in size and connectivity. There are no known general rules for what an arbitrary graph not having explicit symmetries should exhibit to promote the quantum walk. Simulations will only answer the question for one single case, and will not provide any general rules for properties the graph should have. Using artificial neural networks (ANNs) as an aid for detecting when the quantum walk is faster on average than random walk on graphs, going from an initial node to a target node, has been done before. The quantum speedup may not be more than polynomial if the initial state of the quantum walk is purely in the initial node of the graph. We investigate starting the quantum walk in various superposition states, with an additional auxiliary node, to maybe achieve a larger quantum speedup. We suggest different ways to add the auxiliary node and select one of these schemes for use in this thesis. The superposition states examined are two stabiliser states and two magic states, inspired by the Gottesman-Knill theorem. According to this theorem, starting a quantum algorithm in a magic state may give an exponential speedup, but starting in a stabilizer state cannot give an exponential speedup, given that only gates from the Clifford group are used in the algorithm, as well as measurements are performed in the Pauli basis. We show that it is possible to train an ANN to classify graphs into what quantum walk was the fastest for various initial states of the quantum walk. The ANN classifies linear graphs and random graphs better than a random guess. We also show that a convolutional neural network (CNN) with a deeper architecture than earlier proposed for the task, is better at classifying the graphs than before. Our findings pave the way for automated research in novel quantum walk-based algorithms. / Slumpvandringar på grafer är essensiella i viktiga algoritmer för att lösa olika problem, till exempel SAT, booleska uppfyllningsproblem (the satisfiability problem). Genom att göra slumpvandringar snabbare går det att förbättra dessa algoritmer. Kvantversionen av slumpvandringar, kvantvandringar, har visats vara snabbare än klassiska slumpvandringar i specifika fall, till exempel på vissa linjära grafer. Det går att analysera, analytiskt eller genom att simulera vandringarna på grafer, när kvantvandringen är snabbare än slumpvandingen. Problem uppstår dock när graferna blir större, har fler noder samt fler kanter. Det finns inga kända generella regler för vad en godtycklig graf, som inte har några explicita symmetrier, borde uppfylla för att främja kvantvandringen. Simuleringar kommer bara besvara frågan för ett enda fall. De kommer inte att ge några generella regler för vilka egenskaper grafer borde ha. Artificiella neuronnät (ANN) har tidigare används som hjälpmedel för att upptäcka när kvantvandringen är snabbare än slumpvandingen på grafer. Då jämförs tiden det tar i genomsnitt att ta sig från startnoden till slutnoden. Dock är det inte säkert att få kvantacceleration för vandringen om initialtillståndet för kvantvandringen är helt i startnoden. I det här projektet undersöker vi om det går att få en större kvantacceleration hos kvantvandringen genom att starta den i superposition med en extra nod. Vi föreslår olika sätt att lägga till den extra noden till grafen och sen väljer vi en för att använda i resen av projektet. De superpositionstillstånd som undersöks är två av stabilisatortillstånden och två magiska tillstång. Valen av dessa tillstånd är inspirerat av Gottesmann- Knill satsen. Enligt satsen så kan en algoritm som startar i ett magiskt tillstånd ha en exponetiell uppsnabbning, men att starta i någon stabilisatortillstånden inte kan ha det. Detta givet att grindarna som används i algoritmen är från Cliffordgruppen samt att alla mätningar är i Paulibasen. I projektet visar vi att det är möjligt att träna en ANN så att den kan klassificera grafer utifrån vilken kvantvandring, med olika initialtillstånd, som var snabbast. Artificiella neuronnätet kan klassificera linjära grafer och slumpmässiga grafer bättre än slumpen. Vi visar också att faltningsnätverk med en djupare arkitektur än tidigare föreslaget för uppgiften är bättre på att klassificera grafer än innan. Våra resultat banar vägen för en automatiserad forskning i nya kvantvandringsbaserade algoritmer.

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This study examines the total cumulative return and the total risk-adjusted return for OMXSPI and the two investment strategies The Magic Formula and The Acquirer’s Multiple. The aim is to find out if it’s possible to beat the market over time in contradiction to the efficient market hypothesis. Data has been collected to cover a 15-year period between 2005 and 2020. The results end up challenging the efficient market hypothesis with higher total cumulative returns, but also fairly convincingly higher risk-adjusted returns from the strategies. The study also found that the Acquirer’s Multiple outperformed the Magic Formula with regards to both measures.

Autonomous vehicles have gained much importance over the last decade owing to their promising capabilities like improvement in overall traffic flow, reduction in pollution and elimination of human errors. However, when it comes to long-distance transportation or working in complex isolated environments like mines, various factors such as safety, fuel efficiency, transportation cost, robustness, and accuracy become very critical. This thesis, developed at the Connected and Autonomous Systems department of Scania AB in association with KTH, focuses on addressing the issues related to fuel efficiency, robustness and accuracy of an autonomous heavy-duty truck used for mining applications. First, in order to improve the state prediction capabilities of the simulation model, a comparative analysis of two dynamic bicycle models was performed. The first model used the empirical PAC2002 Magic Formula (MF) tyre model to generate the tyre forces, and the latter used a piece-wise Linear approximation of the former. On top of that, in order to account for the nonlinearities and time delays in the lateral direction, the steering dynamic equations were empirically derived and cascaded to the vehicle model. The fidelity of these models was tested against real experimental logs, and the best vehicle model was selected by striking a balance between accuracy and computational efficiency. The Dynamic bicycle model with piece-wise Linear approximation of tyre forces proved to tick-all-the-boxes by providing accurate state predictions within the acceptable error range and handling lateral accelerations up to 4 m/s2. Also, this model proved to be six times more computationally efficient than the industry-standard PAC2002 tyre model. Furthermore, in order to ensure smooth and accurate driving, several Model Predictive Control (MPC) formulations were tested on clothoid-based Single Lane Change (SLC), Double Lane Change (DLC) and Truncated Slalom trajectories with added disturbances in the initial position, heading and velocities. A linear time-varying Spatial error MPC is proposed, which provides a link between spatial-domain and time-domain analysis. This proposed controller proved to be a perfect balance between fuel efficiency which was achieved by minimising braking and acceleration sequences and offset-free tracking along with ensuring that the truck reached its destination within the stipulated time irrespective of the added disturbances. Lastly, a comparative analysis between various Prediction-Simulation model pairs was made, and the best pair was selected in terms of its robustness to parameter changes, simplicity, computational efficiency and accuracy. / Under det senaste årtiondet har utveckling av autonoma fordon blivit allt viktigare på grund av de stora möjligheterna till förbättringar av trafikflöden, minskade utsläpp av föroreningar och eliminering av mänskliga fel. När det gäller långdistanstransporter eller komplexa isolerade miljöer så som gruvor blir faktorer som bränsleeffektivitet, transportkostnad, robusthet och noggrannhet mycket viktiga. Detta examensarbete utvecklat vid avdelningen Connected and Autonomous Systems på Scania i samarbete med KTH fokuserar på frågor gällande bränsleeffektivitet, robusthet och exakthet hos en autonom tung lastbil i gruvmiljö. För att förbättra simuleringsmodellens tillståndsprediktioner, genomfördes en jämförande analys av två dynamiska fordonsmodeller. Den första modellen använde den empiriska däckmodellen PAC2002 Magic Formula (MF) för att approximera däckkrafterna, och den andra använde en stegvis linjär approximation av samma däckmodell. För att ta hänsyn till ickelinjäriteter och laterala tidsfördröjningar inkluderades empiriskt identifierade styrdynamiksekvationer i fordonsmodellen. Modellerna verifierades mot verkliga mätdata från fordon. Den bästa fordonsmodellen valdes genom att hitta en balans mellan noggrannhet och beräkningseffektivitet. Den Dynamiska fordonsmodellen med stegvis linjär approximation av däckkrafter visade goda resultat genom att ge noggranna tillståndsprediktioner inom det acceptabla felområdet och hantera sidoacceleration upp till 4 m/s2 . Den här modellen visade sig också vara sex gånger effektivare än PAC2002-däckmodellen. v För att säkerställa mjuk och korrekt körning testades flera MPC varianter på klotoidbaserade trajektorier av filbyte SLC, dubbelt filbyte DLC och slalom. Störningar i position, riktining och hastighet lades till startpositionen. En MPC med straff på rumslig avvikelse föreslås, vilket ger en länk mellan rumsdomän och tidsdomän. Den föreslagna regleringen visade sig vara en perfekt balans mellan bränsleeffektivitet, genom att minimering av broms- och accelerationssekvenser, och felminimering samtidigt som lastbilen nådde sin destination inom den föreskrivna tiden oberoende av de extra störningarna. Slutligen gjordes en jämförande analys mellan olika kombinationer av simulerings- och prediktionsmodell och den bästa kombinationen valdes med avseende på dess robusthet mot parameterändringar, enkelhet, beräkningseffektivitet och noggrannhet.

Cities involve several systems that work together as a network of urban relationships. These systems are in balance, and they work as a whole that articulates urban life. But what makes a city memorable and special are its events: those magical situations where the uniformity of the experience stops and something unique arise. Those are the moments where our memory is deeply engraved by a particular situation that will come back in our dreams and imaginative processes as an agent image. Four urban events — a space for film edition and writing, an urban stage, a footage archive and park, and a projection space- whose locations have been determined by a Cartesian game dictated by the Plan of Washington DC; and one common discipline, Film, will be the main focus of this research and a way of understanding the relations among Memory and its spaces, Architecture and Film in the City. Each event will respond to the particularities of its context by understanding first the sites and their relation with the city. These sites will be located in the four quadrants of Washington DC- NE, SE, SW and NW- and they will be consider as different communities that, by keeping their own idiosyncrasy, create one city. The question of urban scale as well as the concept of detail as part of an architectural cosmology will be present throughout the process of the thesis by the alternation of micro and macro analysis of each stage of the research. The question of scale will be present as well when comparing the four projects with their differences in shape and size. Characterization and monstrosity as architectural concepts will be incorporated into the project too, by understanding the role of Architecture in the city and what it wants to show or "monstrare" to its inhabitants. / Master of Architecture

Through parallelism with characteristics of magical realism, the building is materialized by deciphering the unseen images latent in ordinary life. WAAC radio station. Old Town, Alexandria, Virginia. / Master of Architecture

This thesis research explores the patterns of player-character relationships and player-character attachment in Animal Crossing: New Horizons (2020) and Genshin Impact (2020). The purpose of the paper is to fill in the existing gap in the literature concerning the psychological and social mechanisms of attachment that players form with non-customizable game characters. The research explores the nature of player-character attachment in its relation to game mechanics and broader social context, as well as its transformative potential.   The research relies on interdisciplinary mixed-methods methodology, drawing from the fields of psychology and anthropology. The first part of the research employs auto-ethnographic data on the authors' personal relationships with game characters. The second part involves a series of qualitative in-depth interviews with players of Animal Crossing and Genshin Impact. Thematic analysis with the elements of case-study methodology is applied to the interview data. The results of the interview analysis are compared between the two player groups, as well as to the findings of the auto-ethnographic inquiry. The main results of the comparative analysis suggest that players’ perceptions of characters in the studied games can be categorized as character-as-object and character-as-other. Further on, a distinction can be made between two types of attachment that players form with characters-as-others. The first one is player-for-character, focused primarily on a player’s relatedness and empathy towards a character. The second one is character-for-player, where a game character is perceived as a supporting and caring figure that transcends the boundaries of the game. The relationship types are not mutually exclusive, and both of them have been found to have transformative potential.