Children undergoing Dialysis spend a lot of time on self-care, including three hospital visits a week, three to ve hours in length, accounting for 30% of their after-school time. As a result, many of these children lack the time to lead an active life, and combined with their ailing health, leads to deteriorating quality of life. As a result, many of these children lack con dence in their capabilities and cannot answer questions such as \Can I bike to school?". Cyclescape, an exercise VR game, aims to provide entertainment to patients undergoing dialysis, improve their quality of life, and help them answer such questions. This thesis explores converting real-world data into a personal game level, consisting of a path in a game that players (patients) can traverse on a stationary bike while undergoing dialysis. We will explore the di erent types of real-world map data available and how they are used in video games. We will then derive di erent goals the map should address to improve the player's condition and then design Cyclescape to meet them. Lastly, we will analyze how successful Cyclescape was in meeting these goals. / Thesis / Master of Applied Science (MASc)

Ett spels karta är begränsande i det att när man valt en viss storlek kan man inte gå utanför den ramen utan att göra relativt resurskrävande operationer. Denna undersökning genomfördes för att se om en trädstruktur kan användas som lösning att hantera en honeycomb-struktur på ett lämpligt sätt för att ständigt kunna utöka ett spels karta. Resultatet visar att det är möjligt att använda trädstrukturen relativt bra till växande kartor men att det inte är att rekommendera till spel, eftersom strukturen i sig är en omväg. I samband med denna karta skapades en slumpmässig path-generator som skulle kunna användas till att generellt skapa slumpmässiga kartor i spel. För att se vad försvårigheter man stöter på när man utvecklar en slumpad map-generator, vilket visade sig vara svårt i och med att man hittade många specialfall.

Made available in DSpace on 2016-12-12T20:22:52Z (GMT). No. of bitstreams: 1 George Henrique R Costa.pdf: 6148949 bytes, checksum: d0ba621121c8746a89db4a33dc576acd (MD5) Previous issue date: 2014-02-20 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The popularization of devices with integrated GPS receiver has considerably boosted the use of digital road maps. For this reason, it is mandatory that they be accurate and up-to-date. The methods currently used to generate these maps photogrammetry and collaborative editing have low frequency of update because they depend on manual intervention. Thus, the need for an automated method for generating road maps is highlighted. The literature presents solutions that use trajectories of moving objects to find the center of the roads, but none of them is prepared for the continuous update of the roads and the refinement of the maps. Therefore, this work aims to propose a new method to find the center of the roads using trajectories provided by GPS receivers integrated in smartphones. It is assumed that the points that represent the center of the roads can be found through approximations provided by an evolutive algorithm such as the genetic algorithm. After that, these points are combined to generate the road map. However, the use of trajectories collected with smartphones provides some challenges, such as: elimination of data with bad accuracy, identification of the means of transport used and reduction of the volume of data processed. Thus, the objective of this work is to propose a structured method that cleans, analyzes and enriches data from smartphones to generate accurate road maps that can be continuously updated, using genetic algorithm. Test results indicate that the method is capable of generating maps with quality close to the reference ones. Based on the scenarios used to perform this comparison, the average difference between them is 2.26 meters. The tests also show that the periodic and continuous update of the map as proposed by the method is viable. / A popularização de dispositivos com receptor GPS integrado aumentou consideravelmente o uso de mapas rodoviários digitais. Por este motivo, é imprescindível que eles sejam acurados e atualizados. Os métodos atualmente utilizados para gerar estes mapas fotogrametria e edição colaborativa têm baixa frequência de atualização, pois dependem de intervenção manual. Desta forma, fica evidente a necessidade de um método automatizado para geração de mapas rodoviários. A literatura apresenta soluções que utilizam trajetórias de objetos móveis para encontrar o centro das vias, mas nenhuma delas está preparada para a atualização contínua das vias e o refinamento dos mapas. Sendo assim, este trabalho visa propor um novo método para encontrar o centro das vias utilizando trajetórias providas por GPS embutido em smartphones. Assume-se que os pontos que representam os centros das vias podem ser obtidos através de aproximações providas por um algoritmo evolutivo, tal como o algoritmo genético. A seguir, estes pontos são combinados para gerar o mapa rodoviário. Entretanto, o uso de trajetórias coletadas com smartphones proporciona alguns desafios, tais como: eliminação de dados com acurácia ruim, identificação do meio de transporte utilizado e redução do volume de dados processados. Portanto, o objetivo do presente trabalho é propor um método estruturado que limpe, analise e enriqueça dados obtidos por smartphones para gerar mapas rodoviários acurados e atualizados continuamente, utilizando algoritmo genético. Os resultados dos testes apontam que o método é capaz de gerar mapas de qualidade próxima a dos mapas de referência. Com base nos cenários utilizados para realizar esta comparação, a diferença média foi de 2,26 metros. Além disso, os testes também demonstram a viabilidade da atualização periódica e contínua dos mapas proposta pelo método.

Due to the high cost of manual content creation within the game development industry, methods for procedural generation of content such as game maps and levels have emerged. However, methods for generating game maps have remained relatively unexplored in competitive multiplayer contexts. Presumably, this is due to the opposing goals of generating game maps that are both interesting and fair. This study aims to explore the possibility of satisfying both these goals simultaneously by separating the generative phase from the phase that enforces fairness. In this endeavor, simple game maps for a generic multiplayer grand strategy game are generated using noise-based methods. The task of partitioning the game map fairly between the players is then modeled as a constrained categorical multiobjective minimization problem that is subsequently solved by two genetic algorithms, the reference-point-based algorithm NSGA-III and the decomposition-based algorithm MOEA/D-IEpsilon. In a primary study, the proposed partitioning method is evaluated based on the quality of the solutions produced, its scalability, and its ability to find symmetrical partitions of symmetrical game maps. The results show that the proposed method makes significant improvement from the initial guess but fails to produce completely fair partitions in general. Explanations and possible solutions to this are presented. The timing results indicate that the proposed method is not applicable in real-time contexts. However, the proposed method might still be applicable in online contexts if smaller game maps are considered and in offline contexts if larger game maps are considered. Finally, the partitioning results show that the proposed method successfully finds fair partitions of symmetrical game maps but fails to find the obvious symmetrical partitions. In a secondary study, the two genetic algorithms are compared to determine which algorithm produces dominating solutions and which algorithm produces most diverse solution. The results indicate that, for the partitioning problems considered in this study, the reference-point-based algorithm is both dominant and produces the most diverse solutions.

Procedurell generering är ett kraftigt verktyg för att kunna skapa en stor mängd spelvärldar utan att själv behöva manuellt designa spelplaner en och en. Med bra programmerade algoritmer kan man få tillgång till en nästan obegränsad mängd av unika spelvärldar med mycket mindre arbete. Vårt uppdrag är att skapa spellogiken och spelplansgenerering till ett spel som ska skickas in som bidrag till Swedish Game Awards[1], som är nordens största tävling för spelutveckling. Vi samarbetar med en annan grupp som ska göra Nätverk och Server-funktionalitet. Deras uppgift är att skapa en huvudserver-applikation, och ett klient/server-system där två spelare kan spela mot varandra med en av spelarna som agerar server. Slutgiltiga målet är att integrera de två olika projekteten till en slutgiltig produkt. Spelet vi tänker skapa är ett schack-baserat spel som utspelar sig i en 3D-miljö. De två spelarna kommer att ha en mängd olika enheter som de kan välja att köpa för sina pengar, kallade för credits i spelet. Spelarna använder sina enheter för att förstöra motspelarens enheter, och målet är att besegra motståndarens kung. Spelet pågår tills någon av spelarnas kungar är besegrad eller tills en av spelarna ger upp. / Procedural generation is a powerful tool for creating a large set of game worlds without having to design each one individually. With the proper implementation, this can allow an almost unlimited amount of unique game worlds using far less resource and time. Our task is to create the game logic and game map generation for a game that will be entered as a contestant in Swedish Game Awards, the biggest competition for game development in the Nordic Countries. We will be working in parallel with a separate group who will be implementing the networking side of the application, where the goal is to have a server where two players can play against each other from separate end systems. As the deadline for the competition approaches, we will then combine the two projects to a finished product. The game we are creating is a chess-influenced game that takes place in a 3D world. Two players will have access to different types of units that can be purchased by the in game resource known as credits, and the main objective is to defeat the enemy king. One game session continues until either of the two kings is defeated, or one of the players surrender.

Cognitive radio (CR) is often described as a context-intelligent radio, capable of changing the transmit parameters dynamically based on the interaction with the environment it operates. The work in this thesis explores the problem of using received signal strength (RSS) measurements taken by a network of CR nodes to generate an interference map of a given geographical area and estimate the locations of multiple primary transmitters that operate simultaneously in the area. A probabilistic model of the problem is developed, and algorithms to address location estimation challenges are proposed. Three approaches are proposed to solve the localization problem. The first approach is based on estimating the locations from the generated interference map when no information about the propagation model or any of its parameters is present. The second approach is based on approximating the maximum likelihood (ML) estimate of the transmitter locations with the grid search method when the model is known and its parameters are available. The third approach also requires the knowledge of model parameters but it is actually based on generating samples from the joint posterior of the unknown location parameter with Markov chain Monte Carlo (MCMC) methods, as an alternative for the highly computationally complex grid search approach. For RF cartography generation problem, we study global and local interpolation techniques, specifically the Delaunay triangulation based techniques as the use of existing triangulation provides a computationally attractive solution. We present a comparative performance evaluation of these interpolation techniques in terms of RF field strength estimation and emitter localization. Even though the estimates obtained from the generated interference maps are less accurate compared to the ML estimator, the rough estimates are utilized to initialize a more accurate algorithm such as the MCMC technique to reduce the complexity of the algorithm. The complexity issues of ML estimators based on full grid search are also addressed by various types of iterative grid search methods. One challenge to apply the ML estimation algorithm to multiple emitter localization problem is that, it requires a pdf approximation to summands of log-normal random variables for likelihood calculations at each grid location. This inspires our investigations on sum of log-normal approximations studied in literature for selecting the appropriate approximation to our model assumptions. As a final extension of this work, we propose our own approximation based on distribution fitting to a set of simulated data and compare our approach with Fenton-Wilkinson's well-known approximation which is a simple and computational efficient approach that fits a log-normal distribution to sum of log-normals by matching the first and second central moments of random variables. We demonstrate that the location estimation accuracy of the grid search technique obtained with our proposed approximation is higher than the one obtained with Fenton-Wilkinson's in many different case scenarios.

Trains are constrained to the railway tracks they operate on. This can be leveraged for absolute train positioning, where a train’s position can be mapped onto a digital track map (DTM). Extensive research has been dedicated to enhancing the accuracy of DTMs. However, certain practical applications necessitate compact DTMs that can be processed and transferred in real-time, thereby introducing a trade-off between accuracy and memory requirements. This study focuses on data reduction techniques for generating compact DTMs, presenting three distinct methods. Equidistantly sampled Cartesian coordinates are the input to all three methods as they employ different approaches: the linear method simplifies the polygonal chain that connects the coordinates, the spline method utilises smoothing B-splines for interpolation, and the geometric method interpolates the coordinates with a cubic spline and analyse the curvature to identify track segments and describe them geometrically. The performance of these methods is evaluated by their compactness in terms of the number of data fields needed, accuracy in representing track length, and the perpendicular distances between the ground truth track and the generated DTM. The compact DTM generation techniques are applied to three evaluation tracks specifically generated for this study, as well as two existing tracks in the Swedish railway network, each with distinct complexities and characteristics. On the evaluation tracks, the geometrical DTM excels when accuracy is prioritised. As greater perpendicular deviations are tolerated, the smoothed spline DTM method outperforms the other techniques in terms of compactness. The linear DTM method is superior when even greater perpendicular deviations are tolerated. On the existing tracks, the linear DTM method is outperforming the other methods in both accuracy and compactness, presumably because of limitations with the used data set. In conclusion, the choice of technique for generating compact DTMs depends on multiple factors, including the characteristics of the track and the desired level of accuracy. / Tåg är bundna till de järnvägsspår de trafikerar. Detta innebär att tågets digitala position kan förfinas genom att knyta tågets sensorinformation till en position på en digital spårkarta. Tidigare forskning har fokuserat på att förbättra precisionen i digitala spårkartor. Eftersom en del praktiska användningsområden av digitala spårkartor kräver att kartan är kompakt för att kunna bearbetas och överföras i realtid, uppstår en avvägning mellan precision och minneskrav. Denna studie fokuserar således på olika tekniker för datareduktion som kan användas för att generera kompakta spårkartor. Tre metoder tillämpas som alla använder samplade koordinater längs med järnvägsspåret som indata. Den linjära metoden förenklar det polygontåg som förbinder koordinaterna. I spline-metoden används utjämnande splines för att interpolera koordinaterna. Den geometriska metoden interpolerar koordinaterna med en kubisk spline och använder kurvaturen i splinen för att identifiera spårsegment och beskriva dessa geometriskt. De tre metoderna utvärderas och jämförs utifrån en analys avseende kompakthet, avvikelse från järnvägsspårets egentliga längd samt genom att mäta de vinkelräta avstånden mellan det riktiga spåret och spåret i den digitala spårkartan. Tre tågspår har skapats syntetiskt för att utvärdera de tre metoderna. Dessutom har två tågsträckor längs med Kinnekullebanan och Södra stambanan valts ut. Analysen visade att den geometriska spårkartan var mest kompakt på de syntetiska tågspåren när precision prioriterades högst. När kraven på precision minskades var spline-kartan mest kompakt på de syntetiska spåren. Däremot var den linjära metoden mest kompakt när kompakthet prioriterades över precision. Den linjära metoden var dominant med avseende på både precision och kompakthet på Kinnekullebanan och Södra stambanan, troligtvis på grund av begränsningar med den data över järnvägen som använts. Slutsatsen från denna studie är att valet av teknik för att generera kompakta spårkartor beror på flera faktorer, inklusive järnvägsspårets egenskaper och krav på precision.

Les enfants souffrant de troubles du langage, comme la dyslexie, rencontrent de grandes difficultés dans l'apprentissage de la lecture et dans toute tâche de lecture, par la suite. Ces difficultés compromettent grandement l'accès au sens des textes auxquels ils sont confrontés durant leur scolarité, ce qui implique des difficultés d'apprentissage et les entraîne souvent vers une situation d'échec scolaire. Depuis une quinzaine d'années, des outils développés dans le domaine du Traitement Automatique des Langues sont détournés pour être utilisés comme stratégie d'aide et de compensation pour les élèves en difficultés. Parallèlement, l'usage de cartes conceptuelles ou de cartes heuristiques pour aider les enfants dyslexiques à formuler leurs pensées, ou à retenir certaines connaissances, s'est développé. Ce travail de thèse vise à répertorier et croiser, d'une part, les connaissances sur le public dyslexique, sa prise en charge et ses difficultés, d'autre part, les possibilités pédagogiques ouvertes par l'usage de cartes, et enfin, les technologies de résumé automatique et d'extraction de mots-clés. L'objectif est de réaliser un logiciel novateur capable de transformer automatiquement un texte donné en une carte, celle-ci doit faciliter la compréhension du texte tout en comprenant des fonctionnalités adaptées à un public d'adolescents dyslexiques. Ce projet a abouti, premièrement, à la réalisation d'une expérimentation exploratoire, sur l'aide à la compréhension de texte grâce aux cartes heuristiques, qui permet de définir de nouveaux axes de recherche ; deuxièmement, à la réalisation d'un prototype de logiciel de cartographie automatique qui est présenté en fin de thèse / Children with language impairment, such as dyslexia, are often faced with important difficulties when learning to read and during any subsequent reading tasks. These difficulties tend to compromise the understanding of the texts they must read during their time at school. This implies learning difficulties and may lead to academic failure. Over the past fifteen years, general tools developed in the field of Natural Language Processing have been transformed into specific tools for that help with and compensate for language impaired students' difficulties. At the same time, the use of concept maps or heuristic maps to encourage dyslexic children express their thoughts, or retain certain knowledge, has become popular. This thesis aims to identify and explore knowledge about the dyslexic public, how society takes care of them and what difficulties they face; the pedagogical possibilities opened up by the use of maps; and the opportunities created by automatic summarization and Information Retrieval fields. The aim of this doctoral research project was to create an innovative piece of software that automatically transforms a given text into a map. It was important that this piece of software facilitate reading comprehension while including functionalities that are adapted to dyslexic teenagers. The project involved carrying out an exploratory experiment on reading comprehension aid, thanks to heuristic maps, that make the identification of new research topics possible, and implementing an automatic mapping software prototype that is presented at the end of this thesis