Interactive Video Game Content Authoring using Procedural Methods

This thesis explores avenues for improving the quality and detail of game graphics, in the context of constraints that are common to most game development studios. The research begins by identifying two dominant constraints; limitations in the capacity of target gaming hardware/platforms, and processes that hinder the productivity of game art/content creation. From these constraints, themes were derived which directed the research‟s focus. These include the use of algorithmic or „procedural‟ methods in the creation of graphics content for games, and the use of an „interactive‟ content creation strategy, to better facilitate artist production workflow. Interactive workflow represents an emerging paradigm shift in content creation processes used by the industry, which directly integrates game rendering technology into the content authoring process. The primary motivation for this is to provide „high frequency‟ visual feedback that enables artists to see games content in context, during the authoring process. By merging these themes, this research develops a production strategy that takes advantage of „high frequency feedback‟ in an interactive workflow, to directly expose procedural methods to artists‟, for use in the content creation process. Procedural methods have a characteristically small „memory footprint‟ and are capable of generating massive volumes of data. Their small „size to data volume‟ ratio makes them particularly well suited for use in game rendering situations, where capacity constraints are an issue. In addition, an interactive authoring environment is well suited to the task of setting parameters for procedural methods, reducing a major barrier to their acceptance by artists. An interactive content authoring environment was developed during this research. Two algorithms were designed and implemented. These algorithms provide artists‟ with abstract mechanisms which accelerate common game content development processes; namely object placement in game environments, and the delivery of variation between similar game objects. In keeping with the theme of this research, the core functionality of these algorithms is delivered via procedural methods. Through this, production overhead that is associated with these content development processes is essentially offloaded from artists onto the processing capability of modern gaming hardware. This research shows how procedurally based content authoring algorithms not only harmonize with the issues of hardware capacity constraints, but also make the authoring of larger and more detailed volumes of games content more feasible in the game production process. Algorithms and ideas developed during this research demonstrate the use of procedurally based, interactive content creation, towards improving detail and complexity in the graphics of games

AN INVESTIGATION OF METAHEURISTICS USING PATH- RELINKING ON THE QUADRATIC ASSIGNMENT PROBLEM

The Quadratic Assignment Problem (QAP) is a widely researched, yet complex, combinatorial optimization problem that is applicable in modeling many real-world problems. Specifically, many optimization problems are formulated as QAPs. To resolve QAPs, the recent trends have been to use metaheuristics rather than exact or heuristic methods, and many researchers have found that the use of hybrid metaheuristics is actually more effective. A newly proposed hybrid metaheuristic is path relinking (PR), which is used to generate solutions by combining two or more reference solutions. In this dissertation, we investigated these diversification and intensification mechanisms using QAP. To satisfy the extensive demands of the computational resources, we utilized a High Throughput Computing (HTC) environment and test cases from the QAPLIB (QAP test case repository). This dissertation consists of three integrated studies that are built upon each other. The first phase explores the effects of the parameter tuning, metaheuristic design, and representation schemes (random keys and permutation solution encoding procedures) of two path-based metaheuristics (Tabu Search and Simulated Annealing) and two population-based metaheuristics (Genetic Algorithms and Artificial Immune Algorithms) using QAP as a testbed. In the second phase of the study, we examined eight tuned metaheuristics representing two representation schemes using problem characteristics. We use problem size, flow and distance dominance measures, sparsity (number of zero entries in the matrices), and the coefficient of correlation measures of the matrices to build search trajectories. The third phase of the dissertation focuses on intensification and diversification mechanisms using path-relinking (PR) procedures (the two variants of position-based path relinking) to enhance the performance of path-based and population-based metaheuristics. The current research in this field has explored the unusual effectiveness of PR algorithms in variety of applications and has emphasized the significance of future research incorporating more sophisticated strategies and frameworks. In addition to addressing these issues, we also examined the effects of solution representations on PR augmentation. For future research, we propose metaheuristic studies using fitness landscape analysis to investigate particular metaheuristics\u27 fitness landscapes and evolution through parameter tuning, solution representation, and PR augmentation. The main research contributions of this dissertation are to widen the knowledge domains of metaheuristic design, representation schemes, parameter tuning, PR mechanism viability, and search trajectory analysis of the fitness landscape using QAPs

Mapping Indigenous Knowledge in the Digital Age

This Special Issue, “Mapping Indigenous Knowledge in the Digital Age”, explores Indigenous engagement with geo-information in contemporary cartography. Indigenous mapping, incorporating performance, process, product, and positionality as well as tangible and intangible heritage, is speedily entering the domain of cartography, and digital technology is facilitating the engagement of communities in mapping their own locational stories, histories, cultural heritage, environmental, and political priorities. In this publication, multimodal and multisensory online maps combine the latest multimedia and telecommunications technology to examine data and support qualitative and quantitative research, as well as to present and store a wide range of temporal/spatial information and archival materials in innovative interactive storytelling formats. It will be of particular interest to researchers engaged in studies of global human and environmental connection in the age of evolving information technology

Model order reduction methods for sensor data assimilation to support the monitoring of embankment dams

Tesi en modalitat de cotutela; Universitat Politècnica de Catalunya i Université libre de BruxellesThe latest monitoring and asset management technologies for large infrastructures involve digital representations that integrate information and physical models, exist in parallel to the real-life structures, and are continuously updated based on assimilated sensor data, in order to accurately represent the actual conditions in the structures. This type of technology is often referred to as Digital Twin. The implementation of such cutting-edge technology in monitoring assets like tailings dams, or embankment dams in general, and other large structures, implies the development of highly efficient numerical tools that, combined with sensor data, may support rapid, informed decision making. For the particular case of embankment dams, enabling this type of technology requires an efficient numerical model that describes the coupled hydro-mechanical phenomena, pertinent to a dam functioning and safety. This may for instance be a Finite Elements (FE) model, describing the groundwater flow through unsaturated porous geomaterials. The process of updating and calibrating a model, such as the above mentioned FE model, based on sensor data is typically referred to as data assimilation. Often, this is achieved via an optimization approach, where a specific problem is solved multiple times for various parametric values, in search for the values that best describe the sensor data. The bottleneck in this type of application is typically the cost of multiple evaluations of the model, that may become prohibitive when the underlying FE model is large. In order to enable such applications, the present work proposes Model Order Reduction (MOR) methods tailored to the hydro-mechanical nonlinear problem at hand. MOR aims at the creation of a surrogate model that seeks an approximation of the FE solution in a reduced-order space. This is achieved by applying an offline-online strategy. In the offline stage, the solution manifold of the full-order problem is sampled, in order to identify a low-order affine subspace, where an accurate approximation of the full-order solution can be captured. To tackle the nonlinearities related to partially saturated conditions in the soil, a similar strategy must be employed in order to define reduced-order spaces where an affine system approximation may be recovered. The resulting Reduced Order Model (ROM) may be used as an efficient surrogate to the FE model in any problem that requires fast and/or repetitive solutions. In this work, MOR techniques are implemented to solve the coupled nonlinear transient problem under consideration. ROMs are created to solve problems that pertain to tailings dams and embankment dams monitoring. The efficiency and the accuracy of these models are demonstrated by solving inverse problems for parametric identification. MOR is found to be a reliable tool, significantly accelerating the inverse identification process while resulting to accurate solutions.Las últimas tecnologías de monitorización y gestión de proyectos como grandes infraestructuras implican modelos digitales que integran información y modelos físicos, existen en paralelo a las estructuras reales y se actualizan continuamente en función de datos de sensores asimilados, con el fin de representar con precisión las condiciones reales de las estructuras. Este tipo de tecnología suele denominarse Digital Twin. La aplicación de esta tecnología de vanguardia en la gestión de grandes obras de infraestructura como las presas de residuos mineros, o las presas de tierra o de materiales sueltos en general, y otras estructuras de gran tamaño, implica el desarrollo de herramientas numéricas muy eficientes que, combinadas con los datos de los sensores, permiten una toma de decisiones rápida e informada. Para el caso particular de las presas de terraplén, habilitar este tipo de tecnología requiere un modelo numérico eficiente que describa los fenómenos hidromecánicos acoplados, pertinentes para el funcionamiento y la seguridad de una presa. Puede tratarse, por ejemplo, de un modelo de elementos finitos (EF) que describa el flujo de agua subterránea a través de geomateriales porosos no saturados. El proceso de actualización y calibración de un modelo, como el modelo de elementos finitos mencionado anteriormente, basado en los datos de los sensores se denomina normalmente asimilación de datos. A menudo, esto se consigue mediante un enfoque de optimización, en el que un problema específico se resuelve múltiples veces para varios valores paramétricos, en busca de los valores que mejor describen los datos de los sensores. El obstáculo en este tipo de aplicaciones suele ser el coste de las múltiples evaluaciones del modelo, que puede llegar a ser prohibitivo cuando el modelo de EF es grande. Para permitir este tipo de aplicaciones, el presente trabajo propone métodos de reducción del orden del modelo (MOR) adaptados al problema hidromecánico no lineal en cuestión. MOR tiene como objetivo la creación de un modelo sustituto que busca una aproximación de la solución de EF en un espacio de orden reducido. Esto se consigue aplicando una estrategia offline-online. En la etapa offline, se muestrea el colector de soluciones del problema de orden completo, con el fin de identificar un subespacio afín de orden reducido, en el que se pueda capturar una aproximación precisa de la solución de orden completo. Para abordar las no linealidades relacionadas con las condiciones de saturación parcial del suelo, debe emplearse una estrategia similar para definir espacios de orden reducido en los que pueda recuperarse una aproximación del sistema afín. El Modelo de Orden Reducido (MOR) resultante puede ser utilizado como un sustituto eficiente del modelo de EF en cualquier problema que requiera soluciones rápidas y/o repetitivas. En este trabajo, se implementan técnicas de MOR para resolver el problema transitorio no lineal acoplado que se está considerando. Los MOR se crean para resolver problemas relacionados con la monitorización de presas de relaves y presas de terraplén. La eficacia y la precisión de estos modelos se demuestran mediante la resolución de problemas inversos para la identificación paramétrica. El MOR resulta ser una herramienta fiable, que acelera significativamente el proceso de identificación inversa y da lugar a soluciones precisas.Postprint (published version

Model order reduction methods for sensor data assimilation to support the monitoring of embankment dams

Tesi en modalitat de cotutela; Universitat Politècnica de Catalunya i Université libre de BruxellesThe latest monitoring and asset management technologies for large infrastructures involve digital representations that integrate information and physical models, exist in parallel to the real-life structures, and are continuously updated based on assimilated sensor data, in order to accurately represent the actual conditions in the structures. This type of technology is often referred to as Digital Twin. The implementation of such cutting-edge technology in monitoring assets like tailings dams, or embankment dams in general, and other large structures, implies the development of highly efficient numerical tools that, combined with sensor data, may support rapid, informed decision making. For the particular case of embankment dams, enabling this type of technology requires an efficient numerical model that describes the coupled hydro-mechanical phenomena, pertinent to a dam functioning and safety. This may for instance be a Finite Elements (FE) model, describing the groundwater flow through unsaturated porous geomaterials. The process of updating and calibrating a model, such as the above mentioned FE model, based on sensor data is typically referred to as data assimilation. Often, this is achieved via an optimization approach, where a specific problem is solved multiple times for various parametric values, in search for the values that best describe the sensor data. The bottleneck in this type of application is typically the cost of multiple evaluations of the model, that may become prohibitive when the underlying FE model is large. In order to enable such applications, the present work proposes Model Order Reduction (MOR) methods tailored to the hydro-mechanical nonlinear problem at hand. MOR aims at the creation of a surrogate model that seeks an approximation of the FE solution in a reduced-order space. This is achieved by applying an offline-online strategy. In the offline stage, the solution manifold of the full-order problem is sampled, in order to identify a low-order affine subspace, where an accurate approximation of the full-order solution can be captured. To tackle the nonlinearities related to partially saturated conditions in the soil, a similar strategy must be employed in order to define reduced-order spaces where an affine system approximation may be recovered. The resulting Reduced Order Model (ROM) may be used as an efficient surrogate to the FE model in any problem that requires fast and/or repetitive solutions. In this work, MOR techniques are implemented to solve the coupled nonlinear transient problem under consideration. ROMs are created to solve problems that pertain to tailings dams and embankment dams monitoring. The efficiency and the accuracy of these models are demonstrated by solving inverse problems for parametric identification. MOR is found to be a reliable tool, significantly accelerating the inverse identification process while resulting to accurate solutions.Las últimas tecnologías de monitorización y gestión de proyectos como grandes infraestructuras implican modelos digitales que integran información y modelos físicos, existen en paralelo a las estructuras reales y se actualizan continuamente en función de datos de sensores asimilados, con el fin de representar con precisión las condiciones reales de las estructuras. Este tipo de tecnología suele denominarse Digital Twin. La aplicación de esta tecnología de vanguardia en la gestión de grandes obras de infraestructura como las presas de residuos mineros, o las presas de tierra o de materiales sueltos en general, y otras estructuras de gran tamaño, implica el desarrollo de herramientas numéricas muy eficientes que, combinadas con los datos de los sensores, permiten una toma de decisiones rápida e informada. Para el caso particular de las presas de terraplén, habilitar este tipo de tecnología requiere un modelo numérico eficiente que describa los fenómenos hidromecánicos acoplados, pertinentes para el funcionamiento y la seguridad de una presa. Puede tratarse, por ejemplo, de un modelo de elementos finitos (EF) que describa el flujo de agua subterránea a través de geomateriales porosos no saturados. El proceso de actualización y calibración de un modelo, como el modelo de elementos finitos mencionado anteriormente, basado en los datos de los sensores se denomina normalmente asimilación de datos. A menudo, esto se consigue mediante un enfoque de optimización, en el que un problema específico se resuelve múltiples veces para varios valores paramétricos, en busca de los valores que mejor describen los datos de los sensores. El obstáculo en este tipo de aplicaciones suele ser el coste de las múltiples evaluaciones del modelo, que puede llegar a ser prohibitivo cuando el modelo de EF es grande. Para permitir este tipo de aplicaciones, el presente trabajo propone métodos de reducción del orden del modelo (MOR) adaptados al problema hidromecánico no lineal en cuestión. MOR tiene como objetivo la creación de un modelo sustituto que busca una aproximación de la solución de EF en un espacio de orden reducido. Esto se consigue aplicando una estrategia offline-online. En la etapa offline, se muestrea el colector de soluciones del problema de orden completo, con el fin de identificar un subespacio afín de orden reducido, en el que se pueda capturar una aproximación precisa de la solución de orden completo. Para abordar las no linealidades relacionadas con las condiciones de saturación parcial del suelo, debe emplearse una estrategia similar para definir espacios de orden reducido en los que pueda recuperarse una aproximación del sistema afín. El Modelo de Orden Reducido (MOR) resultante puede ser utilizado como un sustituto eficiente del modelo de EF en cualquier problema que requiera soluciones rápidas y/o repetitivas. En este trabajo, se implementan técnicas de MOR para resolver el problema transitorio no lineal acoplado que se está considerando. Los MOR se crean para resolver problemas relacionados con la monitorización de presas de relaves y presas de terraplén. La eficacia y la precisión de estos modelos se demuestran mediante la resolución de problemas inversos para la identificación paramétrica. El MOR resulta ser una herramienta fiable, que acelera significativamente el proceso de identificación inversa y da lugar a soluciones precisas.Enginyeria civi

Horses and Oil in His Blood : Mythopoetics and Western Petromelancholia in Alexandra Fuller\u27s The Legend of Colton H. Bryant

Alexandra Fuller’s book The Legend of Colton H. Bryant, often read as merely a sad biography of a young man who meets his demise in the Wyoming energy patch, performs urgent cultural work. Fuller captures Wyoming’s shift from conventional (Easy Oil) extraction to the extreme (Tough Oil) extraction method known as hydraulic fracturing, or fracking, at the dawn of the twenty-first century. This shift to Tough Oil involves far more than engineering concerns, as Stephanie LeMenager points out in her cultural critique Living Oil. LeMenager terms our national failure to acknowledge the crises that accompany Tough Oil practices petromelancholia, focusing much of her attention upon the BP Horizon disaster in the Gulf of Mexico and fracking near urban centers in Appalachia and California. The interior West and its landscapes of extraction remain overlooked, its denizens invisible. In this thesis, I argue that Fuller enacts a Western iteration of petromelancholia, and I make my case using textual evidence from The Legend of Colton H. Bryant, as well as secondary support from Stephanie LeMenager, Robert Warshow, John G. Cawelti, Wallace Stegner, Ray Ring, and many others. In my first chapter, I explore the risks associated with the relinquishment of large tracts of Wyoming and the interior West as sacrifice zones, and I interpret the various strata of Fuller’s unusual comparison of drilling rigs to the Eiffel Tower. In my remaining chapters, I discuss the interplay of Western American mythologies with Colton’s worsening petromelancholic denial. In chapter two, I explore tensions between Wyoming’s cowboy identity and the petro-industrial complex. I then show how Colton’s cowboy repose positions him to enter the oil and gas industry. In chapter three, I explicate Colton’s deterioration and the various elements of his petromelancholia as he attempts to become a self-made man in the Western tradition. In my fourth chapter, I examine Colton’s denial and anger in Fuller’s gun-cleaning scene, and I analyze the ways in which Fuller rethinks two worn tropes of the Western genre, firearms and violence, to illustrate Colton’s deep and fatal petromelancholia