Using simulations to predict the genetic connectivity of the Mojave desert tortoise

The Mojave desert tortoise is a threatened species that is facing habitat fragmentation from human development. Understanding the impact of fragmentation on this species is critical for developing appropriate conservation actions, but the effects of habitat fragmentation are often delayed, making it difficult to assess the impacts of recent landscape change. One tool often used to predict the impacts of fragmentation are agent-based models, which simulate the behavior and life-history of individual “agents”. Agent-based models allow researchers to investigate the impacts of habitat fragmentation under many scenarios, which is useful for guiding conservation actions. However, because agent-based models are computationally intense, they are often limited to small spatial extents and low numbers of agents – while performing these simulations at large scales could lead to important insights, this is often infeasible.In this dissertation, I use a computationally efficient agent-based model to assess the impact of anthropogenic development on the range-wide genetic connectivity of the Mojave desert tortoise. In Chapter 1, I describe the quadtree R package, which implements the region quadtree data structure in C++ and makes it available to the R programming environment – using this data structure increases the speed of the agent-based model. In Chapter 2, I calibrate and validate an agent-based model for predicting desert tortoise genetic connectivity. In Chapter 3, I use the model to make range-wide projections of the influence of anthropogenic development on desert tortoise genetic connectivity

Automating Topology Aware Mapping for Supercomputers

Petascale machines with hundreds of thousands of cores are being built. These machines have varying interconnect topologies and large network diameters. Computation is cheap and communication on the network is becoming the bottleneck for scaling of parallel applications. Network contention, specifically, is becoming an increasingly important factor affecting overall performance. The broad goal of this dissertation is performance optimization of parallel applications through reduction of network contention. Most parallel applications have a certain communication topology. Mapping of tasks in a parallel application based on their communication graph, to the physical processors on a machine can potentially lead to performance improvements. Mapping of the communication graph for an application on to the interconnect topology of a machine while trying to localize communication is the research problem under consideration. The farther different messages travel on the network, greater is the chance of resource sharing between messages. This can create contention on the network for networks commonly used today. Evaluative studies in this dissertation show that on IBM Blue Gene and Cray XT machines, message latencies can be severely affected under contention. Realizing this fact, application developers have started paying attention to the mapping of tasks to physical processors to minimize contention. Placement of communicating tasks on nearby physical processors can minimize the distance traveled by messages and reduce the chances of contention. Performance improvements through topology aware placement for applications such as NAMD and OpenAtom are used to motivate this work. Building on these ideas, the dissertation proposes algorithms and techniques for automatic mapping of parallel applications to relieve the application developers of this burden. The effect of contention on message latencies is studied in depth to guide the design of mapping algorithms. The hop-bytes metric is proposed for the evaluation of mapping algorithms as a better metric than the previously used maximum dilation metric. The main focus of this dissertation is on developing topology aware mapping algorithms for parallel applications with regular and irregular communication patterns. The automatic mapping framework is a suite of such algorithms with capabilities to choose the best mapping for a problem with a given communication graph. The dissertation also briefly discusses completely distributed mapping techniques which will be imperative for machines of the future.published or submitted for publicationnot peer reviewe

Space-optimized texture atlases

Texture atlas parameterization provides an effective way to map a variety of colour and data attributes from 2D texture domains onto polygonal surface meshes. Most of the existing literature focus on how to build seamless texture atlases for continuous photometric detail, but little e ort has been devoted to devise e cient techniques for encoding self-repeating, uncontinuous signals such as building facades. We present a perception-based scheme for generating space-optimized texture atlases speci cally designed for intentionally non-bijective parameterizations. Our scheme combines within-chart tiling support with intelligent packing and perceptual measures for assigning texture space in accordance to the amount of information contents of the image and on its saliency. We demonstrate our optimization scheme in the context of real-time navigation through a gigatexel urban model of an European city. Our scheme achieves signi cant compression ratios and speed-up factors with visually indistinguishable results. We developed a technique that generates space-optimized texture atlases for the particular encoding of uncontinuous signals projected onto geometry. The scene is partitioned using a texture atlas tree that contains for each node a texture atlas. The leaf nodes of the tree contain scene geometry. The level of detail is controlled by traversing the tree and selecting the appropriate texture atlas for a given viewer position and orientation. In a preprocessing step, textures associated to each texture atlas node of the tree are packed. Textures are resized according to a given user-de ned texel size and the size of the geometry that are projected onto. We also use perceptual measures to assign texture space in accordance to image detail. We also explore different techniques for supporting texture wrapping of uncontinuous signals, which involved the development of e cient techniques for compressing texture coordinates via the GPU. Our approach supports texture ltering and DXTC compression without noticeable artifacts. We have implemented a prototype version of our space-optimized texture atlases technique and used it to render the 3D city model of Barcelona achieving interactive rendering frame rates. The whole model was composed by more than three million triangles and contained more than twenty thousand different textures representing the building facades with an average original resolution of 512 pixels per texture. Our scheme achieves up 100:1 compression ratios and speed-up factors of 20 with visually indistinguishable results

Design and performance evaluation of indexing methods for dynamic attributes in mobile database management systems

Ankara : Department of Computer Engineering and Information Science and the Institute of Engineering and Science of Bilkent University, 1997.Thesis(Master's) -- Bilkent University, 1997.Includes bibliographical references leaves 99-104.Tayeb, JamelM.S

Data Structures & Algorithm Analysis in C++

This is the textbook for CSIS 215 at Liberty University.https://digitalcommons.liberty.edu/textbooks/1005/thumbnail.jp

New data structures and algorithms for the efficient management of large spatial datasets

[Resumen] En esta tesis estudiamos la representación eficiente de matrices multidimensionales, presentando nuevas estructuras de datos compactas para almacenar y procesar grids en distintos ámbitos de aplicación. Proponemos varias estructuras de datos estáticas y dinámicas para la representación de matrices binarias o de enteros y estudiamos aplicaciones a la representación de datos raster en Sistemas de Información Geográfica, bases de datos RDF, etc. En primer lugar proponemos una colección de estructuras de datos estáticas para la representación de matrices binarias y de enteros: 1) una nueva representación de matrices binarias con grandes grupos de valores uniformes, con aplicaciones a la representación de datos raster binarios; 2) una nueva estructura de datos para representar matrices multidimensionales; 3) una nueva estructura de datos para representar matrices de enteros con soporte para consultas top-k de rango. También proponemos una nueva representación dinámica de matrices binarias, una nueva estructura de datos que proporciona las mismas funcionalidades que nuestras propuestas estáticas pero también soporta cambios en la matriz. Nuestras estructuras de datos pueden utilizarse en distintos dominios. Proponemos variantes específicas y combinaciones de nuestras propuestas para representar grafos temporales, bases de datos RDF, datos raster binarios o generales y datos raster temporales. También proponemos un nuevo algoritmo para consultar conjuntamente un conjuto de datos raster (almacenado usando nuestras propuestas) y un conjunto de datos vectorial almacenado en una estructura de datos clásica, mostrando que nuestra propuesta puede ser más rápida y usar menos espacio que otras alternativas. Nuestras representaciones proporcionan interesantes trade-offs y son competitivas en espacio y tiempos de consulta con representaciones habituales en los diferentes dominios.[Resumo] Nesta tese estudiamos a representación eficiente de matrices multidimensionais, presentando novas estruturas de datos compactas para almacenar e procesar grids en distintos ámbitos de aplicación. Propoñemos varias estruturas de datos estáticas e dinámicas para a representación de matrices binarias ou de enteiros e estudiamos aplicacións á representación de datos raster en Sistemas de Información Xeográfica, bases de datos RDF, etc. En primeiro lugar propoñemos unha colección de estruturas de datos estáticas para a representación de matrices binarias e de enteiros: 1) unha nova representación de matrices binarias con grandes grupos de valores uniformes, con aplicacións á representación de datos raster binarios; 2) unha nova estrutura de datos para representar matrices multidimensionais; 3) unha nova estrutura de datos para representar matrices de enteiros con soporte para consultas top-k. Tamén propoñemos unha nova representación dinámica de matrices binarias, unha nova estrutura de datos que proporciona as mesmas funcionalidades que as nosas propostas estáticas pero tamén soporta cambios na matriz. As nosas estruturas de datos poden utilizarse en distintos dominios. Propoñemos variantes específicas e combinacións das nosas propostas para representar grafos temporais, bases de datos RDF, datos raster binarios ou xerais e datos raster temporais. Tamén propoñemos un novo algoritmo para consultar conxuntamente datos raster (almacenados usando as nosas propostas) con datos vectoriais almacenados nunha estrutura de datos clásica, amosando que a nosa proposta pode ser máis rápida e usar menos espazo que outras alternativas. As nosas representacións proporcionan interesantes trade-offs e son competitivas en espazo e tempos de consulta con representacións habituais nos diferentes dominios.[Abstract] In this thesis we study the efficient representation of multidimensional grids, presenting new compact data structures to store and query grids in different application domains. We propose several static and dynamic data structures for the representation of binary grids and grids of integers, and study applications to the representation of raster data in Geographic Information Systems, RDF databases, etc. We first propose a collection of static data structures for the representation of binary grids and grids of integers: 1) a new representation of bi-dimensional binary grids with large clusters of uniform values, with applications to the representation of binary raster data; 2) a new data structure to represent multidimensional binary grids; 3) a new data structure to represent grids of integers with support for top-k range queries. We also propose a new dynamic representation of binary grids, a new data structure that provides the same functionalities that our static representations of binary grids but also supports changes in the grid. Our data structures can be used in several application domains. We propose specific variants and combinations of our generic proposals to represent temporal graphs, RDF databases, OLAP databases, binary or general raster data, and temporal raster data. We also propose a new algorithm to jointly query a raster dataset (stored using our representations) and a vectorial dataset stored in a classic data structure, showing that our proposal can be faster and require less space than the usual alternatives. Our representations provide interesting trade-offs and are competitive in terms of space and query times with usual representations in the different domains

Segmentation and Deformable Modelling Techniques for a Virtual Reality Surgical Simulator in Hepatic Oncology

Liver surgical resection is one of the most frequently used curative therapies. However, resectability is problematic. There is a need for a computer-assisted surgical planning and simulation system which can accurately and efficiently simulate the liver, vessels and tumours in actual patients. The present project describes the development of these core segmentation and deformable modelling techniques. For precise detection of irregularly shaped areas with indistinct boundaries, the segmentation incorporated active contours - gradient vector flow (GVF) snakes and level sets. To improve efficiency, a chessboard distance transform was used to replace part of the GVF effort. To automatically initialize the liver volume detection process, a rotating template was introduced to locate the starting slice. For shape maintenance during the segmentation process, a simplified object shape learning step was introduced to avoid occasional significant errors. Skeletonization with fuzzy connectedness was used for vessel segmentation. To achieve real-time interactivity, the deformation regime of this system was based on a single-organ mass-spring system (MSS), which introduced an on-the-fly local mesh refinement to raise the deformation accuracy and the mesh control quality. This method was now extended to a multiple soft-tissue constraint system, by supplementing it with an adaptive constraint mesh generation. A mesh quality measure was tailored based on a wide comparison of classic measures. Adjustable feature and parameter settings were thus provided, to make tissues of interest distinct from adjacent structures, keeping the mesh suitable for on-line topological transformation and deformation. More than 20 actual patient CT and 2 magnetic resonance imaging (MRI) liver datasets were tested to evaluate the performance of the segmentation method. Instrument manipulations of probing, grasping, and simple cutting were successfully simulated on deformable constraint liver tissue models. This project was implemented in conjunction with the Division of Surgery, Hammersmith Hospital, London; the preliminary reality effect was judged satisfactory by the consultant hepatic surgeon