Parallel rendering algorithms for distributed-memory multicomputers

Ankara : Department of Computer Engineering and Information Science and the Institute of Engineering and Science of Bilkent University, 1997.Thesis (Ph. D.) -- Bilkent University, 1997.Includes bibliographical references leaves 166-176.Kurç, Tahsin MertefePh.D

New Algorithms for Computing Field of Vision over 2D Grids

In many computer games checking whether one object is visible from another is very important. Field of Vision (FOV) refers to the set of locations that are visible from a specific position in a scene of a computer game. Once computed, an FOV can be used to quickly determine the visibility of multiple objects from a given position. This thesis summarizes existing algorithms for FOV computation, describes their limitations, and presents new algorithms which aim to address these limitations. We first present an algorithm which makes use of spatial data structures in a way which is new for FOV calculation. We then present a novel technique which updates a previously calculated FOV, rather than re-calculating FOV from scratch. We then compare our algorithms to existing FOV algorithms and show that they provide substantial improvements to running time and efficiency of memory access

Solution of partial differential equations on vector and parallel computers

The present status of numerical methods for partial differential equations on vector and parallel computers was reviewed. The relevant aspects of these computers are discussed and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic equations as well as explicit and implicit methods for initial boundary value problems. The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms. Application areas utilizing these computers are briefly discussed

Image-space decomposition algorithms for sort-first parallel volume rendering of unstructured grids

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 96-100.Kutluca, HüseyinM.S

Schnelle Löser für partielle Differentialgleichungen

The workshop Schnelle Löser für partielle Differentialgleichungen, organised by Randolph E. Bank (La Jolla), Wolfgang Hackbusch(Leipzig), Gabriel Wittum (Heidelberg) was held May 22nd - May 28th, 2005. This meeting was well attended by 47 participants with broad geographic representation from 9 countries and 3 continents. This workshop was a nice blend of researchers with various backgrounds

Local and long-distance organization of prefrontal cortex circuits in the marmoset brain

The prefrontal cortex (PFC) has dramatically expanded in primates, but its organization and interactions with other brain regions are only partially understood. We performed high-resolution connectomic mapping of the marmoset PFC and found two contrasting corticocortical and corticostriatal projection patterns: patchy projections that formed many columns of submillimeter scale in nearby and distant regions and diffuse projections that spread widely across the cortex and striatum. Parcellation-free analyses revealed representations of PFC gradients in these projections\u27 local and global distribution patterns. We also demonstrated column-scale precision of reciprocal corticocortical connectivity, suggesting that PFC contains a mosaic of discrete columns. Diffuse projections showed considerable diversity in the laminar patterns of axonal spread. Altogether, these fine-grained analyses reveal important principles of local and long-distance PFC circuits in marmosets and provide insights into the functional organization of the primate brain

Integration of field-based analysis of plant community dynamics with quantitative analysis of landscape change in the Ray Roberts Lake area, 19871997

This study focused on the effectiveness of integrating traditional plant community analyses with landscape ecological analyses based on remotely sensed data. A temporal analysis of plant community diversity was conducted for major plant communities of the Ray Roberts Lake area using transect monitoring data collected between 1987 and 1997. Landscape analyses were performed with FRAGSTATS*ARC using classified SPOT satellite imagery for 1987 and 1997. Although the methodology developed in this work was exploratory, it was found that characterizing the dynamics of major plant communities in the study area produced a more effective and insightful analysis of Ray Roberts Lake area landscape dynamics

Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons

An Energy Formulation of Surface Tension or Willmore Force For Two-Phase Flow

The motion of a biological cell in liquid is a rich subject for modeling. In the early 1970’s, it was realized by Canham that biological vesicles with lipid bilayer membranes reach a steady state shape that minimizes bending. Helfrich soon after mathematically quantified the related bending energy and showed that the shapes from minimizing this bending energy match the types of shapes observed in nature. The resulting Canham-Helfrich energy, consisting of bending energy and a constant surface area and volume constraint, is a major component of any model of cellular motility. To this end, we consider the cellular vesicle to be a closed interface between two fluids and we present a finite element model for a two-phase flow coupling the minimization of some given energy defined on the interface to the incompressible flow of the two fluids, which is then advected according to the resulting velocity field. We provide a general framework for incorporating the energies on the interface and then focus on three applications of energy on the interface: the first is surface tension minimizing the surface area energy, the second minimizes the bending energy without explicit surface area or volume constraints, the third minimizes the Canham-Helfrich energy including the constraints. We present a semi-implicit model for bending energy which uses an implicit levelset formulation for the interface and couples the forces from the interface to the two phase incompressible Navier-Stokes system through the use of an approximate Dirac delta function defined on a band around the interface. By using energies to describe the motion, our model is immediately provided with a sense of energy stability. We provide various numerical simulations and validations of flow under these three energies in two and three dimensions. Our simulations confirm that enforcing the volume constraint in the incompressible flow is vital to achieve the desired steady state shapes