Resistance and relatedness on an evolutionary graph

When investigating evolution in structured populations, it is often convenient to consider the population as an evolutionary graph—individuals as nodes, and whom they may act with as edges. There has, in recent years, been a surge of interest in evolutionary graphs, especially in the study of the evolution of social behaviours. An inclusive fitness framework is best suited for this type of study. A central requirement for an inclusive fitness analysis is an expression for the genetic similarity between individuals residing on the graph. This has been a major hindrance for work in this area as highly technical mathematics are often required. Here, I derive a result that links genetic relatedness between haploid individuals on an evolutionary graph to the resistance between vertices on a corresponding electrical network. An example that demonstrates the potential computational advantage of this result over contemporary approaches is provided. This result offers more, however, to the study of population genetics than strictly computationally efficient methods. By establishing a link between gene transfer and electric circuit theory, conceptualizations of the latter can enhance understanding of the former.     

Visualization and Computer Graphics on Isotropically Emissive Volumetric Displays

The availability of commodity volumetric displays provides ordinary users with a new means of visualizing 3D data. Many of these displays are in the class of isotropically emissive light devices, which are designed to directly illuminate voxels in a 3D frame buffer, producing x-ray-like visualizations. While this technology can offer intuitive insight into a 3D object, the visualizations are perceptually different from what a computer graphics or visualization system would render on a 2D screen. This paper formalizes rendering on isotropically emissive displays and introduces a novel technique that emulates traditional rendering effects on isotropically emissive volumetric displays, delivering results that are much closer to what is traditionally rendered on regular 2D screens. Such a technique can significantly broaden the capability and usage of isotropically emissive volumetric displays. Our method takes a 3D data set or object as the input, creates an intermediate light field, and outputs a special 3D volume data set called a lumi-volume. This lumi-volume encodes approximated rendering effects in a form suitable for display with accumulative integrals along unobtrusive rays. When a lumi-volume is fed directly into an isotropically emissive volumetric display, it creates a 3D visualization with surface shading effects that are familiar to the users. The key to this technique is an algorithm for creating a 3D lumi-volume from a 4D light field. In this paper, we discuss a number of technical issues, including transparency effects due to the dimension reduction and sampling rates for light fields and lumi-volumes. We show the effectiveness and usability of this technique with a selection of experimental results captured from an isotropically emissive volumetric display, and we demonstrate its potential capability and scalability with computer-simulated high-resolution results.     

Nested Tracking Graphs

Tracking graphs are a well established tool in topological analysis to visualize the evolution of components and their properties over time, i.e., when components appear, disappear, merge, and split. However, tracking graphs are limited to a single level threshold and the graphs may vary substantially even under small changes to the threshold. To examine the evolution of features for varying levels, users have to compare multiple tracking graphs without a direct visual link between them. We propose a novel, interactive, nested graph visualization based on the fact that the tracked superlevel set components for different levels are related to each other through their nesting hierarchy. This approach allows us to set multiple tracking graphs in context to each other and enables users to effectively follow the evolution of components for different levels simultaneously. We demonstrate the effectiveness of our approach on datasets from finite pointset methods, computational fluid dynamics, and cosmology simulations.     

Failure tolerant teleoperation of a kinematically redundant manipulator: an experimental study

Teleoperated robots in harsh environments have a significant likelihood of failures. It has been shown in previous work that a common type of failure such as that of a joint "locking up," when unidentified by the robot controller, can cause considerable performance degradation in the local behavior of the manipulator even for simple point-to-point motion tasks. The effects of a failure become more critical for a system with a human in the loop, where unpredictable behavior of the robotic arm can completely disorient the operator. In this experimental study involving teleoperation of a graphically simulated kinematically redundant manipulator, two control schemes, the pseudoinverse and a proposed failure-tolerant inverse, were randomly presented under both nonfailure and failure scenarios to a group of operators. Based on performance measures derived from the recorded trajectory data and operator ratings of task difficulty, it is seen that the failure-tolerant inverse kinematic control scheme improved the performance of the human/robot system.     

Parallel Approaches for Singular Value Decomposition as Applied to Robotic Manipulator Jacobians

The system of equations that govern kinematically redundant robotic manipulators is commonly solved by finding the singular value decomposition (SVD) of the corresponding Jacobian matrix. This can require a considerable amount of time to compute, thus a parallel SVD algorithm reducing execution time is sought. The approach employed here lends itself to parallelization by using Givens rotations and information from previous decompositions. The key contribution of this research is the presentation and implementation of parallel SVD algorithms to compute the SVD for a set of Jacobians that represent various different joint failure scenarios. Results from implementation of the algorithm on a MasPar MP-1, an IBM SP2, and the PASM prototype parallel computers are compared. Specific issues considered for each implementation include: how data is mapped to the processing elements, the effect that increasing the number of processing elements has on execution time, the type of parallel architecture used, and trade-offs between modes of parallelism.     

Robust static allocation of resources for independent tasks under makespan and dollar cost constraints

Heterogeneous computing (HC) systems composed of interconnected machines with varied computational capabilities often operate in environments where there may be inaccuracies in the estimation of task execution times. Makespan (defined as the completion time for an entire set of tasks) is often the performance feature that needs to be optimized in such systems. Resource allocation is typically performed based on estimates of the computation time of each task on each class of machines. Hence, it is important that makespan be robust against errors in computation time estimates. In this research, the problem of finding a static mapping of tasks to maximize the robustness of makespan against the errors in task execution time estimates given an overall makespan constraint is studied. Two variations of this basic problem are considered: (1) where there is a given, fixed set of machines, (2) where an HC system is to be constructed from a set of machines within a dollar cost constraint. Six heuristic techniques for each of these variations of the problem are presented and evaluated.     

Dealing with the ill-conditioned equations of motion forarticulated figures

Realistic motion simulation for articulated figures has relied on the solution of linear systems of equations. Sometimes the solution of these equations presents a great deal of numerical difficulty, resulting in unrealistic or spurious motion for the figure or in excessive computation because of small integration intervals. The cause of the difficulty is shown to be related to the physical structure of the figure, not the mathematical formulation. It is shown how to determine the severity of ill conditioning and how to obtain physically meaningful solutions without excessive computations, even when dealing with extremely ill-conditioned configurations     

Visualizing the Impact of Geographical Variations on Multivariate Clustering

Traditional multivariate clustering approaches are common in many geovisualization applications. These algorithms are used to define geodemographic profiles, ecosystems and various other land use patterns that are based on multivariate measures. Cluster labels are then projected onto a choropleth map to enable analysts to explore spatial dependencies and heterogeneity within the multivariate attributes. However, local variations in the data and choices of clustering parameters can greatly impact the resultant visualization. In this work, we develop a visual analytics framework for exploring and comparing the impact of geographical variations for multivariate clustering. Our framework employs a variety of graphical configurations and summary statistics to explore the spatial extents of clustering. It also allows users to discover patterns that can be concealed by traditional global clustering via several interactive visualization techniques including a novel drag & drop clustering difference view. We demonstrate the applicability of our framework over a demographics dataset containing quick facts about counties in the continental United States and demonstrate the need for analytical tools that can enable users to explore and compare clustering results over varying geographical features and scales.     

Role of support in lean DeNO x catalysis

This article reviews the accumulated theoretical results, in particular density functional theory calculations, on two catalytic processes, CO oxidation and NO reduction on metal surfaces. Owing to their importance in automotive emission control, these two reactions have generated a lot of interest in the last 20 years. Here the pathways and energetics of the involved elementary reactions under different catalytic conditions are described in detail and the understanding of the reactions is generalized. It is concluded that density functional theory calculations can be applied to catalysis to elucidate mechanisms of complex surface reactions and to understand the electronic structure of chemical processes in general. The achieved molecular knowledge of chemical reactions is certainly beneficial to new catalyst design.     

Role of Support in Lean DeNOx Catalysis

FTIR and pulse thermal analysis were applied to investigate catalysts containing Pt (1 wt%)/Ba (17 wt%) supported on -Al₂O₃, SiO₂ and ZrO₂. The aim was to learn how the support material affects the thermal stability of barium carbonate and its activity in the reaction to bulk Ba(NO₃)₂. The lower thermal stability of BaCO₃ in alumina supported samples was found to influence the formation of barium nitrate during the NO _x storage process. Quantification of Ba(NO₃)₂ formed during NO _x storage indicated that for alumina supported catalysts only ca. 30% of barium present in the sample is involved in the storage process. The low thermal stability found for alumina supported barium nitrite excludes its role in the formation of barium nitrate during interaction of NO _x with the catalyst at 300 °C. The studies indicate that -Al₂O₃ plays a major role in influencing the thermal stability of BaCO₃ and Ba(NO₃)₂. This finding seems to be relevant for the higher activity of -Al₂O₃-supported catalysts in NO _x storage reduction reactions.