Wavefront raycasting using larger filter kernels for on-the-fly GPU gradient reconstruction

The quality of images generated by volume rendering strongly depends on the accuracy of gradient estimation. However, the most commonly used techniques for on-the-fly gradient reconstruction are still very simple, such as central differences; they generally gather only limited neighbourhood information and thus ultimately produce rather poor quality images. While there are many higher-order reconstruction methods, such as 3×3×3 or 5×5×5 filters, which can improve the quality, their excessive sampling costs have meant that they are generally used only for pre-computed gradients, which are then quantized and stored for later runtime re-interpolation. This may introduce further errors and, significantly, may consume valuable texture memory. In this paper, we address these issues by proposing a CUDA-based rendering framework that uses larger filter kernels for on-the-fly gradient computation in real-time raycasting applications. By using adaptive wavefront tracing, our approach can dramatically reduce the memory bandwidth requirements related to larger neighbour samples. To further ensure that samples are consumed wisely, we have devised a novel adaptive sampling scheme and a customized 3D mipmapping technique in the CUDA environment to sample at a proper level of detail as the ray recedes into the distance. We compared our technique with two previous state-of-the-art GPU raycasting algorithms and found that it achieves higher quality imaging and faster rendering performance across a variety of data sets than the previous methods.     

Superquadric glyphs for symmetric second-order tensors

Symmetric second-order tensor fields play a central role in scientific and biomedical studies as well as in image analysis and feature-extraction methods. The utility of displaying tensor field samples has driven the development of visualization techniques that encode the tensor shape and orientation into the geometry of a tensor glyph. With some exceptions, these methods work only for positive-definite tensors (i.e. having positive eigenvalues, such as diffusion tensors). We expand the scope of tensor glyphs to all symmetric second-order tensors in two and three dimensions, gracefully and unambiguously depicting any combination of positive and negative eigenvalues. We generalize a previous method of superquadric glyphs for positive-definite tensors by drawing upon a larger portion of the superquadric shape space, supplemented with a coloring that indicates the quadratic form (including eigenvalue sign). We show that encoding arbitrary eigenvalue magnitudes requires design choices that differ fundamentally from those in previous work on traceless tensors that arise in the study of liquid crystals. Our method starts with a design of 2-D tensor glyphs guided by principles of scale-preservation and symmetry, and creates 3-D glyphs that include the 2-D glyphs in their axis-aligned cross-sections. A key ingredient of our method is a novel way of mapping from the shape space of three-dimensional symmetric second-order tensors to the unit square. We apply our new glyphs to stress tensors from mechanics, geometry tensors and Hessians from image analysis, and rate-of-deformation tensors in computational fluid dynamics.     

High strain electromechanical actuators based on electrodeposited polypyrrole doped with di-(2-ethylhexyl)sulfosuccinate

The low-voltage electromechanical actuation of polypyrrole (PPy) doped with di-(2-ethylhexyl)sulfosuccinate (DEHS) has been investigated. The PPy-DEHS has been prepared both chemically (cast as films from solution) and by more conventional electrochemical polymerization. Very large strains of ∼30% were obtained during slow-scan redox cycling of the electrochemically prepared PPy-DEHS films. In constrast, PPy-DEHS films cast from solutions of the chemically polymerized polymer gave actuation strains of ∼2.5%. The polymerization method was also found to have a significant effect on the structure, conductivity and mechanical properties of the PPy-DEHS materials. The conductivity of the electrochemically polymerized PPy-DEHS was 75 S cm⁻¹, considerably higher than that found for the chemically derived polymer (7 S cm⁻¹). The structure of the PPy-DEHS was further elucidated from UV-vis, Raman and FT-IR spectral studies which indicated that the conjugation length of the PPy could be increased significantly by varying the polymerization method. Films obtained by casting chemically prepared PPy-DEHS showed higher modulus (2.3 GPa) than electropolymerized PPy-DEHS (0.6 GPa), but were more brittle. Both materials were electroactive in acetonitrile/water electrolyte. The higher actuation strain observed in the electrochemically prepared films was attributed to a more open molecular structure (as indicated by the lower modulus) allowing for easier ion diffusion and a higher conductivity allowing easier charge transfer.     

A note: Common due date assignment for a single machine scheduling with the rate-modifying activity

In this paper we study the single machine common due date assignment and scheduling problem with the possibility to perform a rate-modifying activity (RMA) for changing the processing times of the jobs following this activity. The objective is to minimize the total weighted sum of earliness, tardiness and due date costs. Placing the RMA to some position in the schedule can decrease the objective function value. Several properties of the problem are considered which in some cases can reduce the complexity of the solution algorithm.     

Using coverage to automate and improve test purpose based testing

Test purposes have been presented as a solution to avoid the state space explosion when selecting test cases from formal models. Although such techniques work very well with regard to the speed of the test derivation, they leave the tester with one important task that influences the quality of the overall testing process: test purposes have to be formulated manually. In this paper, we present an approach that assists a test engineer with test purpose design in two ways: it allows automatic generation of coverage based test suites and can be used to automatically exercise those aspects of the system that are missed by hand-crafted test purposes. We consider coverage of Lotos specifications, and show how labeled transition systems derived from such specifications have to be extended in order to allow the application of logical coverage criteria to Lotos specifications. We then show how existing tools can be used to efficiently derive test cases and suggest how to use the coverage information to minimize test suites while generating them.     

Convolutional Sparse Coding for High Dynamic Range Imaging

Current HDR acquisition techniques are based on either (i) fusing multibracketed, low dynamic range (LDR) images, (ii) modifying existing hardware and capturing different exposures simultaneously with multiple sensors, or (iii) reconstructing a single image with spatially‐varying pixel exposures. In this paper, we propose a novel algorithm to recover high‐quality HDRI images from a single, coded exposure. The proposed reconstruction method builds on recently‐introduced ideas of convolutional sparse coding (CSC); this paper demonstrates how to make CSC practical for HDR imaging. We demonstrate that the proposed algorithm achieves higher‐quality reconstructions than alternative methods, we evaluate optical coding schemes, analyze algorithmic parameters, and build a prototype coded HDR camera that demonstrates the utility of convolutional sparse HDRI coding with a custom hardware platform.     

Glyphs for Asymmetric Second‐Order 2D Tensors

Tensors model a wide range of physical phenomena. While symmetric tensors are sufficient for some applications (such as diffusion), asymmetric tensors are required, for example, to describe differential properties of fluid flow. Glyphs permit inspecting individual tensor values, but existing tensor glyphs are fully defined only for symmetric tensors. We propose a glyph to visualize asymmetric second‐order two‐dimensional tensors. The glyph includes visual encoding for physically significant attributes of the tensor, including rotation, anisotropic stretching, and isotropic dilation. Our glyph design conserves the symmetry and continuity properties of the underlying tensor, in that transformations of a tensor (such as rotation or negation) correspond to analogous transformations of the glyph. We show results with synthetic data from computational fluid dynamics.     

Parallel Marching Blocks: A Practical Isosurfacing Algorithm for Large Data on Many‐Core Architectures

Interactive isosurface visualisation has been made possible by mapping algorithms to GPU architectures. However, current state‐of‐the‐art isosurfacing algorithms usually consume large amounts of GPU memory owing to the additional acceleration structures they require. As a result, the continued limitations on available GPU memory mean that they are unable to deal with the larger datasets that are now increasingly becoming prevalent. This paper proposes a new parallel isosurface‐extraction algorithm that exploits the blocked organisation of the parallel threads found in modern many‐core platforms to achieve fast isosurface extraction and reduce the associated memory requirements. This is achieved by optimising thread co‐operation within thread‐blocks and reducing redundant computation; ultimately, an indexed triangular mesh can be produced. Experiments have shown that the proposed algorithm is much faster (up to 10×) than state‐of‐the‐art GPU algorithms and has a much smaller memory footprint, enabling it to handle much larger datasets (up to 64×) on the same GPU.     

Invariant crease lines for topological and structural analysis of tensor fields

We introduce a versatile framework for characterizing and extracting salient structures in three-dimensional symmetric second-order tensor fields. The key insight is that degenerate lines in tensor fields, as defined by the standard topological approach, are exactly crease (ridge and valley) lines of a particular tensor invariant called mode. This reformulation allows us to apply well-studied approaches from scientific visualization or computer vision to the extraction of topological lines in tensor fields. More generally, this main result suggests that other tensor invariants, such as anisotropy measures like fractional anisotropy (FA), can be used in the same framework in lieu of mode to identify important structural properties in tensor fields. Our implementation addresses the specific challenge posed by the non-linearity of the considered scalar measures and by the smoothness requirement of the crease manifold computation. We use a combination of smooth reconstruction kernels and adaptive refinement strategy that automatically adjust the resolution of the analysis to the spatial variation of the considered quantities. Together, these improvements allow for the robust application of existing ridge line extraction algorithms in the tensor context of our problem. Results are proposed for a diffusion tensor MRI dataset, and for a benchmark stress tensor field used in engineering research.