Robustness with dynamic IQCs: An exact state-space characterization of nominal stability with applications to robust estimation

For robustness analysis with integral quadratic constraints, we formulate a new positivity condition on the solution of the corresponding linear matrix inequality which is necessary and sufficient for nominal stability of the underlying system. The application of this technical result is illustrated by a complete solution of the L₂-gain and robust H₂-estimator design problems if the uncertainties are characterized by dynamic integral quadratic constraints.     

Effect of Berezinskii-Kosterlitz-Thouless vortex fluctuations on the nuclear spin relaxation rate

In this work we examine the influence of the diffusive motion of vortices in highly anisotropic high-T_c superconductors near the Berezinskii-Kosterlitz-Thouless (BKT) transition temperature T _bkt on the spin-lattice relaxation rate T ₁ ^–1 .We find a jump in T ₁ ^–1 at the temperature T _bkt .     

X-ray focusing with lobster-eye optics: a comparison of theory with experiment

We report an experimental investigation and comparison with simulation of the x-ray focusing of a flat, square profile microchannel plate. We use x rays with an energy of ~1.5 keV from a laser-produced plasma. The images were recorded with x-ray film. We find the focal structure to be consistent with theoretical expectations. The angular resolution of the focus is 0.96 mrad, which is a major improvement over previous results. The measured peak intensity gain is 27 ± 4, which is ~33% of that for a perfect optic.     

Adaptive control of straight worms without derivative measurement

In this paper we consider an adaptive control problem of finite DoF worm-like locomotion systems (WLLS) which contact the ground with Coulomb dry friction. Using a rough mathematical friction law the system is shown to belong to a system class that allows adaptive control. Gaits from the kinematic theory can be tracked by means of adaptive controllers. For this we introduce two different adaptive controllers for λ-tracking and focus on that one which is not based on the derivative of the output. We pay attention to the analysis of such systems and present some theoretical control investigations including proofs. Numerical simulations of tracking different reference signals under arbitrary choice of the system parameters demonstrate and illustrate that the introduced simple adaptive controllers work successfully and effectively. Current experiments are aimed at the justification of theoretical results.     

Coherent Culling and Shading for Large Molecular Dynamics Visualization

Molecular dynamics simulations are a principal tool for studying molecular systems. Such simulations are used to investigate molecular structure, dynamics, and thermodynamical properties, as well as a replacement for, or complement to, costly and dangerous experiments. With the increasing availability of computational power the resulting data sets are becoming increasingly larger, and benchmarks indicate that the interactive visualization on desktop computers poses a challenge when rendering substantially more than millions of glyphs. Trading visual quality for rendering performance is a common approach when interactivity has to be guaranteed. In this paper we address both problems and present a method for high‐quality visualization of massive molecular dynamics data sets. We employ several optimization strategies on different levels of granularity, such as data quantization, data caching in video memory, and a two‐level occlusion culling strategy: coarse culling via hardware occlusion queries and a vertex‐level culling using maximum depth mipmaps. To ensure optimal image quality we employ GPU raycasting and deferred shading with smooth normal vector generation. We demonstrate that our method allows us to interactively render data sets containing tens of millions of high‐quality glyphs.     

Rule cubes for causal investigations

With the complexity of modern vehicles tremendously increasing, quality engineers play a key role within today’s automotive industry. Field data analysis supports corrective actions in development, production and after sales support. We decompose the requirements and show that association rules, being a popular approach to generating explanative models, still exhibit shortcomings. Interactive rule cubes, which have been proposed recently, are a promising alternative. We extend this work by introducing a way of intuitively visualizing and meaningfully ranking them. Moreover, we present methods to interactively factorize a problem and validate hypotheses by ranking patterns based on expectations, and by browsing a cube-based network of related influences. All this is currently in use as an interactive tool for warranty data analysis in the automotive industry. A real-world case study shows how engineers successfully use it in identifying root causes of quality issues.

Estimating body shape of dressed humans

The paper presents a method to estimate the detailed 3D body shape of a person even if heavy or loose clothing is worn. The approach is based on a space of human shapes, learned from a large database of registered body scans. Together with this database we use as input a 3D scan or model of the person wearing clothes and apply a fitting method, based on ICP (iterated closest point) registration and Laplacian mesh deformation. The statistical model of human body shapes enforces that the model stays within the space of human shapes. The method therefore allows us to compute the most likely shape and pose of the subject, even if it is heavily occluded or body parts are not visible. Several experiments demonstrate the applicability and accuracy of our approach to recover occluded or missing body parts from 3D laser scans.     

TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture,Layout, and Context

This paper details a new approach for learning a discriminative model of object classes, incorporating texture, layout, and context information efficiently. The learned model is used for automatic visual understanding and semantic segmentation of photographs. Our discriminative model exploits texture-layout filters, novel features based on textons, which jointly model patterns of texture and their spatial layout. Unary classification and feature selection is achieved using shared boosting to give an efficient classifier which can be applied to a large number of classes. Accurate image segmentation is achieved by incorporating the unary classifier in a conditional random field, which (i) captures the spatial interactions between class labels of neighboring pixels, and (ii) improves the segmentation of specific object instances. Efficient training of the model on large datasets is achieved by exploiting both random feature selection and piecewise training methods. High classification and segmentation accuracy is demonstrated on four varied databases: (i) the MSRC 21-class database containing photographs of real objects viewed under general lighting conditions, poses and viewpoints, (ii) the 7-class Corel subset and (iii) the 7-class Sowerby database used in He et al. (Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 695–702, June 2004), and (iv) a set of video sequences of television shows. The proposed algorithm gives competitive and visually pleasing results for objects that are highly textured (grass, trees, etc.), highly structured (cars, faces, bicycles, airplanes, etc.), and even articulated (body, cow, etc.). J. Shotton is now working at Toshiba Corporate Research & Development Center, Kawasaki, Japan.     

Guaranteeing hard real-time traffic with legitimately short deadlines with the timed token protocol

Synchronous bandwidth, defined as the maximum time a node is allowed to send its synchronous messages while holding the token, is a sensitive parameter for deadline guarantees of synchronous messages in any timed token network. In order to offer such guarantees, synchronous bandwidth has to be allocated carefully to each individual node. This paper studies the synchronous bandwidth allocated to those synchronous message streams whose deadlines are less than twice the Target Token Rotation Time (TTRT). A new approach for allocating synchronous bandwidth to such streams, which can be used with any previously published local synchronous bandwidth allocation (SBA) for guaranteeing a general synchronous message set with its minimum deadline (D_min) no less than 2 · TTRT, is proposed. The proposed scheme can be applied efficiently in practice to any general synchronous message set with D_min > TTRT. Numerical examples are presented to demonstrate the enhanced performance of this new local scheme over any of the previously published local SBA schemes.     

A priori and a posteriori analysis for a locking-free low order quadrilateral hybrid finite element for Reissner–Mindlin plates

This paper proposes a quadrilateral finite element method of the lowest order for Reissner–Mindlin (R–M) plates on the basis of Hellinger–Reissner variational principle, which includes variables of displacements, shear stresses and bending moments. This method uses continuous piecewise isoparametric bilinear interpolation for the approximation of transverse displacement and rotation. The piecewise-independent shear stress/bending moment approximation is constructed by following a self-equilibrium criterion and a shear-stress-enhanced condition. A priori and reliable a posteriori error estimates are derived and shown to be uniform with respect to the plate thickness t. Numerical experiments confirm the theoretical results.