Structured document storage and refined declarative and navigational access mechanisms in HyperStorM

The combination of SGML and database technology allows to refine both declarative and navigational access mechanisms for structured document collection: with regard to declarative access, the user can formulate complex information needs without knowing a query language, the respective document type definition (DTD) or the underlying modelling. Navigational access is eased by hyperlink-rendition mechanisms going beyond plain link-integrity checking. With our approach, the database-internal representation of documents is configurable. It allows for an efficient implementation of operations, because DTD knowledge is not needed for document structure recognition. We show how the number of method invocations and the cost of parsing can be significantly reduced. Edited by Y.C. Tay. Received April 22, 1996 / Accepted March 16, 1997     

Low-Thermal-Conductivity Rare-Earth Zirconates for Potential Thermal-Barrier-Coating Applications

Rare-earth zirconates have been identified as a class of low-thermal-conductivity ceramics for possible use in thermal barrier coatings (TBCs) for gas-turbine engine applications. To document and compare the thermal conductivities of important rare-earth zirconates, we have measured the thermal conductivities of the following hot-pressed ceramics: (i) Gd₂Zr₂O₇ (pyrochlore phase), (ii) Gd₂Zr₂O₇ (fluorite phase), (iii) Gd_2.58Zr_1.57O₇ (fluorite phase), (iv) Nd₂Zr₂O₇ (pyrochlore phase), and (v) Sm₂Zr₂O₇ (pyrochlore phase). We have also measured the thermal conductivity of pressureless-sintered 7 wt% yttria-stabilized zirconia (7YSZ)—the commonly used composition in current TBCs. All rare-earth zirconates investigated here showed nearly identical thermal conductivities, all of which were ∼30% lower than the thermal conductivity of 7YSZ in the temperature range 25°–700°C. This finding is discussed qualitatively with reference to thermal-conductivity theory.     

Improved bibliographic reference parsing based on repeated patterns

Parsing details like author names and titles out of bibliographic references of scientific publications is an important issue that has received considerable attention recently. However, most existing techniques are tailored to the highly standardized reference styles used in the last two to three decades. They do not perform well with the wide variety of reference styles used in older, historic publications. Thus, they are of limited use when creating comprehensive bibliographies covering both historic and contemporary scientific publications. This paper presents a generic approach to bibliographic reference parsing, named RefParse, which is independent of any specific reference style. Its core feature is an inference mechanism that exploits the regularities inherent in any list of references to deduce its format. In addition, our approach learns names of authors, journals, and publishers to increase the accuracy in scenarios where human users double check parsing results to increase data quality. Our evaluation shows that our approach performs comparably to existing ones with contemporary reference lists and also works well with older ones.     

Multiresolution Visualization of Higher Order Adaptive Finite Element Simulations

h –p–adaptive projection with respect to any prescribed threshold value for the visual error. This projection can then be processed by various local rendering methods, e.g. color coding of data or isosurface extraction. Especially for color coding purposes modern texture capabilities are used to directly render higher polynomial data by superposition of polynomial basis function textures and final color look-up tables. Numerical experiments from CFD clearly demonstrate the applicability and efficiency of our approach. Received September 25, 2001; revised March 31, 2003 Published online: May 26, 2003 The authors acknowledge the valuable hints of the anonymous referees.     

Adaptive projection operators in multiresolution scientificvisualization

Recently, multiresolution visualization methods have become an indispensable ingredient of real-time interactive postprocessing. The enormous databases, typically coming along with some hierarchical structure, are locally resolved on different levels of detail to achieve a significant savings of CPU and rendering time. In this paper, the method of adaptive projection and the corresponding operators on data functions, respectively, are introduced. They are defined and discussed as mathematically rigorous foundations for multiresolution data analysis. Keeping in mind data from efficient numerical multigrid methods, this approach applies to hierarchical nested grids consisting of elements which are any tensor product of simplices, generated recursively by an arbitrary, finite set of refinement rules from some coarse grid. The corresponding visualization algorithms, e.g. color shading on slices or isosurface rendering, are confined to an appropriate depth-first traversal of the grid hierarchy. A continuous projection of the data onto an adaptive, extracted subgrid is thereby calculated recursively. The presented concept covers different methods of local error measurement, time-dependent data which have to be interpolated from a sequence of key frames, and a tool for local data focusing. Furthermore, it allows for a continuous level of detail     

Modeling and Simulation of Large Microstructured Particles in Magnetic‐Shape‐Memory Composites

We study composite materials in which single‐crystalline magnetic shape‐memory particles are embedded in a polymer matrix, in the limit of particles much larger than the typical domain size. We first derive an effective macroscopic model, using the mathematical theory of relaxation, and then solve it numerically for practically relevant parameters, and compare with experimental results.     

Feature sensitive multiscale editing on surfaces

A novel editing method for large triangular meshes is presented. We detect surface features, such as edge and corners, by computing local zero and first surface moments, using a robust and noise resistant method. The feature detection is encoded in a finite element matrix, passed to an algebraic multigrid (AMG) algorithm. The AMG algorithm generates a matrix hierarchy ranging from fine to coarse representations of the initial fine grid matrix. This hierarchy comes along with a corresponding multiscale of basis functions, which reflect the surface features on all hierarchy levels. We consider either these basis functions or distinct sets from an induced multiscale domain decomposition as handles for surface manipulation. We present a multiscale editor which enables Boolean operations on this domain decomposition and simply algebraic operations on the basis functions. Users can interactively design their favorite surface handles by simple grouping operations on the multiscale of domains. Several applications on large meshes underline the effectiveness and flexibility of the presented tool.     

Morphological image sequence processing

We present a morphological multi-scale method for image sequence processing, which results in a truly coupled spatio-temporal anisotropic diffusion. The aim of the method is not to smooth the level-sets of single frames but to denoise the whole sequence while retaining geometric features such as spatial edges and highly accelerated motions. This is obtained by an anisotropic spatio-temporal level-set evolution, where the additional artificial time variable serves as the multi-scale parameter. The diffusion tensor of the evolution depends on the morphology of the sequence, given by spatial curvatures of the level-sets and the curvature of trajectories (=acceleration) in sequence-time. We discuss different regularization techniques and describe an operator splitting technique for solving the problem. Finally we compare the new method with existing multi-scale image sequence processing methodologies.     

Mumford-Shah model for one-to-one edge matching.

This paper presents a new algorithm based on the Mumford-Shah model for simultaneously detecting the edge features of two images and jointly estimating a consistent set of transformations to match them. Compared to the current asymmetric methods in the literature, this fully symmetric method allows one to determine one-to-one correspondences between the edge features of two images. The entire variational model is realized in a multiscale framework of the finite element approximation. The optimization process is guided by an estimation minimization-type algorithm and an adaptive generalized gradient flow to guarantee a fast and smooth relaxation. The algorithm is tested on T1 and T2 magnetic resonance image data to study the parameter setting. We also present promising results of four applications of the proposed algorithm: interobject monomodal registration, retinal image registration, matching digital photographs of neurosurgery with its volume data, and motion estimation for frame interpolation.