Automated property verification for large scale B models with ProB

In this paper we describe the successful application of the ProB tool for data validation in several industrial applications. The initial case study centred on the San Juan metro system installed by Siemens. The control software was developed and formally proven with B. However, the development contains certain assumptions about the actual rail network topology which have to be validated separately in order to ensure safe operation. For this task, Siemens has developed custom proof rules for Atelier B. Atelier B, however, was unable to deal with about 80 properties of the deployment (running out of memory). These properties thus had to be validated by hand at great expense, and they need to be revalidated whenever the rail network infrastructure changes. In this paper we show how we were able to use ProB to validate all of the about 300 properties of the San Juan deployment, detecting exactly the same faults automatically in a few minutes that were manually uncovered in about one man-month. We have repeated this task for three ongoing projects at Siemens, notably the ongoing automatisation of the line 1 of the Paris Métro. Here again, about a man month of effort has been replaced by a few minutes of computation. This achievement required the extension of the ProB kernel for large sets as well as an improved constraint propagation algorithm. We also outline some of the effort and features that were required in moving from a tool capable of dealing with medium-sized examples towards a tool able to deal with actual industrial specifications. We also describe the issue of validating ProB, so that it can be integrated into the SIL4 development chain at Siemens.     

Solving Third Order Differential Equations with Maximal Symmetry Group

The largest group of Lie symmetries that a third-order ordinary differential equation (ode) may allow has seven parameters. Equations sharing this property belong to a single equivalence class with a canonical representative v ^′′′(u)=0. Due to this simple canonical form, any equation belonging to this equivalence class may be identified in terms of certain constraints for its coefficients. Furthermore a set of equations for the transformation functions to canonical form may be set up for which large classes of solutions may be determined algorithmically. Based on these steps a solution algorithm is described for any equation with this symmetry type which resembles a similar scheme for second order equations with projective symmetry group. Received March 9, 2000; revised June 8, 2000     

Using visual design experts in critique-based evaluation of 2D vector visualization methods

We describe an experiment in which art and illustration experts evaluated six 2D vector visualization methods. We found that these expert critiques mirrored previously recorded experimental results; these findings support that using artists, visual designers and illustrators to critique scientific visualizations can be faster and more productive than quantitative user studies. Our participants successfully evaluated how well the given methods would let users complete a given set of tasks. Our results show a statistically significant correlation with a previous objective study: designers' subjective predictions of user performance by these methods match users measured performance. The experts improved the evaluation by providing insights into the reasons for the effectiveness of each visualization method and suggesting specific improvements.     

Scientific sketching for collaborative VR visualization design

We present four studies investigating tools and methodologies for artist-scientist-technologist collaboration in designing multivariate, virtual reality (VR) visualizations. Design study 1 identifies the promise of 3D drawing-style interfaces for VR design and also establishes limitations of these tools with respect to precision and support for animation. Design study 2 explores animating artist-created visualization designs with scientific 3D fluid flow data. While results captured an accurate sense of flow that was advantageous as compared to the results of study 1, the potential for visual exploration using the design tools tested was limited. Design study 3 reveals the importance of a new 3D interface that overcomes the precision limitation found in study 1 while remaining accessible to artist collaborators. Drawing upon previous results, design study 4 engages collaborative teams in a design process that begins with traditional paper sketching and moves to animated, interactive, VR prototypes "sketched" by designers in VR using interactive 3D tools. Conclusions from these four studies identify important characteristics of effective artist-accessible VR visualization design tools and lead to a proposed formalized methodology for successful collaborative design that we expect to be useful in guiding future collaborations. We call this proposed methodology Scientific Sketching.     

Interactive volume exploration for feature detection and quantification in industrial CT data

This paper presents a novel method for interactive exploration of industrial CT volumes such as cast metal parts, with the goal of interactively detecting, classifying, and quantifying features using a visualization-driven approach. The standard approach for defect detection builds on region growing, which requires manually tuning parameters such as target ranges for density and size, variance, as well as the specification of seed points. If the results are not satisfactory, region growing must be performed again with different parameters. In contrast, our method allows interactive exploration of the parameter space, completely separated from region growing in an unattended pre-processing stage. The pre-computed feature volume tracks a feature size curve for each voxel over time, which is identified with the main region growing parameter such as variance. A novel 3D transfer function domain over (density, feature size, time) allows for interactive exploration of feature classes. Features and feature size curves can also be explored individually, which helps with transfer function specification and allows coloring individual features and disabling features resulting from CT artifacts. Based on the classification obtained through exploration, the classified features can be quantified immediately.     

Learning Perceptrons and Piecewise Linear Classifiers Sensitive to Example Dependent Costs

This article considers the cost dependent construction of linear and piecewise linear classifiers. Classical learning algorithms from the fields of artificial neural networks and machine learning consider either no costs at all or allow only costs that depend on the classes of the examples that are used for learning. In contrast to class dependent costs, we consider costs that are example, i.e. feature and class dependent. We present a cost sensitive extension of a modified version of the well-known perceptron algorithm that can also be applied in cases, where the classes are linearly non-separable. We also present an extended version of the hybrid learning algorithm DIPOL, that can be applied in the case of linear non-separability, multi-modal class distributions, and multi-class learning problems. We show that the consideration of example dependent costs is a true extension of class dependent costs. The approach is general and can be extended to other neural network architectures like multi-layer perceptrons and radial basis function networks.     

Proton incorporation in yttria-stabilized zirconia during atomic layer deposition

This work elucidated the proton-incorporation mechanism in ALD YSZ¹. Isotope ²H₂O was used as an oxidant to trace proton incorporation. The ratio of ZrO₂ to Y₂O₃ ALD cycles was varied from 1:1 to 5:1. TEM confirmed that the ALD YSZ films grew as fully crystallized columnar grains in the cubic ZrO₂ phase. SIMS indicated that the Y³⁺ and ²H⁺ concentrations were linearly correlated, indicating yttria-deposition-induced proton incorporation. XPS confirmed an appreciable amount of Y(OH)₃ proportional to the ²H⁺ content in the ALD YSZ, as was also detected by SIMS. Oxide ion vacancies created by the replacement of ZrO₂ with relatively small amounts of Y₂O₃ provided additional vacancies for proton incorporation, resulting in steeper [²H⁺]/[Y³⁺] slopes.     

Influence of Surface Modifications on the Spatiotemporal Microdistribution of Quantum Dots In Vivo

For biomedical applications of nanoconstructs, it is a general prerequisite to efficiently reach the desired target site. In this regard, it is crucial to determine the spatiotemporal distribution of nanomaterials at the microscopic tissue level. Therefore, the effect of different surface modifications on the distribution of microinjected quantum dots (QDs) in mouse skeletal muscle tissue has been investigated. In vivo real‐time fluorescence microscopy and particle tracking reveal that carboxyl QDs preferentially attach to components of the extracellular matrix (ECM), whereas QDs coated with polyethylene glycol (PEG) show little interaction with tissue constituents. Transmission electron microscopy elucidates that carboxyl QDs adhere to collagen fibers as well as basement membranes, a type of ECM located on the basolateral side of blood vessel walls. Moreover, carboxyl QDs have been found in endothelial junctions as well as in caveolae of endothelial cells, enabling them to translocate into the vessel lumen. The in vivo QD distribution is confirmed by in vitro experiments. The data suggest that ECM components act as a selective barrier depending on QD surface modification. For future biomedical applications, such as targeting of blood vessel walls, the findings of this study offer design criteria for nanoconstructs that meet the requirements of the respective application.