Automated processing for map generalization using web services

In map generalization various operators are applied to the features of a map in order to maintain and improve the legibility of the map after the scale has been changed. These operators must be applied in the proper sequence and the quality of the results must be continuously evaluated. Cartographic constraints can be used to define the conditions that have to be met in order to make a map legible and compliant to the user needs. The combinatorial optimization approaches shown in this paper use cartographic constraints to control and restrict the selection and application of a variety of different independent generalization operators into an optimal sequence. Different optimization techniques including hill climbing, simulated annealing and genetic deep search are presented and evaluated experimentally by the example of the generalization of buildings in blocks. All algorithms used in this paper have been implemented in a web services framework. This allows the use of distributed and parallel processing in order to speed up the search for optimized generalization operator sequences.

Model‐based reconstruction for T1 mapping using single‐shot inversion‐recovery radial FLASH

Quantitative parameter mapping in MRI is typically performed as a two‐step procedure where serial imaging is followed by pixelwise model fitting. In contrast, model‐based reconstructions directly reconstruct parameter maps from raw data without explicit image reconstruction. Here, we propose a method that determines T1 maps directly from multi‐channel raw data as obtained by a single‐shot inversion‐recovery radial FLASH acquisition with a Golden Angle view order. Joint reconstruction of a T1, spin‐density and flip‐angle map is formulated as a nonlinear inverse problem and solved by the iteratively regularized Gauss‐Newton method. Coil sensitivity profiles are determined from the same data in a preparatory step of the reconstruction. Validations included numerical simulations, in vitro MRI studies of an experimental T1 phantom, and in vivo studies of brain and abdomen of healthy subjects at a field strength of 3 T. The results obtained for a numerical and experimental phantom demonstrated excellent accuracy and precision of model‐based T1 mapping. In vivo studies allowed for high‐resolution T1 mapping of human brain (0.5–0.75 mm in‐plane, 4 mm section thickness) and liver (1.0 mm, 5 mm section) within 3.6–5 s. In conclusion, the proposed method for model‐based T1 mapping may become an alternative to two‐step techniques, which rely on model fitting after serial image reconstruction. More extensive clinical trials now require accelerated computation and online implementation of the algorithm. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 254–263, 2016     

Investigation of Ablation Efficiency of Stainless Steel Using Pulsed Lasers in Burst Mode

Due to its high corrosion resistance and mechanical properties, stainless steel is commonly used in various industrial applications. Although different types of stainless steel are similar in their chemical composition, they can differ significantly in their thermal diffusivity. This property is relevant in the ability of a material to conduct heat and thus, in laser processing. In this frame, this study compares the ablation efficiency and characteristics of polished stainless steel samples of the alloys AISI 304, AISI 420, and AISI 316Ti. They are irradiated with single ultrashort pulses having pulse durations between 250 fs and 10 ps as well as using GHz burst modii. The goal is to investigate the differences in both the ablation threshold and the ablation rate to improve the ablation efficiency. The results show that shorter pulse durations lead to a more efficient ablation process. On the other hand, GHz bursts are found to be, in general, less efficient. In addition, there is a significant difference in the surface morphology depending on the process parameters. The differences in the thermal diffusivity do not significantly influence the ablation threshold fluence but surface morphology and the ablation rate.     

A Shock Tube Study of the Reactions of H Atoms with COS,CS2, and H2S

Reactions of H atoms with COS, CS₂, and H₂S were studied behind reflected shock waves at temperatures between 1170 K and 1830 K and pressures around 1.0 bar by applying atomic resonance absorption spectroscopy (ARAS) for time-resolved measurements of H atoms at L_α. The thermal decomposition of a few ppm ethyl iodide (C₂H₅I) was used as a H-atom source. In the presence of a large excess of the molecular reactant COS, CS₂, or H₂S, a consumption of H was observed which follows a pseudo first-order rate law. Rate coefficients for the reactions: were determined to be: k₁ = 2.4 × 10¹⁴exp(–3415 K/T) cm³mol⁻¹s⁻¹ k₂ = 1.4 × 10¹⁵exp(–9250 K/T) cm³mol⁻¹s⁻¹ k₃ = 2.5 × 10¹⁴exp(–2890 K/T) cm³mol⁻¹s⁻¹     

Nested multigrid methods for time-periodic,parabolic optimal control problems

We present a nested multigrid method to optimize time-periodic, parabolic, partial differential equations (PDE). We consider a quadratic tracking objective with a linear parabolic PDE constraint. The first order optimality conditions, given by a coupled system of boundary value problems can be rewritten as an Fredholm integral equation of the second kind, which is solved by a multigrid of the second kind. The evaluation of the integral operator consists of solving sequentially a boundary value problem for respectively the state and the adjoints. Both problems are solved efficiently by a time-periodic space-time multigrid method.     

Ensemble classification based on generalized additive models

Generalized additive models (GAMs) are a generalization of generalized linear models (GLMs) and constitute a powerful technique which has successfully proven its ability to capture nonlinear relationships between explanatory variables and a response variable in many domains. In this paper, GAMs are proposed as base classifiers for ensemble learning. Three alternative ensemble strategies for binary classification using GAMs as base classifiers are proposed: (i) GAMbag based on Bagging, (ii) GAMrsm based on the Random Subspace Method (RSM), and (iii) GAMens as a combination of both. In an experimental validation performed on 12 data sets from the UCI repository, the proposed algorithms are benchmarked to a single GAM and to decision tree based ensemble classifiers (i.e. RSM, Bagging, Random Forest, and the recently proposed Rotation Forest). From the results a number of conclusions can be drawn. Firstly, the use of an ensemble of GAMs instead of a single GAM always leads to improved prediction performance. Secondly, GAMrsm and GAMens perform comparably, while both versions outperform GAMbag. Finally, the value of using GAMs as base classifiers in an ensemble instead of standard decision trees is demonstrated. GAMbag demonstrates performance comparable to ordinary Bagging. Moreover, GAMrsm and GAMens outperform RSM and Bagging, while these two GAM ensemble variations perform comparably to Random Forest and Rotation Forest. Sensitivity analyses are included for the number of member classifiers in the ensemble, the number of variables included in a random feature subspace and the number of degrees of freedom for GAM spline estimation.     

Information and communication technologies in the life of university freshmen: An analysis of change

The passage from secondary school to university puts students in an environment with different expectations. Not only the expectations towards learning might change, but also towards ICT competences and computer use. The purpose of this article is to find out whether freshmen, after 6 months at the university, changed their self-perception of ICT competences and computer use in comparison with their behaviour at secondary school, and what factors can explain the self-perception of ICT competences and computer use in secondary school, in the university and their possible change. Based on a panel research among 714 freshmen of a large university, this article answers the following questions: (1) What is the self-perception of ICT competences among freshmen and is there a change in this self-perception 6 months after entering the university? (2) How often and for what purpose do freshmen use a computer and is there a change in the frequency of the use of a computer? (3) What factors might influence this attitude, behaviour, and possible change? In function of the basic components of Unified Theory of Acceptance and Use of Technology (Venkatesh, Morris, Davis, & Davis, 2003) hypotheses was developed and tested to answer these questions. Students who consider the computer to be a useful instrument, have control over the computer, possess a certain level of Internet competence, and are at ease with computers are more likely to have the skills needed to maintain a computer, to develop a web site, and to use basic ICT skills. The predictors have little influence on Internet usage. The same predictors contribute modestly to the explanation of the different frequencies of computer use, and a few of the predictors explain parts of change in ICT skills and frequency of computer use.     

Illustrative stream surfaces

Stream surfaces are an intuitive approach to represent 3D vector fields. In many cases, however, they are challenging objects to visualize and to understand, due to a high degree of self-occlusion. Despite the need for adequate rendering methods, little work has been done so far in this important research area. In this paper, we present an illustrative rendering strategy for stream surfaces. In our approach, we apply various rendering techniques, which are inspired by the traditional flow illustrations drawn by Dallmann and Abraham \& Shaw in the early 1980s. Among these techniques are contour lines and halftoning to show the overall surface shape. Flow direction as well as singularities on the stream surface are depicted by illustrative surface streamlines. ;To go beyond reproducing static text book images, we provide several interaction features, such as movable cuts and slabs allowing an interactive exploration of the flow and insights into subjacent structures, e.g., the inner windings of vortex breakdown bubbles. These methods take only the parameterized stream surface as input, require no further preprocessing, and can be freely combined by the user. We explain the design, GPU-implementation, and combination of the different illustrative rendering and interaction methods and demonstrate the potential of our approach by applying it to stream surfaces from various flow simulations. ;