Measuring Lineup Difficulty By Matching Distance Metrics With Subject Choices in Crowd-Sourced Data

Graphics play a crucial role in statistical analysis and data mining. Being able to quantify structure in data that is visible in plots, and how people read the structure from plots is an ongoing challenge. The lineup protocol provides a formal framework for data plots, making inference possible. The data plot is treated like a test statistic, and lineup protocol acts like a comparison with the sampling distribution of the nulls. This article describes metrics for describing structure in data plots and evaluates them in relation to the choices that human readers made during several large Amazon Turk studies using lineups. The metrics that were more specific to the plot types tended to better match subject choices, than generic metrics. The process that we followed to evaluate metrics will be useful for general development of numerically measuring structure in plots, and also in future experiments on lineups for choosing blocks of pictures. Supplementary materials for this article are available online.     

Some contributions to the model order reduction of large scale non-linear electric circuits

Model order Reduction (MOR) has become an ubiquitous technique in the simulation of large-scale dynamical systems (i.e. 10⁴ and more equations). One technique for non-linear MOR is the trajectory piecewise-linear approach (TPWL) [1]. TPWL approximates a non-linear differential system by a weighted sum of linear systems which have a significantly reduced number of equations. One open question is which weight representations provide physical meaning of the weighted sum [2]. In this article we propose two representations. (© 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Framed! Reproducing and Revisiting 150-Year-Old Charts

The Statistical Atlases published by the Census Bureau in the late 1800s utilized a number of novel methods for displaying data. In this paper, we examine the use of framed spine and mosaic plots used in two plates of the Statistical Atlas of 1870. We use forensic statistics to recreate the data using available census information, and then use that data to create framed charts using modern plotting methods. We then examine the effectiveness of the framed charts compared to other alternatives with a user study. The data and code for this study are available online.     

Phase Field Modeling of Brittle and Ductile Fracture

The phase field modeling of brittle fracture was a topic of intense research in the last few years and is now well-established. We refer to the work [1-3], where a thermodynamically consistent framework was developed. The main advantage is that the phase-field-type diffusive crack approach is a smooth continuum formulation which avoids the modeling of discontinuities and can be implemented in a straightforward manner by multi-field finite element methods. Therefore complex crack patterns including branching can be resolved easily. In this paper, we extend the recently outlined phase field model of brittle crack propagation [1-3] towards the analysis of ductile fracture in elastic-plastic solids. In particular, we propose a formulation that is able to predict the brittle-to-ductile failure mode transition under dynamic loading that was first observed in experiments by Kalthoff and Winkler [4]. To this end, we outline a new thermodynamically consistent framework for phase field models of crack propagation in ductile elastic-plastic solids under dynamic loading, develop an incremental variational principle and consider its robust numerical implementation by a multi-field finite element method. The performance of the proposed phase field formulation of fracture is demonstrated by means of the numerical simulation of the classical Kalthoff-Winkler experiment that shows the dynamic failure mode transition. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Intelligent driving in traffic systems with partial lane discipline

It is a most common notion in traffic theory that driving in lanes and keeping lane changes to a minimum leads to smooth and laminar traffic flow, and hence to increased traffic capacity. On the other hand, there exist persistent vehicular traffic systems that are characterised by habitual disregarding of lane markings, and partial or complete loss of laminar traffic flow. Here, we explore the stability of such systems through a microscopic traffic flow model, where the degree of lane-discipline is taken as a variable, represented by the fraction of drivers that disregard lane markings completely. The results show that lane-free traffic may win over completely ordered traffic at high densities, and that partially ordered traffic leads to the poorest overall flow, while not considering the crash probability. Partial order in a lane-free system is similar to partial disorder in a lane-disciplined system in that both lead to decreased traffic capacity. This could explain the reason why standard enforcement methods, which rely on continuous increase of order, often fail to incur order to lane-free traffic systems. The results also provide an insight into the cooperative phenomena in open systems with self-driven particles.     

Complex magnetic ordering as a driving mechanism of multifunctional properties of Heusler alloys from first principles

First-principles calculations are used to study the structural, electronic and magnetic properties of (Pd, Pt)-Mn-Ni-(Ga, In, Sn, Sb) alloys, which display multifunctional properties like the magnetic shape-memory, magnetocaloric and exchange bias effect. The ab initio calculations give a basic understanding of the underlying physics which is associated with the complex magnetic behavior arising from competing ferro- and antiferromagnetic interactions with increasing number of Mn excess atoms in the unit cell. This information allows to optimize, for example, the magnetocaloric effect by using the strong influence of compositional changes on the magnetic interactions. Thermodynamic properties can be calculated by using the ab initio magnetic exchange parameters in finite-temperature Monte Carlo simulations. We present guidelines of how to improve the functional properties. For Pt-Ni-Mn-Ga alloys, a shape memory effect with 14% strain can be achieved in an external magnetic field.     

Raman spectroscopy of synthetic organic pigments used in 20th century works of art

Raman microscopy allows a non‐destructive characterisation of inorganic and organic painting materials such as pigments and organic dyestuffs. The objectives of this study are the more recent organic pigments typically present in paintings and other art works from the 20th century. More than 20 organic synthetic pigments from different chemical classes could be identified by Raman spectroscopy using different excitation wavelengths (457.9, 476.5, 487.9, 514.5, 632.8, and 1064 nm). To evaluate the performance for real paint samples, varying paint mixtures of the Hansa Yellow pigment PY 3 and the binding medium Mowilith, a polyvinyl acetate (PVAC) compound, were characterised; PY 3 was determined at a 1 wt% level in the binder. In addition, commercial tube paints containing the quinacridone violet PV 19 were studied. The pigment was clearly identified in all of these more complex oil and acrylic paints. Finally, alizarin (PR 83) and a green copper phthalocyanine pigment (PG 7) could unambiguously be identified by Raman microscopy in the painting ‘Woman with mandolin in yellow and red’ of Max Beckmann dating 1950. The discovery of a red naphthol AS pigment by Raman spectroscopy in a sample from the ‘Three field workers’ by Georg Baselitz (1964/1965) demonstrated that in some cases complementary chromatographic methods are needed for a comprehensive identification of the organic pigments. Copyright © 2008 John Wiley & Sons, Ltd.     

On numerical methods for discrete least-squares approximation by trigonometric polynomials

Fast, efficient and reliable algorithms for discrete least-squares approximation of a real-valued function given at arbitrary distinct nodes in by trigonometric polynomials are presented. The algorithms are based on schemes for the solution of inverse unitary eigenproblems and require only arithmetic operations as compared to operations needed for algorithms that ignore the structure of the problem. An algorithm which solves this problem with real-valued data and real-valued solution using only real arithmetic is given. Numerical examples are presented that show that the proposed algorithms produce consistently accurate results that are often better than those obtained by general QR decomposition methods for the least-squares problem.