8,304 research outputs found

    Edge currents as a probe of the strongly spin-polarized topological noncentrosymmetric superconductors

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    Recently the influence of antisymmetric spin-orbit coupling has been studied in novel topological superconductors such as half-Heuslers and artificial hetero-structures. We investigate the effect of Rashba and/or Dresselhaus spin-orbit couplings on the band structure and topological properties of a two-dimensional noncentrosymetric superconductor. For this goal, the topological helical edge modes are analyzed for different spin-orbit couplings as well as for several superconducting pairing symmetries. To explore the transport properties, we examine the response of the spin-polarized edge states to an exchange field in a superconductor-ferromagnet heterostructure. The broken chiral symmetry causes the uni-directional currents at opposite edges.Comment: 10 pages, 7 figure

    The material image: Artists’ approaches to reproducing texture in art

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    Since the introduction of computers, there has been a desire to improve the appearance of computer-generated objects in virtual spaces and to display the objects within complex scenes exactly as they appear in reality. This is a straightforward process for artists who through the medium of paint or silver halide are able to directly observe from nature and interpret and capture the world in a highly convincing way. However for computer generated images, the process is more complex, computers have no capability to compare whether the rendering looks right or wrong—only humans can make the final subjective decision. The evolving question is: what are the elements of paintings and drawings produced by artists that capture the qualities, texture, grain, reflection, translucency and absorption of a material, that through the application of coloured brush marks, demonstrate a convincing likeness of the material qualities of e.g.wood, metal, glass and fabric? This paper considers the relationship between texture, objects and artists’ approaches to reproducing texture in art. However texture is problematic as our visual system is able to discriminate the difference between natural and patterned texture, and incorrectly rendered surfaces can hinder understanding. Furthermore to render surfaces with no discernible pattern structure that comprises unlimited variations can result, as demonstrated by the computer generated rendering, in exceptionally large file sizes. The paper explores the relationship between imaging, artists’ approaches to reproducing representations of the attributes of material qualities, the fluid dynamics of a painterly mark, and 2.5D relief in printing. The objective is not to reproduce existing paintings or prints, but to build the surface using a deposition of pigments, paints and inks that explores the relationship between image and surface

    Haptic Hybrid Prototyping (HHP): An AR Application for Texture Evaluation with Semantic Content in Product Design

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    The manufacture of prototypes is costly in economic and temporal terms and in order to carry this out it is necessary to accept certain deviations with respect to the final finishes. This article proposes haptic hybrid prototyping, a haptic-visual product prototyping method created to help product design teams evaluate and select semantic information conveyed between product and user through texturing and ribs of a product in early stages of conceptualization. For the evaluation of this tool, an experiment was realized in which the haptic experience was compared during the interaction with final products and through the HHP. As a result, it was observed that the answers of the interviewees coincided in both situations in 81% of the cases. It was concluded that the HHP enables us to know the semantic information transmitted through haptic-visual means between product and user as well as being able to quantify the clarity with which this information is transmitted. Therefore, this new tool makes it possible to reduce the manufacturing lead time of prototypes as well as the conceptualization phase of the product, providing information on the future success of the product in the market and its economic return

    Tangible Scalar Fields

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    Data Visualization is a field that explores how to most efficiently convey information to the user, most often via visual representations like plots, graphs or glyphs. While this field of research has had great growth within the last couple of years, most of the work has been focused on the visual part of the human visual and auditory system - much less visualization work has been done in regards to the visually impaired. In this thesis, we will look at some previous methods and techniques for visualizing scalar fields via the sense of touch, and additionally provide two novel approaches to visualize a two-dimensional scalar field. Our first approach creates passive physicalizations from a scalar field in a semi-automatic pipeline by encoding the scalar value and field coordinates as positions in 3D space, which we use to construct a triangular mesh built from hexagonal pillars that can be printed on a 3D printer. We further enhance our mesh by encoding a directional attribute on the pillars, creating a visual encoding of the model orientation and improving upon a readability issue by mirroring the mesh. Our second approach uses a haptic force-feedback device to simulate the feeling of moving across a surface based on the scalar field by replicating three physical forces: the normal force, the friction force and the gravity force. We also further extend our approach by introducing a local encoding of global information about the scalar field via a volume representation build from the scalar field.Masteroppgave i informatikkINF399MAMN-PROGMAMN-IN

    Measurement, modeling and perception of painted surfaces : A Multi-scale analysis of the touch-up problem

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    Real-world surfaces typically have geometric features at a range of spatial scales. At the microscale, opaque surfaces are often characterized by bidirectional reflectance distribution functions (BRDF), which describes how a surface scatters incident light. At the mesoscale, surfaces often exhibit visible texture - stochastic or patterned arrangements of geometric features that provide visual information about surface properties such as roughness, smoothness, softness, etc. These textures also affect how light is scattered by the surface, but the effects are at a different spatial scale than those captured by the BRDF. Through this research, we investigate how microscale and mesoscale surface properties interact to contribute to overall surface appearance. This behavior is also the cause of the well-known touch-up problem in the paint industry, where two regions coated with exactly the same paint, look different in color, gloss and/or texture because of differences in application methods. At first, samples were created by applying latex paint to standard wallboard surfaces. Two application methods- spraying and rolling were used. The BRDF and texture properties of the samples were measured, which revealed differences at both the microscale and mesoscale. This data was then used as input for a physically-based image synthesis algorithm, to generate realistic images of the surfaces under different viewing conditions. In order to understand the factors that govern touch-up visibility, psychophysical tests were conducted using calibrated, digital photographs of the samples as stimuli. Images were presented in pairs and a two alternative forced choice design was used for the experiments. These judgments were then used as data for a Thurstonian scaling analysis to produce psychophysical scales of visibility, which helped determine the effect of paint formulation, application methods, and viewing and illumination conditions on the touch-up problem. The results can be used as base data towards development of a psychophysical model that relates physical differences in paint formulation and application methods to visual differences in surface appearance

    PyHST2: an hybrid distributed code for high speed tomographic reconstruction with iterative reconstruction and a priori knowledge capabilities

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    We present the PyHST2 code which is in service at ESRF for phase-contrast and absorption tomography. This code has been engineered to sustain the high data flow typical of the third generation synchrotron facilities (10 terabytes per experiment) by adopting a distributed and pipelined architecture. The code implements, beside a default filtered backprojection reconstruction, iterative reconstruction techniques with a-priori knowledge. These latter are used to improve the reconstruction quality or in order to reduce the required data volume and reach a given quality goal. The implemented a-priori knowledge techniques are based on the total variation penalisation and a new recently found convex functional which is based on overlapping patches. We give details of the different methods and their implementations while the code is distributed under free license. We provide methods for estimating, in the absence of ground-truth data, the optimal parameters values for a-priori techniques

    An investigation of skin tribology phenomena involved in tactile communication through braille and its associated psychophysical response during task-based discrimination

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    Most individuals utilize all five senses, especially their sense of sight, to create a unique sensory experience depicting the surrounding environment. Unfortunately, individuals in the blind and visually impaired (BVI) community lack the sense of sight and rely primarily on tactile means to acquire valuable or potentially vital information, leading to the advent of tactile communication methods like braille. A key challenge in controlling the haptic experience of a surface is the lack of fundamental understanding of how various surface attributes, such as friction and texture, affect the tactile response. Oftentimes, braille users experience tactile confusion when scanning complex tactual codes such as tactile graphics or advanced mathematics commonly seen in the STEM fields, but coding standards and limitations in perceptive resolution reduce the opportunity for innovating or redesigning the language to aid the reader. This dissertation aims to address confusion in tactile information transfer by identifying, characterizing, and developing an understanding of the skin-surface contact interactions experienced during braille reading in order to promote innovations in surface engineering and material design that can improve existing tactile communication methods. The authors first propose a method to directly observe an individual’s cognitive response to tactile experiences through an “oddball paradigm” discrimination task using event-related potential (ERP) via electroencephalography (EEG), a technique that is common in visual and auditory psychological sensory studies. Results indicate that varying levels of friction and roughness from textured samples (i.e. sandpaper) elicit different magnitudes of cognitive activity, suggesting that this technique may prove to be a valuable tool in identifying and understanding the root causes of tactile confusion. The second aspect of the research seeks to characterize the fundamental frictional forces that occur during braille reading by investigating the loading interactions as the fingerpad slides over a single braille dot and then progressively increasing the complexity of the topographies (i.e. dot spacing, orientation, count). Derived from Greenwood and Tabor, the authors develop and propose a multi-term friction model that predicts the adhesion and deformation frictional effects of a single feature during skin-on-dot sliding, identifying deformation as the dominant friction mechanism when a soft body slides over a spherical geometry. Incorporating both computational modeling and large-scale tribological tests under displacement-controlled sliding further decomposes the frictional loading mechanisms showing that surface tension and compression are driven by the elastic material’s Poisson effect dependent on the bulk’s position with respect to the dot feature. Here, loads in the vertical direction are governed by bulk material deformation due to contact pressure and loads in the lateral direction are governed by bulk material deformation due to both contact pressure and frictional shear

    Multi-touch Detection and Semantic Response on Non-parametric Rear-projection Surfaces

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    The ability of human beings to physically touch our surroundings has had a profound impact on our daily lives. Young children learn to explore their world by touch; likewise, many simulation and training applications benefit from natural touch interactivity. As a result, modern interfaces supporting touch input are ubiquitous. Typically, such interfaces are implemented on integrated touch-display surfaces with simple geometry that can be mathematically parameterized, such as planar surfaces and spheres; for more complicated non-parametric surfaces, such parameterizations are not available. In this dissertation, we introduce a method for generalizable optical multi-touch detection and semantic response on uninstrumented non-parametric rear-projection surfaces using an infrared-light-based multi-camera multi-projector platform. In this paradigm, touch input allows users to manipulate complex virtual 3D content that is registered to and displayed on a physical 3D object. Detected touches trigger responses with specific semantic meaning in the context of the virtual content, such as animations or audio responses. The broad problem of touch detection and response can be decomposed into three major components: determining if a touch has occurred, determining where a detected touch has occurred, and determining how to respond to a detected touch. Our fundamental contribution is the design and implementation of a relational lookup table architecture that addresses these challenges through the encoding of coordinate relationships among the cameras, the projectors, the physical surface, and the virtual content. Detecting the presence of touch input primarily involves distinguishing between touches (actual contact events) and hovers (near-contact proximity events). We present and evaluate two algorithms for touch detection and localization utilizing the lookup table architecture. One of the algorithms, a bounded plane sweep, is additionally able to estimate hover-surface distances, which we explore for interactions above surfaces. The proposed method is designed to operate with low latency and to be generalizable. We demonstrate touch-based interactions on several physical parametric and non-parametric surfaces, and we evaluate both system accuracy and the accuracy of typical users in touching desired targets on these surfaces. In a formative human-subject study, we examine how touch interactions are used in the context of healthcare and present an exploratory application of this method in patient simulation. A second study highlights the advantages of touch input on content-matched physical surfaces achieved by the proposed approach, such as decreases in induced cognitive load, increases in system usability, and increases in user touch performance. In this experiment, novice users were nearly as accurate when touching targets on a 3D head-shaped surface as when touching targets on a flat surface, and their self-perception of their accuracy was higher

    Surface engineering of tactile friction

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