Procedural function-based modelling of volumetric microstructures

We propose a new approach to modelling heterogeneous objects containing internal volumetric structures with size of details orders of magnitude smaller than the overall size of the object. The proposed function-based procedural representation provides compact, precise, and arbitrarily parameterised models of coherent microstructures, which can undergo blending, deformations, and other geometric operations, and can be directly rendered and fabricated without generating any auxiliary representations (such as polygonal meshes and voxel arrays). In particular, modelling of regular lattices and cellular microstructures as well as irregular porous media is discussed and illustrated. We also present a method to estimate parameters of the given model by fitting it to microstructure data obtained with magnetic resonance imaging and other measurements of natural and artificial objects. Examples of rendering and digital fabrication of microstructure models are presented

A new mini-navigation tool allows accurate component placement during anterior total hip arthroplasty.

Introduction: Computer-assisted navigation systems have been explored in total hip arthroplasty (THA) to improve component positioning. While these systems traditionally rely on anterior pelvic plane registration, variances in soft tissue thickness overlying anatomical landmarks can lead to registration error, and the supine coronal plane has instead been proposed. The purpose of this study was to evaluate the accuracy of a novel navigation tool, using registration of the anterior pelvic plane or supine coronal plane during simulated anterior THA. Methods: Measurements regarding the acetabular component position, and changes in leg length and offset were recorded. Benchtop phantoms and target measurement values commonly seen in surgery were used for analysis. Measurements for anteversion and inclination, and changes in leg length and offset were recorded by the navigation tool and compared with the known target value of the simulation. Pearson\u27s Results: The device accurately measured cup position and leg length measurements to within 1° and 1 mm of the known target values, respectively. Across all simulations, there was a strong, positive relationship between values obtained by the device and the known target values ( Conclusion: The preliminary findings of this study suggest that the novel navigation tool tested is a potentially viable tool to improve the accuracy of component placement during THA using the anterior approach

Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data

Connected vehicle and driver's assistance applications are greatly facilitated by Enhanced Digital Maps (EDMs) that represent roadway features (e.g., lane edges or centerlines, stop bars). Due to the large number of signalized intersections and miles of roadway, manual development of EDMs on a global basis is not feasible. Mobile Terrestrial Laser Scanning (MTLS) is the preferred data acquisition method to provide data for automated EDM development. Such systems provide an MTLS trajectory and a point cloud for the roadway environment. The challenge is to automatically convert these data into an EDM. This article presents a new processing and feature extraction method, experimental demonstration providing SAE-J2735 map messages for eleven example intersections, and a discussion of the results that points out remaining challenges and suggests directions for future research.Comment: 6 pages, 5 figure

Scenic: A Language for Scenario Specification and Scene Generation

We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning. Specifically, we consider the problems of training a perception system to handle rare events, testing its performance under different conditions, and debugging failures. We show how a probabilistic programming language can help address these problems by specifying distributions encoding interesting types of inputs and sampling these to generate specialized training and test sets. More generally, such languages can be used for cyber-physical systems and robotics to write environment models, an essential prerequisite to any formal analysis. In this paper, we focus on systems like autonomous cars and robots, whose environment is a "scene", a configuration of physical objects and agents. We design a domain-specific language, Scenic, for describing "scenarios" that are distributions over scenes. As a probabilistic programming language, Scenic allows assigning distributions to features of the scene, as well as declaratively imposing hard and soft constraints over the scene. We develop specialized techniques for sampling from the resulting distribution, taking advantage of the structure provided by Scenic's domain-specific syntax. Finally, we apply Scenic in a case study on a convolutional neural network designed to detect cars in road images, improving its performance beyond that achieved by state-of-the-art synthetic data generation methods.Comment: 41 pages, 36 figures. Full version of a PLDI 2019 paper (extending UC Berkeley EECS Department Tech Report No. UCB/EECS-2018-8

Universal IMF vs dark halo response in early-type galaxies: breaking the degeneracy with the fundamental plane

We use the relations between aperture stellar velocity dispersion (\sigma_ap), stellar mass (M_sps), and galaxy size (R_e) for a sample of \sim 150,000 early-type galaxies from SDSS/DR7 to place constraints on the stellar initial mass function (IMF) and dark halo response to galaxy formation. We build LCDM based mass models that reproduce, by construction, the relations between galaxy size, light concentration and stellar mass, and use the spherical Jeans equations to predict \sigma_ap. Given our model assumptions (including those in the stellar population synthesis models), we find that reproducing the median \sigma_ap vs M_sps relation is not possible with {\it both} a universal IMF and a universal dark halo response. Significant departures from a universal IMF and/or dark halo response are required, but there is a degeneracy between these two solutions. We show that this degeneracy can be broken using the strength of the correlation between residuals of the velocity-mass (\Delta log \sigma_ap) and size-mass (\Delta log R_e) relations. The slope of this correlation, d_vr \equiv \Delta log \sigma_ap/\Delta log R_e, varies systematically with galaxy mass from d_vr \simeq -0.45 at M_sps \sim 10^{10}M_sun, to d_vr \simeq -0.15 at M_sps \sim 10^{11.6} M_sun. The virial fundamental plane (FP) has d_vr=-1/2, and thus we find the tilt of the observed FP is mass dependent. Reproducing this tilt requires {\it both} a non-universal IMF and a non-universal halo response. Our best model has mass-follows-light at low masses (Msps < 10^{11.2}M_sun) and unmodified NFW haloes at M_sps \sim 10^{11.5} M_sun. The stellar masses imply a mass dependent IMF which is "lighter" than Salpeter at low masses and "heavier" than Salpeter at high masses.Comment: 19 pages, 16 figures, accepted to MNRAS. More extensive discussion, 4 new figures, conclusions unchange

From 3D Models to 3D Prints: an Overview of the Processing Pipeline

Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044