Data-driven finite elements for geometry and material design

Crafting the behavior of a deformable object is difficult---whether it is a biomechanically accurate character model or a new multimaterial 3D printable design. Getting it right requires constant iteration, performed either manually or driven by an automated system. Unfortunately, Previous algorithms for accelerating three-dimensional finite element analysis of elastic objects suffer from expensive precomputation stages that rely on a priori knowledge of the object's geometry and material composition. In this paper we introduce Data-Driven Finite Elements as a solution to this problem. Given a material palette, our method constructs a metamaterial library which is reusable for subsequent simulations, regardless of object geometry and/or material composition. At runtime, we perform fast coarsening of a simulation mesh using a simple table lookup to select the appropriate metamaterial model for the coarsened elements. When the object's material distribution or geometry changes, we do not need to update the metamaterial library---we simply need to update the metamaterial assignments to the coarsened elements. An important advantage of our approach is that it is applicable to non-linear material models. This is important for designing objects that undergo finite deformation (such as those produced by multimaterial 3D printing). Our method yields speed gains of up to two orders of magnitude while maintaining good accuracy. We demonstrate the effectiveness of the method on both virtual and 3D printed examples in order to show its utility as a tool for deformable object design.National Science Foundation (U.S.) (Grant CCF-1138967)United States. Defense Advanced Research Projects Agency (N66001-12-1-4242

Designing Volumetric Truss Structures

We present the first algorithm for designing volumetric Michell Trusses. Our method uses a parametrization approach to generate trusses made of structural elements aligned with the primary direction of an object's stress field. Such trusses exhibit high strength-to-weight ratios. We demonstrate the structural robustness of our designs via a posteriori physical simulation. We believe our algorithm serves as an important complement to existing structural optimization tools and as a novel standalone design tool itself

A review and road map of entrepreneurial equity financing research

Equity financing in entrepreneurship primarily includes venture capital, corporate venture capital, angel investment, crowdfunding, and accelerators. We take stock of venture financing research to date with two main objectives: (a) to integrate, organize, and assess the large and disparate literature on venture financing; and (b) to identify key considerations relevant for the domain of venture financing moving forward. The net effect is that organizing and assessing existing research in venture financing will assist in launching meaningful, theory-driven research as existing funding models evolve and emerging funding models forge new frontiers

Hierarchical Grammar-Induced Geometry for Data-Efficient Molecular Property Prediction

The prediction of molecular properties is a crucial task in the field of material and drug discovery. The potential benefits of using deep learning techniques are reflected in the wealth of recent literature. Still, these techniques are faced with a common challenge in practice: Labeled data are limited by the cost of manual extraction from literature and laborious experimentation. In this work, we propose a data-efficient property predictor by utilizing a learnable hierarchical molecular grammar that can generate molecules from grammar production rules. Such a grammar induces an explicit geometry of the space of molecular graphs, which provides an informative prior on molecular structural similarity. The property prediction is performed using graph neural diffusion over the grammar-induced geometry. On both small and large datasets, our evaluation shows that this approach outperforms a wide spectrum of baselines, including supervised and pre-trained graph neural networks. We include a detailed ablation study and further analysis of our solution, showing its effectiveness in cases with extremely limited data. Code is available at https://github.com/gmh14/Geo-DEG.Comment: 22 pages, 10 figures; ICML 202

A First Order Predicate Logic Formulation of the 3D Reconstruction Problem and its Solution Space

This paper defines the 3D reconstruction problem as the process of reconstructing a 3D scene from numerous 2D visual images of that scene. It is well known that this problem is ill-posed, and numerous constraints and assumptions are used in 3D reconstruction algorithms in order to reduce the solution space. Unfortunately, most constraints only work in a certain range of situations and often constraints are built into the most fundamental methods (e.g. Area Based Matching assumes that all the pixels in the window belong to the same object). This paper presents a novel formulation of the 3D reconstruction problem, using a voxel framework and first order logic equations, which does not contain any additional constraints or assumptions. Solving this formulation for a set of input images gives all the possible solutions for that set, rather than picking a solution that is deemed most likely. Using this formulation, this paper studies the problem of uniqueness in 3D reconstruction and how the solution space changes for different configurations of input images. It is found that it is not possible to guarantee a unique solution, no matter how many images are taken of the scene, their orientation or even how much color variation is in the scene itself. Results of using the formulation to reconstruct a few small voxel spaces are also presented. They show that the number of solutions is extremely large for even very small voxel spaces (5 x 5 voxel space gives 10 to 10(7) solutions). This shows the need for constraints to reduce the solution space to a reasonable size. Finally, it is noted that because of the discrete nature of the formulation, the solution space size can be easily calculated, making the formulation a useful tool to numerically evaluate the usefulness of any constraints that are added

Prevalence of overweight and obesity in children aged 6–13 years—alarming increase in obesity in Cracow, Poland

This study in children aged 6–13 years (n = 1,499) was performed between October 2008 and March 2009. Height and weight measurements were taken to calculate BMI. The prevalence of overweight and obesity was determined by means of IOTF cut-offs with respect to age. Alarming is the fact that the percentage of obese children in Cracow increased dramatically from 1.04% in boys and 0.20% in girls in 1971 to 7% in boys and 3.6% in girls in 2009. In this report, a higher percentage of overweight boys was observed in rural boys (28.14%) than in urban ones (27.31%). Obesity was identified in an almost twice as high percentage of urban boys (7.78%) as in rural ones (3.52%). A higher percentage of overweight girls was registered in rural areas (16.49%) than in urban ones (16.09%). Obesity was prevailing in rural girls (4.12%) relative to their urban counterparts (3.44%). The highest number of overweight urban boys was diagnosed in the group of 12-year-olds (n = 48) and rural boys in the group of 10-year-olds (n = 39), as well as in urban girls aged 11 (n = 17) and rural girls aged 9 (n = 9). The highest number of obesity was observed in rural boys aged 12 (n = 3) and in urban boys aged 9 and 10 (n = 9 in both groups). In the group of girls, obesity prevailed in urban 9-year-olds (n = 5) and in rural 7-year-olds (n = 5). Conclusions: Overweight and obesity affect boys almost twice as frequently as girls. Obesity is twice as frequent in urban boys as in their rural peers

Human Resources and the Resource Based View of the Firm

The resource-based view (RBV) of the firm has influenced the field of strategic human resource management (SHRM) in a number of ways. This paper explores the impact of the RBV on the theoretical and empirical development of SHRM. It explores how the fields of strategy and SHRM are beginning to converge around a number of issues, and proposes a number of implications of this convergence

Calibration and Characterization of the IceCube Photomultiplier Tube

Over 5,000 PMTs are being deployed at the South Pole to compose the IceCube neutrino observatory. Many are placed deep in the ice to detect Cherenkov light emitted by the products of high-energy neutrino interactions, and others are frozen into tanks on the surface to detect particles from atmospheric cosmic ray showers. IceCube is using the 10-inch diameter R7081-02 made by Hamamatsu Photonics. This paper describes the laboratory characterization and calibration of these PMTs before deployment. PMTs were illuminated with pulses ranging from single photons to saturation level. Parameterizations are given for the single photoelectron charge spectrum and the saturation behavior. Time resolution, late pulses and afterpulses are characterized. Because the PMTs are relatively large, the cathode sensitivity uniformity was measured. The absolute photon detection efficiency was calibrated using Rayleigh-scattered photons from a nitrogen laser. Measured characteristics are discussed in the context of their relevance to IceCube event reconstruction and simulation efforts.Comment: 40 pages, 12 figure

Linking Customer Interaction and Innovation: The Mediating Role of New Organizational Practices

The notion that firms can improve their innovativeness by tapping users and customers for knowledge has become prominent in innovation studies. Similar arguments have been made in the marketing literature. We argue that neither literatures take sufficient account of firm organization. Specifically, firms that attempt to leverage user and customer knowledge in the context of innovation must design an internal organization appropriate to support it. This can be achieved in particular through the use of new organizational practices, notably, intensive vertical and lateral communication, rewarding employees for sharing and acquiring knowledge, and high levels of delegation of decision rights. In this paper, six hypotheses were developed and tested on a data set of 169 Danish firms drawn from a 2001 survey of the 1,000 largest firms in Denmark. A key result is that the link from customer knowledge to innovation is completely mediated by organizational practices