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International Journal for Numerical Methods in Biomedical engineering 2000年第4期16卷

作者： Jinru Chen Department of Mathematics Nanjing Normal University Nanjing 210097 People's Republic of China Institute of Computational Mathematics and Scientific/Engineering Computing Chinese Academy of Sciences P.O. Box 2719 Beijing 100080 People's Republic of China

In this paper, the existence, uniqueness and uniform convergence of the solution of the Carey non-conforming element with non-quasi-uniform partitions is proved for non-self-adjoint and indefinite second-order elliptic problems under a minimal regularity assumption. Furthermore, the optimal error estimate for the solution of Carey non-conforming element method is obtained only under an H 2 smoothness hypothesis. Finally, a two-level Schwarz method which suits non-quasi-uniform partitions is proposed and optimal convergence for the pre-conditioned GMRES method is shown. Copyright © 2000 John Wiley & Sons, Ltd.

关键词： non-self-adjoint and indefinite Carey non-conforming element non-quasi-uniform partition minimal regularity Schwarz method

A First Glance to the Quality Assessment of Dental Photostimulable Phosphor Plates with Deep Learning

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A First Glance to the Quality Assessment of Dental Photostim...

International Joint Conference on Neural Networks (IJCNN)

作者： Ariana Bermudez Saul Calderon-Ramirez Trevor Thang Pascal Tyrrell Armaghan Moemeni Shengxiang Yang Jordina Torrents-Barrena School of Computing Costa Rica Institute of Technology Pattern Recognition and Machine Learning Group Costa Rica Centre for Computational Intelligence (CCI) De Montfort University United Kingdom Faculty of Dentistry University of Toronto Canada Department of Medical Imaging University of Toronto Canada University of Nottingham United Kingdom Department of Mathematics and Computer Engineering Universitat Rovira i Virgili Spain

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Photostimulable Phosphor Plates are commonly used in digital X-ray imaging for dentistry. During its usage, these plates get damaged, influencing the diagnosis performance and confidence of the dentistry professional. We propose a deep learning based classifier to discard or extend the use of photostimulable phosphor (PSP) plates based on their physical damage. The system automatically assesses, for the first time in the literature, when dentists should discard their plates. To validate our methodology, an in-house dataset is built on 25 PSP artifact masks (Carestream, CS 7600) digitally superimposed over 100 Complementary Metal-oxide-semiconductor (CMOS) periapical images (Carestream, RVG 6200) with known radiologic interpretations. From these 2500 images, unique subsets of 100 images were evaluated by 25 dentists to find periapical inflammatory lesions on the tooth. Doctors' opinion on whether the plates should be discarded or not was also collected. State-of-the-art deep convolutional networks were tested using fivefold cross validation, yielding classification accuracies from 87% to almost 89%. Specifically, InceptionV3 and Resnet50 obtained the best performances with statistical significance. Qualitative heat-maps showed that such models can identify and employ artifacts to decide on whether to discard the PSP plate or not. This work intends to be the base line for future works related to the automatic PSP plate assessment.

关键词： Dentistry Machine learning Sensitivity Teeth Visualization Quality assessment Diagnostic radiography

One-Sided Interface for Matrix Operations Using MPI-3 RMA: A Case Study with Elemental

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One-Sided Interface for Matrix Operations Using MPI-3 RMA: A...

International Conference on Parallel Processing (ICPP)

作者： Sayan Ghosh Jeff R. Hammond Antonio J. Peña Pavan Balaji Assefaw H. Gebremedhin Barbara Chapman School of Electrical Engineering and Computer Science Washington State University Pullman WA USA Parallel Computing Lab Intel Corp. Portland OR USA Centro Nacional de Supercomputacion Barcelona ES Mathematics and Computer Science Division Argonne National Laboratory Lemont IL USA Institute for Advanced Computational Science Stony Brook University Stony Brook NY USA

A one-sided programming model separates communication from synchronization, and is the driving principle behind partitioned global address space (PGAS) libraries such as Global Arrays (GA) and SHMEM. PGAS models expose a rich set of functionality that a developer needs in order to implement mathematical algorithms that require frequent multidimensional array accesses. However, use of existing PGAS libraries in application codes often requires significant development effort in order to fully exploit these programming models. On the other hand, a vast majority of scientific codes use MPI either directly or indirectly via third-party scientific computation libraries, and need features to support application-specific communication requirements (e.g., asynchronous update of distributed sparse matrices, commonly arising in machine learning workloads). For such codes it is often impractical to completely shift programming models in favor of special one-sided communication middleware. Instead, an elegant and productive solution is to exploit the one-sided functionality already offered by MPI-3 RMA (Remote Memory Access). We designed a general one-sided interface using the MPI-3 passive RMA model for remote matrix operations in the linear algebra library Elemental, we call the interface we designed RMAInterface. Elemental is an open source library for distributed-memory dense and sparse linear algebra and optimization. We employ RMAInterface to construct a Global Arrays-like API and demonstrate its performance scalability and competitivity with that of the existing GA (with ARMCI-MPI) for a quantum chemistry application.

关键词： Libraries Arrays Two dimensional displays computational modeling Matrices Data models

Survey of physics reasoning on uncertainty concepts in experiments: An assessment of measurement uncertainty for introductory physics labs

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Physical Review Physics Education Research 2023年第2期19卷 020139-020139页

作者： Michael Vignal Gayle Geschwind Benjamin Pollard Rachel Henderson Marcos D. Caballero H. J. Lewandowski JILA National Institute of Standards and Technology and the University of Colorado Boulder Colorado 80309 USA Department of Physics University of Colorado 390 UCB Boulder Colorado 80309 USA Department of Physics Worcester Polytechnic Institute 100 Institute Road Worcester Massachusetts 01609 USA Department of Physics & Astronomy and CREATE for STEM Institute Michigan State University East Lansing Michigan 48824 USA Department of Computational Mathematics Science & Engineering Michigan State University East Lansing Michigan 48824 USA Department of Physics and Center for Computing in Science Education University of Oslo 0315 Oslo Norway

[This paper is part of the Focused Collection on Instructional labs: Improving traditions and new directions.] Measurement uncertainty is a critical feature of experimental research in the physical sciences, and the concepts and practices surrounding measurement uncertainty are important components of physics lab courses. However, there has not been a broadly applicable, research-based assessment tool that allows physics instructors to easily measure students’ knowledge of measurement uncertainty concepts and practices. To address this need, we employed evidence-centered design to create the Survey of Physics Reasoning on Uncertainty Concepts in Experiments (SPRUCE). SPRUCE is a pre-post assessment instrument intended for use in introductory (first and second year) physics lab courses to help instructors and researchers identify student strengths and challenges with measurement uncertainty. In this paper, we discuss the development of SPRUCE’s assessment items guided by evidence-centered design, focusing on how instructors’ and researchers’ assessment priorities were incorporated into the assessment items and how students’ reasoning from pilot testing informed decisions around item answer options. We also present an example of some of the feedback an instructor would receive after implementing SPRUCE in a pre-post fashion, along with a brief discussion of how that feedback could be interpreted and acted upon.

关键词： Assessment Lower undergraduate students

Weighted p-Rényi Entropy Power Inequality: Information Theory to Quantum Shannon Theory

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arXiv 2023年

作者： Lee, Junseo Yeo, Hyeonjun Jeong, Kabgyun School of Electrical and Electronic Engineering Yonsei University Seoul03722 Korea Republic of Quantum Computing R&D Norma Inc. Seoul04799 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Research Institute of Mathematics Seoul National University Seoul08826 Korea Republic of School of Computational Sciences Korea Institute for Advanced Study Seoul02455 Korea Republic of

We study the p-Rényi entropy power inequality with a weight factor t on two independent continuous random variables X and Y . The extension essentially relies on a modulation on the sharp Young’s inequality due to Bobkov and Marsiglietti. Our research provides a key result that can be used as a fundamental research finding in quantum Shannon theory, as it offers a Rényi version of the entropy power inequality for quantum systems. Copyright © 2023, The Authors. All rights reserved.

关键词： Information theory

Understanding viscoelastic flow instabilities: Oldroyd-B and beyond

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arXiv 2022年

作者： Sánchez, Hugo A. Castillo Jovanović, Mihailo R. Kumar, Satish Morozov, Alexander Shankar, V. Subramanian, Ganesh Wilson, Helen J. Department Of Applied Mathematics And Statistics Institute Of Mathematics And Computational Sciences University Of Sao Paulo Brazil Ming Hsieh Department Of Electrical And Computer Engineering University Of Southern California Los AngelesCA90089 United States Department Of Chemical Engineering And Materials Science University Of Minnesota MinneapolisMN55455 United States SUPA School Of Physics And Astronomy The University Of Edinburgh EdinburghEH9 3FD United Kingdom Department Of Chemical Engineering Indian Institute Of Technology Kanpur208016 India Engineering Mechanics Unit Jawaharlal Nehru Center For Advanced Scientific Research Bangalore560064 India Mathematics Department University College London Gower Street LondonWC1E 6BT United Kingdom

The Oldroyd-B model has been used extensively to predict a host of instabilities in shearing flows of viscoelastic fluids, often realized experimentally using polymer solutions. The present review, written on the occasion of the birth centenary of James Oldroyd, provides an overview of instabilities found across major classes of shearing flows. These comprise (i) the canonical rectilinear shearing flows including plane Couette, plane and pipe Poiseuille flows;(ii) viscometric shearing flows with curved streamlines such as those in the TaylorCouette, cone-and-plate and parallel-plate geometries;(iii) non-viscometric shearing flows with an underlying extensional flow topology such as the flow in a cross-slot device;and (iv) multilayer shearing flows. While the underlying focus in all these cases is on results obtained using the Oldroyd-B model, we also discuss their relation to the actual instability, and as to how the shortcomings of the Oldroyd-B model may be overcome by the use of more realistic constitutive models. All the three commonly used tools of stability analysis, viz., modal linear stability, nonmodal stability, and weakly nonlinear stability analyses are discussed, with supporting evidence from experiments and numerical simulations as appropriate. Despite only accounting for a shear-rate-independent viscosity and first normal stress coefficient, the Oldroyd-B model is able to qualitatively predict the majority of instabilities in the aforementioned shearing flows. The review also highlights, where appropriate, open questions in the area of viscoelastic stability. © 2022, CC BY.

关键词： Stability

A Wall-time Minimizing Parallelization Strategy for Approximate Bayesian Computation

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arXiv 2023年

作者： Alamoudi, Emad Reck, Felipe Bundgaard, Nils Graw, Frederik Brusch, Lutz Hasenauer, Jan Schälte, Yannik University of Bonn Life and Medical Sciences Institute Bonn53113 Germany Heidelberg University BioQuant - Center for Quantitative Biology Heidelberg69120 Germany Heidelberg University Interdisciplinary Center for Scientific Computing Heidelberg69120 Germany Friedrich-Alexander-University Erlangen-Nürnberg Department of Medicine 5 Erlangen91054 Germany Dresden01062 Germany Helmholtz Zentrum München Institute of Computational Biology Neuherberg85764 Germany Technische Universität München Center for Mathematics Garching85748 Germany

Approximate Bayesian Computation (ABC) is a widely applicable and popular approach to estimating unknown parameters of mechanistic models. As ABC analyses are computationally expensive, parallelization on high-performance infrastructure is often necessary. However, the existing parallelization strategies leave resources unused at times and thus do not optimally leverage them yet. We present look-ahead scheduling, a wall-time minimizing parallelization strategy for ABC Sequential Monte Carlo algorithms, which utilizes all available resources at practically all times by proactive sampling for prospective tasks. Our strategy can be integrated in e.g. adaptive distance function and summary statistic selection schemes, which is essential in practice. Evaluation of the strategy on different problems and numbers of parallel cores reveals speed-ups of typically 10-20% and up to 50% compared to the best established approach. Thus, the proposed strategy allows to substantially improve the cost and run-time efficiency of ABC methods on high-performance infrastructure. © 2023, CC BY-NC-ND.

关键词： Bayesian networks

Scalability of high-performance PDE solvers

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arXiv 2020年

作者： Fischer, Paul Min, Misun Rathnayake, Thilina Dutta, Som Kolev, Tzanio Dobrev, Veselin Camier, Jean-Sylvain Kronbichler, Martin Warburton, Tim Swirydowicz, Kasia Brown, Jed Mathematics and Computer Science Argonne National Laboratory LemontIL60439 Department of Computer Science University of Illinois at Urbana-Champaign UrbanaIL61801 Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA94550 Institute for Computational Mechanics Technical University of Munich Garching b. Muenchen85748 Germany Department of Computer Science University of Colorado BoulderCO80309 National Renewable Energy Laboratory LakewoodCO80401 Department of Mathematics Virginia Tech BlacksburgVA24061 Mechanical & Aerospace Engineering Utah State University UT84322

Performance tests and analyses are critical to effective HPC software development and are central components in the design and implementation of computational algorithms for achieving faster simulations on existing and future computing architectures for large-scale application problems. In this paper, we explore performance and space-time trade-offs for important compute-intensive kernels of large-scale numerical solvers for PDEs that govern a wide range of physical applications. We consider a sequence of PDE-motivated bake-off problems designed to establish best practices for efficient high-order simulations across a variety of codes and platforms. We measure peak performance (degrees of freedom per second) on a fixed number of nodes and identify effective code optimization strategies for each architecture. In addition to peak performance, we identify the minimum time to solution at 80% parallel efficiency. The performance analysis is based on spectral and p-type finite elements but is equally applicable to a broad spectrum of numerical PDE discretizations, including finite difference, finite volume, and h-type finite *** Codes 35-04 Copyright © 2020, The Authors. All rights reserved.

关键词： Computer architecture

Disentangling quantum neural networks for unified estimation of quantum entropies and distance measures

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Physical Review A 2024年第6期110卷 062418-062418页

作者： Myeongjin Shin Seungwoo Lee Junseo Lee Mingyu Lee Donghwa Ji Hyeonjun Yeo Kabgyun Jeong School of Computing KAIST Daejeon 34141 South Korea Quantum AI Team Norma Inc. Seoul 04799 South Korea Department of Computer Science and Engineering Seoul National University Seoul 08826 South Korea College of Liberal Studies Seoul National University Seoul 08826 South Korea Department of Physics and Astronomy Seoul National University Seoul 08826 South Korea Research Institute of Mathematics Seoul National University Seoul 08826 South Korea School of Computational Sciences Korea Institute for Advanced Study Seoul 02455 South Korea

The estimation of quantum entropies and distance measures, such as von Neumann entropy, Rényi entropy, Tsallis entropy, trace distance, and fidelity-induced distances such as the Bures distance, has been a key area of research in quantum information science. In our study, we introduce the disentangling quantum neural network (DEQNN), designed to efficiently estimate various physical quantities in quantum information. Estimation algorithms for these quantities are generally tied to the size of the Hilbert space of the quantum state to be estimated. Our proposed DEQNN offers a unified dimensionality reduction methodology that can significantly reduce the size of the Hilbert space while preserving the values of diverse physical quantities. We provide an in-depth discussion of the physical scenarios and limitations in which our algorithm is applicable, as well as the learnability of the proposed quantum neural network.

关键词： Hilbert spaces

Automatic Variationally Stable Analysis for Finite Element Computations: Transient Convection-Diffusion Problems

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arXiv 2020年

作者： Valseth, Eirik Behnoudfar, Pouria Dawson, Clint Romkes, Albert Oden Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX78712 United States The Department of Data Science The Norwegian University of Life Science Drøbakveien 31 Ås1433 Norway Department of Scientific Computing and Numerical Analysis Simula Research Laboratory Kristian Augusts gate 23 Oslo0164 Norway PerthWA6152 Australia Department of Mechanical Engineering South Dakota School of Mines & Technology Rapid CitySD57701 United States

We present an application of stable finite element (FE) approximations of convection-diffusion initial boundary value problems (IBVPs) using a weighted least squares FE method, the automatic variationally stable finite element (AVS-FE) method [1]. The transient convection-diffusion problem leads to issues in classical FE methods as the differential operator can be considered a singular perturbation in both space and time. The stability property of the AVS-FE method, allows us significant flexibility in the construction of FE approximations in both space and time. Thus, in this paper, we take two distinct approaches to the FE discretization of the convection-diffusion problem: i) considering a space-time approach in which the temporal discretization is established using finite elements, and ii) a method of lines approach in which we employ the AVS-FE method in space whereas the temporal domain is discretized using the generalized-α method. We also consider another space-time technique in which the temporal direction is partitioned, thereby leading to finite space-time"slices" in an attempt to reduce the computational cost of the space-time discretizations. We present numerical verifications for these approaches, including numerical asymptotic convergence studies highlighting optimal convergence properties. Furthermore, in the spirit of the discontinuous Petrov-Galerkin (DPG) method by Demkowicz and Gopalakrishnan [2–6], the AVS-FE method also leads to readily available a posteriori error estimates through a Riesz representer of the residual of the AVS-FE approximations. Hence, the norm of the resulting local restrictions of these estimates serve as error indicators in both space and time for which we present multiple numerical verifications in mesh adaptive *** Codes 65M60 65M12 65M20 65M50 Copyright © 2020, The Authors. All rights reserved.

关键词： Finite element method