检索结果-内蒙古大学图书馆

Finding key points in a hand image using heatmaps 23

学校读者我要写书评

暂无评论

Finding key points in a hand image using heatmaps

23rd International Youth Scientific School on Coherent Optics and Optical Spectroscopy, COOS 2019

作者： Arslanova, D.V. Grishin, A.E. Denisov, A.I. Galimullin, D.Z. Denisova, N.V. Makarov, R.A. Sibgatullin, M.E. Institute of Computational Mathematics and Information Technology Kazan Federal University Kazan Russia Kazan State Power Engineering University Kazan Russia Kazan Russia Tatarstan Academy of Sciences Institute of Applied Research Kazan Russia Institute of Physics Kazan Federal University Kazan Russia

This paper presents an approach to finding key points in the image of a hand using heat maps. For this, a convolutional model of a neural network and a training method on heatmaps were combined. An open bank of palm photos, supplemented by a set of own images and synthetic data, was used as a dataset. Direct and inverse transformations of two-dimensional coordinates on the plane into heat maps with a 2D Gaussian function centered at coordinate points were applied, data was prepared, the model was trained and tested. As a result of this approach, a neural network model able to recognise real world images was obtained. © Published under licence by IOP Publishing Ltd.

关键词： Neural network models

Unprivileged groups are less served by green cooling services in major European urban areas

学校读者我要写书评

暂无评论

Nature Cities

Nature Cities 2024年 424-435页

作者： Alby Duarte Rocha Stenka Vulova Michael Förster Birgit Kleinschmit Beniamino Gioli Bradley Matthews Carole Helfter Fred Meier Gert-Jan Steeneveld Janet F. Barlow Leena Järvi Nektarios Chrysoulakis Giacomo Nicolini Geoinformation in Environmental Planning Lab Technische Universität Berlin Berlin Germany Department of Environmental Meteorology University of Kassel Kassel Germany Institute of BioEconomy National Research Council (IBE-CNR) Florence Italy Department of Forest- and Soil Sciences Institute of Forest Ecology University of Natural Resources and Life Sciences Vienna Austria Environment Agency Austria Vienna Austria UK Center for Ecology and Hydrology Penicuik UK Chair of Climatology Institute of Ecology Technische Universität Berlin Berlin Germany Meteorology and Air Quality Section Wageningen University Wageningen the Netherlands Department of Meteorology University of Reading Reading UK Institute for Atmospheric and Earth System Research/Physics Helsinki Institute of Sustainability Science University of Helsinki Helsinki Finland Remote Sensing Lab Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas Heraklion Greece CMCC Foundation Euro-Mediterranean Center on Climate Change Viterbo Italy

Heat stress is the leading climate-related cause of premature deaths in Europe. Major heatwaves have struck Europe recently and are expected to increase in magnitude and length. Large cities are particularly threatened due to the urban morphology and imperviousness. Green spaces mitigate heat, providing cooling services through shade provision and evapotranspiration. However, the distribution of green cooling and the population most affected are often unknown. Here we reveal environmental injustice regarding green cooling in 14 major European urban areas. Vulnerable residents in Europe are not concentrated in the suburbs but in run-down central areas that coincide with low-cooling regions. In all studied areas, lower-income residents, tenants, immigrants and unemployed citizens receive below-average green cooling, while upper-income residents, nationals and homeowners experience above-average cooling provision. The fatality risk during extreme heatwaves may increase as vulnerable residents are unable to afford passive or active cooling mitigation.

关键词：

Erratum: "Controlling species densities in structurally perturbed intransitive cycles with higher-order interactions" [Chaos 32(10), 103122 (2022)]

学校读者我要写书评

暂无评论

Chaos (Woodbury, N.Y.) 2023年第4期33卷 049901页

作者： Sourin Chatterjee Sayantan Nag Chowdhury Dibakar Ghosh Chittaranjan Hens Department of Mathematics and Statistics Indian Institute of Science Education and Research Kolkata West Bengal 741246 India. Physics and Applied Mathematics Unit Indian Statistical Institute 203 B. T. Road Kolkata 700108 India. Technology Innovation Hub (TIH) IDEAS (Institute of Data Engineering Analytics and Science Foundation) @ Indian Statistical Institute 203 B. T. Road Kolkata 700108 India. International Institute of Information Technology Gachibowli Hyderabad 500032 India.

Recently, we noticed Figs. 4 and 5 were interchanged in Ref. 1, although their respective captions remain correct (Figs. 1 and 2). A typing mistake in mathemati

关键词：

Generalized Young measures and the hydrodynamic limit of condensing zero range processes

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Loulakis, Michail Stamatakis, Marios G. School of Applied Mathematical and Physical Sciences National Technical University of Athens Polytechnioulopis Zographou Athens15780 Greece Institute of Applied and Computational Mathematics Foundation for Research and Technology Hellas Greece

Condensing zero range processes (ZRPs) are stochastic interacting particle systems that exhibit phase separation with the emergence of a condensate. Standard approaches for deriving a hydrodynamic limit of the density fail in these models, and an effective macroscopic description has not been rigorously established, yet. In this article we prove that the limiting triple (π, W, σ) of the empirical density, the empirical current, and the empirical jump rate of the ZRP satisfies the continuity equation ∂tπ = −divW in the sense of distributions. Here (πt)t≥0 is a w∗continuous curve of finite non-negative measures on the torus Td, σt ∈ H1(Td) and Wt = −∇σt is a vector-valued measure that is absolutely continuous with respect to the Lebesgue measure, for all almost all t ≥ 0. In order to obtain a closed equation we propose a generalization of Young measures and we prove that for symmetric ZRPs on the torus, the hydrodynamic limit of the density is a generalized Young-measure-valued weak solution π = (πt)t≥0 to a saturated filtration equation ∂tπ = ∆Φ(π). Furthermore we prove a one-sided two-blocks estimate and we give an equivalent criterion for its validity. Assuming the validity of the two-blocks estimate one obtains the equation ∂tπ = ∆Φ(πac) for the empirical density, where π = πac + π is the Radon-Nikodym decomposition.60K35, 82C22, 35K65, 46S50 Copyright © 2019, The Authors. All rights reserved.

关键词： Phase separation

Moosinesq Convection in the Cores of Moosive Stars

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Anders, Evan H. Bauer, Evan B. Jermyn, Adam S. Van Kooten, Samuel J. Brown, Benjamin P. Hester, Eric W. Wilkinson, Mindy Goldberg, Jared A. Varesano, Tania Lecoanet, Daniel CIERA Northwestern University EvanstonIL60201 United States Center for Astrophysics | Harvard & Smithsonian 60 Garden St. CambridgeMA02138 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Southwest Research Institute BoulderCO80302 United States Department Astrophysical and Planetary Sciences LASP University of Colorado BoulderCO80309 United States Department of Mathematics The University of California Los Angeles 520 Portola Plaza CA90024 United States Primum Terrae LLC BoulderCO80302 United States Department of Physics University of California Santa BarbaraCA93106 United States Grenoble Institute of Technology Grenoble France Department of Engineering Sciences and Applied Mathematics Northwestern University EvanstonIL60208 United States

Stars with masses 4 × 1027Mmoose ≈ 1.1Mo have core convection zones during their time on the main sequence. In these moosive stars, convection introduces many uncertainties in stellar modeling. In this Letter, we build upon the Boussinesq approximation to present the first-ever simulations of Moosinesq convection, which captures the complex geometric structure of the convection zones of these stars. These flows are bounded in a manner informed by the majestic terrestrial Alces alces (moose) and could have important consequences for the evolution of these stars. We find that Moosinesq convection results in very interesting flow morphologies and rapid heat transfer, and posit this as a mechanism of biomechanical thermoregulation. Copyright © 2022, The Authors. All rights reserved.

关键词： Uncertainty analysis

DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Zeng, Jinzhe Zhang, Duo Peng, Anyang Zhang, Xiangyu He, Sensen Wang, Yan Liu, Xinzijian Bi, Hangrui Li, Yifan Cai, Chun Zhang, Chengqian Du, Yiming Zhu, Jia-Xin Mo, Pinghui Huang, Zhengtao Zeng, Qiyu Shi, Shaochen Qin, Xuejian Yu, Zhaoxi Luo, Chenxing Ding, Ye Liu, Yun-Pei Shi, Ruosong Wang, Zhenyu Bore, Sigbjørn Løland Chang, Junhan Deng, Zhe Ding, Zhaohan Han, Siyuan Jiang, Wanrun Ke, Guolin Liu, Zhaoqing Lu, Denghui Muraoka, Koki Oliaei, Hananeh Singh, Anurag Kumar Que, Haohui Xu, Weihong Xu, Zhangmancang Zhuang, Yong-Bin Dai, Jiayu Giese, Timothy J. Jia, Weile Xu, Ben York, Darrin M. Zhang, Linfeng Wang, Han School of Artificial Intelligence and Data Science Unversity of Science and Technology of China Hefei China AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing China Baidu Inc. Beijing China Department of Computer Science University of Toronto TorontoON Canada Department of Chemistry Princeton University PrincetonNJ08540 United States University of Chinese Academy of Sciences Beijing100871 China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEM College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China College of Integrated Circuits Hunan University Changsha410082 China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Smart Materials and Device Integration School of Material Science and Engineering Wuhan University of Technology Wuhan430070 China College of Science National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense Technology Changsha410073 China ByteDance Research Beijing100098 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Department of Geosciences Princeton University PrincetonNJ08544 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States IKKEM Fujian Xiamen361005 China Graduate

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for molecular dynamics (MD) simulations and related applications. These packages, typically built on specific machine learning frameworks such as TensorFlow, PyTorch, or JAX, face integration challenges when advanced applications demand communication across different frameworks. The previous TensorFlow-based implementation of DeePMD-kit exemplified these limitations. In this work, we introduce DeePMD-kit version 3, a significant update featuring a multi-backend framework that supports TensorFlow, PyTorch, JAX, and PaddlePaddle backends, and demonstrate the versatility of this architecture through the integration of other MLPs packages and of Differentiable Molecular Force Field. This architecture allows seamless backend switching with minimal modifications, enabling users and developers to integrate DeePMD-kit with other packages using different machine learning frameworks. This innovation facilitates the development of more complex and interoperable workflows, paving the way for broader applications of MLPs in scientific research. Copyright © 2025, The Authors. All rights reserved.

关键词： Molecular dynamics

Navigating the challenges in creating complex data systems: a development philosophy

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Dittmer, Sören Roberts, Michael Gilbey, Julian Biguri, Ander Preller, Jacobus Rudd, James H.F. Aston, John A.D. Schönlieb, Carola-Bibiane Selby, Ian Breger, Anna Thorpe, Matthew Weir-McCall, Jonathan R. Gkrania-Klotsas, Effrossyni Korhonen, Anna Jefferson, Emily Langs, Georg Yang, Guang Prosch, Helmut Stanczuk, Jan Tang, Jing Babar, Judith Sánchez, Lorena Escudero Teare, Philip Patel, Mishal Wassin, Marcel Holzer, Markus Walton, Nicholas Lió, Pietro Shadbahr, Tolou Sala, Evis Department of Applied Mathematics and Theoretical Physics University of Cambridge Cambridge United Kingdom Addenbrooke’s Hospital Cambridge University Hospitals NHS Trust Cambridge United Kingdom Department of Medicine University of Cambridge Cambridge United Kingdom Department of Pure Mathematics and Mathematical Statistics University of Cambridge Cambridge United Kingdom ZeTeM University of Bremen Bremen Germany Department of Radiology University of Cambridge Cambridge United Kingdom Faculty of Mathematics University of Vienna Austria Department of Mathematics University of Manchester Manchester United Kingdom Royal Papworth Hospital Cambridge Royal Papworth Hospital NHS Foundation Trust Cambridge United Kingdom Language Technology Laboratory University of Cambridge Cambridge United Kingdom Population Health and Genomics School of Medicine University of Dundee Dundee United Kingdom Department of Biomedical Imaging and Image-guided Therapy Computational Imaging Research Lab Medical University of Vienna Vienna Austria National Heart and Lung Institute Imperial College London London United Kingdom Research Program in Systems Oncology Faculty of Medicine University of Helsinki Helsinki Finland Data Science & Artificial Intelligence AstraZeneca Cambridge United Kingdom Clinical Pharmacology & Safety Sciences AstraZeneca Cambridge United Kingdom Contextflow GmbH Vienna Austria Institute of Astronomy University of Cambridge Cambridge United Kingdom Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom

In this perspective, we argue that despite the democratization of powerful tools for data science and machine learning over the last decade, developing the code for a trustworthy and effective data science system (DSS) is getting harder. Perverse incentives and a lack of widespread software engineering (SE) skills are among many root causes we identify that naturally give rise to the current systemic crisis in reproducibility of DSSs. We analyze why SE and building large complex systems is, in general, hard. Based on these insights, we identify how SE addresses those difficulties and how we can apply and generalize SE methods to construct DSSs that are fit for purpose. We advocate two key development philosophies, namely that one should incrementally grow – not biphasically plan and build – DSSs, and one should always employ two types of feedback loops during development: one which tests the code’s correctness and another that evaluates the code’s efficacy. Copyright © 2022, The Authors. All rights reserved.

关键词： Software engineering

A local character based method for solving linear systems of radiation diffusion problemsI

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Ye, Shuai An, Hengbin Xu, Xinhai State Key Laboratory of High Performance Computing National University of Defense Technology Changsha410073 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing100094 China CAEP Software Center for High Performance Numerical Simulation Beijing100088 China Artificial Intelligence Research Center National Innovation Institute of Defense Technology Beijing100071 China

The radiation diffusion problem is a kind of time-dependent nonlinear equations. For solving the radiation diffusion equations, many linear systems are obtained in the nonlinear iterations at each time step. The cost of linear equations dominates the numerical simulation of radiation diffusion applications, such as inertial confinement fusion, etc. Usually, iterative methods are used to solve the linear systems in a real application. Moreover, the solution of the previous nonlinear iteration or the solution of the previous time step is typically used as the initial guess for solving the current linear equations. Because of the strong local character in ICF, with the advancing of nonlinear iteration and time step, the solution of the linear system changes dramatically in some local domain, and changes mildly or even has no change in the rest domain. In this paper, a local character-based method is proposed to solve the linear systems of radiation diffusion problems. The proposed method consists of three steps: Firstly, a local domain (algebraic domain) is constructed;secondly, the subsystem on the local domain is solved;and lastly, the whole system will be solved. Two methods are given to construct the local domain. One is based on the spatial gradient, and the other is based on the residual. Numerical tests for a two-dimensional heat conduction model problem, and two real application models, the multi-group radiation diffusion equations and the three temperature energy equations, are conducted. The test results show that the solution time for solving the linear system can be reduced dramatically by using the local character-based method. Copyright © 2020, The Authors. All rights reserved.

关键词： Linear systems

Leveraging randomized compiling for the quantum imaginary-time-evolution algorithm

学校读者我要写书评

暂无评论

Physical Review research 2022年第3期4卷 033140-033140页

作者： Jean-Loup Ville Alexis Morvan Akel Hashim Ravi K. Naik Marie Lu Bradley Mitchell John-Mark Kreikebaum Kevin P. O'Brien Joel J. Wallman Ian Hincks Joseph Emerson Ethan Smith Ed Younis Costin Iancu David I. Santiago Irfan Siddiqi Quantum Nanoelectronics Laboratory Dept. of Physics University of California at Berkeley Berkeley California 94720 USA Computational Research Division Lawrence Berkeley National Lab Berkeley California 94720 USA Materials Sciences Division Lawrence Berkeley National Lab Berkeley California 94720 USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Inst. for Quantum Computing and Dept. of Applied Mathematics University of Waterloo Waterloo Ontario Canada N2L 3G1 Quantum Benchmark Inc. Kitchener Ontario Canada N2H 5G5

Recent progress in noisy intermediate-scale quantum (NISQ) hardware shows that quantum devices may be able to tackle complex problems even without error correction. However, coherent errors due to the increased complexity of these devices is an outstanding issue. They can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like quantum imaginary time evolution are susceptible to these errors. This article presents the combination of both noise tailoring using randomized compiling and error mitigation with purification. We also show that cycle benchmarking gives an estimate of the reliability of the purification. We apply this method to the quantum imaginary time evolution of a transverse field Ising model and report an energy estimation error and a ground-state infidelity both below 1%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices.

关键词： Measurement-based quantum computing Quantum algorithms Quantum benchmarking Quantum computation Quantum control Quantum information processing Quantum simulation