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arXiv 2023年

作者： Yuan, Ya-Xiang Zhang, Yi Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

Mirror descent plays a crucial role in constrained optimization and acceleration schemes, along with its corresponding low-resolution ordinary differential equations (ODEs) framework have been proposed. However, the low-resolution ODEs are unable to distinguish between Polyak's heavy-ball method and Nesterov's accelerated gradient method. This problem also arises with accelerated mirror descent. To address this issue, we derive high-resolution ODEs for accelerated mirror descent and propose a general Lyapunov function framework to analyze its convergence rate in both continuous and discrete time. Furthermore, we demonstrate that accelerated mirror descent can minimize the squared gradient norm at an inverse cubic rate. © 2023, CC BY.

关键词： Lyapunov functions

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DMNER: Biomedical Named Entity Recognition by Detection and Matching

DMNER: Biomedical Named Entity Recognition by Detection and ...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Bian, Junyi Jiang, Rongze Zhai, Weiqi Huang, Tianyang Huang, Xiaodi Zhou, Hong Zhu, Shanfeng Fudan University School of Computer Science Shanghai China Fudan University Institute of Science and Technology for Brain-Inspired Intelligence Shanghai China Charles Sturt University School of Computing Mathematics and Engineering Nsw Australia Atypon Systems Llc United Kingdom Zhangjiang Fudan International Innovation Center Fudan University Institute of Science and Technology for Brain-Inspired Intelligence Moe Frontiers Center for Brain Science Shanghai Key Lab of Intelligent Information Processing Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Shanghai China

ISBN: (纸本)9798350386226

Biomedical Named Entity Recognition (NER) is a crucial task in extracting information from biomedical texts. However, the diversity of professional terminology, semantic complexity, and the widespread presence of synonyms pose significant challenges. Traditional methods that rely on sequence labeling training datasets often struggle to handle these complexities. To address this, we introduce a novel framework for BioNER, termed DMNER, which leverages external knowledge and operates in two steps: entity boundary detection and entity category identification through matching. The core of DMNER is its second step, which determines the entity category by retrieving similar entities and their categories from a knowledge dictionary using semantic similarity matching. Our experiments on 10 biomedical datasets demonstrate that DMNER outperforms baselines across these tasks, proving its effectiveness and adaptability. DMNER is versatile and can be applied to various NER tasks, including supervised NER, distantly supervised NER, and NER on multiple datasets with disjoint label sets. The DMNER code is publicly available. © 2024 IEEE.

关键词： Semantics

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A higher order coupled frequency characteristics study of smart magneto-electro-elastic composite plates with cut-outs using finite element methods

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Defence Technology（防务技术） 2021年第1期17卷 100-118页

作者： M.Vinyas D.Harursampath T.Nguyen Thoi Nonlinear Multifunctional Composites Analysis and Design(NMCAD)Laboratory Department of Aerospace EngineeringIndian Institute of ScienceBangalore560012India Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityViet Nam

This article deals with investigating the effect of cut-outs on the natural frequencies of magneto-electroelastic(MEE)plates incorporating finite element methods based on higher order shear deformation theory(HSDT).In order to consider the influence of cut-out,the energy of the cut-out domain is subtracted from the total energy of the entire *** governing equations of motions are derived through incorporating Hamilton’s principle and the solution is obtained using condensation *** proposed numerical formulation is verified with the results of previously published literature as well as the numerical *** addition,this research focuses on evaluating the effect of geometrical skewness and boundary conditions on the frequency *** influence of cut-outs on the degree of coupling between magnetic,electric and elastic fields is also investigated.

关键词： Cut-out Magneto-electro-elastic Natural frequency Higher order shear deformation Coupling

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Empowering magnetic strong coupling and its application for nonlinear refractive index sensing

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Nano Research 2022年第8期15卷 7604-7613页

作者： Song Sun Dong Li Dacheng Wang Zheng Feng Wei Tan Lin Wu Microsystem and Terahertz Research Center China Academy of Engineering PhysicsChengdu 610200China Institute of Electronic Engineering China Academy of Engineering PhysicsMianyang 621999China Science Mathematics and Technology(SMT)Singapore University of Technology and Design(SUTD)8 Somapah RoadSingapore 487372Singapore Institute of High Performance Computing A*STAR(Agency for ScienceTechnology and Research)1 Fusionopolis Way#16-16 ConnexisSingapore 138632Singapore

In the context of quantum strong coupling,the magnetic dipole(MD)emitters are largely overlooked due to the rarity of MD source and the non-magnetic nature of matters at high *** on a semi-classic model,we theoretically demonstrate magnetic strong coupling between an MD cluster(Er^(3+):4 I13/2→4 I15/2 transition at 1,550 nm)and an antenna-in-cavity *** is found that placing the plasmonic diabolo/s-diabolo nanoantenna,which supports strong electric/magnetic dipole mode,inside a dielectric cavity could largely improve the strong coupling coefficient while suppressing the cavity loss rate compared to the bare nanoantenna counterparts,empowering the magnetic quantum strong coupling at a level of 104 emitters,which is remarkable considering the weak MD dipole momentum and small hotspot region at high ***,the two Rabi resonance branches undergo highly asymmetrical changes upon a small variation on the environmental refractive index,which leads to an exotic exponential sensitivity profile by tracing the ratio between the two resonances *** proposed magnetic strong coupling for nonlinear refractive index sensing may add a new category to quantum plasmonic sensors.

关键词： nanoplasmonic cavity magnetic dipole emitter strong coupling Rabi-splitting sensing

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A Two-Layer Crank-Nicolson Linear Finite Element Methods for Second-Order Hyperbolic Optimal Control Problems

SSRN

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SSRN 2023年

作者： Li, Xiaowu Tang, Yuelong Institute of Computational Mathematics College of Science Hunan University of Science and Engineering Hunan Yongzhou425100 China

Abstract. In this paper, we consider a two-layer Crank-Nicolson scheme combined with linear finite element approximation for second-order hyperbolic optimal control problems with control constraints. For state and co-state variables, the time derivatives are first reduced to a first-order system then discretized by the two-layer Crank-Nicolson scheme and the space derivatives are discretizted by linear finite elements. The control variable is dealt with variational discretization technique. Optimal a priori error estimates for state, co-state and control variables are derived. Some numerical examples are presented to illustrate the theoretical convergence rates. © 2023, The Authors. All rights reserved.

关键词： Finite element method

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Preprocessed GMRES for fast solution of linear equations

arXiv

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arXiv 2024年

作者： Zhang, Juan Luo, Yiyi Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University China

The article mainly introduces preprocessing algorithms for solving linear equation systems. This algorithm uses three algorithms as inner iterations, namely RPCG algorithm, ADI algorithm, and Kaczmarz algorithm. Then, it uses BA-GMRES as an outer iteration to solve the linear equation system. These three algorithms can indirectly generate preprocessing matrices, which are used for solving equation systems. In addition, we provide corresponding convergence analysis and numerical examples. Through numerical examples, we demonstrate the effectiveness and feasibility of these preprocessing methods. Furthermore, in the Kaczmarz algorithm, we introduce both constant step size and adaptive step size, and extend the parameter range of the Kaczmarz algorithm to α ∈ (0, ∞). We also study the solution rate of linear equation systems using different step sizes. Numerical examples show that both constant step size and adaptive step size have higher solution efficiency than the solving algorithm without preprocessing. © 2024, CC BY.

关键词： Linear equations

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Symplectic Discretization Approach for Developing New Proximal Point Algorithm

arXiv

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arXiv 2023年

The rapid advancements in high-dimensional statistics and machine learning have increased the use of first-order methods. Many of these methods can be regarded as instances of the proximal point algorithm. Given the importance of the proximal point algorithm, there has been growing interest in developing its accelerated variants. However, some existing accelerated proximal point algorithms exhibit oscillatory behavior, which can impede their numerical convergence rate. In this paper, we first introduce an ODE system and demonstrate its o(1/t2) convergence rate and weak convergence property. Next, we apply the Symplectic Euler Method to discretize the ODE and obtain a new accelerated proximal point algorithm, which we call the Symplectic Proximal Point Algorithm. The reason for using the Symplectic Euler Method is its ability to preserve the geometric structure of the ODEs. Theoretically, we demonstrate that the Symplectic Proximal Point Algorithm achieves an o(1/k2) convergence rate and that the sequences generated by our method converge weakly to the solution set. Practically, our numerical experiments illustrate that the Symplectic Proximal Point Algorithm significantly reduces oscillatory behavior, leading to improved long-time behavior and faster numerical convergence *** Codes 47J20, 47H05, 65K15, 65Y20, 90C25, 90C52 © 2023, CC BY.

关键词： Lyapunov functions

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Energy Efficient Mathematical Model for Cyber-Physical Systems: A Model for Industrial Internet of Things

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SN Computer science 2023年第5期4卷 1-7页

作者： Veerachamy, Ramachandran Rao, Ganga Rama Koteswara Arivanantham, Vishnu Priya Kuppusamy, Sangeetha Velayutham, Priya Govindaraj, Rajeshkumar Department of Computer Science and Engineering GITAM School of Computing GITAM Deemed to be University Bengaluru 561203 India Department of Computer Science and Information Technology Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram 520002 India Department of Computational Intelligence School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore 632014 India Department of Computer Science and Engineering Kongu Engineering College Tamil Nadu Perundurai 638060 India Department of Computer Science and Engineering Paavai Engineering College Tamil Nadu Namakkal 637018 India Department of Information Science and Engineering Bannari Amman Institute of Technology Tamil Nadu Sathyamagalam 638401 India

Proliferated usage of computer devices, smart objects, and electronics significantly impacts the atmosphere, which is inevitable. The existing context has engineered schemes, or Cyber-Physical Systems (CPS), that integrate physical and computation components. The extensive usage of devices has utilized more energy, creating complexity in environmental handling. The problem is improving an automotive function’s reliability, application, or functionality with time and energy constraints. By applying smart technologies, namely Deep Learning (DL) and Machine Learning (ML) in CPS and the Internet of Things (IoT), enduring the utilization of these intensive DL-based approaches has a negative effect on resource utilization. The proposed Energy Efficient Mathematical Model (EEMM) is designed with a mathematical model for IIoT, which guides in solving the drawback of the existing system. The mathematical model integrated CPS-based proposed EEMM has outperformed the existing state-of-art technique. The proposed EEMM attains minimal Energy Consumption (EC) of 521 Jules and the highest reliability rate of 0.987. The proposed EEMM in this research has attained minimal energy usage of 0.987 i for 100 tasks, which is minimal than other existing techniques. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Cyber-attacks Energy IIoT IoT Mathematical model Network Smart objects

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Estimating Soil Organic Carbon from Multispectral Images Using Physics-Informed Neural Networks 17th

Estimating Soil Organic Carbon from Multispectral Images Us...

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17th Asian Conference on Computer Vision, ACCV 2024

作者： Sargeant, James Wei Teng, Shyh Murshed, Manzur Paul, Manoranjan Brennan, David Institute of Innovation Science and Sustainability Federation University Ballarat Australia School of Information Technology Deakin University Burwood Australia School of Computing Mathematics and Engineering Charles Sturt University BathurstNSW2795 Australia Wimmera Catchment Management Authority Horsham Australia

ISBN: (纸本)9789819609628

Understanding the amount of Soil Organic Carbon (SOC) at farm and field scale is a necessary precursor to effective management, important for both agricultural productivity and to reduce CO2 emissions. To avoid the prohibitive cost of measurement, SOC can be estimated by using multispectral images. In this study, we propose a novel Physics-Informed Convolutional Neural Network (CNN) to model well-known but noisy relationship between a soil index and SOC using the network’s loss function. This study is also conducted by resampling the European Land Use/Classification Area Survey (LUCAS) dataset to Sentinel-2 bands. Our experimental results show that our proposed network converges more quickly, has a lower root mean squared error (RMSE) and is more robust (as measured by the standard deviation of RMSE over multiple trials) than a compatible standard CNN. The operation of the novel Physics-Informed CNN is explained in terms of the components of the loss function. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Carbon sequestration

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A preconditioned iteration method for solving saddle point problems

arXiv

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arXiv 2024年

This paper introduces a preconditioned method designed to comprehensively address the saddle point system with the aim of improving convergence efficiency. In the preprocessor construction phase, a technical approach for solving the approximate inverse matrix of sparse matrices is presented. The effectiveness of the proposed method is demonstrated through numerical examples, emphasizing its efficacy in approximating the inverse matrix. Furthermore, the preprocessing technology includes a low-rank processing step, effectively reducing algorithmic complexity. Numerical experiments validate the effectiveness and feasibility of PSLR-GMRES in solving the saddle point system. © 2024, CC BY.

关键词： Iterative methods

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