检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Islam, Tousif Khanna, Gaurav Field, Scott E. Kavli Institute for Theoretical Physics University of California Santa Barbara Kohn Hall Lagoon Rd Santa BarbaraCA93106 United States Theoretical AstroPhysics Including Relativity and Cosmology California Institute of Technology PasadenaCA United States Department of Physics Center for Computational Research University of Rhode Island KingstonRI02881 United States Department of Physics University of Massachusetts DartmouthMA02747 United States Center for Scientific Computing and Data Science Research University of Massachusetts DartmouthMA02747 United States Department of Mathematics University of Massachusetts DartmouthMA02747 United States

gwNRHME is a recently developed framework that seamlessly converts a multi-modal (i.e with several spherical harmonic modes) quasi-circular waveform into multi-modal eccentric waveform if the quadrupolar eccentric waveform is known. Here, we employ the gwNRHME framework to combine a multi-modal quasi-circular waveform model NRHybSur3dq8 and quadrupolar non-spinning eccentric waveform model EccentricIMR to construct multi-modal non-spinning eccentric model NRHybSur3dq8-gwNRHME. Using a total of 35 eccentric numerical relativity (NR) simulations obtained from the SXS and RIT catalogs, we demonstrate that NRHybSur3dq8-gwNRHME model predictions agree well with NR (with typical relative L2 errors of ∼ 0.01 for the dominant quadrupolar mode) for mass ratios 1 ≤ q ≤ 4 and eccentricities up to ∼ 0.2 measured about 10 cycles before the merger. To demonstrate the modularity of the gwNRHME framework, we further combine EccentricIMR with BHPTNRSur1dq1e4 model and develop a non-spinning eccentric models named BHPTNRSur1dq1e4-gwNRHME. Finally, we develop a different variant of these models by replacing EccentricIMR with EccentricTD. Both the gwNRHME framework and associated models are available through the gwModels package. Copyright © 2024, The Authors. All rights reserved.

关键词： Spheres

来源：评论

学校读者我要写书评

暂无评论

Quantum Rényi Entropy Functionals for Bosonic Gaussian Systems

arXiv

引用

arXiv 2022年

作者： Lee, Junseo Jeong, Kabgyun School of Electrical and Electronic Engineering Yonsei University Seoul03722 Korea Republic of Quantum Computing R&D Norma Inc. Seoul04799 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

In this study, the quantum Rényi entropy power inequality of order p > 1 and power κ is introduced as a quantum analog of the classical Rényi-p entropy power inequality. To derive this inequality, we first exploit the Wehrl-p entropy power inequality on bosonic Gaussian systems via the mixing operation of quantum convolution, which is a generalized beam-splitter operation. This observation directly provides a quantum Rényi-p entropy power inequality over a quasi-probability distribution for D-mode bosonic Gaussian regimes. The proposed inequality is expected to be useful for the nontrivial computing of quantum channel capacities, particularly universal upper bounds on bosonic Gaussian quantum channels, and a Gaussian entanglement witness in the case of Gaussian amplifier via squeezing operations. © 2022, CC BY.

关键词： Quantum entanglement

来源：评论

学校读者我要写书评

暂无评论

Rubric-based holistic review represents a change from traditional graduate admissions approaches in physics

引用

Physical Review Physics Education Research 2023年第1期19卷 010134-010134页

作者： Nicholas T. Young N. Verboncoeur Dao Chi Lam Marcos D. Caballero Department of Physics and Astronomy Michigan State University East Lansing Michigan 48824 USA Department of Computational Mathematics Science and Engineering Michigan State University East Lansing Michigan 48824 USA Department of Statistics Michigan State University East Lansing Michigan 48824 USA Center for Computing in Science Education and Department of Physics University of Oslo N-0316 Oslo Norway CREATE for STEM Institute Michigan State University East Lansing Michigan 48824 USA

Rubric-based admissions are claimed to help make the graduate admissions process more equitable, possibly helping to address the historical and ongoing inequities in the U.S. physics graduate school admissions process that have often excluded applicants from minoritized races, ethnicities, genders, and backgrounds. Yet, no studies have examined whether rubric-based admissions methods represent a fundamental change in the admissions process or simply represent a new tool that achieves the same outcome. To address that, we developed supervised machine learning models of graduate admissions data collected from our department over a seven-year period. During the first four years, our department used a traditional admission process and switched to a rubric-based process for the following three years, allowing us to compare which parts of the applications were driving admissions decisions. We find that faculty focused on applicants’ physics GRE scores and grade-point averages when making admissions decisions before the implementation of the rubric. While we were able to develop a sufficiently good model whose results we could trust for the data before the implementation of the rubric, we were unable to do so for the data collected after the implementation of the rubric, despite multiple modifications to the algorithms and data such as implementing Tomek Links. Our inability to model the second dataset despite being able to model the first combined with model comparison analyses suggests that rubric-based admission does change the underlying process. These results suggest that rubric-based holistic review is a method that could make the graduate admission process in physics more equitable.

关键词： Diversity & inclusion Educational policy Graduate students

来源：评论

学校读者我要写书评

暂无评论

DMNER: Biomedical Named Entity Recognition by Detection and Matching

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

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

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 1 .

关键词： Training Dictionaries Codes Semantics Named entity recognition Complexity theory Labeling Data mining Bioinformatics

来源：评论

学校读者我要写书评

暂无评论

High order semi-implicit weighted compact nonlinear scheme for the all-Mach isentropic Euler system

引用

Advances in Aerodynamics 2020年第1期2卷 555-578页

作者： Yanqun Jiang Xun Chen Xu Zhang Tao Xiong Shuguang Zhou Department of Mathematics Southwest University of Science and Technology621010 MianyangChina School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific ComputingXiamen University361005 XiamenChina Computational Aerodynamics Institute China Aerodynamics Research and Development Center621000 MianyangChina

The computation of compressible flows at all Mach numbers is a very challenging *** efficient numerical method for solving this problem needs to have shock-capturing capability in the high Mach number regime,while it can deal with stiffness and accuracy in the low Mach number *** paper designs a high order semi-implicit weighted compact nonlinear scheme(WCNS)for the all-Mach isentropic Euler system of compressible gas *** avoid severe Courant-Friedrichs-Levy(CFL)restrictions for low Mach flows,the nonlinear fluxes in the Euler equations are split into stiff and non-stiff components.A third-order implicit-explicit(IMEX)method is used for the time discretization of the split components and a fifth-order WCNS is used for the spatial discretization of flux *** high order IMEX method is asymptotic preserving and asymptotically accurate in the zero Mach number ***-and two-dimensional numerical examples in both compressible and incompressible regimes are given to demonstrate the advantages of the designed IMEX WCNS.

关键词： High order scheme IMEX time discretization WCNS Asymptotic-preserving property Low Mach number Isentropic Euler equations

来源：评论

学校读者我要写书评

暂无评论

GW190521: Tracing imprints of spin-precession on the most massive black hole binary

arXiv

引用

arXiv 2023年

作者： Miller, Simona J. Isi, Maximiliano Chatziioannou, Katerina Varma, Vijay Mandel, Ilya Department of Physics California Institute of Technology PasadenaCA91125 United States LIGO Laboratory California Institute of Technology PasadenaCA91125 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Department of Mathematics Center for Scientific Computing and Data Science Research University of Massachusetts DartmouthMA02747 United States Max Planck Institute for Gravitational Physics Albert Einstein Institute PotsdamD-14476 Germany School of Physics Astronomy Monash University ClaytonVIC3800 Australia OzGrav: The ARC Centre of Excellence for Gravitational Wave Discovery ClaytonVIC3800 Australia

GW190521 is a remarkable gravitational-wave signal on multiple fronts: its source is the most massive black hole binary identified to date and could have spins misaligned with its orbit, leading to spin-induced precession;an astrophysically consequential property linked to the binary's origin. However, due to its large mass, GW190521 was only observed during its final 3-4 cycles, making precession constraints puzzling and giving rise to alternative interpretations, such as eccentricity. Motivated by these complications, we trace the observational imprints of precession on GW190521 by dissecting the data with a novel time domain technique, allowing us to explore the morphology and interplay of the few observed cycles. We find that precession inference hinges on a quiet portion of the pre-merger data that is suppressed relative to the merger-ringdown. Neither pre-merger nor post-merger data alone are the sole driver of inference, but rather their combination;in the quasi-circular scenario, precession emerges as a mechanism to accommodate the lack of a stronger pre-merger signal in light of the observed post-merger. In terms of source dynamics, the pre-merger suppression arises from a tilting of the binary with respect to the observer. Establishing such a consistent picture between the source dynamics and the observed data is crucial for characterizing the growing number of massive binary observations and bolstering the robustness of ensuing astrophysical claims. © 2023, CC BY.

关键词： Stars

来源：评论

学校读者我要写书评

暂无评论

Automation Intervention for Monitoring Agriculture Farming Scale: A Review

Automation Intervention for Monitoring Agriculture Farming S...

引用

International Conference on computing and Networking Technology (ICCNT)

作者： Kapil Joshi Santosh Kumar Shruti Bhatla Vishal Kaushik Harishchander Anandaram Anil Kumar Department of CSE Uttaranchal Institute of Technology Uttaranchal University Dehradun India Department of Mathematics Sharda School of Basic Sciences and Research Sharda University Greater Noida UP India Department of Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India School of Computer Science UPES Dehradun India Centre for Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu India School of Computing DIT University Dehradun India

Agricultural data is only valuable when it has been managed successfully. As data has evolved into the fundamental ingredient in contemporary agriculture to assist farmers with vital decision, latest developments in managing data are causing Smart Agriculture to rise dramatically. With factual information obtained by sensors, significant advantages emerge with the goal of enhancing production and ecology. This type of data-driven farm management is built on information that can boost efficiency by preventing resource waste and contamination of the ecosystem. Data-driven farming, with the assistance of automated solutions using artificial intelligence techniques, lays the groundwork for potential sustainable *** article analyses the current state of sophisticated agricultural systems by rehashing each critical step, from data processing in field crops to variable interest rate implementations, so that farmers can make optimised decision making to save funds while safeguarding the natural environment and converting how meal would be generated to meet the upcoming population explosion.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Incorporating AI and IoT for Smart Poultry Monitoring and Health Detection

Incorporating AI and IoT for Smart Poultry Monitoring and He...

引用

Augmented Intelligence and Sustainable Systems (ICAISS), International Conference on

作者： Kapil Joshi Arun Kumar Harishchander Anandaram Anil Kumar Ambika Aggarwal Gunjan Chhabra Department of CSE Uttaranchal Institute of Technology Uttaranchal University Dehradun India Department of Mathematics Sharda School of Basic Sciences and Research Sharda University Greater Noida India Centre for Computational Engineering and Networking Amrita School of Artificial Intelligence Coimbatore India School of Computing DIT University Dehradun India Department of CSE UPES Dehradun India Department of CSE Graphic Era Hill University Dehradun India

One vital sector of animal husbandry, poultry farming, is moving towards scale, intelligence, and automated operations. The emergence of digital technology has significantly improved a number of fields. An extensive analysis of the literature is presented in this paper, with a focus on AI-enabled IoT applications for managing poultry health and well-being. This study primarily centred on chicken welfare, considering modern poultry husbandry is challenged with problems pertaining to standardised criteria for welfare evaluation and reliable monitoring methods, notably for broiler wellness and disease outbreak prevention. There is a compelling rationale for using contemporary technology to continually monitor big farms with millions of birds and increase overall production. This is because there are now increasingly affordable processing resources, IoT sensors, and standard algorithms available. The most important sources of protein in the diet are eggs and poultry, thus poultry farm oversight should prioritize the use of cutting-edge technology solutions. As a result, this study presents a systematic review of the most cutting-edge IoT systems with AI capabilities as well as their most recent developments in the creation of smart systems in this field. The study also explores the benefits and problems that AI and IoT present for chicken farming.

关键词：

来源：评论

学校读者我要写书评

暂无评论

LOWEST-DEGREE POLYNOMIAL DE RHAM COMPLEX ON GENERAL QUADRILATERAL GRIDS

arXiv

引用

arXiv 2020年

作者： Qimengquan Ji, Xia Zhang, Shuo University of Chinese Academy of Sciences Beijing100190 China LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing100190 China

This paper devotes to the construction of finite elements on grids that consist of general quadrilaterals not limited in parallelograms. Two finite elements are established for the H1 and H(rot) elliptic problems, respectively. The two finite element spaces on general quadrilateral grids, together with the space of piecewise constant functions, formulate a discretised de Rham complex. First order convergence rate can be proved for both of them under the asymptotic-parallelogram assumption on the grids. The local shape functions of the two spaces are piecewise polynomials, and the global finite element functions are nonconforming. A rigorous analysis is given in this paper that it is impossible to construct a practically useful finite element defined as Ciarlet’s triple whose shape functions are always piecewise polynomials and which can form conforming subspaces on a grid that consists of arbitrary quadrilaterals. Copyright © 2020, The Authors. All rights reserved.

关键词： Polynomials

来源：评论

学校读者我要写书评

暂无评论

Gravitational wave surrogate model for spinning, intermediate mass ratio binaries based on perturbation theory and numerical relativity

arXiv

引用

arXiv 2024年

作者： Rink, Katie Bachhar, Ritesh Islam, Tousif Rifat, Nur E.M. González-Quesada, Kevin Field, Scott E. Khanna, Gaurav Hughes, Scott A. Varma, Vijay Department of Physics Center for Scientific Computing & Visualization Research University of Massachusetts DartmouthMA02747 United States Department of Physics Center for Gravitational Physics University of Texas AustinTX78712 United States Department of Physics Center for Computational Research University of Rhode Island East Hall KingstonRI02881 United States Kavli Institute for Theoretical Physics University of California Santa Barbara Kohn Hall Lagoon Rd Santa BarbaraCA93106 United States Kavli Institute for Theoretical Physics University of California Santa BarbaraCA93106 United States Department of Physics University of Virginia 1827 University Avenue CharlottesvilleVA22903 United States Case Western Reserve University ClevelandOH44106 United States Department of Mathematics Center for Scientific Computing & Visualization Research University of Massachusetts DartmouthMA02747 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States

We present BHPTNRSur2dq1e3, a reduced order surrogate model of gravitational waves emitted from binary black hole (BBH) systems in the comparable to large mass ratio regime with aligned spin (χ1) on the heavier mass (m1). We trained this model on waveform data generated from point particle black hole perturbation theory (ppBHPT) with mass ratios varying from 3 ≤ q ≤ 1000 and spins from −0.8 ≤ χ1 ≤ 0.8. The waveforms are 13,500 m1 long and include all ≤ 4 spin-weighted spherical harmonic modes except the (4, 1) and m = 0 modes. We find that for binaries with χ1 −0.5, retrograde quasi-normal modes are significantly excited, thereby complicating the modeling process. To overcome this issue, we introduce a domain decomposition approach to model the inspiral and merger-ringdown portion of the signal separately. The resulting model can faithfully reproduce ppBHPT waveforms with a median time-domain mismatch error of 8 × 10−5. We then calibrate our model with numerical relativity (NR) data in the comparable mass regime (3 ≤ q ≤ 10). By comparing with spin-aligned BBH NR simulations at q = 15, we find that the dominant quadrupolar (subdominant) modes agree to better than ≈ 10−3 (≈ 10−2) when using a time-domain mismatch error, where the largest source of calibration error comes from the transition-to-plunge and ringdown approximations of perturbation theory. Mismatch errors are below ≈ 10−2 for systems with mass ratios between 6 ≤ q ≤ 15 and typically get smaller at larger mass ratio. Our two models – both the ppBHPT waveform model and the NR-calibrated ppBHPT model – will be publicly available through gwsurrogate and the Black Hole Perturbation Toolkit packages. © 2024, CC BY.

关键词： Perturbation techniques

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：