检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Morales, Mauro E.S. Pira, Lirandë Schleich, Philipp Koor, Kelvin Costa, Pedro C.S. An, Dong Aspuru-Guzik, Alán Lin, Lin Rebentrost, Patrick Berry, Dominic W. Joint Center for Quantum Information and Computer Science University of Maryland United States Centre for Quantum Software and Information University of Technology Sydney Australia Centre for Quantum Technologies National University of Singapore Singapore Department of Computer Science University of Toronto Canada Vector Institute for Artificial Intelligence Toronto Canada ContinoQuantum Sydney Australia Beijing International Center for Mathematical Research Peking University Beijing China Department of Chemistry University of Toronto Canada Canadian Institute for Advanced Research Toronto Canada Acceleration Consortium Toronto Canada Department of Chemical Engineering & Applied Chemistry University of Toronto Toronto Canada Department of Materials Science & Engineering University of Toronto Toronto Canada Lebovic Fellow Canadian Institute for Advanced Research Toronto Canada Department of Mathematics University of California Berkeley United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory Berkeley United States Department of Computer Science National University of Singapore Singapore School of Mathematical and Physical Sciences Macquarie University Sydney Australia

Solving linear systems of equations plays a fundamental role in numerous computational problems from different fields of science. The widespread use of numerical methods to solve these systems motivates investigating the feasibility of solving linear systems problems using quantum computers. In this work, we provide a survey of the main advances in quantum linear systems algorithms, together with some applications. We summarize and analyze the main ideas behind some of the algorithms for the quantum linear systems problem in the literature. The analysis begins by examining the Harrow-Hassidim-Lloyd (HHL) solver. We note its limitations and reliance on computationally expensive quantum methods, then highlight subsequent research efforts which aimed to address these limitations and optimize runtime efficiency and precision via various paradigms. We focus in particular on the post-HHL enhancements which have paved the way towards optimal lower bounds with respect to error tolerance and condition number. By doing so, we propose a taxonomy that categorizes these studies. Furthermore, by contextualizing these developments within the broader landscape of quantum computing, we explore the foundational work that have inspired and informed their development, as well as subsequent refinements. Finally, we discuss the potential applications of these algorithms in differential equations, quantum machine learning, and many-body physics. © 2024, CC BY.

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

A Brief Review of Explainable Artificial Intelligence in Healthcare

SSRN

引用

SSRN 2023年

作者： Sadeghi, Zahra Alizadehsani, Roohallah Cifci, Mehmet Akif Kausar, Samina Rehman, Rizwan Mahanta, Priyakshi Bora, Pranjal Kumar Almasri, Ammar Alkhawaldeh, Rami S. Hussain, Sadiq Alatas, Bilal Shoeibi, Afshin Moosaei, Hossein Hladík, Milan Nahavandi, Saeid Pardalo, Panos M. Institute for Big Data Analytics Faculty of Computer Science Dalhousie University Canada Deakin University Geelong Australia The Institute of Computer Technology Tu Wien University Vienna1040 Austria University of Kotli Azad Jammu and Kashmir Azad Kashmir Kotli Pakistan Centre for Computer Science and Applications Dibrugarh University Assam India Department of Management Information Sys Al-Balqa Applied University Salt19117 Jordan Department of Computer Information Systems The University of Jordan Aqaba77110 Jordan Examination Branch Dibrugarh University Assam Dibrugarh India Department of Software Eng. Firat University Elazig23100 Turkey Data Science and Computational Intelligence Institute University of Granada Spain Department of Informatics Faculty of Science Jan Evangelista Purkyně University in Ústí nad Labem Czech Republic Department of Applied Mathematics School of Computer Science Faculty of Mathematics and Physics Charles University Prague Czech Republic Harvard Paulson School of Engineering and Applied Sciences Harvard University AllstonMA02134 United States Swinburne University of Technology HawthornVIC3122 Australia Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville32611 United States

XAI refers to the techniques and methods for building AI applications which assist end users to interpret output and predictions of AI models. Black box AI applications in high-stakes decision-making situations, such as medical domain have increased the demand for transparency and explainability since wrong predictions may have severe consequences. Model explainability and interpretability are vital successful deployment of AI models in healthcare practices. AI applications' underlying reasoning needs to be transparent to clinicians in order to gain their trust. This paper presents a systematic review of XAI aspects and challenges in the healthcare domain. The primary goals of this study are to review various XAI methods, their challenges, and related machine learning models in healthcare. The methods are discussed under six categories: Features-oriented methods, global methods, concept models, surrogate models, local pixel-based methods, and human-centric methods. Most importantly, the paper explores XAI role in healthcare problems to clarify its necessity in safety-critical applications. The paper intends to establish a comprehensive understanding of XAI-related applications in the healthcare field by reviewing the related experimental results. To facilitate future research for filling research gaps, the importance of XAI models from different viewpoints and their limitations are investigated. © 2023, The Authors. All rights reserved.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Correction: Unbiased and multilevel methods for a class of diffusions partially observed via marked point processes

引用

Statistics and Computing 2024年第6期34卷 1-1页

作者： Alvarez, Miguel Jasra, Ajay Ruzayqat, Hamza Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia School of Data Science The Chinese University of Hong Kong Shenzhen China

来源：评论

学校读者我要写书评

暂无评论

Two Algorithms for Designing Control over Centerof-Mass Motion of a Moving Object with Incomplete Description 2

Two Algorithms for Designing Control over Centerof-Mass Moti...

引用

2nd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2020

作者： Kolesnikova, S.I. Paraev, Yu. I. Tsvetnitskaya, S.A. St.Petersburg State University of Aerospae Instrumentation Institute of Computational Systems and Programming St. Petersburg Russia National Research Tomsk State University Institute of Applied Mathematics and Computer Science Tomsk Russia

ISBN: (纸本)9781728188409

The methods of nonlinear adaptation based on an analytical design of aggregated regulators and modal control are discussed for solving the problem of nonlinear control over a robotic arm operating under the conditions of nonrandom noise. A comparative analysis of control is performed under different types of noise variables. It is shown that both control systems are adaptive and robust, while their transient process quality characteristics differ. The results of numerical modeling support the method of nonlinear adaptation as far as the value of overshoot is concerned in the case of nonrandom noise and evidence in favor of the method of modal control identifying the noise for off-design conditions (random high level noise). © 2020 IEEE.

关键词： Quality control

来源：评论

学校读者我要写书评

暂无评论

Fuzzy-Rough Nearest Neighbour Approaches for Emotion Detection in Tweets

arXiv

引用

arXiv 2021年

作者： Kaminska, Olha Cornelis, Chris Hoste, Veronique Computational Web Intelligence Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium LT3 Language and Translation Technology Team Ghent University Ghent Belgium

Social media are an essential source of meaningful data that can be used in different tasks such as sentiment analysis and emotion recognition. Mostly, these tasks are solved with deep learning methods. Due to the fuzzy nature of textual data, we consider using classification methods based on fuzzy rough sets. Specifically, we develop an approach for the SemEval-2018 emotion detection task, based on the fuzzy rough nearest neighbour (FRNN) classifier enhanced with ordered weighted average (OWA) operators. We use tuned ensembles of FRNN–OWA models based on different text embedding methods. Our results are competitive with the best SemEval solutions based on more complicated deep learning methods. Copyright © 2021, The Authors. All rights reserved.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection

arXiv

引用

arXiv 2023年

作者： Ćiprijanović, A. Lewis, A. Pedro, K. Madireddy, S. Nord, B. Perdue, G.N. Wild, S.M. Fermi National Accelerator Laboratory BataviaIL60510 United States Department of Astronomy and Astrophysics University of Chicago ChicagoIL60637 United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL60439 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Laboratory for Nuclear Science MIT CambridgeMA02139 United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

Artificial intelligence methods show great promise in increasing the quality and speed of work with large astronomical datasets, but the high complexity of these methods leads to the extraction of dataset-specific, non-robust features. Therefore, such methods do not generalize well across multiple datasets. We present a universal domain adaptation method, DeepAstroUDA, as an approach to overcome this challenge. This algorithm performs semi-supervised domain adaptation and can be applied to datasets with different data distributions and class overlaps. Non-overlapping classes can be present in any of the two datasets (the labeled source domain, or the unlabeled target domain), and the method can even be used in the presence of unknown classes. We apply our method to three examples of galaxy morphology classification tasks of different complexities (3-class and 10-class problems), with anomaly detection: 1) datasets created after different numbers of observing years from a single survey (LSST mock data of 1 and 10 years of observations);2) data from different surveys (SDSS and DECaLS);and 3) data from observing fields with different depths within one survey (wide field and Stripe 82 deep field of SDSS). For the first time, we demonstrate the successful use of domain adaptation between very discrepant observational datasets. DeepAstroUDA is capable of bridging the gap between two astronomical surveys, increasing classification accuracy in both domains (up to 40% on the unlabeled data), and making model performance consistent across datasets. Furthermore, our method also performs well as an anomaly detection algorithm and successfully clusters unknown class samples even in the unlabeled target dataset. © 2023, CC BY.

关键词： Galaxies

来源：评论

学校读者我要写书评

暂无评论

Alpha (α) assumed rotations and shear strains for spatially isotropic polygonal Reissner-Mindlin plate elements (αARS-Poly)

引用

computers and Structures 2023年 274卷

作者： Nguyen, Son H. Nam, Nguyen N. Hoang, Tien-Dat Nguyen, Tan N. Nguyen-Thoi, T. Division of Computational Mathematics and Engineering Institute for Computational Science Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Electrical and Electronic Engineering Phenikaa University Hanoi12116 Viet Nam Division of English Taught Mechanical Engineering Faculty of International Training Thai Nguyen University of Technology Thai Nguyen City Viet Nam Department of Architectural Engineering Sejong University 209 Neungdong-ro Gwangjin-gu Seoul05006 Korea Republic of Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Mechanical - Electrical and Computer Engineering School of Engineering and Technology Van Lang University Ho Chi Minh City Viet Nam

This paper proposes simple and efficient alpha assumed rotations and shear strains for polygonal plate elements, named αARS-Poly. In the αARS approach, an alternative assumption of the tangent rotations along element boundaries is applied by using the approximation of the rotations in Timoshenko's beam theory. Then, the quadratic term of this assumed field is linearly scaled up by adding an artificial positive scaling factor α>0. Through examination of the relative errors in the energy (s-) norm regarding α in numerical experiences, the value α=0.5 can be chosen as a general-fixed value that possibly achieves the optimal relative errors of the s-norm. The value α=0.5 seems to be not only mesh-independent but also problem-independent. The αARS-Poly element using α=0.5 passes all critical tests (spatially isotropic, zero-energy mode, and bending path tests) for a finite plate element which ensures the element orientation-independent property, solution stability, and free shear-locking in the thin plate limit. The implementation of the αARS-Poly element is straightforward through a unified form of the stiffness matrix for all arbitrary convex-shaped polygonal meshes. Numerical results show that the proposed element achieves high reliable and optimal results with uniform and excellent convergent rates in the static and free vibration analyses. © 2022 Elsevier Ltd

关键词： Finite element method

来源：评论

学校读者我要写书评

暂无评论

Disk2Planet: A Robust and Automated Machine Learning Tool for Parameter Inference in Disk-Planet Systems

arXiv

引用

arXiv 2024年

作者： Mao, Shunyuan Dong, Ruobing Yi, Kwang Moo Lu, Lu Wang, Sifan Perdikaris, Paris Department of Physics and Astronomy University of Victoria VictoriaBCV8P 5C2 Canada Kavli Institute for Astronomy and Astrophysics Peking University Beijing100871 China Department of Computer Science University of British Columbia VancouverBCV6T 1Z4 Canada Department of Statistics and Data Science Yale University New HavenCT06511 United States Graduate Group in Applied Mathematics and Computational Science University of Pennsylvania PhiladelphiaPA19104 United States Institute for Foundations of Data Science Yale University New HavenCT06520 United States Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania PhiladelphiaPA19104 United States

We introduce Disk2Planet, a machine learning-based tool to infer key parameters in disk-planet systems from observed protoplanetary disk structures. Disk2Planet takes as input the disk structures in the form of two-dimensional density and velocity maps, and outputs disk and planet properties, that is, the Shakura-Sunyaev viscosity, the disk aspect ratio, the planet-star mass ratio, and the planet's radius and azimuth. We integrate the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an evolutionary algorithm tailored for complex optimization problems, and the Protoplanetary Disk Operator Network (PPDONet), a neural network designed to predict solutions of disk-planet interactions. Our tool is fully automated and can retrieve parameters in one system in three minutes on an Nvidia A100 graphics processing unit. We empirically demonstrate that our tool achieves percent-level or higher accuracy, and is able to handle missing data and unknown levels of noise. Copyright © 2024, The Authors. All rights reserved.

关键词： Open source software

来源：评论

学校读者我要写书评

暂无评论

Dynamics of a two-group structured malaria transmission model

引用

Informatics in Medicine Unlocked 2022年 29卷

作者： Tchoumi, S.Y. Dongmo, E.Z. Kamgang, J.C. Tchuenche, J.M. Department of Mathematics and Computer Sciences ENSAI – University of N'Gaoundéré P.O. Box 455 N'Gaoundéré Cameroon Department of Mathematics and Computer Sciences Faculty of Sciences – University of N'Gaoundéré P.O. Box 454 N'Gaoundéré Cameroon School of Computer Science and Applied Mathematics University of the Witwatersrand Johannesburg South Africa School of Computational and Communication Sciences and Engineering Nelson Mandela African Institute of Science and Technology Arusha Tanzania

Malaria is an infectious vector-borne disease of global public concern, with high morbidity and mortality in children less than 5 years old. We propose a two-group malaria model structured by age with the SEIS dynamic in individuals aged below 5 years old, and SEIRS dynamic in individuals aged above 5 years. We compute the basic reproduction number and show that the DFE is locally asymptotically stable when R₀1, we prove the existence of a unique endemic equilibrium. On the other hand, if R₀≤1, under certain conditions, the system can have one endemic equilibrium or two endemic equilibria. Using partial rank correlation coefficients and Latin hypercube sampling, sensitivity analysis is carried out to determine the relative importance of model parameters to disease transmission. The average per capita biting rate of mosquitoes on susceptible humans under 5 years old b₂, recovery rate of infectious humans under 5 years old ω_e, recovery rate of infectious humans over 5 years old ω_a and the recruitment of mosquitoes Λ_v are the most impactful parameters. Graphically, it is shown that any intervention to reduce the contact between the mosquito and individuals under five has a greater positive impact on the level of endemicity in the total population compared to the case when the contact between mosquitoes and individuals over 5 years old is reduced. The public health implication of this result is that the fight against malaria should be stepped up in children under 5 years old to mitigate its spread. © 2022 The Authors

关键词： Age-structured Basic reproduction number Local stability Malaria Sensitivity analysis

来源：评论

学校读者我要写书评

暂无评论

Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA

引用

Health Data science 2021年第1期2021卷 78-87页

作者： Raj Dandekar Emma Wang George Barbastathis Chris Rackauckas Department of Computational Science and Engineering Massachusetts Institute of TechnologyCambridgeUSA MA 02139 Department of Electrical Engineering and Computer Sciences Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Singapore-MIT Alliance for Research and Technology(SMART)Centre Singapore 138602 Department of Applied Mathematics Massachusetts Institute of TechnologyCambridgeMA 02139USA

In the wake of the rapid surge in the COVID-19-infected cases seen in Southern and West-Central USA in the period of June-July 2020,there is an urgent need to develop robust,data-driven models to quantify the effect which early reopening had on the infected case count *** particular,it is imperative to address the question:How many infected cases could have been prevented,had the worst affected states not reopened early?To address this question,we have developed a novel COVID-19 model by augmenting the classical SIR epidemiological model with a neural network *** model decomposes the contribution of quarantine strength to the infection time series,allowing us to quantify the role of quarantine control and the associated reopening policies in the US states which showed a major surge in *** show that the upsurge in the infected cases seen in these states is strongly corelated with a drop in the quarantine/lockdown strength diagnosed by our ***,our results demonstrate that in the event of a stricter lockdown without early reopening,the number of active infected cases recorded on 14 July could have been reduced by more than 40%in all states considered,with the actual number of infections reduced being more than 100,000 for the states of Florida and *** we continue our fight against COVID-19,our proposed model can be used as a valuable asset to simulate the effect of several reopening strategies on the infected count evolution,for any region under consideration.

关键词： COV neural Central

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：