检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Mikuni, Vinicius Nachman, Benjamin National Energy Research Scientific Computing Center Berkeley Lab BerkeleyCA94720 United States Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States

Machine learning has become an essential tool in jet physics. Due to their complex, high-dimensional nature, jets can be explored holistically by neural networks in ways that are not possible manually. However, innovations in all areas of jet physics are proceeding in parallel. We show that specially constructed machine learning models trained for a specific jet classification task can improve the accuracy, precision, or speed of all other jet physics tasks. This is demonstrated by training on a particular multiclass generation and classification task and then using the learned representation for different generation and classification tasks, for datasets with a different (full) detector simulation, for jets from a different collision system (pp versus ep), for generative models, for likelihood ratio estimation, and for anomaly detection. We consider, our OmniLearn approach thus as a jet-physics foundation model. It is made publicly available for use in any area where state-of-the-art precision is required for analyses involving jets and their substructure. © 2025, CC BY.

关键词： Jets

来源：评论

学校读者我要写书评

暂无评论

A Landscape-Aware Differential Evolution for Multimodal Optimization Problems

引用

IEEE Transactions on Evolutionary Computation 2025年

作者： Lin, Guo-Yun Chen, Zong-Gan Liu, Chuanbin Jiang, Yuncheng Kwong, Sam Zhang, Jun Zhan, Zhi-Hui South China Normal University School of Computer Science Guangzhou510631 China Ministry of Education Center for Scientific Research and Development in Higher Education Institutes China Lingnan University Department of Computing and Decision Science Hong Kong Nankai University College of Artificial Intelligence Tianjin300350 China ERICA Hanyang University 15588 Korea Republic of

How to simultaneously locate multiple global peaks and achieve certain accuracy on the found peaks are two key challenges in solving multimodal optimization problems (MMOPs). In this article, a landscape-aware differential evolution (LADE) algorithm is proposed for MMOPs, which utilizes landscape knowledge to maintain sufficient diversity and provide efficient search guidance. In detail, the landscape knowledge is efficiently utilized in the following three aspects. First, a landscape-aware peak exploration helps each individual evolve adaptively to locate a peak and simulates the regions of the found peaks according to search history to avoid an individual re-locating an already found peak. Second, a landscape-aware peak distinction distinguishes whether an individual locates a new global peak, a new local peak, or an already found peak. Accuracy refinement can thus only be conducted on the global peaks to enhance the search efficiency. Third, a landscape-aware reinitialization specifies the initial position of an individual adaptively according to the distribution and distinction of the found peaks, which helps explore more peaks. The experiments are conducted on the widely-used benchmark MMOPs and multimodal nonlinear equation system problems. Experimental results show that LADE obtains generally better or competitive performance compared with seven well-performing recent algorithms and four winner algorithms in the IEEE CEC competitions for multimodal optimization. © 1997-2012 IEEE.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Agricultural consumer Internet of Things devices: Methods for optimizing data aggregation

引用

Alexandria Engineering Journal 2025年 125卷 692-699页

作者： Mengash, Hanan Abdullah Mahgoub, Hany Alshuhail, Asma Darem, Abdulbasit A. Majdoubi, Jihen Yafoz, Ayman Alsini, Raed Alghushairy, Omar Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Computer Science Applied College at Mahayil King Khalid University Saudi Arabia Department of Information Systems College of Computer Sciences & Information Technology King Faisal University Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border University Arar73213 Saudi Arabia Engineering and Technology Unit Applied College Majmaah University Al Majmaah11952 Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Department of Information Systems and Technology College of Computer Science and Engineering University of Jeddah Jeddah21589 Saudi Arabia

With the advent of state-of-the-art computer and digital technology, modern civilisation has been immensely facilitated and optimised. The Internet of Things (IoT) has grown in importance in recent years, allowing us to monitor our physical environments and broadening our horizons. The "practice, science, or art" of farming is defined as tending to land, growing crops with the use of different tools and techniques, and then selling the harvested food. If farmers optimise their operations with the help of a Wireless Sensor Network (WSN), they will be able to work much more efficiently and effectively. Data aggregation involves collecting information from multiple sensors. The data aggregation process is optimised by applying metaheuristic techniques. A Genetic Algorithm (GA) is a method for modelling evolution that uses mutation, crossover, and natural selection as its building blocks. The key benefit of the Artificial Bee Colony (ABC) approach is that it simultaneously considers local and global search, and it doesn't get trapped calculating its local minima. Naturalistic algorithms like ALO model their hunting behaviour after that of ant-lions and doodlebugs. It manages to find a happy medium between exploration and exploitation with just one operator. Experimental evidences show that the proposed metaheuristic technique, ABC-ALO, which combines the best elements of Artificial Bee Colony and Ant Lion Optimisation, is superior to existing metaheuristic approaches in terms of lifetime computation, or the number of alive nodes at different round counts. © 2025

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

MASSIVE(TM) - THE MASS-STORAGE SYSTEM IV ENTERPRISE

引用

PROCEEDINGS OF THE IEEE 1993年第4期81卷 621-630页

作者： SLOAN, JL OLEAR, BT KITTS, DL IRWIN, BL Scientific Computing Division National Center for Atmospheric Research Boulder CO USA

The Mass Storage System IV Enterprise is a fourth-generation mass storage system being designed at the National center for Atmospheric research. It will Provide file system service to teraflops computing systems appropriate to Grand Challenge problems. A bitfile managed by MaSSIVE(TM) can be a complete, self-contained UNIX(TM) file system specific to a particular MaSSIVE(TM) client. MaSSIVE(TM) will stage whole file systems from archival storage onto online storage devices and then provide its clients with raw block access to the staged file system. It will comply with the IEEE Mass Storage System Reference Model, and will consist of co-operating processes distributed across a network of supermicrocomputers. The client interface to a file system will be implemented through a custom device driver that will permit I/O to MaSSIVE(TM) online storage devices. The device interface through a high bandwidth data fabric to the storage device will use common device controller-specific protocols. As file systems are unmounted by clients or clients disconnect from the data fabric, file systems may be migrated back to archive storage and removed from online storage. Prototypes for portions of MaSSIVE(TM) are under development.

关键词： Computer networks Supercomputers Bandwidth Control systems Protocols FDDI Computer interfaces Engines Environmental economics High performance computing

来源：评论

学校读者我要写书评

暂无评论

Neural Synthetic Profiles from Remote Sensing and Observations (NeSPReSO) — Reconstructing temperature and salinity fields in the Gulf of Mexico

引用

Ocean Modelling 2025年 196卷

作者： Miranda, Jose R. Zavala-Romero, Olmo Hiron, Luna Chassignet, Eric P. Subrahmanyam, Bulusu Meunier, Thomas Helber, Robert W. Pallas-Sanz, Enric Tenreiro, Miguel Department of Scientific Computing Florida State University TallahasseeFL United States Center for Ocean-Atmospheric Prediction Studies Florida State University TallahasseeFL United States School of the Earth Ocean and Environment University of South Carolina ColumbiaFL United States Woods Hole Oceanographic Institution Woods HoleMS United States Laboratoire d'Océanographie Physique et Spatiale Ifremer/UBO/CNRS/IRD Brittany Plouzané France Ocean Sciences Division US Naval Research Laboratory Hancock CountyMS United States Ensenada Center for Scientific Research and Higher Education BC Ensenada Mexico

Accurate circulation modeling in the Gulf of Mexico (GoM) is hampered by the limited availability of in-situ subsurface data, leading to inaccuracies in subsurface representations. These inaccuracies diminish the reliability of ocean models and constrain the duration of dependable forecasts. This study introduces NeSPReSO (Neural Synthetic Profiles from Remote Sensing and Observations), a data-driven method to efficiently and accurately estimate subsurface temperature and salinity profiles using satellite-derived surface data. This provides an alternative to conventional synthetic data generation techniques. Principal Component Analysis (PCA) is applied to extract the main features of temperature and salinity profiles of an Argo dataset. Then, a neural network is trained to predict these principal features using inputs such as time, location, and satellite-derived absolute dynamic topography alongside sea surface temperature and salinity. The model, evaluated using additional Argo profiles and glider data collected in the Gulf of Mexico, over-performs other traditional synthetic data generation methods, such as the Gravest Empirical Modes (GEM), Multiple Linear Regression (MLR) and Improved Synthetic Ocean Profile (ISOP), in terms of root mean square error and bias. Our findings indicate that our method effectively captures the main variations of subsurface fields, and that synthetic profiles generated by the model align well with actual observations, accurately capturing key features such as thermoclines, haloclines, and temperature-salinity structure of the region. This new method will be implemented in GoM data assimilative models and is expected to improve the accuracy of modeled subsurface currents. © 2025 Elsevier Ltd

关键词： Data assimilation Gulf of Mexico Loop current Machine learning Synthetic temperature and salinity

来源：评论

学校读者我要写书评

暂无评论

Superconvergent Discontinuous Galerkin Method for the Scalar Teukolsky Equation on Hyperboloidal Domains: Efficient Waveform and Self-Force Computation

arXiv

引用

arXiv 2025年

作者： Vishal, Manas Field, Scott E. Gottlieb, Sigal Ryan, Jennifer Department of Mathematics University of Massachusetts DartmouthMA02747 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 KTH Royal Institute of Technology Stockholm Sweden

The long-time evolution of extreme mass-ratio inspiral systems requires minimal phase and dispersion errors to accurately compute far-field waveforms, while high accuracy is essential near the smaller black hole (modeled as a Dirac delta distribution) for self-force computations. Spectrally accurate methods, such as nodal discontinuous Galerkin (DG) methods, are well suited for these tasks. Their numerical errors typically decrease as ∝ (∆x)N+1, where ∆x is the subdomain size and N is the polynomial degree of the approximation. However, certain DG schemes exhibit superconvergence, where truncation, phase, and dispersion errors can decrease as fast as ∝ (∆x)2N+1. Superconvergent numerical solvers are, by construction, extremely efficient and accurate. We theoretically demonstrate that our DG scheme for the scalar Teukolsky equation with a distributional source is superconvergent, and this property is retained when combined with the hyperboloidal layer compactification technique. This ensures that waveforms, total energy and angular-momentum fluxes, and self-force computations benefit from superconvergence. We empirically verify this behavior across a family of hyperboloidal layer compactifications with varying degrees of smoothness. Additionally, we show that self-force quantities for circular orbits, computed at the point particle’s location, also exhibit a certain degree of superconvergence. Our results underscore the potential benefits of numerical superconvergence for efficient and accurate gravitational waveform simulations based on DG methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Galerkin methods

来源：评论

学校读者我要写书评

暂无评论

Immersive Embedded Consumer Model Leveraging AI with Zero-Trust Architecture for Cyber-Physical System

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Rehman, Amjad Haseeb, Khalid Kolivand, Hoshang Saba, Tanzila Al-Khasawneh, Mahmoud A. Ahmad, Shabir Ullah, Inam Lab Riyadh12435 Saudi Arabia Liverpool John Moores University School of Computer Science and Mathematics United Kingdom School of Computing and Digital Technologies Staffordshire University Liverpool Staffordshire United Kingdom University City Sharjah 1797 United Arab Emirates Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Jordan School of Computing Skyline University College Sharjah United Arab Emirates Incheon Startup Park Center of Artificial Intelligence for Medical Instruments Convensia-daero Incheon204 Korea Republic of Gachon University Department of Computer Engineering Seongnam13120 Korea Republic of

The rapid expansion of the wireless network and its combination with the Consumer Internet of Things (CIoT) has introduced significant research challenges for Cyber-Physical Systems (CPS). The distributed nature of these embedded networks provides big data analytics with the integration of sensors, electronic devices, hardware, and network components. They provide diverse functionalities while sensing the observing environment based on the demand of network users with timely feedback, which supports efficient decision-making. However, CIoT devices in CPS increasingly interact with both physical and digital environments, such interaction raises the research challenges of performance optimization, data breaches, and long-run seamless connectivity. In addition, the constraint devices demanded lightweight communication methods to remain robust and enhance network stability. This paper presents an adaptive model that leverages AI-based optimization techniques with efficient data management and utilization of resources in consumer applications. Moreover, the integrated edges provide consistency and resilience of communication services in unpredictable systems, while adopting a Zero-Trust architecture with more trustworthy and secure transmissions. It increases the system's scalability and improves the response time with the limited computing power of devices for real-time processing. Simulation results demonstrated the significant outcomes of the proposed model over the dynamic scenarios for packet delivery ratio by 35.5%, network throughput by 38.7%, energy consumption by 41.6%, and latency by 45% against existing solutions. © 1975-2011 IEEE.

关键词： consumer technologies edge intelligence embedded systems information security technological development

来源：评论

学校读者我要写书评

暂无评论

WORKSTATION CLUSTERS RISE AND SHINE

引用

SCIENCE 1993年第5123期261卷 852-853页

作者： BUZBEE, B Director of the Scientific Computing Division National Center for Atmospheric Research Boulder CO 80307

The workstation cluster has become a lower cost alternative for researchers needing access to single-site supercomputing. Workstation clusters are networked together in some fashion and appear to be a single resource.

关键词： Supercomputers Cost efficiency Input output Mainframe computers Microprocessors Technology Maintenance costs Computer software Central processing units Parallel computing

来源：评论

学校读者我要写书评

暂无评论

Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRI

Gaussian Process Emulators for Few-Shot Segmentation in Ca...

引用

15th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2024, Held in Conjunction with MICCAI 2024

作者： Viti, Bruno Thaler, Franz Kapper, Kathrin Lisa Urschler, Martin Holler, Martin Karabelas, Elias Department of Mathematics and Scientific Computing University of Graz Graz Austria Institute for Medical Informatics Statistics and Documentation Medical University of Graz Graz Austria Institute of Computer Graphics and Vision Graz University of Technology Graz Austria Gottfried Schatz Research Center: Medical Physics and Biophysics Medical University of Graz Graz Austria BioTechMed-Graz Graz Austria

ISBN: (纸本)9783031877551

Segmentation of cardiac magnetic resonance images (MRI) is crucial for the analysis and assessment of cardiac function, helping to diagnose and treat various cardiovascular diseases. Most recent techniques rely on deep learning and usually require an extensive amount of labeled data. To overcome this problem, few-shot learning has the capability of reducing data dependency on labeled data. In this work, we introduce a new method that merges few-shot learning with a U-Net architecture and Gaussian Process Emulators (GPEs), enhancing data integration from a support set for improved performance. GPEs are trained to learn the relation between the support images and the corresponding masks in latent space, facilitating the segmentation of unseen query images given only a small labeled support set at inference. We test our model with the M&Ms-2 public dataset to assess its ability to segment the heart in cardiac magnetic resonance imaging from different orientations, and compare it with state-of-the-art unsupervised and few-shot methods. Our architecture shows higher DICE coefficients compared to these methods, especially in the more challenging setups where the size of the support set is considerably small. The code is available on GitLab (https://***/bruno_viti/gpe_4_cardiac_fss). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

TORSION OF ABELIAN VARIETIES OF FINITE CHARACTERISTIC

引用

MATHEMATICAL NOTES 1977年第1-2期22卷 493-498页

作者： ZARKHIN, YG Scientific-Research Computing Center Academy of Sciences of the USSR USSR

The finiteness of the torsion of Abelian varieties with a complete real field of endomorphisms in the maximal Abelian extension of the field of definition is proven. This assertion is formally deduced from the finiteness hypothesis for isogenic Abelian varieties, proven for characteristic p > 2. The structure is studied of the Lie algebra of Galois groups acting in a Tate module; in particular, for fields of characteristic greater than two there is proven one-dimensionality of the center of the Lie algebra.

关键词：

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：