检索结果-内蒙古大学图书馆

Physics-informed machine learning with smoothed particle hydrodynamics: Hierarchy of reduced Lagrangian models of turbulence

引用

Physical Review Fluids 2023年第5期8卷 054602-054602页

作者： Michael Woodward Yifeng Tian Criston Hyett Chris Fryer Mikhail Stepanov Daniel Livescu Michael Chertkov Graduate Interdisciplinary Program in Applied Mathematics University of Arizona Tucson Arizona 85721 USA Department of Mathematics University of Arizona Tucson Arizona 85721 USA Computer Computational and Statistical Sciences Division LANL Los Alamos New Mexico 87544 USA

Building efficient, accurate, and generalizable reduced-order models of developed turbulence remains a major challenge. This manuscript approaches this problem by developing a hierarchy of parameterized reduced Lagrangian models for turbulent flows, and it investigates the effects of enforcing physical structure through smoothed particle hydrodynamics (SPH) versus relying on neural networks (NNs) as universal function approximators. Starting from NN parametrizations of a Lagrangian acceleration operator, this hierarchy of models gradually incorporates a weakly compressible and parameterized SPH framework, which enforces physical symmetries, such as Galilean, rotational, and translational invariances. Within this hierarchy, two new parameterized smoothing kernels are developed to increase the flexibility of the learn-able SPH simulators. For each model we experiment with different loss functions which are minimized using gradient based optimization, where efficient computations of gradients are obtained by using automatic differentiation and sensitivity analysis. Each model within the hierarchy is trained on two data sets associated with weakly compressible homogeneous isotropic turbulence: (1) a validation set using weakly compressible SPH; and (2) a high-fidelity set from direct numerical simulations. Numerical evidence shows that encoding more SPH structure improves generalizability to different turbulent Mach numbers and time shifts, and that including the novel parameterized smoothing kernels improves the accuracy of SPH at the resolved scales.

关键词： Sensitivity analysis

来源：评论

学校读者我要写书评

暂无评论

Universality of ac conduction for generalized space-charge transport in ordered solids

引用

Physical Review B 2005年第16期72卷 165110-165110页

作者： H. H. P. Gommans M. Kemerink W. H. A. Schilders Department of Applied Physics Eindhoven University of Technology 5600 MB Eindhoven The Netherlands Department of Mathematics and Computer Science Eindhoven University of Technology 5600 MB Eindhoven The Netherlands

On numerous nonmetallic systems, the ac conductivity is observed to follow an approximate power law behavior σ(ω)=ωs with 0<s⩽1. We show that the presence of nonlimiting, i.e., ohmic, contacts on the sample nece...

On numerous nonmetallic systems, the ac conductivity is observed to follow an approximate power law behavior σ(ω)=ωs with 0

关键词：

来源：评论

学校读者我要写书评

暂无评论

Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study

IEEE Transactions on Energy Markets, Policy and Regulation

引用

IEEE Transactions on Energy Markets, Policy and Regulation 2024年第1期2卷 40-51页

作者： Ferrando, Robert Pagnier, Laurent Mieth, Robert Liang, Zhirui Dvorkin, Yury Bienstock, Daniel Chertkov, Michael University of Arizona Program in Applied Mathematics and Department of Mathematics TucsonAZ85721 United States Department of Industrial and Systems Engineering at Rutgers University PiscatawayNJ08854 United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218-2625 United States Elec. and Comp. Eng. and Ralph o'Connor Sustainable Energy Institute Department of Civil and Systems Engineering Johns Hopkins University BaltimoreMD21218-2625 United States Columbia University IEOR New YorkNY10027 United States

This article addresses the challenge of efficiently recovering exact solutions to the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Aware Active Set learning OPF (PIMA-AS-OPF), leverages physical constraints and market properties to ensure physical and economic feasibility of market-clearing outcomes. Specifically, PIMA-AS-OPF employs the active set learning technique and expands its capabilities to account for curtailment in load or renewable power generation, which is a common challenge in real-world power systems. The core of PIMA-AS-OPF is a fully-connected neural network that takes the net load and the system topology as input. The outputs of this neural network include active constraints such as saturated generators and transmission lines, as well as non-zero load shedding and wind curtailments. These outputs allow for reducing the original market-clearing optimization to a system of linear equations, which can be solved efficiently and yield both the dispatch decisions and the locational marginal prices (LMPs). The dispatch decisions and LMPs are then tested for their feasibility with respect to the requirements for efficient market-clearing results. The accuracy and scalability of the proposed method is tested on a realistic 1814-bus NYISO system with current and future renewable energy penetration levels. © 2023 IEEE.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

Minimum-Latency Broadcast Scheduling in Wireless Ad Hoc Networks

Minimum-Latency Broadcast Scheduling in Wireless Ad Hoc Netw...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： S. C. -H. Huang P.-J. Wan X. Jia H. Du W. Shang Department of Computer Science City University of Hong Kong Hong Kong China Department of Computer Science Illinois Institute of Technology USA Institute of Applied Mathematics Chinese Academy and Sciences China

A wide range of applications for wireless ad hoc networks are time-critical and impose stringent requirement on the communication latency. This paper studies the problem Minimum-Latency Broadcast Scheduling (MLBS) in wireless ad hoc networks represented by unit-disk graphs. This problem is NP-hard. A trivial lower bound on the minimum broadcast latency is the radius R of the network with respect to the source of the broadcast, which is the maximum distance of all the nodes from the source of the broadcast. The previously best-known approximation algorithm for MLBS produces a broadcast schedule with latency at most 648 R. In this paper, we present three progressively improved approximation algorithms for MLBS. They produce broadcast schedules with latency at most 24 R -23, 16 R -15, and R + O (log R) respectively.

关键词： Mobile ad hoc networks Delay Approximation algorithms Processor scheduling computer science Peer to peer computing Scheduling algorithm Time factors Radio broadcasting Communications Society

来源：评论

学校读者我要写书评

暂无评论

On Semiseparable Kernels and Efficient Computation of Regularized System Identification and Function Estimation ⁎

引用

IFAC-PapersOnLine 2020年第2期53卷 462-467页

作者： Tianshi Chen Martin S. Andersen School of Science and Engineering and Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark

A long-standing problem for kernel-based regularization methods is their high computational complexity O(N 3 ), where N is the number of data points. In this paper, we show that for semiseparable kernels and some typical input signals, their computational complexity can be lowered to O(Nq 2 ), where q is the output kernel’s semiseparability rank that only depends on the chosen kernel and the input signal.

关键词： System identification kernel-based regularization semiseparable kernels kernel design efficient computation

来源：评论

学校读者我要写书评

暂无评论

Practical and dynamic key management scheme for a user hierarchy

引用

Journal of Zhejiang University: science 2006年第3期7卷 296-301页

作者： Jeng, Fuh-Gwo Wang, Chung-Ming Institute of Computer Science National Chung Hsing University Taichung 402 Taiwan Department of Applied Mathematics National Chiayi University Chiayi 60004 Taiwan

We propose a practical and dynamic key management scheme based on the Rabin public key system and a set of matrices with canonical matrix multiplication to solve the access control problem in an arbitrary partially ordered user hierarchy. The advantage is in ensuring that the security class in the higher level can derive any of its successor's secret keys directly and efficiently and show it is dynamic while a security class is added into or a class is removed from the hierarchy. Even the ex-member problem can be solved efficiently. Moreover, any user can freely change its own key for some security reasons.

关键词： Public key cryptography

来源：评论

学校读者我要写书评

暂无评论

Pain Classification Using Statistical Feature Extraction Using Machine Learning Approach: A Pilot Study

Pain Classification Using Statistical Feature Extraction Usi...

引用

IEEE International Conference on Control System, Computing and Engineering (ICCSCE)

作者： Sudimanto Agung Trisetyarso Iman Herwidiana Kartowisastro Widodo Budiharto Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science Computer Engineering Department Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jl. K. H. Syahdan No. 9 Kemanggisan Palmerah Jakarta Indonesia

Electrodermal activity (EDA) is a general term for all electrical phenomena occurring on the skin, both passive and active. EDA measurements are used by researchers to measure levels of stress, emotion, mental strain, and so on. Measuring human stress levels, emotions, and mental strain are generally associated with the skin conductance response. The function GSR sensor is not only used to read people’s psychology but also can be used as a pain sensor used to read the degree of pain in the skin. This pilot study uses sample data from ***. The *** data is galvanic skin response sensor data. The output of this sensor is the conductivity value that occurs in the skin. The data obtained from *** will be extracted using the mean, standard deviation, maximum, minimum, RMS, skewness, and peak-to-peak characteristics. The extracted functions are selected using the forward selection method. The results of the feature selection are three features with an accuracy percentage greater than 50%, namely the mean feature, the RMS feature, and the skewness feature. The machine learning models used are bagged tree, SVM, and K-NN models. Of the three models used, the bagged tree model has the highest accuracy rate, at 98.05%, with an F1 score is 0.9807. The KNN model with k=10 has the lowest level of accuracy compared to other models, at 96.75%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deoscillated adaptive graph collaborative filtering

arXiv

引用

arXiv 2020年

作者： Liu, Zhiwei Meng, Lin Jiang, Fei Zhang, Jiawei Yu, Philip S. Department of Computer Science University of Illinois Chicago United States Department of Computer Science Florida State University United States Committee on Computational and Applied Mathematics University of Chicago United States

Collaborative Filtering (CF) signals are crucial for a Recommender System (RS) model to learn user and item embeddings. High-order information can alleviate the cold-start issue of CF-based methods, which is modeled through propagating the information over the user-item bipartite graph. Recent Graph Neural Networks (GNNs) propose to stack multiple aggregation layers to propagate high-order signals. However, there are three challenges, the oscillation problem, varying locality of bipartite graph, and the fixed propagation pattern, which spoil the ability of the multilayer structure to propagate information. In this paper, we theoretically prove the existence and boundary of the oscillation problem, and empirically study the varying locality and layer-fixed propagation problems. We propose a new RS model, named as Deoscillated adaptive Graph Collaborative Filtering (DGCF), which is constituted by stacking multiple CHP layers and LA layers. We conduct extensive experiments on real-world datasets to verify the effectiveness of DGCF. Detailed analyses indicate that DGCF solves oscillation problems, adaptively learns local factors, and has layer-wise propagation patterns. Our code is available online. Copyright © 2020, The Authors. All rights reserved.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Exploiting software product lines to develop cloud computing applications 12

Exploiting software product lines to develop cloud computing...

引用

16th International Software Product Line Conference, SPLC 2012

作者： Cavalcante, Everton Almeida, André Batista, Thais Cacho, Nélio Lopes, Frederico Delicato, Flavia C. Sena, Thiago Pires, Paulo F. Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Natal Brazil Federal Institute of Education Science and Technology of Rio Grande do Norte Parnamirim Brazil School of Science and Technology Federal University of Rio Grande do Norte Natal Brazil Department of Computer Science Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781450310956

With the advance of the Cloud Computing paradigm, new challenges in terms of models, tools, and techniques to support developers to design, build and deploy complex software systems that make full use of the cloud technology arise. In the heterogeneous scenario of this new paradigm, the development of applications using cloud services becomes hard, and the software product lines (SPL) approach is potentially promising for this context since specificities of the cloud platforms, such as services heterogeneity, pricing model, and other aspects can be catered as variabilities to core features. In this perspective, this paper (i) proposes a seamless adaptation of the SPL-based development to include important features of cloud-based applications, and (ii) reports the experience of developing HW-CSPL, a SPL for the Health Watcher (HW) System, which allows citizens to register complaints and consult information regarding the public health system of a city. Several functionalities of this system were implemented using different Cloud Computing platforms, and run time specificities of this application deployed on the cloud were analyzed, as well as other information such as change impact and pricing. Copyright 2012 ACM.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Wearable Fall Detection Based on Motion Signals Using Hybrid Deep Residual Neural Network 1

引用

15th Multi-disciplinary International Conference on Artificial Intelligence, MIWAI 2022

作者： Mekruksavanich, Sakorn Jantawong, Ponnipa Hnoohom, Narit Jitpattanakul, Anuchit Department of Computer Engineering School of Information and Communication Technology University of Phayao Phayao Mueang Phayao Thailand Image Information and Intelligence Laboratory Department of Computer Engineering Faculty of Engineering Mahidol University Nakhon Pathom Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9783031209925

ISBN: (纸本)9783031209918

There have been several approaches for wearable fall detection devices during the last twenty years. The majority of technologies relied on machine learning. Although the given findings appear that the issue is practically addressed, critical problems remain about feature extraction and selection. In this research, the constraint of machine learning on feature extraction is addressed by including a hybrid convolutional operation in our proposed deep residual network, called the DeepFall model. The proposed network automatically generates high-level motion signal characteristics that can be utilized to track falls and everyday activities. FallAllD dataset, a publicly available standard dataset for fall detection that gathered motion signals of falls and other events, was utilized to analyze the proposed network. We performed investigations using a 5-fold cross-validation technique to determine overall accuracy and F-measure. The experimental outcomes show that the proposed DeepFall performs better accuracy (95.19%) and F-measure (92.79%) than the state-of-the-art baseline deep learning networks. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fall detection

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：