检索结果-内蒙古大学图书馆

Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

Internet of Things and Cyber-Physical systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Graph Pyramid Autoformer for Long- Term Traffic Forecasting 22

Graph Pyramid Autoformer for Long- Term Traffic Forecasting

引用

22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023

作者： Zhong, Weiheng Mallick, Tanwi MacFarlane, Jane Meidani, Hadi Balaprakash, Prasanna University of Illinois at Urbana-Champaign Department of Civil Environmental Engineering ChampaignIL United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States Sustainable Energy Systems Group Lawrence Berkeley National Laboratory BerkeleyCA United States Computing and Computational Sciences Directorate Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350345346

Accurate traffic forecasting is vital to an intelligent transportation system. Although many deep learning models have achieved state-of-art performance for short-term traffic forecasting of up to 1 hour, long-term traffic forecasting that spans multiple hours remains a major challenge. To that end, we develop Graph Pyramid Autoformer (GPA), an attention-based spatial-temporal graph neural network that uses a novel pyramid autocorrelation attention mechanism. It enables learning from long temporal sequences on graphs and improves long-term traffic forecasting accuracy. We demonstrate the efficacy of the GPA using two benchmark traffic datasets: Los Angeles' METR-LA and the Bay Area's PEMS-BAY. Notably, our model has outperformed a range of existing state-of-the-art methods, delivering up to a 25 % improvement in the accuracy of long-term traffic forecasts. Our code is available at: https://***/WeiheneZlExplainable-Graph-Autoformer. © 2023 IEEE.

关键词： Graph Neural Network Long-term forecasting Pyramid Autocorrelation attention

来源：评论

学校读者我要写书评

暂无评论

OUTLIER SYNTHESIS VIA HAMILTONIAN MONTE CARLO FOR OUT-OF-DISTRIBUTION DETECTION

arXiv

引用

arXiv 2025年

作者： Li, Hengzhuang Zhang, Teng National Engineering Research Center for Big Data Technology and System Service Computing Technology and Systems Laboratory Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Out-of-distribution (OOD) detection is crucial for developing trustworthy and reliable machine learning systems. Recent advances in training with auxiliary OOD data demonstrate efficacy in enhancing detection capabilities. Nonetheless, these methods heavily rely on acquiring a large pool of high-quality natural outliers. Some prior methods try to alleviate this problem by synthesizing virtual outliers but suffer from either poor quality or high cost due to the monotonous sampling strategy and the heavy-parameterized generative models. In this paper, we overcome all these problems by proposing the Hamiltonian Monte Carlo Outlier Synthesis (HamOS) framework, which views the synthesis process as sampling from Markov chains. Based solely on the in-distribution data, the Markov chains can extensively traverse the feature space and generate diverse and representative outliers, hence exposing the model to miscellaneous potential OOD scenarios. The Hamiltonian Monte Carlo with sampling acceptance rate almost close to 1 also makes our framework enjoy great efficiency. By empirically competing with SOTA baselines on both standard and large-scale benchmarks, we verify the efficacy and efficiency of our proposed HamOS. Our code is available at: https://***/Fir-lat/HamOS_OOD. © 2025, CC BY.

关键词： Markov chains

来源：评论

学校读者我要写书评

暂无评论

Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling

Scalable and Consistent Graph Neural Networks for Distribute...

引用

High Performance computing, Networking, Storage and Analysis, SC-W: Workshops of the International Conference for

作者： Shivam Barwey Riccardo Balin Bethany Lusch Saumil Patel Ramesh Balakrishnan Pinaki Pal Romit Maulik Venkatram Vishwanath Argonne National Laboratory Transportation and Power Systems USA Argonne National Laboratory Leadership Computing Facility USA Computational Science Division Argonne National Laboratory USA Information Sciences and Technology Pennsylvania State University USA Argonne National Laboratory Mathematics and Computer Science USA

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

This work develops a distributed graph neural network (GNN) methodology for mesh-based modeling applications using a consistent neural message passing layer. As the name implies, the focus is on enabling scalable operations that satisfy physical consistency via halo nodes at sub-graph boundaries. Here, consistency refers to the fact that a GNN trained and evaluated on one rank (one large graph) is arithmetically equivalent to evaluations on multiple ranks (a partitioned graph). This concept is demonstrated by interfacing GNNs with NekRS, a GPU-capable exascale CFD solver developed at Argonne National laboratory. It is shown how the NekRS mesh partitioning can be linked to the distributed GNN training and inference routines, resulting in a scalable mesh-based data-driven modeling workflow. We study the impact of consistency on the scalability of mesh-based GNNs, demonstrating efficient scaling in consistent GNNs for up to O(1B) graph nodes on the Frontier exascale supercomputer.

关键词： Training Data-driven modeling Analytical models Costs Message passing Scalability Writing Graph neural networks Supercomputers Standards

来源：评论

学校读者我要写书评

暂无评论

High-Performance SVD Partial Spectrum Computation 23

High-Performance SVD Partial Spectrum Computation

引用

2023 International Conference for High Performance computing, Networking, Storage and Analysis, SC 2023

作者： Keyes, David Ltaief, Hatem Nakatsukasa, Yuji Sukkari, Dalal Computer Electrical and Mathematical Sciences & Engineering Division King Abdullah University of Science & Technology Thuwal Saudi Arabia Mathematical Institute University of Oxford Oxford United Kingdom Innovative Computing Laboratory University of Tennessee Knoxville United States

ISBN: (纸本)9798400701092

We introduce a new singular value decomposition (SVD) solver based on the QR-based Dynamically Weighted Halley (QDWH) algorithm for computing the partial spectrum SVD (QDWHpartial-SVD) problems. By optimizing the rational function underlying the algorithms in the desired part of the spectrum only, the QDWHpartial-SVD algorithm efficiently computes a fraction (say 1 - 20%) of the leading singular values/vectors. We develop a high-performance implementation of QDWHpartial-SVD 1 on distributed-memory manycore systems and demonstrate its numerical robustness. We perform a benchmarking campaign against counterparts from the state-of-the-art numerical libraries across various matrix sizes using up to 36K MPI processes. Experimental results show performance speedups for QDWHpartial-SVD up to 6X and 2X against vendor-optimized PDGESVD from ScaLAPACK and KSVD on a Cray XC40 system using 1152 nodes based on two-socket 16-core Intel Haswell CPU, respectively. We also port our QDWHpartial-SVD software library to a system composed of 256 nodes with two-socket 64-Core AMD EPYC Milan CPU and achieve performance speedup up to 4X compared to vendor-optimized PDGESVD from ScaLAPACK. We also compare energy consumption for the two algorithms and demonstrate how QDWHpartial-SVD can further outperform PDGESVD in that regard by performing fewer memory-bound operations. © 2023 Owner/Author(s).

关键词： Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

Autotuning PolyBench benchmarks with LLVM Clang/Polly loop optimization pragmas using Bayesian optimization

Autotuning PolyBench benchmarks with LLVM Clang/Polly loop o...

引用

作者： Wu, Xingfu Kruse, Michael Balaprakash, Prasanna Finkel, Hal Hovland, Paul Taylor, Valerie Hall, Mary Mathematics & Computer Science Division Argonne National Laboratory LemontIL United States Argonne Leadership Computing Facility Argonne National Laboratory LemontIL United States Department of Computer Science University of Utah Salt Lake CityUT United States

We develop a ytopt autotuning framework that leverages Bayesian optimization to explore the parameter space search and compare four different supervised learning methods within Bayesian optimization and evaluate their effectiveness. We select six of the most complex PolyBench benchmarks and apply the newly developed LLVM Clang/Polly loop optimization pragmas to the benchmarks to optimize them. We then use the autotuning framework to optimize the pragma parameters to improve their performance. The experimental results show that our autotuning approach outperforms the other compiling methods to provide the smallest execution time for the benchmarks syr2k, 3mm, heat-3d, lu, and covariance with two large datasets in 200 code evaluations for effectively searching the parameter spaces with up to 170,368 different configurations. We find that the Floyd–Warshall benchmark did not benefit from autotuning. To cope with this issue, we provide some compiler option solutions to improve the performance. Then we present loop autotuning without a user's knowledge using a simple mctree autotuning framework to further improve the performance of the Floyd–Warshall benchmark. We also extend the ytopt autotuning framework to tune a deep learning application. © 2021 John Wiley & Sons Ltd.

关键词： Large dataset

来源：评论

学校读者我要写书评

暂无评论

Modeling Route Representation With Mixed-Scale Hierarchical Transformer

Modeling Route Representation With Mixed-Scale Hierarchical ...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hanyuan Zhang Yuqi Chen Xinyu Zhang Qize Jiang Liang Li Baihua Zheng Weiwei Sun School of Computer Science Fudan University Shanghai Key Laboratory of Data Science Fudan University Shanghai Institute of Intelligent Electronics & Systems School of Computing and Information Systems Singapore Management University

Modeling route representation aims to obtain contextual representations of an entire route for various traffic-related tasks. In reality, spatial-temporal data often exhibits multi-scale characteristics, which are utilized by many studies to enhance their performance. However, there is still a lack of in-depth research on how to effectively incorporate the multi-scale spatial-temporal information into transformer structure to adequately model route representation. In this paper, we propose a novel hierarchical route representation framework called RouteMT, which effectively captures multi-scale spatial-temporal characteristics of routes and leverages a mixed-scale transformer architecture to fuse intra and interroute features. Experiments on real data confirm RouteMT’s superior performance and versatility.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Experimental observation of coherent-perfect-absorber and laser points in anti-PT symmetry

引用

Physical Review A 2024年第3期110卷 033504页

作者： Minye Yang Qi Zhong Zhilu Ye Şahin K. Özdemir Mohamed Farhat Ramy El-Ganainy Pai-Yen Chen State Key Laboratory for Manufacturing Systems Engineering School of Electronic Science and Engineering Department of Electrical and Computer Engineering Department of Engineering Science and Mechanics The Materials Research Institute Computer Electrical and Mathematical Science and Engineering Division Department of Physics Henes Center for Quantum Phenomena

The coexistence of coherent perfect absorber and laser or amplifier (CPAL) point is a peculiar spectral singularity associated with the scattering matrices of non-Hermitian systems. While the potential of CPAL systems for sensing application has been highlighted recently, the extreme sensitivity of parity-time (PT)-symmetric CPAL devices to the input signal deviations has so far impeded their practical utilization. Here we explore a strategy for implementing CPAL circuits by exploiting another type of non-Hermitian symmetry, namely anti-PT (APT) symmetry. We demonstrate that the condition for building CPAL in our proposed APT-symmetric electronic circuits additionally requires parity symmetry, which simplifies the circuit design and implementation. Additionally, we show that this newly proposed structure is 1.85 times more robust compared to previous CPAL devices studied in the literature.

关键词： Noise Quantum sensing Non-Hermitian systems PT-symmetry

来源：评论

学校读者我要写书评

暂无评论

A Globally Convergent Method for computing B-stationary Points of Mathematical Programs with Equilibrium Constraints

arXiv

引用

arXiv 2025年

作者： Nurkanovic, Armin Leyffer, Sven Systems Control and Optimization Laboratory Department of Microsystems Engineering University of Freiburg Germany Mathematics and Computer Science Division Argonne National Laboratory United States

This paper introduces a method that globally converges to Bstationary points of mathematical programs with equilibrium constraints (MPECs) in a finite number of iterations. B-stationarity is necessary for optimality and means that no feasible first-order direction improves the objective. Given a feasible point of an MPEC, B-stationarity can be certified by solving a linear program with equilibrium constraints (LPEC) constructed at this point. The proposed method solves a sequence of LPECs, which either certify B-stationarity or provide an active-set estimate for the complementarity constraints, and nonlinear programs (NLPs) - referred to as branch NLPs (BNLPs) - obtained by fixing the active set in the MPEC. A BNLP is more regular than the MPEC, easier to solve, and with the correct active set, its solution coincides with the solution of the MPEC. The method has two phases: the first phase identifies a feasible BNLP or certifies local infeasibility, and the second phase solves a finite sequence of BNLPs until a B-stationary point of the MPECis found. The paper provides a detailed convergence analysis and discusses implementation details. In addition, extensive numerical experiments and an open-source software implementation are provided. The experiments demonstrate that the proposed method is more robust and faster than relaxation-based methods, while also providing a certificate of B-stationarity without requiring the usual too-restrictive *** Codes 90C30, 90C33, 49M37, 65K10, 90C11 © 2025, CC BY.

关键词： Nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

Initial Experiences with DAOS Object Storage on Aurora

Initial Experiences with DAOS Object Storage on Aurora

引用

High Performance computing, Networking, Storage and Analysis, SC-W: Workshops of the International Conference for

作者： Rob Latham Robert B. Ross Philip Carns Shane Snyder Kevin Harms Kaushik Velusamy Paul Coffman Gordon McPheeters Mathematics and Computer Science Division Argonne National Laboratory Lemont IL USA Argonne Leadership Computing Facility Argonne National Laboratory Lemont IL USA

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

The storage subsystem of the Aurora platform at Argonne National laboratory offers the potential for unprecedented application I/O performance. Its hardware stack combines NVMe drives, persistent memory devices, a large collection of storage servers, and a unified RDMA-capable network fabric. Its software stack is based on the DAOS object storage system, thereby putting into practice decades of I/O research into minimizing overhead, maximizing access concurrency, and streamlining application interfaces. Taken together, these elements combine to present up to 230 PiB of projected storage capacity and up to 31 TiB/s of projected I/O throughput to applications executing on *** storage platform is unique, however, and presents a new set of challenges to practitioners. To unlock the full potential of this system, we must revisit fundamental issues such as hardware topology, network concurrency, and I/O APIs to understand their impact on real-world I/O performance. In this paper we present our initial experiences with the DAOS storage system on Aurora and characterize its sensitivity to these parameters at small scale. We discuss our initial impressions and offer recommendations for how to extract maximum effective performance from this class of storage system.

关键词： Concurrent computing Performance evaluation Ion radiation effects Sensitivity Nonvolatile memory Throughput Hardware Topology Servers Magnetosphere

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：