检索结果-内蒙古大学图书馆

IAENG International Journal of computer science 2025年第1期52卷 23-31页

作者： Guo, Ying Wang, Li School of Computer Science and software Engineering University of Science and Technology Liaoning Anshan114051 China College of Computer Science and Technology Liaoning Anshan114051 China

End-to-end training has emerged as a prominent trend in speech recognition, with Conformer models effectively integrating Transformer and CNN architectures. However, their complexity and high computational cost pose deployment challenges. To address these issues, we propose a multi-task Chinese speech recognition method based on the Squeezeformer model. We replace the FMCF structure in Conformer with an MF/CF structure, leveraging the convolutional module as a local Multi- Head Attention (MHA) module to enhance efficiency. Multilevel down-sampling and up-sampling using a time-series U-Net further reduce computational costs. By eliminating redundant LayerNorm layers and employing depthwise separable convolutions, we streamline the model, reduce parameters, and lower deployment costs. An Adaptor Layer is integrated into the MHSA module to mitigate the vanishing gradient problem, and a ScaleVar Layer is added to enhance flexibility. Additionally, the RealFormer module is introduced on the decoding side to improve context understanding. Combining Connectionist Temporal Classification (CTC) with attention-based encoding and decoding models for multi-task learning improves performance and accuracy. Experimental results show that the proposed method reduces the parameters on AISHELL-1 dataset by 16% and reduces the character error rate to 5.50%. At the same time, it also shows good performance on AISHELL-2 dataset. © (2025), (International Association of Engineers). All rights reserved.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Adaptive coupled-sliding-variable-based finite-time control of composite formation for multi-robot systems

引用

science China(Information sciences) 2024年第10期67卷 244-260页

作者： Xinru MA Hengyu LI Jun LIU Yueying WANG Shaorong XIE Jun LUO School of Mechatronic Engineering and Automation Shanghai University School of Mathematics and Computer Application Technology Jining University School of Computer Science Shanghai University College of Mechanical and Vehicle Engineering Chongqing University

This paper focuses on the finite-time control(FTC) of the composite formation consensus(CFC)problems for multi-robot systems(MRSs). The CFC problems are firstly proposed for MRSs under the complex network topology of cooperative or cooperative-competitive networks. Regarding the problems of FTC and CFC on multiple Lagrange systems(MLSs), coupled sliding variables are introduced to deal with the robustness and consistent convergence. Then, the adaptive finite-time protocols are given based on the displacement approaches. With the premised FTC, tender-tracking methods are further developed for the problems of tracking information disparity. Stability analyses of those MLSs mentioned above are clarified with Lyapunov candidates considering the coupled sliding vectors, which provide new verification for tender-tracking systems. Under the given coupled-sliding-variable-based finite-time protocols, MLSs distributively adjust the local formation error to achieve global CFC and perform uniform convergence in time-varying tracking. Finally, simulation experiments are conducted while providing practical solutions for the theoretical results.

关键词： composite formation time-vary tracking information disparity tender-tracking finite-time control nonlinear robots complex networks symmetry consensus

来源：评论

学校读者我要写书评

暂无评论

Privacy-preserving recommendation with coarse-grained spatiotemporal contexts

引用

science China(Information sciences) 2025年第4期68卷 66-81页

作者： Lei CHEN Chen GAO Jiahuan LEI Xiaoyi DU Xinlei SHI Hengliang LUO Depeng JIN Yong LI Meng WANG Department of Electronic Engineering BNRist Tsinghua University Meituan Inc. School of Computer Science and Information Engineering Hefei University of Technology

The behavior of users on online life service platforms like Meituan and Yelp often occurs within specific finegrained spatiotemporal contexts(i.e., when and where). Recommender systems, designed to serve millions of users, typically operate in a fully server-based manner, requiring on-device users to upload their behavioral data, including fine-grained spatiotemporal contexts, to the server, which has sparked public concern regarding privacy. Consequently, user devices only upload coarse-grained spatiotemporal contexts for user privacy protection. However, previous research mostly focuses on modeling fine-grained spatiotemporal contexts using knowledge graph convolutional models, which are not applicable to coarse-grained spatiotemporal contexts in privacy-constrained recommender systems. In this paper, we investigate privacy-preserving recommendation by leveraging coarse-grained spatiotemporal contexts. We propose the coarse-grained spatiotemporal knowledge graph for privacy-preserving recommendation(CSKG), which explicitly models spatiotemporal co-occurrences using common-sense knowledge from coarse-grained contexts. Specifically, we begin by constructing a spatiotemporal knowledge graph tailored to coarse-grained spatiotemporal contexts. Then we employ a learnable metagraph network that integrates common-sense information to filter and extract co-occurrences. CSKG evaluates the impact of coarsegrained spatiotemporal contexts on user behavior through the use of a knowledge graph convolutional network. Finally, we introduce joint learning to effectively learn representations. By conducting experiments on two real large-scale datasets,we achieve an average improvement of about 11.0% on two ranking metrics. The results clearly demonstrate that CSKG outperforms state-of-the-art baselines.

关键词： privacy-preserveing coarse-grained spatiotemporal contexts recommender systems

来源：评论

学校读者我要写书评

暂无评论

BAHBench: A Unified Benchmark for Evaluating Bio-Acoustic Health with Acoustic Foundation Models

引用

IEEE Journal of Biomedical and Health Informatics 2025年第6期PP卷 PP页

作者： Xu, Weixiang Dong, Zhongren Peng, Jing Wang, Runming Zhang, Zixing Hunan Normal University School of Information Science and Engineering Changsha410081 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Hunan University Shenzhen Research Institute Shenzhen518000 China

Acoustic foundation models, through self-supervised learning on large amounts of unlabeled speech data, can acquire rich acoustic representations. In recent years, these models have demonstrated substantial potential in audio-based health-related tasks, remarkably enhancing the efficiency and quality of healthcare services and contributing to the advancement of smart healthcare. However, there is currently a lack of systematic research and exploration on the performance of acoustic foundation models in health-related tasks. Furthermore, inconsistencies in evaluation methods and experimental setups hinder fair comparisons between different methods, severely impeding progress in this field. To address these challenges, we establish a unified Benchmark for evaluating Bio-Acoustic health via acoustic foundation models, namely BAHBench. BAHBench encompasses 6 distinct health-related tasks and evaluates 12 acoustic foundation models within a unified evaluation framework and parameter settings, enabling fair comparisons across different models. Our objective is to explore the effectiveness of current acoustic foundation models in health-related tasks. Thus, we discuss the impact of model size and data diversity on performance, and investigate feature selection and efficient fine-tuning strategy. Experimental results show that different health-related tasks benefit from features from different layers of the foundation model, while LoRA fine-tuning further enhances the model's performance on downstream tasks. Our goal is to provide clear and comprehensive guidance for future researchers. The code related to this study will be available to the research community to promote transparency and reproducibility. © 2013 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Inductive Lottery Ticket Learning for Graph Neural Networks

引用

Journal of computer science & technology 2024年第6期39卷 1223-1237页

作者： Yong-Duo Sui Xiang Wang Tianlong Chen Meng Wang Xiang-Nan He Tat-Seng Chua School of Data Science University of Science and Technology of ChinaHefei 230027China Department of Electrical and Computer Engineering The University of Texas at AustinAustin 78712U.S.A School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230009China School of Computing National University of SingaporeSingapore

Graph neural networks (GNNs) have gained increasing popularity, while usually suffering from unaffordable computations for real-world large-scale applications. Hence, pruning GNNs is of great need but largely unexplored. The recent work Unified GNN Sparsification (UGS) studies lottery ticket learning for GNNs, aiming to find a subset of model parameters and graph structures that can best maintain the GNN performance. However, it is tailed for the transductive setting, failing to generalize to unseen graphs, which are common in inductive tasks like graph classification. In this work, we propose a simple and effective learning paradigm, Inductive Co-Pruning of GNNs (ICPG), to endow graph lottery tickets with inductive pruning capacity. To prune the input graphs, we design a predictive model to generate importance scores for each edge based on the input. To prune the model parameters, it views the weight’s magnitude as their importance scores. Then we design an iterative co-pruning strategy to trim the graph edges and GNN weights based on their importance scores. Although it might be strikingly simple, ICPG surpasses the existing pruning method and can be universally applicable in both inductive and transductive learning settings. On 10 graph-classification and two node-classification benchmarks, ICPG achieves the same performance level with 14.26%–43.12% sparsity for graphs and 48.80%–91.41% sparsity for the GNN model.

关键词： lottery ticket hypothesis graph neural networks neural network pruning

来源：评论

学校读者我要写书评

暂无评论

Edge Caching Placement Optimization for Improving User Experience 24

Edge Caching Placement Optimization for Improving User Exper...

引用

2024 2nd International Conference on Internet of Things and Cloud Computing technology, IoTCCT 2024

作者： Luo, Jian Tang, Bing Liu, Yu Yang, Qing School of Computer Science and Engineering Hunan University of Science and Technology Hunan Xiangtan China School of Computer Science Guangzhou Maritime University Guangdong Guangzhou China

ISBN: (纸本)9798400710148

In recent years, the rapid expansion of short video services has led to a surge in internet traffic from mobile devices. Transferring a large volume of popular videos from centralized cloud servers to edge data centers or edge servers can incur significant expenses for these providers, highlighting the importance of a well-defined edge cache placement strategy. This paper explores into the cache placement problem of popular videos on short video platforms within edge environments, aiming to optimize user experience while minimizing cache deployment costs. Initially, we assess user experience holistically, considering both user preferences for popular videos and the latency involved in fetching requested content. Subsequently, we quantify cache placement expenses, accounting for both video transmission and storage costs. Ultimately, we formulate the placement problem as a single objective optimization problem maximizing overall user experience. A genetic algorithm is proposed to solve the problem. Simulation results indicate that, compared to traditional edge caching placement algorithms, our proposed strategy can reduce the average response time by 17% and improve the cache hit rate by 21%. © 2024 Copyright held by the owner/author(s).

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

A Survey of Deep Learning-Based Multimodal Vehicle Trajectory Prediction Methods 17th

A Survey of Deep Learning-Based Multimodal Vehicle Trajecto...

引用

17th China Conference on Wireless Sensor Networks, CWSN 2023

作者： Wang, Xiaoliang Zhou, Lian Liu, Yuzhen School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China

ISBN: (纸本)9789819710096

With the rapid development of deep learning, an increasing number of researchers have paid attention to and engaged in research in the field of autonomous driving, achieving numerous remarkable achievements. The paper aims to explore the current status and methods of trajectory prediction for autonomous vehicles, and reviews some commonly used trajectory prediction techniques and algorithms. The existing vehicle trajectory prediction tasks mainly involve extracting and modeling the historical trajectory sequences of the target vehicle and the surrounding environmental information features, to infer multimodal trajectories for a certain future time duration. The paper focuses on deep learning-based multimodal trajectory prediction methods, including traditional convolutional neural networks, recurrent neural networks, graph neural networks, attention mechanisms, and the latest research results of mixed models composed of multiple network structures. Additionally, two large-scale publicly available datasets in the field of autonomous driving, the Argoverse dataset and the nuScenes dataset are introduced, and the performance of existing evaluation metrics is analyzed. Finally, through the analysis and comparison of these methods, the paper summarizes and deduces the possible future directions of vehicle trajectory prediction and the existing technological bottlenecks, aiming to provide useful assistance and prospects for future research and application of autonomous vehicle trajectory prediction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Crystalline/Non-Crystalline Carbon Co-Modified Strategy to Construct N,S Co-Doped Carbon Layer Wrapped Fe_(0.95)S_(1.05)/Carbon Nanotubes for Enhanced Lithium Storage Property

引用

Acta Metallurgica Sinica(English Letters) 2025年第1期38卷 93-101页

作者： Liang Chen Lan−Yun Yang Li−Ting Zeng Xu Liu Xin−Rui Li Yu−Shan Tian Wei Wang Gang−Yong Li Chen−Xi Xu Zhao−Hui Hou Key Laboratory of Hunan Province for Advanced Carbon‒based Functional Materials School of Chemistry and Chemical EngineeringHunan Institute of Science and TechnologyYueyang414006China College of Materials Science and Engineering Central South University of Forestry and TechnologyChangsha410004China

Due to their high theoretical capacity and abundant resources,transition metal sulfides are regarded as a prospering alternative to replace the commercial graphite anode in lithium-ion batteries(LIBs),particularly for large-scale energy storage and conversion ***,low conductivity,easy agglomeration and obvious volume change greatly impede their practical *** this work,a novel crystalline/non-crystalline carbon co-modified strategy is proposed to fabricate N,S co-doped carbon(NSC)layer wrapped Fe_(0.95)S_(1.05)/carbon nanotubes(CNTs)composite(Fe_(0.95)S_(1.05)/CNTs@NSC)through a simple Fenton reaction followed by a sulfurization *** characterizations and analyses reveal that this strategy well combines the advantages of crystalline CNTs and non-crystalline NSC,ensuring good conductivity and a high contribution to capacity from the carbon ***,the joint encapsulation of Fe_(0.95)S_(1.05)by both CNTs and NSC can significantly mitigate the agglomeration and volume change of Fe_(0.95)S_(1.05)during the continuous charge/discharge *** from these advantageous features,the resultant Fe_(0.95)S_(1.05)/CNTs@NSC composite displays much improved cycling stability and rate capability when compared to the ***,our research offers a distinct and innovative approach to design and construct advanced transition metal sulfides/carbon composite anodes for LIBs.

关键词： Lithium-ion batteries Crystalline/non-crystalline carbon Joint encapsulation Fe_(0.95)S_(1.05)/CNTs@NSC Lithium storage property

来源：评论

学校读者我要写书评

暂无评论

Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication:Progress, Insights and Trends

引用

IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1539-1556页

作者： Weihao Song Zidong Wang Zhongkui Li Jianan Wang Qing-Long Han IEEE the State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceCollege of Engineering Peking University the Department of Computer Science Brunel University London the School of Aerospace Engineering Beijing Institute of Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

The nonlinear filtering problem has enduringly been an active research topic in both academia and industry due to its ever-growing theoretical importance and practical *** main objective of nonlinear filtering is to infer the states of a nonlinear dynamical system of interest based on the available noisy measurements. In recent years, the advance of network communication technology has not only popularized the networked systems with apparent advantages in terms of installation,cost and maintenance, but also brought about a series of challenges to the design of nonlinear filtering algorithms, among which the communication constraint has been recognized as a dominating concern. In this context, a great number of investigations have been launched towards the networked nonlinear filtering problem with communication constraints, and many samplebased nonlinear filters have been developed to deal with the highly nonlinear and/or non-Gaussian scenarios. The aim of this paper is to provide a timely survey about the recent advances on the sample-based networked nonlinear filtering problem from the perspective of communication constraints. More specifically, we first review three important families of sample-based filtering methods known as the unscented Kalman filter, particle filter,and maximum correntropy filter. Then, the latest developments are surveyed with stress on the topics regarding incomplete/imperfect information, limited resources and cyber ***, several challenges and open problems are highlighted to shed some lights on the possible trends of future research in this realm.

关键词： Communication constraints maximum correntropy filter networked nonlinear filtering particle filter sample-based approximation unscented Kalman filter

来源：评论

学校读者我要写书评

暂无评论

Refinement modeling and verification of secure operating systems for communication in digital twins

引用

Digital Communications and Networks 2024年第2期10卷 304-314页

作者： Zhenjiang Qian Gaofei Sun Xiaoshuang Xing Gaurav Dhiman School of Computer Science and Engineering Changshu Institute of TechnologySuzhou215500China University Centre for Research and Development Department of Computer Science and EngineeringChandigarh UniversityMohali140413India Department of Computer Science and Engineering Graphic Era Deemed to be UniversityDehradun248002India

In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the digital twin communication system implementation is completely *** verification is currently recognized as a method to ensure the correctness of software system for communication in digital twins because it uses rigorous mathematical methods to verify the correctness of systems for communication in digital twins and can effectively help system designers determine whether the system is designed and implemented *** this paper,we use the interactive theorem proving tool Isabelle/HOL to construct the formal model of the X86 architecture,and to model the related assembly *** verification result shows that the system states obtained after the operations of relevant assembly instructions is consistent with the expected states,indicating that the system meets the design expectations.

关键词： Theorem proving Isabelle/HOL Formal verification System modeling Correctness verification

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：