检索结果-内蒙古大学图书馆

2023 World Wide Web Conference, WWW 2023

作者： Wang, Kaibin He, Qiang Chen, Feifei Jin, Hai Yang, Yun School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computing Technologies Swinburne University of Technology Australia School of Information Technology Deakin University Australia National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450394161

Federated learning (FL) has been widely acknowledged as a promising solution to training machine learning (ML) model training with privacy preservation. To reduce the traffic overheads incurred by FL systems, edge servers have been included between clients and the parameter server to aggregate clients' local models. Recent studies on this edge-assisted hierarchical FL scheme have focused on ensuring or accelerating model convergence by coping with various factors, e.g., uncertain network conditions, unreliable clients, heterogeneous compute resources, etc. This paper presents our three new discoveries of the edge-assisted hierarchical FL scheme: 1) it wastes significant time during its two-phase training rounds;2) it does not recognize or utilize model diversity when producing a global model;and 3) it is vulnerable to model poisoning attacks. To overcome these drawbacks, we propose FedEdge, a novel edge-assisted hierarchical FL scheme that accelerates model training with asynchronous local federated training and adaptive model aggregation. Extensive experiments are conducted on two widely-used public datasets. The results demonstrate that, compared with state-of-the-art FL schemes, FedEdge accelerates model convergence by 1.14 × -3.20 ×, and improves model accuracy by 2.14% - 6.63%. © 2023 ACM.

关键词： Edge computing

来源：评论

学校读者我要写书评

暂无评论

Asymmetric scattering behaviors of spin wave dependent on magnetic vortex chirality

引用

Chinese Physics B 2023年第10期32卷 635-640页

作者：张雪枫沈帝虎马晓萍宋成于海明朴红光 Hubei Engineering Research Center of Weak Magnetic-Field Detection China Three Gorges UniversityYichang 443002China Department of Physics College of ScienceYanbian UniversityYanji 133002China Key Laboratory of Advanced Materials(MOE) School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Fert Beijing Institute School of Integrated Circuit Science and EngineeringBeijing Advanced Innovation Center for Big Data and Brain ComputingBeihang UniversityBeijing 100191China

We investigate asymmetric spin wave scattering behaviors caused by vortex chirality in a cross-shaped ferromagnetic system by using the micromagnetic *** the system,four scattering behaviors are found:(i)asymmetric skew scattering,depending on the polarity of vortex core,(ii)back scattering(reflection),depending on the vortex core stiffness,(iii)side deflection scattering,depending on structural symmetry of the vortex circulation,and(iv)geometrical scattering,depending on waveguide *** first and second scattering behaviors are attributed to nonlinear topological magnon spin Hall effect related to magnon spin-transfer torque effect,which has value for magnonic exploration and application.

关键词： magnonics magnetic vortex spin wave magnetic chirality

来源：评论

学校读者我要写书评

暂无评论

Dispatcher: Resource-aware Nakamoto Blockchain via Hierarchical Topology and Adaptive Incentives

引用

Distributed Ledger Technologies: Research and Practice 2024年第2期3卷 1-20页

作者： Hai Jin Shuohua Dong Xiaohai Dai Yuandi Cai Jiang Xiao National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Mainstream blockchain systems such as Bitcoin and Ethereum are revolutionizing the financial industry by adopting the Nakamoto consensus protocol, i.e., Proof-of-Work (PoW). Only nodes with sufficient computing resources can work out the PoW difficulties, thereby increasing the mining cost of malicious attackers and ensuring the security of blockchain systems. Such an assumption of having abundant resources leads to drawbacks of low throughput and risk of centralization. In this article, we present Dispatcher, a novel distributed consensus protocol that takes resource heterogeneity into account to ensure resource-aware PoW with high efficiency. Dispatcher introduces a hierarchical topology to offer flexible PoW difficulties tailored for different nodes’ resources. In particular, it utilizes the limited resource of each node to jointly maximize the performance by concurrent mining. Moreover, we design an adaptive incentive mechanism to fit the available resource of blockchain nodes to rewards. Our experiments show that Dispatcher enjoys a substantial performance margin over the state-of-the-art. We can achieve a 50% throughput improvement compared with OHIE.

关键词： Blockchain resource heterogeneity incentive hierarchical architecture

来源：评论

学校读者我要写书评

暂无评论

TransUNet for Image Forgery Localization 3

TransUNet for Image Forgery Localization

引用

3rd International Conference on Computer Graphics, Image, and Virtualization, ICCGIV 2023

作者： Li, Kedi Li, Lin Li, Qingyan School of Science Jimei University Xiamen361021 China Computer Engineering College Jimei University Xiamen361021 China Digital Fujian Big Data Modeling and Intelligent Computing Institute Jimei University Xiamen361021 China

ISBN: (纸本)9781510671720

Image tampering can easily be used in illegal activities such as false propaganda, fake news and falsifying evidence in court which may have a negative impact on society. Therefore, we need to constantly update and improve the image tampering detection technology. TransUNet is an efficient model for medical image segmentation. This paper modified and migrated TransUNet which to image forgery localization, and conducted experiments on standard datasets to demonstrate the effectiveness of TransUNet. The findings shows that the proposed framework is superior to several existing forged area localization techniques. © 2023 SPIE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Joint Focal Loss and Dominant Gradient Correction for Gradient Conflict in Federated Learning 20

Joint Focal Loss and Dominant Gradient Correction for Gradie...

引用

20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Wang, Jiajun Mao, Yingchi Wang, Zibo Wu, Jun Wu, Jie Hohai University Key Laboratory of Water Big Data Technology of Ministry of Water Resources Nanjing China Hohai University School of Computer and Information Nanjing China Temple University Center for Networked Computing Philadelphia United States

ISBN: (纸本)9798350324334

Federated learning faces significant challenges of data heterogeneity among clients. In this heterogeneous data scenario, the preference of local models can result in gradient conflict during the global aggregation phase. This can significantly lead to a decrease in the global accuracy. In this paper, we present a novel Federated Learning Mitigating Gradient Conflict method named FedMGC that aims to mitigate gradient conflict. FedMGC replaces the cross-entropy loss function with the focal loss function. This balances the proportion of each class in the loss and reduces the preference of the local models for majority classes. In the global aggregation phase, we design the dominant gradient correction method called DGC to improve the global accuracy. Specifically, we select some of the gradients with small outliers to form the dominant gradients. And then we use dominant gradients to adjust the local gradients and alleviate the gradient conflict. In the evaluation experiments on heterogeneous datasets, FedMGC achieves higher test accuracy compared to baselines. In particular, over the CIFAR-10 dataset, FedMGC achieves 3.88%, 1.7% and 1.31% higher test accuracy than those of FedAvg, FedProx and FedNova, respectively. © 2023 IEEE.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

A Framework for Early Detection of Cyberbullying in Chinese-English Code-Mixed Social Media Text Using Natural Language Processing and Machine Learning 5

A Framework for Early Detection of Cyberbullying in Chinese-...

引用

5th International Conference on Natural Language Processing, ICNLP 2023

作者： Chu, Carlin Chun-Fai So, Raymond Li, Simon Siu-Wai Kwong, Ernest Kan-Lam Chiu, Chun-Hung The Hang Seng University of Hong Kong Department of Computing Hong Kong The Hang Seng University of Hong Kong Big Data Intelligence Centre Hong Kong School of Business Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798350302219

This study develops a new expert system framework to address the issue of early detection of cyberbullying incidents in Chinese-English code-mixed language on social media networks. The framework covers the crawling of session-based social media texts with potential cyberbullying messages with a crowdsourcing web application to systematically retrieve and manually annotate a cyberbullying dataset, and most importantly establishes an explainable artificial intelligence model based on natural language processing algorithm for identification of targeted emotional colloquial slang phrases and machine learning method using Shapley value and transfer learning approach for automatic early detection of cyberbullying incidents in Chinese-English codemixed language. © 2023 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

LCS-based Visual Recognition for AGV Guide Paths under Complex Illumination Conditions 15

LCS-based Visual Recognition for AGV Guide Paths under Compl...

引用

15th International Conference on Measurement Technology and Mechanical Automation, ICMTMA 2023

作者： Wang, Z.M. Li, M. Gao, C. Jin, X.M. School of Computer Science and Technology Xi'An University of Posts and Telecommunications Shaanxi Xi'an710121 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Shaanxi Xi'an710121 China Xi'An Key Laboratory of Big Data and Intelligent Computing Shaanxi Xi'an710121 China

Complex lighting is one of the most challenging problems in automatic guided vehicle (AGV) vision recognition system. In order to overcome the influence of uneven illumination on the accuracy and robustness of path recognition, this paper proposes the LCS based visual recognition for AGV guide paths under complex illumination conditions method, which converts the collected image into an invariant image through logarithmic chromaticity space (LCS) to eliminate the influence of illumination, and the minimum average entropy angle is used as the projection angle to generate the invariant image to improve the speed of image conversion to the invariant image. Experimental results show that the proposed method can effectively improve the robustness of AGV vision recognition system under complex lighting conditions. © Published under licence by IOP Publishing Ltd.

关键词： Lighting

来源：评论

学校读者我要写书评

暂无评论

Intention Recognition Method Based on Resting-state and P300 Task-state Dynamic Brain Functional Network Features 15

Intention Recognition Method Based on Resting-state and P300...

引用

15th International Conference on Measurement Technology and Mechanical Automation, ICMTMA 2023

作者： Yi, X. Wang, Z.M. Heng, X. School of Computer Science and Technology Xi'An University of Posts and Telecommunications Shaanxi Xi'an710121 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Shaanxi Xi'an710121 China Xi 'An Key Laboratory of Big Data and Intelligent Computing Shaanxi Xi'an710121 China

In order to reconfigure its structure from the static state in the vision odd ball task, so as to realize the intention recognition based on the characteristics of the brain functional network. The thesis proposes the intention recognition method based on resting state and P300 task state dynamic brain functional network features. First, the brain connectivity in each time window is constructed into a brain functional network using phase lock value (PLV). Then, extract the global features (global efficiency, transitivity) of the brain functional network, and use Louvain algorithm to obtain the brain functional network community. The experimental results show that in the (100-200) ms of P300 task status, the core nodes are mainly concentrated in the forehead region and the central region, while in the (300-500) ms of P300, the core nodes are concentrated in the temporal lobe. The recognition accuracy based on this method reaches 93%. © Published under licence by IOP Publishing Ltd.

关键词： Brain Function Network Intention Recognition P300 PLV Sliding Windows

来源：评论

学校读者我要写书评

暂无评论

Analyzing the Convergence of Federated Learning with Biased Client Participation 9th

Analyzing the Convergence of Federated Learning with Bias...

引用

19th International Conference on Advanced data Mining and Applications, ADMA 2023

作者： Tan, Lei Hu, Miao Zhou, Yipeng Wu, Di School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou510006 China School of Computing Faculty of Science and Engineering Macquarie University SydneyNSW2109 Australia

ISBN: (纸本)9783031466632

Federated Learning (FL) is a promising decentralized machine learning framework that enables a massive number of clients (e.g., smartphones) to collaboratively train a global model over the Internet without sacrificing their privacy. Though FL’s efficacy in non-convex problems is proven, its convergence amidst biased client participation lacks theoretical study. In this paper, we analyze the convergence of FedAvg on non-convex problems, which is the most renowned FL algorithm. We assume even data distribution but non-IID among clients, and elucidate the convergence rate of FedAvg in situations characterized by biased client participation. Our analysis reveals that biased client participation can significantly reduce the precision of the FL model. We validate this through trace-driven experiments, demonstrating that unbiased client participation results in 11% to 50% higher test accuracy compared to extremely biased client participation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

A Joint Learning Sentiment Analysis Method Incorporating Emoji-Augmentation 8

A Joint Learning Sentiment Analysis Method Incorporating Emo...

引用

8th IEEE International Conference on Cloud computing and Intelligence Systems, CCIS 2022

作者： Chen, Jie Luo, Luping Ji, Bojing Zhao, Shu Zhang, Yanping Anhui University The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology China Chizhou University School of Big Data and Artificial Intelligence China

ISBN: (纸本)9781665477352

Social media is the platform for most people to share their opinions, emojis are also widely used to express moods, emotions, and feelings on social media. There have been many researched on emojis and sentiment analysis. However, existing methods mainly face two limitations. First, since deep learning relies on large amounts of labeled data, the training samples of emoji are not enough to achieve the training effect. Second, they consider the sentiment of emojis and texts separately, not fully exploring the impact of emojis on the sentiment polarity of texts. In this paper, we propose a joint learning sentiment analysis method incorporating emoji-augmentation, and the method has two advantages compared with the existing work. First, We optimize the easy data augmentation method so that the newly generated sentences can also preserve the semantic information of emojis, which relieves the problem of insufficient training data with emojis. Second, it fuses emojis and text features to allow the model to better learn the mutual emotional semantics between text and emojis, jointly training emojis and words to obtain the sentence representations containing more semantic information of both emojis and text. Our experimental results show that the proposed method can significantly improve the performance compared with several baselines on two datasets. © 2022 IEEE.

关键词： Sentiment analysis

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：