检索结果-南通市图书馆

Personalized federated few-shot node classification

science China(Information sciences) 2025年第1期68卷 204-218页

作者： Yunfeng ZHAO Xintong HE Guoxian YU Jun WANG Yongqing ZHENG Carlotta DOMENICONI School of Software Shandong University Joint SDU-NTU Centre for Artificial Intelligence Research Shandong University Department of Mathematics National University of Singapore Department of computer science George Mason University

Personalized federated learning(PFL) aims to train customized models for individual clients in a decentralized setting, with the account of non-independent and identically distributed data across clients. However, most PFL methods adopt uniform classification layers for diverse clients and give rise to error-prone predictions, due to the task heterogeneity notably prominent in decentralized graph data scenarios. Although some PFL solutions setup client-specific classification layers for each client and optimize them only locally, they are corrupted with limited local training data. We propose an innovative solution called federated parameter decoupling and node augmentation(Fed PANo) to address these problems and to achieve personalized federated few-shot node classification, which is a prevalent and challenging but unexplored topic. Specifically, Fed PANo first separates the local model into the GNN and classifier to handle unique client-specific task variations. The GNN is trained through federated learning to capture shared knowledge of graph nodes across clients, while the classifier is custom-designed and trained individually for each client. Additionally, a generic classifier shared among clients is adopted to encourage the GNN's grasp of shared information. Then Fed PANo further proposes the node generator along with its local and collaborative training strategies to deal with the node scarcity of clients. Extensive experimental results on benchmark datasets confirm that Fed PANo outperforms eight competitive baselines across different settings.

关键词： personalized federated learning few-shot learning node classification task heterogeneity parameter decoupling node augmentation

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

SEFormer:A Lightweight CNN-Transformer Based on Separable Multiscale Depthwise Convolution and Efficient Self-Attention for Rotating Machinery Fault Diagnosis

引用

computers, Materials & Continua 2025年第1期82卷 1417-1437页

作者： Hongxing Wang Xilai Ju Hua Zhu Huafeng Li State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing210016China School of computer science and Engineering Nanyang Technological UniversitySingapore639798Singapore

Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain ***,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis ***,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault ***,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative *** complexity results in high computational costs and limited industrial *** tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault ***,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration ***,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global ***,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and *** study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.

关键词： CNN-Transformer separable multiscale depthwise convolution efficient self-attention fault diagnosis

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Hydrogen Energy Storage System:Review on Recent Progress

引用

Energy Engineering 2025年第1期122卷 1-39页

作者： MilleniumWong Hadi Nabipour Afrouzi Research Centre for Sustainable Technologies Faculty of EngineeringComputing and ScienceSwinburne University of TechnologyJalan Simpang TigaKuchingSarawak93350Malaysia College of Engineering Faculty of ComputingEngineering and the Built EnvironmentBirmingham City UniversityBirminghamWest MidlandsEnglandB47XGUK

A hydrogen energy storage system(HESS)is one of the many risingmodern green innovations,using excess energy to generate hydrogen and storing it for various *** that,there have been many discussions about commercializing HESS and improving it ***,the design and sizing process can be overwhelming to comprehend with various sources to examine,and understanding optimal design methodologies is crucial to optimize a HESS *** that,this review aims to collect and analyse a wide range of HESS studies to summarise recent *** different collections of studies are studied,one was sourced by the main author for preliminary readings,and another was obtained via *** findings from the Web of science platform were also examined for amore comprehensive *** findings include the People’sRepublic of China has been active in HESS research,as most works and active organizations originate from this *** has been mainly researched to support power generation and balance load demands,with financial analysis being the common scope of *** is a common tool used for HESS design,modelling,and optimization as it can handle complex *** neural network(ANN)has the potential to be used to model the HESS,but additional review is required as a formof future *** a commercialization perspective,pressurized hydrogen tanks are ideal for hydrogen storage in a HESS,but other methods can be considered after additional research and *** this review,it can be implied that modelling works will be the way forward for HESS research,but extensive collaborations and additional review are ***,this review summarized various takeaways that future research works on HESS can use.

关键词： Hydrogen energy storage system VOSViewer design review sizing

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Subnetwork-based federated few-shot semantic segmentation of organ images

引用

Optoelectronics Letters 2025年

作者： Wu Junpeng Zhao Meng Zhang Huanping Key Laboratory of computer Vision and System of Ministry of Education， School of computer science and Engineering， Tianjin University of Technology

Federated learning(FL)， as a distributed learning paradigm， allows multiple medical institutions to collaborate on learning without the need to centralize all client data. However， existing methods pay little attention to more challenging medical image semantic segmentation tasks， especially in the scenario of the imbalanced dataset in federated few-shot learning. In this paper， we propose a subnetwork-based federated few-shot organ image segmentation method. Firstly， individual clients train using local training samples and then upload local model gradients to the server. The server utilizes their respective local model gradients to update the subnetwork maintained on the server and generate aggregation weights for forming personalized model parameters. Through this method， we can learn the similarities between different clients to address data heterogeneity issues. In addition， to enhance the communication efficiency between clients and the server， we have also designed a personalized layer aggregation strategy， which only transmits partial layer model parameters during the communication process to improve communication efficiency. Finally， we conducted experiments on ABD-MRI and ABD-CT datasets to demonstrate the effectiveness of our method.

关键词：

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Navigating the pathways:TAR-DNA-binding-protein-43 aggregation,axonal transport,and local synthesis in amyotrophic lateral sclerosis pathology

引用

Neural Regeneration Research 2025年第10期20卷 2921-2922页

作者： Ori Bar Avi Eran Perlson Department of Physiology and Pharmacology Faculty of Medical&Health ScienceTel-Aviv UniversityTel-AvivIsrael Sagol School of Neuroscience Tel-Aviv UniversityTel-AvivIsrael

Neurons are highly polarized cells with axons reaching over a meter long in adult *** survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and *** mechanisms include axonal transport,local synthesis,and liquid-liquid phase *** and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).

关键词： synthesis local aggregation

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

RE-SEGNN:recurrent semantic evidence-aware graph neural network for temporal knowledge graph forecasting

引用

science China(Information sciences) 2025年

作者： Wenyu CAI Mengfan LI Xuanhua SHI Yuanxin FAN Quntao ZHU Hai JIN 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 TechnologyHuazhong University of Science and Technology

Temporal knowledge graph(TKG) reasoning, has seen widespread use for modeling real-world events, particularly in extrapolation settings. Nevertheless, most previous studies are embedded models, which require both entity and relation embedding to make predictions, ignoring the semantic correlations among different entities and relations within the same timestamp. This can lead to random and nonsensical predictions when unseen entities or relations occur. Furthermore, many existing models exhibit limitations in handling highly correlated historical facts with extensive temporal depth. They often either overlook such facts or overly accentuate the relationships between recurring past occurrences and their current counterparts. Due to the dynamic nature of TKG, effectively capturing the evolving semantics between different timestamps can be *** address these shortcomings, we propose the recurrent semantic evidenceaware graph neural network(RE-SEGNN), a novel graph neural network that can learn the semantics of entities and relations simultaneously. For the former challenge, our model can predict a possible answer to missing quadruples based on semantics when facing unseen entities or relations. For the latter problem, based on an obvious established force, both the recency and frequency of semantic history tend to confer a higher reference value for the current. We use the Hawkes process to compute the semantic trend, which allows the semantics of recent facts to gain more attention than those of distant facts. Experimental results show that RE-SEGNN outperforms all SOTA models in entity prediction on 6 widely used datasets, and 5 datasets in relation prediction. Furthermore, the case study shows how our model can deal with unseen entities and relations.

关键词：

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials

引用

computer Modeling in Engineering & sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef Walek Jaromír Kopecek Department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree Regression(DTR),and Gaussian Process Regression(GPR)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPR method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

引用

computer Modeling in Engineering & sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and Data science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of Electrical and Electronics Engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia Department of computer science and Engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia Department of computer science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

引用

Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.MUHAMMAD M.SARFRAZ Department of Humanities and sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

关键词： Nanofluidics

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Brain age estimation:premise,promise,and problems

引用

Neural Regeneration Research 2025年第8期20卷 2313-2314页

作者： Jarrad Perron Ji Hyun Ko Graduate Program in Biomedical Engineering Price Faculty of EngineeringUniversity of ManitobaWinnipegMBCanada PrairieNeuro Research Centre Kleysen Institute for Advanced MedicineHealth Sciences CentreWinnipegMBCanada Department of Human Anatomy and Cell science Rady Faculty of Health SciencesUniversity of ManitobaWinnipegMBCanada

Premise:The com bined effects of modern healthcare practices which prolong lifespan and declining birthrates have created unprecedented changes in age demographics worldwide that are especially pronounced in Japan,South Korea,Europe,and North *** old age is the most significant predictor of dementia,global healthcare systems must rise to the challenge of providing care for those with neurodegenerative disorders.

关键词： estimation providing birth

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：