检索结果-内蒙古大学图书馆

Heterogeneous Fault-Tolerant Aggregate Signcryption with Equality Test for Vehicular Sensor networks

Computer Modeling in Engineering & sciences 2023年第10期137卷 555-575页

作者： Yang Zhao Jingmin An Hao Li Saru Kumari Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of ChinaChengdu610054China Department of Mathematics Chaudhary Charan Singh UniversityMeerut250004India

The vehicular sensor network (VSN) is an important part of intelligent transportation, which is used for real-timedetection and operation control of vehicles and real-time transmission of data and information. In the environmentofVSN, massive private data generated by vehicles are transmitted in open channels and used by other vehicle users,so it is crucial to maintain high transmission efficiency and high confidentiality of data. To deal with this problem, inthis paper, we propose a heterogeneous fault-tolerant aggregate signcryption scheme with an equality test (HFTASET).The scheme combines fault-tolerant and aggregate signcryption,whichnot onlymakes up for the deficiency oflow security of aggregate signature, but alsomakes up for the deficiency that aggregate signcryption cannot tolerateinvalid signature. The scheme supports one verification pass when all signcryptions are valid, and it supportsunbounded aggregation when the total number of signcryptions grows dynamically. In addition, this schemesupports heterogeneous equality test, and realizes the access control of private data in different cryptographicenvironments, so as to achieve flexibility in the application of our scheme and realize the function of quick searchof plaintext or ciphertext. Then, the security of HFTAS-ET is demonstrated by strict theoretical analysis. Finally, weconduct strict and standardized experimental operation and performance evaluation, which shows that the schemehas better performance.

关键词： Aggregate signcryption fault-tolerant heterogeneous equality test vehicular sensor network

来源：评论

学校读者我要写书评

暂无评论

SFPGCL: Specificity-preserving federated population graph contrastive learning for multi-site ASD identification using rs-fMRI data

引用

Computerized Medical Imaging and Graphics 2025年 124卷 102558页

作者： Ren, Yudan Ma, Zihan Ding, Zhenqing Yang, Ruonan Li, Xiao He, Xiaowei Liu, Tianming School of Information Science & Technology Northwest University Xi'an China School of Network and Data Center Northwest University Xi'an China Cortical Architecture Imaging and Discovery Lab School of Computing University of Georgia United States

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that affects people's social communication and daily routine. Most existing imaging studies on ASD use single site resting-state functional magnetic resonance imaging (rs-fMRI) data, which may suffer from limited samples and geographic bias. Improving the generalization ability of the diagnostic models often necessitates a large-scale dataset from multiple imaging sites. However, centralizing multi-site data generally faces inherent challenges related to privacy, security, and storage burden. Federated learning (FL) can address these issues by enabling collaborative model training without centralizing data. Nevertheless, multi-site rs-fMRI data introduces site variations, causing unfavorable data heterogeneity. This negatively impacts biomarker identification and diagnostic decision. Moreover, previous FL approaches for fMRI analysis often ignore site-specific demographic information, such as age, gender, and full intelligence quotient (FIQ), providing useful information as non-imaging features. On the other hand, Graph Neural networks (GNNs) are gaining popularity in fMRI representation learning due to their powerful graph representation capabilities. However, existing methods often focus on extracting subject-specific connectivity patterns and overlook inter-subject relationships in brain functional topology. In this study, we propose a specificity-preserving federated population graph contrastive learning (SFPGCL) framework for rs-fMRI analysis and multi-site ASD identification, including a server and multiple clients/sites for federated model aggregation. At each client, our model consists of a shared branch and a personalized branch, where parameters of the shared branch are sent to the sever, while those of the personalized branch remain local. This setup facilitates invariant knowledge sharing among sites and also helps preserve site specificity. In the shared branch, we employ a spatio-te

关键词： Brain mapping

来源：评论

学校读者我要写书评

暂无评论

Efficient selective planar emitters for thermophotovoltaic systems at 1473 K

引用

Applied Thermal Engineering 2025年 276卷

作者： Jian Wang Shouhao Zhang Xiaoyu Sun Chong Wang Zunqian Tang Fangyuan Yu Zirui Zhao Jun Mao Qian Zhang Feng Cao School of Science and Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Harbin Institute of Technology Shenzhen 518055 China School of Materials Science and Engineering and Institute of Materials Genome & Big Data Harbin Institute of Technology Shenzhen 518055 China

The development of efficient thermophotovoltaic (TPV) energy conversion systems can significantly address global energy crises and environmental pollution. Selective emitters in TPV systems play a crucial role in converting broad-spectra thermal radiation into narrowband radiation, thus effectively enhancing the energy conversion efficiency of TPV systems. However, achieving selective emitters with superior thermal stability, particularly at temperature above 1273 K, remains a significant challenge. The selective emitter exhibits an exceptional performance with a high in-band emittance of 0.92 under normal incidence, an outstanding emittance over 0.83 at an oblique incidence angle of 60°, as well as excellent thermal stability at 1473 K. The superior performance of the emitter is predominantly attributed to innovative optical design, including the introduction of co-sputtered ultra-high-temperature ceramics composite ceramic layers, thermal barrier layers and surface encapsulation layers. The TPV system combined with a 0.72 eV-GaSb photovoltaic cell, a filter, and the designed emitter, is predicted to achieve an energy conversion efficiency of approximately 27.4 % and a power output of 1.15 W/cm 2 at 1473 K. These findings highlight the potential of the multilayer selective thermal emitters as promising candidates for improving the performance of TPV systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Caching Strategy Based on Many-to-Many Matching Game in D2D networks

引用

Tsinghua science and technology 2021年第6期26卷 857-868页

作者： Kaihang Yu Zhonggui Ma Runyu Ni Tao Zhang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Key Lab of Information Network Security Ministry of Public SecurityShanghai 201204China

Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components of next-generation wireless networks. This paper focuses on the influences of different caching strategies in Device-to-Device(D2D) networks. We model the D2D User Equipments(DUEs) as the Gauss determinantal point process considering the repulsion between DUEs, as well as the caching replacement process as a many-to-many matching game. By analyzing existing caching placement strategies, a new caching strategy is proposed, which represents the preference list of DUEs as the ratio of content popularity to cached probability. There are two distinct features in the proposed caching strategy.(1) It can cache other contents besides high popularity contents.(2) It can improve the cache hit ratio and reduce the latency compared with three caching placement strategies: Least Recently Used(LRU), Equal Probability Random Cache(EPRC), and the Most Popular Content Cache(MPC). Meanwhile, we analyze the effect of caching on the system performance in terms of different content popularity factors and cache capacity. Simulation results show that our proposed caching strategy is superior to the three other comparison strategies and can significantly improve the cache hit ratio and reduce the latency.

关键词： caching strategy Device-to-Device(D2D)networks Gauss determinantal point process many-to-many matching game

来源：评论

学校读者我要写书评

暂无评论

Generative Retrieval Meets Multi-Graded Relevance 38

Generative Retrieval Meets Multi-Graded Relevance

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Tang, Yubao Zhang, Ruqing Guo, Jiafeng de Rijke, Maarten Chen, Wei Cheng, Xueqi CAS Key Lab of Network Data Science and Technology ICT CAS China University of Chinese Academy of Sciences China University of Amsterdam Netherlands

Generative retrieval represents a novel approach to information retrieval. It uses an encoder-decoder architecture to directly produce relevant document identifiers (docids) for queries. While this method offers benefits, current approaches are limited to scenarios with binary relevance data, overlooking the potential for documents to have multi-graded relevance. Extending generative retrieval to accommodate multi-graded relevance poses challenges, including the need to reconcile likelihood probabilities for docid pairs and the possibility of multiple relevant documents sharing the same identifier. To address these challenges, we introduce a framework called GRaded Generative Retrieval (GR2). GR2 focuses on two key components: ensuring relevant and distinct identifiers, and implementing multi-graded constrained contrastive training. First, we create identifiers that are both semantically relevant and sufficiently distinct to represent individual documents effectively. This is achieved by jointly optimizing the relevance and distinctness of docids through a combination of docid generation and autoencoder models. Second, we incorporate information about the relationship between relevance grades to guide the training process. We use a constrained contrastive training strategy to bring the representations of queries and the identifiers of their relevant documents closer together, based on their respective relevance grades. Extensive experiments on datasets with both multi-graded and binary relevance demonstrate the effectiveness of GR. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mamba-Sea: A Mamba-based Framework with Global-to-Local Sequence Augmentation for Generalizable Medical Image Segmentation

arXiv

引用

arXiv 2025年

作者： Cheng, Zihan Guo, Jintao Zhang, Jian Qi, Lei Zhou, Luping Shi, Yinghuan Gao, Yang Shanghai Jiao Tong University School of Medicine Shanghai200025 China National Institute of Healthcare Data Science Nanjing University Jiangsu Nanjing210093 China State Key Laboratory for Novel Software Technology the National Institute of Healthcare Data Science Nanjing University Jiangsu Nanjing210093 China School of Computer Science and Engineering Key Lab of Computer Network and Information Integration Southeast University Jiangsu Nanjing211189 China School of Electrical and Information Engineering The University of Sydney SydneyNSW2006 Australia

To segment medical images with distribution shifts, domain generalization (DG) has emerged as a promising setting to train models on source domains that can generalize to unseen target domains. Existing DG methods are mainly based on CNN or ViT architectures. Recently, advanced state space models, represented by Mamba, have shown promising results in various supervised medical image segmentation. The success of Mamba is primarily owing to its ability to capture long-range dependencies while keeping linear complexity with input sequence length, making it a promising alternative to CNNs and ViTs. Inspired by the success, in the paper, we explore the potential of the Mamba architecture to address distribution shifts in DG for medical image segmentation. Specifically, we propose a novel Mamba-based framework, Mamba-Sea, incorporating global-to-local sequence augmentation to improve the model’s generalizability under domain shift issues. Our Mamba-Sea introduces a global augmentation mechanism designed to simulate potential variations in appearance across different sites, aiming to suppress the model’s learning of domain-specific information. At the local level, we propose a sequence-wise augmentation along input sequences, which perturbs the style of tokens within random continuous sub-sequences by modeling and resampling style statistics associated with domain shifts. To our best knowledge, Mamba-Sea is the first work to explore the generalization of Mamba for medical image segmentation, providing an advanced and promising Mamba-based architecture with strong robustness to domain shifts. Remarkably, our proposed method is the first to surpass a Dice coefficient of 90% on the Prostate dataset, which exceeds previous SOTA of 88.61%. The code is available at https://***/orange-czh/Mamba-Sea. Copyright © 2025, The Authors. All rights reserved.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Evaluating natural language generation via unbalanced optimal transport 29

Evaluating natural language generation via unbalanced optima...

引用

29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Chen, Yimeng Lan, Yanyan Xiong, Ruibin Pang, Liang Ma, Zhiming Cheng, Xueqi University of Chinese Academy of Sciences China CAS Key Lab of Network Data Science and Technology Institute of Computing Technology CAS China Academy of Mathematics and Systems Science CAS China

ISBN: (纸本)9780999241165

Embedding-based evaluation measures have shown promising improvements on the correlation with human judgments in natural language generation. In these measures, various intrinsic metrics are used in the computation, including generalized precision, recall, F-score and the earth mover's distance. However, the relations between these metrics are unclear, making it difficult to determine which measure to use in real applications. In this paper, we provide an in-depth study on the relations between these metrics. Inspired by the optimal transportation theory, we prove that these metrics correspond to the optimal transport problem with different hard marginal constraints. However, these hard marginal constraints may cause the problem of incomplete and noisy matching in the evaluation process. Therefore we propose a family of new evaluation metrics, namely Lazy Earth Mover's Distances, based on the more general unbalanced optimal transport problem. Experimental results on WMT18 and WMT19 show that our proposed metrics have the ability to produce more consistent evaluation results with human judgements, as compared with existing intrinsic metrics. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Computation theory

来源：评论

学校读者我要写书评

暂无评论

Novel way to research nonlinear feedback shift register

引用

science China(Information sciences) 2014年第9期57卷 161-174页

作者： ZHAO DaWei PENG HaiPeng LI LiXiang HUI SiLi YANG YiXian Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and Telecommunications Zhejiang Provincial Key Lab of Data Storage and Transmission Technology Hangzhou Dianzi University National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and Telecommunications Shandong Provincial Key Laboratory of Computer Network Shandong Computer Science Center

In this paper,we regard the nonlinear feedback shift register(NLFSR)as a special Boolean network,and use semi-tensor product of matrices and matrix expression of logic to convert the dynamic equations of NLFSR into an equivalent algebraic *** on them,we propose some novel and generalized techniques to study ***,a general method is presented to solve an open problem of how to obtain the properties(the number of fixed points and the cycles with different lengths)of the state sequences produced by a given NLFSR,i.e.,the analysis of a given *** then show how to construct all 22n-(l-n)/22n-lshortest n-stage feedback shift registers(nFSR)and at least 22n-(l-n)-1/22n-l-1shortest n-stage nonlinear feedback shift registers(nNLFSR)which can output a given nonperiodic/periodic sequence with length ***,we propose two novel cycles joining algorithms for the construction of full-length ***,two algorithms are presented to construct 22n-2-1different full-length nNLFSRs,respectively.

关键词： nonlinear feedback shift register semi-tensor product Boolean network full-length nNLFSR binary sequence

来源：评论

学校读者我要写书评

暂无评论

Promoting Open-Domain Dialogue Generation Through Learning Pattern Information Between Contexts and Responses 12th

Promoting Open-Domain Dialogue Generation Through Learning P...

引用

12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023

作者： Liu, Mengjuan Liu, Chenyang Yang, Yunfan Liu, Jiang Jing, Mohan Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9783031446955

Recently, utilizing deep neural networks to build the open-domain dialogue models has become a hot topic. However, the responses generated by these models suffer from many problems such as responses not being contextualized and tend to generate generic responses that lack information content, damaging the user’s experience seriously. Therefore, many studies try introducing more information into the dialogue models to make the generated responses more vivid and informative. Unlike them, this paper improves the quality of generated responses by learning the implicit pattern information between contexts and responses in the training samples. In this paper, we first build an open-domain dialogue model based on the pre-trained language model (i.e., GPT-2). And then, an improved scheduled sampling method is proposed for pre-trained models, by which the responses can be used to guide the response generation in the training phase while avoiding the exposure bias problem. More importantly, we design a response-aware mechanism for mining the implicit pattern information between contexts and responses so that the generated replies are more diverse and approximate to human replies. Finally, we evaluate the proposed model (RAD) on the Persona-Chat and DailyDialog datasets;and the experimental results show that our model outperforms the baselines on most automatic and manual metrics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Visual Named Entity Linking: A New dataset and A Baseline

Visual Named Entity Linking: A New Dataset and A Baseline

引用

2022 Findings of the Association for Computational Linguistics: EMNLP 2022

作者： Sun, Wenxiang Fan, Yixing Guo, Jiafeng Zhang, Ruqing Cheng, Xueqi CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

Visual Entity Linking (VEL) is a task to link regions of images with their corresponding entities in Knowledge Bases (KBs), which is beneficial for many computer vision tasks such as image retrieval, image caption, and visual question answering. While existing tasks in VEL either rely on textual data to complement a multi-modal linking or only link objects with general entities, which fails to perform named entity linking on large amounts of image data. In this paper, we consider a purely Visual-based Named Entity Linking (VNEL) task, where the input only consists of an image. The task is to identify objects of interest (i.e., visual entity mentions) in images and link them to corresponding named entities in KBs. Since each entity often contains rich visual and textual information in KBs, we thus propose three different sub-tasks, i.e., visual to visual entity linking (V2VEL), visual to textual entity linking (V2TEL), and visual to visual-textual entity linking (V2VTEL). In addition, we present a high-quality human-annotated visual person linking dataset, named WIKIPerson. Based on WIKIPerson, we establish a series of baseline algorithms for the solution of each sub-task, and conduct experiments to verify the quality of the proposed datasets and the effectiveness of baseline methods. We envision this work to be helpful for soliciting more works regarding VNEL in the future. The codes and datasets are publicly available at https://***/ict-bigdatalab/VNEL. © 2022 Association for Computational Linguistics.

关键词： Image retrieval

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：