检索结果-内蒙古大学图书馆

作者： Jiang, Xutong Dou, Ruihan He, Qiang Zhang, Xuyun Dou, Wanchun State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Faculty of Mathematics University of Waterloo Waterloo Canada Department of Computer Science and Software Engineering Swinburne University of Technology Melbourne Australia Department of Computing Macquarie University Sydney Australia College of Big Data and Intelligent Engineering Southwest Forestry University China

Edge computing is regarded as an extension of cloud computing that brings computing and storage resources to the network edge. For some Industrial Internet of Things (IIoT) applications such as supply-chain supervision and collaboration, Internet of Vehicles, real-time video analysis and so forth, users should be authenticated before visiting the geographically distributed edge servers. Limited by the considerable latency between the cloud and edge servers, and the limited capacity of edge servers, it is infeasible to copy the authentication method from cloud servers when users are authenticated in edge servers. In view of this challenge, this paper proposes a novel token-based authentication scheme, named EdgeAuth, that enables fast edge user authentication through collaboration among cloud servers and edge servers. Under the EdgeAuth scheme, edge servers can rapidly verify the credentials of users who have been authenticated by the cloud server. EdgeAuth can also protect users from a series of authentication attacks, for example, the replay attack, DoS attack and man-in-the-middle attack. The results of experiments conducted on a simulated edge computing environment validate the usefulness of EdgeAuth through a comparison in latency and throughput against two baseline schemes. © 2023 John Wiley & Sons Ltd.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Community partition based source localization in early time 9

Community partition based source localization in early time

引用

9th IEEE International Conference on data Science in Cyberspace, DSC 2024

作者： Shi, Jinchen Fang, Yang Tan, Zhen Yang, Hui Zhao, Xiang National University of Defense Technology National Key Laboratory of Information Systems Engineering Changsha China National University of Defense Technology Changsha China The 30th Research Institute of China Electronics Technology Group Corporation Chengdu China National University of Defense Technology Laboratory for Big Data and Decision Changsha China

ISBN: (纸本)9798350391367

Since the widespread transmission of viruses, especially the outbreak of COVID-19, the identification of the source has become a crucial research direction. Due to the inability to acquire the states of all nodes and the significant cost of obtaining the state of each node in large networks, utilizing a limited number of sensors to monitor the entire network has become an important research focus. Previous methods simply fused observation results in various ways, while a recent model ESL based on expert support scores was proposed to enhance the model flexibility and improve the computational process. However, this method only improved the calculation process as it deploys the sensors randomly without effective information acquisition process. Therefore, we chose a sensor deployment method suitable for evidence theory and combined it with evidence theory to further enhance the accuracy and transferability of source localization using evidence theory. The results have been confirmed with real network data, demonstrating the effectiveness of our approach. © 2024 IEEE.

关键词： Sensor nodes

来源：评论

学校读者我要写书评

暂无评论

Ship Target Detection Algorithm Based on Improved YOLOv5 3

Ship Target Detection Algorithm Based on Improved YOLOv5

引用

3rd International Conference on Computer Science, Electronic Information engineering and Intelligent Control Technology, CEI 2023

作者： Zhu, Louyu Bi, Zhenbo School of Information Engineering Zhejiang Ocean University Zhoushan China Zhejiang Ocean University Department of Physics Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhoushan China

ISBN: (纸本)9798350372052

In view of the low accuracy and low efficiency of traditional ship target detection methods, this paper introduces an improved ship target detection method based on YOLOv5. Firstly, we preprocess the ship target data set, which includes graph denoising, graph enhancement and so on. Secondly, based on the benchmark YOLOv5 object detection algorithm, SimAM attention mechanism module is introduced. Then, a pyramid feature fusion strategy is added to filter conflicting information in airspace to suppress inconsistent features and improve the network's feature fusion capability for targets of different scales. Finally, the trained model is tested to achieve accurate evaluation of ship target detection. Experimental results show that the proposed ship target detection method is compared with YOLOv5s in accuracy rate, recall rate, mAP@0.5 and mAP@0.5: 0.95 increased by 1.9, 3.8, 2.6 and 7.3 percentage points. Respectively, which can meet the requirements of detection speed and obtain better detection accuracy, effectively realizing high-speed and high-precision ship detection. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Visualization and visual analysis of vessel trajectory data: A survey

引用

Visual Informatics 2021年第4期5卷 1-10页

作者： Haiyan Liu Xiaohui Chen Yidi Wang Bing Zhang Yunpeng Chen Ying Zhao Fangfang Zhou Institute of Data and Target Engineering Information Engineering UniversityZhengzhouChina School of Computer Science and Engineering Central South UniversityChangshaChina Rail Data Research and Application Key Laboratory of Hunan Province ChangshaChina

Maritime transports play a critical role in international trade and *** vessels sailing around the world continuously generate vessel trajectory data that contain rich spatial–temporal patterns of vessel *** and understanding these patterns are valuable for maritime traffic surveillance and *** essential techniques in complex data analysis and understanding,visualization and visual analysis have been widely used in vessel trajectory data *** paper presents a literature review on the visualization and visual analysis of vessel trajectory ***,we introduce commonly used vessel trajectory data sets and summarize main operations in vessel trajectory data ***,we provide a taxonomy of visualization and visual analysis of vessel trajectory data based on existing approaches and introduce representative works in ***,we expound on the prospects of the remaining challenges and directions for future research.

关键词： Maritime traffic Vessel trajectory data Automatic identification system Visualization and visual analysis

来源：评论

学校读者我要写书评

暂无评论

CW-YOLO: joint learning for mask wearing detection in low-light conditions

引用

Frontiers of Computer Science 2023年第6期17卷 191-193页

作者： Mingqiang GUO Hongting SHENG Zhizheng ZHANG Ying HUANG Xueye CHEN Cunjin WANG Jiaming ZHANG School of Computer Science China University of GeosciencesWuhan 430074China National Engineering Research Center of Geographic Information System Wuhan 430074China Wuhan Zondy Cyber Technology Co.Ltd. Wuhan 430074China Shenzhen Data Management Center of Planning and Natural Resources Shenzhen 518000China Key Laboratory of Urban Land Resources Monitoring and Simulation(Ministry of Natural Resources) Shenzhen 518000China College of Engineering Boston UniversityBoston 02215USA

1 Introduction With the rapid progress of Artificial Intelligence(AI)technology in object detection and face recognition,deep learning methods for face mask wearing detection have become increasingly mature and continuously take into account the needs of efficiency and ***,these conventional detection methods mostly ignore the complexity of real-world application scenarios,such as extremely darkness and gloomy *** unfavorable conditions lead to a series of image degradations that seriously hamper machine vision *** camera parameter adjustment,auxiliary lighting,or pre-processing enhancement[1]can weaken these negative effects to some extent to promote the detection,they will also result in increased hardware and time costs.

关键词： hardware lighting weather

来源：评论

学校读者我要写书评

暂无评论

Preparation of Photo-responsive DNA Supramolecular Hydrogels and Their Application as UV Radiometers

引用

Chemical Research in Chinese Universities 2023年第1期39卷 115-120页

作者： DING Yuqiao LI Yujie YANG Bo PAN Yufan CHENG Jiafeng MENG Siwen LIU Dongsheng XU Lijin DONG Yuanchen Department of Chemistry Renmin University of ChinaBeijing100872P.R.China Engineering Research Center of Advanced Rare Earth Materials Ministry of EducationDepartment of ChemistryTsinghua UniversityBeijing100084P.R.China CAS Key Laboratory of Colloid Interface and Chemical ThermodynamicsBeijing National Laboratory for Molecular SciencesInstitute of ChemistryChinese Academy of SciencesBeijing100190P.R.China University of Chinese Academy of Sciences Beijing100049P.R.China

Ultraviolet light(UV)is an essential component of ambient light,but high dose UV would damage genome *** semiconductors and soft materials have been employed to detect the UV,the complex process and the instrumental requirement have limited the application in daily *** this study,taking advantage of sequence designability,a series of hydrogels with different gel-sol transition rates was constructed under the same UV intensity by introducing competing hybridization to tune the stability of the molecular *** estimating the transition time between each system under UV light irradiation,the intensity of UV could be roughly estimated,which provided a convenient method for the visual detection of UV.

关键词： Photo-responsive DNA hydrogel Azobenzene Gel-sol transition UV detection

来源：评论

学校读者我要写书评

暂无评论

Understanding and Detecting Privacy Leakage Vulnerabilities in Hyperledger Fabric Chaincodes 35

Understanding and Detecting Privacy Leakage Vulnerabilities ...

引用

35th IEEE International Symposium on Software Reliability engineering, ISSRE 2024

作者： Chen, Ziming Li, Yue Gao, Jianbo Zhang, Jiashuo Wang, Ke Hu, Jianbin Guan, Zhi Chen, Zhong Peking University School of Computer Science Beijing China Taiyuan University of Technology College of Computer Science and Technology Taiyuan China Beijing Jiaotong University Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing China Peking University Chongqing Research Institute of Big Data Chongqing China Peking University National Engineering Research Center for Software Engineering Beijing China

ISBN: (纸本)9798350353884

The application on a blockchain cannot maintain secrecy because its data is replicated across all peers in the network. To remedy this problem, Hyperledger Fabric introduces private data collection (PDC) into its smart contract (i.e. chaincode) to facilitate applications that require privacy. However, recent studies have revealed that PDC is too complex for chaincode developers to fully understand and use correctly, leading to privacy leaks vulnerabilities. In this paper, we present an empirical study on the prevalence of PDC misuse in chaincodes by extracting privacy leakage cases from StackOverflow posts and Hyperledger Fabric repositories on GitHub. Subsequently, we systematically categorize the misuse of PDC into three categories of vulnerabilities resulting in the leakage of private data and provide formal definitions for them. Furthermore, we develop PDChecker, an automated security analysis framework for identifying the privacy and security vulnerabilities in Fabric chaincodes. We evaluated PDChecker on 956 real-world chaincodes applying PDC and found that 67.78% of them contain at least one privacy leakage vulnerability. In addition, PDChecker uncovered 10 zero-day vulnerabilities documented by the china National Vulnerability database. © 2024 IEEE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Multivariate Time Series Classification via Hierarchical Graph Embedding

Multivariate Time Series Classification via Hierarchical Gra...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Wenhao Niu Xingrui Zhuo Gongqing Wu JunWei Lv Zan Zhang Chenyang Bu Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China) School of Computer Science and Information Engineering Hefei University of Technology Anhui China

Multivariate time series classification aims to determine the labels for multivariate time series samples. Although variable interaction relationships and sample similarity relationships exist in multivariate time series, the available related methods usually ignore the rich relationships and are ineffective in exploiting these. To solve this problem, we propose a Hierarchical Graph Embedding for Multivariate Time Series Classification (MTSC-HGE), which consists of a variable-wise attentive graph pooling module and a sample-wise graph convolutional module to obtain the relationships of variables and samples. Specifically, we design an attentive graph pooling module based on self-attention, which can obtain sample features fusing temporal patterns and variable interaction relationships in samples. Furthermore, we propose a graph mapping criterion that converts the MTS dataset into a graph based on dynamic time warping to explicitly reflect the similarity relationships between samples. To capture latent sample relationships, a GCN module is utilized on the sample graph to integrate sample features obtained from the attentive graph pool module. In addition, a classifier takes the rich representation output by the model to get the final predicted class. Extensive experiments on 14 public datasets show that MTSC-HGE significantly outperforms state-of-the-art baselines.

关键词：

来源：评论

学校读者我要写书评

暂无评论

EvoChart: A Benchmark and a Self-Training Approach Towards Real-World Chart Understanding 39

EvoChart: A Benchmark and a Self-Training Approach Towards R...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Huang, Muye Lai, Han Zhang, Xinyu Wu, Wenjun Ma, Jie Zhang, Lingling Liu, Jun School of Computer Science and Technology Xi’an Jiaotong University China MOE KLINNS Lab Xi’an Jiaotong University China Shaanxi Province Key Laboratory of Big Data Knowledge Engineering China

ISBN: (纸本)157735897X

Chart understanding enables automated data analysis for humans, which requires models to achieve highly accurate visual comprehension. While existing Visual Language Models (VLMs) have shown progress in chart understanding, the lack of high-quality training data and comprehensive evaluation benchmarks hinders VLM chart comprehension. In this paper, we introduce EvoChart, a novel self-training method for generating synthetic chart data to enhance VLMs’ capabilities in real-world chart comprehension. We also propose EvoChart-QA, a noval benchmark for measuring models’ chart comprehension abilities in real-world scenarios. Specifically, EvoChart is a unique self-training data synthesis approach that simultaneously produces high-quality training corpus and a high-performance chart understanding model. EvoChart-QA consists of 650 distinct real-world charts collected from 140 different websites and 1,250 expert-curated questions that focus on chart understanding. Experimental results on various open-source and proprietary VLMs tested on EvoChart-QA demonstrate that even the best proprietary model, GPT-4o, achieves only 49.8% accuracy. Moreover, the EvoChart method significantly boosts the performance of open-source VLMs on real-world chart understanding tasks, achieving 54.2% accuracy on EvoChart-QA. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

THz Optical Image Recognition Method via AM-Res2Net Model

THz Optical Image Recognition Method via AM-Res2Net Model

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Song, Jiazhen Xi, Sixing Guan, Xun Zhang, Xiao-Ping Wang, Xiaolei Liu, Zhenyu Tsinghua Shenzhen International Graduate School Institute of Data and Information Shenzhen China Hebei University of Engineering School of Mathematics and Physics Handan China Nankai University Institute of Modern Optics Tianjin Key Laboratory of Micro-Scale Optical Information Science and Technology College of Electronic Information and Optical Engineering Tianjin China

ISBN: (纸本)9798350351255

Terahertz (THz) waves possess great properties such as ultra-large bandwidth, good penetration, strong reflectivity to metallic materials, and low photon energy, making them widely applicable in fields such as optical communication, optical networks, and optical imaging. Therefore, THz optical imaging, as a novel non-destructive testing technology, demonstrates significant application value in areas such as body security scanning. However, existing THz imaging systems require that targets be close to the detector in order to avoid issues like visible stripes, increased noise, reduced contrast, and blurred edges, which can significantly reduce the quality of imaging results. To solve this problem, this study proposes an AM-Res2Net model to achieve accurate THz optical image recognition. The proposed model, compared with the Res2Net model, uses multiple small kernel convolutions to replace a single large kernel convolution. Furthermore, the proposed model also replaces the activation function and introduces the attention mechanism in the residual structure. The AM-Res2Net model tested on the THz optical image set constructed in this study achieved a recognition accuracy of 94.3%, which is higher than the ResNet and Res2Net models. © 2024 IEEE.

关键词： Optical tomography

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：