检索结果-内蒙古大学图书馆

2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Huang, Wenxin Li, Dongyang Hu, Ruimin Liang, Chao Zhong, Xian School of Computer and Information Engineering Hubei University China National Engineering Research Center for Multimedia Software Wuhan University China Research Institute of Wuhan University Shenzhen China School of Computer Science and Technology Wuhan University of Technology China

ISBN: (纸本)9781665438643

Person re-identification (re-ID) gains plenty of achievements as a retrieval problem in constrained camera networks. However, most of the researches are concentrated on visual appearance, they still suffer from the complicated environments in unconstrained urban/campus surveillance scenario due to unreliable visual representations with extremely challenging problems as lack of training samples, amounts of irrelevant crowds, etc. Besides, most of the existing person re-ID datasets neglect the physical truth of realistic investigation application: 1) investigators search only few suspects among amounts of crowds. Moreover, he may not go through by every camera in the surveillance area and may appear in the same camera several times;and 2) the corresponding characteristic in multi-space of the same ID can be verified with each other. Therefore, we propose a person retrieval in physical world (PRPW) dataset with large-scale unconstrained surveillance scenario. It contains over 1.4 million bounding boxes, including 20 labeled IDs and numerous irrelevant crowds captured by 86 cameras. Furthermore, over 30,000 records of 20 mobile trajectories are collected in this dataset, and the 20 mobile trajectories are partially overlapped while passing by 86 cameras. Finally, based on two common senses and a verification experiment, we provide a proposal to tackle with PRPW task on the basis of trajectory association which utilizes global optimization to compensate for the errors caused by visual expression on local observation points. The comparison experiments with two typical unsupervised person re-ID methods are implemented on the constructed dataset. © 2021 IEEE

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Theoretical Analyses of Integral-Type Zhang Neurodynamics with Disturbances Inhibited Handling Temporally-Varying Nonlinear System of Equations

Theoretical Analyses of Integral-Type Zhang Neurodynamics wi...

引用

Chinese Automation Congress (CAC)

作者： Mingzhi Mao Ji Lu Yang Shi Yunong Zhang School of Software Engineering Sun Yat-sen University Zhuhai P. R. China School of Computer Science and Engineering Sun Yat-sen University Guangzhou P. R. China

We design and present an integral-type Zhang neurodynamics (ITZN) model for handling temporally-varying nonlinear system of equations (TVNSE). To investigate the disturbances inhibition of the model, the general form of the disturbed ITZN model is presented, and it is instantiated by introducing the constant disturbance, bounded random disturbance, and linear-form temporally-varying disturbance, resulting in three corresponding disturbed ITZN variants. Finally, by means of Lyapunov theory and Laplace transformation, we theoretically prove the globally exponential convergence of the ITZN model and the effective disturbances inhibition of the three disturbed ITZN variants.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ContractTinker: LLM-Empowered Vulnerability Repair for Real-World Smart Contracts

arXiv

引用

arXiv 2024年

作者： Wang, Che Zhang, Jiashuo Gao, Jianbo Xia, Libin Guan, Zhi Chen, Zhong School of Computer Science Peking University Beijing China Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing China National Engineering Research Center for Software Engineering Peking University Beijing China

Smart contracts are susceptible to being exploited by attackers, especially when facing real-world vulnerabilities. To mitigate this risk, developers often rely on third-party audit services to identify potential vulnerabilities before project deployment. Nevertheless, repairing the identified vulnerabilities is still complex and labor-intensive, particularly for developers lacking security expertise. Moreover, existing pattern-based repair tools mostly fail to address real-world vulnerabilities due to their lack of high-level semantic understanding. To fill this gap, we propose ContractTinker, a Large Language Models (LLMs)-empowered tool for real-world vulnerability repair. The key insight is our adoption of the Chain-of-Thought approach to break down the entire generation task into sub-tasks. Additionally, to reduce hallucination, we integrate program static analysis to guide the LLM. We evaluate ContractTinker on 48 high-risk vulnerabilities. The experimental results show that among the patches generated by ContractTinker, 23 (48%) are valid patches that fix the vulnerabilities, while 10 (21%) require only minor modifications. A video of ContractTinker is available at https://***/HWFVi-YHcPE. Copyright © 2024, The Authors. All rights reserved.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

GPUSCAN++: Efficient Structural Graph Clustering on GPUs

arXiv

引用

arXiv 2023年

作者： Yuan, Long Zhou, Zeyu Lin, Xuemin Chen, Zi Zhao, Xiang Zhang, Fan The School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China The School of Computer Science and Engineering The University of New South Wales Sydney Australia The Software Engineering Institute East China Normal University Shanghai China The College of Systems Engineering National University of Defense Technology Changsha China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China

Structural clustering is one of the most popular graph clustering methods, which has achieved great performance improvement by utilizing GPUs. Even though, the state-of-the-art GPU-based structural clustering algorithm, GPUSCAN, still suffers from efficiency issues since lots of extra costs are introduced for parallelization. Moreover, GPUSCAN assumes that the graph is resident in the GPU memory. However, the GPU memory capacity is limited currently while many real-world graphs are big and cannot fit in the GPU memory, which makes GPUSCAN unable to handle large graphs. Motivated by this, we present a new GPU-based structural clustering algorithm, GPUSCAN++, in this paper. To address the efficiency issue, we propose a new progressive clustering method tailored for GPUs that not only avoid high parallelization costs but also fully exploits the computing resources of GPUs. To address the GPU memory limitation issue, we propose a partition-based algorithm for structural clustering that can process large graphs with limited GPU memory. We conduct experiments on real graphs, and the experimental results demonstrate that our algorithm can achieve up to 168 times speedup compared with the state-of-the-art GPU-based algorithm when the graph can be resident in the GPU memory. Moreover, our algorithm is scalable to handle large graphs. As an example, our algorithm can finish the structural clustering on a graph with 1.8 billion edges using less than 2 GB GPU memory. Copyright © 2023, The Authors. All rights reserved.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Privacy-preserving cloud-fog–based traceable road condition monitoring in VANET

Privacy-preserving cloud-fog–based traceable road condition...

引用

作者： Wang, Wei Wu, Lei Qu, Wenlei Liu, Zhaoman Wang, Hao School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China Shandong Provincial Key Laboratory for Software Engineering Jinan China

With the development of intelligent vehicles, the research on road condition monitoring has attracted much attention in the vehicular ad hoc network (VANET). The combination of VANET, cloud computing, and fog computing provides on-demand computational resources while creating a lot of new challenges. In this paper, we propose an efficient privacy-preserving cloud-fog–based traceable road surface condition monitoring scheme. We use certificateless aggregate signcryption technology to implement multiple messages aggregation verification, which greatly saves computing resources and bandwidth. Moreover, we also use a traceable vehicle pseudo identity generated by a trace authority (TRA) to achieve identity privacy protection. To ensure the privacy of the fog and cloud server, the road condition information is reported in ciphertext format. In addition, the cloud server can perform ciphertext equivalence test operation to distinguish different road condition information of the same area without compromising the confidentiality. The ciphertext, which exceeds the set threshold, is uploaded to the blockchain. It can be stored permanently and never be tampered with or deleted. Finally, we demonstrate the correctness of the proposed scheme and show that the proposed scheme has higher efficiency. © 2020 John Wiley & Sons, Ltd.

关键词： Fog

来源：评论

学校读者我要写书评

暂无评论

One-to-Multiple Clean-Label Image Camouflage (Omclic) Based Backdoor Attack on Deep Learning

SSRN

引用

SSRN 2023年

作者： Wang, Guohong Ma, Hua Gao, Yansong Abuadbba, Alsharif Zhang, Zhi Wei, Kang Al-Sarawi, Said F. Zhang, Gongxuan Abbott, Derek School of Cyber Science and Engineering Nanjing University of Science and Technology Jiangsu Nanjing China School of Electrical and Electronic Engineering The University of Adelaide Australia Department of Computer Science and Software Engineering The University of Western Australia Australia Data61 Commonwealth Scientific and Industrial Research Organisation CSIRO Australia

Image camouflage has been utilized to create clean-label poisoned images for implanting backdoor into a DL model. But there exists a crucial limitation that one attack/poisoned image can only fit a single input size of the DL model, which greatly increases its attack budget when attacking multiple commonly adopted input sizes of DL models. This work proposes to constructively craft an attack image through camouflaging but can fit multiple DL models’ input sizes simultaneously, namely OmClic. Thus, through OmClic, we are able to always implant a backdoor regardless of which common input size is chosen by the user to train the DL model given the same attack budget (i.e., a fraction of the poisoning rate). With our camouflaging algorithm formulated as a multi-objective optimization, M = 5 input sizes can be concurrently targeted with one attack image, which artifact is retained to be almost visually imperceptible at the same time. Extensive evaluations validate the proposed OmClic can reliably succeed in various settings using diverse types of images. Further experiments on OmClic based backdoor insertion to DL models show that high backdoor performances (i.e., attack success rate and clean data accuracy) are achievable no matter which common input size is randomly chosen by the user to train the model. So that the OmClic based backdoor attack budget is reduced by M× compared to the state-of-the-art camouflage based backdoor attack as a baseline. Significantly, the same set of OmClic based poisonous attack images is transferable to different model architectures for backdoor implant. © 2023, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Financial Loan Overdue Risk Detection via Meta-path-based Graph Neural Network

Financial Loan Overdue Risk Detection via Meta-path-based Gr...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Jinze Chen Jieli Liu Zhiying Wu Shanhe Zhao Quanzhong Li Jiajing Wu School of Computer Science and Engineering Sun Yat-sen University Guangzhou China School of Software Engineering Sun Yat-sen University Zhuhai China Merchants Union Consumer Finance Company Limited Shenzhen China

Overdue risk detection of consumer loans is a critical issue faced by consumer finance companies. Unlike other types of loans, such as mortgage loans and guaranteed loans, consumer loans only regard personal credit as collateral. As a high overdue rate will result in economic losses to financial companies, it is of great significance for lenders to accurately detect risky customers. However, the large volume of credit data and the variety of customer characteristics make the risk detection via manual expert analysis rather challenging. Additionally, previous loan risk detection approaches based on machine learning classification neglect the relations between different customers, and traditional graph neural networks lack the exploration of loan overdue patterns. In this paper, we construct a heterogeneous graph based on real credit data from a consumer finance company. We analyze the distribution of meta-paths and propose a meta-path-based graph neural network that combines both lower-order and higher-order features. Experimental results show that our model is able to detect more risky customers by exploring overdue patterns and can achieve the best effect in the loan overdue detection task.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Explicit Analysis of Age of Synchronization in IoT Networks

Explicit Analysis of Age of Synchronization in IoT Networks

引用

IEEE International Conference on Information Communication and Signal Processing (ICICSP)

作者： Zhiwei Jin Siyuan Zhou Yunquan Dong Bin Tang Guoping Tan College of Information Science and Engineering Hohai University Nanjing China Key Laboratory of Water Big Data Technology of Ministry of Water Resources Hohai University Nanjing China College of Computer Science and Software Engineering Hohai University Nanjing China School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

The Internet of Things (IoT) has the capability to support the synchronous transmission of dynamically sensed environmental status information to base stations. To improve transmission timeliness, previous studies have commonly utilized Age of Information (AoI) as a metric for network performance. However, AoI falls short in capturing status synchronicity, as synchronization requires knowledge of updates from both the transmitter and the receiver, which AoI cannot reflect due to its inability to track changes at the transmitter. In this work, we adopt the Age of Synchronization (AoS) as a metric to quantify the time elapsed since the freshest information at the receiver becomes desynchronized. Specifically, we develop a model for an IoT communication network to derive closed-form expressions for the average peak AoS (PAoS) and average AoS, considering discrete geometric and uniformly distributed packet arrivals. Ad-ditionally, the analysis has been carried out for both first-come-first-served (FCFS) and last-come-first-served with preemptive resume (LCFS-PR) service disciplines. Within these results, we prove that network's synchronization performance worsens with longer packet arrival intervals but improves with higher arrival rates. LCFS-PR strategy makes synchronization independent of packet arrival, solely influenced by service rate. Additionally, AoS consistently remains lower than AoI in the same system, with both tending to converge as packet arrival rate rises.

关键词： Measurement Closed-form solutions Transmitters Processor scheduling Wireless networks Receivers Signal processing Synchronization Internet of Things Queueing analysis

来源：评论

学校读者我要写书评

暂无评论

A Crossover Algebra for Solving Minimum Spanning Tree in Network Design with Diameter Constraints

A Crossover Algebra for Solving Minimum Spanning Tree in Net...

引用

2021 International Conference on Cloud computer, IoT and Intelligence System, CCIIS 2021

作者： Wang, Ziyi Shi, Kai Qiao, Fuqiang Li, Huanran School of Computer Science and Engineering Tianjin University of Technology China College of Software and Communications Tianjin Sino-German University of Applied Sciences Tianjin China

The minimum spanning tree problem with diameter constraint is an important problem for many applications such as network design and reliability. The diameter constraint makes it be different from the common minimum spanning tree problem, it is difficult to get the optimal solution, even the feasible solution can not be obtained by the traditional method. To address this problem, in this paper, a new crossover algebra is designed to ensure that the crossover tree still satisfies the diameter constraint. During the crossover process, structure of the subtree will be retained, thus avoiding the problem that the new generated tree is not a feasible solution. Experimental results show the effectiveness of the improved algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Algebra

来源：评论

学校读者我要写书评

暂无评论

computer-Vision-Based Non-Contact Paste Concentration Measurement*

Computer-Vision-Based Non-Contact Paste Concentration Measur...

引用

Automation in Manufacturing, Transportation and Logistics (ICaMaL), International Conference on

作者： Tailin Liang Zhaolin Yuan State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing China Department of Industrial and Systems Engineering Research Institute of Advanced Manufacturing The Hong Kong Polytechnic University Hong Kong China

ISBN: (数字)9798350378658

ISBN: (纸本)9798350378665

For monitoring the paste concentration, existing techniques, such as ultrasonic concentration meters and neutron meters, suffer from radiation hazards and low precision in high concentrations. This paper proposes a novel non-contact concentration measurement method based on deep learning. With the dataset collected by preparing the paste with different concentrations and taking photographs from the paste surface, a convolutional neural network is trained to extract the features from images and predict the concentration. The experiments indicate that the measurement accuracy is close to 88.79 % for the manual stirring paste dataset and 91.42 % for the automatic stirring paste dataset, which are sufficient in industrial applications. As a substitution of traditional concentration measurement instruments, the proposed vision-based concentration measurement method is non-contact and its accuracy is sufficient in industrial applications.

关键词： Meters Deep learning Accuracy Ultrasonic variables measurement Transportation Manuals Feature extraction Surface texture Convolutional neural networks Surface treatment

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：