检索结果-内蒙古大学图书馆

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Xiaogeng Liu Minghui Li Haoyu Wang Shengshan Hu Dengpan Ye Hai Jin Libing Wu Chaowei Xiao School of Cyber Science and Engineering Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Software Engineering Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan University School of Computer Science and Technology Huazhong University of Science and Technology Cluster and Grid Computing Lab Arizona State University

Deep neural networks are proven to be vulnerable to backdoor attacks. Detecting the trigger samples during the inference stage, i.e., the test-time trigger sample detection, can prevent the backdoor from being triggered. However, existing detection methods often require the defenders to have high accessibility to victim models, extra clean data, or knowledge about the appearance of backdoor triggers, limiting their practicality. In this paper, we propose the test-time corruption robustness consistency evaluation (TeCo) 1 1 https://***/CGCL-codes/TeCo, a novel test-time trigger sample detection method that only needs the hard-label outputs of the victim models without any extra information. Our journey begins with the intriguing observation that the backdoor-infected models have similar performance across different image corruptions for the clean images, but perform discrepantly for the trigger samples. Based on this phenomenon, we design TeCo to evaluate test-time robustness consistency by calculating the deviation of severity that leads to predictions' transition across different corruptions. Extensive experiments demonstrate that compared with state-of-the-art defenses, which even require either certain information about the trigger types or accessibility of clean data, TeCo outperforms them on different backdoor attacks, datasets, and model architectures, enjoying a higher AUROC by 10% and 5 times of stability.

关键词：

来源：评论

学校读者我要写书评

暂无评论

VAction: A Lightweight and Integrated VR Training system for Authentic Film-Shooting Experience 25

VAction: A Lightweight and Integrated VR Training System for...

引用

2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Wang, Shaocong Qu, Che Yu, Minjing Zhou, Chao Wang, Yuntao Wen, Yu-Hui Shi, Yuanchun Liu, Yong-Jin Department of Computer Science and Technology Tsinghua University Beijing China Film & TV Technology Department Beijing Film Academy Beijing China College of Intelligence and Computing Tianjin University Tianjin China Human Computer Interaction Technology Intelligent Information Processing Laboratory Institute of Software Chinese Acadamy of Sciences Beijing China School of Computer Science and Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798400713941

The film industry exerts significant economic and cultural influence, and its rapid development is contingent upon the expertise of industry professionals, underscoring the critical importance of film-shooting education. However, this process typically necessitates multiple practice in complex professional venues using expensive equipment, presenting a significant obstacle for ordinary learners who struggle to access such training environments. Despite VR technology has already shown its potential in education, existing research has not addressed the crucial learning component of replicating the shooting process. Moreover, the limited functionality of traditional controllers hinder the fulfillment of the educational requirements. Therefore, we developed VAction VR system, combining high-fidelity virtual environments with a custom-designed controller to simulate the real-world camera operation experience. The system's lightweight design ensures cost-effective and efficient deployment. Experiment results demonstrated that VAction significantly outperforms traditional methods in both practice effectiveness and user experience, indicating its potential and usefulness in film-shooting education. © 2025 Copyright held by the owner/author(s).

关键词： Film Production Education Interaction Design Training system Virtual Reality

来源：评论

学校读者我要写书评

暂无评论

Using Lock-Free Design for Throughput-Optimized Cache Eviction

引用

Proceedings of the ACM on Measurement and Analysis of computing systems 2025年第2期9卷 1-28页

作者： Chao Dong Fang Wang Hong Jiang Dan Feng Key Laboratory of Information Storage System Wuhan National Laboratory for Optoelectronics) Engineering Research Center of data storage systems and Technology School of Computer Science and Technology) Ministry of Education of China Huazhong University of Science and Technology Wuhan Hubei China Department of Computer Science and Engineering University of Texas at Arlington Arlington Texas USA

In large-scale information systems, storage device performance continues to improve while workloads expand in size and access characteristics. This growth puts tremendous pressure on caches and storage hierarchy in terms of concurrent throughput. However, existing cache eviction policies often struggle to provide adequate concurrent throughput due to their reliance on coarse-grained locking mechanisms and complex data structures. This paper presents a practical approach to cache eviction algorithm design, called Mobius, that optimizes the concurrent throughput of caches and reduces cache operation latency by utilizing lock-free data structures, while maintaining comparable hit ratios. Mobius includes two key designs. First, Mobius employs two lock-free FIFO queues to manage cache items, ensuring that all cache operations are executed efficiently in parallel. Second, Mobius integrates a consecutive detection mechanism that merges multiple modifications during eviction into a single operation, thereby reducing data races. Extensive evaluations using both synthetic and real-world workloads from high-concurrency clusters demonstrate that Mobius achieves a concurrent-throughput improvement ranging from 1.2× to 8.5× over state-of-the-art methods, while also maintaining lower latency and comparable cache hit ratios. The implementation of Mobius in CacheLib and RocksDB highlights its effectiveness in enhancing cache performance in practical scenarios.

关键词： cache eviction policy concurrency fifo queue lock-free throughput

来源：评论

学校读者我要写书评

暂无评论

A Decentralized Threshold Credential Management with Fine-Grained Authentication for VANETs

引用

IEEE Transactions on Information Forensics and Security 2025年 20卷 5818-5831页

作者： Zhang, Jing Wang, Xin Cui, Jie Li, Ru Zhong, Hong Anhui University School of Computer Science and Technology Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Hefei 230039 China Anhui University Anhui Engineering Laboratory of IoT Security Technologies Hefei 230039 China Anhui University School of Computer Science and Technology Hefei 230039 China

In Vehicular Ad-hoc Networks (VANETs), vehicles must authenticate their identities before accessing services. However, existing authentication schemes based on anonymous credentials still face single-point failure in multi-authority scenarios. In addition, in traditional anonymous credential schemes, the public key of credential authority is used directly to verify the credential, which may increase the risk of vehicle privacy being misused. To address these issues, we propose a decentralized threshold credential management system with fine-grained authentication for VANETs. The decentralized credential management architecture is proposed for VANETs with multiple credential authorities, each credential authority consists of multiple credential managers who issue credentials using the threshold mechanism, effectively solving the single-point failure. Based on this architecture, we design a fine grained, privacy-preserving authentication scheme that allows vehicles to autonomously perform selective attribute disclosure, credential aggregation, and randomization before requesting verification from the Cloud Service Provider, thereby achieving a balance between privacy preservation and authentication efficiency. The security proofs and analysis show that our scheme satisfies the target security properties. Performance evaluations indicate that our scheme enables efficient, flexible credential management and authentication in VANETs while ensuring privacy preservation. © 2005-2012 IEEE.

关键词： anonymous credentials authentication decentralization privacy preservation VANETs

来源：评论

学校读者我要写书评

暂无评论

Pricing Policy for a Dynamic Spectrum Allocation Scheme with Batch Requests and Impatient Packets in Cognitive Radio Networks

引用

Journal of systems science and systems Engineering 2022年第2期31卷 133-149页

作者： Haixing Wu Shunfu Jin Wuyi Yue School of Information Science and Engineering Yanshan UniversityQinhuangdao 066004China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan UniversityQinhuangdao 066004China Department of Intelligence and Informatics Konan UniversityKobe 658-8501Japan

In cognitive radio networks(CRNs),multiple secondary users may send out requests simultaneously and one secondary user may send out multiple requests at one time,i.e.,request arrivals usually show an aggregate ***,a secondary user packet waiting in the buffer may leave the system due to impatience before it is transmitted,and this impatient behavior inevitably has an impact on the system *** to investigate the influence of the aggregate behavior of requests and the likelihood of impatience on a dynamic spectrum allocation scheme in CRNs,in this paper a batch arrival queueing model with possible reneging and potential transmission interruption is *** constructing a Markov chain and presenting a transition rate matrix,the steady-state distribution of the queueing model along with a dynamic spectrum allocation scheme is derived to analyze the stochastic behavior of the ***,some important performance measures such as the loss rate,the balk rate and the average delay of secondary user packets are ***,system experiments are carried out to show the change trends of the performance measures with respect to batch arrival rates of secondary user packets for different impatience parameters,different batch sizes of secondary user packets,and different arrival rates of primary user ***,a pricing policy for secondary users is presented and the dynamic spectrum allocation scheme is socially optimized.

关键词： Cognitive radio networks dynamic spectrum scheme batch arrival impatient packets Markov chain social optimization

来源：评论

学校读者我要写书评

暂无评论

Bilinear Graph Neural Network-Enhanced Web services Classification 23

Bilinear Graph Neural Network-Enhanced Web Services Classifi...

引用

23rd IEEE International Conference on High Performance computing and Communications, 7th IEEE International Conference on Data science and systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Zhang, Lulu Cao, Buqing Peng, Mi Qing, Yueying Kang, Guosheng Liu, Jianxun Fletcher, Kenneth K. School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory of Service Computing and New Software Service Technology Xiangtan China University of Massachusetts Boston Department of Computer Science Boston United States

ISBN: (纸本)9781665494571

With the growing number of Web services, classifying Web services accurately and efficiently has become a challenging problem. Effective service classification is conducive to improving the quality of service discovery and the efficiency of service composition. Existing graph neural network methods represent the target service node by a weighted sum of the features of the neighbor service nodes, and have achieved remarkable results in service classification. However, these methods ignore the impact of possible interactions between neighbor service nodes on the target service node. To address this problem, we propose a Web services classification method based on bilinear graph neural network. Our proposed method can model the bilinear interactions between neighbor service nodes and effectively improve the accuracy of service classification. First, our proposed model uses the Word2Vec model to extract the latent semantic vectors from service description documents. We then construct the service relationship network according to tags and shared annotation relationships of Web services. Next, a bilinear aggregator is used to model the pairwise interactions between neighbor service nodes, highlighting the local common attributes. Finally, the bilinear aggregator is combined with the weighted sum aggregator to construct a bilinear graph neural network, which can learn more comprehensive representations of services. The experimental results on the real dataset from ProgrammableWeb show that the classification accuracy of the proposed method is greatly improved compared with DeepWalk, Node2Vec, GCN, and GAT. © 2021 IEEE.

关键词： Smart cities Annotations Mashups Semantics Quality of service Feature extraction Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

AMSC: Adaptive Multi-channel Graph Convolutional Network-Enhanced Web services Classification 23

AMSC: Adaptive Multi-channel Graph Convolutional Network-Enh...

引用

作者： Qing, Yueying Cao, Buqing Peng, Mi Zhang, Lulu Kang, Guosheng Liu, Jianxun Fletcher, Kenneth K. School of Computer Science and Engineering Hunan University of Science and Technology Hunan Key Laboratory of Service Computing and New Software Service Technology Xiangtan China University of Massachusetts Boston Department of Computer Science Boston United States

ISBN: (纸本)9781665494571

With the development of Service Oriented Architecture (SOA), the number of Web services on the Internet is also growing rapidly. Classifying Web services accurately and efficiently is helpful to improve the quality of services discovery and promote the efficiency of service composition. However, existing deep learning-based Web services classification methods, such as graph convolutional networks (GCNs), are incapable of adaptively learning the correlation between service topology structure and service node features concurrently, resulting in unsatisfactory classification performance. To address this problem, this paper proposes an adaptive multi-channel GCN-enhanced Web services classification method. In this method, we first extract specific and shared embedding, in the Web API node isomorphic network, from the node features, topology, and combination of Web service nodes. Then, an attention mechanism is used to learn the importance weight of each embedding. By doing this, we adaptively integrate these weights to ensure the consistency and difference of each learned embedding. Finally, experimental results on real datasets from Programmable Web show that compared with LINE, Node2vec, Deep-walk, GCN, and GAT, the method proposed in this paper has an average improvement in accuracy of 19.81%, 19.35%, 19.16%, 11.56%, and 7.75% respectively. © 2021 IEEE.

关键词： Correlation Adaptive systems Network topology Smart cities Quality of service Feature extraction Topology

来源：评论

学校读者我要写书评

暂无评论

Question-Answer Cross Language Image Matching for Weakly Supervised Semantic Segmentation

arXiv

引用

arXiv 2024年

作者： Deng, Songhe Zhuo, Wei Xie, Jinheng Shen, Linlin Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China

Class Activation Map (CAM) has emerged as a popular tool for weakly supervised semantic segmentation (WSSS), allowing the localization of object regions in an image using only image-level labels. However, existing CAM methods suffer from under-activation of target object regions and false-activation of background regions due to the fact that a lack of detailed supervision can hinder the model’s ability to understand the image as a whole. In this paper, we propose a novel Question-Answer Cross-Language-Image Matching framework for WSSS (QA-CLIMS), leveraging the vision-language foundation model to maximize the text-based understanding of images and guide the generation of activation maps. First, a series of carefully designed questions are posed to the VQA (Visual Question Answering) model with Question-Answer Prompt Engineering (QAPE) to generate a corpus of both foreground target objects and backgrounds that are adaptive to query images. We then employ contrastive learning in a Region Image Text Contrastive (RITC) network to compare the obtained foreground and background regions with the generated corpus. Our approach exploits the rich textual information from the open vocabulary as additional supervision, enabling the model to generate high-quality CAMs with a more complete object region and reduce false-activation of background regions. We conduct extensive analysis to validate the proposed method and show that our approach performs state-of-the-art on both PASCAL VOC 2012 and MS COCO datasets. Code is available at: https://***/CVI-SZU/QA-CLIMS Copyright © 2024, The Authors. All rights reserved.

关键词： Chemical activation

来源：评论

学校读者我要写书评

暂无评论

Edge-Driven Industrial computing Power Networks: Digital Twin-Empowered Service Provisioning by Hybrid Soft Actor-Critic

引用

IEEE Transactions on Vehicular technology 2025年第5期74卷 8095-8109页

作者： Zhang, Long Song, Deng-Ao Zhang, Hongliang Tian, Ni Zhuang, Zirui Niyato, Dusit Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Nanyang Technological University College of Computing and Data Science 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

With the proliferation of data-intensive industrial applications, the collaboration of computing powers among standalone edge servers is vital to provision such services for smart devices. In this paper, we propose an edge-driven industrial computing power network (CPN) by orchestrating the computing and network resources of edge servers through the centralized resource scheduling and decentralized task computing. However, efficient task offloading and collaborative processing is challenging, which requires higher degrees of network automation and intelligence. Therefore, we incorporate digital twins (DTs) into the edge-driven CPN architecture, where the DTs are created as the digital replicas to assist both the computation offloading and collaborative processing. A joint optimization problem of the computing power assignment, service association, task partition, and transmit power control is formulated for maximizing the system average weighted utility. Due to the temporal-spatial variability of tasks and the resulted dynamic environment, we transform the original problem as a Markov decision process aiming at maximizing the long-term average weighted utility. To efficiently handle the high-dimensional discrete-continuous action space, a hybrid soft actor-critic based deep reinforcement learning algorithm is developed for optimizing the joint design. Simulation results validate the superiority of our proposed algorithm over the benchmarks, showing the significant gains obtained by integrating DTs into the edge-driven CPN. © 1967-2012 IEEE.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

The Role of Blockchain Integration in Edge computing for 6G IoT: Challenges and Applications 7

The Role of Blockchain Integration in Edge Computing for 6G ...

引用

7th International Conference on Internet Applications, Protocols, and services, NETAPPS 2024

作者： Alawadhi, Abdulwadood Almogahed, Abdullah Shtayt, Bushra Abdullah Barraood, Samera Obaid Adawy, Mohammad Ibrahim Al-Jamili, Omar InterNetWorks Research Laboratory School of Computing Universiti Utara Malaysia Kedah Sintok Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor Parit Raja Malaysia Information Technologies Management Management Technical College of Basra Southern Technical University Basra Iraq Department of Computer Science College of Computers and Information Technology Hadhramout University Hadhramout Yemen Faculty of Information Technology The World Islamic Sciences and Education University Amman Jordan School of Computing Universiti Utara Malaysia Kedah Sintok Malaysia

ISBN: (纸本)9798331519513

Blockchain is the technology on which cryptocurrencies operate within the 6G Internet of Things. Due to its flexibility, it has received significant adoption in numerous applications as a possible distributed data management solution. Nonetheless, a significant obstacle that impedes blockchain's potential is its constrained scalability, which limits its capacity to facilitate applications requiring frequent transactions. Conversely, edge computing, an innovative technology, addresses the limitations of conventional cloud-based systems by decentralizing cloud functionalities and alleviating problems such as elevated latency and insufficient security. Nonetheless, edge computing presently encounters challenges related to decentralized governance and security. As a result, the integration of blockchain and edge computing within a cohesive framework offers substantial benefits, such as dependable network access and governance, decentralized storage, and computing at the peripheries. This integration effectively mitigates many security problems and guarantees data integrity in edge computing contexts. This article offers a comprehensive analysis of blockchain technology, its attributes, and its relevance in the context of 6G. Additionally, it investigates the amalgamation of blockchain and edge computing, analyzes diverse application cases, and addresses the related issues. Finally, the report delineates contemporary research trajectories and draws conclusions based on the findings. © 2024 IEEE.

关键词： Mobile edge computing

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：