检索结果-内蒙古大学图书馆

20th European Conference on Computer systems, EuroSys 2025, co-located 30th ACM International Conference on Architectural Support for Programming Languages and Operating systems, ASPLOS 2025

作者： He, Haiheng Liu, Haifeng Zheng, Long Huang, Yu Shen, Xinyang Huang, Wenkan Cao, Chuaihu Liao, Xiaofei Jin, Hai Xue, Jingling 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 Technology Huazhong University of Science and Technology Wuhan China School of Computer Science and Engineering University of New South Wales Australia

ISBN: (纸本)9798400711961

Heterogeneous Graph Neural Networks (HGNNs) are pivotal for extracting semantic and structural information from heterogeneous graphs. Traditional HGNN implementations often grapple with the challenges of excessive metapath instances, requiring substantial storage or incurring high instance-matching overhead. These methods typically suffer from redundant instance encoding and costly semantic graph construction. Addressing these issues, we introduce an advanced Metapath Graph (MG) abstraction that encapsulates the structural information of all metapath instances within a compact representation. This approach significantly reduces storage demands, eliminates redundant instance encodings, and foregoes the need for constructing semantic graphs, thereby facilitating rapid HGNN inference. Our software-based system, MetaHG, leverages layerwise encoding and aggregation to avoid redundancies without the necessity of semantic graphs. It incorporates a fast, lightweight partitioning method to efficiently manage large graphs. Distinctively, MetaHG seamlessly integrates with both dynamic HGNNs and homogeneous GNNs, unlike conventional systems. Comparative evaluations demonstrate that MetaHG surpasses the state-of-the-art BFS- and DFS-based HGNN systems, MAGNN and the software implementation of MetaNMP, by 42.5× and 4.53×, respectively, on average. © 2025 Copyright held by the owner/author(s).

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

AdaptHM: A Fully Adaptive data Migration Strategy for Hybrid Memory systems

引用

IEEE Transactions on Computer-Aided Design of Integrated Circuits and systems 2025年第3期44卷 923-936页

作者： Peng, Zhouxuan Feng, Dan Chen, Jianxi Hu, Jing Liu, Yachun Hu, Jinlei Zhang, Jintong Wan, Tianyu Chen, Zuoning Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology MoE of China Wuhan430074 China Chinese Academy of Engineering Beijing100088 China

data migration strategies (DMSs) improve the overall performance of hybrid memory systems by migrating frequently accessed (hot) data to faster memory. However, designing an efficient DMS is challenging since the key metrics of DMS - hot data selection, migration granularity, and migration frequency - are sensitive to access patterns of workloads. Most existing strategies focus on only one of these metrics and often overlook the crucial impact of access patterns, resulting in suboptimal performance and unnecessary migration traffic. In this article, we propose AdaptHM, a fully access-pattern-aware Adaptive DMS for Hybrid Memory systems. AdaptHM achieves adaptability on all three metrics through its unique multilevel data framework. First, AdaptHM adopts a group-level competition policy to select hot blocks, which responds faster to access patterns than threshold-based policies. Second, AdaptHM enables segment-level dynamic migration granularity by decoupling migration from remapping, which shows better-access pattern resilience than existing schemes with fixed-size global migration granularity. Third, AdaptHM adjusts the migration frequency at set-level by periodically assessing the migration benefit, avoiding unnecessary migrations. Experimental results demonstrate that AdaptHM improves the performance by an average of 12.78% and reduces energy consumption by up to 37.24% compared to the state-of-the-art scheme. © 1982-2012 IEEE.

关键词： Frequency modulation

来源：评论

学校读者我要写书评

暂无评论

Spatiotemporal deformation analysis of glaciers and surrounding landscapes in the Shishapangma region using InSAR techniques

引用

Journal of Mountain Science 2025年第1期22卷 210-229页

作者： LIANG Wenli LIU Rui JI Qin KOU Pinglang Chongqing Key Laboratory of GIS Application School of Geography and TourismChongqing Normal UniversityChongqing 401331China National Earth System Science Data Center Beijing 100000China Chongqing Engineering Research Center of Spatial Big Data Intelligent Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Tourism Multisource Data Perception and Decision Ministry of Culture and Tourism(TMDPDMCT)Chongqing University of Posts and TelecommunicationsChongqing 400065China

Glacier dynamics in the Himalayan midlatitudes,particularly in regions like the Shishapangma,are not yet fully understood,especially the localized topographic and climatic impacts on glacier *** study analyzes the spatiotemporal characteristics of glacier surface deformation in the Shishapangma region using the Small Baseline Subset(SBAS)Interferometric Synthetic Aperture Radar(In SAR)*** analysis reveals an average deformation rate of-4.02±17.65 mm/yr across the entire study area,with glacier regions exhibiting significantly higher rates of uplift(16.87±13.20 mm/yr)and subsidence(20.11±14.55 mm/yr)compared to non-glacier *** identifies significant surface lowering on the mountain flanks and localized uplift in certain catchments,emphasizing the higher deformation rates in glacial areas compared to non-glacial *** found a strong positive correlation between temperature and cumulative deformation(correlation coefficient of 0.63),particularly in glacier areas(0.82).The research highlights the role of temperature as the primary driver of glacier wastage,particularly at lower elevations,with strong correlations found between temperature and cumulative *** also indicates the complex interactions between topographic features,notably,slope gradient,which shows a positive correlation with subsidence rates,especially for slopes below 35°.South-,southwest-,and west-facing slopes exhibit significant uplift,while north-,northeast-,and east-facing slopes predominantly ***,we identified transition zones between debris-covered glaciers and clean ice as areas of most intense deformation,with average rates exceeding 30 mm/yr,highlighting these as potential high-risk zones for *** study comprehensively analyzes the deformation characteristics in both glacier and non-glacier areas in the Shishapangma region,revealing the complex interplay of topographic,climatic,and hydrological factors influencing glacier dynamic

关键词： Glacier melting SBAS-InSAR Topographic factors Temperature change Middle Himalayas

来源：评论

学校读者我要写书评

暂无评论

Seer: Accelerating Block chain Transaction Execution by Fine-Grained Branch Prediction 51st

Seer: Accelerating Block chain Transaction Execution by Fine...

引用

51st International Conference on Very Large data Bases, VLDB 2025

作者： Zhang, Shijie Cheng, Ru Liu, Xinpeng Xiao, Jiang Jin, Hai Li, Bo 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 Technology Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong

Increasingly popular decentralized applications (dApps) with complex application logic incur significant overhead for executing smart contract transactions, which greatly limits public block chain performance. Pre-executing transactions off the critical path can mitigate substantial I/O and computation costs during execution. However, pre-execution does not yield any state transitions, rendering the system state inconsistent with actual execution. This inconsistency can lead to deviations in pre-execution paths when processing smart contracts with multiple state-related branches, thus diminishing pre-execution effectiveness. In this paper, we develop Seer, a novel public block chain execution engine that incorporates fine-grained branch prediction to fully exploit pre-execution effectiveness. Seerpredicts state-related branches using a two-level prediction approach, reducing inconsistent execution paths more efficiently than executing all possible branches. To enable effective reuse of pre execution results, Seer employs checkpoint-based fast-path execution, enhancing transaction execution for both successful and unsuccessful predictions. Evaluations with realistic block chain workloads demonstrate that Seer delivers an average of 27.7× transaction-level speedup and an overall 20.6× speedup in the execution phase over vanilla Ethereum, outperforming existing block chain execution acceleration solutions. © 2025, VLDB Endowment, All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Efficient Modeling Attack on Multiplexer PUFs via Kronecker Matrix Multiplication

引用

IEEE Transactions on Computer-Aided Design of Integrated Circuits and systems 2025年

作者： Wang, Hongfei Wan, Caixue Jin, Hai 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 Cyber Science and Engineering Wuhan430074 China Huazhong University of Science and Technology 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 Technology Wuhan430074 China

The Physical Unclonable Function (PUF) is valued for its lightweight nature and unique functionality, making it a common choice for securing hardware products requiring authentication and key generation mechanisms. In response to the susceptibility of individual PUFs to modeling attacks, advanced PUF variants have been developed to improve security measures. One notable type in this regard is the multiplexer-based composition of arbiter PUFs, known as MPUF, which aims to meet high reliability and security standards simultaneously. Current research on attacking MPUF encounters challenges such as substantial demands for training CRPs and low success rates. In this work, we propose a novel numerical modeling attack strategy for MPUFs. Using Kronecker products from mathematical perspective, this method precisely describe the MPUF model without using complex network architectures, boosting attack accuracy and overall efficiency. Experiment comparison with state-of-the-art works demonstrates that our method achieves better performance in terms of attack accuracy, robustness, and efficiency. Our method is able to successfully attack a (512, 8)-MPUF in 32.71 minutes with 97.14% accuracy, outperforming all existing attack methods on MPUFs. More, we validate our method through experiments with hardware implementations on FPGAs. The advantages of our method also include the adaptability to be employed to attack other MPUF variations like cMPUF and rMPUF, and the capability to be integrated with an existing attack method for launching efficient attack on MPUFs leveraging reliability information. © 2025 IEEE.

关键词： modeling attack multiplexer-based PUF Physical unclonable function

来源：评论

学校读者我要写书评

暂无评论

Area Coverage Reliability Evaluation for Collaborative Intelligence and Meta-Computing of Decentralized Industrial Internet of Things

引用

IEEE Internet of Things Journal 2025年第10期12卷 13734-13745页

作者： Zhu, Chenlu Fan, Xiaoxuan Deng, Xianjun Liu, Shenghao Yin, Duan Gao, Hanjun Yang, Laurence T. Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China China Mobile Communications Group Terminal Co Beijing China CNNC Wuhan Nuclear Power Operation Technology Co Wuhan China

Industrial Internet of Things (IIoT) is evolving towards decentralization and autonomous operation. Nodes in decentralized IIoT collaboratively sense data and communicate to participate in meta-computing and provide diverse intelligent services. Area coverage reliability evaluates the information collaborative intelligence sensing and communication capabilities of nodes in decentralized IIoT for a target area. It serves as a crucial performance evaluation metric for the meta-computing and intelligent services of decentralized IIoT. Existing area coverage reliability evaluation algorithms do not consider the dynamic node states in decentralized IIoT, and overlook the capability of nodes to collaborate in meta-computing. To address these issues, this paper proposes a novel Confident Information Coverage (CIC)-based area coverage reliability metric (CACREL), which comprehensively considers node multistate, node collaboration, network coverage rate, and network connectivity. To effectively evaluate CACREL, a CIC-based coverage reliability evaluation algorithm (CACR) is proposed. Specifically, CACR transforms complex networks into grid networks and utilizes a Coverage Table (CT) to describe different coverage states of each grid, which reduces the complexity of the area coverage reliability evaluation. Additionally, CACR employs a reliable path algorithm to converge the CT of each grid to the sink node based on grid connectivity. Simulation results demonstrate that the proposed CACR can accurately evaluate the area coverage reliability of decentralized IIoT and enhance its service performance. © 2014 IEEE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

OHMiner: An Overlap-centric system for Efficient Hypergraph Pattern Mining 25

OHMiner: An Overlap-centric System for Efficient Hypergraph ...

引用

20th European Conference on Computer systems, EuroSys 2025, co-located 30th ACM International Conference on Architectural Support for Programming Languages and Operating systems, ASPLOS 2025

作者： Qi, Hao Luo, Kang He, Ligang Zhang, Yu Cai, Minzhi Dai, Jingxin He, Bingsheng Jin, Hai Zhang, Zhan Zhao, Jin Yue, Hengshan Yu, Hui Liao, Xiaofei 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 Technology Huazhong University of Science and Technology China Department of Computer Science University of Warwick United Kingdom National University of Singapore Singapore Zhejiang Lab China Jilin University China

ISBN: (纸本)9798400711961

Hypergraph Pattern Mining (HPM) aims to identify all the instances of user-interested subhypergraphs (patterns) in hypergraphs, which has been widely used in various applications. However, existing solutions either need significant enumeration overhead because they extend subhypergraphs at the granularity of vertices, or suffer from massive redundant computations because they often need to repeatedly fetch and process the same incident hyperedges for different vertices. This paper presents an overlap-centric system named OHMiner to efficiently support HPM. OHMiner proposes an overlap-centric execution model to determine the subhypergraphs isomorphism through computing and comparing overlaps among hyperedges using set operations. This model aims to efficiently handle the vertices that collectively share the same incident hyperedges. To automatically and precisely retrieve an arbitrary pattern’s overlapping semantics without performing redundant set computations, OHMiner further proposes a redundancy-free compiler, which constructs an Overlap Intersection Graph (OIG) for the pattern, optimizes the OIG, and generates an overlap-centric execution plan to guide the procedure of HPM. Moreover, OHMiner designs an overlap-centric parallel execution engine, which adopts an incremental overlap-pruned approach to fast validate candidates for HPM. Additionally, it proposes a degree-aware data store to support efficient generation of candidates. Through evaluating OHMiner on a broad range of real-world hypergraphs with various patterns, our experimental results show that OHMiner outperforms the state-of-the-art HPM system by 5.4×-22.2×. © 2025 Copyright held by the owner/author(s).

关键词： Compiler

来源：评论

学校读者我要写书评

暂无评论

UARC:Unsupervised Anomalous Traffic Detection with Improved U-Shaped Autoencoder and RetNet Based Multi-clustering 26th

UARC:Unsupervised Anomalous Traffic Detection with Improved ...

引用

26th International Conference on Information and Communications Security, ICICS 2024

作者： Xie, Yunyang Chen, Kai Li, Shenghui Li, Bingqian Zhang, Ning Hubei Key Laboratory of Distributed System Security Hubei Engin eering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University Technology Wuhan430074 China

ISBN: (纸本)9789819787975

With the ongoing advancement of deep learning, modern network intrusion detection systems increasingly favor utilizing deep learning networks to improve their ability to learn traffic characteristics. To address the challenge of obtaining a substantial amount of labeled training data, many intrusion detection systems now focus on unsupervised anomaly detection methods. Despite this shift, researchers still face the daunting task of distinguishing a significant volume of anomalous traffic and dealing with data imbalance. To address these real-world challenges, we introduce UARC, a system capable of achieving unsupervised anomaly traffic detection through multi-clustering. UARC utilizes an enhanced U-shaped autoencoder and a feature fusion method incorporating Masked Retnet to effectively extract spatiotemporal features from network traffic. It combines these techniques with the HDBSCAN algorithm for multi-clustering of traffic, providing a form of reverse guidance for network learning. Experimental results on multiple datasets demonstrate that UARC can cluster various types of traffic with an impressive accuracy rate of up to 97.96%, while achieving a 99.70% AUC value for anomaly detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

FIRE: combining multi-stage filtering with taint analysis for scalable recurring vulnerability detection 24

FIRE: combining multi-stage filtering with taint analysis fo...

引用

Proceedings of the 33rd USENIX Conference on Security Symposium

作者： Siyue Feng Yueming Wu Wenjie Xue Sikui Pan Deqing Zou Yang Liu Hai Jin 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 Cluster and Grid Computing Lab and School of Cyber Science and Engineering Huazhong University of Science and Technology China Nanyang Technological University Singapore 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 Cluster and Grid Computing Lab and School of Cyber Science and Engineering Huazhong University of Science and Technology China and Jinyinhu Laboratory China 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 Cluster and Grid Computing Lab and School of Computer Science and Technology Huazhong University of Science and Technology China

ISBN: (纸本)9781939133441

With the continuous development of software open-sourcing, the reuse of open-source software has led to a significant increase in the occurrence of recurring vulnerabilities. These vulnerabilities often arise through the practice of copying and pasting existing vulnerabilities. Many methods have been proposed for detecting recurring vulnerabilities, but they often struggle to ensure both high efficiency and consideration of semantic information about vulnerabilities and patches. In this paper, we introduce FIRE, a scalable method for large-scale recurring vulnerability detection. It utilizes multi-stage filtering and differential taint paths to achieve precise clone vulnerability scanning at an extensive scale. In our evaluation across ten open-source software projects, FIRE demonstrates a precision of 90.0% in detecting 298 recurring vulnerabilities out of 385 ground truth instance. This surpasses the performance of existing advanced recurring vulnerability detection tools, detecting 31.4% more vulnerabilities than VUDDY and 47.0% more than MOVERY. When detecting vulnerabilities in large-scale software, FIRE outperforms MOVERY by saving about twice the time, enabling the scanning of recurring vulnerabilities on an ultra-large scale.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MLPFormer: MLP-integrated transformer for colorectal histopathology whole slide image segmentation

引用

Neural Computing and Applications 2025年第6期37卷 4651-4661页

作者： Wang, Yuxuan Li, Dan Li, Xuechen Guo, Yan Zuo, Yanfei Shen, Linlin Department of Computer Science Wenzhou-Kean University Wenzhou China School of Electronics and Information Engineering Wuyi University Jiangmen China Department of Histo Pathology Shanghai Histo Pathology Diagnostic Center Shanghai China College of Computer Sicence and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

Colorectal intraepithelial neoplasia is a precancerous lesion of colorectal cancer, which is mainly diagnosed using pathological images. According to the characteristics of lesions, precancerous lesions can be classified into four different grades, i.e., background, normal, low and high level. However, due to the continuity of lesion development, tissue in different stages has high similarity. Recently, visual transformers have achieved impressive results in different visual tasks, due to their capacity of capturing long-range dependencies. However, due to computational cost, transformer cannot well extract detailed feature, which is important for lesion grading. To accurately segment pathological tissues with high similarity, in this work, we embed the multi-head MLP mixer module in the transformer network to extract cell and edge information. Furthermore, we propose a hierarchical MLP decoder to facilitate multi-scale feature fusion. The proposed transformer, namely MLPFormer, achieves remarkable results against competitive baselines on the Histo-CRC Biopsy dataset. The experimental results demonstrate that MLPFormer significantly outperforms the competitive baselines, i.e., a 3% dice improvement is achieved over the SegFormer series. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Image segmentation

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：