检索结果-内蒙古大学图书馆

24th IEEE International Conference on Data Mining, ICDM 2024

作者： Zhao, Jinbiao Zhang, Zhao Ren, Jiahuan Zhang, Haijun Zhao, Zhongqiu Wang, Meng School of Computer Science and Information Engineering Hefei University of Technology Hefei China Yunnan Key Laboratory of Software Engineering Yunan China Harbin Institute of Technology Department of Computer Science Shenzhen China

ISBN: (纸本)9798331506681

Performing an object detection task after the restoration of a hazy image, or rather detecting with the network backbone directly, will result in the inclusion of information mixed with dehazing, which tends to interfere with detection performance. To address these issues, we propose a novel framework for detecting objects in dehazed images via Dual Cross-Stage Partial Learning (DCSP). Specifically, we introduce a Cross-Stage Partial (CSP) module for extracting clean feature information after dehazing. Secondly, to enhance data integrity, we employ a skip-input strategy to supplement information related to object detection features that may be lost during the dehazing task, while avoiding the gradient vanishing problem. In addition, CSP is also introduced to facilitate comprehensive learning of multiple feature representations. Finally, to avoid the inclusion of irrelevant dehazing information in detection, we apply a Ground-Truth Flow at detection network (at dark3), for fine feature information calibration. Additionally, we created a synthetic fog dataset to expand the training data for DCSP. Experimental results on both synthetic and real-world datasets demonstrate the effectiveness and accuracy of the proposed method. The code is available at https://***/zhaojinbiao/DCSP. © 2024 IEEE.

关键词： Demulsification

来源：评论

学校读者我要写书评

暂无评论

ICCG:low-cost and efficient consistency with adaptive synchronization for metadata replication

引用

Frontiers of Computer Science 2025年第1期19卷 53-70页

作者： Chenhao ZHANG Liang WANG Jing SHANG Zhiwen XIAO Limin XIAO Meng HAN Bing WEI Runnan SHEN Jinquan WANG State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China School of Cyberspace Security Hainan UniversityHaikou 570228China China Mobile Information Technology Center Beijing 100033China

The rapid growth in the storage scale of wide-area distributed file systems (DFS) calls for fast and scalable metadata management. Metadata replication is the widely used technique for improving the performance and scalability of metadata management. Because of the POSIX requirement of file systems, many existing metadata management techniques utilize a costly design for the sake of metadata consistency, leading to unacceptable performance overhead. We propose a new metadata consistency maintenance method (ICCG), which includes an incremental consistency guaranteed directory tree synchronization (ICGDT) and a causal consistency guaranteed replica index synchronization (CCGRI), to ensure system performance without sacrificing metadata consistency. ICGDT uses a flexible consistency scheme based on the state of files and directories maintained through the conflict state tree to provide an incremental consistency for metadata, which satisfies both metadata consistency and performance requirements. CCGRI ensures low latency and consistent access to data by establishing a causal consistency for replica indexes through multi-version extent trees and logical time. Experimental results demonstrate the effectiveness of our methods. Compared with the strong consistency policies widely used in modern DFSes, our methods significantly improve the system performance. For example, in file creation, ICCG can improve the performance of directory tree operations by at least 36.4 times.

关键词： metadata management metadata replication consistency directory tree replica index

来源：评论

学校读者我要写书评

暂无评论

A dynamic and resource sharing virtual network mapping algorithm

引用

Digital Communications and Networks 2023年第5期9卷 1101-1112页

作者： Xiancui Xiao Xiangwei Zheng Ji Bian Cun Ji Xinchun Cui School of Information Science and Engineering Shandong Normal UniversityJinan250014China School of Information Engineering Shandong Management UniversityJinan250358China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan250014China School of Computer Science and Technology Qufu Normal UniversityRizhao276800China

Network virtualization can effectively establish dedicated virtual networks to implement various network ***,the existing research works have some shortcomings,for example,although computing resource properties of individual nodes are considered,node storage properties and the network topology properties are usually ignored in Virtual Network(VN)modelling,which leads to the inaccurate measurement of node availability and *** addition,most static virtual network mapping methods allocate fixed resources to users during the entire life cycle,and the users’actual resource requirements vary with the workload,which results in resource allocation *** on the above analysis,in this paper,we propose a dynamic resource sharing virtual network mapping algorithm named NMA-PRS-VNE,first,we construct a new,more realistic network framework in which the properties of nodes include computing resources,storage resources and topology *** the node mapping process,three properties of the node are used to measure its mapping ***,we consider the resources of adjacent nodes and links instead of the traditional method of measuring the availability and priority of nodes by considering only the resource properties,so as to more accurately select the physical mapping nodes that meet the constraints and conditions and improve the success rate of subsequent link ***,we divide the resource requirements of Virtual Network Requests(VNRs)into basic subrequirements and variable sub-variable requirements to complete dynamic resource *** former represents monopolizing resource requirements by the VNRs,while the latter represents shared resources by many VNRs with the probability of occupying resources,where we keep a balance between resource sharing and collision among users by calculating the collision *** results show that the proposed NMAPRS-VNE can increase the average acceptance rate and network revenu

关键词： Network virtualization VNRs Network frameworks Dynamic resource allocation Resource sharing

来源：评论

学校读者我要写书评

暂无评论

PAIR: Protein-aptamer interaction prediction based on language models and contrastive learning framework

PAIR: Protein-aptamer interaction prediction based on langua...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhang, Jun Yan, Zhiqiang Zeng, Hao Zhu, Zexuan Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Shenzhen University College of Computer Science and Software Engineering Shenzhen China

ISBN: (纸本)9798350386226

Aptamers are single-stranded DNA or RNA oligonucleotides that selectively bind to specific targets, making them valuable for drug design and diagnostic applications. Identifying the interactions between aptamers and target proteins is crucial for these applications. The systematic evolution of ligands by exponential enrichment process, traditionally used for this purpose, is challenging and time-consuming. The resulting aptamers often suffer from limitations in stability and diversity. Computational approaches have shown promise in aiding the discovery of high-performance aptamers, but existing methods are usually constrained by insufficient training data and limited generalizability. Recently, advancements in pre-training large language models have offered a new avenue to mitigate the dependency on large datasets. In this study, we propose a novel method to predict aptamer-protein interactions using large language models within a contrastive learning framework. Experimental results demonstrate that our method exhibits superior generalization and outperforms existing approaches. This method holds promise as a powerful tool for predicting aptamer-protein interactions. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

AF-SSD: Self-attention Fusion Sampling and Fuzzy Classification for Enhanced Small Object Detection 21st

AF-SSD: Self-attention Fusion Sampling and Fuzzy Classifica...

引用

21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Xiao, He Jiang, Qingping Guo, Songhao Yang, Jiahui Liu, Qiuming School of Software Engineering Jiangxi University of Science and Technology Nanchang China Nanchang Key laboratory of Virtual Digital Factory and Cultural Communications Nanchang China

ISBN: (纸本)9789819601219

Raw point clouds are extensively used in 3D object detection due to their detailed spatial positioning information, which surpasses that of voxelized point clouds. However, point-based 3D object detection networks often prioritize local information over the scene’s overall context when selecting sampling locations, mainly focusing on the cloud’s spatial distribution. This is particularly problematic for small objects like cyclists and pedestrians, where point cloud data are naturally sparse, negatively impacting the accuracy of regression and classification. To tackle these challenges, we introduce a novel single-stage 3D detection algorithm named AF-SSD. Our approach begins with a sampling module driven by a self-attention mechanism that merges spatial and feature distances, facilitating a comprehensive understanding of the point cloud’s global information while retaining more points of foreground objects. Additionally, we apply fuzzy classification theory in the bounding box regression of the detection head to refine the Non-Maximum Suppression (NMS), further mitigating missed detections due to the spatial clustering of multiple small objects. Our experiments on the KITTI dataset demonstrate that our algorithm achieves competitive regression precision and performance for pedestrian detection, in line with current state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Accelerated Peridynamic Computation on GPU for Quasi-static Fracture Simulations

引用

Journal of Peridynamics and Nonlocal Modeling 2024年第1期6卷 206-229页

作者： Zhong, Jiandong Han, Fei Zhang, Ling Department of Engineering Mechanics Dalian University of Technology Dalian 116023 China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Dalian University of Technology Dalian 116023 China

Due to the adoption of integral equations instead of partial differential equations to describe the deformations of materials, the peridynamics has advantages in dealing with fracture problems. However, the non-local effect of peridynamics brings too much computation cost to make large-scale engineering applications challenging. In this paper, a parallel algorithm in the Compute Unified Device Architecture (CUDA) framework is presented to speed up the computational process of a peridynamic model for quasistatic fracture simulations on GPU, in which the peridynamic model is numerically implemented by the peridynamics-based finite element method (PeriFEM) [1]. The parallel algorithm makes crack simulations by the pure peridynamics with millions of degrees of freedom possible with one GPU. To validate the accuracy and efficiency of the parallel algorithm based on PeriFEM, several numerical benchmarks are performed, and the results are compared with those obtained by the finite element method (FEM) and the serial algorithm. The results of the comparison show that the presented parallel algorithm is effective and efficient. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Crack simulation CUDA Finite element method Parallel computing Peridynamic

来源：评论

学校读者我要写书评

暂无评论

Diversifying Message Aggregation in Multi-Agent Communication Via Normalized Tensor Nuclear Norm Regularization 48

Diversifying Message Aggregation in Multi-Agent Communicatio...

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Zhai, Yuanzhao Xu, Kele Ding, Bo Feng, Dawei Gao, Zijian Wang, Huaimin National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

ISBN: (纸本)9781728163277

The use of graph attention networks (GAT) in communication-enhanced multi-agent reinforcement learning (Comm-MARL) has become prevalent. While successful, GAT can lead to homogeneity in the strategies of message aggregation, which can severely limit multi-agent coordination. To address this challenge, we study the adjacency tensor of the communication graph. Then we define a new nuclear tensor rank and its convex surrogate, the normalized tensor nuclear norm to measure the homogeneity of message aggregation. Leveraging the norm, we further propose a plug-and-play regularizer on the adjacency tensor, named Normalized Tensor Nuclear Norm Regularization (NTNNR), to actively enrich the diversity of message aggregation during the training stage. NTNNR is agnostic to specific Comm-MARL algorithms and can be flexibly integrated with different graph-attention methods. Empirical results demonstrate that aggregating messages using NTNNR-enhanced GAT can improve the efficiency of the training and achieve higher asymptotic performance than existing message aggregation methods. © 2023 IEEE.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

Complementary Learning System Based Intrinsic Reward in Reinforcement Learning 48

Complementary Learning System Based Intrinsic Reward in Rein...

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Gao, Zijian Xu, Kele Jia, Hongda Wan, Tianjiao Ding, Bo Feng, Dawei Mao, Xinjun Wang, Huaimin National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

ISBN: (纸本)9781728163277

Deep reinforcement learning has achieved encouraging performance in many realms. However, one of its primary challenges is the sparsity of extrinsic rewards, which is still far from solved. Complementary learning system theory suggests that effective human learning relies on two complementary learning systems utilizing short-term and long-term memories. Inspired by the fact that humans evaluate curiosity by comparing current observations with historical information, we propose a novel intrinsic reward, namely CLS-IR, which aims to address the problems caused by sparse extrinsic rewards. Specifically, we train a self-supervised predictive model with short-term and long-term memories via exponential moving averages. We employ the information gain between the two memories as the intrinsic reward, which does not incur additional training costs but leads to better exploration. To investigate the effectiveness of CLS-IR, we conduct extensive experimental evaluations;the results demonstrate that CLS-IR can achieve state-of-the-art performance on Atari games and DeepMind Control Suite. © 2023 IEEE.

关键词： complementary learning system Deep reinforcement learning exploration intrinsic reward

来源：评论

学校读者我要写书评

暂无评论

VulLoc:vulnerability localization based on inducing commits and fixing commits

引用

Frontiers of Computer Science 2023年第3期17卷 243-245页

作者： Lili BO Yue LI Xiaobing SUN Xiaoxue WU Bin LI School of Information Engineering Yangzhou UniversityYangzhou 225127China Key Laboratory of Safety-Critical Software Ministry of Industry and Information TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China

1 Introduction software evolves with the code change,including fixing the vulnerabilities,refactoring the software and adding new ***,developers from open-source projects often look for the information of inducing commits when devising the fixing patches of a vulnerability[1].In the process of fixing the current vulnerabilities,it is inevitable to introduce new *** is shown in Fig.1,after vulnerability1 occurs,developers committed the code changes to fix vulnerability1,but cause *** this paper,commits that introduce new vulnerabilities are called vulnerability-inducing commits,and commits that finally fix the vulnerability are known as vulnerability-fixing *** the following,they are abbreviated as vul-inducing commits and vul-fixing commits,respectively.

关键词： functions commit finally

来源：评论

学校读者我要写书评

暂无评论

Progressive Diversifying Policy for Multi-Agent Reinforcement Learning 48

Progressive Diversifying Policy for Multi-Agent Reinforcemen...

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Sun, Shaoqi Zhai, Yuanzhao Xu, Kele Feng, Dawei Ding, Bo National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

ISBN: (纸本)9781728163277

Multi-Agent Reinforcement Learning (MARL) has recently achieved promising performance in many collaborative decision making tasks. However, one of the main bottleneck challenges for MARL is the sparsity of the team reward, which can lead to the homogenization of agents' behaviors. To address these issues, we propose a Progressive Diversifying Policy (PDP) algorithm in this paper. Specifically, we propose to actively amplify the diversity between agents' policies during learning and exploit diversity as an additional intrinsic reward for MARL. Furthermore, we propose a progressive diversity boosting policy to find a better team policy. Leveraging the aforementioned improvements, our method can handle sparse team rewards and alleviate the homogeneous behaviors of agents. We conduct experiments on widely-used MARL environments and the results show that PDP can provide state-of-the-art performance while maintaining a competitive convergence speed. © 2023 IEEE.

关键词： Homogeneous behavior Multi-agent reinforcement learning Policy diversity Sparse reward

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：