检索结果-内蒙古大学图书馆

Domain Adaptation for Label Distribution Learning

IEEE Transactions on Big Data 2025年第3期11卷 1221-1234页

作者： Wu, Haitao Li, Weiwei Jia, Xiuyi Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing210016 China Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China

Label distribution learning (LDL) suffers from the dilemma of insufficient target data in real-world applications, while domain adaptation (DA) seems to be able to provide a solution. However, most existing methods of DA, assuming that the instances can correspond to the explicit class information, are devoted only to classification but not to LDL. We argue that indiscriminately applying such DA methods might cause performance degradation in LDL tasks. In this paper, we propose LDL-DA, a novel algorithm dedicated to supervised domain adaptation for label distribution learning, which jointly learns a shared encoding representation from two aspects: 1) contrastive alignment of scarce supervised target data, and 2) minimizing the distance between prototypes of the same label combination. Experiments show that LDL-DA outperforms existing DA methods adapted to LDL, and provides early positive results in DA for LDL. To the best of our knowledge, this paper is the first research on DA for LDL. © 2015 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

PosParser: A Heuristic Online Log Parsing Method Based on Part-of-Speech Tagging

引用

IEEE Transactions on Big Data 2025年第3期11卷 1334-1345页

作者： Jiang, Jinzhao Fu, Yuanyuan Xu, Jian Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China

Log parsing, the process of transforming raw logs into structured data, is a key step in the complex computer system's intelligent operation and maintenance and therefore has received extensive attention. Among all log parsing methods, heuristic log parsing methods are lightweight and can work in a streaming mode to well meet the real-time parsing requirements. However, the existing log representations used in the heuristic log parsing methods are not powerful in distinguishing log messages, which leads to low parsing accuracy and weak generality. Inspired by trigger word extraction of the event detection task in natural language processing (NLP), this paper proposes an online log parser, named PosParser, which employs the part-of-speech (PoS) tagging to extract a function token sequence (FTS) as the log message representation, and then identify event templates of log messages through the FTS. Experimental results on sixteen logs from real systems demonstrate that the FTS is powerful in distinguishing log messages from different event templates, and PosParser not only performs better in terms of parsing accuracy than state-of-the-art methods but is also comparable to them in efficiency. © 2015 IEEE.

关键词： Real time systems

来源：评论

学校读者我要写书评

暂无评论

On Resilience Against Cyber-Physical Uncertainties in Distributed Nash Equilibrium Seeking Strategies for Heterogeneous Games

引用

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 138-147页

作者： Maojiao Ye IEEE the School of Automation Nanjing University of Science and Technology

This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical *** particular, we are concerned with parametric uncertainties in the control channel of the players. Moreover, the weights on communication links can be compromised by time-varying uncertainties, which can result from possibly malicious attacks,faults and disturbances. To deal with the unavailability of measurement of optimization errors, an output observer is constructed,based on which adaptive laws are designed to compensate for physical uncertainties. With adaptive laws, a new distributed Nash equilibrium seeking strategy is designed by further integrating consensus protocols and gradient search ***, to further accommodate compromised communication weights resulting from cyber-uncertainties, the coupling strengths of the consensus module are designed to be adaptive. As a byproduct, the coupling strengths are independent of any global information. With theoretical investigations, it is proven that the proposed strategies are resilient to these uncertainties and players' actions are convergent to the Nash equilibrium. Simulation examples are given to numerically validate the effectiveness of the proposed strategies.

关键词： Adaptive law cyber-physical systems distributed Nash equilibrium seeking uncertainties

来源：评论

学校读者我要写书评

暂无评论

Characterization of size-resolved aerosol hygroscopicity and liquid water content in nanjing of the Yangtze River Delta

引用

Journal of Environmental sciences 2025年第5期151卷 26-41页

作者： Youling Jiang Yan Ma Jun Zheng Nan Ye Cheng Yuan School of Environmental Science and Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing 210044China School of Emergency Management Nanjing University of Information Science&TechnologyNanjing 210044China

Aerosol hygroscopicity and liquid water content(ALWC)have important influences on the environmental and climate effect of *** this study,we measured the hygroscopic growth factors(GF)of particles with dry diameters of 40,80,150,and 200 nm during the wintertime in *** the GF-derived hygroscopicity parameter(κ_(gf))and ALWC increased with particle size,but displayed differing diurnal variations,withκ_(gf)peaking around the midday,while ALWC peaking in the early ***,ammonium and oxygenated organic aerosols(OOA)were found as the chemical components mostly strongly correlated with ALWC.A closure study suggests that during midday photo-oxidation and nighttime high ALWC periods,theκof organic aerosols(κ_(org))was underestimated when using previous ***,we re-constructed parameterizations forκ_(org)and the oxidation level of organics for these periods,which indicates a higher hygroscopicity of photochemically formed OOA than the aqueous OOA,yet both being much higher than the generally assumed OOA ***,in a typical high ALWC episode,concurrently increased ALWC,nitrate,OOA as well as aerosol surface area and mass concentrations were observed under elevated ambient *** strongly indicates a coupled effect that the hygroscopic secondary aerosols,in particular nitratewith strong hygroscopicity,led to large increase in ALWC,which in turn synergistically boosted nitrate and OOA formation by heterogeneous/aqueous *** interaction may represent an important mechanism contributing to enhanced formation of secondary aerosols and rapid growth of fine particulate matter under relatively high RH conditions.

关键词： Aerosol hygroscopicity Aerosol liquid water content Photo-oxidation Aqueous/heterogeneous reactions

来源：评论

学校读者我要写书评

暂无评论

Enhanced Multi-Scale Object Detection Algorithm for Foggy Traffic Scenarios

引用

computers, Materials & Continua 2025年第2期82卷 2451-2474页

作者： Honglin Wang Zitong Shi Cheng Zhu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China School of Electrical&Computer Engineering University of Illinois at Urbana ChampaignUrbanaIL 61801USA

In foggy traffic scenarios, existing object detection algorithms face challenges such as low detection accuracy, poor robustness, occlusion, missed detections, and false detections. To address this issue, a multi-scale object detection algorithm based on an improved YOLOv8 has been proposed. Firstly, a lightweight attention mechanism, Triplet Attention, is introduced to enhance the algorithm’s ability to extract multi-dimensional and multi-scale features, thereby improving the receptive capability of the feature maps. Secondly, the Diverse Branch Block (DBB) is integrated into the CSP Bottleneck with two Convolutions (C2F) module to strengthen the fusion of semantic information across different layers. Thirdly, a new decoupled detection head is proposed by redesigning the original network head based on the Diverse Branch Block module to improve detection accuracy and reduce missed and false detections. Finally, the Minimum Point Distance based Intersection-over-Union (MPDIoU) is used to replace the original YOLOv8 Complete Intersection-over-Union (CIoU) to accelerate the network’s training convergence. Comparative experiments and dehazing pre-processing tests were conducted on the RTTS and VOC-Fog datasets. Compared to the baseline YOLOv8 model, the improved algorithm achieved mean Average Precision (mAP) improvements of 4.6% and 3.8%, respectively. After defogging pre-processing, the mAP increased by 5.3% and 4.4%, respectively. The experimental results demonstrate that the improved algorithm exhibits high practicality and effectiveness in foggy traffic scenarios.

关键词： Deep learning object detection foggy scenes traffic detection YOLOv8

来源：评论

学校读者我要写书评

暂无评论

A Generative Image Steganography Based on Disentangled Attribute Feature Transformation and Invertible Mapping Rule

引用

computers, Materials & Continua 2025年第4期83卷 1149-1171页

作者： Xiang Zhang Shenyan Han Wenbin Huang Daoyong Fu School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Engineering Research Center of Digital Forensics Nanjing University of Information Science and TechnologyMinistry of EducationNanjing210044China

Generative image steganography is a technique that directly generates stego images from secret *** traditional methods,it theoretically resists steganalysis because there is no cover ***,the existing generative image steganography methods generally have good steganography performance,but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information ***,this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping ***,the reference image is disentangled by a content and an attribute encoder to obtain content features and attribute features,***,a mean mapping rule is introduced to map the binary secret information into a noise vector,conforming to the distribution of attribute *** noise vector is input into the generator to produce the attribute transformed stego image with the content feature of the reference ***,we design an adversarial loss,a reconstruction loss,and an image diversity loss to train the proposed *** results demonstrate that the stego images generated by the proposed method are of high quality,with an average extraction accuracy of 99.4%for the hidden ***,since the stego image has a uniform distribution similar to the attribute-transformed image without secret information,it effectively resists both subjective and objective steganalysis.

关键词： Image information hiding generative information hiding disentangled attribute feature transformation invertible mapping rule steganalysis resistance

来源：评论

学校读者我要写书评

暂无评论

Labeling-based centrality approaches for identifying critical edges on temporal graphs

引用

Frontiers of computer science 2025年第2期19卷 89-104页

作者： Tianming ZHANG Jie ZHAO Cibo YU Lu CHEN Yunjun GAO Bin CAO Jing FAN Ge YU School of Computer Science and Technology Zhejiang University of TechnologyHangzhou 310023China School of Computer Science and Technology Zhejiang UniversityHangzhou 310013China Department of Computer Science Northeastern UniversityShenyang 110819China

Edge closeness and betweenness centralities are widely used path-based metrics for characterizing the importance of edges in *** general graphs,edge closeness centrality indicates the importance of edges by the shortest distances from the edge to all the other *** betweenness centrality ranks which edges are significant based on the fraction of all-pairs shortest paths that pass through the ***,extensive research efforts go into centrality computation over general graphs that omit time ***,numerous real-world networks are modeled as temporal graphs,where the nodes are related to each other at different time *** temporal property is important and should not be neglected because it guides the flow of information in the *** state of affairs motivates the paper’s study of edge centrality computation methods on temporal *** introduce the concepts of the label,and label dominance relation,and then propose multi-thread parallel labeling-based methods on OpenMP to efficiently compute edge closeness and betweenness centralities *** types of optimal temporal *** edge closeness centrality computation,a time segmentation strategy and two observations are presented to aggregate some related temporal edges for uniform *** edge betweenness centrality computation,to improve efficiency,temporal edge dependency formulas,a labeling-based forward-backward scanning strategy,and a compression-based optimization method are further proposed to iteratively accumulate centrality *** experiments using 13 real temporal graphs are conducted to provide detailed insights into the efficiency and effectiveness of the proposed *** with state-ofthe-art methods,labeling-based methods are capable of up to two orders of magnitude speedup.

关键词： temporal graph closeness centrality between-ness centrality temporal path

来源：评论

学校读者我要写书评

暂无评论

YOLO-LFD: A Lightweight and Fast Model for Forest Fire Detection

引用

computers, Materials & Continua 2025年第2期82卷 3399-3417页

作者： Honglin Wang Yangyang Zhang Cheng Zhu School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Electrical&Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA

Forest fires pose a serious threat to ecological balance, air quality, and the safety of both humans and wildlife. This paper presents an improved model based on You Only Look Once version 5 (YOLOv5), named YOLO Lightweight Fire Detector (YOLO-LFD), to address the limitations of traditional sensor-based fire detection methods in terms of real-time performance and accuracy. The proposed model is designed to enhance inference speed while maintaining high detection accuracy on resource-constrained devices such as drones and embedded systems. Firstly, we introduce Depthwise Separable Convolutions (DSConv) to reduce the complexity of the feature extraction network. Secondly, we design and implement the Lightweight Faster Implementation of Cross Stage Partial (CSP) Bottleneck with 2 Convolutions (C2f-Light) and the CSP Structure with 3 Compact Inverted Blocks (C3CIB) modules to replace the traditional C3 modules. This optimization enhances deep feature extraction and semantic information processing, thereby significantly increasing inference speed. To enhance the detection capability for small fires, the model employs a Normalized Wasserstein Distance (NWD) loss function, which effectively reduces the missed detection rate and improves the accuracy of detecting small fire sources. Experimental results demonstrate that compared to the baseline YOLOv5s model, the YOLO-LFD model not only increases inference speed by 19.3% but also significantly improves the detection accuracy for small fire targets, with only a 1.6% reduction in overall mean average precision (mAP)@0.5. Through these innovative improvements to YOLOv5s, the YOLO-LFD model achieves a balance between speed and accuracy, making it particularly suitable for real-time detection tasks on mobile and embedded devices.

关键词： Forest fire detection YOLOv5 lightweight small object detection

来源：评论

学校读者我要写书评

暂无评论

Classifying extended,localized and critical states in quasiperiodic lattices via unsupervised learning

引用

Chinese Physics B 2025年第1期34卷 422-427页

作者： Bohan Zheng Siyu Zhu Xingping Zhou Tong Liu School of Computer Science and Technology School of SoftwareNanjing University of Posts and TelecommunicationsNanjing 210023China Institute of Quantum Information and Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Department of Applied Physics School of ScienceNanjing University of Posts and TelecommunicationsNanjing 210003China

Classification of quantum phases is one of the most important areas of research in condensed matter *** this work,we obtain the phase diagram of one-dimensional quasiperiodic models via unsupervised ***,we choose two advanced unsupervised learning algorithms,namely,density-based spatial clustering of applications with noise(DBSCAN)and ordering points to identify the clustering structure(OPTICS),to explore the distinct phases of the Aubry–André–Harper model and the quasiperiodic p-wave *** unsupervised learning results match well with those obtained through traditional numerical ***,we assess similarity across different algorithms and find that the highest degree of similarity between the results of unsupervised learning algorithms and those of traditional algorithms exceeds 98%.Our work sheds light on applications of unsupervised learning for phase classification.

关键词： quantum phase quasiperiodic machine learning

来源：评论

学校读者我要写书评

暂无评论

Task Offloading in Edge Computing Considering the Dynamics of Tasks and Networks Based on Grey Numbers

引用

IEEE Internet of Things Journal 2025年第11期12卷 17742-17752页

作者： Hao, Yongsheng Cao, Jie Nanjing University of Information Science and Technology School of Computer Science Nanjing210044 China Xuzhou University of Technology Xuzhou221018 China

Task offloading from edge devices to the cloud is typically modeled using Directed Acyclic Graphs (DAGs), which assume predefined task details and stable network conditions. However, obtaining detailed task information is often impractical, particularly in dynamic network environments. This paper addresses these challenges by utilizing grey number theory to effectively capture the uncertainties inherent in both task characteristics and network conditions. Through a comprehensive comparative analysis of grey numbers, a Deep Q-Network (DQN) offloading method based on grey numbers is proposed, significantly improving the scheduling process. This study is the first to explore task offloading for edge devices while considering task uncertainty and network dynamics using grey number theory. Simulation results confirm the efficiency of the proposed method in selecting solutions that meet predefined criteria, with the DQN approach demonstrating significant improvements in scheduling performance. © 2025 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：