检索结果-内蒙古大学图书馆

Temporal-spectral correlation dynamics of Raman random fiber laser

science China(information sciences) 2025年第4期68卷 166-176页

作者： Longqun NI Yifei QI Xingyu BAO Jing ZHANG Pan WANG Han WU Zinan WANG Key Laboratory of Optical Fiber Sensing and Communications University of Electronic Science and Technology of China College of Electronics and Information Engineering Sichuan University

Raman random fiber laser(RRFL) possesses rich physical properties of spectral, temporal, and spatial domains due to its unique feedback mechanism and complex nonlinear effects. Characterizing and controlling the microscopic evolution dynamics of RRFL are crucial to driving breakthrough advances in fields such as inertial confinement fusion and fundamental physics. In this work, a novel experimental and theoretical analysis of the evolution of the temporal spectral correlations of the RRFL in the transition and steady states is conducted. In the transitional state, the microscopic dynamics of the RRFL excitation process is revealed comprehensively: the temporal-correlation growth curve contrasts with that of resonant-cavity lasers, and the formation and degradation of spectral correlation are observed. In the steady state, the overall spectrum is characterized by partial correlation, and the correlation characteristics of RRFL mainly originate from the spectral random spikes, which offers a novel dimension for the precise control of RRFL correlation. This work provides new insights into underlying physical properties of continuous broadband lasers, offering key guidance for laser design, control, and applications.

关键词： random fiber laser microscopic characteristics temporal-spectral correlation random spikes nonlinear optics

来源：评论

学校读者我要写书评

暂无评论

DMF: A Deep Multimodal Fusion-Based Network Traffic Classification Model

引用

Computers, Materials & Continua 2025年第5期83卷 2267-2285页

作者： Xiangbin Wang Qingjun Yuan Weina Niu Qianwei Meng Yongjuan Wang Chunxiang Gu Henan Key Laboratory of Network Cryptography Technology Information Engineering UniversityZhengzhou450001China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China

With the rise of encrypted traffic,traditional network analysis methods have become less effective,leading to a shift towards deep learning-based *** these,multimodal learning-based classification methods have gained attention due to their ability to leverage diverse feature sets from encrypted traffic,improving classification ***,existing research predominantly relies on late fusion techniques,which hinder the full utilization of deep features within the *** address this limitation,we propose a novel multimodal encrypted traffic classification model that synchronizes modality fusion with multiscale feature ***,our approach performs real-time fusion of modalities at each stage of feature extraction,enhancing feature representation at each level and preserving inter-level correlations for more effective *** continuous fusion strategy improves the model’s ability to detect subtle variations in encrypted traffic,while boosting its robustness and adaptability to evolving network *** results on two real-world encrypted traffic datasets demonstrate that our method achieves a classification accuracy of 98.23% and 97.63%,outperforming existing multimodal learning-based methods.

关键词： Deep fusion intrusion detection multimodal learning network traffic classification

来源：评论

学校读者我要写书评

暂无评论

Prospects on mangrove knowledge services in the smart era:From plant atlas to knowledge graphs

引用

science China Earth sciences 2025年第1期68卷 111-127页

作者： Zhi-Wei HOU Wenlong JING Cheng-Zhi QIN Ji YANG Qing XIA Xiaoling YIN Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangdong Academy of SciencesGuangzhou510070China Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou511458China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing100049China School of Traffic&Transportation Engineering Changsha University of Science and TechnologyChangsha410114China

Mangroves are crucial to the ecological security of the Earth and human *** management,conservation,and restoration are of great importance and necessitate the support of spatio-temporal information and multidisciplinary knowledge such as biology and *** knowledge services such as plant atlas provide illustrated textual knowledge of ***,this kind of service is oriented to information retrieval and is incapable of effectively mining and utilizing fragmented knowledge from multi-source heterogeneous data,facing the problem of“massive data,rare knowledge”.Knowledge graphs are capable of extracting,organizing,and fusing the knowledge contained in massive data into semantic networks that can be understood and computed by *** provide a solution for the realization of intelligent knowledge *** on the urgent need for mangrove knowledge acquisition,formal representation,and intelligent services,this paper proposes a research prospect on mangrove knowledge graphs and knowledge *** first analyze the similarities and differences between various domain-specific concepts of *** this basis,we define the mangrove knowledge graph as a large-scale knowledge base that integrates multi-disciplinary knowledge and spatio-temporal information with mangrove ecosystems as the ***,we propose a research framework for mangrove knowledge services that can realize the transformation from multi-modal data to intelligent knowledge services,including multiple research levels such as ubiquitous data sensing and aggregation,knowledge organization and graph construction,and intelligent mangrove knowledge ***,the methods and workflow for constructing mangrove knowledge graphs are ***,we discuss the challenges and possible future directions of mangrove knowledge services in the smart era,including the construction of a mangrove knowledge system that integrates the domain-specific charac

关键词： Mangrove Tupu Knowledge graph Multi-modal Knowledge service

来源：评论

学校读者我要写书评

暂无评论

Driver-personality-involved car-following energy management strategies for FCHEVs

引用

International Journal of Hydrogen Energy 2025年 138卷 445-458页

作者： Tao, Fazhan Liu, Weibo Zhu, Longlong Wang, Jun School of Information Engineering Henan University of Science and Technology Luoyang China Longmen Laboratory Luoyang China

The safety and energy-saving driven co-optimization of vehicle speed and energy management for fuel cell/battery hybrid electric vehicle (FCHEV) has become a research hotspot in automotive. However, in the existing research, the coupling relationship among driving styles, vehicle dynamics, and energy consumption is complex and not fully taken into account, resulting in limited performance of FCHEV. To address this issue, a car-following energy management strategy (EMS) incorporating driving styles is proposed in this paper. Firstly, a hybrid adaptive noise-resistant clustering algorithm is designed to accurately and efficiently identify driving styles by combining support vector machines and artificial neural networks. Secondly, considering the impact of driving styles on vehicle speed control, driving styles based full velocity difference model is established and optimized by genetic algorithm (GA), which guarantees driving safety under different driving styles. Thirdly, to enhance the energy-saving potential of EMS, adaptive equivalent consumption minimization strategy (ECMS) is proposed, where equivalent factors are offline optimized by GA with driving styles and adaptively adjusted online. Simulation results indicate that, compared to the ECMS, the proposed method in this paper achieves a reduction in hydrogen consumption of approximately 12.31% under UDDS conditions, 12.76% under NEDC conditions, 16.47% under HWFET-UDDS conditions, and 11.42% under composite conditions. © 2025 Hydrogen Energy Publications LLC

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

An overview on IRS-enabled sensing and communications for 6G: architectures, fundamental limits, and joint beamforming designs

引用

science China(information sciences) 2025年第5期68卷 170-193页

作者： Xianxin SONG Yuan FANG Feng WANG Zixiang REN Xianghao YU Ye ZHANG Fan LIU Jie XU Derrick Wing Kwan NG Rui ZHANG Shuguang CUI School of Science and Engineering (SSE) Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen)and Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Department of Electrical Engineering City University of Hong Kong School of Information Engineering Guangdong University of Technology Key Laboratory of Wireless-Optical Communications Chinese Academy of Sciences School of Information Science and Technology University of Science and Technology of China Computer School Beijing Information Science and Technology University National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University School of Electrical Engineering and Telecommunications University of New South Wales School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Department of Electrical and Computer Engineering National University of Singapore

This study presents an overview on intelligent reflecting surface(IRS)-enabled sensing and communication for the forthcoming sixth-generation(6G) wireless networks, in which IRSs are strategically deployed to proactively reconfigure wireless environments to improve both sensing and communication(S&C) performance. First, we exploit a single IRS to enable wireless sensing in the base station's(BS's) non-line-of-sight(NLoS) area. In particular, we present three IRS-enabled NLoS target sensing architectures with fully-passive, semi-passive, and active IRSs, respectively. We compare their pros and cons by analyzing the fundamental sensing performance limits for target detection and parameter estimation. Next, we consider a single IRS to facilitate integrated sensing and communication(ISAC), in which the transmit signals at the BS are used for achieving both S&C functionalities, aided by the IRS through reflective beamforming. We present joint transmit signal and receiver processing designs for realizing efficient ISAC, and jointly optimize the transmit beamforming at the BS and reflective beamforming at the IRS to balance the fundamental performance tradeoff between S&C. Furthermore, we discuss multi-IRS networked ISAC, by particularly focusing on multi-IRS-enabled multi-link ISAC, multi-region ISAC, and ISAC signal routing, respectively. Finally, we highlight various promising research topics in this area to motivate future work.

关键词： integrated sensing and communication (ISAC) intelligent reflecting surface (IRS) non-line-of-sight (NLoS) sensing sensing and communication tradeoff

来源：评论

学校读者我要写书评

暂无评论

Hybrid-Layer Data Storage with High-Orthogonality Random Meta-Channels

引用

engineering 2025年第2期45卷 79-87页

作者： Dong Zhao Hongkun Lian Xueliang Kang Kun Huang Department of Optics and Optical Engineering University of Science and Technology of ChinaHefei 230026China Anhui Key Laboratory of Optoelectronic Science and Technology University of Science and Technology of ChinaHefei 230026China School of Electrical and Information Engineering North Minzu UniversityYinchuan 750021China

Optical data storage(ODS)is a low-cost and high-durability counterpart of traditional electronic or mag-netic *** a means of enhancing ODS capacity,the multiple recording layer(MRL)method is more promising than other approaches such as reducing the recording volume and multiplexing ***,the architecture of current MRLs is identical to that of recording data into physical layers with rigid space,which leads to either severe interlayer crosstalk or finite recording layers constrained by the short working distances of the ***,we propose the concept of hybrid-layer ODS,which can record optical information into a physical layer and multiple virtual layers by using high-orthogonality random *** the virtual layer,32 images are experimentally reconstructed through holog-raphy,where their holographic phases are encoded into 16 printed images and complementary images in the physical layer,yielding a capacity of 2.5 Tbit cm^(-3).A higher capacity is achievable with more virtual layers,suggesting hybrid-layer ODS as a possible candidate for next-generation ODS.

关键词： Optical data storage Metasurfaces High-orthogonality meta-channels Physical layer Virtual layer

来源：评论

学校读者我要写书评

暂无评论

Joint Task Offloading and Resource Allocation Strategy for Space-Air-Ground Integrated Vehicular Networks

引用

清华大学学报自然科学版（英文版） 2025年第3期30卷 1027-1043页

作者： Yuanshuo Gang Yuexia Zhang Zhihai Zhuo School of Information and Communication Engineering Beijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100101China

Space-Air-Ground integrated Vehicular Network(SAGVN)aims to achieve ubiquitous connectivity and provide abundant computational resources to enhance the performance and efficiency of the vehicular ***,there are still challenges to overcome,including the scheduling of multilayered computational resources and the scarcity of spectrum *** address these problems,we propose a joint Task Offloading(TO)and Resource Allocation(RA)strategy in SAGVN(namely JTRSS).This strategy establishes an SAGVN model that incorporates air and space networks to expand the options for vehicular TO,and enhances the edge-computing resources of the system by deploying edge *** minimize the system average cost,we use the JTRSS algorithm to decompose the original problem into a number of subproblems.A maximum rate matching algorithm is used to address the channel allocation and the Lagrangian multiplier method is employed for computational *** acquire the optimal TO decision,a differential fusion cuckoo search algorithm is *** simulation results demonstrate the significant superiority of the JTRSS algorithm in optimizing the system average cost.

关键词： edge computing Resource Allocation(RA) Space-Air-Ground integrated Vehicular Network(SAGVN) Task Offloading(TO)

来源：评论

学校读者我要写书评

暂无评论

IPFA-Net: Important Points Feature Aggregating Net for Point Cloud Classification and Segmentation

引用

Chinese Journal of Electronics 2025年第1期34卷 322-337页

作者： Jingya Wang Yu Zhang Bin Zhang Jinxiang Xia Weidong Wang School of Information and Software Engineering University of Electronic Science and Technology of China National Key Laboratory of Automotive Chassis Integration and Bionics Jilin University

This paper focuses on the problems of point cloud deep neural networks in classification and segmentation tasks, including losing important information during down-sampling, ignoring relationships among points when extracting features, and network performance being susceptible to the sparsity of point cloud. To begin with, this paper proposes a farthest point sampling-important points sampling method for down-sampling, which can preserve important information of point clouds and maintain the geometry of input data. Then, the local feature relation aggregating method is proposed for feature extraction, improving the network's ability to learn contextual information and extract rich local region features. Based on these methods, the important points feature aggregating net(IPFA-Net) is designed for point cloud classification and segmentation tasks. Furthermore, this paper proposes the multi-scale multi-density feature connecting method to reduce the negative impact of point cloud data sparsity on network performance. Finally, the effectiveness of IPFA-Net is demonstrated through experiments on ModelNet40, ShapeNet part, and ScanNet v2 datasets. IPFA-Net is robust to reducing the number of point clouds, with only a 3.3% decrease in accuracy under a 16-fold reduction of point number. In the part segmentation experiments, our method achieves the best segmentation performance for five objects.

关键词： Point cloud compression Representation learning Geometry Fuses Semantics Artificial neural networks Feature extraction Sampling methods Robustness Data mining

来源：评论

学校读者我要写书评

暂无评论

Time-Varying Formation Tracking Control of Heterogeneous Multi-Agent systems With Intermittent Communications and Directed Switching Networks

引用

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems Control theory Autonomous systems Stability

来源：评论

学校读者我要写书评

暂无评论

EPAFusion: A Novel Fusion Network Based on Enhancement and Progressive Aware for Infrared-Visible Images in Low-Light

引用

IEEE Sensors Journal 2025年第9期25卷 15378-15390页

作者： Qi, Jianhuan Ni, Bo Yu, Qida Ni, Haibin Zhou, Xiaoyan Chang, Jianhua Nanjing University of Information Science and Technology School of Electronics and Information Engineering Nanjing210044 China Nanjing University of Information Science and Technology Jiangsu Provincial Key Laboratory of Meteorological Observation and Information Processing Nanjing210044 China

Most infrared and visible image fusion algorithms demonstrate satisfactory performance under normal lighting conditions, but often perform poorly in low-light environments because the texture details in visible images are barely visible in the dark. To resolve this issue, we have proposed a novel fusion network based on enhancement and progressive aware for infrared-visible images in low-light (EPAFusion). The EPAFusion network efficiently brightens low-light environments while fusing complementary information from the two modalities. Specifically, we design a degraded illumination disentangled network (DIDNet), which is specially used to eliminate the degraded illumination effect in the visible image and enhance the feature information of the source image. Then, a progressive complementary-aware fusion network (PCAFNet), which is used to generate fused images with rich texture details and high contrast by integrating the complementary information of the dual modal through a progressive approach. Extensive comparative experiments have demonstrated that EPAFusion exhibits superior to state-of-the-art fusion algorithms in terms of subjective and objective evaluation metrics. Particularly, low-light enhancement and dual-modal-aware fusion provide more effective information to the fused image. © 2001-2012 IEEE.

关键词： Image fusion

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：