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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on information Photonics and Optical Communications, IPOC 2024

作者： Yang, Bofan Li, Shangyuan Zheng, Xiaoping Xue, Xiaoxiao Department of Electronic Engineering Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China

We demonstrate spectral phase measurement of microcombs through stepped interference with an electro-optic comb generated by a phase modulator. The temporal waveform of a normal-dispersion microcomb is characterized u... 详细信息

ISBN: (纸本)9798350379266

关键词： Phase measurement

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Multi-sensor missile-borne LiDAR point cloud data augmentation based on Monte Carlo distortion simulation

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CAAI Transactions on Intelligence technology 2025年第1期10卷 300-316页

作者： Luda Zhao Yihua Hu Fei Han Zhenglei Dou Shanshan Li Yan Zhang Qilong Wu College of Electronic Engineering National University of Defense TechnologyHefeiChina State Key Laboratory of Pulsed Power Laser Technology National University of Defense TechnologyHefeiChina Anhui Province Key Laboratory of Electronic Restriction National University of Defense TechnologyHefeiChina Information Security Research Center Hefei Comprehensive National Science CenterHefeiChina Anhui Provincial Military Region Chinese PLAHefeiChina

Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing *** to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and ***,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding *** address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical ***,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud *** effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this *** experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.

关键词： data augmentation LiDAR missile-borne imaging Monte Carlo simulation point cloud

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Modeling and Control Strategies for Flight Service Vehicle Queue Behavior in Non Cooperative Games 1

Modeling and Control Strategies for Flight Service Vehicle Q...

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1st International Conference on Applied Physics and Mathematics, ICAPM 2023

作者： Wang, Sibo Hao, Shougang Zhang, Ping Ou, Jian Zhang, Tao Wen, Tao Research and Development Center Civil Aviation Electronic Technology co. Ltd. Sichuan Chengdu China Engineering Technology Research Center The Second Research Institute of CAAC Sichuan Chengdu China

From the perspective of the running process for service vehicles, based on the analysis of the benefits maximization of the special needs vehicles joining the queue as the scheduling goal, and aiming at the shortcomings of traditional task scheduling strategies, methods and models, a non-cooperative game behavior optimization scheduling model with security, economy and environmental protection as the optimization goals was proposed by using game theory. At the same time, the vehicle service capability, service times and import Angle are limited to ensure that the model is more in line with the actual operation scenario. In order to judge the deviation between the game result and the actual operation, the game efficiency matrix is constructed, and Nash equilibrium is used to prove that the model has an equilibrium point. On the basis of the game model, the strategy layer, the game layer and the optimization layer are divided into queue behavior control strategy methods. Finally, this paper verifies the feasibility of the model by using the actual parameter changes to determine the best parameter combination suitable for the model. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Game theory

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Using UAV-based multispectral images and CGS-YOLO algorithm to distinguish maize seeding from weed

Artificial Intelligence in Agriculture

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Artificial Intelligence in Agriculture 2025年第2期15卷 162-181页

作者： Boyi Tang Jingping Zhou Chunjiang Zhao Yuchun Pan Yao Lu Chang Liu Kai Ma Xuguang Sun Ruifang Zhang Xiaohe Gu Information Technology Research Center Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China College of Information Engineering Northwest A&F UniversityYangling 712100China Beijing PAIDE Science and Technology Development Co. LtdBeijingChina College of Land and Resources Hebei Agricultural UniversityChina

Accurate recognition of maize seedlings on the plot scale under the disturbance of weeds is crucial for early seedling replenishment and weed ***,UAV-based maize seedling recognition depends primarily on RGB *** main purpose of this study is to compare the performances of multispectral images and RGB images of unmanned aerial vehicle(UAV)on maize seeding recognition using deep learning ***,we aim to assess the disturbance of different weed coverage on the recognition of maize ***,principal component analysis was used in multispectral image ***,by introducing the CARAFE sampling operator and a small target detection layer(SLAY),we extracted the contextual information of each pixel to retain weak features in the maize seedling ***,the global attention mechanism(GAM)was employed to capture the features of maize seedlings using the dual attention mechanism of spatial and channel *** CGS-YOLO algorithm was constructed and ***,we compared the performance of the improved algorithm with a series of deep learning algorithms,including YOLO v3,v5,v6 and *** results show that after PCA transformation,the recognition mAP of maize seedlings reaches 82.6%,representing 3.1 percentage points improvement compared to RGB *** with YOLOv8,YOLOv6,YOLOv5,and YOLOv3,the CGS-YOLO algorithm has improved mAP by 3.8,4.2,4.5 and 6.6 percentage points,*** the increase of weed coverage,the recognition effect of maize seedlings gradually *** weed coverage was more than 70%,the mAP difference becomes significant,but CGS-YOLO still maintains a recognition mAP of 72%.Therefore,in maize seedings recognition,UAV-based multispectral images perform better than RGB *** application of CGS-YOLO deep learning algorithm with UAV multi-spectral images proves beneficial in the recognition of maize seedlings under weed disturbance.

关键词： Object detection Maize seedlings Weed disturbance YOLO UAV multispectral images

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Enhancing Offensive Language Detection with Data Augmentation and Knowledge Distillation

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research 2024年第2期6卷 29-40页

作者： Jiawen Deng Zhuang Chen Hao Sun Zhexin Zhang Jincenzi Wu Satoshi Nakagawa Fuji Ren Minlie Huang The CoAl group DCSTInstitute for Artificial InteligenceState Key Lab of Intelligent Technology and SystemsBeijing National Research Center for Information Science and TechnologyTsinghua UniversityBeijing 100084China Graduate School of Information Science&Technology The University of Tokyo.Tokyo 1138654Japan School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengduSichuan611731China

Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language *** data is the basis for developing detectors;however,the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English *** significantly affects the accuracy of Chinese offensive language detectors in practical applications,especially when dealing with hard cases or out-of-domain *** alleviate the limitations posed by available datasets,we introduce AugCOLD(Augmented Chinese Offensive Language Dataset),a large-scale unsupervised dataset containing 1 million samples gathered by data crawling and model ***,we employ a multiteacher distillation framework to enhance detection performance with unsupervised *** is,we build multiple teachers with publicly accessible datasets and use them to assign soft labels to *** soft labels serve as a bridge for knowledge to be distilled from both AugCOLD and multiteacher to the student network,i.e.,the final offensive *** conduct experiments on multiple public test sets and our well-designed hard tests,demonstrating that our proposal can effectively improve the generalization and robustness of the offensive language detector.

关键词： COLD dealing limitations

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The Digital Twin City in Enhancing Flood Evacuation Systems: Future Opportunities and Challenges

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IEEE Access 2025年 13卷 32371-32383页

作者： Setijadi Prihatmanto, Ary Prasetyadi, Abdurrakhman Yoganingrum, Ambar Sutriadi, Ridwan Hadiana, Ana Bandung Institute of Technology School of Electrical and Informatics Engineering Bandung40132 Indonesia National Research and Innovation Agency Research Center for Data and Information Science Bandung40231 Indonesia Bandung Institute of Technology School of Architecture Planning and Policy Development Bandung40132 Indonesia

In recent decades, the increasing frequency and severity of natural disasters have necessitated the development of more effective disaster management systems. This paper explores the potential of digital twin technology to enhance flood evacuation systems. A digital twin-city model can simulate urban environments, predict flood inundation, and identify optimal evacuation routes in real-time. The study conducts a systematic literature review to assess current advancements, evaluating the integration of 3D city models, artificial intelligence, and Internet of things sensors in flood evacuation planning. Results indicate that digital twin technology significantly improves predictive capabilities and evacuation efficiency, although data integration, model accuracy, and computational demands remain. Future research should focus on enhancing data integration, refining simulation models, improving predictive analytics, developing advanced visualization tools, and validating models across diverse environments to ensure reliability and effectiveness. © 2025 The Authors.

关键词： Digital elevation model

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The Current State of Fingerprinting in Operational technology Environments

The Current State of Fingerprinting in Operational Technolog...

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2023 Congress in Computer Science, Computer Engineering, and Applied Computing, CSCE 2023

作者： Manyfield-Donald, Cheronika Mitchell, Candice Engineer Research and Development Center Information Technology Laboratory VicksburgMS United States

ISBN: (纸本)9798350327595

Observing the increase in cybersecurity attacks on our nation's and even world's critical infrastructures, heightens the priority need for being proactive in detecting possible intrusions. Each endpoint that connects information technology to operational technology is a vulnerability endpoint. Identification of these endpoints is the first step in fortifying the critical infrastructure. Sadly, most entities do not have a complete blueprint of their system's network. This is why the introduction of network fingerprinting arose. This initial step of our research discusses networking fingerprinting as a tool to identify components of a critical infrastructure, outlines previous work and identifies some network fingerprinting tools. The work shows that fingerprinting and operational technology (OT) asset identification is still woefully lacking in its ability and suggests possible future improvements. © 2023 IEEE.

关键词： active scanning cybersecurity network fingerprinting operational technology passive scanning

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Dynamic Residual Graph Attention Network for Network Intrusion Detection System 6

Dynamic Residual Graph Attention Network for Network Intrusi...

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6th International Conference on Next Generation Data-Driven Networks, NGDN 2024

作者： Wang, Song Zhang, Zhenming Li, Wei Yin, Chen Ma, Yu Xu, Weiyao Weihai Comprehensive Research Center of Electronic Information Technology Miit Weihai China Development Center of Industry and Information Technology of Weihai Weihai China Shandong Vocational University of Foreign Affairs Weihai China Shandong Polytechnic College Jining China Zaozhuang University Zaozhuang China

ISBN: (纸本)9798350388374

With the rapid development of the industrial internet, it greatly promotes the advancement of social productivity. In the context of frequent network attacks, the security issues have become increasingly important. Network intrusion detection system(NIDS) is an important component of industrial internet security defense, which detects and prevents attack traffic by monitoring the status of network traffic. Many researchers have conducted research in this field, such as traditional machine learning methods. However, these methods still have some practical problems and many challenges remain unresolved. In this paper, we focus on the original network traffic and present an intrusion detection method based on the dynamic residual graph attention network (DRGAT). We introduce residual calculation and an improved dynamic attention mechanism to form a more robust graph-based NIDS, which can represent and learn traffic information, and detect various attack traffic with high accuracy. Experiments on two public datasets show that the proposed method outperforms the most advanced methods in multiple performance indicators, providing impetus for further research. © 2024 IEEE.

关键词： Network intrusion

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Dielectric Patch Resonator and Antenna

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China Communications 2023年第8期20卷 209-219页

作者： Jianxin Chen Xueying Wang Shichang Tang Yongle Wu School of Information Science and Technology and Research Center for Intelligent Information TechnologyNantong UniversityNantong 226019China Nantong Research Institute for Advanced Communication Technologies Chongchuan DistrictNantong 226019China School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

This paper presents an overview of dielectric patch(DP)antennas developed in recent *** employed DP resonator composed of a DP and a bottom substrate is analyzed comprehensively here,enabling the easy realization of a quasi-planar DP *** combines the dual advantages of the conventional microstrip patch(MP)antenna and dielectric resonator(DR)antenna in terms of profile,gain,bandwidth,radiation efficiency,and design ***,the DP antenna inherits the multi-mode characteristic of the DR antenna,thus it has a large number of high-order modes,including TMmn mode and TEmn *** high-order modes are widely applied,for example,by combining with the dominant TM10 mode to expand the bandwidth,or selecting multiple higher-order modes to implement a high-gain ***,the non-radiation high-order modes are also utilized to produce natural radiation null in filtering antenna *** this paper,the design theories and techniques of DP antenna are introduced and investigated,including calculation and control methods of the resonant mode frequencies,analysis of the radiation mechanism,and applications of the multi-mode *** overview could provide guidance for the subsequent antenna design,thus effectively avoid time-consuming optimization.

关键词： dielectric patch(DP)resonator DP antenna radiation mechanism multi-mode characteristic

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Generation of six-lobe photoelectron angular distribution via three-leaf clover laser field

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Optical and Quantum electronics 2024年第11期56卷 1-11页

作者： Xu, Shengliang Huang, Liang Zhang, Xiaodong Kuang, Jidi Hong, Zuofei Wang, Run GAC Automotive Research & amp Development Center Guangzhou China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology Wuhan China College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua China

We theoretically investigate the low-energy photoelectron angular distribution (PAD) during ionization of the P± atomic orbitals by counter-rotating two-color circularly polarized laser fields. Our study reveals a transition from three-lobe to six-lobe structure in the low-energy PAD for P+ orbital when the intensity ratio between the co-rotating 800-nm (ω0) and counter-rotating 400-nm (2ω0) laser components is increased, while the three-lobe structure is maintained for the P- orbital. The three-lobe structure is exclusively attributed to the (6×2ω0-1×ω0) pathway, whereas the (5×2ω0+1×ω0) pathway begins to dominate for the six-lobe structure. These results clearly and unambiguously demonstrate that the PAD in counter-rotating laser fields can be utilized for the detection of P+ and P- orbitals and also offer additional degrees of freedom for precisely controlling the contributions of various ionization pathways. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Angular distribution

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