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Link Budget and Enhanced communication Distance for Ambient Internet of Things

ZTE communications 2024年第1期22卷 16-23页

作者： YANG Yibing LIU Ming XU Rongtao WANG Gongpu GONG Wei School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China

Backscatter communications will play an important role in connecting everything for beyond 5G(B5G)and 6G *** open challenge for backscatter communications is that the signals suffer a round-trip path loss so that the communication distance is *** this paper,we first calculate the communication distance upper bounds for both uplink and downlink by measuring the tag sensitivity and reflection *** is found that the activation voltage of the envelope detection diode of the downlink tag is the main factor limiting the back-scatter communication *** on this analysis,we then propose to implement a low-noise amplifier(LNA)module before the envelope detection at the tag to enhance the incident signal *** experimental results on the hardware platform show that our method can increase the downlink communication range by nearly 20 m.

关键词： ambient IoT(AIoT) B5G backscatter communication link budget low-noise amplifier(LNA) Release 19 tag chip sensitivity upper bounds

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Dynamic Resource Allocation for ISAC enabled Internet of Vehicles 30

Dynamic Resource Allocation for ISAC enabled Internet of Veh...

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30th International Conference on Mobile Computing and Networking, ACM MobiCom 2024

作者： Xu, Wenxuan Zhang, Yibo Wang, Jingjing Zhang, LanJie Li, Qi School of Information and Communication Engineering Beijing Information Science and Technology University 60088567 China School of Cyber Science and Technology Beihang University 60013789 China School of Information and Communication Engineering Beijing University of Technology 60022281 China

ISBN: (纸本)9798400704895

The development of wireless communication technology is reshaping the landscape of intelligent transportation systems, particularly in the realm of internet of vehicles (IoV). Among these, integrated sensing and communications (ISAC) has garnered widespread attention by leveraging shared hardware resources or even spectrum between sensing and communication to achieve integrated benefits. For IoV, parameters such as target position and speed estimated by ISAC can be used as prior information for resource allocation and beamforming to improve communication performance. In this paper, we focus on ISAC-enabled IoV, where radar sensing signals and communication signals are transmitted within different slots of a subframe to avoid interference. We propose a resource allocation scheme to maximize system throughput while meeting the differentiated needs of all users, where spatial division multiple access is dynamically employed based on network load. Simulation outcomes verify the efficiency of the suggested algorithm. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Radar interference

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Text Watermarking-Based Federated Learning Backdoor Attack Detection Scheme 6

Text Watermarking-Based Federated Learning Backdoor Attack D...

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

作者： Zuo, Yiming Yang, Zheng Chen, Dongdong Gu, Ke Jiang, Luyao Changsha University of Science & Technology School of Computer and Communication Engineering ChangSha China

ISBN: (纸本)9798350388374

With the widespread application of federated learning across various domains, backdoor attacks pose a serious threat to the security of models. In this paper, we proposes a text watermarking-based federated learning backdoor attack detection scheme. The core idea of the scheme is to use the aggregation server to embed and verify the text watermark in the process of global model aggregation, so as to achieve tracking and security protection of the global model. Secondly, in order to deal with the situation that malicious attackers may forge text watermarks, we also deployed a backdoor attack detection and defense based on local gradient symbols on the aggregation server. The scheme detects the gradient information uploaded by the local device, and only when the gradient symbols of most local models are consistent, can it be included in the aggregation process of the global model to ensure the security of the model. Finally, the experimental results verify the effectiveness of this method. © 2024 IEEE.

关键词： Federated learning

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Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 649-660页

作者： Meilin Li Yue Long Tieshan Li Hongjing Liang C.L.Philip Chen the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China IEEE the Yangtze Delta Region Institute University of Electronic Science and Technology of ChinaHuzhou 313000 the Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing 100089China the School of Computer Science and Engineering South China University of TechnologyGuangzhou 510006

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first ***,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale *** is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event *** addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable ***,the results are extended to regional consensus of the MASs with the bounded control *** simulations show the effectiveness of the proposed approach.

关键词： Constrained input designable minimum inter-event time directed communication topology dynamic event-triggered mechanism MASs consensus control

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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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I/O Efficient Early Bursting Cohesive Subgraph Discovery in Massive Temporal Networks

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Journal of computer science & technology 2022年第6期37卷 1337-1355页

作者： Yuan Li Jie Dai Xiao-Lin Fan Yu-Hai Zhao Guo-Ren Wang School of Information Science and Technology North China University of TechnologyBeijing 100144China School of Computer Science and Engineering Northeastern UniversityShenyang 110169China School of Computer Beijing Institute of TechnologyBeijing 100081China

Temporal networks are an effective way to encode temporal information into graph data *** the bursting cohesive subgraph(BCS),which accumulates its cohesiveness at the fastest rate,is an important problem in temporal *** BCS has a large number of applications,such as representing emergency events in social media,traffic congestion in road networks and epidemic outbreak in ***,existing methods demand the BCS lasting for a time interval,which neglects the timeliness of the *** this paper,we design an early bursting cohesive subgraph(EBCS)model based on the k-core to enable identifying the burstiness as soon as *** find the EBCS,we first construct a time weight graph(TWG)to measure the bursting level by integrating the topological and temporal ***,we propose a global search algorithm,called GS-EBCS,which can find the exact EBCS by iteratively removing nodes from the ***,we propose a local search algorithm,named LS-EBCS,to find the EBCS by first expanding from a seed node until obtaining a candidate k-core and then refining the k-core to the result subgraph in an optimal time ***,considering the situation that the massive temporal networks cannot be completely put into the memory,we first design an I/O method to build the TWG and then develop I/O efficient global search and local search algorithms,namely I/O-GS and I/O-LS respectively,to find the EBCS under the semi-external *** experiments,conducted on four real temporal networks,demonstrate the efficiency and effectiveness of our proposed *** example,on the DBLP dataset,I/O-LS and LS-EBCS have comparable running time,while the maximum memory usage of I/O-LS is only 6.5 MB,which is much smaller than that of LS-EBCS taking 308.7 MB.

关键词： early bursting cohesive subgraph(EBCS) I/O efficient algorithm semi-external model temporal network

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Automated object recognition in high-resolution optical remote sensing imagery

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National science Review 2023年第6期10卷 38-41页

作者： Yazhou Yao Tao Chen Hanbo Bi Xinhao Cai Gensheng Pei Guoye Yang Zhiyuan Yan Xian Sun Xing Xu Hai Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology (NIST) Aerospace Information Research Institute Chinese Academy of Sciences Department of Computer Science and Technology Tsinghua University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

INTRODUCTION With the rapid development of remote sensing technology,high-quality remote sensing images have become widely *** automated object detection and recognition of these images,which aims to automatically locate objects of interest in remote sensing images and distinguish their specific categories,is an important fundamental task in the *** provides an effective means for geospatial object monitoring in many social applications,such as intelligent transportation,urban planning,environmental monitoring and homeland security.

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A Load-Balancing Strategy Based on Multi-Task Learning in a Distributed Training Environment 4

A Load-Balancing Strategy Based on Multi-Task Learning in a ...

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4th International Conference on Advances in Electrical engineering and computer Applications, AEECA 2023

作者： Huang, Yinqi Zhou, Wenjiang Li, Liang Lyu, Ting Xu, Haitao Univerisity of Science and Technology Beijing School of Computer and Communication Engineering Beijing China China Academy of Information and Communications Technology Beijing China Shunde Innovation School Univerisity of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798350308082

With the development of machine learning and big data technologies, distributed training has become an important way to improve computational efficiency. However, in the distributed training environment, the performance difference between workers and the interference of unrelated tasks may lead to the uneven load of the system and cause the 'straggler phenomenon'. Therefore, how to solve the straggler phenomenon and achieve load balancing of the system is a pressing problem of distributed training. To address the shortcomings of the existing parallel computing model DSSP, this paper proposes a load-balancing strategy for DDP, which effectively reduces the load difference by adjusting the batch size and data size of workers in the training process. Then, to explore the correlation between data size in DDP and synchronization threshold in DSSP in dynamic adjustment, we perform multi-task learning for the two dynamic adjustment strategies and integrate the proposed Joint Multi-Task Prediction scheme on DSSP to implement a new parallel computing model ESP. extensive experiments The results show that ESP can not only guarantee the model accuracy but also effectively improve the training speed in distributed training. © 2023 IEEE.

关键词： Computational efficiency

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SCANet: Spatial-Channel Attention Feature Extraction Network for Remote Sensing Images 11th

SCANet: Spatial-Channel Attention Feature Extraction Network...

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11th International Conference on Signal and Information Processing, Network and computers, ICSINC 2023

作者： Zhang, Xiaolu Wang, Zhaoshun Wei, Chuncheng Zhang, Jianheng School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China China Unicom Digital Technology Co. Ltd. Beijing China

ISBN: (纸本)9789819721238

This study focuses on adding channel and spatial attention modules to a residual block for more effectively interpreting high-resolution remote sensing images. Three feature extraction networks are constructed through parallel and sequential combinations to select a network for high-resolution remote sensing images. Furthermore, these three networks are combined with classification, semantic segmentation, and object detection networks. The results of ablation and comparative experiments on different remote sensing data sets—NWPU-RESISC45, DeepGlobe, and DOTA—reveal that the three constructed methods have achieved good results in semantic segmentation and classification tasks. The construction method of sequential combination (spatial–channel) is the most improved. The effectiveness and general applicability of the proposed feature extraction networks are verified. These feature extraction networks can be used in classification, semantic segmentation, and object detection tasks for remote sensing images and can effectively improve the accuracy of the network. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Feature extraction

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Research on optimization model of differentiated toll rate of expressway towards sustainable transportation development

Advances in Transportation Studies

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Advances in Transportation Studies 2024年 62卷 191-208页

作者： Zhu, Z. Zhang, X. Wei, Z. Liu, M. Yu, C. Wula, Z. Platform of Transport Technology Thinktank Research Institute of Highway Ministry of Transport Beijing100088 China School of Transportation Science and Engineering Beihang University Beijing100191 China School of Computer Science and Engineering Beihang University Beijing100191 China

To explore the basis and implementation effects of differential toll rate formulation for expressways, reduce the financial burden of expressway operators, and scientifically guide traffic flow, this study proposes an expressway differential toll rate optimization model. The model is demonstrated using two pilot sections of G25 and G1112 expressways in J province of China, where differential tolling is implemented. Based on the change characteristics of traffic flow and toll amount of the two pilot sections before and after differential tolling, we propose an optimization model of differential toll rate for expressways that maximizes the net revenue of expressway operators while minimizing individual travel impedance. The optimization model is solved using MATLAB, and an optimal differential toll rate scheme by road section, time period, and vehicle type is obtained. The evaluation of the model is based on the net revenue of highway operators and individual travel impedance. The findings reveal that the proposed optimal rate scheme improves the net revenue of road operators while reducing individual travel impedance compared to the original toll rate scheme. Specifically, the differential toll pilot sections of G25 and G1112 can increase net revenue by approximately Rmb25,000,000 and Rmb16,000,000 per month, respectively, and reduce vehicle travel impedance by about Rmb37 and Rmb32 per vehicle. The proposed model balances highway operator revenue with individual travel costs, leading to more sustainable and efficient expressway use, which benefits expressway transportation sustainability. © 2024, Aracne Editrice. All rights reserved.

关键词： Vehicles

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