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arXiv 2024年

作者： Xie, Jinxia Zhong, Bineng Mo, Zhiyi Zhang, Shengping Shi, Liangtao Song, Shuxiang Ji, Rongrong Key Laboratory of Education Blockchain and Intelligent Technology Ministry of Education China Guangxi Key Lab of Multi-Source Information Mining & Security China Guangxi Normal University Guilin541004 China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University China School of Computer Science and Technology Harbin Institute of Technology China Media Analytics and Computing Lab School of Informatics Xiamen University China

The rich spatio-temporal information is crucial to capture the complicated target appearance variations in visual tracking. However, most top-performing tracking algorithms rely on many hand-crafted components for spatio-temporal information aggregation. Consequently, the spatio-temporal information is far away from being fully explored. To alleviate this issue, we propose an adaptive tracker with spatio-temporal transformers (named AQATrack), which adopts simple autoregressive queries to effectively learn spatio-temporal information without many hand-designed components. Firstly, we introduce a set of learnable and autoregressive queries to capture the instantaneous target appearance changes in a sliding window fashion. Then, we design a novel attention mechanism for the interaction of existing queries to generate a new query in current frame. Finally, based on the initial target template and learnt autoregressive queries, a spatio-temporal information fusion module (STM) is designed for spatio-temporal formation aggregation to locate a target object. Benefiting from the STM, we can effectively combine the static appearance and instantaneous changes to guide robust tracking. Extensive experiments show that our method significantly improves the tracker’s performance on six popular tracking benchmarks: LaSOT, LaSOText, TrackingNet, GOT-10k, TNL2K, and *** and models will be here. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Modulation Signal Recognition Based on Feature Fusion and Residual CNN in Fractal Noise Background 6

Modulation Signal Recognition Based on Feature Fusion and Re...

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6th International Conference on Signal and Image Processing, ICSIP 2021

作者： Chen, Di Xiong, Gang Huang, Baigang Wang, Lijun No.36 Research Institute of Cetc Science and Technology On Communication Information Security Control Laboratory Jiaxing China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Institute of Navigation and Sensing Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9780738133737

In this paper, a modulated signal recognition method based on feature fusion and ResCNN (FF-ResCNN) under generalized fractal noise background is proposed. Firstly, in the feature extraction and fusion part, considering the robustness, anti-noise and interpretability of the features, the fusion feature vectors of generalized fractal spectrum, instantaneous feature and high-order cumulant feature are constructed. Secondly, in order to suppress the possible gradient and degradation problems, the ResCNN model is used to train and classify the fusion features when the CNN model is used to further collect the deep-level abstract features. Finally, feature extraction, feature fusion and classification experiments are carried out for nine modulated signals under two noise types (GWN and fractal noise). Experimental results show that in the case of generalized fractal noise, when SNR=0dB, the recognition accuracy of signal modulation type reaches 95.42%, which verifies the superiority of the proposed method. At the same time, the simulation analysis is carried out for different feature fusion schemes, which provides a valuable reference for feature combination optimization under different noise environment. © 2021 IEEE.

关键词： Feature extraction

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STAR-RIS-UAV Aided Coordinated Multipoint Cellular System for Multi-user Networks

arXiv

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arXiv 2023年

作者： Shi, Baihua Wang, Yang Li, Danqi Cai, Wenlong Lin, Jinyong Zhang, Shuo Shi, Weiping Yan, Shihao Shu, Feng The School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China The School of Information and Communication Engineering Hainan University Haikou570228 China The National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing100854 China The School of Science Security Research Institute Edith Cowan University PerthWA6027 Australia

Different with conventional reconfigurable intelligent surface (RIS), simultaneous transmitting and reflecting RIS (STAR-RIS) can reflect and transmit the signals to the receiver. In this paper, to serve more ground users and increase the deployment flexibility, we investigate an unmanned aerial vehicle equipped with a STAR-RIS (STAR-RIS-UAV) aided wireless communications for multi-user networks. Energy splitting (ES) and mode switching (MS) protocols are considered to control the reflection and transmission coefficients of STAR-RIS elements. To maximize the sum rate of the STAR-RIS-UAV aided coordinated multipoint cellular system for multi-user networks, the corresponding beamforming vectors as well as transmitted and reflected coefficients matrices are optimized. Specifically, instead of adopting the alternating optimization, we design an iteration method to optimize all variables for both ES and MS protocols at the same time. Simulation results reveal that STAR-RIS-UAV aided wireless communication system has a much higher sum rate than the system with conventional RIS or without RIS. Furthermore, the proposed structure is more flexible than a fixed STAR-RIS and could greatly promote the sum rate. Copyright © 2023, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Regulation of Corn Starch on the Properties of Tremella Polysaccharide-Egg White Protein-Orange Juice Composite Gel And Its Application in 3d Printing

SSRN

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SSRN 2024年

作者： Liu, Lili Shao, Beibei Yang, Wanlin Cheng, Weiwei Ding, Yue Xiao, Feng College of Food and Bioengineering National Experimental Teaching Demonstration Center for Food Processing and Security Henan Engineering Technology Research Center of Food Raw Materials International Joint Laboratory of Food Processing and Quality Safety Control of Henan Province Henan Engineering Technology Research Center of Food Microbiology Henan University of Science and Technology Luoyang471023 China School of instrument Science and Opto-Electronics Engineering Beijing Information Science and Technology University Beijing100192 China

The purpose of this paper was to explore the regulation of corn starch (CS) on tremella polysaccharide-egg white protein-orange juice (TFP-EWP-OJ) composite gel to develop a new 3D printing material. The effects of CS concentration on the characterisation of TFP-EWP-OJ composite gel were investigated. The results showed that the addition of CS improved the rheological property, WHC and TPA of TFP-EWP-OJ composite gel. This meant that the addition of CS gave the TFP-EWP-OJ composite gel better hardness, viscosity and flow properties. In addition, the network structure of the TFP-EWP-OJ composite gel was more compact as the concentration of CS increased and no new covalent bonds are formed between the two. The results of 3D printing showed that the cylindricity printed with TFP-EWP-OJ composite gel with 0.12 g/mL CS added had the best 3D printing structure and highest printing accuracy at 1.2 mm nozzle diameter and 35 mm/s printing speed. © 2024, The Authors. All rights reserved.

关键词： Citrus fruits

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Autoregressive Queries for Adaptive Tracking with Spatio-Temporal Transformers

Autoregressive Queries for Adaptive Tracking with Spatio-Tem...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Jinxia Xie Bineng Zhong Zhiyi Mo Shengping Zhang Liangtao Shi Shuxiang Song Rongrong Ji Key Laboratory of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University Guilin China Guangxi Key Lab of Multi-Source Information Mining & Security Guangxi Normal University Guilin China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University School of Computer Science and Technology Harbin Institute of Technology Media Analytics and Computing Lab School of Informatics Xiamen University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

The rich spatio-temporal information is crucial to capture the complicated target appearance variations in visual tracking. However, most top-performing tracking algorithms rely on many hand-crafted components for spatio-temporal information aggregation. Consequently, the spatio-temporal information is far away from being fully explored. To alleviate this issue, we propose an adaptive tracker with spatio-temporal transformers (named AQA-Track), which adopts simple autoregressive queries to effectively learn spatio-temporal information without many hand-designed components. Firstly, we introduce a set of learnable and autoregressive queries to capture the instantaneous target appearance changes in a sliding window fashion. Then, we design a novel attention mechanism for the interaction of existing queries to generate a new query in current frame. Finally, based on the initial target template and learnt autoregressive queries, a spatio-temporal information fusion module (STM) is designed for spatiotemporal formation aggregation to locate a target object. Benefiting from the STM, we can effectively combine the static appearance and instantaneous changes to guide robust tracking. Extensive experiments show that our method significantly improves the tracker's performance on six popular tracking benchmarks: LaSOT, LaSOT ext , TrackingNet, GOT-10k, TNL2K, and UAV123. Code and models will be https://***/orgs/GXNU-ZhongLab.

关键词： Adaptation models Visualization Computer vision Target tracking Computational modeling Transformers Market research

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Size-Invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection

arXiv

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arXiv 2024年

作者： Li, Feiran Xu, Qianqian Bao, Shilong Yang, Zhiyong Cong, Runmin Cao, Xiaochun Huang, Qingming Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Science Beijing Jiaotong University Beijing China School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Cyber Science and Tech. Sun Yat-Sen University Shenzhen Campus China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

This paper explores the size-invariance of evaluation metrics in Salient Object Detection (SOD), especially when multiple targets of diverse sizes co-exist in the same image. We observe that current metrics are size-sensitive, where larger objects are focused, and smaller ones tend to be ignored. We argue that the evaluation should be size-invariant because bias based on size is unjustified without additional semantic information. In pursuit of this, we propose a generic approach that evaluates each salient object separately and then combines the results, effectively alleviating the imbalance. We further develop an optimization framework tailored to this goal, achieving considerable improvements in detecting objects of different sizes. Theoretically, we provide evidence supporting the validity of our new metrics and present the generalization analysis of SOD. Extensive experiments demonstrate the effectiveness of our method. The code is available at https://***/Ferry-Li/SI-SOD. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Experimental Study on Target Localization for DTMB-Based Passive Bistatic Radar 3rd

Experimental Study on Target Localization for DTMB-Based Pas...

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3rd EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2021

作者： Qian, Jiachuan Li, Haijie Zhu, Huijie Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China The 36th Research Institute of China Electronics Technology Group Corporation Jiaxing314033 China Huaxin Consulting and Designing Institute Co. Ltd. Hangzhou China

ISBN: (纸本)9783030901950

This paper introduces the target localization experiment using the digital television terrestrial broadcasting (DTMB) signal. Firstly, the feasibility and advantages of DTMB signal as an external illumination source signal are analyzed. Then the ambiguity function of DTMB signal is analyzed, as well as its distance and Doppler resolution. ECA algorithm is introduced to suppress direct wave and multipath clutter. In order to obtain the positioning results of target, the array antenna is used as the direction-finding antenna to measure the azimuth angle of target. Finally, the target localization experiment based on DTMB signal is designed, and the localization information of target is determined by combining the actual position of TV Tower and receiver in two dimensions. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Clutter (information theory)

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Remote Attestation for Intelligent Electronic Devices in Smart Grid Based on Trusted Level Measurement

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Chinese Journal of Electronics 2020年第3期29卷 437-446页

作者： WANG Yong LI Jun'e CHEN Xiong LIN Hai YU Fajiang LUO Jianbo Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of EducationSchool of Cyber Science and Engineering Wuhan University NARI Group Corporation State Grid Electric Power Research Institute NARI Technology Co.Ltd. State Key Laboratory of Smart Grid Protection and Control

To reduce the implementation complexity and excessive overhead caused by remote attestation,we propose a new remote attestation scheme based on trusted level measurement considering the limited system resources of the Intelligent electronic devices(IEDs) in smart grid. In this scheme, a lightweight trusted level measurement mechanism is designed, and a new dynamic weighted multi-classifier integration method based on Binary tree Support vector machine(BT-SVM) is proposed. The trusted level of configuration information and running state of an IED are measured through trusted third party. The measurement parameters and attestation period are dynamically adjusted according to different trusted levels of an IED, so that reducing computational overhead and communication delays in remote attestation process. Analysis and experiments show that the proposed scheme can enhance the security of IEDs in smart grid by occupying a small amount of computation and communication resources.

关键词： Smart grid Intelligent electronic devices(IEDs) Remote attestation Trusted level measurement

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Automatic Smart Contract Generation with Knowledge Extraction and Unified Modeling Language 7th

Automatic Smart Contract Generation with Knowledge Extracti...

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7th International Conference on Smart Computing and Communication, SmartCom 2022

作者： Ran, Peiyun Liu, Mingsheng Zheng, Jianwu Bhuiyan, Zakirul Alam Li, Jianhua Li, Gang Yu, Shiyuan Wang, Lifeng Tang, Song Zhao, Peng School of Cyberspace Security of Beihang University Beijing China Shijiazhuang Institute of Railway Technology Hebei Shijiazhuang050041 China Key Laboratory of Traffic Safety and Control of Hebei Province Shijiazhuang China School of Transportation Shijiazhuang Tiedao University Hebei Shaoxing China Department of Computer and Information Sciences Fordham University JMH 334 E Fordham Road BronxNY10458 United States School of Information Science and Technology Shijiazhuang TieDao University No. 17 East North Second Ring Road Changan District Shijiazhuang China Co. Ltd. Beijing China Beijing Public Security Burea Beijing China Hebei Huaye Jike Information Technology Co. Ltd. Shijiazhuang China Institute of Applied Mathematics of Hebei Academy of Sciences Shijiazhuang China The First Hospital of Hebei Medical University Shijiazhuang China

ISBN: (纸本)9783031281235

Since the launch of Ethereum in 2013, the smart contract has been a momentous part of the blockchain systems due to its character of automatic execution. The generation of smart contracts has also attracted extensive attention from the academic community. However, the preparation and generation of smart contracts are still mainly manual so far, which limits the scalability of the smart contracts. In this paper, we put forward a new method to generate smart contracts automatically based on knowledge extraction and Unified Modeling Language (UML), which can significantly accelerate the generation of smart contracts. We will describe this method in more detail based on the logistics supply chain. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smart contract

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引用

6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Xie, Yifan Zhou, Wenan Hu, Huamiao Lu, Zhicheng Wu, Mengyuan School of Computer Science Beijing University of Posts and Telecommunications Beijing China Science and Technology on Communication Information Security Control Laboratory Beijing China

ISBN: (纸本)9781728186351

Code similarity detection is one of the important means to maintain the healthy development of the software eco-environment. Early code similarity detection method is mainly based on the code attribute measurement technology, this method can quickly detect more obvious similar parts on small-scale code datasets, but when faced with large-scale datasets or code segments with similar syntax and semantics, the detection performance is not effective. The new code similarity detection technology based on tree-structure representation and machine learning can adapt to different data changes, thus providing new solutions. This paper proposes a new detection method that combines the abstract syntax tree (AST) structure and unsupervised clustering, this new method can improve the detection efficiency of code clustering analysis, because it not only considers the syntax and semantic information of the code, but also reduces the workload of code data preprocessing through unsupervised clustering. © 2020 IEEE.

关键词： Cluster analysis

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