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2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum, AIBDF 2022

作者： Zhang, Hua Wang, Jiong College of Computer and Control Engineering Minjiang University China

ISBN: (纸本)9781510663107

Different from source coding, which only emphasizes coding efficiency, fault-tolerant coding adds some redundant information during coding to strengthen the ability of error resistance, so as to obtain the best gain with the least redundancy. Therefore, the application of fault-tolerant coding in the repair of mobile cache system of satellite Internet of Things can effectively improve the security of information storage of satellite Internet of Things. Based on this, this paper introduces the repair method of mobile cache system of satellite Internet of Things based on fault-tolerant coding from the aspects of data deployment and data collection, so as to repair the invalid data in time and ensure the integrity and availability of the saved data. At the same time, a specific method to optimize its system parameters is proposed. The repair of mobile cache system of satellite Internet of Things based on fault-tolerant coding can effectively solve the disadvantages of low price and short service time of sensor node terminal equipment in Internet of Things, and avoid problems such as data storage failure or performance weakening of cache communication system caused by sensor leaving satellite coverage and power exhaustion, so as to provide corresponding reference for the development of satellite Internet of Things. © 2023 SPIE.

关键词： Internet of things

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Learnable three-dimensional Gabor convolutional network with global affinity attention for hyperspectral image classification

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Chinese Physics B 2022年第12期31卷 118-135页

作者： Hai-Zhu Pan Mo-Qi Liu Hai-Miao Ge Qi Yuan College of Computer and Control Engineering Qiqihar UniversityQiqihar 161000China College of Telecommunication and Electronic Engineering Qiqihar UniversityQiqihar 161000China

Benefiting from the development of hyperspectral imaging technology,hyperspectral image(HSI)classification has become a valuable direction in remote sensing image ***,researchers have found a connection between convolutional neural networks(CNNs)and Gabor ***,some Gabor-based CNN methods have been proposed for HSI ***,most Gabor-based CNN methods still manually generate Gabor filters whose parameters are empirically set and remain unchanged during the CNN learning ***,these methods require patch cubes as network *** patch cubes may contain interference pixels,which will negatively affect the classification *** address these problems,in this paper,we propose a learnable three-dimensional(3D)Gabor convolutional network with global affinity attention for HSI *** precisely,the learnable 3D Gabor convolution kernel is constructed by the 3D Gabor filter,which can be learned and updated during the training ***,spatial and spectral global affinity attention modules are introduced to capture more discriminative features between spatial locations and spectral bands in the patch cube,thus alleviating the interfering pixels *** results on three well-known HSI datasets(including two natural crop scenarios and one urban scenario)have demonstrated that the proposed network can achieve powerful classification performance and outperforms widely used machine-learning-based and deep-learning-based methods.

关键词： image processing remote sensing 3D Gabor filter neural networks global affinity attention

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Contrastive Consensus Graph Learning for Multi-View Clustering

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IEEE/CAA Journal of Automatica Sinica 2022年第11期9卷 2027-2030页

作者： Shiping Wang Xincan Lin Zihan Fang Shide Du Guobao Xiao the College of Computer and Data Science Fuzhou UniversityFuzhou 350108China the College of Computer and Control Engineering Minjiang UniversityFuzhou 350108China

Dear Editor,This letter proposes a contrastive consensus graph learning model for multi-view *** are usually built to outline the correlation between multi-model objects in clustering task,and multiview graph clusteri... 详细信息

关键词： letter integrate property

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Intelligent Orchestrating of IoT Microservices Based on Reinforcement Learning

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Chinese Journal of Electronics 2022年第5期31卷 930-937页

作者： WU Yuqin SHEN Congqi CHEN Shuhan WU Chunming LI Shunbin WEI Ruan College of Computer Science and Technology Zhejiang University College of Information and Electrical Engineering Ningde Normal University Zhejiang Lab College of Control Science and Engineering Zhejiang University

With the recent increase in the number of Internet of things(IoT) services, an intelligent scheduling strategy is needed to manage these services. In this paper, the problem of automatic choreography of microservices in IoT is explored. A type of reinforcement learning(RL) algorithm called TD3 is used to generate the optimal choreography policy under the framework of a softwaredefined network. The optimal policy is gradually reached during the learning procedure to achieve the goal, despite the dynamic characteristics of the network environment. The simulation results show that compared with other methods, the TD3 algorithm converges faster after a certain number of iterations, and it performs better than other non-RL algorithms by obtaining the highest reward. The TD3 algorithm can effciently adjust the traffic transmission path and provide qualified IoT services.

关键词： software-defined network telecommunication scheduling intelligent orchestrating nonRL algorithms reinforcement learning software defined networking optimal choreography policy reinforcement learning algorithm Internet of things services network environment IoT microservices TD3 algorithm traffic transmission path Internet of Things qualified IoT services intelligent scheduling strategy dynamic characteristics

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A spatio-temporal multi-scale fusion algorithm for pine wood nematode disease tree detection

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Journal of Forestry Research 2024年第6期35卷 267-278页

作者： Chao Li Keyi Li Yu Ji Zekun Xu Juntao Gu Weipeng Jing College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040People’s Republic of China Heilongjiang Province Cyberspace Research Center Harbin 150090People’s Republic of China

Pine wood nematode infection is a devastating *** aerial vehicle(UAV)remote sensing enables timely and precise ***,UAV aerial images are challenged by small target size and complex sur-face backgrounds which hinder their effectiveness in *** address these challenges,based on the analysis and optimization of UAV remote sensing images,this study developed a spatio-temporal multi-scale fusion algorithm for disease *** multi-head,self-attention mechanism is incorporated to address the issue of excessive features generated by complex surface backgrounds in UAV *** enables adaptive feature control to suppress redundant information and boost the model’s feature extraction *** SPD-Conv module was introduced to address the problem of loss of small target feature information dur-ing feature extraction,enhancing the preservation of key ***,the gather-and-distribute mechanism was implemented to augment the model’s multi-scale feature fusion capacity,preventing the loss of local details during fusion and enriching small target feature *** study established a dataset of pine wood nematode disease in the Huangshan area using DJI(DJ-Innovations)*** results show that the accuracy of the proposed model with spatio-temporal multi-scale fusion reached 78.5%,6.6%higher than that of the benchmark *** upon the timeliness and flexibility of UAV remote sensing,the pro-posed model effectively addressed the challenges of detect-ing small and medium-size targets in complex backgrounds,thereby enhancing the detection efficiency for pine wood nematode *** facilitates early preemptive preser-vation of diseased trees,augments the overall monitoring proficiency of pine wood nematode diseases,and supplies technical aid for proficient monitoring.

关键词： Pine wood nematode disease UAV remote sensing Object detection Deep learning YOLOv8

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Fuzzy-Inverse-Model-Based Networked Tracking control Frameworks of Time-Varying Signals

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1708-1710页

作者： Shiwen Tong Dianwei Qian Keya Yuan Dexin Liu Yuan Li Jiancheng Zhang the College of Robotics Beijing Union UniversityBeijing 100101China the School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China

Dear Editor,Tracking control in networked environment is a very challenging problem due to the contradiction of rapid response to the time-varying signal and the inevitable delay introduced by networks. This letter has proposed several fuzzy-inverse-model-based network tracking control frameworks which are helpful in handling the system with nonlinear dynamics and uncertainties.

关键词： contradiction letter inverse

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Radar style transfer for metric robot localisation on lidar maps

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CAAI Transactions on Intelligence Technology 2023年第1期8卷 139-148页

作者： Huan Yin Yue Wang Jun Wu Rong Xiong College of Control Science and Engineering Zhejiang UniversityHangzhouChina Department of Electronic and Computer Engineering Hong Kong University of Science and TechnologyKowloonHong KongChina

Lidar and visual data are affected heavily in adverse weather conditions due to sensing mechanisms,which bring potential safety hazards for vehicle *** sensing is desirable to build a more robust navigation *** this paper,a cross-modality radar localisation on prior lidar maps is ***,the proposed workflow consists of two parts:first,bird's-eye-view radar images are transferred to fake lidar images by training a generative adversarial network *** with online radar scans,a Monte Carlo localisation framework is built to track the robot pose on lidar *** whole online localisation system only needs a rotating radar sensor and a pre-built global lidar *** the experimental section,the authors conduct an ablation study on image settings and test the proposed system on Oxford Radar Robot Car *** promising results show that the proposed localisation system could track the robot pose successfully,thus demonstrating the feasibility of radar style transfer for metric robot localisation on lidar maps.

关键词： lidar local maps

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EFFNet: Semantic Segmentation Network for Enhanced Feature Fusion in Traffic Scenes 3

EFFNet: Semantic Segmentation Network for Enhanced Feature F...

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3rd International Conference on computer Graphics, Image, and Virtualization, ICCGIV 2023

作者： Zhang, Shiwei Liu, Qicheng College of Computer and control engineering Yantai University Yantai China

ISBN: (纸本)9781510671720

Semantic segmentation of high-resolution traffic scene images is a challenging task due to complex backgrounds, diverse object shapes, similar appearances of multiple objects, and multi-scale characteristics of the same object. Many existing semantic segmentation networks only perform simple feature fusion when dealing with different object shapes and multi-scale properties of the same object, often failing to provide satisfactory results. To address these issues, we propose an end-to-end multi-scale feature fusion network called EFFNet for traffic scenes semantic segmentation. EFFNet adopts an encoder-decoder structure, where ResNet-34 is used as the backbone network for feature extraction. At each stage of feature extraction, we introduce the Feature Fusion Module for multi-scale information. The Feature Fusion Module fuses the feature maps extracted by the backbone network at different stages, enriching the spatial and semantic information of the feature maps. Through end-to-end training, the accuracy of the segmentation results is significantly improved. We evaluated EFFNet on the traffic datasets Camvid and Cityscapes using a device equipped with a GTX 1650Ti graphics card. The results show that EFFNet achieves Miou scores of 55.3% and 50% on these two datasets, respectively. This indicates that EFFNet outperforms existing methods and demonstrates excellent segmentation accuracy in traffic scenes semantic segmentation tasks. © 2023 SPIE.

关键词： Semantic Segmentation

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Design of temperature and humidity control device for substation terminal cabinet 6

Design of temperature and humidity control device for substa...

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6th IEEE International Conference on Automation, Electronics and Electrical engineering, AUTEEE 2023

作者： Yumu, Chen Jingjing, Su Zihan, Zhang Chengpu, Song Xin, Chen Jiancheng, Sheng Minjiang University College of Computer and Control Engineering Fuzhou China

ISBN: (纸本)9798350305623

Based on the substation outdoor box cabinet in the operation process, which is prone to condensation and overheating, this paper designs a temperature and humidity control device for outdoor box cabinet of substation based on STM32 micro-controller. The device uses STM32 as the main control unit, and uses DHT 11 temperature and humidity sensor to detect the temperature and humidity of the box cabinet, and compare the threshold value to judge the temperature and humidity in the box cabinet and control the heater and fan to effectively drive moisture and heat. © 2023 IEEE.

关键词： Intelligent control outdoor box cabinet STM32 single-chip microcomputer Temperature and humidity

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Near-Source Attack for Isolated Networks with Covert Channel Transmission 10

Near-Source Attack for Isolated Networks with Covert Channel...

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10th IEEE International Conference on Cyber Security and Cloud Computing and 9th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Ruan, Zhiqiang Yang, Yuchen Chen, Lejia Minjiang University College of Computer and Control Engineering Fuzhou China

ISBN: (纸本)9798350312461

This paper investigates a new attack method called "near-source attack". It leverages the broadcast frames of the 802.11 protocol to establish a hidden tunnel and bypass physical isolation networks or air-gapped networks. We first analyze and implement a common technology known as Ghost Tunnel, which allows the attacker to control the target host and transmit information without being detected. However, this method suffers from frame loss, repeated frame, and attack transparency. We then propose an improved solution to deliver malicious programs to the target host using a modified BadUSB hardware device. Once the attackers successfully get in the isolated networks, they can bypass security protection devices and exploit vulnerabilities of communication protocols, so that they can remote control of target devices and hidden data transmission. We further conducted experiments to verify the feasibility and effectiveness of this attack scheme. The results indicate that the attack logic is capable of inducing the target host to engage in covert communication. Finally, we give some defense measures for such attacks. © 2023 IEEE.

关键词： Remote control

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