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13th IEEE International Conference on CYBER Technology in Automation, control, and intelligent Systems, CYBER 2023

作者： Han, Qiaoni Cheng, Guowen Tang, Zhenning Liu, Chang School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Center for Biomedical Engineering School of Information Science and Technology Fudan University Shanghai200433 China

ISBN: (纸本)9798350315196

In order to mitigate the adverse impact of denial of service (DoS) attacks, this work designs a parameter self-tuning controller based on fuzzy rules for vehicle platoons with vehicle-to-vehicle (V2V) communications. Aiming at achieving the cooperative adaptive cruise control (CACC) of the vehicles with a required inter-vehicle distance and the same velocity, while considering the possible DoS attacks, we propose a parameter self-tuning longitudinal controller combining linear control and fuzzy control to enhance the stability and resilience of the platoon systems. Firstly, by analyzing the dynamic characteristics of vehicles and the mechanism of DoS attacks, we establish the dynamic model of vehicle platoons and model the impact of random DoS attacks as a constant data transmission delay, whose probability distribution can be defined using the Bernoulli random variable. Then, a linear controller based on fuzzy control is designed for longitudinal control to guarantee that the platoon keeps a reference velocity and the specified inter-vehicle distance under DoS attacks. Finally, thorough simulations are performed and the detailed results show the performance of the secure longitudinal control scheme for vehicle platoons in terms of stability and security. © 2023 IEEE.

关键词： Fuzzy control

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Research on the Detection of Abnormal Cervical Cells Based on Improved YOLOv7

Research on the Detection of Abnormal Cervical Cells Based o...

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6th International Conference on intelligent Computing and Signal processing (ICSP)

作者： Xuewei Wang Shuang Yuan Lidong Yang Dawei Niu Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Inner Mongolia University of Science and Technology School of Digtial and Intelligence Industry Inner Mongolia China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Cervical cytologic screening is clinically important for the prevention and diagnosis of cervical cancer. Aiming at the many challenges in the detection of abnormal cervical cells, including the difficult detection of small targets of abnormal cervical cells, complex backgrounds, and uneven cell morphology, a detection algorithm for abnormal cervical cells based on improved YOLOv7 was proposed. The algorithm utilizes Deformable Convolutional Networks v2 (DCNv2) that adaptively de-tunes the scale and receptive field size to more effectively cope with the complexity and diversity of cervical cell images. The experimental results show that the improved YOLOv7 algorithm mAP achieves 57.26%, up to 73.88% accuracy, and 46.90% recall on the cervical abnormal cell dataset. Compared with the benchmark model, they increased by 4.07%, 3.39%, and 5.69%, respectively.

关键词： Accuracy Sensitivity Shape Prevention and mitigation Signal processing algorithms Signal processing Feature extraction Convolutional neural networks Detection algorithms Cervical cancer

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Bearing-Based Target Entrapping control of Multiple Uncertain Agents With Arbitrary Maneuvers

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IFAC-PapersOnLine 2023年第2期56卷 8821-8826页

作者： Haifan Su Ziwen Yang Shanying Zhu Cailian Chen Wenbin Yu Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

This paper is concerned with bearing-based cooperative target entrapping control of multiple uncertain agents with arbitrary maneuvers including shape deformation, rotations, scalings, etc. A leader-follower structure is used, where the leaders move with the predesigned trajectories, and the followers are steered by an estimation-based control method, integrating a distance estimator using bearing measurements and a stress matrix-based formation controller. The signum functions are used to compensate for the uncertainties so that the agents’ accelerations can be piecewise continuous and bounded to track the desired dynamics. With proper design of the leaders’ trajectories and a geometric configuration, an affine matrix is determined so that the inter-agent relative bearings can be persistently exciting since the bearing rates are related to different weighted combinations of the affine matrix vectors. The asymptotic convergence of the estimation and control error is proved using Filipov properties and cascaded system theories. A sufficient condition for inter-agent collision avoidance is also proposed. Finally, simulation results are given to validate the effectiveness of the method.

关键词： Target entrapping control bearing measurement persistent excitation uncertainty

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Generalized Zero-shot Learning Based on Dual Latent Space Reconstruction

Generalized Zero-shot Learning Based on Dual Latent Space Re...

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2022 International Conference on intelligent Systems, Communications, and Computer Networks, ISCCN 2022

作者： Xu, Yangdongfang Yang, Guan Liu, Xiaoming Liu, Yang School of Computer Science Zhongyuan University of Technology Zhengzhou China Henan Key Laboratory on Public Opinion Intelligent Analysis Zhengzhou China Zhengzhou Key Laboratory of Text Processing and Image Understanding Zhengzhou China School of Telecommunications Engineering Xidian University Xi’an China

ISBN: (纸本)9781510657342

Generalized Zero-Shot Learning (GZSL) is characterized as a training process that comprises visual samples from seen classes and semantic samples from seen and unseen classes, followed by a testing process that classifies visual samples from seen and unseen classes. Existing zero-shot learning (ZSL) approaches suffer from domain shift and information loss issues as a result of class differences between visible and unseen classes, as well as uneven image distribution. In this study, a generalized zero-shot learning strategy based on dual latent space reconstruction (DLR-GZSL) is proposed. The method aims to establish a latent space of shared semantic and visual information, uses dual learning to align different modal representations to alleviate the domain shift problem, uses triplet loss to improve intra-class diversity and inter-class separability of the generated samples, and uses information bottleneck to retain as much valid generated feature information as possible to reduce information loss. Experiments on the CUB, SUN, AWA1, and AWA2 datasets reveal that the suggested method has more accurate than previous methods, demonstrating its effectiveness. © 2022 SPIE.

关键词： Zero-shot learning

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Aggregating Correlation Filter with Multiple Kernels Learning for Robust Visual Object Tracking 22

Aggregating Correlation Filter with Multiple Kernels Learnin...

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8th International Conference on Computing and Artificial Intelligence, ICCAI 2022

作者： Wei, Yanxia Xiao, Hairong Feng, Deying Mu, Jian Yang, Jie School of Mechanical and Automotive Engineering Liaocheng University China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Liaocheng University China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)9781450396110

Recently, Discriminative Correlation Filter based trackers have increasingly become popular in the domain of visual object tracking, which is benefited by their effective and robustness in terms of tracking performance. However, the significant variations of target appearance, such as Occlusion or Deformation, always suppress the performance improvement. Although the multi-feature fusion strategy partly alleviates the above factors, the synthetic scheme also ambiguates the overall presentation ability of multiple features and results in degradation of discriminative power during classification filter learning. In this paper, we present a novel tracking framework based on the correlation filter with multiple kernel learning. Instead of directly integrating different features, we decompose a tracking process into several module, including low-dimension modules and high-dimension modules. The handcraft features extracted from low-dimension modules are robust to the small variation of target while the semantic convolutional features from the high-dimension modules can distinguish the target object from the relative complex tracking environment. In addition, we also design a reliability detection mechanism based on the confidence map to accurately measure the important degree of each kernel learning and precisely estimate the target state in the subsequent frames. For verifying our proposed tracker, we conduct extensive experiments on several standard sequence benchmark. Experiment results show that our proposed trackers perform favorably against other state-of-the-art trackers. © 2022 ACM.

关键词： Semantics

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Attn-VAE-GAN:Text-Driven High-Fidelity image Generation Model with Deep Fusion of Self-Attention and Variational Autoencoder

Attn-VAE-GAN:Text-Driven High-Fidelity Image Generation Mode...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chen Yang Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University School of Computer Science and Engineering Chongqing Three Gorges University

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

In the current realm of research on text-to-image (T2I) transformation, the daunting task of translating natural language descriptions into visually realistic images is apparent. This intricate undertaking requires models to deeply comprehend cross-modal information and achieve precise semantic mapping. Despite the commendable progress made by GANs in image synthesis—crafting high-resolution, lifelike visual effects from random noise—persistent challenges like training instability, mode collapse, and fidelity issues persist, prompting the need for innovative *** study introduces an avant-garde text-driven high-fidelity image generation model, labeled as Attn-VAE-GAN. The initial integration of a generator module featuring a fused Self-Attention mechanism empowers the model to thoroughly grasp and accurately capture intricate semantic information from the input text. Moreover, the assimilation of a Variational Autoencoder (VAE) module taps into its latent representation learning prowess to optimize both image quality and diversity. To amplify the realism and detail expression of the generated images, a meticulously designed comprehensive loss function combines intrinsic VAE loss and hinge *** results underscore the substantial enhancement achieved by the Attn-VAE model in both the quality and diversity of the generated images across diverse publicly available benchmark datasets.

关键词： Training Representation learning Measurement Technological innovation image synthesis Semantics Neural networks

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NPIPVis:A visualization system involving NBA visual analysis and integrated learning model prediction

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Virtual Reality & intelligent Hardware 2022年第5期4卷 444-458页

作者： Zhuo SHI Mingrui LI Meng WANG Jing SHEN Wei CHEN Xiaonan LUO Department of Art and Design University of Guilin Electronic TechnologyGuilin 541004China Department of Computer and Information Security University of Guilin Electronic TechnologyGuilin 541004China Department of Guangxi Key Laboratory of Image and Graphic Intelligent Processing University of Guilin Electronic TechnologyGuilin 541004China Department of State Key Laboratory of CAD&CG University of ZhejiangHangzhou 310058China

Background Data-driven event analysis has gradually become the backbone of modern competitive sports analysis. Competitive sports data analysis tasks increasingly use computer vision and machine-learning models for intelligent data analysis. Existing sports visualization systems focus on the player–team data visualization, which is not intuitive enough for team season win–loss data and game time-series data visualization and neglects the prediction of all-star players. Methods This study used an interactive visualization system designed with parallel aggregated ordered hypergraph dynamic hypergraphs, Calliope visualization data story technology,and i Storyline narrative visualization technology to visualize the regular statistics and game time data of players and teams. NPIPVis includes dynamic hypergraphs of a team’s wins and losses and game plot narrative visualization components. In addition, an integrated learning-based all-star player prediction model, SRR-voting, which starts from the existing minority and majority samples, was proposed using the synthetic minority oversampling technique and Random Under Sampler methods to generate and eliminate samples of a certain size to balance the number of allstar and average players in the datasets. Next, a random forest algorithm was introduced to extract and construct the features of players and combined with the voting integrated model to predict the all-star players, using GridSearch CV, to optimize the hyperparameters of each model in integrated learning and then combined with five-fold cross-validation to improve the generalization ability of the model. Finally, the SHapley Additive ex Planations(SHAP) model was introduced to enhance the interpretability of the model. Results The experimental results of comparing the SRR-voting model with six common models show that the accuracy, F1-score, and recall metrics are significantly improved, which verifies the effectiveness and practicality of the SRR-voting model. Conc

关键词： Sports visualization Parallel aggregated ordered hypergraph Calliope IStoryline Integrated learning SHAP model

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Edible prodelphinidins that improve postprandial hyperglycemia were discovered in Chinese bayberry(Myrica rubra *** Zucc.)fruits

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Food Science and Human Wellness 2025年第3期14卷 1008-1016页

作者： Yi Wang Laiming Zhang Jiaxiong Wu Chengxiao Yu Xingqian Ye Haibo Pan Shiguo Chen College of Biosystems Engineering and Food Science National-Local Joint Engineering Laboratory of Intelligent Food Technology and EquipmentZhejiang Key Laboratory for Agro-food ProcessingIntegrated Research Base of Southern Fruit and Vegetable Preservation TechnologyZhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality ControlZhejiang UniversityHangzhou 310058China Ningbo Research Institute Zhejiang UniversityNingbo 315100China Zhejiang University Zhongyuan Institute Zhengzhou 450000China Innovation Center of Yangtze River Delta Zhejiang UniversityJiaxing 314102China

Plant polyphenols are potential substitutes for clinicalα-glucosidase *** previous studies indicated that prodelphinidins from Chinese bayberry leaves(BLPs)have strongerα-glucosidase inhibitory activity than other common polyphenols,but they have no safe history of *** is a reasonable prospect that prodelphinidins from Chinese bayberry fruits(BFPs)can improve postprandial hyperglycemia,though known active components are only myricetin and ***,the aim of this study was to analyze structure and hypoglycemic effect of BFPs of“Biqi”(BQPs)and“Dongkui”(DKPs)cultivars,and compare their difference with *** contents of BQPs and DKPs were(221.73±0.60)and(136.82±4.33)mg epicatechin(EC)equivalents/g dry weight,*** most subunits were epigallocatechin gallate along with a small amount of epigallocatechin,epicatechin gallate and EC connected by B-type linkages and a small portion of A-type linkages with mean polymerization degree of 4.25 and 4.08,***,BQPs and DKPs wereα-glucosidase inhibitors with half inhibitory concentration of 11.91 and 9.47μg/m L respectively,which were significantly stronger than *** could also improve postprandial hyperglycemia of normal mice and high fat diet-induced type II diabetic ***,edible prodelphinidins,which have stronger hypoglycemic effect than BLPs,were first found in Chinese bayberry fruits.

关键词： Chinese bayberry fruit Prodelphinidins Structure α-Glucosidase Postprandial hyperglycemia

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MASS FLOW DETECTION TECHNOLOGY FOR SEED AND FERTILISER PARTICLES AND ITS APPLICATION IN UAV-BASED SPREADING

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INMATEH - Agricultural Engineering 2025年第1期75卷 584-599页

作者： Wang, Yanshuang Song, Cancan Gao, Yongqi Lan, Yubin Wang, Guobin Ming, Rui College of Agricultural Engineering and Food Science Shandong University of Technology Zibo China Shandong University of Technology Sub-center of National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology Zibo China Research of Institute of Ecological Unmanned Farm Shandong University of Technology Zibo China School of Computer and Big Data Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China

The processes of sowing and fertiliser application represent a significant aspect of agricultural production. In order to achieve efficient and precise seeding and fertiliser application, mass flow detection of seed and fertiliser particles can facilitate real-time monitoring and precise decision-making for intelligent seeding and fertiliser application. However, the diversity of seed and fertiliser particle types and particle flow modes presents a challenge for existing detection methods, particularly in meeting the varying operational requirements, especially for particle mass flow detection in low-altitude and high-speed sowing operations of agricultural drones. In such cases, the overlap and flow rate will have a significant impact on the detection results due to the large displacement and the continuous high-throughput dense phase of the particle flow. This paper provides a summary of the existing seed and fertiliser particle mass flow detection techniques and their underlying working principles. It compares the direct detection based on mass with the indirect detection methods based on velocity and concentration, and analyses their respective advantages, disadvantages and applicability. It also explores the possibility of optimising the existing detection methods for the specific needs of agricultural UAVs and considers the potential introduction of cutting-edge science and technology in order to develop an efficient, accurate and convenient detection system to meet the growing market demand. © (2025), (INMA Bucharest). All Rights Reserved.

关键词： Precision agriculture

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Antifungal activity of curcumin-mediated photodynamic inactivation against Fusarium graminearum on maize

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Grain & Oil Science and Technology 2025年第1期8卷 21-31页

作者： Shuliang Dong Lu Chen Shaojie Li Konglong Feng Guang Liu Hao Dong Guizhi Xu Huajian Ou Yang Liu Yong Zhao Jingjing Wang Guangdong Provincial Key Laboratory of Intelligent Food Manufacturing Foshan UniversityFoshan 528225China College of Food Science and Technology Shanghai Ocean UniversityShanghai 201306China Shanghai Sixth People’s Hospital Affiliated to Shanghai JiaoTong University Shanghai 201306China Sericultural&Agri-Food Research Institute Guangdong Academy of Agricultural Sciences/Key Laboratory of Functional Foods Ministry of Agriculture and Rural Affairs/Guangdong Key Laboratory of Agricultural Products ProcessingGuangzhou 510610China College of Light Industry and Food Sciences Zhongkai University of Agriculture and EngineeringGuangzhou 510225China National Technical Center(Foshan)for Quality Control of Famous and Special Agricultural Products Foshan 528225China

The natural curcumin-mediated photodynamic inactivation(PDI)was developed,and its inactivation potency against Fusarium graminearum in vitro and in vivo was systematically investigated by fluorescence probe assay,trypan blue staining,scanning electron microscope(SEM),confocal laser scanning microscopy(CLSM),*** showed that under the irradiation of blue LED,the photosensitizer of curcumin was excited to generate massive reactive oxygen species(ROS)in the cells of ***,and the PDI completely inactivated their mycelia and spores under the treatment of 150μM curcumin and 10.8 J/cm^(2)*** analysis found that the PDI ruptured the cellular microstructures,damaged the cell membrane by increasing its permeability and oxidizing the lipids,degraded the intracellular DNA and proteins inside the spores of ***,the PDI also potently killed>99.99%spores of *** on maize under the treatment of 200μM curcumin and 10.8 J/cm^(2)***,the PDI suppressed the production of zearalenone(ZEN),and residual ZEN could not be detected after the storage of maize for 10 ***,this study systematically explored the inactivation efficiency of curcumin-mediated PDI against both the mycelia and spores of ***,which provides a valid and promising method to control the fungal hazards in grains.

关键词： Fusarium graminearum Photodynamic inactivation(PDI) Spores Mycelia Zearalenone(ZEN)

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