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Conference on Vehicle control and Intelligence (CVCI)

作者： Wenzhao Tang Wenbin Tang Xiaohong Jiao Yahui Zhang Dongxue Zhang Hebei Key Laboratory of Industrial Computer Control Engineering Yanshan University Qinhuangdao Hebei Province China School of Mechanical Engineering Yanshan University Qinhuangdao China

ISBN: (数字)9798331504892

ISBN: (纸本)9798331504908

This study establishes an acceleration prediction model of the preceding vehicle tailored for cooperative adaptive cruise control (CACC) systems that address the common challenges posed by V2V communication delays or no communication from the preceding vehicle. The designed model integrates a temporal convolutional network (TCN) with the Transformer architecture block to create a sophisticated mechanism for temporal data analysis. This integration leverages the strengths of TCN in capturing spatial features and the multi-attention mechanism of Transformers to enhance the recognition of long-term dependencies in the time series of data. The synergy between these techniques not only effectively narrows the identification gap between short-term and long-term dependencies but also helps to process spatial information for accurate time-series prediction, significantly improving prediction accuracy. Simulations using the NGSIM dataset confirm the model's prediction performance over the traditional model. Further, the potential of the method to solve the communication delay problem is verified, highlighting the effectiveness of TCN and Transformer multi-attention mechanism in improving the CACC capability.

关键词： Adaptation models Accuracy Uncertainty Adaptive systems Time series analysis Vehicular ad hoc networks Predictive models Transformers Delays Cruise control

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2D Indoor Localization Using Multipath Triangles in MIMO Networks

2D Indoor Localization Using Multipath Triangles in MIMO Net...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Shi, Xuesha Tian, Zengshan Li, Ze Zou, Jian Chongqing University of Posts and Telecommunications School of Communications and Information Engineering Chongqing400065 China Ministry of Education Chongqing University of Posts and Telecommunications Key Laboratory of Industrial Internet of Things & Networked Control Chongqing400065 China

ISBN: (纸本)9798350351255

In response to the drawbacks of indoor multi-station joint localization, this paper proposes a high-precision indoor single-station localization technique based on the multipath shape factor (SF). A geometric localization model was constructed using the reflection and direct path. The localization equation was constructed using time of flight (ToF) and angle of arrival (AoA), and the Cramér-Rao lower bound (CRLB) of localization error was derived. Through CRLB, this paper introduced multipath SFs and derived the calculation expression of SFs. However, localization accuracy is affected by observation errors and other factors, and no effective method has been proposed yet. To improve localization accuracy and reduce algorithm complexity, this paper first proposes a compressive sensing multidimensional parameter estimation algorithm based on particle swarm optimization (PSO). Then, this paper proposes a multipath selection algorithm based on the SF. Finally, we conduct the simulation using commercial-grade wireless ray propagation modeling software. The experimental results show that the median location error is around 0.18 m by combining the two algorithms proposed in this paper. © 2024 IEEE.

关键词： Cramer-Rao bounds

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An Improved Fault-Tolerant control and Stabilization for Positive Polynomial Fuzzy Systems

An Improved Fault-Tolerant Control and Stabilization for Pos...

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IEEE International Conference on control Science and Systems engineering (CCSSE)

作者： Ziguang Wang Aiwen Meng Mingxuan Wang Zhiquan Li Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei China College of Electronic and Information Engineering Hebei University Hebei China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

This paper presents an improved analysis method to design a fault-tolerant controller for positive polynomial fuzzy systems based on static output feedback as well as actuator faults. Firstly, inspired by the property of fault matrix, a new approach of controller design is presented, and some constraint conditions are introduced to guarantee the stability conditions and posi-tivity conditions to be convex simultaneously. Furthermore, by comparing with the existing methods, this method not only can eliminate the binding to the input matrix B, but also is able to provide a wider range of stability region. Besides, to enhance the relaxation of the stability analysis, we introduce the up-to-date Taylor series membership functions (TSMFs) approximation method such that the information embedded in the membership functions and the state boundary information can be taken into the stability conditions. As a result, on the strength of Lyapunov stability theory, the stability analysis is performed via sum-of-squares (SOS) approach. Finally, a simulation example is given to illustrate the effectiveness and reliability of the proposed method.

关键词： Fault tolerant systems Fault tolerant control Reliability theory Taylor series Systems engineering and theory Stability analysis Polynomials Output feedback Fuzzy systems Lyapunov methods

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Recent advances in heterogeneous catalysis of solar-driven carbon dioxide conversion

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Journal of Environmental Sciences 2024年第6期140卷 165-182页

作者： Jun Xu Farzaneh Arabpour Roghabadi Ying Luo Vahid Ahmadi Qian Wang Zheng Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuoHenan 454000China Department of Process Engineering Faculty of Chemical EngineeringTarbiat Modares UniversityTehranIran Optoelectronics and Nanophotonics Research Group Faculty of Electrical and Computer EngineeringTarbiat Modares UniversityTehranIran Graduate School of Engineering Nagoya UniversityFuro-choChikusa-kuNagoya 464-8603Japan

Solar-driven carbon dioxide(CO_(2))conversion including photocatalytic(PC),photoelectrochemical(PEC),photovoltaic plus electrochemical(PV/EC)systems,offers a renewable and scalable way to produce fuels and high-value chemicals for environment and energy *** review summarizes the basic fundament and the recent advances in the field of solar-driven CO_(2)*** the visible-light absorption is an important strategy to improve solar energy conversion *** separation and migration of photogenerated charges carriers to surface sites and the surface catalytic processes also determine the photocatalytic *** engineering including co-catalyst loading,defect engineering,morphology control,surface modification,surface phase junction,and Z-scheme photocatalytic system construction,have become fundamental strategies to obtain high-efficiency *** to photocatalysis,these strategies have been applied to improve the conversion efficiency and Faradaic efficiency of typical PEC *** PV/EC systems,the electrode surface structure and morphology,electrolyte effects,and mass transport conditions affect the activity and selectivity of electrochemical CO_(2)***,the challenges and prospects are addressed for the development of solar-driven CO_(2)conversion system with high energy conversion efficiency,high product selectivity and stability.

关键词： Solar-driven CO_(2)reduction Photocatalytic system Photoelectrochemical system Photovoltaic plus electrochemical system Surface/interface engineering

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Semi-Cervixseg: A Multi-Stage Training Strategy for Semi-Supervised Cervical Segmentation

Semi-Cervixseg: A Multi-Stage Training Strategy for Semi-Sup...

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IEEE International Symposium on Biomedical Imaging

作者： Juntao Jiang Yali Bi Chunlin Zhou Yong Liu Jiangning Zhang College of Control Science and Engineering Zhejiang University College of Computer and Information Science Southwest University State Key Laboratory of Industrial Control Technology Zhejiang University Youtu Lab Tencent

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Image segmentation plays a critical role in computer-aided diagnosis and treatment planning for cervical cancer. Obtaining a large number of labeled images for supervised cervical segmentation is often labor-intensive and time-consuming. In this paper, we propose a multi-stage semi-supervised learning framework (Semi-CervixSeg) to address the cervical seg-mentation task in ultrasound images for Fetal Ultrasound Grand Challenge: Semi-Supervised Cervical Segmentation in ISBI 2025. Specifically, in the initial stage, we utilize unlabeled data through a multi-view random augmentation strategy, using consistency constraints and a contrastive learning method. Subsequently, a progressive multi-stage training strategy is adopted to generate and optimize pseudo-labels, further improving segmentation results. Experimental re-sults demonstrate that the proposed method significantly im-proves segmentation performance compared with supervised methods. As a technical report for the challenge, this paper elaborates on our methodology and experimental findings in detail. The code can be accessed at h t t p s: / / g i t hub. com/juntaoJianggavin/Semi-CervixSeg.

关键词： Training Image segmentation Ultrasonic imaging Codes Contrastive learning Semisupervised learning Writing Data models Planning computer aided diagnosis

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Study on Landslide Susceptibility Evaluation Based on Improved Multivariable Weighted Model: A Case Study of Lushan County, China 3

Study on Landslide Susceptibility Evaluation Based on Improv...

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3rd IEEE International Conference on Software engineering and Artificial Intelligence, SEAI 2023

作者： Zhao, Li Duan, Gonghao Wuhan Institute of Technology School of Computer Science and Engineering Wuhan China Automation for Complex Systems Hubei Key Laboratory of Advanced Control and Intelligent Wuhan China

ISBN: (纸本)9798350337952

The evaluation of regional geological hazard susceptibility is of great significance to the prevention and control of geological hazard. In this paper, the "4-20"Lushan earthquake disaster area as the research area, combined with GIS and characteristics of the research area, through correlation analysis, selected 9 influencing factors as the evaluation factors. The study was conducted using a weighted information volume-logistic regression model (WI-LR). The results were classified into five sensitivity levels: very low, low, medium, high and very high. The results show that the landslide prone areas in Lushan County are concentrated in the area below the middle of the county seat, mostly near rivers, faults and areas with peak acceleration greater than 0.4. Among them, WI-LR model (AUC=0.918) > deterministic factor model (CF =0.908) > weighted information quantity model (WI) (AUC=0.896) > information quantity model I (AUC=0.853) > information quantity logistic regression model I-LR (AUC=0.799). It indicates that WI-LR model has high evaluation accuracy. © 2023 IEEE.

关键词： Hazards

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OSAP‐Loss:Efficient optimization of average precision via involving samples after positive ones towards remote sensing image retrieval

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1191-1212页

作者： Xin Yuan Xin Xu Xiao Wang Kai Zhang Liang Liao Zheng Wang Chia‐Wen Lin School of Computer Science and Technology Wuhan University of Science and TechnologyWuhanChina Hubei Province Key Laboratory of Intelligent Information Processing and Real‐time Industrial System Wuhan University of Science and TechnologyWuhanChina Nanyang Technological University SingaporeSingapore School of Computer Science Wuhan UniversityWuhanChina Department of Electrical Engineering Industrial Technology Research InstituteNational Tsing Hua UniversityHsinchuChina

In existing remote sensing image retrieval(RSIR)datasets,the number of images among different classes varies dramatically,which leads to a severe class imbalance *** studies propose to train the model with the ranking‐based metric(e.g.,average precision[AP]),because AP is robust to class ***,current AP‐based methods overlook an important issue:only optimising samples ranking before each positive sample,which is limited by the definition of AP and is prone to local *** achieve global optimisation of AP,a novel method,namely Optimising Samples after positive ones&AP loss(OSAP‐Loss)is proposed in this ***,a novel superior ranking function is designed to make the AP loss differentiable while providing a tighter upper ***,a novel loss called Optimising Samples after Positive ones(OSP)loss is proposed to involve all positive and negative samples ranking after each positive one and to provide a more flexible optimisation strategy for each ***,a graphics processing unit memory‐free mechanism is developed to thoroughly address the non‐decomposability of AP *** experimental results on RSIR as well as conventional image retrieval datasets show the superiority and competitive performance of OSAP‐Loss compared to the state‐of‐the‐art.

关键词： computer vision image retrieval metric learning

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A Study of Data Augmentation for Imbalance Problem in Network Traffic 3

A Study of Data Augmentation for Imbalance Problem in Networ...

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3rd International Conference on Blockchain Technology and Information Security, ICBCTIS 2023

作者： Wang, Xu Sun, Shimin Han, Li School of Computer Science and Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Autonomous Intelligent Technology and System School of Software Tiangong University Tianjin China School of Computer Science and Engineering Tianjin University of Technology National Engineering Laboratory for Computer Virus Prevention and Control Technology Tianjin China

ISBN: (纸本)9798350340402

The complexity and diversity of smart grid systems increase the likelihood of anomalies in communications between devices in the system, and how these anomalies are detected is critical to the security of the grid system. However, the distribution of traffic types in the grid is often highly unbalanced, with the total amount of normal traffic data often far outweighing the anomalous data. This imbalance compromises the effectiveness of the detection model and poses a significant threat to the overall security of the grid This paper improves on traditional conditional generation adversarial neural networks and designs a new approach to overcome this obstacle and enhance the security of smart grid systems. In the generator part, the spatial features of the data are captured by convolutional neural networks, and the temporal features of the data are captured by gated recurrent units. By integrating these two components into the generative network we can generate synthetic data with both temporal and spatial features, thus enhancing the minority class samples. By incorporating the augmented minority data into the training process, the proposed approach enables the detection model to understand the distribution of features of the minority anomaly samples more accurately. This improved learning accuracy translates into improved model performance, resulting in higher detection rates for Previously under-represented anomalies. In addition, our approach effectively addresses the inherent bias towards traffic types with higher flows typically observed in asymmetric datasets, thus providing a more equitable and comprehensive security solution for smart grid systems. © 2023 IEEE.

关键词： Anomaly detection

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Grid-Metaverse: The Path From Digital Twins and Prototype Tests on DC Microgrids

Grid-Metaverse: The Path From Digital Twins and Prototype Te...

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Ma, Wenxuan Liu, Mengxiang Hong, Guangrun Yang, Shuo Deng, Ruilong Zhejiang University State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Hangzhou310027 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom

ISBN: (纸本)9798350333336

With the development of cutting-edge technologies and the efforts of business giants, Metaverse is becoming increasingly reachable. In addition to the fields of healthcare, education and cultural tourism, Metaverse will also have a profound impact on the power grid. The digital twin (DT) is regarded as the foundation of Metaverse, but its high cost hinders the broad application of DTs in power grids. In this paper, we propose a path to build the DTs in the direct current (DC) microgrid, which is a representative block in the future power grid with the penetration of renewable energy sources, forming Grid-Metaverse that can significantly reduce the cost and improve the interactivity. A model-based DT, which is originated from the physical model, and a data-driven DT, using the graph neural network with the data from the model-based one, are built together to illustrate this path and to show their roles in the Grid-Metaverse. Moreover, in the prototype tests, the threats of denial-of-service (DoS) and false data injection (FDI) attacks are validated through the developed DTs. © 2023 IEEE.

关键词： Renewable energy resources

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MATS-DROP: A HIGHLY SENSITIVE HIGH-THROUGHPUT SINGLE-CELL WHOLE TRANSCRIPTOMIC SEQUENCING METHOD 26

MATS-DROP: A HIGHLY SENSITIVE HIGH-THROUGHPUT SINGLE-CELL WH...

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26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Cao, Wenjian Pan, Yating Mu, Ying Zhu, Qiangyuan Research Center for Analytical Instrumentation College of Control Science and Engineering State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Research Center for Analytical Instrumentation College of Life Sciences State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781733419048

The unprecedented single-cell resolution provided by single-cell RNA sequencing (scRNA-seq) powered the progress of biomedical research, leading to revolutionary discoveries. However, current high-throughput scRNA-seq methods are limited by sensitivity and can only detect polyadenylated transcripts. Utilizing polymer-tethered degenerate primer and droplet-based microfluidics, we developed a high-throughput scRNA-seq method with high sensitivity and whole transcriptomic detection capability. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Microfluidics

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