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2024 China Automation Congress, CAC 2024

作者： Zhu, Jinyang Xu, Zhezhuang Lin, Ye College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350368604

Using machine vision for meter reading significantly enhances the efficiency of industrial monitoring. However, meters in outdoor environment are often subject to the noise such as rain and fog, which affect the accuracy of meter readings. Additionally, the meter images and labels under noise are hard to obtain. To address these challenges, We propose a method for pointer meter reading under noise based on virtual data generation. Firstly, We utilize Unity to construct an industrial meter scene, which generates the images of meter under noise and theri labels. Secondly, we develop a U-Net network with an ASPP module, which expands the receptive field of network and enhances the ability of segmentation network to capture global semantic information under noise. Finally, the angular method is used to calculate the meter readings. Experimental results show that this method can effectively read meters under noise in outdoor environments. © 2024 IEEE.

关键词： Virtual addresses

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Semi-supervised learning with GAN for Semantic Segmentation of Wood Defect image

Semi-supervised learning with GAN for Semantic Segmentation ...

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2024 China Automation Congress, CAC 2024

作者： Zheng, Kunxin Zheng, Song Xu, Zhezhuang Lin, Ye Zhu, Yuhang College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798350368604

Automatic defect detection on wood surface is essential for ensuring product quality. Semantic segmentation methods have shown outstanding performance in wood defect detection. However, it is costly to acquire correct pixel-level labels of wood surface defects due to the complicated characteristics. To mitigate the cost of acquiring high-quality datasets, this study proposes a semi-supervised defect detection approach based on generative adversarial networks, which contains a generator and a discriminator. The generator is utilized to generate pixel-level segmentation results of wood defect images. To improve the segmentation performance, the discriminator learns against the generator by judging the goodness of the prediction results and generates supervised signals for the prediction results of unlabeled images. With this learning model, the proposed method can enhance segmentation performance using unlabeled images and alleviate the burden of data annotation. We validate the effectiveness of the proposed approach on a collected dataset of wood defects. Experimental results demonstrate the remarkable performance of our method even when utilizing only a small amount of annotated data. © 2024 IEEE.

关键词： Generative adversarial networks

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Active-IRS-Enabled Energy-Efficiency Optimizations for UAV-Based 6G Mobile Wireless Networks 57

Active-IRS-Enabled Energy-Efficiency Optimizations for UAV-B...

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57th Annual Conference on information Sciences and Systems, CISS 2023

作者： Wang, Fei Zhang, Xi Southwest University Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China Texas AandM University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States

ISBN: (纸本)9781665451819

We propose the novel scheme to solve a multi-objective optimization problem over an unmanned aerial vehicle (UAV) communications system to jointly minimize the energy consumption of the UAV and ground users (GUs). In particular, the UAV communicates with multiple GUs using active intelligent reflecting surfaces (IRSs), which can actively amplify and thus significantly enhance the strengths of reflected signals. We develop an energy minimization scheme based on the multi-objective hierarchical deep reinforcement learning (DRL), by decomposing the formulated optimization problem into two-layered subproblems. By solving the upper-level subproblem, we derive the optimal UAV trajectory and GUs scheduling strategies to minimize the UAV's energy consumption. By solving the lower-level subproblem, we obtain the IRS's phase shifts and amplification factors and GUs' transmit/receive beamforming to minimize the GUs' energy consumption. Finally, we validate and evaluate the proposed schemes through simulations, which show that the UAV's and GUs' energy consumption can be significantly reduced by using the active IRS, when the thermal noise powers at the IRS are much smaller than those at the UAV and GUs. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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In-situ fabrication of vertical heterogeneous nickel diselenide-molybdenum diselenide architectures as bifunctional overall water-splitting electrocatalyst

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Journal of Materials Science & Technology 2024年第10期177卷 256-263页

作者： He Zhou Jingrui Hou Limin Zhang Dezhi Kong Hui Wang Longhui Zeng Zhiwei Ren Tingting Xu Ye Wang Key Laboratory of Material Physics Ministry of EducationSchool of Physics and MicroelectronicsZhengzhou UniversityZhengzhou 450001China Department of Electrical and Computer Engineering University of California at San DiegoSan DiegoCA 92093USA Department of Electronic and Information Engineering The Hong Kong Polytechnic UniversityHung HomKowloon 999077Hong KongChina

Despite the rapid advances in electrocatalysts based on two-dimensional(2D)transition metal dichalco-genides(TMDs)materials,they are subject to serious aggregation,poor conductivity and the presence of inactive basal ***,we have successfully demonstrated the in-situ construction of NiSe_(2)-MoSe_(2) heterostructure arrays on carbon cloth(NiSe_(2)-MoSe_(2)/CC)by a facile two-step hydrothermal *** presence of the synergistic effect in the heterostructures effectively optimizes the poor conductivity and hydrophilicity,and thus enables fast electron transfer,leading to enhanced electrochemical ***-thermore,density functional theory calculations reveal that the electrons redistribution at the heterojunc-tion interface and the reduced Gibbs free energy of hydrogen adsorption for hydrogen evolution reaction(HER)/the Gibbs free energy change value of rate-determining step for oxygen evolution reaction(OER),thus enhancing the HER/OER catalytic ***,the device displays a good performance with a low overpotential of 98 and 310 mV for HER and OER,respectively,and a low cell voltage of 1.59 V for its corresponding electrolyzer(10 mA cm^(-2)).This work presents the high-performance water splitting of bifunctional electrocatalysts based on 2D TMDs materials and offers a novel design concept of interface engineering.

关键词： Bifunctional electrocatalyst Heterostructures Hydrogen/oxygen evolution reaction Water splitting Synergistic effect

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Investigation of degradation and recovery characteristics of NBTI in 28-nm high-k metal gate process

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Chinese Physics B 2023年第12期32卷 628-635页

作者：巩伟泰李闫孙亚宾石艳玲李小进 Shanghai Key Laboratory of Multidimensional Information Processing and the Department of Electrical Engineering East China Normal UniversityShanghai 200241China

Degradation induced by the negative bias temperature instability(NBTI)can be attributed to three mutually uncoupled physical mechanisms,i.e.,the generation of interface traps(ΔV_(IT)),hole trapping in pre-existing gate oxide defects(ΔV_(HT)),and the generation of gate oxide defects(ΔV_(OT)).In this work,the characteristic of NBTI for p-type MOSFET fabricated by using a 28-nm high-k metal gate(HKMG)process is thoroughly *** experimental results show that the degradation is enhanced at a larger stress bias and higher *** effects of the three underlying subcomponents are evaluated by using the comprehensive *** is found that the generation of interface traps dominates the NBTI degradation during long-time NBTI ***,the NBTI parameters of the power-law time exponent and temperature activation energy as well as the gate oxide field acceleration are *** dependence of operating lifetime on stress bias and temperature is also *** is observed that NBTI lifetime significantly decreases as the stress ***,the decrease of charges related to interface traps and hole detrapping in pre-existing gate oxide defects are used to explain the recovery mechanism after stress.

关键词： negative bias temperature instability(NBTI) high-k metal gate(HKMG) threshold voltage shift interface trap gate oxide defect

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Data secure transmission intelligent prediction algorithm for mobile industrial IoT networks

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Digital Communications and Networks 2023年第2期9卷 400-410页

作者： Lingwei Xu Hao Yin Hong Jia Wenzhong Lin Xinpeng Zhou Yong Fu Xu Yu Department of Information Science and Technology Qingdao University of Science and TechnologyQingdao266061China Fujian Key Laboratory of Sensing and Computing for Smart Cities Xiamen UniversityXiamen361005China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control(Minjiang University) Fuzhou350121China Faculty of Information Science and Engineering Ocean University of ChinaQingdao266100China Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center(National Supercomputer Center in Jinan)JinanChina

Mobile Industrial Internet of Things(IIoT)applications have achieved the explosive growth in recent *** mobile IIoT has flourished and become the backbone of the industry,laying a solid foundation for the interconnection of all *** variety of application scenarios has brought serious challenges to mobile IIoT networks,which face complex and changeable communication *** data secure transmission is critical for mobile IIoT *** paper investigates the data secure transmission performance prediction of mobile IIoT *** cut down computational complexity,we propose a data secure transmission scheme employing Transmit Antenna Selection(TAS).The novel secrecy performance expressions are first ***,to realize real-time secrecy analysis,we design an improved Convolutional Neural Network(CNN)model,and propose an intelligent data secure transmission performance prediction *** mobile signals,the important features may be removed by the pooling *** will lead to negative effects on the secrecy performance prediction.A novel nine-layer improved CNN model is *** of the input and output layers,it removes the pooling layer and contains six convolution ***,Back-Propagation(BP)and LeNet methods are employed to compare with the proposed *** simulation analysis,good prediction accuracy is achieved by the CNN *** prediction accuracy obtains a 59%increase.

关键词： Mobile IIoT networks Data secure transmission Performance analysis Intelligent prediction Improved CNN

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Recent progress in printing flexible electronics: A review

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Science China(Technological Sciences) 2024年第8期67卷 2363-2386页

作者： BI Sheng GAO BuHan HAN Xu HE ZhengRan METTS Jacob JIANG ChengMing ASARE-YEBOAH Kyeiwaa Key Laboratory for Precision and Non-traditional Machining Technology of the Ministry of Education School of Mechanical EngineeringDalian University of TechnologyDalian 116024China Center for Materials for Information Technology The University of AlabamaTuscaloosaAL 35487USA Department of Electrical and Computer Engineering Penn State BehrendEriePA 16563USA

Miniaturization and flexibility are becoming the trend in the development of electronic products. These key features are driving new methods in the manufacturing of such products. Printed electronics technology is a novel additive manufacturing technique that uses active inks to print onto a diverse set of substrates, realizing large-area, low-cost, flexible and green manufacturing of electronic products. These advantageous properties make it extremely compatible with flexible electronics fabrication and extend as far as offering revolutionary methods in the production of flexible electronic devices. In this paper, the details of a printing process system are introduced, including the materials that can be employed as inks, common substrates, and the most recently reported printing strategies. An assessment of future setbacks and developments of printed flexible electronics is also presented.

关键词： flexible electronics printing process conductive ink flexible substrate

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Experimental Study on Motion Controller based on NN-ARX and ARMAX Actuator Identification for 3-DoF Delta Parallel Robot 11

Experimental Study on Motion Controller based on NN-ARX and ...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Jalali, Hasan Damavandi, Hossein Kalhor, Ahmad Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran Sadjad University Faculty of Computer Engineering and Information Technology Mashhad Iran University of Tehran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350308105

Today, system identification plays a pivotal role in control science and offering a myriad of applications. This paper places its focus on the identification of actuator models within real-world delta robots for informing controller design. Two identification methods, namely NN-ARX and ARMAX, have been employed to extract the dynamic characteristics of the robot actuators, resulting in dynamic models of these integral components being derived. These dynamic models have been utilized in simulations for controller design, and due to the disparities in the identification models, distinct controllers have been realized. Subsequently, these controllers have been practically implemented on delta robots, and their performances have been subjected to a comprehensive comparative analysis. The results demonstrate that controllers integrating the identified actuator models outperformed those designed without the incorporation of the identification models. In practice, the implementation of controllers based on NN-ARX yielded the most favorable results among all the tested controllers. This research not only underscores the importance of accurate actuator models in control system design but also highlights the superior performance of neural network-based controllers in real-world robotic applications. In particular, the practical results of NN-ARX-based controllers were able to achieve significantly lower RMSE of 2.3562, 1.9531, and 2.1185 for the three motors, respectively, as opposed to the 4.1369, 3.0125, and 3.0363 achieved by the ARMAX-based controllers. © 2023 IEEE.

关键词： Controllers

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ISAC-Driven Channel-State-Estimation for Statistical-QoS Based MURLLC Over 6G M-MIMO Mobile Networks Using FBC

ISAC-Driven Channel-State-Estimation for Statistical-QoS Bas...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhang, Xi Zhu, Qixuan Texas A&m University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States

ISBN: (纸本)9798350351255

The massive ultra-reliable and low-latency communications (mURLLC) services are emerging as a new traffic type to support communications among massive numbers of mobile users (MUs) demanding the stringent delay and error-rate bounded quality-of-services (QoS) requirements in 6G. Correspondingly, the integrated sensing and communications (ISAC) technique can improve various QoS performances through spectrum/hardware sharing between target-sensing and data-communications. In addition, the massive multiple-input multiple-output (massive MIMO) and finite blocklength coding (FBC) have been also widely recognized as the powerful 6G techniques to efficiently support mURLLC. However, how to apply the ISAC technique to accurately sense and estimate the wireless channel state while transmitting the information from the base station to MUs to support mURLLC using massive MIMO and FBC has imposed many new difficulties not encountered before. To conquer these challenges, in this paper we propose the new ISAC performance metrics for statistical-QoS guaranteed mURLLC over 6G massive MIMO mobile networks using FBC. First, we establish system models for ISAC-based architectures. Second, we detect targeted MUs and estimate the channel state using the radar sensing echo. Third, we develop a new ISAC performance metric as a function of the data-communication rate and channel state estimation distortion. Finally, we use the numerical analyses to validate and evaluate our developed ISAC performances in supporting mURLLC-oriented QoS requirements. © 2024 IEEE.

关键词： Channel estimation

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Distracted driving behaviour recognition based on transfer learning and model fusion

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International Journal of Wireless and Mobile Computing 2023年第2期24卷 159-168页

作者： Luo, Guantai Xiao, Wanghui Chen, Xinwei Tao, Jin Zhang, Chentao -HIT Research Institute of Engineering and Technology Quanzhou Fujian China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou Fujian China Department of Instrumental and Electrical Engineering Xiamen University Fujian Xiamen China

In the recognition of distracted driving behaviour, traditional manual feature extraction is subjective and complex;single deep convolutional network also has problems such as insufficient generalisation performance and stability. To solve the above problems, this paper proposes a distracted driving behaviour recognition method based on transfer learning and model fusion. First, based on the transfer learning method, the deep convolutional neural network models ResNet18 and ResNet34 are used to extract the features of some images, respectively. Furthermore, the pre-trained model is fine-tuned to obtain four deep convolutional neural network models. Finally, the four network models are fused by stacking method, using 5-fold cross-validation method to reduce over-fitting. Experimental results show that the recognition accuracy of distracted driving behaviour after model fusion reaches 95.47%. The fusion model has higher model generalisation performance and recognition accuracy, which can provide certain technical support for the research of distracted driving behaviour recognition. © 2023 Inderscience Enterprises Ltd.

关键词： Convolutional neural networks

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