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Microwave heating as a universal method to transform confined molecules into armchair graphene nanoribbons

Nano Research 2023年第7期16卷 10644-10651页

作者： Haoyuan Zhang Yingzhi Chen Kunpeng Tang Ziheng Lin Xuan Li Hongwei Zhang Yifan Zhang Chi Ho Wong Chi Wah Leung Chee Leung Mak Yuan Hu Weili Cui Kecheng Cao Lei Shi State Key Laboratory of Optoelectronic Materials and Technologies Nanotechnology Research CenterGuangdong Province Key Lab of Display Material and TechnologySchool of Materials Science and EngineeringSun Yat-sen UniversityGuangzhou 510275China Huzhou Key Laboratory of Environmental Functional Materials and Pollution Control School of EngineeringHuzhou UniversityHuzhou 313000China Department of Industrial and Systems Engineering Research Institute for Advanced ManufacturingThe Hong Kong Polytechnic UniversityHong Kong 999077China Department of Applied Physics The Hong Kong Polytechnic UniversityHong Kong 999077China Shanghai Key Laboratory of High-resolution Electron Microscopy ShanghaiTech UniversityShanghai 201210China

Armchair graphene nanoribbons(AGNRs)with sub-nanometer width are potential materials for the fabrication of novel nanodevices thanks to their moderate direct band *** are usually synthesized by polymerizing precursor molecules on substrate ***,it is time-consuming and not suitable for large-scale *** can also be grown by transforming precursor molecules inside single-walled carbon nanotubes(SWCNTs)via furnace annealing,but the obtained AGNRs are normally *** this work,microwave heating is applied for transforming precursor molecules into *** fast heating process allows synthesizing the AGNRs in *** different molecules were successfully transformed into AGNRs,suggesting that it is a universal *** importantly,as demonstrated by Raman spectroscopy,aberrationcorrected high-resolution transmission electron microscopy and theoretical calculations,less twisted AGNRs are synthesized by the microwave heating than the furnace *** results reveal a route for rapid production of AGNRs in large scale,which would benefit future applications in novel AGNRs-based semiconductor devices.

关键词： armchair graphene nanoribbons(AGNRs) microwave heating single-walled carbon nanotubes(SWCNTs) Raman spectroscopy

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An Improved PI controller for Stiction Compensation of control Valves in Process Industry

An Improved PI Controller for Stiction Compensation of Contr...

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第43届中国控制会议

作者： Dong Yang Xun Lang Jiande Wu Yumin Lang Lei Xie Hongye Su Department of Electronic Engineering School of Information Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University State Key Laboratory of Industrial Control Technology Zhejiang University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the process industry, limit cycles are mostly induced by stiction-related nonlinearity in control valves, severely deteriorating control loop performance. Such problem highlights the importance of compensating for oscillations due to valve stiction. To this end, this work introduces an improved PI controller(IPIC) for stiction compensation, which retains the advantages of the traditional PI controller with fewer adjustment parameters. The enhancement involves nonlinear variation of the integral gain based on instantaneous error. Additionally, a differential evolution algorithm is utilized for controller *** to state-of-the-art methods in setpoint tracking, disturbance rejection, and robustness to parameter uncertainties, the proposed approach exhibits superior performance.

关键词： Stiction Limit Cycle Nonlinear PI controller Differential Evolution Algorithm

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RF-Based Drone Detection Under Open Set Setting

RF-Based Drone Detection Under Open Set Setting

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IEEE International Conference on Communications in China (ICCC)

作者： Ningning Yu Jiajun Wu Chengwei Zhou Zhiguo Shi Jiming Chen Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Zhejiang University Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

As the explosive increase of drone classes, most existing radio frequency (RF) based drone detection methods belong to the supervised learning approaches, which brings the risk of misclassifying unknown classes. To address this problem, an open set signal recognition method for unknown drone detection is proposed to deal with such a scenario where testing classes do not exactly match training classes. In particular, dilated convolution layers with multi-level receptive fields are used in the process of signal semantic construction, which facilitates feature extraction by jointly exploiting the image-transmission signals and the flight control signals of drones. Besides, an outlier analysis-based classifier is designed in the semantic classification process, which relaxes the necessity of manually setting the bounding thresholds. Furthermore, a newly established real-world dataset DroneRFaSpectra is also released, which includes 12 drone classes with a total number of 8334 samples. Experimental results demonstrate that the proposed method outperforms the compared detection methods, achieving the highest detection rate of 99.26% for unknown drones.

关键词： Training Convolution Semantics Supervised learning Process control Feature extraction Explosives

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Translation Invariant Global Estimation of Heading Angle Using Sinogram of LiDAR Point Cloud

arXiv

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arXiv 2022年

作者： Ding, Xiaqing Xu, Xuecheng Lu, Sha Jiao, Yanmei Tan, Mengwen Xiong, Rong Deng, Huanjun Li, Mingyang Wang, Yue State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang China Alibaba Group Hangzhou310052 China

Global point cloud registration is an essential module for localization, of which the main difficulty exists in estimating the rotation globally without initial value. With the aid of gravity alignment, the degree of freedom in point cloud registration could be reduced to 4DoF, in which only the heading angle is required for rotation estimation. In this paper, we propose a fast and accurate global heading angle estimation method for gravity-aligned point clouds. Our key idea is that we generate a translation invariant representation based on Radon Transform, allowing us to solve the decoupled heading angle globally with circular cross-correlation. Besides, for heading angle estimation between point clouds with different distributions, we implement this heading angle estimator as a differentiable module to train a feature extraction network end-to-end. The experimental results validate the effectiveness of the proposed method in heading angle estimation and show better performance compared with other methods. © 2022, CC BY-NC-ND.

关键词： Surface measurement

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DIRECT DIGITAL CRISPR/CAS-ASSISTED ASSAY FOR ULTRASENSITIVE DETECTION OF PATHOGENS 26

DIRECT DIGITAL CRISPR/CAS-ASSISTED ASSAY FOR ULTRASENSITIVE ...

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

作者： Xia, Liping Yin, Juxin Zhuang, Jianjian Yin, Weihong Zou, Zheyu Mu, Ying Research Centre for Analytical Instrumentation Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China School of information and Electrical Engineering Zhejiang University City College Hangzhou China Affiliated Hangzhou First People's Hospital Zhejiang University School of Medicine Hangzhou China

ISBN: (纸本)9781733419048

Herein, we developed a Direct Digital Dual-crRNAs (3D) assay integrated on an adsorption-free self-priming microfluidic chip for ultrasensitive detection of pathogens. This 3D assay combined the advantages of rapid amplification of RPA, specific cleavage of Cas12a, accurate quantification of digital PCR, and point-of-care testing (POCT) of microfluidics, enabling accurate and reliable digital absolute quantification of Salmonella in POCT. Our method can provide a good linear relationship of Salmonella detection in the range from 2.58×101 to 2.58×104 cells/mL with a limit of detection ~2 cells/mL in 30 minutes. Moreover, the assay could directly detect Salmonella in milk without nucleic acid extraction. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized systems for Chemistry and Life Sciences. All rights reserved.

关键词： Salmonella

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Few Shot Object Detection Based on Graph Attention Network

Few Shot Object Detection Based on Graph Attention Network

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Pattern Recognition and Machine Learning (PRML), IEEE International Conference on

作者： Rou Ding Yu Zhang State Key Laboratory of Industrial Control Technology Zhejiang University of Control Science and Engineering Zhejiang China Key Laboratory of Collaborative sensing and autonomous unmanned systems of Zhejiang Province Zhejiang China

Few shot object detection is a challenging task in computer vision, as it involves detecting objects from a small number of examples. This makes it difficult for traditional object detection methods to generalize well to new classes or scenes. In this paper, we propose a siamese neural network model that utilizes the power of Faster RCNN for few shot object detection. The network takes in support and query datasets and extracts both support and query features. To supplement category information between various support features, we use Pearson similarity to enhance the features and extract support prototypes. We propose a graph attention network that can perform association matching between support prototype and proposals. Through this network, we facilitate information exchange between support features and query features, which helps to supplement the information of query images. We divide the training process into two stages. In the first stage, we use a large amount of basic category data to train the basic detection ability. In the second stage, we further train our model on few shot novel class and base class mixed datasets to improve its generalization performance. Experimental results on the public Pascal VOC dataset demonstrate that our proposed method achieves state-of-the-art few shot object detection performance.

关键词：

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Trajectory Tracking control for Autonomous Parking Based on Adaptive Reduced-horizon Model Predictive control

Trajectory Tracking Control for Autonomous Parking Based on ...

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IEEE International Conference on Networking, Sensing and control

作者： Minghan Cai Weimin Wu Xiaoling Zhou The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9781665472449

In this paper, an adaptive reduced-horizon model predictive control is proposed for autonomous parking trajectory tracking. Given the reference trajectory, the discrete linear time varying model is obtained by linearizing and discretizing along the reference trajectory point. Furthermore, the model is reformulated into a combined incremental form. Then, a standard quadratic programming problem is established, and the optimal control strategy is obtained by solving the problem online at every time instant. Meanwhiles, the prediction horizon will reduce adaptively by solving the constrained optimization problem, and it will minimize the computation time complexity of the MPC-based controller. The actual parking scenarios are co-simulated in Simulink and Carsim, which shows the effectiveness and feasibility of the proposed method.

关键词： Adaptation models Trajectory tracking Software packages Simulation Trajectory Quadratic programming Time complexity

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Learning the Inverse Kinematics of Magnetic Continuum Robot for Teleoperated Navigation

Learning the Inverse Kinematics of Magnetic Continuum Robot ...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Pingyu Xiang Ke Qiu Danying Sun Jingyu Zhang Qin Fang Xiangyu Mi Shudong Wang Mengxiao Chen Yue Wang Rong Xiong Haojian Lu State Key Laboratory of Industrial Control and Technology and Institute of Cyber-Systems and Control Zhejiang University Hangzhou China State Key Laboratory of Electrical Insulation and Power Equipment School of Electrical Engineering Xian Jiaotong University Research Center for Humanoid Sensing Zhejiang Lab 311100 Zhejiang Lab Nanhu Headquarters Hangzhou P.R. China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Magnetic continuum robots are subject to external magnetic fields and deformed remotely, simplifying the robot’s transmission mechanism and providing it with significant potential for miniaturization and operational flexibility. However, modeling magnetic field distribution generated by permanent magnets is complex and requires time-consuming pre-calibrations. Moreover, it is highly susceptible to environments with ferromagnetic materials, posing significant challenges for the control of magnetic continuum robots. In response, we propose an approach that does not overly focus on the magnetic field distribution but instead directly learns the inverse kinematics of magnetic continuum robots end-to-end. Binding the robot’s configuration to the pose of external magnets, precise control of continuum robots is facilitated. Additionally, we leverage teleoperation techniques to broaden the applicability of this method. By mounting magnets on a robotic arm and directly utilizing the target pose of the external magnet predicted by a multi-layer perceptron (MLP), we achieve the operation and navigation of magnetic continuum robots in complex environments. Experiments demonstrate that the mean control accuracy along the robot using our learning-based inverse kinematics is about half of the robot’s diameter.

关键词： Uncertainty Navigation Kinematics Manipulators Permanent magnets Continuum robots Magnetic fields Robots Intelligent robots Magnetic susceptibility

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Application Design of Virtual Immersion Command Information System

Application Design of Virtual Immersion Command Information ...

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International Conference on Big Data and Information Analytics (BigDIA)

作者： Renjie Liu Hongli Chen Mingyang Wang Jian Zhu Zhenqian Zhang Ming Zhang Key Laboratory of Information System and Technology Beijing Institute of Control and Electronic Technology Beijing China Laboratory of Artificial Intelligence Integration Development and Security Application China Industrial Control Systems Cyber Emergency Response Team Beijing China

Based on the existing resources of general command information system, the virtually immersive display system is constructed. In this paper, the application design of virtual and augmented reality display system was discussed. The main contents included the overall system design, business requirements, application design of virtual reality (VR) and augmented reality (AR) table display system, expected results, and equipment selection. The deployment and application of VR and AR display system were introduced. Therefore, the hardware selection of VR and AR were HTC Vive and XLOOG X200 products, respectively. The Unreal Engine 4 was selected as the software development platform. This solution meets the current immersive display requirements. The system integrates VR and AR display application capabilities and can fully serve the command and control requirements in the future virtual field.

关键词：

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Heterogeneous Gateway Planning for Semantic Communication in industrial Networks

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Sun, Yuyi Xing, Fangyuan Guo, Zhenwei Chen, Huimin He, Shibo Hangzhou Normal University School of Information Science and Technology Hangzhou China Southeast University School of Cyber Science and Engineering Nanjing China Hangzhou Innovation Institute of Beihang University Research Center of Cyber Science and Technology Hangzhou China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China

Semantic Communication (SemCom) has become a promising approach to transmit the information entropy instead of the raw data, which can increase the transmission efficiency and robustness. SemCom recently attracts more attention on the research of Internet of Things (IoT). Previous work focused more on new SemCom framework for IoT applications or lightweight SemCom models which can be easily deployed at IoT end-devices. However, the adaptation of SemCom in industrial networks still remains to be explored. In this article, we focus on gateway planning for SemCom in industrial networks. Specifically, in order to meet the different requirements of various nodes in industrial networks, we build a heterogeneous architecture of gateway planning for SemCom. Then, the Structure-Similarity-Index-Measure (SSIM) model in SemCom is introduced to illustrate the Signal-to-Noise Ratio (SNR) and compression ratio. Based on this, we build the bridge between the SSIM and the number of gateways to analyze our problem. To apply minimum gateways to cover the heterogeneous nodes and meet the SemCom transmission conditions, we formulate the problem as an NP-hard problem and simplify the problem to find the solution. Greedy-Based Algorithm (GBA) and Heuristic-Deep Q Network (H-DQN) algorithm are designed to solve this problem, and simulations are demonstrated to compare H-DQN, Q-learning, GBA and Branch and Bound (BB). The experimental results show that H-DQN outperforms other algorithms, deploying less gateways and saving over 50% of operation time. Besides, the throughput of our system is 1.3× larger than that of the single coverage system with less gateways. © 2015 IEEE.

关键词： Gateways (computer networks)

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