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8th International Conference on Image, Vision and computing, ICIVC 2023

作者： Wang, Haijuan Bai, Lin Ji, Bo Shen, Jiaming Jin, Ying Ye, Fei Zhu, Chunlin School of Electronics and Control Engineering Chang'An University Xi'an China Zhejiang Aerospace Runbo Measurement and Control Technology Co. Ltd. Hangzhou China Xi'An Aeronautics Computing Technique Research Institute Xi'an China

ISBN: (纸本)9798350335231

Automatic recognition and extraction of roads from high-resolution satellite images is a crucial task in remote sensing and computer vision. With the continuous development of remote sensing technology, more ground object information is contained in images, making it more challenging to extract roads due to increased interference. This paper proposes a gated fusion and dual attention network with an encoder-decoder structure to address this problem. The full-stage gated fusion module in skip connection selectively fuses feature maps of different scales using the Gated Fusion (GFF) unit, which increases the receptive field of the network and improves the accuracy of road extraction. The context extraction and dual attention module introduce rich global information and simultaneously weights features from both spatial and channel dimensions. This improves the semantic segmentation problem caused by focusing only on local information in current road extraction models. Experimental results on two public datasets show that GFDANet can effectively extract roads in complex scenes. © 2023 IEEE.

关键词： Roads and streets

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High-performance and Multi-functional control of Transformerless Single-phase Smart Inverter for Grid-connected PV System

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Journal of Modern Power Systems and Clean Energy 2021年第6期9卷 1386-1394页

作者： Kamran Zeb Saif Ul Islam Waqar Uddin Imran Khan Muhammad Ishfaq Tiago Davi Curi Busarello H.J.Kim Department of Electrical Engineering Pusan National University School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Control Automation and Computing EngineeringFederal University of Santa Catarina Blumenau

Highly reliable and flexible control is required for distributed generation(DG) to efficiently connect to the *** inverters play a key role in the control and integration of DG into the power grid and provide advanced functionalities. In this paper, an energy-based single-phase voltage-source smart inverter(SPV-SSI) of 5 k VA is designed and analyzed in detail. SPV-SSI is capable of supplying the power to local load and the utility load up to the rated capacity of the inverter, injecting the power into the grid, storing the energy in lead-acid battery bank, controlling the voltage at the point of common coupling(PCC) during voltage sags or faults, and making decisions on real-time pricing information obtained from the utility grid through advanced metering. The complete design of smart inverter in dq frame, bi-directional DC-DC buck-boost converter, IEEE standard 1547 based islanding and recloser, and static synchronous compensator(STATCOM) functionalities is presented in this paper. Moreover, adaptive controllers, i. e., fuzzy proportional-integral(F-PI) controller and fuzzy-sliding mode controller(F-SMC) are designed. The performances of F-PI controller and F-SMC are superior, stable, and robust compared with those of conventionally tuned PI controllers for voltage control loop(islanded mode) and current control loop(grid-connected mode).

关键词： Distributed generation(DG) inverter convert-er fuzzy-sliding mode controller(F-SMC) fuzzy proportionalintegral(F-PI)controller

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Reproducible Fabrication of Liquid Metal Droplet with FIB Sputtering for Contact Angle Measurement in SEM

Reproducible Fabrication of Liquid Metal Droplet with FIB Sp...

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International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)

作者： Yuning Lei Sergej Fatikow Department of Computing Science Division Microrobotics and Control Engineering University of Oldenburg Oldenburg Germany

ISBN: (数字)9798350376807

ISBN: (纸本)9798350376814

The wetting phenomenons of surfaces, such as surface tension, are a critical concern for various micro- and nanoelectromechanical systems (MEMS/NEMS) due to scaling effects. In recent years, a lot of efforts have been made in research and industry to study wetting phenomena at the micron and nanometer scales, among which, the liquid metal droplet-based contact angle measurement (CAM) method allows for the characterization of surface wetting properties in a scanning electron microscope (SEM), thus obtaining a resolution that goes beyond the limits of an optical microscope. However, reproducible fabrication of specific micrometer-scale droplets is a key challenge towards the automation of this technique. In this paper, we provide a reliable and reproducible method for the fabrication of specific-sized liquid metal droplets. This includes the generation of droplets at specific locations based on electromigration techniques and the use of focused ion beam (FIB) induced sputtering techniques to fabricate droplets of specific sizes. Using Galinstan as an example, this paper reports its sputtering yield of 0.866 μm 3 .nC −1 , along with the process of determining it. We also demonstrated the reproducibility of fabricating liquid metal droplets with a radius of 10 μm and 5 μm, the results show standard deviations of 0.168 μm and 0.63 μm, respectively.

关键词： Fabrication Electromigration Scanning electron microscopy Liquids Automation Metals Process control

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Characterization of Tunable Multilayer Graphene Ink by a Microstrip Transmission Line

Characterization of Tunable Multilayer Graphene Ink by a Mic...

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International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)

作者： Shakir Ullah Warda Saeed Muhammad Yasir Department of Computing Sciences Division of Microrobotics and Control Engineering University of Oldenburg Oldenburg Germany

ISBN: (数字)9798350376807

ISBN: (纸本)9798350376814

This paper presents microwave characterization of multilayered graphene in the frequency range of 8–12 GHz. Thru, Reflect, Line calibration method has been used to shift calibration planes from the edge of a microstrip line to graphene. Transmission coefficient is measured for varying bias voltages. Values of complex impedance of graphene are derived from the transmission coefficient. Prototypes have been fabricated consisting of a microstrip line with different gaps on which multilayered graphene ink is deposited. By decreasing the gap size in the microstrip line, the resistance, reactance and the tuning range of graphene decreases.

关键词： Resistance Voltage measurement Graphene Prototypes Ink Transmission line measurements Microwave theory and techniques

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Artificial Enhanced Image Inpainting for Broadband SMM

Artificial Enhanced Image Inpainting for Broadband SMM

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International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)

作者： Markus F. Wieghaus Warda Saeed Muhammad Yasir Department of Computing Science Division Microrobotics and Control Engineering University of Oldenburg Oldenburg Germany

ISBN: (数字)9798350376807

ISBN: (纸本)9798350376814

Scanning probe microscopy techniques changed the understanding of micro and nanometer scaled objects. Since the invention of the scanning tunneling microscope and the atomic force microscope, these techniques were further developed and combined with different measurement methodologies such as scanning microwave microscopy. By introducing an electromagnetic signal in the microwave frequency range via the scanning probe microscope tip to the sample, electromagnetic characteristics of the specimen can be acquired. Using a series of frequencies in one scan, even more information like dopant concentration or different layers of material can be captured. The drawback of this method is the long data acquisition time, which cannot be neglected on nanometer scale. To address this issue, we are using reduced raster scan techniques with broadband scanning microwave microscopy and calculate the missing data information by using image inpainting algorithms afterwards. In this work we will present the development of a deep learning algorithm and compare the output of it with different inpainting algorithms, which can even be used in other scanning probe microscope setups.

关键词： Atomic measurements Atomic force microscopy Scanning probe microscopy Neural networks Training data Tunneling Broadband communication

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Improving graph collaborative filtering with network motifs

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Neural computing and Applications 2025年 1-20页

作者： Zhang, Yuqi Yu, Jian Liu, Zhizhong Wang, Guiling Nguyen, Minh Sheng, Quan Z. Wang, Nancy Department of Computer and Information Sciences Auckland University of Technology Auckland Central1010 New Zealand School of Computer and Control Engineering Yantai University Shandong Yantai264005 China School of Information Science and Technology North China University of Technology Beijing100144 China School of Computing Macquarie University SydneyNSW2109 Australia

Deep learning on graphs, specifically graph convolutional networks (GCNs), has exhibited exceptional efficacy in the domain of recommender systems. Most GCNs have a message-passing architecture that enables nodes to aggregate information from neighbours iteratively through multiple layers. This enables GCNs to learn from higher-order information, but the model does not allow for direct captions of the local structural patterns. Our rationale is to investigate the effectiveness of capturing such local patterns for graph-based collaborative filtering to enhance model’s learning ability per layer. This technique combines lower-order and higher-order interactions during layer-wise propagation. In this paper, we propose MotifGCN to aggregate both lower-order and higher-order information in each graph convolution layer. Specifically, we develop dedicated algorithms of generating motif adjacency matrices. The matrices are then used for motif-enhanced neighbourhood aggregation in each layer. As this paper focuses on recommender systems, MotifGCN is built on the basis of bipartite graphs. Our experiments on four real-world datasets show that MotifGCN has a superior performance compared to various state-of-the-art methods. © The Author(s) 2025.

关键词： Collaborative filtering

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User Input Search - Custom Motion Estimation Algorithm Optimized for UAVs

User Input Search - Custom Motion Estimation Algorithm Optim...

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Proceedings of the International Convention MIPRO

作者： J. Benjak D. Hofman Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing Zagreb Croatia

Unmanned aerial vehicle technology is growing rapidly as it finds its application in the various industries, including military & defense, agriculture, logistics, transportation, healthcare, entertainment and many others. One of the fastest growing industries including drones is the entertainment industry. More specifically, First Person View (FPV) piloting has become a popular sport which attracts huge masses. In FPV systems, the pilot wears FPV goggles and controls the drone using a controller, and the drone transmits video data to the goggles in real time. Since drones usually fly very quickly, the video quality in terms of resolution, compression artefacts and end-to-end delay must be maintained. This paper explores the idea of optimizing the Motion Estimation (ME) algorithm of existing High Efficiency Video Coding (HEVC) algorithms by utilizing user input from the controller. For example, if the drone is directed to hover to the left, then it would make sense to search for the most similar blocks in the previous video frame only on the left side of the referent block. For the purpose of this research, a HEVC video coder was customized to receive additional input besides the video data – the user input from the controller, or in other words, drone movement directions. We call this ME algorithm User Input Search (UIS). Our UIS algorithm is compared with the standard ME algorithms and its efficiency is tested.

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A novel analytical model for estimating vehicle delay at isolated signalised intersections

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International Journal of Simulation and Process Modelling 2022年第1-2期19卷 71-85页

作者： Qiao, Feng Liu, Huixin Luo, Dan Sun, Haochen Chen, Yinong School of Information and Control Engineering Shenyang Institute of Technology Fushun113122 China Faculty of Information and Control Engineering Shenyang Jianzhu University Shenyang100168 China School of Information Engineering Henan University of Science and Technology Henan Luoyang471000 China School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85287-8809 United States

This paper proposes a novel analytical model to estimate the average vehicle delay at signalised intersections under saturated or oversaturated conditions based on the investigation and analysis of the existing methods to deal with the problems arising in the process of acceleration, deceleration, and the transmissibility of the cycle-by-cycle average vehicle delay. The proposed model employs and combines the operating and queuing characteristics of vehicles to produce the analytic formula. To verify the effectiveness of the proposed model, simulation experiments are conducted, and the error rates and the correlation coefficients are investigated, which confirm that the proposed model possesses certain significant advantages over the existing models in saturated and oversaturated conditions. The results of research work show that the proposed model can provide transportation engineers or professionals with an effective tool for analysing, timing and managing the saturated or oversaturated signalised intersections. © 2022 Inderscience Enterprises Ltd.

关键词： Analytical models

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A spintronic memristive circuit on the optimized RBF-MLP neural network

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Chinese Physics B 2022年第11期31卷 272-283页

作者： Yuan Ge Jie Li Wenwu Jiang Lidan Wang Shukai Duan School of Artificial Intelligence Southwest UniversityChongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China

A radial basis function network(RBF)has excellent generalization ability and approximation accuracy when its parameters are set ***,when relying only on traditional methods,it is difficult to obtain optimal network parameters and construct a stable model as *** view of this,a novel radial basis neural network(RBF-MLP)is proposed in this *** connecting two networks to work cooperatively,the RBF’s parameters can be adjusted adaptively by the structure of the multi-layer perceptron(MLP)to realize the effect of the backpropagation updating ***,a genetic algorithm is used to optimize the network’s hidden layer to confirm the optimal neurons(basis function)number *** addition,a memristive circuit model is proposed to realize the neural network’s operation based on the characteristics of spin *** is verified that the network can adaptively construct a network model with outstanding robustness and can stably achieve 98.33%accuracy in the processing of the Modified National Institute of Standards and Technology(MNIST)dataset classification *** experimental results show that the method has considerable application value.

关键词： radial basis function network(RBF) genetic algorithm spintronic memristor memristive circuit

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Memristor-based multi-synaptic spiking neuron circuit for spiking neural network

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Chinese Physics B 2022年第4期31卷 225-233页

作者： Wenwu Jiang Jie Li Hongbo Liu Xicong Qian Yuan Ge Lidan Wang Shukai Duan College of Artificial Intelligence Southwest UniversityChongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China

Spiking neural networks(SNNs) are widely used in many fields because they work closer to biological ***,due to its computational complexity,many SNNs implementations are limited to computer ***,this paper proposes a multi-synaptic circuit(MSC) based on memristor,which realizes the multi-synapse connection between neurons and the multi-delay transmission of pulse *** synapse circuit participates in the calculation of the network while transmitting the pulse signal,and completes the complex calculations on the software with ***,a new spiking neuron circuit based on the leaky integrate-and-fire(LIF) model is designed in this *** amplitude and width of the pulse emitted by the spiking neuron circuit can be adjusted as *** combination of spiking neuron circuit and MSC forms the multi-synaptic spiking neuron(MSSN).The MSSN was simulated in PSPICE and the expected result was obtained,which verified the feasibility of the ***,a small SNN was designed based on the mathematical model of *** the SNN is trained and optimized,it obtains a good accuracy in the classification of the IRIS-dataset,which verifies the practicability of the design in the network.

关键词： memristor multi-synaptic circuit spiking neuron spiking neural network(SNN)

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