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21st Polish control Conference, PCC 2023

作者： Krauze, Piotr Placzek, Marek Zmudka, Zbigniew Bauke, Dawid Olszowka, Przemyslaw Turek, Jakub Wycislok, Artur Ziaja, Maciej Zosgornik, Szymon Janusz, Wojciech Przybyla, Grzegorz Wychowanski, Michal Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Akademicka 16 Gliwice44-100 Poland Silesian University of Technology Faculty of Mechanical Engineering Konarskiego 18A Gliwice44-100 Poland Silesian University of Technology Faculty of Energy and Environmental Engineering Konarskiego 18 Gliwice44-100 Poland Engineering Office Ozarow27-530 Poland Gliwice Poland

ISBN: (纸本)9783031351693

The article presents results of experimental identification of MR (magnetorheological) damper model for an off-road vehicle. Original shock-absorbers of the vehicle were replaced by suspension MR dampers supplied by a dedicated measurement and control system. The vehicle includes several sensors which allow to observe electric currents controlling MR dampers, forces generated in the front vehicle suspension columns and other sensors which measure deflection of these suspension parts. The front part of the semi-active suspension was tested using laboratory setup with vibration mechanical exciters generating sinusoidally variable excitation at frequency equal to 12 Hz. MR dampers were directly controlled by peripheral electronic units generating different constant currents equal to 0, 0.11 and 0.37 A. As a result, evaluated force-velocity characteristics and analysis of MR damper behaviour in the target vehicle were carried out. Further steps of analysis included mathematical description of the selected MR damper using several types of MR damper models, i.e.: Bingham and hyperbolic tangent function models as well as their variants including first-order output dynamics. It was shown that the dynamic model based on hyperbolic tangent function offers the best fitness to the response of the actual MR damper with respect to the mean-squared error. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Off road vehicles

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MG6D: A Deep Fusion Approach for 6D Pose Estimation with Mamba and Graph Convolution Network

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IEEE Access 2025年 13卷 100433-100445页

作者： Zhu, Jiaqi Li, Bin Zhao, Xinhua Tianjin University of Technology School of Computer Science and Engineering Tianjin 300384 China Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin 300384 China

Accurate and efficient 6D pose estimation is a fundamental technology in many industrial applications. While existing dense correspondence methods have shown progress, they face challenges in multimodal feature fusion under complex scenarios involving occlusions, illumination variations, and sensor noise. This paper proposes a novel 6D pose estimation framework that addresses these limitations through a hybrid Mamba-Graph architecture. The algorithm first introduces a panoramic attention fusion Mamba module, leveraging state-space modeling to capture long-range dependencies in multi-modal data while establishing cross-dimensional interactions between channel and spatial features to emphasize critical information. A dynamic graph convolutional adaptive fusion module is then designed to enable cross-modal geometric consistency modeling via multi-modal feature integration. Finally, a texture-geometry co-driven keypoint selection mechanism is proposed to ensure keypoint distributions satisfy both spatial uniformity and discriminability requirements. Experimental results on three common datasets demonstrate that the proposed algorithm achieves ADD(-S) metrics of 99.82%, 80.26%, and 97.2%, respectively. Notably, it exhibits significant advantages in pose estimation for objects with repetitive textures and high symmetry. © 2013 IEEE.

关键词： 6D pose estimation Fusion Mamba Graph feature fusion Panoramic Attention

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Research of Improved TD3 Robotic Arm Path Planning using Evolutionary Algorithm 5

Research of Improved TD3 Robotic Arm Path Planning using Evo...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhang, Feng Xiong, Jianqiang Yuan, Shuai Wen, Ke Shenyang Jianzhu University Liaoning Province Big Data Management and Analysis Laboratory of Urban Construction Shenyang Branch of National Special Computer Engineering Technology Research Center School of Electrical and Control Engineering Shenyang110168 China Shenyang Jianzhu University School of Electrical and Control Engineering Shenyang110168 China Shenyang Jianzhu University School of Computer Science and Engineering Shenyang110168 China

ISBN: (纸本)9798350307320

Nowadays, application of automated intelligent robot arm devices to improve industrial production efficiency has become a popular research field in the world. The previous off-line path planning method of robotic arm has the inadequacies of low efficiency and slow speed. Although the deep reinforcement learning has accomplished many achievements in the path planning of control manipulator, there are still some problems such as long training time and low planning accuracy. To solve the abovementioned issues, we propose an improved Twin Delayed Deep Deterministic policy gradient (TD3) algorithm (Improved Cross-Entropy Method-TD3: ICEM-TD3) for the path planning of the robotic arm. First, this paper combines evolutionary strategies with TD3 to generate action networks. Then the exploration of TD3 algorithm in the action space is replaced by the exploration in the parameter space. In addition, this paper designs a new reward function to weaken the redundancy of planning and accelerate the convergence speed of training. Finally, the Gazebo simulator is adopted to verify the proposed algorithm, and the results illustrate that the proposed algorithm can greatly improve the accuracy of the path planning of the manipulator using deep reinforcement learning. © 2023 IEEE.

关键词： Motion planning

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Polyp Segmentation Neural Network with Simple Encoding Structure and Reverse Attention Module 13

Polyp Segmentation Neural Network with Simple Encoding Struc...

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13th International Conference on Information technology in Medicine and Education, ITME 2023

作者： Wang, Jie Li, Zuoyong Xu, Haiping Cheng, Xuesong Teng, Shenghua College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China Fujian Key Laboratory of Medical Big Data Engineering Fujian Provincial Hospital Fuzhou350001 China College of Mathematics and Data Science Minjiang University Fuzhou350121 China

ISBN: (纸本)9798350319156

Colorectal cancer is a common malignancy. In colonoscopy images, computer-assisted polyp segmentation helps doctors diagnose and treat disorders more precisely. In recent years, some methods based on deep convolutional neural networks have made significant breakthroughs in this task. However, only a few algorithms explicitly consider the effect of light intensity on segmentation performance, which results in algorithms needing to be more robust for complex samples. This paper proposes a neural network combining a simple encoding structure with a reverse attention module. Specifically, the model uses HarDNet68 as the backbone network, adds a camouflage identification module (CIM) to enhance the capture of polyp details on the underlying features, and finally utilizes adaptive feature fusion with the reverse attention module (RAM). The proposed model effectively addresses the challenge of poor segmentation quality in colonoscopy images caused by inconsistent illumination. Extensive experiments on five datasets show that the proposed model performs well in polyp segmentation. © 2023 IEEE.

关键词： Diseases

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Real-time FPGA implementation of the Semi-Global Matching stereo vision algorithm for a 4K/UHD video stream

TechRxiv

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TechRxiv 2023年

作者： Grabowski, Mariusz Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

In this paper, we propose a real-time FPGA implementation of the Semi-Global Matching (SGM) stereo vision algorithm. The designed module supports a 4K/Ultra HD (3840×2160 pixels @ 30 frames per second) video stream in a 4 pixel per clock (ppc) format and a 64-pixel disparity range. The baseline SGM implementation had to be modified to process pixels in the 4ppc format and meet the timing constrains, however, our version provides results comparable to the original design. The solution has been positively evaluated on the Xilinx VC707 development board with a Virtex-7 FPGA device. © 2023, CC BY.

关键词： Field programmable gate arrays (FPGA)

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Retinal Vessel Segmentation Based on UNet and Edge Detection 12

Retinal Vessel Segmentation Based on UNet and Edge Detection

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12th International Conference on Information technology in Medicine and Education, ITME 2022

作者： Yan, Peixin Li, Zuoyong Hu, Rong Cao, Xinrong Fujian University of Technology College of Computer Science and Mathematics Fuzhou350118 China Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Colloge of Computer and Control Engineering Fuzhou350121 China

ISBN: (纸本)9798350310153

Retinal vessel segmentation is important for the diagnosis of many diseases. The segmentation of microscopic vessels is one of the challenges because of the complex structure of retinal vessels, which makes it challenging to tell the vessels apart from the background. In order to improve the segmentation performance of retinal vessels, we use the edge detection method of HED to optimize the segmentation effect of UNet. Using Hybrid Dilated Convolution not only increases the perceptual field, but also avoids the loss of information continuity caused by the continuous use of dilated convolution. The Pyramid Pooling Module is used at the end of the encoder to compensate for the information loss caused by downsampling. Finally, the output of edge detection and image segmentation is combined as the final result. The model is evaluated in two mainstream datasets DRIVE and CHASE-DB1, and the experimental results show that the proposed model can improve the performance of retinal vessel segmentation. © 2022 IEEE.

关键词： Convolution

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Towards construction of analog solver of Schroedinger and Ginzburg-Landau equation based on Long Line

arXiv

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arXiv 2023年

作者： Pluszyński, Lukasz Pomorski, Krzystof Cracow University of Technology Department of Computer Science Poland Cracow University of Technology Department of Automatic Control and Computer Engineering Poland Quantum Hardware Systems Lodz Poland

The analog electronic computers are a type of circuitry used to calculate specific problems using the physical relationships between the voltages and currents following classical laws of physics. One specific class of these circuits are computers based on the interactions between passive circuit elements. Models presented by Gabriel Kron in 1945 are the example of using such passive elements to construct a solver for the problem of free quantum particles confined by rectangular potential. Numerical validation of Kron's second model is conducted for different shapes of particle confining potential. Kron's model is generalized by introduction of non-linear resistive elements what implies deformation of Schroedinger equation solution into Ginzburg-Landau form. © 2023, CC BY.

关键词： Analog computers

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A generative deep learning framework for airfoil flow field prediction with sparse data

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Chinese Journal of Aeronautics 2022年第1期35卷 470-484页

作者： Haizhou WU Xuejun LIU Wei AN Hongqiang LYU MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Aerodynamic Noise Control Mianyang 621000China State Key Laboratory of Aerodynamics Mianyang 621000China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210023China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Deep learning has been probed for the airfoil performance prediction in recent *** with the expensive CFD simulations and wind tunnel experiments,deep learning models can be leveraged to somewhat mitigate such expenses with proper ***,effective training of the data-driven models in deep learning severely hinges on the data in diversity and *** this paper,we present a novel data augmented Generative Adversarial Network(GAN),daGAN,for rapid and accurate flow filed prediction,allowing the adaption to the task with sparse *** presented approach consists of two modules,pre-training module and fine-tuning *** pre-training module utilizes a conditional GAN(cGAN)to preliminarily estimate the distribution of the training *** the fine-tuning module,we propose a novel adversarial architecture with two generators one of which fulfils a promising data augmentation operation,so that the complement data is adequately incorporated to boost the generalization of the *** use numerical simulation data to verify the generalization of daGAN on airfoils and flow conditions with sparse training *** results show that daGAN is a promising tool for rapid and accurate evaluation of detailed flow field without the requirement for big training data.

关键词： CFD Flow field Generative adversarial networks(GANs) Sparse data Supercritical airfoil

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Demand-Side Joint Electricity and Carbon Trading Mechanism

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2024年 2卷 14-25页

作者： Hua, Haochen Chen, Xingying Gan, Lei Sun, Jiaxiang Dong, Nanqing Liu, Di Qin, Zhaoming Li, Kang Hu, Shiyan College of Energy and Electrical Engineering Hohai University Nanjing211100 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Department of Automation Tsinghua University Beijing100084 China Automatic Control Laboratory at Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland School of Electronic and Electrical Engineering University of Leeds LeedsLS2 9JT United Kingdom School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Decarbonization of the whole energy chain has been recognized as a measure to tackle the global challenge of climate change, and significant progress has already been made on the generation side to integrate renewable energy. However, the demand side is the single largest underlying factor in shaping decarbonization roadmap. Hence, the carbon emission cost should also be shared by the users according to their power consumption. In this paper, a joint electricity-carbon trading framework is designed to reduce the carbon emission through trading and demand response. A delayed carbon emission liability settlement for asynchronous markets is proposed to ameliorate the users' optimal decision from single-point optimization to interval-based optimization. To develop the optimal strategy of trading within the proposed mechanism, an improved proximal policy optimization (PPO) algorithm based on Monte Carlo reward sampling is applied. Simulation studies reveal that, compared with the market without carbon trading and users without delayed settlement, the proposed mechanism has achieved a carbon emission reduction by 40.7% and 12.7% respectively. Simulations also show the algorithm's training efficiency can be significantly improved with the proposed Monte Carlo sampling method. © 2023 IEEE.

关键词： Real time systems

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Analysis of selected dielectric parameters of insulating liquids

Analysis of selected dielectric parameters of insulating liq...

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International Scientific Conference on Electric Power engineering (EPE)

作者： Aleksandra Płużek Łukasz Nagi Michał Kozioł Małgorzata Zygarlicka Department of Electrical Power and Renewable Energy Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength.

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