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From Fourier to Neural ODEs: Flow Matching for Modeling complex systems 41

From Fourier to Neural ODEs: Flow Matching for Modeling Comp...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Li, Xin Zhang, Jingdong Zhu, Qunxi Zhao, Chengli Zhang, Xue Duan, Xiaojun Lin, Wei College of Science National University of Defense Technology Hunan Changsha410073 China School of Mathematical Sciences LMNS SCMS Fudan University China Research Institute of Intelligent Complex Systems Fudan University China State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institutes of Brain Science Fudan University China Shanghai Artificial Intelligence Laboratory China

Modeling complex systems using standard neural ordinary differential equations (NODEs) often faces some essential challenges, including high computational costs and susceptibility to local optima. To address these challenges, we propose a simulation-free framework, called Fourier NODEs (FNODEs), that effectively trains NODEs by directly matching the target vector field based on Fourier analysis. Specifically, we employ the Fourier analysis to estimate temporal and potential high-order spatial gradients from noisy observational data. We then incorporate the estimated spatial gradients as additional inputs to a neural network. Furthermore, we utilize the estimated temporal gradient as the optimization objective for the output of the neural network. Later, the trained neural network generates more data points through an ODE solver without participating in the computational graph, facilitating more accurate estimations of gradients based on Fourier analysis. These two steps form a positive feedback loop, enabling accurate dynamics modeling in our framework. Consequently, our approach outperforms state-of-the-art methods in terms of training time, dynamics prediction, and robustness. Finally, we demonstrate the superior performance of our framework using a number of representative complex systems. Copyright 2024 by the author(s)

关键词： Large scale systems

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Generating Waste Heat Energy from CPU Based on Thermoelectric Power Generator

Generating Waste Heat Energy from CPU Based on Thermoelectri...

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2021 China Automation Congress, CAC 2021

作者： Qian, Kun Cai, Yeyun Xu, Kun Deng, Fang Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781665426473

Heat dissipation is extremely important for electronic component such as CPU or GPU of the computer. Now most researchers only design optimal heat sink for CPU for better heat dissipation, while few of them consider waste heat recycling of CPU. The CPU can be used as the heat source, while the original system has fan and heat sink as the cooling system. Thus, the original CPU working condition is very suitable for thermoelectric power generation and will bring great benefit to system itself. However, adding thermoelectric generator will increase the temperature of CPU, which will decrease the performance of the computer. It is necessary to reduce the hot side temperature while generating energy as much as possible. To achieve this, this paper designed a kind of intelligent waste heat generation system based on thermoelectric power generator. Three different shape heat sinks are designed, contrasted, and tested. By building experimental platform and establishing simulation model, the power of thermoelectric power generation and temperature change of the three heat sink structures are compared. The fin shaped heat sink is considered has the best output performance while keeping the hot side temperature within the acceptance range. The maximum output power is 10.67mW, and the maximum hot side temperature is 72◦C during the experiment. © 2021 IEEE

关键词： Waste heat

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Generative Adversarial Network Based NDVI Super-resolution Reconstruction 12

Generative Adversarial Network Based NDVI Super-resolution R...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Sun, Zhengbao Pan, Hongyu Yue, Kun Yunnan University School of Engineering Kunming China Chinese Academy of Sciences Aerospace Information Reasearch Institute Beijing China Yunnan University School of Information Science and Engineering Kunming China Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Kunming China

ISBN: (纸本)9798350340181

Low resolution satellite remote sensing images remains a challenge for obtaining high-precision Normalized Difference Vegetation Index (NDVI), and contain some important vegetation cover information for supporting environmental analyses of the surface in large-scale regions, since high-resolution satellite remote sensing observations are still incomplete nowadays. In this paper, we consider the spatial resolution and time series characteristics of remote sensing images, and propose a super-resolution reconstruction algorithm for NDVI fused with Time features by optimizing the Super-Resolution Generative Adversarial Network (TSRGAN). Empirical research in the Salween River estuary area shows that the proposed approach has performance significant advantages in terms of PSNR and SSIM. © 2023 IEEE.

关键词： Remote sensing

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A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot 16th

A Modified Artificial Potential Field Method Based on Subgoa...

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16th International Conference on intelligent Robotics and Applications, ICIRA 2023

作者： Mo, Jixue Gao, Changqing Liu, Fei Yang, Qingkai Fang, Hao Department of Mathematics and Theories Pengcheng Laboratory Shenzhen518055 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Industrial Training Center Shenzhen Polytechnic Shenzhen518055 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789819964826

In this paper, a modified artificial potential field (MAPF) method was proposed for general mobile robot navigation system. This MAPF method can effectively solve the unreachable goal problem and the local minima problem of traditional APF method. The first key idea of MAPF method is to modify the repulsive force function and thus optimize the direction of total repulsive force;the second key idea is to generate a serials of subgoal points around obstacles with specific method, so as to help the robot escape from or keep away from local minima area. By comparing with other similar algorithms in simulation environment, the MAPF algorithm can generate shorter paths efficiently. More importantly, it also can generate effective paths in multi-obstacle environment where other algorithms cannot. Finally the simulation results verified the reasonability and practicability of the proposed MAPF method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion planning

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Design and locomotion characteristic analysis of a novel tensegrity hopping robot

Design and locomotion characteristic analysis of a novel ten...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Mo, Jixue Gao, Changqing Fang, Hao Yang, Qingkai Peng Cheng Laboratory Department of Strategic and Advanced Interdisciplinary Research Shenzhen518055 China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Beijing Institute of Technology School of Automation Beijing100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9798350325706

In consideration of the poor locomotion ability of most traditional tensegrity robot, a novel tensegrity hopping robot powered by push-pull electromagnets was proposed with better locomotivity. It is able to conduct stable consecutive progressing action and turning action through hopping. This paper covers the structural design, theoretical modeling of the robot's hopping process, as well as its self-righting analysis, simulation and experimental verification. The average moving speed and relative moving speed were measured to be 0.334m/s and 0.641 body length/s respectively, which obviously surpass the general moving ability of most traditional tensegrity robot. In addition, the robot was also validated to have good self-righting characteristic for stable consecutive hopping. Thus this robot can be potentially applied for search, rescue, detection, etc. in outdoor and unstructured environment. © 2023 IEEE.

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complex Industrial Process Monitoring using Improved Dynamic Latent Variables - Neighborhood Preserving Embedding

Complex Industrial Process Monitoring using Improved Dynamic...

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Chinese Automation Congress (CAC)

作者： Hancheng Wang Peng Li Mingxi Ai Jiande Wu Chuangyan Yang Qingmin Xu School of Information Science and Engineering name of organization Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In complex industrial process monitoring, prevalent challenges include high dimensionality, extensive redundancies, and dynamic characteristics. In this paper, we propose an Improved Dynamic Latent Variable-Neighborhood Preserving Embedding (DLV -NPE) algorithm specifically designed to tackle these issues. The methodology begins with the implementation of a variance-covariance feature selection method to minimize redundancies among monitoring variables. This is followed using a dynamic latent variable algorithm to extract dynamic regression properties from the selected variables. Subsequently, the NPE algorithm is employed to preserve the residuals of high-dimensional dynamic latent variables and the high-dimensional residuals of selected variables, thereby preserving the integrity of the low-dimensional manifold structure. Finally, Bayesian inference is applied to develop comprehensive monitoring indicators. The efficacy of the DL V -NPE algorithm is validated through its application to the Tennessee Eastman (TE) process, where it demonstrates superior fault detection capabilities compared to other algorithms.

关键词： Process monitoring Manifolds Fault diagnosis Statistical analysis Heuristic algorithms Fault detection Termination of employment Feature extraction Inference algorithms Bayes methods

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Efficient Facial Expression Recognition Network Based on Spot-Adaptive Knowledge Distillation 26

Efficient Facial Expression Recognition Network Based on Spo...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Wen, Xin Liu, Zhen-Tao Chen, Dan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9798331521950

Facial expression recognition plays a key role in promoting the development of comprehensive intelligence and building friendly human-computer interaction. Due to the interference of feature noise in expression data, the lightweight facial expression recognition model with fewer parameters is difficult to learn more expression features through simple training, which limits the improvement of its recognition performance. An efficient facial expression recognition network based on Spot-adaptive Knowledge Distillation is proposed in this paper. Inspired by VoVNetV2, the network designed in this paper is lightweightly improved using Depthwise Separable Convolution and the parameter-free SimAM attention mechanism, reducing the number of parameters to 0.21 M. To further improve the recognition accuracy of the model, Spot-adaptive Knowledge Distillation is employed to improve the characterization ability of the model. The recognition accuracies of the student network designed in this paper on the KDEF and RAF-DB datasets are 93.05% and 81.17% respectively after spot-adaptive distillation. © 2025 IEEE.

关键词： Facial Expression Recognition Knowledge Distillation Lightweight Neural Network

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Semantic Segmentation of Indoor Point Clouds with the Channel Attention Mechanism

Semantic Segmentation of Indoor Point Clouds with the Channe...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Wei Lu, Yisheng Zhang, Tao Chen, Jun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geoexploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

In recent years, the semantic segmentation of 3D point cloud has received increasing attention the field of computer vision, because 3D point cloud can better reflect our 3D space. Because of the unstructured and disordered characteristics of 3D point cloud data, semantic segmentation of point cloud is still a difficult task. Our network automatically learns the importance of feature channels by adding a channel attention module, which enables the network to obtain better training results. After the channel attention module is fused, the important channels in the features are enhanced, and the unimportant channels are suppressed, making the network training more efficient. In this paper, we propose an indoor point cloud semantic segmentation method combined with channel attention mechanism. The experimental results show that our method achieves better results than other methods. © 2022 IEEE.

关键词： Semantic Segmentation

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Manual Alignment of Dual End-Effectors for Piezo-Driven Microhand

Manual Alignment of Dual End-Effectors for Piezo-Driven Micr...

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IEEE International Conference on Real-time computing and Robotics (RCAR)

作者： Jichao Pang Dan Liu Xiaoqing Tang Yan Chen Qiang Huang Tatsuo Arai Xiaoming Liu Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical EngineeringBeijing Institute of Technology Key Laboratory of Biomimetc Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

In recent years, micromanipulator with dual end-effectors called microhand has been widely used in industrial and biological fields. Whether the tip positions of the two end-effectors of the microhand can be accurately aligned seriously affects the precise grasping of the microhand. However, few researchers have presented practical ways for precisely aligning the tip positions of a 6-DOF microhand’s two end- effectors. This paper proposes a novel, inexpensive, lightweight, robust, and easy-to-use microhand dual end-effectors clamping device that can precisely and quickly align the two end-effectors of a 6-DOF microhand. First, we describe the microhand dual end-effectors clamping device’s lightweight structural design. After that, we simplify the microhand dual end-effectors clamping device model and create a mathematical model to determine the relationship between the end-effectors’ tip position and the rotation angles of screw No.1, screw No.2, screw No.3 of the microhand dual end-effectors clamping device. Through experimentation, we are able to attain precise alignment of the two end-effectors tip positions of the 6-DOF microhand, so we confirm that our mathematical model is true. Finally, we use the impulse response of PZT in the microhand’s lower module to confirm the stability of the microhand dual end- effectors clamping device. We believe that the proposed the microhand dual end-effectors clamping device has great potential in industrial and biological applications as a universal tool for precise alignment of the tip positions of the two end-effectors of a 6-DOF microhand.

关键词： Costs Accuracy Fasteners End effectors 6-DOF Mathematical models Biology

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Diagnosis of Diabetes Type Using Random Forest Algorithm and SVM for Improving Accuracy 1

引用

International Conference on Advances in Communication Technology and Computer Engineering, ICACTCE 2023

作者： Hai, Tao Zhou, Jincheng Olatunji, Timothy A. Ajoboh, Oluwakemi A. Chen, Lee Iwendi, Celestine Omeoga, Nkechi Sinha, Anurag School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun558000 China Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education Guizhou University Guizhou Guiyang550025 China School of Information and Artificial Intelligence Nanchang Institute of Science and Technology Nanchang China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Duyun558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Qiannan Duyun558000 China School of Creative Technologies University of Bolton BoltonBL3 5AB United Kingdom Manchester Metropolitan University Manchester United Kingdom Department of Computer Science and Information Technology IGNOU New Delhi India

ISBN: (数字)9783031371646

ISBN: (纸本)9783031371639

To improve the accuracy in the detection of diabetes-type diagnosis using Random Forest Algorithm and Support Vector Method. A dataset on diabetes was collected on ***. Support vector method analysis was performed on the data using kernel as linear, poly, and rbf with random state = 42 and test size = 0.2. The Random Forest Algorithm with n_estimators = 100 has the same accuracy as the support vector method with the kernel as rbf. When it comes to type diagnosis for a patient having diabetes, the Random Forest Algorithm and Support Vector Method with kernel rbf can be used, unlike another kernel of the Support Vector Method. The dataset was also visualized using power. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Radial basis function networks

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