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Chimera-inspired dynamics: When higher-order interactions are expressed differently

Physical Review E 2024年第4期110卷 044204页

作者： Xinrui Ji Xiang Li Institute of Complex Networks and Intelligent Systems Shanghai Research Institute for Intelligent Autonomous Systems The Frontiers Science Center for Intelligent Autonomous Systems and The State key laboratory of Intelligent Autonomous Systems Department of Control Science and Engineering College of Electronics and Information Engineering

The exploration of chimera-inspired dynamics in nonlocally coupled networks of Kuramoto oscillators with higher-order interactions is still in its nascent stages. Concurrently, the investigation of collective phenomena in higher-order interaction networks is gaining attraction. Here, we observe that hypergraph networks tend to synchronize through lower-order interactions, whereas simplicial complex networks exhibit a preference for higher-order interactions. This observation suggests that higher-order representations manifest substantial differences in chimera-inspired synchronization regions. Moreover, we introduce an explicit expression for identifying the chimera state. With a comprehensive basin stability analysis and the interplay of pairwise and higher-order interaction strengths, the emergence of the chimera state is inherent in high-order interaction networks. Our findings contribute to the understanding of chimera-inspired dynamics in higher-order interaction networks.

关键词： Chimera states Continuous phase transition Coupled oscillators Synchronization Synchronization transition

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EMOST: A dual-branch hybrid network for medical image fusion via efficient model module and sparse transformer

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Computers in Biology and Medicine 2024年 179卷 108771-108771页

作者： Wang, Wenqing He, Ji Liu, Han School of Automation and Information Engineering Xi'an University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

Multimodal medical image fusion fuses images with different modalities and provides more comprehensive and integrated diagnostic information. However, current multimodal image fusion methods cannot effectively model non-local contextual feature relationships, and due to direct aggregation of the extracted features, they introduce unnecessary implicit noise into the fused images. To solve the above problems, this paper proposes a novel dual-branch hybrid fusion network called EMOST for medical image fusion that combines a convolutional neural network (CNN) and a transformer. First, to extract more comprehensive feature information, an effective feature extraction module is proposed, which consists of an efficient dense block (EDB), an attention module (AM), a multiscale convolution block (MCB), and three sparse transformer blocks (STB). Meanwhile, a lightweight efficient model (EMO) is used in the feature extraction module to exploit the efficiency of the CNN with the dynamic modeling capability of the transformer. Additionally, the STB is incorporated to adaptively maintain the most useful self-attention values and remove as much redundant noise as possible by developing the top-k selection operator. Moreover, a novel feature fusion rule is designed to efficiently integrate the features. Experiments are conducted on four types of multimodal medical images. The proposed method shows higher performance than the art-of-the-state methods in terms of quantitative and qualitative evaluations. The code of the proposed method is available at https://***/XUTauto/EMOST. © 2024 Elsevier Ltd

关键词： Feature extraction

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Minimal Curvature and Range Path Connecting Two Oriented Points

Minimal Curvature and Range Path Connecting Two Oriented Poi...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Guo, Kun Xu, Cheng Wei, Zhenyan Xu, Heng Beijing Institute of Mechanical and Electrical Engineering Beijing100074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing100074 China

ISBN: (纸本)9789811694912

Time and acceleration constraints have been extensively considered in flight vehicle path planning area. However, the limits of the required acceleration guaranteeing the existence of a path has not been fully studied yet. This paper presents an algebraic proof of the minimax curvature path connecting two oriented points with one inflection point, and then the minimal required acceleration and flight time are analyzed for all planar scenarios. It is revealed that for some geometry conditions, there exists a specific combination of curvature and range limits, while for other conditions, this combination can change continuously by increasing one and decreasing another. For all cases, the optimal paths are concatenations of circular arcs of equivalent radii in different forms, which means that to reduce the acceleration and flight time to the utmost, the overload should be evenly distributed along the whole path. The results in this paper can support fast on-line path planning in the presence of incident direction constraint with limited maneuverability and fuel. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion planning

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Research on Multi-target Association Tracking Algorithm Based on IMM

Research on Multi-target Association Tracking Algorithm Base...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Siting, Peng Lei, Li Yichao, Ma Jun, Ren Beijing Electro-Mechanical Engineering Institute Beijing100074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811694912

Radar sensors are important detection and tracking equipment in national defense work. There are multiple targets in actual combat scenarios. It is necessary to quickly and accurately capture suspicious targets in the reconnaissance area and track them in real time. complex electromagnetic interference conditions and multi-target tracking requirements pose a great challenge to track correlation. This paper establishes a multi-target maneuver scenario and uses a joint probabilistic data interconnection algorithm based on interactive multi-model (IMM) to perform multi-target tracking. Correlation tracking, simulation results show that the algorithm is used to correlate the target maneuver and measurement information with good accuracy. Interactive multi-model filtering can mix the estimation results of each filter to generate a fused state estimation result. The description of the model is more accurate, which improves the tracking accuracy and tracking stability of the algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Kalman filters

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Multi-Destination Cooperative Task Offloading in Blockchain-Based Vehicular Edge Computing Networks

Multi-Destination Cooperative Task Offloading in Blockchain-...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Lang, Ping Tian, Daxin Duan, Xuting Zhou, Jianshan State Key Lab of Intelligent Transportation System Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China School of Transportation Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798350316308

As a novel computing paradigm, the Vehicular Edge Computing (VEC) network provides an additional avenue for onboard task execution for connected and automated vehicles (CAVs) in unmanned systems. In a VEC network, CAVs can offload tasks to different external servers for execution and obtain results. However, existing task offloading studies only focus on the one-to-one offloading of onboard tasks to edge servers, ignoring the requirements of parallel task execution and security. In this paper, we propose a blockchain-based multi-destination cooperative task offloading architecture in a VEC network. Based on this architecture, we analyze the task offloading and blockchain models and formulate a multi-destination cooperative task offloading optimization problem. Finally, we compare the performance of different multi-destination task offloading methods in simulations and demonstrate the effectiveness of the proposed architecture and optimization. © 2023 IEEE.

关键词： Blockchain

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Error Modeling Method of Aircraft HWIL Simulation system Based on BP Wavelet Neural Network 18th

Error Modeling Method of Aircraft HWIL Simulation System Ba...

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18th Chinese intelligent systems Conference, CISC 2022

作者： Tong, Jiahui Liu, Jin Li, Jing Zhang, Qing Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100190 China Beijing Electro-Mechanical Engineering Institute Beijing102299 China

ISBN: (纸本)9789811962028

In order to ensure the confidence of hardware-in-the-loop(HWIL) simulation results, the simulation equipment and system are required to simulate the realistic flight environment;However, the additional error introduced by the simulation system in the guidance and control loop should be minimized. By studying the error model of the aircraft HWIL simulation system and analyzing the impact of the HWIL simulation system on the guidance and control quality, we can recognize the real performance of the guidance and control system, find out the key factors affecting the performance of the HWIL simulation system, provide decision-making basis for the development of simulation equipment, and improve and enhance the reliability of the simulation system. Based on BP wavelet neural network, the mathematical modeling of the aircraft HWIL simulation system error is carried out, and the modeling method and process are introduced in detail. A new method of aircraft HWIL simulation system error modeling with input and output data is proposed, and the applicability of modeling method is analyzed, and satisfactory accuracy results are obtained. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Errors

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Remote Sensing Image Object Detection Algorithm Based on Receptive Field Enhancement

Remote Sensing Image Object Detection Algorithm Based on Rec...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： MingJun, Liu Yun, Zhang Rui, Zhang Cheng, Xu Beijing Electro-Mechanical Engineering Institute Beijing10074 China Science and Technology on Complex System Control and Intelligent Agent Corporation Laboratory Beijing10074 China

ISBN: (纸本)9789811694912

Small object detection algorithm is always a difficult research topic in remote sensing images. A remote sensing image object detection algorithm which is based on receptive field enhancement is proposed in this paper. Firstly, the backbone network is the SSD net. In order to form the feature map pyramid, the receptive field enhanced convolution module is added in feature extraction. Then, the feature maps of the low-level and the high-level are spliced, so he output feature map retains the rich context information. Because it contains the information in the low-level feature map and the high-level feature map, which are location information and semantic information, respectively. Finally, based on the idea of dilated convolution, the receptive field enhancement module is designed to make the receptive field of the feature map larger. And the feature information is filtered to reduce the aliasing effect when the feature map is spliced. After the experimental result on remote sensing image dataset NWPU vhr-10, the average detection accuracy of the algorithm is 90%, which improves the object detection accuracy, especially the detection accuracy of the small objects. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolution

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Relative Roughness Measurement Based Real-Time Speed Planning for Autonomous Vehicles on Rugged Road

Relative Roughness Measurement Based Real-Time Speed Plannin...

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

作者： Liang Wang Tianwei Niu Shoukun Wang Shuai Wang Junzheng Wang Key Laboratory of Drive and Control of Servo Motion System School of Automation Beijing Institute of Technology Beijing China The State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing Institute of Technology Beijing China

In order to guarantee autonomous vehicles' autonomy, mobility, and ride quality in rugged environments, a real-time speed planning method based on the time-frequency transformation of terrain characteristics is designed to achieve adaptive speed planning of autonomous vehicles in rough ground. On the one hand, the vertical profile of the lidar's point cloud data is converted from the time domain to the frequency domain in real time, and the integrated area of the sub-frequency range in the frequency domain is chosen as the relative roughness quantification value to realize the roughness quantification under various terrains. On the other hand, to model the relationship between vehicle speed and relative roughness, iterative search is utilized to create a speed and roughness model, and sliding windows are employed to update the roughness to achieve continuous mapping between speed and roughness. Ultimately, a number of tests were conducted on various rough roads using the oil exploration vehicle EV-56 as the study object. The experimental results show that the proposed method can identify the terrain roughness changes under complex terrain and change their speed within 0.2 m accuracy.

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Design, Analysis, and Experiment of a Novel Ultrasonic Printing system

Design, Analysis, and Experiment of a Novel Ultrasonic Print...

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2022 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2022

作者： Pei, Zhichao Zhao, Haoxiang Li, Dongjie Wang, Lefeng Rong, Weibin Sun, Lining Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin China Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin China

ISBN: (数字)9781665475433

ISBN: (纸本)9781665475433

Ultrasonic-driven printing technology is widely used in bioprinting because of its high precision, good biocompatibility, and low cost. However, the conventional ultrasonic printing technology still has problems such as cross-contamination of bio-ink during storage, transportation, and processing, and cumbersome ink replacement process. Therefore, a new ultrasonic printing device is developed in this paper, which uses PZT plates as the driving element. And a fluid sub-system has been fabricated based on the self-made glass micro-nozzle, which is connected to the drive element using ultrasonic couplant gel. The separation of the fluid system and the drive system has been realized through the modular design, thereby realizing the rapid replacement of different inks and this relatively independent fluid system is of great benefit to better sealing and aseptic operation. In addition, a digital model is built to analyze its working mechanism. And an experimental system is established to characterize the performance of the device. The results show that the system can generate droplets stably and accurately, and the droplet volume can be controlled by the excitation voltage amplitude and pulse width. © 2022 IEEE.

关键词： Biocompatibility

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A 3D Point Attacker for LiDAR-Based Localization

A 3D Point Attacker for LiDAR-Based Localization

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International Conference on control and Automation (ICCA)

作者： Shiquan Yi Jiakai Gao Yang Lyu Lin Hua Xinkai Liang Quan Pan School of Automation Northwestern Polytechnical University Xi'an Shaanxi PR China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing PR China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

The safety and security issues of autonomous navigation function become the main obstacles that hinder the widespread applications of self-driving cars and unmanned systems. In this paper, we investigate the vulnerability of LiDAR-based localization methods to adversarial attacks. Specifically, we developed a feature-based spoofing attack strategy to degrade the localization performance of LiDAR-based localization algorithms. Reflecting on the vulnerability, we additionally provide a resilient strategy to defend existing LiDAR-based localization methods against this attack. The proposed attack strategy is tested on the KITTI dataset to illustrate its effectiveness.

关键词： Location awareness Simultaneous localization and mapping Laser radar Accuracy Three-dimensional displays Perturbation methods Feature extraction

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