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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Zhang, Pengyu Zhang, Wei Mao, Li Chen, Jiayi Hu, Zhi Shanghai University of Engineering Science Laboratory of Intelligent Control and Robotics 333 Longteng Road Shanghai China Computer Engineering College Dalian University of Technology 1 Guangning Road Dalian China

ISBN: (纸本)9789819733231

This paper explores positive edge-consensus in directed networks with spanning trees using output feedback protocols. First, a novel positive system observer is proposed, which introduces a parameter to enhance the design freedom of the observer. Furthermore, using positive system theory and graph theory, sufficient conditions are proposed and the sufficient conditions based solely on the network’s edge count. Specifically, an optimized bound is given for the eigenvalue of the Laplacian matrix, and an improved consensus and non-negative condition is obtained. Finally, the effectiveness of the proposed control protocol is verified utilizing numerical simulations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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DialogNTM: Context Reconstruction in Multi-Turn Dialogue Generation using Neural Turing Machines

DialogNTM: Context Reconstruction in Multi-Turn Dialogue Gen...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhao, Haohao Liu, Meiling Zhou, Jiyun Fu, Kaiquan College of Computer and Control Engineering Northeast Forestry University Harbin China Lieber Institute Johns Hopkins University Baltimore United States South Dakota State University Department of Electrical Engineering and Computer Science BrookingsSD United States

ISBN: (纸本)9781665410205

In actual conversational scenarios, we can often determine which parts of the previous dialogue are more critical based on the current inquiry. However, the existing contextual modeling methods often encode the query sentence and the dialogue history in a unified manner, which fails to effectively highlight the inference effect of the query sentence. Moreover, these methods typically process the dialogue history only at the information extraction level, neglecting the treatment of the context itself. In this paper, we propose a novel conversational context modeling technique called DialogNTM. Based on the guidance of the query sentence, the technology can effectively eliminate redundant information by reconstructing the representation of the context. Specifically, we have tweaked the memory and input flow of the Neural Turing Machine (NTM) to encode contextual information in memory and guide the read, write, and erase operations of memory through query sentence. This design simulates the human brain's dynamic retrieval and renewal mechanism of previous memories when dealing with current problems. We have conducted extensive experiments on three publicly available datasets to verify the effectiveness of the DialogNTM model. Compared to the benchmark model, DialogNTM showed significant performance improvements ranging from 11% to 73% across multiple automated evaluation metrics (3.52% to 8.68% in absolute terms). © 2024 IEEE.

关键词： Turing machines

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Detection of healthy and pathological heartbeat dynamics in ECG signals using multivariate recurrence networks with multiple scale factors

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Chinese Physics B 2023年第10期32卷 273-282页

作者：马璐陈梅辉何爱军程德强杨小冬 School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Suzhou Vocational and Technical College Suzhou 234000China School of Computer Science and Technology China University of Mining and TechnologyXuzhou 221116China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China

The electrocardiogram(ECG)is one of the physiological signals applied in medical clinics to determine health *** physiological complexity of the cardiac system is related to age,disease,*** the investigation of the effects of age and cardiovascular disease on the cardiac system,we then construct multivariate recurrence networks with multiple scale factors from multivariate time *** propose a new concept of cross-clustering coefficient entropy to construct a weighted network,and calculate the average weighted path length and the graph energy of the weighted network to quantitatively probe the topological *** obtained results suggest that these two network measures show distinct changes between different *** is because,with aging or cardiovascular disease,a reduction in the conductivity or structural changes in the myocardium of the heart contributes to a reduction in the complexity of the cardiac ***,the complexity of the cardiac system is *** that,the support vector machine(SVM)classifier is adopted to evaluate the performance of the proposed *** of 94.1%and 95.58%between healthy and myocardial infarction is achieved on two ***,this method can be adopted for the development of a noninvasive and low-cost clinical prognostic system to identify heart-related diseases and detect hidden state changes in the cardiac system.

关键词： electrocardiogram signals multivariate recurrence networks cross-clustering coefficient entropy multiscale analysis

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Docking to a Specific Person of an Autonomous Mobile Manipulator Using UWB Positioning and RGB-D Camera

Docking to a Specific Person of an Autonomous Mobile Manipul...

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2023 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2023

作者： Song, Kai-Tai Huang, Yu-Yun Deng, Shu-Huan Hsieh, Yuan-Shuo National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Institute of Electrical and Control Engineering Hsinchu Taiwan

ISBN: (纸本)9798350302714

In this paper, a novel navigation method is proposed to dock a mobile manipulator in front of a specific person by combining the ultra-wideband (UWB) positioning system with image-based motion control. The UWB is used for a longer distance human identification and positioning. As the robot approaches the target person, face recognition and face pose estimation are used for close docking control the person. The experimental results show that the average error of docking to a person is 5.2° in orientation and 8.48cm in distance. The integrated experimental results demonstrate that the autonomous mobile manipulator can navigate to a target person and handover an object to the person. © 2023 IEEE.

关键词： Face recognition

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Boarding Pass Positioning with Jointly Multi-channel Segmentation and Perspective Transformation Correction 4th

Boarding Pass Positioning with Jointly Multi-channel Segmen...

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Wu, Jiahui Li, Zuoyong Keikhosrokiani, Pantea Cai, Yuanzheng College of Computer and Data Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Computer Sciences Universiti Sains Malaysia Penang Minden11800 Malaysia

ISBN: (纸本)9783031200953

To solve the problem of boarding pass positioning with image tilt and sticking, we proposed a jointly boarding pass positioning and correction algorithm using multi-channel color components. First, a local threshold segmentation is performed on red and blue components in RGB color space to determine the general area of the boarding pass. Then, edge detection is performed on the blue component and pixel value standardization statistics on the three components to obtain partial edges and internal information of the boarding pass to refine the binary image. Next, the watershed algorithm is used to achieve precise positioning of the boarding pass. Finally, the segmentation and the boarding pass are completely rectified through perspective transformation. The results of segmentation and correction of boarding passes in actual scenarios show that the proposed algorithm can complete segmentation and correction under complex conditions such as boarding pass images sticking to each other, uneven illumination, and large-angle tilt. The average time spent on the test set is 0.049s, and the segmentation and correction success rate is 95.16 %. The proposed algorithm has high application value. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Binary images

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PCB Defect Detection Method Based on Improved RetinaNet 1

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Xu, Yusheng Cao, Xinrong Hu, Rong Keikhosrokiani, Pantea Li, Zuoyong College of Computer Science and Mathematics Fujian University of Technology Fuzhou350118 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Computer Sciences Universiti Sains Malaysia Penang11800 Malaysia

ISBN: (数字)9783031200991

ISBN: (纸本)9783031200984

In the electronic industry product quality control, PCB defect detection is a crucial part, which has the characteristics of small defect size and high similarity. The existing defect detection methods are still not good enough for detecting small target defects;therefore, the algorithm in this paper proposes an improved algorithm for PCB defect detection based on the RetinaNet model. The ResNet-D residual structure and efficient channel focus module are introduced in the model backbone network to enhance its feature extraction capability and achieve the purpose of improving the detection accuracy. At the same time, the method replaces the original multi-step learning decay strategy with a cosine annealing scheduling learning strategy, which optimizes the training process of the model. Finally, the performance of the method is verified on the publicly available PCB defect dataset from the Open Laboratory of Intelligent Robotics, Peking University. The experimental results show that the algorithm improves the mAP value by 3.2% compared with the original algorithm, while the fastest detection speed reaches 36.9 FPS, which can effectively improve the defect detection performance of PCB. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Defects

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Detection of EEG signals in normal and epileptic seizures with multiscale multifractal analysis approach via weighted horizontal visibility graph

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Chinese Physics B 2023年第11期32卷 401-407页

作者：马璐任彦霖何爱军程德强杨小冬 School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Suzhou Vocational and Technical College Suzhou 234000China School of Computer Science and Technology China University of Mining and TechnologyXuzhou 221116China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China

Electroencephalogram(EEG) signals contain important information about the regulation of brain system. Thus, automatic detection of epilepsy by analyzing the characteristics obtained from EEG signals has important research implications in the field of clinical medicine. In this paper, the horizontal visibility graph(HVG) algorithm is used to map multifractal EEG signals into complex networks. Then, we study the structure of the networks and explore the nonlinear dynamics properties of the EEG signals inherited from these networks. In order to better describe complex brain behaviors, we use the angle between two connected nodes as the edge weight of the network and construct the weighted horizontal visibility graph(WHVG). In our studies, fractality and multifractality of WHVG are innovatively used to analyze the structure of related networks. However, these methods only analyze the reconstructed dynamical system in general characterizations,they are not sufficient to describe the complex behavior and cannot provide a comprehensive picture of the system. To this effect, we propose an improved multiscale multifractal analysis(MMA) for network, which extends the description of the network dynamics features by focusing on the relationship between the multifractality and the measured scale-free ***, neural networks are applied to train the above-mentioned parameters for the classification and identification of three kinds of EEG signals, i.e., health, interictal phase, and ictal phase. By evaluating our experimental results, the classification accuracy is 99.0%, reflecting the effectiveness of the WHVG algorithm in extracting the potential dynamic characteristics of EEG signals.

关键词： epilepsy EEG signal horizontal visibility graph complex network

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A Multi-robot Exploration Approach for Larger Maps with Unreliable Communications

A Multi-robot Exploration Approach for Larger Maps with Unre...

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2022 IEEE International Conference on Unmanned Systems, ICUS 2022

作者： Wu, Lingxin Luo, Haibo College of Computer and Data Science College of Software FuZhou University Fuzhou China College of Computer and Control Engineering Minjiang University Fuzhou China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

The issues of limited communication distance and task capability are rarely discussed in designing multi-robot cooperative methods. However, these are important problems that cannot be avoided in practical applications. In this paper, simulation experiments are carried out on some task maps that are larger than the team's task ability. The effect of the dispersion of members on the team's task performance is tested, and the existing methods are improved by introducing long-range communication to auxiliary data sharing. At the same time, we use the calculation of Energy-Benefit to improve the task selection method based on the minimum distance to the target. Compared with existing strategies, the improved scheme performs better on communication-constrained large-map exploration tasks. © 2022 IEEE.

关键词： Multipurpose robots

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PEBU-Net: A lightweight segmentation network for blueberry bruising based on Unet3+ using hyperspectral transmission imaging

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Measurement: Journal of the International Measurement Confederation 2025年 253卷

作者： Dai, Jingyuan Wang, Guozheng Yang, Mianqing Liu, Dayang College of Computer and Control Engineering Northeast Forestry University Heilongjiang Harbin150040 China

Quantitative segmentation of blueberry bruising is essential for farmers and processors to effectively manage blueberries of varying quality, thereby improving economic returns. This study proposed a lightweight semantic segmentation model called PEBU-Net, which accurately detects internal bruising in blueberries resulting from mechanical damage using hyperspectral transmittance images (HSTIs). The model is based on the UNet3 + architecture, utilizing fewer filters to create a lightweight framework. Subsequently, a partial self-attention module is used to reduce the impact of redundant information. Then, a novel encoder module is proposed to retain key features during the downsampling process. In addition, using atrous spatial pyramid pooling, which incorporates an efficient multi-scale attention mechanism, enhances the model's ability to extract high-level features at different scales. Finally, the performance of the proposed model was validated by ablation experiments, comparison experiments, and visualization images of the segmentation result. The results showed that the accuracy, dice coefficients, and mean intersection over union of PEBU-Net for blueberry bruise segmentation were 95.1 %, 93.4 %, and 84.8 %, respectively. These results demonstrated improvements of 1.4 %, 2 %, and 4.4 % over the baseline model. Compared to other semantic segmentation models, the proposed PEBU-Net achieved optimal segmentation performance. Concurrently, the model size of just 7.6 MB significantly reduces the computational cost and memory usage in practical applications. The proposed lightweight segmentation model based on HSTIs achieves high-precision segmentation of bruised blueberries, which provides a technical reference for bruise segmentation of other fruits. © 2025 Elsevier Ltd

关键词： Semantic Segmentation

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Drift-free localisation using prior cross-source map for indoor low-light environments

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IET Cyber-Systems and Robotics 2023年第1期5卷 122-131页

作者： Junyi Tao Weichen Dai Da Kong Jiayan Wan Bin He Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina School of Computer Science Hangzhou Dianzi UniversityHangzhouChina Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province HangzhouChina

In this study,a localisation system without cumulative errors is ***,depth odometry is achieved only by using the depth information from the depth *** the point cloud cross-source map registration is realised by 3D particle filtering to obtain the pose of the point cloud relative to the ***,we fuse the odometry results with the point cloud to map registration results,so the system can operate effectively even if the map is *** effectiveness of the system for long-term localisation,localisation in the incomplete map,and localisation in low light through multiple experiments on the self-recorded dataset is *** with other methods,the results are better than theirs and achieve high indoor localisation accuracy.

关键词： indoor positioning robots

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