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IEEE Joint International information Technology and Artificial Intelligence Conference (ITAIC)

作者： Siyu Chen Wei Li School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan People’s Republic of China Image Processing and Intelligent Control Key Laboratory Education Ministry of China Wuhan People’s Republic of China

ISBN: (数字)9781728152448

ISBN: (纸本)9781728152455

In recent years, Deep Neural Network (DNN) has been widely used in the domain of computer vision, but its further development is restricted because of the lack of train samples. Fine-tuning is one of deep transfer learning methods to solve this problem. Nowadays, some existing Fine-tuning approaches assume that if the fine-tuned network could be as close to the pre-trained network as possible, the source knowledge would be fully utilized to improve the study effect. Although these approaches work pretty well, the assumptions on which they are based have not been systematically proved. Due to the complexity of DNNs, offering a reasonable and accurate explanation of the performance of the network is significant for designing new algorithms. In this paper, we design a series of experiments with or without transfer learning respectively, to characterize the relationship between network differences and network performance. The results show that there is an obvious negative correlation between them under certain circumstances. This conclusion can not only provide a more reasonable explanation for the relevant transfer learning algorithm, but also provide support and inspiration for the future work.

关键词： Knowledge engineering Correlation Transfer learning Neural networks Task analysis information technology Knowledge transfer

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Spatiotemporal prediction of ionospheric TEC based on denoising wavelet transform convolution

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GPS Solutions 2025年第3期29卷 1-17页

作者： Zhou, Rui Wu, Yanxiong Cai, Jianxian Liu, Haijun Le, Huijun Xiao, Jian Ma, Yan Institute of Intelligent Emergency Information Processing Institute of Disaster Prevention Langfang China College of Electronic Science and Control Engineering Institute of Disaster Prevention Langfang China Langfang Key Laboratory of Accurately-Controlled Active Seismic Source Sanhe China Hebei Key Laboratory of Seismic Disaster Instrument and Monitoring Technology Sanhe China Key Laboratory of Earth and Planetary Physics Institute of Geology and Geophysics Chinese Academy of Sciences Beijing China College of Earth and Planetary Sciences University of the Chinese Academy of Sciences Beijing China

The existing ionospheric Total Electron Content (TEC) spatiotemporal prediction models, such as Convolutional Gated Recurrent Unit (ConvGRU), Convolutional Long Short-Term Memory (ConvLSTM) and Prediction Recurrent Neural Networks (PredRNN) are all convolution-based models, which will encounter difficulties in extracting low-frequency features using large convolution kernels due to over parametrization. One solution is to replace convolution with the recently proposed wavelet transform convolution (WTConv), which convolves in the wavelet transform domain. However, there is a noise band in wavelet transform domain, and WTConv did not consider its adverse effects. To address this issue, this article proposed denoising wavelet transform convolution (DWTConv) by removing the noise from WTConv. Then, we proposed DWTConvLSTM by replacing the convolution in ConvLSTM with DWTConv. In addition, an attention module called Channel and Spatial Attention (CSA) was proposed to focus on important features. Based on DWTConvLSTM and CSA, this paper proposed a spatiotemporal model CSA-DWTConvLSTM for TEC prediction. Finally, the proposed CSA-DWTConvLSTM was compared with 4 state-of-the-art models in TEC prediction, including C1PG, ConvGRU, ConvLSTM and PredRNN on a 6-year Global Ionospheric Maps (GIMs), with 4 years as the training set and 2 years as the test set. The experimental results indicate that compared to C1PG, ConvGRU, ConvLSTM, and PredRNN, CSA-DWTConvLSTM’s RMSE decreased by 21.22%, 17.08%, 14.26%, and 11.57% in high solar activity years, and by 24.53%, 21.61%, 17.32%, and 13.28% in low solar activity years. Additionally, the superiority of CSA-DWTConvLSTM was further validated from both spatial and temporal perspectives, as well as in extreme situations. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Channel and spatial attention Spatiotemporal prediction Total electron content Wavelet transform

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Interdependence between individual and social learning shapes cooperation with asymmetric exploration

arXiv

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arXiv 2025年

作者： Hou, Zhihao She, Zhikun Liang, Quanyi Su, Qi Li, Daqing School of Mathematical Sciences Beihang University Beijing100191 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Reliability and Systems Engineering Beihang University Beijing100083 China

Cooperation on social networks is crucial for understanding human survival and development. Although network structure has been found to significantly influence cooperation, some human experiments indicate that it cannot fully explain the evolutionary patterns of cooperation. While evidence suggests that this gap arises from human exploration, our understanding of its impact mechanisms and characteristics, such as asymmetry, remains limited. Here, we seek to formalize human exploration as an individual learning process involving trial and reflection, and integrate social learning to examine how their interdependence shapes cooperation. We find that individual learning can alter the imitative tendency of social learning, while its cooperative tendency in turn relies on social learning and players' decision preferences. By analyzing a series of key experiments, we show that the above coupled dynamics can explain human behavior in game interactions. Furthermore, we find that individual learning can promote cooperation when its probability is negatively correlated with payoffs, a mechanism rooted in the psychological tendency to avoid trial-and-error when individuals are satisfied with their current payoffs. These results link long-unexplained asymmetric exploration with the cooperation-promoting ability of social networks, helping to bridge the gap between theoretical research and reality. © 2025, CC BY.

关键词： Human engineering

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Correlation-aware deep generative model for unsupervised anomaly detection

arXiv

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arXiv 2020年

作者： Fan, Haoyi Zhang, Fengbin Wang, Ruidong Xi, Liang Li, Zuoyong School of Computer Science and Technology Harbin University of Science and Technology Harbin150080 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

Unsupervised anomaly detection aims to identify anomalous samples from highly complex and unstructured data, which is pervasive in both fundamental research and industrial applications. However, most existing methods neglect the complex correlation among data samples, which is important for capturing normal patterns from which the abnormal ones deviate. In this paper, we propose a method of Correlation aware unsupervised Anomaly detection via Deep Gaussian Mixture Model (CADGMM), which captures the complex correlation among data points for high-quality low-dimensional representation learning. More specifically, the relations among data samples are correlated firstly in forms of a graph structure, in which, the node denotes the sample and the edge denotes the correlation between two samples from the feature space. Then, a dual-encoder that consists of a graph encoder and a feature encoder, is employed to encode both the feature and correlation information of samples into the low-dimensional latent space jointly, followed by a decoder for data reconstruction. Finally, a separate estimation network as a Gaussian Mixture Model is utilized to estimate the density of the learned latent vector, and the anomalies can be detected by measuring the energy of the samples. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed *** Codes 68T30 Copyright © 2020, The Authors. All rights reserved.

关键词： Anomaly detection

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Abnormal resting-state EEG power and impaired inhibition control in young smokers

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Neuroscience Letters 2021年 761卷 136120页

作者： Dong, Fang Li, Xiaojian Zhang, Yunmiao Jia, Shaodi Zhang, Shidi Xue, Ting Ren, Yan Lv, Xiaoqi Yuan, Kai Yu, Dahua Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou 014010 Inner Mongolia China College of Information Engineering Inner Mongolia University of Technology Hohhot 010051 Inner Mongolia China School of Life Science and Technology Xidian University Xi'an 710071 Shaanxi China

Exposure to nicotine during adolescence may cause neurophysiological changes and increase the risks of developing nicotine dependence;it can even lead to lifelong smoking. The intake of nicotine may also lead to abnormal patterns of oscillatory brain activity and inhibition control deficits. However, little is known about the specific relationship between oscillatory brain activity during the resting state and inhibition control capacity in young smokers. In the present study, we acquired resting-state electroencephalography (EEG) data from thirty-four young smokers and 39 age-matched non-smoking controls. Inhibition control performance was measured by a Go/NoGo task. Compared with non-smoking controls, we detected reduced low-frequency delta band activity in the frontal, central and posterior cortices of young smokers. Furthermore, young smokers committed more errors in response to infrequent NoGo trials. Notably, we demonstrated that delta absolute power in the frontal region was negatively correlated with NoGo errors and that alpha power in the central region was positively correlated with NoGo errors in non-smoking controls but not in young smokers. These findings may suggest that these inhibitory control processes were associated with alterations in oscillatory brain activity during the resting state. Our findings suggest that alterations of power spectra in delta bands may act as a useful biomarker of inhibitory control performance and provide a scientific basis for the diagnosis and treatment of nicotine addiction in adolescents. © 2021 Elsevier B.V.

关键词： Brain oscillations Electroencephalography (EEG) Inhibition control Resting state Young smokers

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Research on Attitude control of Quadrotor UAV Based on Active Disturbance Rejection control

Research on Attitude Control of Quadrotor UAV Based on Activ...

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Chinese control and Decision Conference, CCDC

作者： Zuling Song Yongji Wang Lei Liu Zhongtao Cheng Ye Yang National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Science and Technology on Aerospace Intelligent Control Laboratory Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

Aiming at enhancing the disturbance suppression ability of attitude control of quadrotor UAV (Unmanned Aerial Vehicle), design an ADRC(Active Disturbance Rejection control) based on quadrotor UAV. Different from the traditional trial adjustment of the parameter b0 in ADRC design, it can be derived according to the characteristics of the quadrotor model in this paper. Firstly, a non-linear kinematic model of a quadrotor UAV is established, and then each module of the ADRC is designed and debugged by modules. Finally, the system is simulated and verified. The experimental results show that ADRC has a stronger disturbance suppression capability than PID control, which greatly improves the stability of the system and enhances the drone's flight control ability in complex environments.

关键词： Attitude control Unmanned aerial vehicles Propellers Aircraft Robust control Atmospheric modeling

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Learning Latent Semantic Attributes for Zero-Shot Object Detection

Learning Latent Semantic Attributes for Zero-Shot Object Det...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Kang Wang Lu Zhang Yifan Tan Jiajia Zhao Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China

ISBN: (数字)9781728192284

ISBN: (纸本)9781728185361

Zero-shot Object Detection (ZSD) aims to locate and classify instances of unseen categories. Existing methods focus on learning the mapping from visual space to semantic space, while the learning of discriminative representations for ZSD has not gained enough attention. In this paper, we demonstrate the necessity to learn discriminative semantic representations for ZSD, and propose a new end-to-end framework for this task. Our framework is able to learn discriminative semantic representations in an augmented space introduced for both user-defined and latent attributes, and refine the user-defined attributes with the help of unseen and external classes. The proposed method is extensively evaluated on two challenging ZSD datasets, and the experimental results show that our method significantly outperforms several existing methods.

关键词： Visualization Conferences Semantics Object detection Tools Boosting Task analysis

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control-oriented fault detection of solid oxide fuel cell system unknown input on fuel supply

Control-oriented fault detection of solid oxide fuel cell sy...

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作者： Wu, Xiao-long Xu, Yuan-wu Xue, Tao Shuai, Junchao Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China Wuhan Industrial Economic Development Research Center Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China

As the solid oxide fuel cell (SOFC) system work environment is a high-temperature environment for a long time, it is difficult to obtain the SOFC stack internal state change directly. When the fault occurs, it is difficult to determine where the fault occurs. Moreover, the existing literature ignores the impact of faults, which creates many problems for SOFC system control. Therefore, a state observer-based fault detection method, which is used to detect the input flow sensor fault and the fuel input fault, is proposed. Their advantage is that they do not need data processing. To realize the fault detection, the observer is used to track the changes of SOFC stack chamber temperature. To obtain the observer estimation parameter, an approach from the actual stack structure parameters is employed to approximate the observer parameters. The results show the proposed fault detect method can judge fuel input fault type quickly and shield the disturbances signals from the sensor effectively. The proposed method also can be used to other operating points or air input fault. © 2018 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd

关键词： Fault detection

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The Research of G-Mixing and G-Equicontinuity on the Hyperspace of Topological Group Action

The Research of G-Mixing and G-Equicontinuity on the Hypersp...

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International Conference on Measuring Technology and Mechatronics Automation, ICMTMA

作者： Ji Zhan-Jiang Shi Wei School of Information and Electronic Engineering Wuzhou University China Guangxi Colleges and Universities Key Laboratory of Image Processing and Intelligent Information System Wuzhou University China Guangxi Colleges and Universities Key Laboratory of Professional Software Technology Wuzhou University China Party Committee Office Wuzhou Vocational College China

ISBN: (数字)9781728170817

ISBN: (纸本)9781728170824

G-mixing and G-equicontinuity have an important significance in terms of theory and application. According to the definition of mixing and equicontinuity, we give the concept of G-mixing and G-equicontinuity in this paper. By inference, some conclusions of the hyperspace were extended to the hyperspace of topological group action. We have the following result: (1)Let (K,H, f̅,G) be the hyperspace of (X, d, G, f) and f : X → X be a pseudo equivariant map. All non-empty open set are invariable for G . If f is a G-mixing map, then f̅ is a G-mixing map; (2)Let (K,H, f̅,G) be the hyperspace of (X,d,G, f) and f : X → X be a equivariant map. Then f is a G-mild mixing map if and only if f̅ is a G-mild mixing map;(3)Let (K,H, f̅,G) be the hyperspace of (X,d,G, f) and f :X → X be a equivariant map. Then f is a G-equicontinuity map if and only if f̅ is a Gequicontinuity map. These results enriched the theory of the G-mixing and G-equicontinuity on the hyperspace of topological group action.

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The Research of G-Chain Transitive and G-Chain Mixing on the Hyperspace of Topological Group Action

The Research of G-Chain Transitive and G-Chain Mixing on the...

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International Conference on Measuring Technology and Mechatronics Automation, ICMTMA

ISBN: (数字)9781728170817

ISBN: (纸本)9781728170824

G-chain transitive and G-chain mixing have an important significance in terms of theory and application. According to the definition of chain transitive and chain mixing, we give the concept of G-chain transitiveand G-chain mixing in this paper. By inference, some conclusions of the hyperspace were extended to the hyperspace of topological group action. We have the following result: (1)Letbe the hyperspace of. Ifis a G-chain transitive map, thenis a G-chain transitive map; (2)Letbe the hyperspace of. Ifis a G-chain mixing map, thenis a G-chain mixing map; (3)Letbe the hyperspace ofandbe a equivariant map. All non-empty open set are invariable for. Thenis a G-exact map if and only ifis a G-exact map. These results enriched the theory of the G-chain transitive and G-chain mixing on the hyperspace of topological group action.

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