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Multi-modal fusion for robust hand gesture recognition based on heterogeneous networks

Science China(Technological Sciences) 2023年第11期66卷 3219-3230页

作者： ZOU YongXiang CHENG Long HAN LiJun LI ZhengWei School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Hand gesture recognition has become a vital subject in the fields of human-computer interaction and rehabilitation *** paper presents a multi-modal fusion for hand gesture recognition(MFHG)model,which uses two heterogeneous networks to extract and fuse the features of the vision-based motion signals and the surface electromyography(s EMG)signals,*** extract the features of the vision-based motion signals,a graph neural network,named the cumulation graph attention(CGAT)model,is first proposed to characterize the prior knowledge of motion coupling between finger *** CGAT model uses the cumulation mechanism to combine the early and late extracted features to improve motion-based hand gesture *** the s EMG signals,a time-frequency convolutional neural network model,named TF-CNN,is proposed to extract both the signals'time-domain and frequency-domain *** improve the performance of hand gesture recognition,the deep features from multiple modes are merged with an average layer,and then the regularization items containing center loss and the mutual information loss are employed to enhance the robustness of this multi-modal ***,a data set containing the multi-modal signals from seven subjects on different days is built to verify the performance of the multi-modal *** experimental results indicate that the MFHG can reach 99.96%and 92.46%accuracy on hand gesture recognition in the cases of within-session and cross-day,respectively.

关键词： leap motion s EMG multi-modal graph neural network hand gesture recognition

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Effects of acid deposition control in China:a review based on responses of subtropical forests

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Frontiers of Environmental Science & Engineering 2024年第6期18卷 115-126页

作者： Danni Xie Xiaodong Ge Lei Duan Jan Mulder School of Land Engineering Chang’an UniversityXi’an 710064China State Key Laboratory of Environmental Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China Faculty of Environmental Sciences and Natural Resource Management Norwegian University of Life SciencesBox 5003NO-1432ÅsNorway

For many decades,acid deposition used to pose a significant regional air pollution challenge in *** substantial emission control of anthropogenically derived sulfur and nitrogen containing gasses,both sulfur and nitrogen deposition,as well as the acid rain-affected area,have significantly decreased compared to their peak ***,particularly in the humid subtropics,are sensitive to acid deposition,as evidenced by soil acidification,sulfate and nitrate leaching in stream water,and elevated soil nitrous oxide *** in the total deposition of sulfur and nitrogen,caused a significant decline in sulfate and nitrate leaching from subtropical forest and subsequently in sulfate and nitrate concentrations in stream water,although there was about a 5-year *** delay may be attributed to the desorption of accumulated sulfate and continued elevated mineralization of accumulated nitrogen *** of nitrous oxide,a potent greenhouse gas,also declined in nitrogen-saturated subtropical forest soils,as soil water nitrate concentration ***,subtropical forests in China suffering from elevated acid deposition have begun to ***,the current levels of sulfur and nitrogen deposition continue to exceed the critical loads,i.e.,the assigned threshold levels in accordance with emission control policies,in more than 10%of the country’s land area,respectively,indicating remaining risks of acidification and ***,further emission reductions are urgently needed,also because they will help achieving goals related to air quality and nitrous oxide emissions.

关键词： Acidification Critical load Nitrous oxide Surface water chemistry Recovery

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Decomposing Visual and Semantic Correlations for Both Fully Supervised and Few-Shot Image Classification

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1658-1668页

作者： Zhang, Chunjie Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Most image classification methods are designed to either boost the classification accuracies with abundant supervision, or cope with the shortage of supervision information. This is often achieved by using the visual and semantic information of other sources. However, these methods use the visual and semantic information within the same class independently, leaving their intrinsic correlations unconsidered. Objects and disturbing components as well as noise exist on the same image. Besides, semantic representations also contain noisy information. To solve the problems mentioned above, we propose a novel method for both fully supervised image classification and few-shot image classification by decomposing visual and semantic correlations. We jointly explore the intrinsic correlations of visual and semantic information of images within the same class. For each class, we decompose its visual and semantic correlations using low-rank and sparse constraint respectively. The decomposed low-rank parts character the intrinsic correlations of images can be used in a linear transformation way. Using the decomposed parts of each class, Classification can be achieved by reconstruction error minimization. We conduct experiments on several datasets for both fully supervised image classification and few-shot image classification. Experimental results well show the effectiveness of the proposed method. © 2020 IEEE.

关键词： Semantics

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Social Radars: Finding Targets in Cyberspace for Cybersecurity

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 279-282页

作者： Lili Fan Changxian Zeng Yutong Wang Jiaqi Ma Fei-Yue Wang School of Information and Electronics Beijing Institute of TechnologyBeijing 100081China School of Science Dalian Minzu UniversityDalian 116600China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Department of Civil and Environmental Engineering University of CaliforniaLos AngelesCA 90024 USA IEEE State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

INSPIRED by the insight from American political scientist Lasswell, who summarized the environmental role in societal surveillance [1], Schramm coined the term “social radar” [2] as it resembles the activities of radar in collecting and processing information, playing a crucial role in helping humans perceive changes in the internal and external environment and promptly adjusting adaptive behaviors.

关键词： prompt summarized insight

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China’s carbon neutrality:an extensive and profound systemic reform

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Frontiers of Environmental Science & Engineering 2023年第2期17卷 1-7页

作者： Xi Lu Dan Tong Kebin He State Key Joint Laboratory of Environment Simulation and Pollution Control and School of Environment Tsinghua UniversityBeijing 100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing 100084China Beijing Laboratory of Environmental Frontier Technologies Tsinghua UniversityBeijing 100084China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China

China is the largest developing economy and carbon dioxide emitter in the world,the carbon neutrality goal of which will have a profound influence on the mitigation pathway of global climate *** transition towards a carbon-neutral society is integrated into the construction of ecological civilization in China,and brings profound implications for China’s socioeconomic ***,we not only summarize the major challenges in achieving carbon neutrality in China,but also identify the four potential new opportunities:namely,the acceleration of technology innovations,narrowing regional disparity by reshaping the value of resources,transforming the industrial structure,and co-benefits of pollution and carbon ***,we provide five policy suggestions and highlight the importance of balancing economic growth and carbon mitigation,and the joint efforts among the government,the enterprises,and the residents.

关键词： Carbon neutrality Energy structure Technology-dependent society Coordinated mitigation for air pollutants and CO_(2)

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Development and control of Underwater Gliding Robots:A Review

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1543-1560页

作者： Jian Wang Zhengxing Wu Huijie Dong Min Tan Junzhi Yu the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking UniversityBeijing 100871China

As one of the most effective vehicles for ocean development and exploration,underwater gliding robots(UGRs)have the unique characteristics of low energy consumption and strong ***,by borrowing the motion principles of current underwater robots,a variety of novel UGRs have emerged with improving their maneuverability,concealment,and environmental friendliness,which significantly broadens the ocean *** this paper,we provide a comprehensive review of underwater gliding robots,including prototype design and their key *** the perspective of motion characteristics,we categorize the underwater gliding robots in terms of traditional underwater gliders(UGs),hybrid-driven UGs,bio-inspired UGs,thermal UGs,and ***,their buoyancy driven system,dynamic and energy model,and motion control are concluded with detailed ***,we have discussed the current critical issues and future *** review offers valuable insight into the development of next-generation underwater robots well-suited for various oceanic applications,and aims to gain more attention of researchers and engineers to this growing field.

关键词： Buoyancy driven motion control oceanic applications system development underwater gliding robots

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ChatGPT Chats on Computational Experiments:From Interactive Intelligence to Imaginative Intelligence for Design of Artificial Societies and Optimization of Foundational Models

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1357-1360页

作者： Xiao Xue Xiangning Yu Fei-Yue Wang College of Intelligence and Computing Tianjin UniversityTianjin 300350China State Key Laboratory for Management and Control of Complex Systems the Institute of Automdtion of Chinese Academg of SciencesBeijing 100190China

POWERED by the rapid development of Internet,the penetration of the Internet of Things,the emergence of big data,and the rise of social media,more and more complex systems are exhibiting the characteristics of social,physical,and information *** systems are known as cyber-physicalsocial systems(CPSS)[1],[2].These CPSS face unprecedented challenges in design,analysis,management,control and integration due to their involvement with human and social factors[3],[4].To cope with this challenge,there are two main approaches to CPSS research.

关键词： Intelligence Foundation involvement

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Semantic Coherence Guided Multiview Similarity for Image Classification with Varied Supervision

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 3072-3082页

作者： Zhang, Chunjie Cao, Ping Bai, Huihui Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Pairwise similarity has been widely used for image classification by propagating the class information from labeled images to unlabeled images and predicting the classes of unlabeled images accordingly. Although widely used, pairwise similarity based classification methods have two drawbacks. On one hand, visual-semantic similarity consistency does not always hold due to semantic gap. On the other hand, the reliability of pairwise similarity is also influenced by the number and underlying distribution of labeled images. A well-designed classification model cannot be easily generalized to few-shot classification tasks. To solve these two problems, in this article, we propose a semantic coherence guided multiview similarity (SCG-MV) for image classification method with varied supervision levels. We measure the semantic coherence between image pairs for classifier learning. This is achieved by first conducting line search along the line segment between each image pair, and then measure the semantics of each interval. The similarity of one image pair can then be obtained by aggregating the semantic coherence of all the intervals. In this way, we can model image similarities more finely and discriminatively. To make use of multiview information, we also use the semantic coherence guided image similarities to learn multiview classifiers. The proposed semantic coherence guided method can be combined with other similarity based methods for image classification with various levels of supervision. We conduct both few-shot and fully supervised classification experiments on four datasets with the results well prove the discriminative power and generalization ability of the proposed method. © 2020 IEEE.

关键词： Semantics

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Convection-UNet: A Deep Convolutional Neural Network for Convection Detection based on the Geo High-speed Imager of Fengyun-4B

Convection-UNet: A Deep Convolutional Neural Network for Con...

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2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms, PRMVIA 2023

作者： Wang, Yufei Xiao, Baihua Chinese Academy of Sciences University of Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing China Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing China

ISBN: (纸本)9798350346596

Deep convection can cause a variety of severe weather conditions such as thunderstorms, strong winds, and heavy rainfall. Satellite observations provide all-weather and multi-directional observations, facilitating the timely detection of such weather systems, which is crucial to saving lives and property. However, previous methods based on channel feature extraction and threshold filtering did not make full use of information in satellite images, which led to limitations on such complex problems as strong convection detection. In this study, we propose a novel framework of a deep learning-based model Convection-UNet to detect convection. We use channel 4 to 7 of FY-4B GHI that we select according to the microphysical properties of convection as input and radar reflectivity as label. We combine the detailed training time and test time data augmentation strategies and build a deep neural network to automatically extract spatial context features and achieve end-to-end learning. Results show that the performance of our method far exceeds the previous channel extraction combined with threshold filtering methods such as BT and BTD at least 0.24 on Fi-measure. We also show that our channel selection and data augmentation strategies are of great significance to detect convection. © 2023 IEEE.

关键词： Feature extraction

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Attention Markets of Blockchain-Based Decentralized Autonomous Organizations

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1370-1380页

作者： Juanjuan Li Rui Qin Sangtian Guan Wenwen Ding Fei Lin Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

The attention is a scarce resource in decentralized autonomous organizations(DAOs),as their self-governance relies heavily on the attention-intensive decision-making process of“proposal and voting”.To prevent the negative effects of pro-posers’attention-capturing strategies that contribute to the“tragedy of the commons”and ensure an efficient distribution of attention among multiple proposals,it is necessary to establish a market-driven allocation scheme for DAOs’***,the Harberger tax-based attention markets are designed to facilitate its allocation via continuous and automated trading,where the individualized Harberger tax rate(HTR)determined by the pro-posers’reputation is ***,the Stackelberg game model is formulated in these markets,casting attention to owners in the role of leaders and other competitive proposers as *** equilibrium trading strategies are also discussed to unravel the intricate dynamics of attention ***,utilizing the single-round Stackelberg game as an illustrative example,the existence of Nash equilibrium trading strategies is ***,the impact of individualized HTR on trading strategies is investigated,and results suggest that it has a negative correlation with leaders’self-accessed prices and ownership duration,but its effect on their revenues varies under different *** study is expected to provide valuable insights into leveraging attention resources to improve DAOs’governance and decision-making process.

关键词： Attention decentralized autonomous organizations Harberger tax Stackelberg game.

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