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Parallel Light Fields: A Perspective and A Framework

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 542-544页

作者： fei-yue Wang Yu Shen IEEE State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of ScienceBeijing 100049

Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simplified expression of light fields with depth information discarded. In theory, computer vision tasks may achieve better performance as long as complete light fields are acquired.

关键词： computer Framework simplified

Heterogeneous Image Knowledge Driven Visual Perception

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 255-257页

作者： Lan Yan Wenbo Zheng fei-yue Wang IEEE the College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China the School of Computer Science and Artificial Intelligence Wuhan University of TechnologyWuhan 430070China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous images.Facing the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

关键词： Visual visual knowledge

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’attention.First,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 adopted.Then,the Stackelberg game model is formulated in these markets,casting attention to owners in the role of leaders and other competitive proposers as followers.Its equilibrium trading strategies are also discussed to unravel the intricate dynamics of attention pricing.Moreover,utilizing the single-round Stackelberg game as an illustrative example,the existence of Nash equilibrium trading strategies is demonstrated.Finally,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 conditions.This 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.

Parallel intelligent education with ChatGPT

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 12-18页

作者： Jiacun WANG Ying TANG Ryan HARE fei-yue WANG Department of Computer Science and Software Engineering Monmouth UniversityNew Jersey 07764USA Department of Electrical and Computer Engineering Rowan UniversityNew Jersey 08028USA Institute of Automation Chinese Academy of SciencesBeijing 100190China

This paper presents a framework for parallel intelligent education that involves physical and virtual learning for a personalized learning experience.We especially focus on Chat Generative Pre-trained Transformer(ChatGPT)owing to its considerable potential to supplement regular class learning.We address the strengths and weaknesses of learning with ChatGPT.Finally,we discuss the challenges and solutions of the proposed parallel intelligent education with ChatGPT.

关键词： education GPT intelligent

Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 231-239页

作者： Yahui Liu Bin Tian Yisheng Lv Lingxi Li fei-yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190 IEEE the Transportation and Autonomous Systems Institute(TASI)and the Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis(IUPUI)Indianapolis 46202 USA

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://***/yahuiliu99/PointC onT.

关键词： Content-based Transformer deep learning feature aggregator local attention point cloud classification

The engineering of circular causality for specialization and design of complex systems:cad2CAS and casCAD2

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Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 323-332页

作者： Xiaolong LIANG Rui QIN Juanjuan LI fei-yue WANG Faculty of Innovation Engineering Macao University of Science and TechnologyMacao999078China State Key Laboratory of Multimodal Artificial Intelligence Systems Chinese Academy of SciencesBeijing100190China The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing100190China

The emergence of decentralized autonomous organizations and operations(DAOs),equipped with innovative mechanisms,enables new possibilities for transforming traditional social collaborative relationships.Mechanisms are the underlying driver for DAOs.However,as a complex system encompassing both social complexity and engineering complexity.

关键词： complexity. circular equipped

Construction of a nomogram model to predict technical difficulty in performing laparoscopic sphincter-preserving radical resection for rectal cancer

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World Journal of Gastroenterology 2024年第18期30卷 2418-2439页

作者： Xiao-Cong Zhou Shi-Wei Guan fei-yue Ke Gaurav Dhamija Qiang Wang Bang-fei Chen Medical University(Wenzhou Central Hospital) Wenzhou 325000Zhejiang ProvinceChina Department of Hepatobiliary Surgery The Dingli Clinical Institute of Wenzhou Medical University(Wenzhou Central Hospital)Wenzhou 325000Zhejiang ProvinceChina Postgraduate Training Base Alliance of Wenzhou Medical University Wenzhou Central HospitalWenzhou 325000Zhejiang ProvinceChina School of International Studies Wenzhou Medical UniversityWenzhou Central HospitalWenzhou 325000Zhejiang ProvinceChina Department of Radiology The Dingli Clinical Institute of Wenzhou Medical University(Wenzhou Central Hospital)Wenzhou 325000Zhejiang ProvinceChina Department of Colorectal Surgery The Affiliated Zhejiang HospitalZhejiang University School of Medicine(Zhejiang Hospital)Hangzhou 310000Zhejiang ProvinceChina

BACKGROUND Colorectal surgeons are well aware that performing surgery for rectal cancer becomes more challenging in obese patients with narrow and deep pelvic cavities.Therefore,it is essential for colorectal surgeons to have a comprehensive understanding of pelvic structure prior to surgery and anticipate potential surgical difficulties.AIM To evaluate predictive parameters for technical challenges encountered during laparoscopic radical sphincter-preserving surgery for rectal cancer.METHODS We retrospectively gathered data from 162 consecutive patients who underwent laparoscopic radical sphincterpreserving surgery for rectal cancer.Three-dimensional reconstruction of pelvic bone and soft tissue parameters was conducted using computed tomography(CT)scans.Operative difficulty was categorized as either high or low,and multivariate logistic regression analysis was employed to identify predictors of operative difficulty,ultimately creating a nomogram.RESULTS Out of 162 patients,21(13.0%)were classified in the high surgical difficulty group,while 141(87.0%)were in the low surgical difficulty group.Multivariate logistic regression analysis showed that the surgical approach using laparoscopic intersphincteric dissection,intraoperative preventive ostomy,and the sacrococcygeal distance were independent risk factors for highly difficult laparoscopic radical sphincter-sparing surgery for rectal cancer(P<0.05).Conversely,the anterior-posterior diameter of pelvic inlet/sacrococcygeal distance was identified as a protective factor(P<0.05).A nomogram was subsequently constructed,demonstrating good predictive accuracy(C-index=0.834).CONCLUSION The surgical approach,intraoperative preventive ostomy,the sacrococcygeal distance,and the anterior-posterior diameter of pelvic inlet/sacrococcygeal distance could help to predict the difficulty of laparoscopic radical sphincter-preserving surgery.

关键词： Nomogram Rectal cancer Laparoscopic operation Sphincter-preserving surgery Technical difficulty

Parallel Vision ■ Image Synthesis/Augmentation

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 782-784页

作者： Wenwen Zhang Wenbo Zheng Qiang Li fei-yue Wang the School of Computer Science Shaanxi Normal UniversityXi’an 710119China the School of Computer Science and Technology Wuhan 430070China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,Scene understanding is an essential task in computer vision.The ultimate objective of scene understanding is to instruct computers to understand and reason about the scenes as humans do.Parallel vision is ... 详细信息

关键词： instru explanation computer

Sustainable Mining in the Era of Artificial Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 1-4页

作者： Long Chen Yuting Xie Yutong Wang Shirong Ge fei-yue Wang IEEE the State Key Laboratory for Management and Control of Complex Systems at the Institute of Automation Chinese Academy of SciencesBeijing 100190China the National Laboratory of Pattern Recognition at the Institute of Automation and Waytous Ltd.China the School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhou 510275GuangdongChina the School of Mechanical Electronic and Information Engineering China University of Mining and Technology BeijingBejing 100083China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190China

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread use.Over-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

关键词： Sustainable mining consequences