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第一届北京视觉科学会议(Beijing Vision Science Conference(BVSC)2016)

作者： Peng Zhou Jing Li Jieqiong Wang Likun Ai Huiguang He State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Department of Radiology Beijing Tongren Hospital Capital Medical University NO 1 Dong Jiao Min X Eye Center Beijing Tongren Hospital Capital Medical University NO 1 Dong Jiao Min Xiang Eastern

PURPOSE:To investigate the changes of resting-state interhemispheric functional connectivity in the brain of the ametropic amblyopia patients.

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Motion vehicles tracking in intelligent transportation visual surveillance systems

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Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of Science and Technology 2012年第SUPPL.2期36卷 216-222页

作者： Wu, Lin-Feng Xiong, Gang Qian, Shou-Yi Xie, Li Zhejiang Provincial Key Lab. of Information Network Technology Department of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Cloud Computing Industrial Technology Innovation and Incubation Center Dongguan Research Institute of CASIA Chinese Academy of Sciences Dongguan 523808 China Wenzhou Research Institute of Electronics and Information Wenzhou 325003 China

In terms of the difficulty of vehicle tracking in complex environment of the visual surveillance system, an object tracking algorithm is proposed for the applications in practical visual surveillance systems for intelligent traffic. A block-based Gaussian mixture background modeling method for object detection is presented to reduce the computational complexity of moving vehicle object abstraction. An adaptive tracking algorithm fused with color features and texture features is described to better adapt the traffic scene variation. The experimental results show that the proposed algorithm can effectively deal with the complex urban traffic conditions and the tracking performance is better than the conventional particle filter method and single feature based non-adaptive object tracking method.

关键词： Tracking (position)

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Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第2期8卷 1046-1056页

作者： Chen, Long Li, Yuchen Huang, Chao Li, Bai Xing, Yang Tian, Daxin Li, Li Hu, Zhongxu Na, Xiaoxiang Li, Zixuan Teng, Siyu Lv, Chen Wang, Jinjun Cao, Dongpu Zheng, Nanning Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Waytous Ltd Beijing 100083 Peoples R China BNU HKBU United Int Coll Zhuhai 519087 Peoples R China Hong Kong Baptist Univ Kowloon Hong Kong 999077 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong 999077 Peoples R China Hunan Univ Coll Mech & Vehicle Engn Changsha 410012 Peoples R China Cranfield Univ Sch Aerosp Transport & Mfg Bedford MK43 0AL England Beihang Univ Sch Transportat Sci & Engn Beijing 100191 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Nanyang Technol Univ Dept Mech & Aerosp Engn Singapore 639798 Singapore Univ Cambridge Ctr Sustainable Rd Freight Cambridge CB2 1PZ England Xi An Jiao Tong Univ Coll Artificial Intelligence Xian 710049 Peoples R China Tsinghua Univ Sch Mech Engn Beijing 100084 Peoples R China

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks, lack of systematic summary and research directions in the future. Here we propose a Survey of Surveys (SoS) for total technologies of AD and IVs that reviews the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. To our knowledge, this article is the first SoS with milestones in AD and IVs, which constitutes our complete research work together with two other technical surveys. We anticipate that this article will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future.

关键词： Autonomous vehicles Planning Vehicle dynamics Heuristic algorithms Object detection Location awareness Task analysis Survey of surveys milestones autonomous driving intelligent vehicles

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Data-Driven Modeling and Random Search Optimization Method for the Polysilicon Cvd Reactor

SSRN

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SSRN 2022年

作者： Xi, Bangwen Xiong, Gang Shen, Zhen Tamir, Tariku Sinshaw He, Chang Song, Yonggang Liu, Xiong State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Intelligent Manufacturing Center Qingdao Academy of Intelligent Industries Qingdao266109 China Xinte Energy Co. Ltd Urumqi830000 China

Polysilicon is mainly obtained by chemical vapor deposition(CVD) reaction, in which hydrogen gas and trichlorosilane(TCS) are fed into the CVD reactor to produce polysilicon. However, the feeding parameters are mainly adjusted in a step-by-step manner according to the actual deposition results, which is inefficient to optimize and prone to resource wastage. In this paper, based on the existing mechanistic model of the CVD reactor, we combine the history data with the specific parameters to construct a simulator. A random search algorithm is used to determine the optimal feeding parameters. With the simulator, the polysilicon productivity can be increased by 704 kg, and the power consumption reduced by 3.8 kWh/kg. © 2022, The Authors. All rights reserved.

关键词： Simulators

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Micro/nanoliter droplet extraction by controlling acoustic vortex with miniwatt

arXiv

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arXiv 2021年

作者： Zhang, Han Yang, Jun Zhou, Yun Zheng, Jianfeng Cheng, Yong Bai, Bichao Zhang, Guoxin Lv, Yisheng CAS Key Laboratory of Noise and Vibration Institute of Acoustics Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China The National Center for Nanoscience and Technology Beijing100190 China School of Mechanical Engineering Changzhou University Changzhou213164 China Institute of Mechanics School of Civil Engineering & Mechanics Yanshan University Qinhuangdao066004 China Al-ion Battery Research Center Department of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266580 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Micro/nanoliter droplet is capable of achieving versatile applications with tiny volume and substantial surface energy, which is a big plus over bulk liquid. Yet, the contradiction of elaborate manipulation and enough power is still a challenge. Here, we unleash the potential of our miniwatt aspirators pumping up liquid and creating droplets with the help of acoustic vortex beams, inspired by the power mechanism that spirals are significant for most mollusks that live in water. These droplet aspirators produce very large interface deformations by small radiation pressures with orbit angular momentum from spiral-electrode transducers. The precisely contactless manipulation of physical, chemical and biological objects at micrometric down to nanometric scales, promises tremendous development in fields as diverse as microrobotics, nanoreactors, or nanoassemblies. Copyright © 2021, The Authors. All rights reserved.

关键词： Vortex flow

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A Simplified Variant for Graph Convolutional Network Based Knowledge Graph Completion Model

A Simplified Variant for Graph Convolutional Network Based K...

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Yashen Wang Qiang Li Yi Zhang Xuecheng Zhang Zhuoya Ju Jian Sun National Engineering Laboratory for Risk Perception and Prevention (RPP) Key Laboratory of Cognition and Intelligence Technology (CIT) China Academy of Electronics and Information Technology Artificial Intelligence Institute of CETC Beijing China The State Key Laboratory for Management and Control of Complex Systems Scientific and Technological Innovation Center of ARI Institute of Automation Chinese Academy of Sciences Beijing China CETC Academy of Electronics and Information Technology Group Co. Ltd. Beijing China Khoury College of Computer Science Northeastern University U.S.A Scientific and Technological Innovation Center of ARI Beijing China Qi An Xin Technology Group Inc. Beijing China

Knowledge graphs (KGs) serve as useful resources for various applications including machine learning, data mining, and artificial intelligence. Knowledge Graph Completion (KGC) aims at reasoning over known (observed) facts and infer the missing (unobserved) relationships, to improve KG's coverage. Many recent works have laid stress on leveraging Graph Convolutional Networks (GCNs) for KGC task, which obtain good representation learning ability for graph-structured data, and have achieved satisfactory results. However, GCN-based researches continue to improve these lines of models by introducing an increasingly complex feature space. Especially, the hyper-parameter space of conventional GCN-based KGC model is too huge, resulting in low computational efficiency and excessive storage pressure. To overcome this problem, this paper investigates a simplified and generic variant for GCN-based KGC model, and shows that simple changes in the architecture of the underlying architecture (with a Subtraction Operator and an Addition Operator), can compte with state-of-the-art GCN-based models. Therefore, this paper proposes a easy-to-accomplish plug-in unit, which could be loaded into any current GCN-based KGC architectures, and help them maximize the maintenance of native model's original performance while significantly reducing parameter scale.

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A novel in vivo Cerenkov luminescence image-guided surgery on primary and metastatic colorectal cancer

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JOURNAL OF BIOPHOTONICS 2020年第3期13卷 e201960152-e201960152页

作者： Zhang, Zeyu Qu, Yawei Cao, Yu Shi, Xiaojing Guo, Hongbo Zhang, Xiaojun Zheng, Sheng Liu, Haifeng Hu, Zhenhua Tian, Jie Xidian Univ Engn Res Ctr Mol & Neuro Imaging Sch Life Sci & Technol Minist Educ Xian Shaanxi Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Key Lab Mol ImagingCAS Key Lab Mol Imagi Beijing Peoples R China Chinese Peoples Liberat Army Gen Hosp Med Ctr 3 Dept Gastroenterol 69 Yongding Rd Beijing Peoples R China Harbin Inst Technol Dept Control Sci & Engn Harbin Heilongjiang Peoples R China Chinese Peoples Liberat Army Gen Hosp Med Ctr 3 Dept Anorectal Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Northwest Univ Sch Informat Sci & Technol Xian Shaanxi Peoples R China Chinese Peoples Liberat Army Gen Hosp Dept Nucl Med Beijing Peoples R China Beihang Univ Beijing Adv Innovat Ctr Big Data Based Precis Med Sch Med Beijing Peoples R China

Intraoperative Cerenkov luminescence imaging (CLI) can effectively improve the performance of tumor surgery. Nevertheless, the existing approaches are still unsatisfying to the clinical demands of open surgery. This study develops a novel intraoperative in vivo CLI approach to investigate the potential and value of Cerenkov luminescence (CL) image-guided surgery. A system characterized with high sensitivity (19.61 kBq mL(-1 18)F-FDG) and desirable spatial resolution (88.34 mu m) is developed. CL image-guided surgery is performed on colorectal cancer (CRC) models of mice and swine. Tumor surgery is guided by the static CL images, and the resection quality is evaluated quantitatively and contrasted with other imaging modalities exemplified by bioluminescence imaging (BLI). The in vivo results demonstrated the effectiveness of the proposed intraoperative CLI approach for removing primary and metastatic CRC. Safety of performing in vivo CL image-guided surgery is verified as well through radiation measurements of related staffs. Overall, the developed intraoperative in vivo CLI approach can efficiently improve the cancer treatment.

关键词： Cerenkov luminescence imaging colorectal cancer image-guided surgery in vivo

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Hierarchical Connectome Modes and Critical state Jointly Maximize Human Brain Functional Diversity

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Physical Review Letters 2019年第3期123卷 038301-038301页

作者： Rong Wang Pan Lin Mianxin Liu Ying Wu Tao Zhou Changsong Zhou State Key Laboratory for Strength and Vibration of Mechanical Structures Shaanxi Engineering Laboratory for Vibration Control of Aerospace Structures School of Aerospace Engineering Xi’an Jiaotong University Xi’an 710049 China Department of Physics Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong) Institute of Computational and Theoretical Studies Hong Kong Baptist University Kowloon Tong Hong Kong College of Science Xi’an University of Science and Technology Xi’an 710054 China Key Laboratory of Cognitive Science College of Biomedical Engineering South-Central University for Nationalities Wuhan 430074 China Complex Lab University of Electronic Science and Technology of China Chengdu 611731 People’s Republic of China Research Centre HKBU Institute of Research and Continuing Education Shenzhen 518057 China Beijing Computational Science Research Center Beijing 100084 China Department of Physics Zhejiang University Hangzhou 310058 China

The brain requires diverse segregated and integrated processing to perform normal functions in terms of anatomical structure and self-organized dynamics with critical features, but the fundamental relationships between the complex structural connectome, critical state, and functional diversity remain unknown. Herein, we extend the eigenmode analysis to investigate the joint contribution of hierarchical modular structural organization and critical state to brain functional diversity. We show that the structural modes inherent to the hierarchical modular structural connectome allow a nested functional segregation and integration across multiple spatiotemporal scales. The real brain hierarchical modular organization provides large structural capacity for diverse functional interactions, which are generated by sequentially activating and recruiting the hierarchical connectome modes, and the critical state can best explore the capacity to maximize the functional diversity. Our results reveal structural and dynamical mechanisms that jointly support a balanced segregated and integrated brain processing with diverse functional interactions, and they also shed light on dysfunctional segregation and integration in neurodegenerative diseases and neuropsychiatric disorders.

关键词： Scaling laws of complex systems Self-organized criticality Brain network

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In vivo multifunctional fluorescence imaging using liposome-coated lanthanide nanoparticles in near-infrared-II/IIa/IIb windows

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NANO TODAY 2021年 38卷 101120-101120页

作者： Yang, Junying He, Shuqing Hu, Zhenhua Zhang, Zeyu Cao, Caiguang Cheng, Zhen Fang, Chihua Tian, Jie Southern Med Univ Zhujiang Hosp Dept Hepatobiliary Surg Guangzhou 510280 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst CAS Key Lab Mol Imaging Beijing Key Lab Mol ImagingInst Automat Beijing 100190 Peoples R China Shenzhen Technol Univ Coll Hlth Sci & Environm Engn Shenzhen 518118 Peoples R China Beihang Univ Beijing Adv Innovat Ctr Big Data Based Precis Med Sch Med Beijing 100191 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Prov Clin & Engn Ctr Digital Med Guangzhou 510280 Peoples R China Stanford Univ Canary Ctr Stanford Canc Early Detect Mol Imaging Program Stanford MIPS Bio X Program Stanford CA 94305 USA Stanford Univ Canary Ctr Stanford Canc Early Detect Dept Radiol Stanford CA 94305 USA

In vivo fluorescence imaging in the near-infrared II window (NIR-II, 1000-1700 nm) has great improvements in imaging quality compared with the visible (400-700 nm) and the NIR-I (700-900 nm) window due to the low autofluorescence and the reduced scattering. To date, a variety of NIR-II fluorophores have been synthesized and applied in vivo imaging and disease diagnosis. Multifunction is believed as one of the developing trends. In this study, we report a liposome-coated lanthanide nanoparticle, named as NPs@Lips, which can emit three-wavelengths fluorescence (1000-1100 nm (NIR-II), 1300-1350 nm (NIR-IIa), 1500-1700 nm (NIR-IIb) simultaneously under an 808 nm laser excitation. The imaging results demonstrated that the images in longer wavelengths provided a higher resolution and enhanced signal-to-noise (S/N) ratio than the ones in shorter wavelengths. Then, the NPs@Lips were studied for in vivo multifunctional biological imaging, including brown adipose tissue imaging, vascular imaging and lymph node localization biopsy. Interestingly, NPs@Lips can accumulate in brown adipose tissue without any targeting molecules, which provided an alternative sensitive and non-radiation method for brown adipose tissue imaging in the field of metabolic disorders. Overall, the NPs@Lips were potential NIR-II probe for multifunctional nanomedicine applications. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： NIR-II IIa IIb windows Fluorescence imaging Brown adipose tissue Multifunctional nanoprobe Rare-earth-doped nanoparticle Excretory capacity

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Parallel medical imaging for intelligent medical image analysis: Concepts, methods, and applications

arXiv

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arXiv 2019年

作者： Gou, Chao Shen, Tianyu Zheng, Wenbo Xue, Huadan Yu, Hui Ji, Qiang Jin, Zhengyu Wang, Fei-Yue School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Radiology Peking Union Medical College Hospital Chinese Academy of Medical Sciences Peking Union Medical College Beijing100730 China School of Creative Technologies University of Portsmouth PortsmouthPO1 2DJ United Kingdom Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Qingdao Academy of Intelligent Industries Qingdao266000 China

Data-driven artificial intelligence technologies have made much progress in medical image analysis in the last decades. However, it still remains challenging due to its distinctive complexity of acquiring and annotating image data, extracting medical domain knowledge, and explaining the diagnostic decision for medical image analysis. In this paper, we propose a data-knowledge-driven framework termed as Parallel Medical Imaging (PMI) for intelligent medical image analysis based on the methodology of interactive ACP-based parallel intelligence. In the PMI framework, computational experiments with predictive learning in a data-driven way are conducted to extract medical knowledge for diagnostic decision support. Artificial imaging systems are introduced to select and prescriptively generate medical image data in a knowledge-driven way to utilize medical domain knowledge. Through the closed-loop optimization based on parallel execution, our proposed PMI framework can boost the generalization ability and alleviate the limitation of medical interpretation for diagnostic decisions. Furthermore, we illustrate the preliminary implementation of PMI method through the case studies of mammogram analysis and skin lesion image analysis. Experimental results on several public medical image datasets demonstrate the effectiveness of proposed PMI. © 2019, CC BY.

关键词： Medical imaging

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