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New Energy and Power engineering (ICNEPE), International Conference on

作者： Hao Xia Xiongyao Deng Shizhong Ma Yuxiang Yan Ancheng Xue Yu Liu Zhihuai Shu Naichao Chang Zhongqing Li Jiangwen Meng Xuewei Dou Shenqiang Wang Fangying Wu Chen Fan State Key Laboratory of Alternate Electrical Power System with Renewable Energy Source (North China Electric Power University) Beijing China National Electric Power Dispatching and Control Center of State Grid Corporation of China Beijing China China Electric Power Research Institute Beijing China Beijing Sifang Engineering Co. Ltd Beijing China Power Automation Department China Electric Power Research Institute Nanjing China

In existing protection and monitoring system of substation(S-PMS), there are compatibility problems between hardware and software or between software-hardware combinations and systems, including differences in communication protocols between different manufacturers and differences in system adaptation. Compatibility issues have become a growing focus area for the power industry. This paper proposes a method to evaluates the compatibility of the protection and monitoring system of substation based on the G1 and expert investigation, for the existing or unbuilt substations. In detail, Firstly, according to the compatibility requirements of the substation protection and monitoring system, corresponding indicators are proposed and a comprehensive compatibility evaluation model is constructed. Secondly, based on the comprehensive evaluation model, the evaluation results of typical stations without domestic chips and optimized stations using domestic chips are compared to verify the feasibility of the proposed method.

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An Integration Evaluation Method for Substation Protection and Monitoring system Based on G1 Method and Expert Investigation

An Integration Evaluation Method for Substation Protection a...

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New Energy and Power engineering (ICNEPE), International Conference on

作者： Xiongyao Deng Yuxiang Yan Chang Lin Hao Xia Ancheng Xue Zhihuai Shu Yu Liu Naichao Chang Chen Fan Zhongqing Li Jiangwen Meng Xuewei Dou Shenqiang Wang Long Zhang Fangying Wu State Key Laboratory of Alternate Electric Power System with Renewable Energy Source (North China Electric Power University) Beijing China National Electric Power Dispatching and Control Center of State Grid Corporation of China Beijing China Power Automation Department China Electric Power Research Institute Nanjing China China Electric Power Research Institute Beijing China Beijing Sifang Engineering Co. Ltd Beijing China

Substation is the core hub of power system. With the expansion of the scale of the power system and the improvement of its intelligence, the problems of the redundancy of architecture and equipment in the protection and monitoring system of substation can no longer be ignored. This paper proposes an evaluation method for integration in the protection and monitoring system based on G1 method. Firstly, according to the requirements of integration in the protection and monitoring system, the corresponding indicators are proposed to form an index system for evaluating integration. And then, an evaluation method is proposed for integration of the protection and monitoring system, based on G1 method and expert investigation. Finally, the feasibility of the evaluation method is verified by comparing and analyzing the evaluation results of a typical substation and its structural optimization substation.

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SUNet: Scale-aware Unified Network for Panoptic Segmentation

arXiv

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arXiv 2022年

作者： Yan, Weihao Qian, Yeqiang Wang, Chunxiang Yang, Ming The 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 University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China

Panoptic segmentation combines the advantages of semantic and instance segmentation, which can provide both pixel-level and instance-level environmental perception information for intelligent vehicles. However, it is challenged with segmenting objects of various scales, especially on extremely large and small ones. In this work, we propose two lightweight modules to mitigate this problem. First, Pixel-relation Block is designed to model global context information for large-scale things, which is based on a query-independent formulation and brings small parameter increments. Then, Convectional Network is constructed to collect extra high-resolution information for small-scale stuff, supplying more appropriate semantic features for the downstream segmentation branches. Based on these two modules, we present an end-to-end Scale-aware Unified Network (SUNet), which is more adaptable to multi-scale objects. Extensive experiments on Cityscapes and COCO demonstrate the effectiveness of the proposed methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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Mercury transformation processes in nature: Critical knowledge gaps and perspectives for moving forward

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Journal of Environmental Sciences 2022年第9期34卷 152-165页

作者： Zhiyuan Gao Wang Zheng Yanbin Li Yurong Liu Mengjie Wu Shouying Li Ping Li Guangliang Liu Xuewu Fu Shuxiao Wang Feiyue Wang Yong Cai Xinbin Feng Baohua Gu Huan Zhong Yongguang Yin Centre for Earth Observation Science and Department of Environment and GeographyUniversity of ManitobaWinnipegMB R3T 2N2Canada Institute of Surface-Earth System Science Tianjin UniversityTianjin 300192China Key Laboratory of Marine Chemistry Theory and Technology Ministry of Education and College of Chemistry and Chemical EngineeringOcean University of ChinaQingdao 266100China State Key Laboratory of Agricultural Microbiology Huazhong Agricultural UniversityWuhan 430070China School of the Environment Nanjing UniversityState Key Laboratory of Pollution Control and Resource ReuseNanjing 210023China State Key Laboratory of Environmental Geochemistry Institute of GeochemistryChinese Academy of SciencesGuiyang 550081China Department of Chemistry and Biochemistry Florida International UniversityMiamiFL 33199USA School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua UniversityBeijing 100084China Environmental Sciences Division Oak Ridge National LaboratoryOak RidgeTennessee 37831USA Environmental and Life Sciences Program(EnLS) Trent UniversityPeterboroughOntario K9L 0G2Canada Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China

The transformation of mercury(Hg) in the environment plays a vital role in the cycling of Hg and its risk to the ecosystem and human health. Of particular importance are Hg oxidation/reduction and methylation/demethylation processes driven or mediated by the dynamics of light, microorganisms, and organic carbon, among others. Advances in understanding those Hg transformation processes determine our capacity of projecting and mitigating Hg risk. Here, we provide a critical analysis of major knowledge gaps in our understanding of Hg transformation in nature, with perspectives on approaches moving forward. Our analysis focuses on Hg transformation processes in the environment, as well as emerging methodology in exploring these processes. Future avenues for improving the understanding of Hg transformation processes to protect ecosystem and human health are also explored.

关键词： Mercury oxidation reduction methylation demethylation isotope fractionation

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Artificial intelligence for geoscience:Progress,challenges,and perspectives

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The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie Zhao Sheng Wang Chaojun Ouyang Min Chen Chenying Liu Jin Zhang Long Yu Fei Wang Yong Xie Jun Li Fang Wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian Yongjun Xu Chengqing Yu Wei Han Tao Sun Zezhi Shao Tangwen Qian Zhao Chen Jiangyuan Zeng Huai Zhang Husi Letu Bing Zhang Li Wang Lei Luo Chong Shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang Wei Zhao Nan Li Chaolei Zheng Yang Zhou Changping Huang Defeng Feng Qingsong Xu Yan Wu Danfeng Hong Zhenyu Wang Yinyi Lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng Shi Lizhe Wang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China School of Computer Science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China Data Science in Earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China School of Geographical Sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials Science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy University of CaliforniaCaliforniaRiversideCA 92521USA Institute of Remote Sensing and Geographical Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and Remote Sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing Earth science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

关键词： Earth utilizing landscape

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An Integrated Neural Unmanned system for Multi-Domain Perception and Decision-Making

An Integrated Neural Unmanned System for Multi-Domain Percep...

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IEEE International Conference on Robotics and Biomimetics

作者： Qiming Liu Neng Xu Jinpeng Zhang Hesheng Wang Department of Automation Shanghai Jiao Tong University Shanghai China SJTU Paris Elite Institute of Technology Shanghai Jiao Tong University Shanghai China Second Academy of China Aerospace Science and Industry Corporation (CASIC) Beijing China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665481106

Most recent intelligent systems study the perception or policy modules independently but ignore the inter-connection between them, which results in low information efficiency and high network redundancy, in the end, leads to the incomplete utilization of network potential and poor system-level end-to-end intelligence. This paper proposes an integrated end-to-end network that adapts to multi-domain inputs and multi-function outputs. “Integration” is defined in this paper in mainly three aspects: network structure level, optimization level, and functional level. The integrated network architecture is capable of fusing multiple raw sensory inputs and outputting multiple perceptions and decisions simultaneously. We first implement the integrated system in a virtual simulation environ-ment and investigate the domain transformation methods to real world. Comprehensive experiment results in both virtual and real environments show that our proposed system can behave normally under exploration, target-driven navigation and target shooting tasks.

关键词： Training Point cloud compression Target tracking Navigation Robot kinematics Redundancy Robot sensing systems

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Antagonism between ambient ozone increase and urbanization-oriented population migration on Chinese cardiopulmonary mortality

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The Innovation 2023年第6期4卷 48-58页

作者： Haitong Zhe Sun Junchao Zhao Xiang Liu Minghao Qiu Huizhong Shen Serge Guillas Chiara Giorio Zosia Staniaszek Pei Yu Michelle W.L.Wan Man Mei Chim Kim Robin van Daalen Yilin Li Zhenze Liu Mingtao Xia Shengxian Ke Haifan Zhao Haikun Wang Kebin He Huan Liu Yuming Guo Alexander T.Archibald lYusuf Hamied Department of Chemistry University of CambridgeCambridge CB21EWUK Department of Earth Sciences University of CambridgeCambridge CB23EQUK Department of Environmental Health and Engineering Johns Hopkins Bloomberg School of Public HealthBaltimoreMD 21205USA State Key Joint Laboratory of ESPC State Environmental Protection Key Laboratory of Sources and Control of Air Pollution ComplexSchool of EnvironmentTsinghua UniversityBejing 100084China School of Atmospheric Sciences Nanjing UniversityNanjing 210023China Department of Earth System Science Stanford UniversityStanfordCA 94305USA School of Environmental Science and Engineering Southern University of Science and TechnologyShenzhen 518p55China Department of Statistical Science University College LondonLondon WC1E 6BTUK The Alan Turing Institute London NW12DBUK School of Public Heath and Preventive Medicine Monash UniversityMelboumeVIC 3004Australia British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary CareUniversity of CambridgeCambridge CB18RNUK Heart and Lung Research Institute University of CambridgeCambridge CB20BDUK Baroelona Supercomputing Center Department of Earth Sciences08034 BarcelonaSpain School of Environmental Science and Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Mathematics University of CaliformiaLos AngelesLos AngelesCA 90095USA State Key Laboratory of New Ceramics and Fine Processing KeyLaboratory of Advanced Materials of Ministry of EducationSchool of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Department of Engineering University of CambridgeCambridge CB21PZUK National Centre for Atmospheric Science Cambridge CB21EWUK

Everincreasing ambient ozone(O3)pollution in China has been exacerbating cardiopulmonary premature ***,the urban-rural exposure inequity has seldom been ***,we assess populationcale 03 exposure and mortality burdens between 1990 and 2019 based on integrated pollution tracking and epidemiological *** find Chinese population have been suffering from climbing 03 exposure by 4.3±2.8 ppb per decade as a result of rapid urbanization and growing prosperity of socioeconomic *** residents are broadly exposed to 9.8±4.1 ppb higher ambient O3 than the adjacent urban citizens,and thus urbaniza-tion-oriented migration compromises the exposure-associated mortality on total *** excess premature deaths attributable to longterm 03 exposure,373,500(95%uncertainty interval[U]:240,600-510,900)in 2019,is underestimated in previous studies due to ignorance of cardiovascular *** 03 pollution policy should focus more on rural population who are facing an aggravating threat of mortality risks to ameliorate environmental health injustice.

关键词： ambient urban urbanization

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A Risk-Averse Just-In-Time Scheme for Learning-Based Operation of Microgrids with Coupled Electricity-Hydrogen-Ammonia under Uncertainties

arXiv

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arXiv 2024年

作者： Li, Longyan Ning, Chao Pan, Guangsheng Zhang, Leiqi Gu, Wei Zhao, Liang Du, Wenli Shahidehpour, Mohammad Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China School of Electrical Engineering Southeast University Nanjing210096 China Zhejiang Key Laboratory of Distributed Generations and Microgrid Technology State Grid Zhejiang Electric Power Research Institute Hangzhou310014 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology China Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

This paper proposes a Risk-Averse Just-In-Time (RAJIT) operation scheme for Ammonia-Hydrogen-based Micro-Grids (AHMGs) to boost electricity-hydrogen-ammonia coupling under uncertainties. First, an off-grid AHMG model is developed, featuring a novel multi-mode ammonia synthesis process and a hydrogen-ammonia dual gas turbine with tunable feed-in ratios. Subsequently, a state-behavior mapping strategy linking hydrogen storage levels with the operation modes of ammonia synthesis is established to prevent cost-ineffective shutdowns. The proposed model substantially improves operational flexibility but results in a challenging nonlinear fractional program. Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs. Unlike conventional one-size-fits-all schemes using one optimization method throughout, the data-driven RAJIT intelligently switches between cost-effective deterministic optimization and risk-averse online-learning distributionally robust optimization depending on actual risk profiles, thus capitalizing on the respective strengths of these two optimization methods. To facilitate the solution of the resulting nonlinear program, we develop an equivalent-reformulation-based solution methodology by leveraging a constraint-tightening technique. Numerical simulations demonstrate that the proposed scheme guarantees safety and yields an overall cost reduction up to 14.6% compared with several state-of-the-art methods. © 2024, CC BY.

关键词： Ammonia

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Comparative Molecular Transformations of Dissolved Organic Matter Induced by Chlorination and Ammonia/Chlorine Oxidation Process

SSRN

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SSRN 2023年

作者： Ye, Bei Song, Zhi-Min Wu, De-Xiu Liang, Jun-Kun Wang, Wen-Long Hu, Wei Yu, Yang Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Environmental Protection Key Laboratory of Microorganism Application and Risk Control Institute of Environment and Ecology Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Key Laboratory of Microorganism Application and Risk Control of Shenzhen Guangdong Provincial Engineering Research Center for Urban Water Recycling and Environmental Safety Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Environmental Engineering Graduate School of Engineering Kyoto University Kyoto6158540 Japan Pingshan District Urban Management and Law Enforcement Bureau Shenzhen518118 China Department of Earth System Science Tsinghua University Beijing100084 China

The ammonia/chlorine oxidation process can greatly degrade PPCPs in water. However, its effect on molecular transformations of natural organic matter (NOM) and effluent organic matter (EfOM) are still poorly understood. In this study, molecular transformations of NOM and EfOM occurring during ammonia/chlorine were explored and compared with those occurred during chlorination, using spectroscopy and mass spectrometry. Phenolic and highly unsaturated aliphatic compounds together with aliphatic compounds were found to be predominant in both NOM and EfOM samples, all of which were significantly degraded after two processes. The ammonia/chlorine process led to greater decreases in the molecular weights of such components but lower reductions in aromaticity. Compared with chlorination, ammonia/chlorine was found to be more likely to degrade compounds while remaining fluorophores or chromophores. The CH(N)O(S) precursors were found to be similar for both processes but their products were quite different. The CH(N)O(S) precursors that only found in ammonia/chlorine had higher molecular weights and greater degrees of oxidation but lower degrees of saturation. In contrast, the unique CH(N)O(S) products that only found in ammonia/chlorine exhibited lower molecular weights and lower degrees of oxidation degrees together with higher degrees of saturation. Lower total abundance of chlorinated byproducts was found by ammonia/chlorine compared with chlorination, although the former process provided a richer diversity. In all water samples, chlorinated byproducts were mainly generated by substitution reactions during ammonia/chlorine and chlorination. Overall, the findings of this study could provide new insights into the transformations of NOM and EfOM induced by ammonia/chlorine and chlorination. © 2023, The Authors. All rights reserved.

关键词： Ammonia

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Procedure Recognition by Knowledge-Driven Segmentation in Robotic-Assisted Vitreoretinal Surgery

Procedure Recognition by Knowledge-Driven Segmentation in Ro...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Zhen Li Yawen Deng Qiang Ye Weihong Yu Haoxiang Qi Yaliang Liu Zhangguo Yu Gui-Bin Bian School of Electronic and Information Engineering Tongji University Shanghai China Institute of Automation Chinese Academy of Sciences Beijing China School of Mechatronic Engineering Beijing Institute of Technology Beijing China Department of Ophthalmology Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China International Joint Research Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Internal limiting membrane (ILM) peeling is a vital vitreoretinal surgery procedure. However, due to the thickness of just 1-2 micrometers and the intricacies associated with its varying density and adhesion, the difficulty of manipulation exceeds the physiological limits of human perception and operation. Surgical robot is characterized by high precision and stability. However, navigating intricate intraocular environments and handling minuscule high-precision areas remain enormous challenges. These include issues of uneven lighting, field-of-view loss, and motion blur. This paper proposed a perception method named ‘Multimodal Surgical Process Recognition based on Domain Knowledge and Segmentation (MSPR-DKS),’ designed to address these challenges and provide input for the precise control of robots. Moreover, a comprehensive dataset focused on ILM peeling during macular hole surgeries was established. Experimental results underscore the efficacy of this approach, with segmentation accuracies exceeding 99.27% for instruments and macular holes and an average accuracy of 98.97% in recognizing surgical processes. This study paves the way for leveraging domain knowledge and image segmentation to improve robot-assisted manipulation of soft tissues in ophthalmology.

关键词： Image segmentation Visualization Accuracy Medical robotics Motion segmentation Surgery Lighting

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