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SSRN 2023年

作者： Hu, Zhen Zhou, Wenyu Liang, Xun Guan, Qingfeng Wen, Youyue Liao, Weilin Yan, Yuchao Han, Cuiyan School of Geography and Information Engineering China University of Geosciences Hubei Wuhan430078 China National Engineering Research Center of GIS China University of Geosciences Hubei province Wuhan430078 China South China Institute of Environmental Science Ministry of Ecology and Environment Guangzhou510535 China National Key Laboratory of Urban Ecological Environment Simulation and Protection Guangzhou510535 China Guangdong Key Laboratory for Urbanization and Geo-simulation School of Geography and Planning Sun Yat-sen University Guangzhou510275 China Institute of Carbon Neutrality Sino-French Institute for Earth System Science College of Urban and Environmental Sciences Peking University Beijing100871 China Wuhan HopeTop Technology Co. Ltd. Wuhan430223 China

Discovering how vegetation responds to climatic factors is critical for understanding terrestrial ecosystem dynamics and predicting future vegetation states. In this study, we employ Explainable Artificial Intelligence (XAI) to unravel the spatiotemporal patterns of vegetation across a global scale over 12 months. Our approach utilizes the Long Short-Term Memory (LSTM) model to capture pixel-level vegetation dynamics driven by climatic factors. By leveraging the Permutation Feature Importance (PFI) method, we unveil the spatial distribution and temporal variability of each climate factor's contribution as learned by LSTM. Our results demonstrate that considering the long-term memory effect significantly enhances the explanatory power of climate factors for vegetation ecosystems in high latitudes of the Northern Hemisphere (R2>0.8). Notably, solar radiation emerges as the dominant factor worldwide, governing vegetation growth in 71.78% of the research regions, followed by precipitation (16.56%) and temperature (11.66%) variations. Furthermore, we uncover that vegetation in terrestrial ecosystems exhibits heightened sensitivity to historical temperature from 9 to 12 months ago, historical precipitation in the last three months, and historical solar radiation from 6 to 8 months ago throughout the 12-month historical time series. These findings highlight the significant lag effect of climatic factors on vegetation greenness changes and contribute to a better understanding of the impact of global climate change on terrestrial ecosystems, facilitating the development of more effective response strategies. © 2023, The Authors. All rights reserved.

关键词： Vegetation

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Vehicle detection based on point cloud intensity and distance clustering

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Journal of Physics: Conference Series 2021年第4期1748卷

作者： Zhao Wang Xing Wang Bin Fang Kun Yu Jie Ma School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China National key laboratory of multispectral information processing technology Huazhong University of Science and Technology Wuhan 430074 China Science and technology on complex system control and intelligent agent cooperation laboratory Beijing 100074 China

In the intelligent transportation system, vehicle detection is one of the essential technologies in obstacle avoidance and navigation, however the existing vehicle detection methods cannot meet the actual needs. This paper presents a vehicle detection method combines the intensity and distance information of point cloud, which improves the segmentation performance of nearby objects. Specifically, the data of point cloud collected by lidar is preprocessed first. Then the processed point cloud is clustered by combining its coordinate and intensity information. Finally, the clustered suspected targets are fed to the random forest classifier. Our method can efficiently detect and classify targets in large-scale disordered 3D point cloud with high accuracy. In the real-scanned Livox Mid-40 Lidar dataset, our proposed method improves the detection accuracy by 31% compared with the traditional Euclidean clustering.

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Contrasting Trends and Drivers of Global Surface and Canopy Urban Heat Islands

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Geophysical Research Letters 2023年第15期50卷 e2023GL104661-e2023GL104661页

作者： Du, Huilin Zhan, Wenfeng Voogt, James Bechtel, Benjamin Chakraborty, T.C. Liu, Zihan Hu, Leiqiu Wang, Zhihua Li, Jiufeng Fu, Peng Liao, Weilin Luo, Ming Li, Long Wang, Shasha Huang, Fan Miao, Shiqi Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System Science Nanjing University Nanjing China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing China Department of Geography Western University LondonON Canada Department of Geography Ruhr-University Bochum Bochum Germany Atmospheric Sciences and Global Change Division Pacific Northwest National Laboratory RichlandWA United States Department of Atmospheric Science University of Alabama in Huntsville HuntsvilleAL United States School of Sustainable Engineering and the Built Environment Arizona State University TempeAZ United States Center for Environment Energy and Economy HarrisburgPA United States Guangdong Key Laboratory for Urbanization and Geo-simulation School of Geography and Planning Sun Yat-sen University Guangzhou China

A comprehensive comparison of the trends and drivers of global surface and canopy urban heat islands (termed Is and Ic trends, respectively) is critical for better designing urban heat mitigation strategies. However, such a global comparison remains largely absent. Using spatially continuous land surface temperatures and surface air temperatures (2003–2020), here we find that the magnitude of the global mean Is trend (0.19 ± 0.006°C/decade, mean ± SE) for 5,643 cities worldwide is nearly six-times the corresponding Ic trend (0.03 ± 0.002°C/decade) during the day, while the former (0.06 ± 0.004°C/decade) is double the latter (0.03 ± 0.002°C/decade) at night. Variable importance scores indicate that global daytime Is trend is slightly more controlled by surface property, while background climate plays a more dominant role in regulating global daytime Ic trend. At night, both global Is and Ic trends are mainly controlled by background climate. © 2023. The Authors.

关键词： Surface properties

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Multi-task Paired Masking with Alignment Modeling for Medical Vision-Language Pre-training

arXiv

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arXiv 2023年

作者： Zhang, Ke Yang, Yan Yu, Jun Jiang, Hanliang Fan, Jianping Huang, Qingming Han, Weidong The Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Regional Medical Center for National Institute of Respiratory Diseases Sir Run Run Shaw Hospital College of Medicine Zhejiang University Hangzhou310016 China AI Lab at Lenovo Research 100094 China The School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China The Department of Medical Oncology at Sir Run Run Shaw Hospital College of Medicine Zhejiang University Hangzhou China The College of Mathematical Medicine Zhejiang Normal University Jinhua China

In recent years, the growing demand for medical imaging diagnosis has placed a significant burden on radiologists. As a solution, Medical Vision-Language Pre-training (Med-VLP) methods have been proposed to learn universal representations from medical images and reports, benefiting downstream tasks without requiring fine-grained annotations. However, existing methods have overlooked the importance of cross-modal alignment in joint image-text reconstruction, resulting in insufficient cross-modal interaction. To address this limitation, we propose a unified Med-VLP framework based on Multi-task Paired Masking with Alignment (MPMA) to integrate the cross-modal alignment task into the joint image-text reconstruction framework to achieve more comprehensive cross-modal interaction, while a Global and Local Alignment (GLA) module is designed to assist self-supervised paradigm in obtaining semantic representations with rich domain knowledge. Furthermore, we introduce a Memory-Augmented Cross-Modal Fusion (MA-CMF) module to fully integrate visual information to assist report reconstruction and fuse the multi-modal representations adequately. Experimental results demonstrate that the proposed unified approach outperforms previous methods in all downstream tasks, including uni-modal, cross-modal, and multimodal tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Alignment

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S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

arXiv

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arXiv 2024年

作者： Wang, Xiao Tang, Ke Dai, Xingyuan Xu, Jintao Du, Quancheng Ai, Rui Wang, Yuxiao Gu, Weihao Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei230031 China Haomo Technology Co. Ltd. Beijing100192 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266114 China The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S4TP) framework. Specifically, S4TP integrates the Social-Aware Trajectory Prediction (SATP) and Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to effectively encode the driving scene and incorporates an AV’s planned trajectory during the prediction decoding process. SADRF assesses the expected surrounding risk degrees during AVs-HDVs interactions, each with different social characteristics, visualized as two-dimensional heat maps centered on the AV. SADRF models the driving intentions of the surrounding HDVs and predicts trajectories based on the representation of vehicular interactions. S4TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs’ trajectories as input. With the integration of SADRF, S4TP executes real-time online optimization of the planned trajectory of AV within low-risk regions, thus improving the safety and the interpretability of the planned trajectory. We have conducted comprehensive tests of the proposed method using the SMARTS simulator. Experimental results in complex social scenarios, such as unprotected left-turn intersections, merging, cruising, and overtaking, validate the superiority of our proposed S4TP in terms of safety and rationality. S4TP achieves a pass rate of 100% across all scenarios, surpassing the current state-of-the-art methods Fanta of 98.25% and Predictive-Decision of 94.75%. Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Near-real-time global gridded daily CO2 emissions 2021

arXiv

引用

arXiv 2022年

作者： Dou, Xinyu Hong, Jinpyo Ciais, Philippe Chevallier, Frédéric Yan, Feifan Yu, Ying Hu, Yifan Huo, Da Sun, Yun Wang, Yilong Davis, Steven J. Crippa, Monica Janssens-Maenhout, Greet Guizzardi, Diego Solazzo, Efisio Lin, Xiaojuan Song, Xuanren Zhu, Biqing Cui, Duo Ke, Piyu Wang, Hengqi Zhou, Wenwen Huang, Xia Deng, Zhu Liu, Zhu Department of Earth System Science Tsinghua University Beijing100084 China Department of Computer Science and Technology Tsinghua University Beijing100084 China Laboratoire des Sciences du Climat et de l'Environnement LSCE/IPSL CEA-CNRS-UVSQ UniversitéParis-Saclay Gif-sur-Yvette France Key Laboratory of Marine Environment and Ecology Frontiers Science Center for Deep Ocean Multispheres and Earth System Ministry of Education Ocean University of China Qingdao266100 China Environmental Sciences and Engineering University of North Carolina at Chapel Hill Chapel Hill United States Key Laboratory of Sustainable Forest Ecosystem Management Northeast Forestry University Harbin150040 China School of Environmental Science and Engineering Tianjin University Tianjin300072 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China Department of Earth System Science University of California IrvineCA United States Ispra Italy Product and Solution & Website Business Unit Alibaba Cloud Hangzhou311121 China

We present a near-real-time global gridded daily CO2 emissions dataset (GRACED) throughout 2021. GRACED provides gridded CO2 emissions at a 0.1°×0.1°spatial resolution and 1-day temporal resolution from cement production and fossil fuel combustion over seven sectors, including industry, power, residential consumption, ground transportation, international aviation, domestic aviation, and international shipping. GRACED is prepared from a near-real-time daily national CO2 emissions estimates (Carbon Monitor), multi-source spatial activity data emissions and satellite NO2 data for time variations of those spatial activity data. GRACED provides the most timely overview of emissions distribution changes, which enables more accurate and timely identification of when and where fossil CO2 emissions have rebounded and decreased. Uncertainty analysis of GRACED gives a grid-level two-sigma uncertainty of value of ±19.9% in 2021, indicating the reliability of GRACED was not sacrificed for the sake of higher spatiotemporal resolution that GRACED provides. Continuing to update GRACED in a timely manner could help policymakers monitor energy and climate policies’ effectiveness and make adjustments quickly. © 2022, CC BY.

关键词： Uncertainty analysis

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Automated Assembly by Two-Fingered Microhand for Fabrication of Soft Magnetic Microrobots

Automated Assembly by Two-Fingered Microhand for Fabrication...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Yue Zhao Xiaoming Liu Ruixi Wang Dan Liu Masaru Kojima Qiang Huang Tatsuo Arai Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing China School of Mechatronical Engineering Beijing Institute of Technology Beijing China Department of Intelligent Manufacturing Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Materials Engineering Science Osaka University Osaka Japan Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Micro-assembly is an emerging method to fabricate microrobots with multiple modules or particles. However, there is always a lack of a flexible and efficient method to freely create the desired magnetic soft microrobots. In this paper, an automated assembly system based on a two-fingered microhand is presented for fabricating magnetic soft microrobots. Our proposed system can automatically pick and place components to assemble microrobots with a two-fingered micromanipulator, and orient these components through an external magnetic field. The automated assembly has the advantages of high accuracy, high speed, and high success rate. It can endow magnetic microrobots with flexible material selection, arbitrary geometry design, and programable magnetization profile. We can make full use of this system to fabricate multiple magnetic soft microrobots. The experiment results demonstrate that this system can efficiently fabricate microrobots with excellent mechanical properties, which have application potential in robotics, biomedical engineering, and environmental governance.

关键词： Three-dimensional displays Shape Micromanipulators Magnetization Manuals Three-dimensional printing Soft magnetic materials

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Society 5.0: Metaverse Facilitated Human-centric “5H” Services Across Cyber-Physical-Social Spaces

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IFAC-PapersOnLine 2024年第3期58卷 159-164页

作者： Xiao Wang Jun Huang QingHua Ni Zhe Wan HuaDan Xue Larry Stapleton Fei-Yue Wang Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei 230601 China Macau University of Science and Technology Macau 999078 China Beijing Normal University Beijing 100875 China Department of Radiology Peking Union Medical College Hospital Shuaifuyuan Beijing 100730 Dongcheng District China Brownsbarn Thomastown Co. Kilkenny Ireland R95D8P2 Qingdao Academy of Intelligent Industries Qingdao 266109 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

Cyber-Physical-Social systems bridge the gap between social resource organization and distribution, and give birth to Society 5.0, which represents a transformative vision aimed at realizing the human-centric paradigm for more efficient and effective sustainable development. In this paper, we discuss the decentralized paradigm in fostering human needs-driven smart services, in line with Maslow’s hierarchy of needs theory. Societies 5.0 is committed to optimizing the use of natural, artificial, and social resources by enhancing democratic participation and ensuring that decision-making processes are more transparent, reliable, and aligned with the needs of the populace in sustainable ways. Moreover, our discussion extends to how Society 5.0’s principles correlate with the United Nations Sustainable Development Goals (SDGs), providing a framework that supports health, education, and poverty reduction, among other targets. This approach also aligns with the Human Development Index (HDI), reinforcing the notion that technological progress in Society 5.0 does not overshadow but rather complements and enhances human values, paving a synergistic path towards sustainable development that is both advanced and fundamentally human-centric.

关键词： Cyber-Physical-Social systems Society 5.0 Human-Centric Services Socio-technical synergistic sustainable development

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Fast two-bit operations in inductively coupled flux qubits

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Physical Review B 2005年第2期71卷 024532-024532页

作者： J. Q. You Y. Nakamura Franco Nori Frontier Research System The Institute of Physical and Chemical Research (RIKEN) Wako-shi 351-0198 Japan Department of Physics and National Laboratory for Surface Physics Fudan University Shanghai 200433 China NEC Fundamental and Environmental Research Laboratories Tsukuba Ibaraki 305-8051 Japan CREST Japan Science and Technology Agency (JST) Kawaguchi Saitama 332-0012 Japan Center for Theoretical Physics Physics Department Center for the Study of Complex Systems University of Michigan Ann Arbor Michigan 48109-1120 USA

A central problem for implementing efficient quantum computing is how to realize fast operations (both one- and two-bit ones). However, this is difficult to achieve for a collection of qubits, especially for those separated far away, because the interbit coupling is usually much weaker than the intrabit coupling. Here we present an experimentally feasible method to effectively couple two flux qubits via a common inductance and treat both single and coupled flux qubits with more realistic models, which include the loop inductance. The main advantage of our proposal is that a strong interbit coupling can be achieved using a small inductance, so that two-bit as fast as one-bit operations can be easily realized. We also show the flux dependence of the transitions between states for the coupled flux qubits.

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An Intrusive Gibbs Sampling Method for Implementating the Non-Synchronous Measurements of Microphone Arrays: An Alternative Way for the Expectation Maximization Algorithm of Non-Synchronous Measurements

SSRN

引用

SSRN 2024年

作者： Xu, Lingji Zeng, Fanchang Antoni, Jerome Yu, Liang Li, Zhenglin Wang, Ran Jiang, Weikang Southern Marine Science and Engineering Guangdong Laboratory Zhuhai519000 China Ministry of Education Zhuhai519082 China Laboratoire Vibrations Acoustique INSA-Lyon Batiment St. Exupery 25 bis av. Jean Capelle Villeurbanne69621 Cedex France School of Civil Aviation Northwestern Polytechnical University Xi’an710072 China State Key Laboratory of Airliner Integration Technology and Flight Simulation Shanghai200126 China College of Logistics Engineering Shanghai Maritime University Shanghai201306 China State Key Laboratory of Mechanical System Vibration Shanghai Jiao Tong University Shanghai200240 China

The non-synchronous measurements of microphone arrays are a powerful method for achieving large arrays and/or high microphone density by scanning the object of interest from a sequential movement of an arbitrary prototype array. It has attracted great interest recently since it is beyond the fundamental limitation of working frequency that is determined by the aperture and microphone density of an array. A crucial problem of non-synchronous measurements is to recover the missing phase relations information between consecutive positions compared with the synchronous measurements. The problem in the traditional solution is generally attributed to the matrix completion problem of a block diagonal spectral matrix. In the paper, this problem of non-synchronous measurements has been investigated as a problem of solving a system of equations in the Bayesian formalism. The Gibbs sampling method (a probabilistic approach) is proposed in this paper to reconstruct the source field that is encoded by unobservable latent variables. The proposed method can directly sample in the posterior probability density function (PDF) of all random variables. In the numerical simulations, convergence diagnosis of the Markov chain is illustrated through three approaches (i.e. trace plot, ergodic mean plot, and autocorrelation function plot). Acoustical source reconstruction error is also discussed with respect to the frequency range, signal-to-noise ratio (SNR), measurement distances, and shift distance of non-synchronous measurements. The proposed method is shown to return similar results with the Expectation Maximization algorithm of non-synchronous measurements. The effectiveness of the proposed method is also validated by experiments in a semi-anechoic chamber. © 2024, The Authors. All rights reserved.

关键词： Probability density function

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