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4th Asia-Pacific Artificial Intelligence and big data Forum, AIBDF 2024

作者： Zhao, Feng Fan, Wenxuan Han, Zhongwei Chen, Hongyu School of Computer Science and Technology Shandong Technology and Business University Shandong Yantai China Yantai Key Laboratory of Big Data Modeling and Intelligent Computing Shandong Yantai China Immersion Technology and Evaluation Shandong Engineering Research Center Shandong Yantai China Information Engineering College Yantai Institute of Technology Shandong Yantai China Shandong Technology and Business University Shandong Yantai China

ISBN: (纸本)9798400710865

Functional connectivity networks (FCNs), particularly those utilizing the phase lag index (PLI) method, have been instrumental in elucidating the pathological features of Major Depressive Disorder (MDD) by assessing the synchrony and lag of electroencephalogram (EEG) signal waveforms. Currently, the more prevalent methods are traditional FCNs that quantify phase synchronization as scalar values and dynamic FCNs (D-FCNs) that employ sliding window approaches to capture the instantaneous variations in functional connectivity. However, these two methods merely capture the low-level functional connections between paired regions of interest (ROIs) from both the static and dynamic perspectives, and fail to reflect the high-level functional connections involving multiple ROIs. Moreover, the feature dimension of the dynamic FCN is excessively high, and there exists a phase mismatch issue between different samples, which renders it impossible to be directly applied to the classification task, and no better solution is available at present. To mitigate these issues, we proposed a comprehensive framework that includes segmenting EEG sequences based on PLI to construct dynamic FCNs;employing seventh-order central moments for feature extraction to form low-order FCNs (Lo-FCNs);and establishing high-order FCNs (Ho-FCNs) based on Pearson correlation theory derived from Lo-FCNs. We conducted classification experiments across four distinct EEG frequency bands using our proposed framework while analyzing relevant features through graph theory and brain topological mapping techniques. The experiments showed that the proposed framework has a high classification accuracy rate in the classification experiments of MDD and NC, and proved the importance of high-order features in classification experiments, indicating that they may serve as physiological markers for MDD diagnosis. © 2024 Copyright held by the owner/author(s).

关键词： Electroencephalography

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Application of machine learning in ocean data

Application of machine learning in ocean data

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作者： Lou, Ranran Lv, Zhihan Dang, Shuping Su, Tianyun Li, Xinfang Qingdao China Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and Technology Qingdao China Marine Data and Information Center The First Institute of Oceanography MNR Qingdao China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Qingdao China Thuwal Saudi Arabia

In recent years, machine learning has become a hot research method in various fields and has been applied to every aspect of our life, providing an intelligent solution to problems that could not be solved or difficult to be solved before. Machine learning is driven by data. It learns from a part of the input data and builds a model. The model is used to predict and analyze another part of the data to get the results people want. With the continuous advancement of ocean observation technology, the amount of ocean data and data dimensions are rising sharply. The use of traditional data analysis methods to analyze massive amounts of data has revealed many shortcomings. The development of machine learning has solved these shortcomings. Nowadays, the use of machine learning technology to analyze and apply ocean data becomes the focus of scientific research. This method has important practical and long-term significance for protecting the ocean environment, predicting ocean elements, exploring the unknown, and responding to extreme weather. This paper focuses on the analysis of the state of the art and specific practices of machine learning in ocean data, review the application examples of machine learning in various fields such as ocean sound source identification and positioning, ocean element prediction, ocean biodiversity monitoring, and deep-sea resource monitoring. We also point out some constraints that still exist in the research and put forward the future development direction and application prospects. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.

关键词： Biodiversity

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Decadal variations in near-surface wind speed across the Northern Hemisphere on a centennial timescale and their possible causes

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Advances in Climate Change Research 2024年第6期15卷 1003-1012页

作者： Lin-Wei LI Jin-Lin ZHA Ting CHUNA Jian WU De-Ming ZHAO Wen-Xuan FAN Yan-Jun LYU Hui-Ping JIANG Key Laboratory of Atmospheric Environment and Processes in the Boundary Layer Over the Low-Latitude Plateau Region Department of Atmospheric ScienceYunnan UniversityKunming 650091China Key Laboratory of Regional Climate and Environment for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Center for Energy&Environmental Policy Research Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China

The reduction in near-surface wind speed(NSWS),followed by its recent recovery,could be a feature of decadal ***,existing studies mainly analyse the characteristics and causes of NSWS changes on regional scales and over short *** decadal variations and underlying causes of global NSWS changes over long timescales remain *** this study,we investigated the characteristics of NSWS changes in the Northern Hemisphere(NH)on a centennial scale(1900–2010)and identify the potential causes of decadal variations by using an information flow *** results indicate that NSWS in the NH experienced a remarkable decadal variation,increasing during 1900–1945 and 1970–1980 and decreasing during 1945–1970 and 1980–***,regional differences in the distribution features and decadal variations of NSWS were *** and North America showed the highest data overlap compared to other regions,reaching 59.4%.The longest period of decadal variation in NSWS was found in North America(14 years),followed by Europe(11 years),with Asia showing the smallest period(10 years).When determining the effects of large-scale ocean–atmosphere circulation fields or internal climate models on NSWS changes,prioritising causality between the two variables and the study period is essential,rather than relying solely on simple correlation *** to the information flow technique,the decadal variations in NSWS over North America during 1950–2010 were linked with the Western Hemisphere Warm Pool,whereas the North Atlantic Oscillation influenced those in *** Tropical Northern Atlantic was the driver over *** study offers a scientific foundation for understanding NSWS characteristics on a centennial timescale and the primary causes of decadal variations in NSWS across the NH.

关键词： Near-surface wind speed Centennial timescale Information flow Regional difference Northern Hemisphere

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Low-rank matrix recovery with total generalized variation for defending adversarial examples

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Frontiers of Information technology & Electronic Engineering 2024年第3期25卷 432-445页

作者： Wen LI Hengyou WANG Lianzhi HUO Qiang HE Linlin CHEN Zhiquan HE Wing W.Y.Ng School of Science Beijing University of Civil Engineering and ArchitectureBeijing 100044China School of Computer Science and Engineering South China University of TechnologyGuangzhou 510006China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen 518060China Institute of Big Data Modeling and Technology Beijing University of Civil Engineering and ArchitectureBeijing 100044China

Low-rank matrix decomposition with first-order total variation(TV)regularization exhibits excellent performance in exploration of image *** advantage of its excellent performance in image denoising,we apply it to improve the robustness of deep neural ***,although TV regularization can improve the robustness of the model,it reduces the accuracy of normal samples due to its *** our work,we develop a new low-rank matrix recovery model,called LRTGV,which incorporates total generalized variation(TGV)regularization into the reweighted low-rank matrix recovery *** the proposed model,TGV is used to better reconstruct texture information without *** reweighted nuclear norm and Li-norm can enhance the global structure ***,the proposed LRTGV can destroy the structure of adversarial noise while re-enhancing the global structure and local texture of the *** solve the challenging optimal model issue,we propose an algorithm based on the alternating direction method of *** results show that the proposed algorithm has a certain defense capability against black-box attacks,and outperforms state-of-the-art low-rank matrix recovery methods in image restoration.

关键词： Total generalized variation Low-rank matrix Alternating direction method of multipliers Adversarial example

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Observation-based sources evolution of non-methane hydrocarbons (NMHCs) in a megacity of China

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Journal of Environmental Sciences 2023年第2期124卷 794-805页

作者： Yarong Peng Hongli Wang Qian Wang Shengao Jing Jingyu An Yaqin Gao Cheng Huang Rusha Yan Haixia Dai Tiantao Cheng Qiang Zhang Meng Li Jianlin Hu Zhihao Shi Li Li Shengrong Lou Shikang Tao Qinyao Hu Jun Lu Changhong Chen Department of Environmental Science and Engineering Shanghai Key Laboratory of Atmospheric Particle Pollution and PreventionInstitute of Atmospheric SciencesFudan UniversityShanghai 200438China State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex Shanghai Academy of Environmental SciencesShanghai 200233China Department of Atmospheric and Oceanic Sciences Institute of Atmospheric SciencesFudan UniversityShanghai 200438China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingTsinghua UniversityBeijing 100084China Big Data Institute for Carbon Emission and Environmental Pollution Fudan UniversityShanghai 200438China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China

Both concentrations and emissions of many air pollutants have been decreasing due to implement of control measures in China,in contrast to the fact that an increase in emissions of non-methane hydrocarbons(NMHCs)has been *** study employed seven years continuous NMHCsmeasurements and the related activities data of Shanghai,a megacity in China,to explore evolution of emissions and effectiveness of air pollution control *** mixing ratio of NMHCs showed no statistical interannual changes,of which their compositions exhibited marked *** resulted in a decreasing trend of ozone formation potential by 3.8%/year(p<0.05,the same below),which should be beneficial to ozone pollution mitigation as its production in Shanghai is in the NMHCs-limited *** alkanes,aromatics and acetylene changed by+3.7%/year,-5.9%/year and-7.4%/year,respectively,and alkenes showed no apparent *** sources were apportioned by a positive matrix factorization ***,vehicular emissions(-5.9%/year)and petrochemical industry emissions(-7.1%/year)decreased significantly,but the decrease slowed down;significant reduction in solvent usage(-9.0%/year)appeared after 2010;however,emissions of natural gas(+12.6%/year)and fuel evaporation(with an increasing fraction)became more *** inconsistency between observations and inventories was found in interannual trend and speciation as well as source contributions,emphasizing the need for further validation in NMHCs emission *** study confirms the effectiveness of measures targeting mobile and centralized emissions from industrial sources and reveals a need focusing on fugitive emissions,which provided new insights into future air policies in polluted region.

关键词： Characteristics Source apportionment Observation-based Interannual trend Shanghai

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The Warm Arctic-Cold Eurasia Pattern and Its Key Region in Winter in CMIP6 Model Simulations

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Advances in Atmospheric Sciences 2023年第12期40卷 2138-2153,I0002-I0006页

作者： Liang ZHAO Yunwen LIU Yihui DING Qingquan LI Wei DONG Xinyong SHEN Wei CHENG Haoxin YAO Ziniu XIAO State Key Laboratory of Numerical Modeling for Atmosphere Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China Neijiang Meteorological Bureau Neijiang 641000China China Meteorological Administration National Climate CenterBeijing 100081China Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou 310058China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China Beijing Institute of the Applied Meteorology Beijing 100029China

An enhanced Warm Arctic-Cold Eurasia(WACE)pattern has been a notable feature in recent winters of the Northern ***,divergent results between model and observational studies of the WACE still *** study evaluates the performance of 39 climate models participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)in simulating the WACE pattern in winter of 1980-2014 and explores the key factors causing the differences in the simulation capability among the *** results show that the multimodel ensemble(MME)can better simulate the spatial distribution of the WACE pattern than most single *** that can/cannot simulate both the climatology and the standard deviation of the Eurasian winter surface air temperature well,especially the latter,usually can/cannot simulate the WACE pattern *** mainly results from the different abilities of the models to simulate the range and intensity of the warm anomaly in the Barents Sea-Kara seas(BKS)*** analysis shows that a good performance of the models in the BKS area is usually related to their ability to simulate location and persistence of Ural blocking(UB),which can transport heat to the BKS region,causing the warm Arctic,and strengthen the westerly trough downstream,cooling central ***,simulation of UB is key and significantly affects the model’s performance in simulating the WACE.

关键词： warm Arctic-cold Eurasia pattern Arctic amplification CMIP6 simulation evaluation extreme climate blocking highs

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China's current forest age structure will lead to weakened carbon sinks in the near future

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The Innovation 2023年第6期4卷 38-47页

作者： Rong Shang Jing M.Chen Mingzhu Xu Xudong Lin Peng Li Guirui Yu Nianpeng He Li Xu Peng Gong Liangyun Liu Han Liu Wenzhe Jiao Key Laboratory for Humid Subtropical Eco-Geogr aphical Processes of the Ministy of Education School of Geographical SciencesFujian Normal UniversityFuzhou 350117China Department of Geography and Planning University of TorontoTorontoOntario M5S 3G3Canada Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBejing 100101China Institute for Climate and Carbon Neutrality Department of Geography and Department of Earth SciencesUniversity of Hong KongHong Kong 999077China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Land Consolidation and Rehabilitation Center Ministry of Natural ResourcesBeijing 100035China Department of Civil and Environmental Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA

Forests are chiefly responsible for the terrestrial carbon sink that greatly re duces the buildup of CO_(2)concentrations in the atmosphere and alleviates climate *** predictions of terrestrial carbon sinks in the future have so far ignored the variation of forest carbon uptake with forest ***,we predict the role of China's current forest age in future carbon sink capacity by generating a high-resolution(30 m)forest age map in 2019 over China's landmass using satellite and forest inventory data and deriving forest growth curves using measurements of forest biomass and age in 3,121 *** China's forests currently have large proportions of young and middle-age stands,we project that China's forests will maintain high growth rates for about 15 ***,as the forests grow older,their net primary productivity will decline by 5.0%±1.4%in 2050,8.4%±1.6%in 2060,and 16.6%±2.8%in 2100,indicating weakened carbon sinks in the near *** weakening of forest carbon sinks can be potentially mitigated by optimizing forest age structure through selective logging and implementing new or improved *** finding is important not only for the global carbon cycle and climate projections but also for developing forest management strategies to enhance land sinks by alleviating the age effect.

关键词： forest carbon structure

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Estimating the value of a statistical life in China: A contingent valuation study in six representative cities

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Chinese Journal of Population,Resources and Environment 2023年第4期21卷 269-278页

作者： Chaoji Cao Xinke Song Wenjia Cai Yichao Li Jianhui Cong Xueying Yu Mengzhao Gao Can Wang Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing100084China Center for Healthy Cities Institute for China Sustainable UrbanizationTsinghua UniversityBeijing100084China Tsinghua Urban Institute Tsinghua UniversityBeijing100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Center for Statistical Science Tsinghua UniversityBeijing100084China Department of Industrial Engineering Tsinghua UniversityBeijing100084China School of Economics and Management Shanxi UniversityTaiyuan030000China School of Economics and Management Beihang UniversityBeijing100191China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang UniversityBeijing100191China Key Laboratory of Big Data-Based Precision Medicine(Beihang University) Ministry of Industry and Information TechnologyBeijing100191China

The value of a statistical life(VSL)is a crucial tool for monetizing health *** explore the VSL in China,this study examines people’s willingness to pay(WTP)to reduce death risk from air pollution in six representative cities in China based on face-to-face contingent valuation interviews(n=3936)from March 7,2019 to September 30,*** results reveal that the WTP varied from CNY 455 to 763 in 2019(USD 66-111),corresponding to a VSL range of CNY 3.79-6.36 million(USD 549395-921940).The VSL in China in 2019 is estimated to be CNY 4.76 million(USD 689659).The statistics indicate that monthly expenditure levels,environmental concerns,risk attitudes,and assumed market acceptance,which have seldom been dis‐cussed in previous studies,significantly impact WTP and *** findings will serve as a reference for ana‐lyzing mortality risk reduction benefits in future research and for policymaking.

关键词： Air pollution Contingent valuation method Willingness to pay Value of a statistical life China

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Projected near-surface wind speed and wind energy over Central Asia using dynamical downscaling with bias-corrected global climate models

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Advances in Climate Change Research 2024年第4期15卷 669-679页

作者： Jin-Lin ZHA Ting CHUAN Yuan QIU Jian WU De-Ming ZHAO Wen-Xuan FAN Yan-Jun LYU Hui-Ping JIANG Kai-Qiang DENG Miguel ANDRES-MARTIN Cesar AZORIN-MOLINA Deliang CHEN Key Laboratory of Atmospheric Environment and Processes in the Boundary Layer over the Low-Latitude Plateau Region Department of Atmospheric ScienceYunnan UniversityKunming 650091China Key Laboratory of Regional Climate and Environment for Temperate East Asia Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China Center for Energy&Environmental Policy Research Beijing Institute of Technology Beijing 100081China Key Laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China School of Atmospheric Sciences Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Centro de Investigaciones Sobre Desertificacion Consejo Superior de Investigaciones Cientificas(CIDECSIC-UV-Generalitat Valenciana)ClimateAtmosphere and Ocean Laboratory(Climatoc-Lab)Moncada 46113Spain Regional Climate Group.Deparment of Earth Sciences University of GothenburgGothenburg 40530Sweden

Wind energy development in Central Asia can help alleviate drought and fragile ***,current studies mainly used the global climate models(GCMs)to project wind speed and *** simulated biases in GCMs remain prominent,which induce a large uncertainty in the projected *** reduce the uncertainties of projected near-surface wind speed(NSW)and better serve the wind energy development in Central Asia,the Weather Research and Forecasting(WRF)model with bias-corrected GCMs was *** with the outputs of GCMs,dynamical downscaling acquired using the WRF model can better capture the high-and low-value centres of NSWS,especially those of Central Asia's ***,the simulated NSWS bias was also *** future changes in wind speed and wind energy,under the Representative Concentration Pathway 4.5(RCP4.5)scenario,NSWS during 2031-2050 is projected to decrease compared with that in *** magnitude of NSwS reduction during 2031-2050 willreach 0.1 m s^(-1).and the maximum reduction is projected to occur over the central and western regions(>0.2 m s^(-1)).Furthermore,future wind power density(WPD)can reveal nonstationarity and strong volatility,although a downward trend is expected during *** addition,the higher frequency of wind speeds at the turbine hub height exceeding 3.0 m s^(-1)can render the plain regions more suitable for wind energy development than the mountains from 2031 to *** study can serve as a guide in gaining insights into future changes in wind energy across Central Asia and provide a scientific basis for decision makers in the formulation of policies for addressing climate change.

关键词： Near-surface wind speed Wind power density Dynamical downscaling Central Asia WRF

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An Operational Assessment Framework for Near Real-time Cropland Dynamics:Toward Sustainable Cropland Use in Mid-Spine Belt of Beautiful China

Journal of Remote Sensing

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Journal of Remote Sensing 2023年第1期3卷 247-263页

作者： Zhenrong Du Le Yu Xin Chen Xiyu Li Dailiang Peng Shijun Zheng Pengyu Hao Jianyu Yang Huadong Guo Peng Gong Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China Ministry of Education Ecological Field Station for East Asian Migratory Birds Beijing 100084China Tsinghua University(Department of Earth System Science)-Xi’an Institute of Surveying and Mapping Joint Research Center for Next-Generation Smart Mapping Beijing 100084China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China University of Chinese Academy of Sciences Beijing 100049China Food and Agriculture Organization of the United Nations Viale delle Terme di Caracalla00153 RomeItaly College of Land Science and Technology China Agricultural UniversityBeijing 100193China Department of Geography Department of Earth Sciences and Institute for Climate and Carbon NeutralityUniversity of Hong KongHong Kong 999077China

Cropland monitoring is a crucial component for a broad user community from Land Use and Land Cover Change study to food security policy *** with the rich natural ecological environment and variable agricultural production conditions of Mid-Spine Belt of Beautiful China(MSBBC),this study developed a novel operational assessment framework that combined the near real-time land cover mapping platform(i.e.,FROM-GLC Plus),the FAO Agricultural Stress Index System,and the land degradation monitoring method suggested by United Nations Convention to Combat Desertification for the timely monitoring of cropland extent change,cropland conditions,and cropland *** integrated monitoring system,this framework can provide convenient access to high-spatiotemporalresolution cropland maps(30 m,dekadal)and instant(near real time)cropland *** to the monitoring results,we found that the abnormally high temperatures of summer 2022 adversely affected crop health in the southwest of ***,our results suggested that China’s ecological restoration projects made remarkable achievement in *** productivity of more than 70% of cropland in MSBBC has improved,and only~6% cropland(~3.69×10^(4) km^(2))has degraded since 2000,mainly distributed in cropland with steep slope,insufficient precipitation,and intensive ***-specific measures,such as conservation tillage,improved tillage systems,and cropland ecological projects,should be adopted for sustainable cropland use and further increase in land carrying capacity of MSBBC to achieve balanced east-west development in China.

关键词： Sustainable southwest policy

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