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An Innovative K-Anonymity Privacy-Preserving Algorithm to Improve data Availability in the Context of Big data

Computers, Materials & Continua 2024年第4期79卷 1561-1579页

作者： Linlin Yuan Tiantian Zhang Yuling Chen Yuxiang Yang Huang Li State Key Laboratory of Public Big data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China College of Information Engineering Guizhou Open UniversityGuiyang550025China Guizhou Academy of Tobacco Science Guiyang550025China

The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more *** K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big ***,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data *** addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be *** on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data ***,we construct a new information loss function based on the information quantity *** that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss *** addition,to reduce information loss,we improve K-anonymity in two ***,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering *** addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of ***,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information ***,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.

关键词： Blockchain big data K-anonymity 2-means clustering greedy algorithm mean-center method

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Neuro-symbolic approaches in artificial intelligence

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National Science Review 2022年第6期9卷 35-37页

作者： Pascal Hitzler Aaron Eberhart Monireh Ebrahimi Md Kamruzzaman Sarker Lu Zhou Department of Computer Science Kansas State University center for open source data and ai technologies (CODaiT) IBM Watson Department of Computing Sciences University of Hartford

Neuro-symbolic artificial intelligence refers to a field of research and applications that combines machine learning methods based on artificial neural networks, such as deep learning, with symbolic approaches to computing and artificial intelligence(ai), as can be found for example in the ai subfield of knowledge representation and reasoning.

关键词： artificial intelligence deep learning knowledge representation and reasoning neuro-symbolic integration

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Enhancing cut selection through reinforcement learning

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Science China Mathematics 2024年第6期67卷 1377-1394页

作者： Shengchao Wang Liang Chen Lingfeng Niu Yu-Hong Dai Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing100190China Research center on Fictitious Economy and data Science Chinese Academy of SciencesBeijing100190China

With the rapid development of artificial intelligence in recent years,applying various learning techniques to solve mixed-integer linear programming(MILP)problems has emerged as a burgeoning research *** from constructing end-to-end models directly,integrating learning approaches with some modules in the traditional methods for solving MILPs is also a promising *** cutting plane method is one of the fundamental algorithms used in modern MILP solvers,and the selection of appropriate cuts from the candidate cuts subset is crucial for enhancing *** to the reliance on expert knowledge and problem-specific heuristics,classical cut selection methods are not always transferable and often limit the scalability and generalizability of the cutting plane *** provide a more efficient and generalizable strategy,we propose a reinforcement learning(RL)framework to enhance cut selection in the solving process of ***,we design feature vectors to incorporate the inherent properties of MILP and computational information from the solver and represent MILP instances as bipartite ***,we choose the weighted metrics to approximate the proximity of feasible solutions to the convex hull and utilize the learning method to determine the weights assigned to each ***,a graph convolutional neural network is adopted with a self-attention mechanism to predict the value of weighting ***,we transform the cut selection process into a Markov decision process and utilize RL method to train the *** experiments are conducted based on a leading open-source MILP solver *** on both general and specific datasets validate the effectiveness and efficiency of our proposed approach.

关键词： reinforcement learning mixed-integer linear programming cutting plane method cut selection

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New Record Ocean Temperatures and Related Climate Indicators in 2023

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Advances in Atmospheric Sciences 2024年第6期41卷 1068-1082页

作者： Lijing CHENG John ABRAHAM Kevin E.TRENBERTH Tim BOYER Michael EMANN Jiang ZHU Fan WANG Fujiang YU Ricardo LOCARNINI John FASULLO Fei ZHENG Yuanlong LI Bin ZHANG Liying WAN Xingrong CHEN Dakui WANG Licheng FENG Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Viktor GOURETSKI Gengxin CHEN Alexey MISHONOV Jim REAGAN Karina VON SCHUCKMANN Yuying PAN Zhetao TAN Yujing ZHU Wangxu WEI Guancheng LI Qiuping REN Lijuan CAO Yayang LU International center for Climate and Environment Sciences Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of St.Thomas School of EngineeringMinnesota 55105USA NSF National center for Atmospheric Research BoulderColorado 80307USA University of Auckland Auckland 1010New Zealand National Oceanic and Atmospheric Administration National Centers for Environmental InformationSilver SpringMaryland 20910USA Department of Earth and Environmental Science University of PennsylvaniaPhiladelphiaPennsylvania 19104USA Institute of Oceanology Chinese Academy of SciencesQingdao 266071China National Marine Environmental Forecasting center Ministry of Natural Resources of ChinaBeijing 100081China Oceanographic data center Chinese Academy of SciencesQingdao 266071China College of Oceanography Hohai UniversityNanjing 210098China National Marine data and Information Service Tianjin 300171China Italian National Agency for New technologies Energy and Sustainable Economic DevelopmentS.Teresa Research CenterLerici 19032Italy Istituto Nazionale di Geofisica e Vulcanologia Sede di BolognaBologna 40128Italy South China Sea Institute of Oceanology Chinese Academy of SciencesGuangzhou 510301China ESSIC/CISESS-MD University of MarylandCollege ParkMD20740USA Mercator Ocean International Toulouse 31400France Eco-Environmental Monitoring and Research center Pearl River Valley and South China Sea Ecology and Environment AdministrationMinistry of Ecology and EnvironmentPRCGuangzhou 510611China National Meteorological Information center China Meteorological AdministrationBeijing 100081China International Research center of Big data for Sustainable Development Goals Beijing 100094China

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human *** 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record *** 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the *** with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of *** density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

关键词： ocean heat content salinity stratification global warming climate

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A robust synthesis route of confined carbyne

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Nano Research 2024年第7期17卷 6274-6280页

作者： Yanghao Feng Wendi Zhang Kunpeng Tang Yingzhi Chen Jiou Zhang Kecheng Cao Weili Cui Lei Shi State Key Laboratory of Optoelectronic Materials and technologies Nanotechnology Research CenterGuangdong Basic Research Center of Excellence for Functional Molecular EngineeringSchool of Materials Science and EngineeringSun Yat-sen UniversityGuangzhou 510275China School of Physical Science and Technology and Shanghai Key Laboratory of High-resolution Electron Microscopy Shanghai Tech UniversityShanghai 201210China

The unique mechanical,optical,and electrical properties of carbyne,a one-dimensional allotrope of carbon,make it a highly promising material for various *** has been demonstrated that carbon nanotubes(CNTs)can serve as an ideal host for the formation of confined carbyne(CC),with the yield being influenced by the quality of the carbon nanotubes for confinement and the carbon source for carbyne *** this study,a robust synthesis route of CC within CNTs is proposed.C70 was utilized as a precursor to provide an additional carbon source,based on its ability to supply more carbon atoms than C60 at the same filling ***-step transformation processes,including defect creation,were designed to enhance the yield of *** a result,the yield of CC was significantly increased for the C70 encapsulated single-walled CNTs by more than an order of magnitude than the empty counterparts,which also surpasses that of the double-walled CNTs,making it the most effective route for synthesizing *** findings highlight the importance of the additional carbon source and the optimal pathway for CC formation,offering valuable insights for the application of materials with high yield.

关键词： confined carbyne yield enhancement carbon nanotube C70 encapsulation defect introduction Raman spectroscopy

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Phenology of different types of vegetation and their response to climate change in the Qilian Mountains,China

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Journal of Mountain Science 2024年第2期21卷 511-525页

作者： ZHAO Kaixin LI Xuemei ZHANG Zhengrong LIU Xinyu Faculty of Geomatics Lanzhou Jiaotong UniversityLanzhou 730070China National-Local Joint Engineering Research center of technologies and Applications for National Geographic State Monitoring Lanzhou 730070China Gansu Provincial Engineering Laboratory for National Geographic State Monitoring Lanzhou 730070China

The Qilian Mountains(QM)possess a delicate vegetation ecosystem,amplifying the evident response of vegetation phenology to climate *** relationship between changes in vegetation growth and climate remains *** this end,we used MODIS NDVI data to extract the phenological parameters of the vegetation including meadow(MDW),grassland(GSD),and alpine vegetation(ALV))in the QM from 2002 to ***,we employed path analysis to reveal the direct and indirect impacts of seasonal climate change on vegetation ***,we decomposed the vegetation phenology in a time series using the trigonometric seasonality,Box-Cox transformation,ARMA errors,and Trend Seasonal components model(TBATS).The findings showed a distinct pattern in the vegetation phenology of the QM,characterized by a progressive shift towards an earlier start of the growing season(SOS),a delayed end of the growing season(EOS),and an extended length of the growing season(LOS).The growth cycle of MDW,GSD,and ALV in the QM species is clearly *** SOS for MDW and GSD occurred earlier,mainly between late April and August,while the SOS for ALVs occurred between mid-May and mid-August,a one-month delay compared to the other *** EOS in MDW and GSD were concentrated between late August and April and early September and early January,*** phenology exhibits distinct responses to seasonal temperature and precipitation *** advancement and delay of SOS were mainly influenced by the direct effect of spring temperatures and precipitation,which affected 19.59%and 22.17%of the study area,*** advancement and delay of EOS were mainly influenced by the direct effect of fall temperatures and precipitation,which affected 30.18%and 21.17%of the area,*** the contrary,the direct effects of temperature and precipitation in summer and winter on vegetation phenology seem less noticeable and were mainly influenced by indirect *** indirec

关键词： Vegetation phenology Time series decomposition Path Analysis Climate change

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Crop pest image recognition based on the improved ViT method Author links open overlay panel

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Information Processing in Agriculture 2024年第2期11卷 249-259页

作者： Xueqian Fu Qiaoyu Ma Feifei Yang Chunyu Zhang Xiaolong Zhao Fuhao Chang Lingling Han College of Information and Electrical Engineering China Agricultural UniversityBeijingChina National Innovation center for Digital Fishery China Agricultural UniversityBeijingChina Key Laboratory of Smart Farming technologies for Aquatic Animal and Livestock Ministry of Agriculture and Rural AffairsBeijingChina Beijing Engineering and Technology Research center for Internet of Things in Agriculture BeijingChina

The crop pests and diseases in agriculture is one of the most important reason for the reduction of bulk grain and oil crops and the decline of fruit and vegetable crop quality,which threaten macroeconomic stability and sustainable ***,the recognition method based on manual and instruments has been unable to meet the needs of scientific research and production due to its strong subjectivity and low *** recognition method based on pattern recognition and deep learning can automatically fit image features,and use features to classify and predict *** study introduced the improved Vision Transformer(ViT)method for crop pest image *** them,the region with the most obvious features can be effectively selected by block *** self-attention mechanism of the transformer can better excavate the special solution that is not an obvious lesion *** the experiment,data with 7 classes of examples are used for *** can be illustrated from results that this method has high accuracy and can give full play to the advantages of image processing and recognition technology,accurately judge the crop diseases and pests category,provide method reference for agricultural diseases and pests identification research,and further optimize the crop diseases and pests control work for agricultural workers in need.

关键词： Crop diseases recognition Fruit tree leaf disease Vision Transformer Deep learning Computer Vision

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Factors Influencing the Spatial Variability of air Temperature Urban Heat Island Intensity in Chinese Cities

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Advances in Atmospheric Sciences 2024年第5期41卷 817-829页

作者： Heng LYU Wei WANG Keer ZHANG Chang CAO Wei XIAO Xuhui LEE Key Laboratory of Meteorological Disaster Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)/Key Laboratory of Ecosystem Carbon Source and SinkChina Meteorological Administration(ECSS-CMA)/Jiangsu Key Laboratory of Agricultural MeteorologyNanjing University of Information Science&TechnologyNanjing 210044China Key Laboratory of Urban Meteorology China Meteorological AdministrationBeijing 100089China School of the Environment Yale UniversityNew HavenCT 06511USA

Few studies have investigated the spatial patterns of the air temperature urban heat island(AUHI)and its controlling *** this study,the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers.A total of 355 urban clusters were *** performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its *** results show that the midday AUHI is negatively correlated with climate wetness(humid:0.34 K;semi-humid:0.50 K;semi-arid:0.73 K).The annual mean midnight AUHI does not show discernible spatial patterns,but is generally stronger than the midday *** urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid(0.32±0.09 K)and the semi-arid(0.36±0.11 K)climate *** release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate *** rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations.A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land.

关键词： air temperature urban heat island spatial variations biophysical drivers Chinese cities climate model

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A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains

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Journal of Arid Land 2024年第2期16卷 195-219页

作者： LIU Xinyu LI Xuemei ZHANG Zhengrong ZHAO Kaixin LI Lanhai Faculty of Geomatics Lanzhou Jiaotong UniversityLanzhou 730070China National-Local Joint Engineering Research center of technologies and Applications for National Geographic State Monitoring Lanzhou 730070China Gansu Provincial Engineering Laboratory for National Geographic State Monitoring Lanzhou 730070China State Key Laboratory of Desert and Oasis Ecology Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqi 830011China Research center for Ecology and Environment of Central Asia Chinese Academy of SciencesUrumqi 830011China

Climate warming profoundly affects hydrological changes,agricultural production,and human *** and semi-arid areas of China are currently displaying a marked trend of warming and *** Chinese Tianshan Mountains(CTM)have a high climate sensitivity,rendering the region particularly vulnerable to the effects of climate *** this study,we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset(1961-2014)and 24 global climate models(GCMs)of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess the applicability of the CMIP6 GCMs in the CTM at the regional *** on this,we conducted a systematic review of the interannual trends,dry-wet transitions(based on the standardized precipitation index(SPI)),and spatial distribution patterns of climate change in the CTM during *** further projected future temperature and precipitation changes over three terms(near-term(2021-2040),mid-term(2041-2060),and long-term(2081-2100))relative to the historical period(1961-2014)under four shared socio-economic pathway(SSP)scenarios(i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).It was found that the CTM had experienced significant warming and wetting from 1961 to 2014,and will also experience warming in the future(2021-2100).Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble(MME)from the CMIP6 *** MME simulation results indicated an apparent wetting in 2008,which occurred later than the wetting observed from the CN05.1 in *** GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the *** and wetting are more rapid in the northern part of the *** the end of the 21st century,all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet ***,the rise in precipitation fails to counterbal

关键词： climate change Coupled Model Intercomparison Project Phase 6(CMIP6) global climate models(GCMs) shared socio-economic pathway(SSP)scenarios standardized precipitation index(SPI) Chinese Tianshan Mountains

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A Study on the Assessment and Integration of Multi-source Evapotranspiration Products over the Tibetan Plateau

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Advances in Atmospheric Sciences 2024年第3期41卷 435-448页

作者： Ming CHENG Lei ZHONG Yaoming MA Han MA Yaoxin CHANG Peizhen LI Meilin CHENG Xian WANG Nan GE School of Earth and Space Sciences University of Science and Technology of ChinaHefei 230026China CAS center for Excellence in Comparative Planetology Hefei 230026China Jiangsu Collaborative Innovation center for Climate Change Nanjing 210023China Frontiers Science center for Planetary Exploration and Emerging technologies University of Science and Technology of ChinaHefei 230026China Land-Atmosphere Interaction and its Climatic Effects Group State Key Laboratory of Tibetan Plateau Earth SystemResources and Environment(TPESRE)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China College of Atmospheric Science Lanzhou UniversityLanzhou 730000China National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes Dingri 858200China Kathmandu center of Research and Education Chinese Academy of SciencesBeijing 100101China China-Pakistan Joint Research center on Earth Sciences Chinese Academy of SciencesIslamabad 45320Pakistan

Evapotranspiration(ET)is a crucial variable in the terrestrial water,carbon,and energy *** present,a large number of multi source ET products *** to sparse observations,however,great challenges exist in the evaluation and integration of ET products in remote and complex areas such as the Tibetan Plateau(TP).In this paper,the applicability of the multiple collocation(MC)method over the TP is evaluated for the first time,and the uncertainty of multisource ET products(based on reanalysis,remote sensing,and land surface models)is further analyzed,which provides a theoretical basis for ET data *** results show that 1)ET uncertainties quantified via the MC method are lower in RS-based ET products(5.95 vs.7.06 mm month^(-1))than in LSM ET products(10.22 vs.17.97 mm month^(-1))and reanalysis ET estimates(7.27 vs.12.26 mm month-1).2)A multisource evapotranspiration(MET)dataset is generated at a monthly temporal scale with a spatial resolution of 0.25°across the TP during *** has better performance than any individual product.3)Based on the fusion product,the total ET amount over the TP and its patterns of spatiotemporal variability are clearly *** annual total ET over the entire TP is approximately 380.60 ***,an increasing trend of 1.59±0.85 mm yr^(-1)over the TP is shown during *** study provides a basis for future studies on water and energy cycles and water resource management over the TP and surrounding regions.

关键词： evapotranspiration data fusion multiple collocation the Tibetan Plateau

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