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A dataset of lake level changes in China between 2002 and 2023 using multi-altimeter data

big Earth data 2024年第1期8卷 166-188页

作者： Shanmu Ma Jingjuan Liao Ruofan Jing Jiaming Chen Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina International research Center of big data for Sustainable Development Goals BeijingChina University of Chinese Academy of Sciences BeijingChina

Lake water levels are an important indicator of water balance and water cycles,and are essential for climate and environmental change studies and water resource ***,lake level measurements are scarce or inconsistent throughout the country,and traditional gauge measurements of many lakes are not feasible,so satellite altimetry is a vital alternative to gauge lake ***,the accuracy and sam-pling frequency of lake level time series are usually low because of time and space coverage limitations;therefore,it is necessary to utilize multialtimeter data to monitor lake levels and obtain lake level changes over long time *** this study,we extracted the water level changes in 988 lakes(>10 km^(2))in China between 2002 and 2023 based on ICESat/-2,Cryosat-2,Jason-1/2/3,and Sentinel-3A/3B altimetry data using waveform retracking,lake level extraction,lake level time series construction,the fusion of multi-altimeter lake level time series,and outlier removal.A total of 55%of the lakes in this dataset have been monitored for more than 10 years,and 34%have more than 12 times the annual average water level *** the same time,in situ data from 21 lakes were used for validation,and the average root mean square error(RMSE)for each of the datasets of ICESat/-2,Cryosat-2,Jason-1/2/3,and Sentinel-3A/3B versus the in situ lake levels are 0.223 m,0.163 m,0.207 m,0.596 m,0.295 m,0.275 m,0.243 m,and 0.317 m,respectively,and the mean RMSE of the fused lake levels reaches 0.332 *** the monitoring period,the water levels in Chinese lakes generally *** overall annual average rate of change at the 20 and 10-year scales was 0.123 m/a and 0.151 m/a,respectively,among which the overall water levels in large lakes increased *** lakes with a faster rate of decline in the water level were primarily *** water storage in each lake region in China shows an upward trend,with the most significant increase in the Tibetan Plateau reg

关键词： Lake level multi-altimeter China spatiotemporal variation

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IoTDQ: An Industrial IoT data Analysis Library for Apache IoTDB

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big data Mining and Analytics 2024年第1期7卷 29-41页

作者： Pengyu Chen Wendi He Wenxuan Ma Xiangdong Huang Chen Wang School of Software Tsinghua UniversityBeijing 100084China National Engineering research Center for big data Software(NERCBDS) Tsinghua UniversityBeijing 100084China

There is a growing demand for time series data analysis in industry *** loTDB is a time series database designed for the Internet of Things(loT)with enhanced storage and I/O *** User-Defined Functions(UDF)provided,computation for time series can be executed on Apache loTDB *** satisfy most of the common requirements in industrial time series analysis,we create a UDF library,loTDQ,on Apache *** library integrates stream computation functions on data quality analysis,data profiling,anomaly detection,data repairing,*** enables users to conduct a wide range of analyses,such as monitoring,error diagnosis,equipment reliability *** provides a framework for users to examine loT time series with data quality *** show that loTDQ keeps the same level of performance compared to mainstream alternatives,and shortens I/O consumption for Apache loTDB users.

关键词： industrial big data data quality data mining and analytics

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Perpendicular-Cutdepth:Perpendicular Direction Depth Cutting data Augmentation Method

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Computers, Materials & Continua 2024年第4期79卷 927-941页

作者： Le Zou Linsong Hu Yifan Wang Zhize Wu Xiaofeng Wang Anhui Provincial Engineering Laboratory of big data Technology Application forUrban Infrastructure School ofArtificial Intelligence and Big DataHefei UniversityHefei230601China institute of Applied Optimization School of Artificial Intelligence and Big DataHefei UniversityHefei230601China

Depth estimation is an important task in computer *** data at scale for monocular depth estimation is challenging,as this task requires simultaneously capturing RGB images and depth ***,data augmentation is crucial for this *** data augmentationmethods often employ pixel-wise transformations,whichmay inadvertently disrupt edge *** this paper,we propose a data augmentationmethod formonocular depth estimation,which we refer to as the Perpendicular-Cutdepth *** method involves cutting realworld depth maps along perpendicular directions and pasting them onto input images,thereby diversifying the data without compromising edge *** validate the effectiveness of the algorithm,we compared it with existing convolutional neural network(CNN)against the current mainstream data augmentation ***,to verify the algorithm’s applicability to Transformer networks,we designed an encoder-decoder network structure based on Transformer to assess the generalization of our proposed *** results demonstrate that,in the field of monocular depth estimation,our proposed method,Perpendicular-Cutdepth,outperforms traditional data *** the indoor dataset NYU,our method increases accuracy from0.900 to 0.907 and reduces the error rate from0.357 to *** the outdoor dataset KITTI,our method improves accuracy from 0.9638 to 0.9642 and decreases the error rate from 0.060 to 0.0598.

关键词： Perpendicular depth estimation data augmentation

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Theoretical Exploration of Alloying Effects on Stabilities and Mechanical Properties ofγʹPhase in Novel Co–Al–Nb-Base Superalloys

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Acta Metallurgica Sinica(English Letters) 2024年第7期37卷 1238-1248页

作者： Guan-Cheng Gu Zhao-Jing Han Ze-Yu Chen Zhao-Xuan Li Sheng-Bao Xia Zheng-Ning Li Hua Jin Wei-Wei Xu Xing-Jun Liu Shenzhen research institute of Xiamen University School of Aerospace EngineeringXiamen UniversityXiamen361005China institute of Materials Genome and big data Harbin Institute of TechnologyShenzhen518055China

The new developedγ/γʹCo–Al–Nb-base alloys show great potentials as high-temperature ***,finding appropriate compositions to improve performance of alloys still poses a great challenge to the development of Co–Al–Nb-base *** by the lack of alloying effects on fundamental properties of criticalγʹphase,we systematically performed a theoretical investigation on the effect of alloying elements TM(TM:Ti,V,Cr,Zr,Mo,Ta,W,Re,and Ru)on phase stabilities and mechanical properties of L1_(2)-typeγʹ(Co,Ni)_(3)(Al,Nb).By analyzing the stability ofγʹphase with respect to its competitive B2 and D0_(19) phases,the results shown that Ti,V,and Cr enhance the L1_(2) stability and widen the L1_(2)–D0_(19) energy barrier,in which V yields the maximum *** analysis of electronic structure indicated that the alternation of valence electrons at fermi level would be the atomic origin for doping TM inγʹ*** calculated results of mechanical properties shown that V and Cr are expected to be optimal dopant for enhancing the strength and the ductility ofγʹ*** addition of Ta is also beneficial for enhancing the strength at the slight expense of ductility ofγʹ*** drawing the mechanical maps,the preferred composition range for the phases with desired properties is roughly demarcated in theory for the multi-addition of V/Cr and V/Ta inγʹ*** findings would be useful for optimizing the performance of novelγ/γʹCo–Al–Nb-base superalloys.

关键词： Co-Al-Nb-base superalloys γ/γʹdual-phase Phase stability Mechanical properties First-principle methods

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Reproductive Characteristics and Trends of Major Pregnancy Outcomes of Women at Different Parities-beijing Municipality,China,2013-2022

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China CDC weekly 2024年第31期6卷 786-792页

作者： Zhaoxia Jia Yongxian Zhao Lei Wang Qingqing Wu Moning Guo Jianpeng Zheng Lili Huang Junhua Wang Zhao Wang Di Zhang Minghui Wu Department of information and statistics Beijing Obstetrics and Gynecology HospitalCapital Medical UniversityBeijing Maternal and Child Health Care HospitalBeijingChina Department of data resources and statistics Beijing Municipal Health Big Data and Policy Research CenterBeijingChina

Summary What is already known about this topic?With socioeconomic development,the increase of older pregnancies and multiparas has brought risks to mothers and *** is added by this report?As parities increased,the proportion of women of advanced maternal age(AMA)and non-local domicile increased,while the proportion of women with higher education levels *** with≥3 parities are more likely to have preterm birth(PTB)and *** are the implications for public health practice?A comprehensive analysis of pregnancy traits among women at different parities offers a robust foundation for tailored strategies against adverse pregnancy outcomes.

关键词： mother pregnancy likely

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Time-sensitive prediction of NO_(2) concentration in China using an ensemble machine learning model from multi-source data

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Journal of Environmental Sciences 2024年第3期137卷 30-40页

作者： Chenliang Tao Man Jia Guoqiang Wang Yuqiang Zhang Qingzhu Zhang Xianfeng Wang Qiao Wang Wenxing Wang big data research Center for Ecology and Environment Environment Research InstituteShandong UniversityQingdao 266237China Shandong Provincial Eco-environment Monitoring Center Jinan 250101China

Nitrogen dioxide(NO_(2))poses a critical potential risk to environmental quality and public health.A reliable machine learning(ML)forecasting framework will be useful to provide valuable information to support government *** on the data from1609 air quality monitors across China from 2014-2020,this study designed an ensemble ML model by integrating multiple types of spatial-temporal variables and three sub-models for time-sensitive prediction over a wide *** ensemble ML model incorporates a residual connection to the gated recurrent unit(GRU)network and adopts the advantage of Transformer,extreme gradient boosting(XGBoost)and GRU with residual connection network,resulting in a 4.1%±1.0%lower root mean square error over XGBoost for the test *** ensemble model shows great prediction performance,with coefficient of determination of 0.91,0.86,and 0.77 for 1-hr,3-hr,and 24-hr averages for the test results,*** particular,this model has achieved excellent performance with low spatial uncertainty in Central,East,and North China,the major site-dense *** the interpretability analysis based on the Shapley value for different temporal resolutions,we found that the contribution of atmospheric chemical processes is more important for hourly predictions compared with the daily scale predictions,while the impact of meteorological conditions would be ever-prominent for the *** with existing models for different spatiotemporal scales,the present model can be implemented at any air quality monitoring station across China to facilitate achieving rapid and dependable forecast of NO_(2),which will help developing effective control policies.

关键词： Air quality prediction Deep learning Ensemble method Nitrogen dioxide Spatiotemporal covariates

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Trends in the Incidence of High-Risk Newborns Based on a New Conceptual Framework-beijing Municipality,China,2013-2022

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China CDC weekly 2024年第31期6卷 767-771页

作者： Yongxian Zhao Zhaoxia Jia Lei Wang Qingqing Wu Moning Guo Dong Han Lili Huang Junhua Wang Di Zhang Zhao Wang Minghui Wu beijing Obstetrics and Gynecology Hospital Capital Medical UniversityBeijing Maternal and Child Health Care HospitalBeijingChina beijing Municipal Health big data and Policy research Center BeijingChina

Summary What is already known on this topic?A new conceptual term,small and vulnerable newborns(SVN),bringing preterm birth,small for gestational age(SGA),or low birth weight(LBW)together is being advocated for assessing whether a child is at high *** is added by this report?According to the new conceptual term,the increasing incidence of high-risk newborns(from 9.82%to 10.96%)has been observed among 2,005,408 newborns over the period from 2013 to 2022,which is higher than using any of the three definitions of *** age≥35,primiparity,and multiple births are high risks for *** are the implications for public health practice?The new conceptual framework should be used to better assess the number of high-risk *** should be paid to multiple births to prevent preterm-related *** reduce term newborns who are SGA,we need to be concerned not only with multiple pregnancies but also with first-time mothers.

关键词： beijing bringing mother

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A Survey of LLM datasets:From Autoregressive Model to AI Chatbot

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Journal of Computer Science & Technology 2024年第3期39卷 542-566页

作者：杜非马新建杨婧如柳熠罗超然王学斌姜海鸥景翔 National Key Laboratory of data Space Technology and System Beijing 100195China Advanced institute of big data Beijing 100195China Fu Foundation School of Engineering and Applied Science Columbia UniversityNY 10027U.S.A. School of Software and Microelectronics Peking UniversityBeijing 100091China CCF IEEE

Since OpenAI opened access to ChatGPT,large language models(LLMs)become an increasingly popular topic attracting researchers’attention from abundant ***,public researchers meet some problems when developing LLMs given that most of the LLMs are produced by industries and the training details are typically *** datasets are an important setup of LLMs,this paper does a holistic survey on the training datasets used in both the pre-train and fine-tune *** paper first summarizes 16 pre-train datasets and 16 fine-tune datasets used in the state-of-the-art ***,based on the properties of the pre-train and fine-tune processes,it comments on pre-train datasets from quality,quantity,and relation with models,and comments on fine-tune datasets from quality,quantity,and *** study then critically figures out the problems and research trends that exist in current LLM *** study helps public researchers train and investigate LLMs by visual cases and provides useful comments to the research community regarding data *** the best of our knowledge,this paper is the first to summarize and discuss datasets used in both autoregressive and chat *** survey offers insights and suggestions to researchers and LLM developers as they build their models,and contributes to the LLM study by pointing out the existing problems of LLM studies from the perspective of data.

关键词： large language model(LLM) autoregressive model AI chatbot natural language processing(NLP)corpora OpenAI

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A Distributed Computing Algorithm for Electricity Carbon Emission Flow and Carbon Emission Intensity

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Protection and Control of Modern Power Systems 2024年第2期9卷 138-146页

作者： Xingping Wu Wei Yang Ning Zhang Chunlei Zhou Jinwei Song Chongqing Kang big data Center of China Network Chinese Society of Electrical Engineering State Network big data Center Department of Electrical Engineering Tsinghua UniversityBeijingChina 不详 big data Center State Grid Corporation of ChinaBeijing 100052China Department of Electrical Engi-neering Tsinghua UniversityBeijingChina

The calculation of the indirect carbon emis-sion is essential for power system policy making,carbon market development,and power grid *** em-bedded carbon emissions of the electricity system are commonly calculated by carbon emission flow ***,the calculation procedure is time-consuming,especially for a country with 500-1000 thousand nodes,making it challenging to obtain nationwide carbon emis-sions intensity ***,the calculation procedure requires to gather all the grid data with high classified levels from different power grid companies,which can prevent data sharing and cooperation among different *** paper proposes a distributed computing algorithm for indirect carbon emission that can reduce the time consumption and provide privacy *** core idea is to utilize the sparsity of the nodes’flow matrix of the nationwide grid to partition the computing procedure into parallel sub-procedures exe-cuted in multiple *** flow and structure data of the regional grid are transformed irreversibly for pri-vacy protection,when transmitted between terminals.A 1-master-and-N-slave layout is adopted to verify the *** algorithm is suitable for large grid compa-nies with headquarter and branches in provinces,such as the State Grid Corporation of China.

关键词： Carbon emission flow cooperative computing carbon emission intensity matrix block par-tition power flow tracing parallel computing privacy protection

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A visual modeling method for spatiotemporal and multidimensional features in epidemiological analysis:Applied COVID-19 aggregated datasets

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Computational Visual Media 2024年第1期10卷 161-186页

作者： Yu Dong Christy Jie Liang Yi Chen Jie Hua School of Computer Science University of Technology SydneySydneyNSW2007Australia beijing Key Laboratory of big data Technology for Food Safety Beijing Technology and Business UniversityBeijing100048China

The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological ***,most epidemiology visualizations do not support the combined analysis of objective factors that might influence the transmission situation,resulting in a lack of quantitative and qualitative *** address this issue,we developed a portrait-based visual modeling method called+*** method considers the spatiotemporal features of virus transmission patterns and multidimensional features of objective risk factors in communities,enabling portrait-based exploration and comparison in epidemiological *** applied+msRNAer to aggregate COVID-19-related datasets in New South Wales,Australia,combining COVID-19 case number trends,geo-information,intervention events,and expert-supervised risk factors extracted from local government area-based *** perfected the+msRNAer workflow with collaborative views and evaluated its feasibility,effectiveness,and usefulness through one user study and three subject-driven case *** feedback from experts indicates that+msRNAer provides a general understanding for analyzing comprehension that not only compares relationships between cases in time-varying and risk factors through portraits but also supports navigation in fundamental geographical,timeline,and other factor *** adopting interactions,experts discovered functional and practical implications for potential patterns of long-standing community factors regarding the vulnerability faced by the *** confirmed that+msRNAer is expected to deliver visual modeling benefits with spatiotemporal and multidimensional features in other epidemiological analysis scenarios.

关键词： visual modeling epidemiological analysis spatiotemporal multidimensional COVID-19

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