Applying mixed oxygen ionic and electronic conducting(MIEC)oxides as the cathode offers a promis-ing solution to enhance the performance of solid oxide fuel cells(SOFCs).However,the phase instability in CO_(2)-contain...Applying mixed oxygen ionic and electronic conducting(MIEC)oxides as the cathode offers a promis-ing solution to enhance the performance of solid oxide fuel cells(SOFCs).However,the phase instability in CO_(2)-containing air and sluggish oxygen reduction activity of MIEC cathodes remain a long-term chal-lenge for optimizing the electrochemical performance of SOFCs.Herein,a heterovalent co-doping strategy is proposed to enhance the oxygen reduction activity and CO_(2)tolerance of SOFCs cathodes,which can be demonstrated by developing a novel BaCo_(0.6)Fe_(0.4)O_(3)-δ(BCF)-based MIEC oxide,BaCo_(0.6)Fe_(0.2)Sn_(0.1) Y_(0.1)O_(3-δ)(BCFSY).In addition to improving the stability of BCF-based perovskites,this strategy achieves an opti-mized balance of ionic mobility and oxygen vacancies due to the synergies between the effects of the co-dopants.Compared with single-doped materials,BCFSY exhibits improved CO_(2)tolerance and consider-ably higher ORR activity,which is reflected in a significantly lower polarization resistance of 0.15Ωcm^(2) at 600℃.The results of this work provide an efficient tactic for designing electrode materials for SOFCs.展开更多
With the development of location‐based services and Big data technology,vehicle map matching techniques are growing rapidly,which is the fundamental techniques in the study of exploring global positioning system(GPS)...With the development of location‐based services and Big data technology,vehicle map matching techniques are growing rapidly,which is the fundamental techniques in the study of exploring global positioning system(GPS)data.The pre‐processed GPS data can provide the guarantee of high‐quality data for the research of mining passenger’s points of interest and urban computing services.The existing surveys mainly focus on map‐matching algorithms,but there are few descriptions on the key phases of the acquisition of sampling data,floating car and road data preprocessing in vehicle map matching systems.To address these limitations,the contribution of this survey on map matching techniques lies in the following aspects:(i)the background knowledge,function and system framework of vehicle map matching techniques;(ii)description of floating car data and road network structure to understand the detailed phase of map matching;(iii)data preprocessing rules,specific methodologies,and significance of floating car and road data;(iv)map matching algorithms are classified by the sampling frequency and data information.The authors give the introduction of open‐source GPS sampling data sets,and the evaluation measurements of map‐matching approaches;(v)the suggestions on data preprocessing and map matching algorithms in the future work.展开更多
With the development of network services and location-based systems,many mobile applications begin to use users’geographical location to provide better services.In terms of social networks,geographical location is ac...With the development of network services and location-based systems,many mobile applications begin to use users’geographical location to provide better services.In terms of social networks,geographical location is actively shared by users.In some applications with recommendation services,before the geographical location recommendation is provided,the authors have to obtain user’s permission.This kind of social network integrated with geographical location information is called location-based social networks(abbreviate for LBSNs).In the LBSN,each user has location information when he or she checked in hotels or feature spots.Based on this information,they can identify user’s trajectory of movement behaviour and activity patterns.In general,if there is friendship between two users,their trajectories in reality are likely to be similar.In this study,according to user’s geographical location information over a period of time,they explore whether there exists friendly relationship between two users based on trajectory similarity and the structure theory of graphs.In particular,they propose a new factor function and a factor graph model based on user’s geographical location to predict the friendship between two users in the real LBSN.展开更多
Glacial diamictite may provide important information on paleoenvironment and average composition of the upper continental crust(UCC).In this study,we report sedimentary facies,petrological and geochemical characterist...Glacial diamictite may provide important information on paleoenvironment and average composition of the upper continental crust(UCC).In this study,we report sedimentary facies,petrological and geochemical characteristics of Neoproterozoic diamictite from a profile of the Luoquan Formation on the southern margin of the North China Block(NCB).Upwards the sampling profile,lithostratigraphic strata vary from massive diamictite with poorly sorted carbonate gravels to laminated diamictite with small gravels of terrestrial detrital materials.Along the profile,CaO-MgO-LOI-Sr values decrease with the increase of SiO_(2)-Al2O_(3)-K2O contents.All these petrological and geochemical variations indicate a change from lodgement till deposition in the proximal of ice sheet to ice-rafting deposition in glacial-marine environment with less dolomite to supply their source.Together with previous studies on diamictite from other outcrops on the NCB,the deposition of Luoquan diamictite reflects that the glaciation on the NCB vanished and the ice-rafting effect weakened with glacial transgression process.In addition,significant co-variations of various elements with La and Al2O_(3)confirm the significant conservation of most analyzed elements during the sedimentary processes to produce diamictite.展开更多
Although the popular database systems perform well on query optimization,they still face poor query execution plans when the join operations across multiple tables are complex.Bad execution planning usually results in...Although the popular database systems perform well on query optimization,they still face poor query execution plans when the join operations across multiple tables are complex.Bad execution planning usually results in bad cardinality estimations.The cardinality estimation models in traditional databases cannot provide high-quality estimation,because they are not capable of capturing the correlation between multiple tables in an effective fashion.Recently,the state-of-the-art learning-based cardinality estimation is estimated to work better than the traditional empirical methods.Basically,they used deep neural networks to compute the relationships and correlations of tables.In this paper,we propose a vertical scanning convolutional neural network(abbreviated as VSCNN)to capture the relationships between words in the word vector in order to generate a feature map.The proposed learning-based cardinality estimator converts Structured Query Language(SQL)queries from a sentence to a word vector and we encode table names in the one-hot encoding method and the samples into bitmaps,separately,and then merge them to obtain enough semantic information from data samples.In particular,the feature map obtained by VSCNN contains semantic information including tables,joins,and predicates about SQL queries.Importantly,in order to improve the accuracy of cardinality estimation,we propose the negative sampling method for training the word vector by gradient descent from the base table and compress it into a bitmap.Extensive experiments are conducted and the results show that the estimation quality of q-error of the proposed vertical scanning convolutional neural network based model is reduced by at least 14.6%when compared with the estimators in traditional databases.展开更多
基金supported by the National Natural Science Foundation of China (No. 22078022)China Postdoctoral Science Foundation (No.2021M690379)
文摘Applying mixed oxygen ionic and electronic conducting(MIEC)oxides as the cathode offers a promis-ing solution to enhance the performance of solid oxide fuel cells(SOFCs).However,the phase instability in CO_(2)-containing air and sluggish oxygen reduction activity of MIEC cathodes remain a long-term chal-lenge for optimizing the electrochemical performance of SOFCs.Herein,a heterovalent co-doping strategy is proposed to enhance the oxygen reduction activity and CO_(2)tolerance of SOFCs cathodes,which can be demonstrated by developing a novel BaCo_(0.6)Fe_(0.4)O_(3)-δ(BCF)-based MIEC oxide,BaCo_(0.6)Fe_(0.2)Sn_(0.1) Y_(0.1)O_(3-δ)(BCFSY).In addition to improving the stability of BCF-based perovskites,this strategy achieves an opti-mized balance of ionic mobility and oxygen vacancies due to the synergies between the effects of the co-dopants.Compared with single-doped materials,BCFSY exhibits improved CO_(2)tolerance and consider-ably higher ORR activity,which is reflected in a significantly lower polarization resistance of 0.15Ωcm^(2) at 600℃.The results of this work provide an efficient tactic for designing electrode materials for SOFCs.
基金National Natural Science Foundation of China,Grant/Award Numbers:61772091,61802035,61962006,71701026,U1802271,U2001212,62072311Sichuan Science and Technology Program,Grant/Award Numbers:2021JDJQ00212018JY0448,2019YFG0106,2019YFS0067,2020YJ0481,2020YFS0466,2020YJ0430,2020JDR0164,2020YFG0153,20YYJC2785+5 种基金CCF‐Huawei Database System Innovation Research Plan:CCF‐Huawei,Grant/Award Number:DBIR2020004ANatural Science Foundation of Guangxi,Grant/Award Number:2018GXNSFDA138005A Project Supported by SiChuan Landscape and Recreation Research Center,Grant/Award Number:JGYQ2018010Innovative Research Team Construction Plan in Universities of Sichuan Province,Grant/Award Number:18TD0027Guangdong Province Key Laboratory of Popular High Performance Computers:2017B030314073Key R&D Program of Guangdong province,Grant/Award Number:2018B030325002。
文摘With the development of location‐based services and Big data technology,vehicle map matching techniques are growing rapidly,which is the fundamental techniques in the study of exploring global positioning system(GPS)data.The pre‐processed GPS data can provide the guarantee of high‐quality data for the research of mining passenger’s points of interest and urban computing services.The existing surveys mainly focus on map‐matching algorithms,but there are few descriptions on the key phases of the acquisition of sampling data,floating car and road data preprocessing in vehicle map matching systems.To address these limitations,the contribution of this survey on map matching techniques lies in the following aspects:(i)the background knowledge,function and system framework of vehicle map matching techniques;(ii)description of floating car data and road network structure to understand the detailed phase of map matching;(iii)data preprocessing rules,specific methodologies,and significance of floating car and road data;(iv)map matching algorithms are classified by the sampling frequency and data information.The authors give the introduction of open‐source GPS sampling data sets,and the evaluation measurements of map‐matching approaches;(v)the suggestions on data preprocessing and map matching algorithms in the future work.
基金This work was partially supported by the National Natural Science Foundation of China(grant nos.61772091,61802035,61962006,61702058,71701026)the Sichuan Science and Technology Program(grant nos.2018JY0448,2019YFG0106,2019YFS0067,2020YJ0481,2020YFS0466,2020YJ0430,and 2020JDR0164)+4 种基金the Natural Science Foundation of Guangxi(grant no.2018GXNSFDA138005)a Project Supported by SiChuan Landscape and Recreation Research Center(grant no.JGYQ2018010)the Innovative Research Team Construction Plan in Universities of Sichuan Province(grant no.18TD0027)Guangdong Province Key Laboratory of Popular High Performance Computers(grant no.2017B030314073)the Key R&D Program of Guangdong province(grant no.2018B030325002).
文摘With the development of network services and location-based systems,many mobile applications begin to use users’geographical location to provide better services.In terms of social networks,geographical location is actively shared by users.In some applications with recommendation services,before the geographical location recommendation is provided,the authors have to obtain user’s permission.This kind of social network integrated with geographical location information is called location-based social networks(abbreviate for LBSNs).In the LBSN,each user has location information when he or she checked in hotels or feature spots.Based on this information,they can identify user’s trajectory of movement behaviour and activity patterns.In general,if there is friendship between two users,their trajectories in reality are likely to be similar.In this study,according to user’s geographical location information over a period of time,they explore whether there exists friendly relationship between two users based on trajectory similarity and the structure theory of graphs.In particular,they propose a new factor function and a factor graph model based on user’s geographical location to predict the friendship between two users in the real LBSN.
基金supported by the National Natural Science Foundation of China (Mos.41776069 and 41572047 to Yuanyuan Xiao)Strategic Priority Research Program of the Chinese Academy of Sciences (No.XDB42020302)+1 种基金the Taishan Scholar Program of Shandong (No.ts201712075)Aoshan Scholar Program of the Pilot National Laboratory for Marine Science and Technology (Qingdao) to Weidong Sun。
文摘Glacial diamictite may provide important information on paleoenvironment and average composition of the upper continental crust(UCC).In this study,we report sedimentary facies,petrological and geochemical characteristics of Neoproterozoic diamictite from a profile of the Luoquan Formation on the southern margin of the North China Block(NCB).Upwards the sampling profile,lithostratigraphic strata vary from massive diamictite with poorly sorted carbonate gravels to laminated diamictite with small gravels of terrestrial detrital materials.Along the profile,CaO-MgO-LOI-Sr values decrease with the increase of SiO_(2)-Al2O_(3)-K2O contents.All these petrological and geochemical variations indicate a change from lodgement till deposition in the proximal of ice sheet to ice-rafting deposition in glacial-marine environment with less dolomite to supply their source.Together with previous studies on diamictite from other outcrops on the NCB,the deposition of Luoquan diamictite reflects that the glaciation on the NCB vanished and the ice-rafting effect weakened with glacial transgression process.In addition,significant co-variations of various elements with La and Al2O_(3)confirm the significant conservation of most analyzed elements during the sedimentary processes to produce diamictite.
基金the CCF-Huawei Database System Innovation Research Plan under Grant No.CCF-HuaweiDBIR2020004Athe National Natural Science Foundation of China under Grant Nos.61772091,61802035,61962006 and 61962038+1 种基金the Sichuan Science and Technology Program under Grant Nos.2021JDJQ0021 and 2020YJ0481the Digital Media Art,Key Laboratory of Sichuan Province,Sichuan Conservatory of Music,Chengdu,China under Grant No.21DMAKL02.
文摘Although the popular database systems perform well on query optimization,they still face poor query execution plans when the join operations across multiple tables are complex.Bad execution planning usually results in bad cardinality estimations.The cardinality estimation models in traditional databases cannot provide high-quality estimation,because they are not capable of capturing the correlation between multiple tables in an effective fashion.Recently,the state-of-the-art learning-based cardinality estimation is estimated to work better than the traditional empirical methods.Basically,they used deep neural networks to compute the relationships and correlations of tables.In this paper,we propose a vertical scanning convolutional neural network(abbreviated as VSCNN)to capture the relationships between words in the word vector in order to generate a feature map.The proposed learning-based cardinality estimator converts Structured Query Language(SQL)queries from a sentence to a word vector and we encode table names in the one-hot encoding method and the samples into bitmaps,separately,and then merge them to obtain enough semantic information from data samples.In particular,the feature map obtained by VSCNN contains semantic information including tables,joins,and predicates about SQL queries.Importantly,in order to improve the accuracy of cardinality estimation,we propose the negative sampling method for training the word vector by gradient descent from the base table and compress it into a bitmap.Extensive experiments are conducted and the results show that the estimation quality of q-error of the proposed vertical scanning convolutional neural network based model is reduced by at least 14.6%when compared with the estimators in traditional databases.
