As a new type of production factor in healthcare,healthcare data elements have been rapidly integrated into various health production processes,such as clinical assistance,health management,biological testing,and oper...As a new type of production factor in healthcare,healthcare data elements have been rapidly integrated into various health production processes,such as clinical assistance,health management,biological testing,and operation and supervision[1,2].Healthcare data elements include biolog.ical and clinical data that are related to disease,environ-mental health data that are associated with life,and operational and healthcare management data that are related to healthcare activities(Figure 1).Activities such as the construction of a data value assessment system,the devel-opment of a data circulation and sharing platform,and the authorization of data compliance and operation products support the strong growth momentum of the market for health care data elements in China[3].展开更多
The data production elements are driving profound transformations in the real economy across production objects,methods,and tools,generating significant economic effects such as industrial structure upgrading.This pap...The data production elements are driving profound transformations in the real economy across production objects,methods,and tools,generating significant economic effects such as industrial structure upgrading.This paper aims to reveal the impact mechanism of the data elements on the“three transformations”(high-end,intelligent,and green)in the manufacturing sector,theoretically elucidating the intrinsic mechanisms by which the data elements influence these transformations.The study finds that the data elements significantly enhance the high-end,intelligent,and green levels of China's manufacturing industry.In terms of the pathways of impact,the data elements primarily influence the development of high-tech industries and overall green technological innovation,thereby affecting the high-end,intelligent,and green transformation of the industry.展开更多
This paper explores the development of interpretable data elements from raw data using Kolmogorov-Arnold Networks(KAN).With the exponential growth of data in contemporary society,there is an urgent need for effective ...This paper explores the development of interpretable data elements from raw data using Kolmogorov-Arnold Networks(KAN).With the exponential growth of data in contemporary society,there is an urgent need for effective data processing methods to unlock the full potential of this resource.The study focuses on the application of KAN in the transportation sector to transform raw traffic data into meaningful data elements.The core of the research is the KANT-GCN model,which synergizes Kolmogorov-Arnold Networks with Temporal Graph Convolutional Networks(T-GCN).This innovative model demonstrates superior performance in predicting traffic speeds,outperforming existing methods in terms of accuracy,reliability,and interpretability.The model was evaluated using real-world datasets from Shenzhen,Los Angeles,and the San Francisco Bay Area,showing significant improvements in different metrics.The paper highlights the potential of KAN-T-GCN to revolutionize data-driven decision-making in traffic management and other sectors,underscoring its ability to handle dynamic updates and maintain data integrity.展开更多
This article explores the characteristics of data resources from the perspective of production factors,analyzes the demand for trustworthy circulation technology,designs a fusion architecture and related solutions,inc...This article explores the characteristics of data resources from the perspective of production factors,analyzes the demand for trustworthy circulation technology,designs a fusion architecture and related solutions,including multi-party data intersection calculation,distributed machine learning,etc.It also compares performance differences,conducts formal verification,points out the value and limitations of architecture innovation,and looks forward to future opportunities.展开更多
A multivariate statistical analysis was performed on multi-element soil geochemical data from the Koda Hill-Bulenga gold prospects in the Wa-Lawra gold belt, northwest Ghana. The objectives of the study were to define...A multivariate statistical analysis was performed on multi-element soil geochemical data from the Koda Hill-Bulenga gold prospects in the Wa-Lawra gold belt, northwest Ghana. The objectives of the study were to define gold relationships with other trace elements to determine possible pathfinder elements for gold from the soil geochemical data. The study focused on seven elements, namely, Au, Fe, Pb, Mn, Ag, As and Cu. Factor analysis and hierarchical cluster analysis were performed on the analyzed samples. Factor analysis explained 79.093% of the total variance of the data through three factors. This had the gold factor being factor 3, having associations of copper, iron, lead and manganese and accounting for 20.903% of the total variance. From hierarchical clustering, gold was also observed to be clustering with lead, copper, arsenic and silver. There was further indication that, gold concentrations were lower than that of its associations. It can be inferred from the results that, the occurrence of gold and its associated elements can be linked to both primary dispersion from underlying rocks and secondary processes such as lateritization. This data shows that Fe and Mn strongly associated with gold, and alongside Pb, Ag, As and Cu, these elements can be used as pathfinders for gold in the area, with ferruginous zones as targets.展开更多
This report analyzes the existing problems in terminology referring to clinical symptoms of traditional Chinese medicine(TCM)from the viewpoint of data sharing and elaborates the necessity of establishing a standard d...This report analyzes the existing problems in terminology referring to clinical symptoms of traditional Chinese medicine(TCM)from the viewpoint of data sharing and elaborates the necessity of establishing a standard directory of clinical data elements of TCM.We evaluated the principles and methods of data element extraction according to the status quo of the clinical information system and characteristics of symptoms for TCM and consequently proposed a three-layer model for optimal extraction.展开更多
For digitalization of traditional Chinese medicine(TCM),research is being conducted on objectivization of diagnosis and treatment,mathematical models of TCM theories,and application of modern information technology to...For digitalization of traditional Chinese medicine(TCM),research is being conducted on objectivization of diagnosis and treatment,mathematical models of TCM theories,and application of modern information technology to digitize the vast amounts of existing information.However,the author believes that TCM practitioners should first conduct a systematic and comprehensive refined analysis on the knowledge of TCM and unify data elements used in computer intelligence to avoid ambiguity.Thus,we must overcome the epistemological constraints and carefully analyze the relationship among data elements to achieve systematic results and administer TCM appropriately.展开更多
With increasing demand for data circulation,ensuring data security and privacy is paramount,specifically protecting privacy while maximizing utility.Blockchain,while decentralized and transparent,faces challenges in p...With increasing demand for data circulation,ensuring data security and privacy is paramount,specifically protecting privacy while maximizing utility.Blockchain,while decentralized and transparent,faces challenges in privacy protection and data verification,especially for sensitive data.Existing schemes often suffer from inefficiency and high overhead.We propose a privacy protection scheme using BGV homomorphic encryption and Pedersen Secret Sharing.This scheme enables secure computation on encrypted data,with Pedersen sharding and verifying the private key,ensuring data consistency and immutability.The blockchain framework manages key shards,verifies secrets,and aids security auditing.This approach allows for trusted computation without revealing the underlying data.Preliminary results demonstrate the scheme's feasibility in ensuring data privacy and security,making data available but not visible.This study provides an effective solution for data sharing and privacy protection in blockchain applications.展开更多
[Objective]In response to the issue of insufficient integrity in hourly routine meteorological element data files,this paper aims to improve the availability and reliability of data files,and provide high-quality data...[Objective]In response to the issue of insufficient integrity in hourly routine meteorological element data files,this paper aims to improve the availability and reliability of data files,and provide high-quality data file support for meteorological forecasting and services.[Method]In this paper,an efficient and accurate method for data file quality control and fusion processing is developed.By locating the missing measurement time,data are extracted from the"AWZ.db"database and the minute routine meteorological element data file,and merged into the hourly routine meteorological element data file.[Result]Data processing efficiency and accuracy are significantly improved,and the problem of incomplete hourly routine meteorological element data files is solved.At the same time,it emphasizes the importance of ensuring the accuracy of the files used and carefully checking and verifying the fusion results,and proposes strategies to improve data quality.[Conclusion]This method provides convenience for observation personnel and effectively improves the integrity and accuracy of data files.In the future,it is expected to provide more reliable data support for meteorological forecasting and services.展开更多
Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control ...Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control preconstruction duration and manage time variances can lead to financial insecurities,incomplete contract documents,permitting issues,and unrealistic schedules and resource allocation during this phase.To minimize time variances and ensure a productive decision-making process,project owners should be familiar with critical elements in a project that cause variances in the preconstruction phase timeline.In this study,the impacts of eleven critical preconstruction elements on time variances were analyzed.These eleven preconstruction elements are considered critical in how they impact time variances during the preconstruction phase.They were determined to be critical based either on significantly impacting time variance during the preconstruction phase or believed to be critical from findings from previous studies,however,the findings from this study showed no significant impact on the time variances.In most previous studies focusing on the elements impacting project schedules,data were collected by surveying construction professionals.In this study,objective and quantitative data related to project preconstruction elements were used as opposed to self-reported data.Using the results of this study,project owners and stakeholders will be able to evaluate the critical preconstruction elements impacting the timing of their projects and prioritize decisions related to the critical elements early on during the preconstruction phase.展开更多
Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements ...Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements of statistical methods due to the closure effect.In this study,we applied an integrated approach combining compositional data,multifractal,and multivariate statistical analyses to identify the nonlinear complexity of the spatial distributions of elemental concentrations in the Er’renshan ore field.Initially,the raw concentrations were transformed into log-ratios following the principles of composition data theory to alleviate the impact of the closure effect.Multifractal analysis was then conducted to characterise the nonlinear complexity of the concentration distributions.Furthermore,principal component analysis(PCA)and factor analysis(FA)were applied to identify spurious correlations and the potential factors controlling the distribution patterns.The results demonstrate that:a)the raw data are biased,while the log-ratio data are unbiased and more reliable;b)the spatial distributions of elemental concentrations exhibit nonlinear complexity;and c)the elemental distribution in the study area is largely controlled by structural factors.展开更多
Exploiting mobile elements （MEs） to accomplish data collection in wireless sensor networks （WSNs） can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large dat...Exploiting mobile elements （MEs） to accomplish data collection in wireless sensor networks （WSNs） can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large data collection latency for the network, which is unacceptable for data-critical applications. In this paper, we address this problem by minimizing the traveling length of MEs. Our methods mainly consist of two steps： we first construct a virtual grid network and select the minimal stop point set （SPS） from it; then, we make optimal scheduling for the MEs based on the SPS in order to minimize their traveling length. Different implementations of genetic algorithm （GA） are used to solve the problem. Our methods are evaluated by extensive simulations. The results show that these methods can greatly reduce the traveling length of MEs, and decrease the data collection latency.展开更多
The first plan on data elements since the listing of the National Bureau of Data of China has been released.On December 15th,2023,the National Bureau of Data of China drafted the Three-year Plan for“Data Elements X”...The first plan on data elements since the listing of the National Bureau of Data of China has been released.On December 15th,2023,the National Bureau of Data of China drafted the Three-year Plan for“Data Elements X”(2024-2026)(Exposure Draft),and solicited opinions from the public.展开更多
Concern for individual perception is essential to enhance greenspace management.Various landscape elements are key factors affecting visitors’perception engaging in greenspaces.Targeting Belgian public greenspaces,we...Concern for individual perception is essential to enhance greenspace management.Various landscape elements are key factors affecting visitors’perception engaging in greenspaces.Targeting Belgian public greenspaces,we develop a comprehensive approach to quantify visitors’perceptions from multiple dimensions.Applying user-generated data and unsupervised machine learning approach,we identified the landscape elements and classified the greenspaces to extract perception rates and detect dominant elements.The satisfaction of every landscape element was then analyzed by the natural language process approach and standardized major axis regression to discover their contributions to overall satisfaction.Furthermore,we calculated and visualized the positive and negative interactions between elements through network analysis.Integrating the perception rates and contributions,inconsistency was observed between the dominant element and the most contributing element.The perception rate of the human element was in an overwhelmingly dominant position,with 2.46.Despite the variations among the 5 greenspace groups,multiple natural elements highly contributed to overall satisfaction,especially animal and vegetation,which achieved contributions higher than 1.2 in most of the groups.Regarding the interactions,stronger negative interactions appeared generally,reaching up to 0.496.The coexistence of natural and artificial elements has a stronger collective effect on greenspace perception,regardless of positive or negative interaction.By providing an understanding of the landscape elements,our findings can assist greenspace planners in identifying key factors of different greenspace categories from various perspectives and support explicit and effective greenspace management.展开更多
To analyze the errors of processing data, the testing principle for jet elements is introduced and the property of testing system is theoretically and experimentally studied. On the basis of the above, the method of p...To analyze the errors of processing data, the testing principle for jet elements is introduced and the property of testing system is theoretically and experimentally studied. On the basis of the above, the method of processing data is presented and the error formulae, which are the functions of the testing system property, are derived. Finally, the methods of reducing the errors are provided. The measured results are in correspondence with the theoretical conclusion.展开更多
Flexible roll forming is a promising manufacturing method for the production of variable cross section products. Considering the large plastic strain in this forming process which is much larger than that of uniform d...Flexible roll forming is a promising manufacturing method for the production of variable cross section products. Considering the large plastic strain in this forming process which is much larger than that of uniform deformation phase of uniaxial tensile test, the widely adopted method of simulating the forming processes with non-supplemented material data from uniaxial tensile test will certainly lead to large error. To reduce this error, the material data is supplemented based on three constitutive models. Then a finite element model of a six passes flexible roll forming process is established based on the supplemented material data and the original material data from the uniaxial tensile test. The flexible roll forming experiment of a B pillar reinforcing plate is carried out to verify the proposed method. Final cross section shapes of the experimental and the simulated results are compared. It is shown that the simulation calculated with supplemented material data based on Swift model agrees well with the experimental results, while the simulation based on original material data could not predict the actual deformation accurately. The results indicate that this material supplement method is reliable and indispensible, and the simulation model can well reflect the real metal forming process. Detailed analysis of the distribution and history of plastic strain at different positions are performed. A new material data supplement method is proposed to tackle the problem which is ignored in other roll forming simulations, and thus the forming process simulation accuracy can be greatly improved.展开更多
In order to construct the data mining frame for the generic project risk research, the basic definitions of the generic project risk element were given, and then a new model of the generic project risk element was pre...In order to construct the data mining frame for the generic project risk research, the basic definitions of the generic project risk element were given, and then a new model of the generic project risk element was presented with the definitions. From the model, data mining method was used to acquire the risk transmission matrix from the historical databases analysis. The quantitative calculation problem among the generic project risk elements was solved. This method deals with well the risk element transmission problems with limited states. And in order to get the limited states, fuzzy theory was used to discrete the historical data in historical databases. In an example, the controlling risk degree is chosen as P(Rs≥2) ≤0.1, it means that the probability of risk state which is not less than 2 in project is not more than 0.1, the risk element R3 is chosen to control the project, respectively. The result shows that three risk element transmission matrix can be acquired in 4 risk elements, and the frequency histogram and cumulative frequency histogram of each risk element are also given.展开更多
An experience is presented using the finite element method （FEM） and data mining （DM） techniques to develop models that can be used to optimieze the skin-pass rolling process based on its operating conditions. A F...An experience is presented using the finite element method （FEM） and data mining （DM） techniques to develop models that can be used to optimieze the skin-pass rolling process based on its operating conditions. A FE model based on a real skin-pass process is built and validated. Based on this model, a group of FE models is simulated with different adjustment parameters and with different materials for the sheet; both variables are chosen from pre-set ranges, From all FE model simulations, a database is generated; this database is made up of the above mentioned adjustment parameters, sheet properties and the variables of the process arising from the simulation of the model. Various types of data mining algorithms are used to develop predictive models for each of the variables of the process.The best predictive models can be used to predict experimentally hard-to-measure variables （internal stresses, internal straine, etc.） which are useful in the optimal design of the process or to be applied in real time control systems of a skin-pass process in -plant.展开更多
For the regression model about longitudinal data, we combine the robust estimation equation with the elemental empirical likelihood method, and propose an efficient robust estimator, where the robust estimation equati...For the regression model about longitudinal data, we combine the robust estimation equation with the elemental empirical likelihood method, and propose an efficient robust estimator, where the robust estimation equation is based on bounded scoring function and the covariate depended weight function. This method reduces the influence of outliers in response variables and covariates on parameter estimation, takes into account the correlation between data, and improves the efficiency of estimation. The simulation results show that the proposed method is robust and efficient.展开更多
The concentrations of seven essential trace elements in 149 freshwater fish from eight fish species （European eel, bream, common carp, European catfish, roach, perch, pike and pikeperch） from five different French f...The concentrations of seven essential trace elements in 149 freshwater fish from eight fish species （European eel, bream, common carp, European catfish, roach, perch, pike and pikeperch） from five different French fishing areas from contaminated and control sites were measured by inductively coupled plasma mass spectrometry after microwave digestion under pressure. Differences in the concentration of elements in the muscles of these species were examined and the mean levels were compared for each species with previous French and European studies. The condition factor and the differences between the control and contaminated sites and between predatory and non-predatory groups, with respect to the concentration of these elements, were also studied.展开更多
基金supported by National Natural Science Foundation of China(Grants 72474022,71974011,72174022,71972012,71874009)"BIT think tank"Promotion Plan of Science and Technology Innovation Program of Beijing Institute of Technology(Grants 2024CX14017,2023CX13029).
文摘As a new type of production factor in healthcare,healthcare data elements have been rapidly integrated into various health production processes,such as clinical assistance,health management,biological testing,and operation and supervision[1,2].Healthcare data elements include biolog.ical and clinical data that are related to disease,environ-mental health data that are associated with life,and operational and healthcare management data that are related to healthcare activities(Figure 1).Activities such as the construction of a data value assessment system,the devel-opment of a data circulation and sharing platform,and the authorization of data compliance and operation products support the strong growth momentum of the market for health care data elements in China[3].
文摘The data production elements are driving profound transformations in the real economy across production objects,methods,and tools,generating significant economic effects such as industrial structure upgrading.This paper aims to reveal the impact mechanism of the data elements on the“three transformations”(high-end,intelligent,and green)in the manufacturing sector,theoretically elucidating the intrinsic mechanisms by which the data elements influence these transformations.The study finds that the data elements significantly enhance the high-end,intelligent,and green levels of China's manufacturing industry.In terms of the pathways of impact,the data elements primarily influence the development of high-tech industries and overall green technological innovation,thereby affecting the high-end,intelligent,and green transformation of the industry.
基金supported by the EU H2020 Research and Innovation Program under the Marie Sklodowska-Curie Grant Agreement(Project-DEEP,Grant No.101109045)the National Natural Science Foundation of China(No.NSFC 61925105 and 62171257)the Tsinghua University-China Mobile Communications Group Co.,Ltd.Joint Institute,and the Fundamental Research Funds for the Central Universities,China(No.FRF-NP-20-03).
文摘This paper explores the development of interpretable data elements from raw data using Kolmogorov-Arnold Networks(KAN).With the exponential growth of data in contemporary society,there is an urgent need for effective data processing methods to unlock the full potential of this resource.The study focuses on the application of KAN in the transportation sector to transform raw traffic data into meaningful data elements.The core of the research is the KANT-GCN model,which synergizes Kolmogorov-Arnold Networks with Temporal Graph Convolutional Networks(T-GCN).This innovative model demonstrates superior performance in predicting traffic speeds,outperforming existing methods in terms of accuracy,reliability,and interpretability.The model was evaluated using real-world datasets from Shenzhen,Los Angeles,and the San Francisco Bay Area,showing significant improvements in different metrics.The paper highlights the potential of KAN-T-GCN to revolutionize data-driven decision-making in traffic management and other sectors,underscoring its ability to handle dynamic updates and maintain data integrity.
文摘This article explores the characteristics of data resources from the perspective of production factors,analyzes the demand for trustworthy circulation technology,designs a fusion architecture and related solutions,including multi-party data intersection calculation,distributed machine learning,etc.It also compares performance differences,conducts formal verification,points out the value and limitations of architecture innovation,and looks forward to future opportunities.
文摘A multivariate statistical analysis was performed on multi-element soil geochemical data from the Koda Hill-Bulenga gold prospects in the Wa-Lawra gold belt, northwest Ghana. The objectives of the study were to define gold relationships with other trace elements to determine possible pathfinder elements for gold from the soil geochemical data. The study focused on seven elements, namely, Au, Fe, Pb, Mn, Ag, As and Cu. Factor analysis and hierarchical cluster analysis were performed on the analyzed samples. Factor analysis explained 79.093% of the total variance of the data through three factors. This had the gold factor being factor 3, having associations of copper, iron, lead and manganese and accounting for 20.903% of the total variance. From hierarchical clustering, gold was also observed to be clustering with lead, copper, arsenic and silver. There was further indication that, gold concentrations were lower than that of its associations. It can be inferred from the results that, the occurrence of gold and its associated elements can be linked to both primary dispersion from underlying rocks and secondary processes such as lateritization. This data shows that Fe and Mn strongly associated with gold, and alongside Pb, Ag, As and Cu, these elements can be used as pathfinders for gold in the area, with ferruginous zones as targets.
基金funding support from the Innovation Platform Open Fund Project of Hunan Provincial Universities (No. 13K076)National Key Discipline Open Fund Project of TCM diagnostics in Hunan University of Chinese Medicine (2015zyzd18)
文摘This report analyzes the existing problems in terminology referring to clinical symptoms of traditional Chinese medicine(TCM)from the viewpoint of data sharing and elaborates the necessity of establishing a standard directory of clinical data elements of TCM.We evaluated the principles and methods of data element extraction according to the status quo of the clinical information system and characteristics of symptoms for TCM and consequently proposed a three-layer model for optimal extraction.
基金the funding support from the National Natural Science Foundation of China(No.81373702)
文摘For digitalization of traditional Chinese medicine(TCM),research is being conducted on objectivization of diagnosis and treatment,mathematical models of TCM theories,and application of modern information technology to digitize the vast amounts of existing information.However,the author believes that TCM practitioners should first conduct a systematic and comprehensive refined analysis on the knowledge of TCM and unify data elements used in computer intelligence to avoid ambiguity.Thus,we must overcome the epistemological constraints and carefully analyze the relationship among data elements to achieve systematic results and administer TCM appropriately.
基金supported by the National Key Research and Development Plan in China(Grant No.2020YFB1005500)。
文摘With increasing demand for data circulation,ensuring data security and privacy is paramount,specifically protecting privacy while maximizing utility.Blockchain,while decentralized and transparent,faces challenges in privacy protection and data verification,especially for sensitive data.Existing schemes often suffer from inefficiency and high overhead.We propose a privacy protection scheme using BGV homomorphic encryption and Pedersen Secret Sharing.This scheme enables secure computation on encrypted data,with Pedersen sharding and verifying the private key,ensuring data consistency and immutability.The blockchain framework manages key shards,verifies secrets,and aids security auditing.This approach allows for trusted computation without revealing the underlying data.Preliminary results demonstrate the scheme's feasibility in ensuring data privacy and security,making data available but not visible.This study provides an effective solution for data sharing and privacy protection in blockchain applications.
基金the Fifth Batch of Innovation Teams of Wuzhou Meteorological Bureau"Wuzhou Innovation Team for Enhancing the Comprehensive Meteorological Observation Ability through Digitization and Intelligence"Wuzhou Science and Technology Planning Project(202402122,202402119).
文摘[Objective]In response to the issue of insufficient integrity in hourly routine meteorological element data files,this paper aims to improve the availability and reliability of data files,and provide high-quality data file support for meteorological forecasting and services.[Method]In this paper,an efficient and accurate method for data file quality control and fusion processing is developed.By locating the missing measurement time,data are extracted from the"AWZ.db"database and the minute routine meteorological element data file,and merged into the hourly routine meteorological element data file.[Result]Data processing efficiency and accuracy are significantly improved,and the problem of incomplete hourly routine meteorological element data files is solved.At the same time,it emphasizes the importance of ensuring the accuracy of the files used and carefully checking and verifying the fusion results,and proposes strategies to improve data quality.[Conclusion]This method provides convenience for observation personnel and effectively improves the integrity and accuracy of data files.In the future,it is expected to provide more reliable data support for meteorological forecasting and services.
文摘Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control preconstruction duration and manage time variances can lead to financial insecurities,incomplete contract documents,permitting issues,and unrealistic schedules and resource allocation during this phase.To minimize time variances and ensure a productive decision-making process,project owners should be familiar with critical elements in a project that cause variances in the preconstruction phase timeline.In this study,the impacts of eleven critical preconstruction elements on time variances were analyzed.These eleven preconstruction elements are considered critical in how they impact time variances during the preconstruction phase.They were determined to be critical based either on significantly impacting time variance during the preconstruction phase or believed to be critical from findings from previous studies,however,the findings from this study showed no significant impact on the time variances.In most previous studies focusing on the elements impacting project schedules,data were collected by surveying construction professionals.In this study,objective and quantitative data related to project preconstruction elements were used as opposed to self-reported data.Using the results of this study,project owners and stakeholders will be able to evaluate the critical preconstruction elements impacting the timing of their projects and prioritize decisions related to the critical elements early on during the preconstruction phase.
基金supported by the Doctoral Research Start-up Fund,East China University of Technology(DHBK2019313)the Open Research Fund Program of Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring(Central South University),the Ministry of Education(2020YSJS10)+1 种基金the Open Research Fund Program of Shandong Provincial Engineering Laboratory of Application and Development of Big Data for Deep Gold Exploration(SDK202224)the Basic Scientific Research Fund of the Institute of Geophysical and Geochemical Exploration,Chinese Academy of Geological Sciences(AS2022P03).
文摘Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements of statistical methods due to the closure effect.In this study,we applied an integrated approach combining compositional data,multifractal,and multivariate statistical analyses to identify the nonlinear complexity of the spatial distributions of elemental concentrations in the Er’renshan ore field.Initially,the raw concentrations were transformed into log-ratios following the principles of composition data theory to alleviate the impact of the closure effect.Multifractal analysis was then conducted to characterise the nonlinear complexity of the concentration distributions.Furthermore,principal component analysis(PCA)and factor analysis(FA)were applied to identify spurious correlations and the potential factors controlling the distribution patterns.The results demonstrate that:a)the raw data are biased,while the log-ratio data are unbiased and more reliable;b)the spatial distributions of elemental concentrations exhibit nonlinear complexity;and c)the elemental distribution in the study area is largely controlled by structural factors.
基金supported by Tianjin Municipal Information Industry Office (No. 082044012)
文摘Exploiting mobile elements （MEs） to accomplish data collection in wireless sensor networks （WSNs） can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large data collection latency for the network, which is unacceptable for data-critical applications. In this paper, we address this problem by minimizing the traveling length of MEs. Our methods mainly consist of two steps： we first construct a virtual grid network and select the minimal stop point set （SPS） from it; then, we make optimal scheduling for the MEs based on the SPS in order to minimize their traveling length. Different implementations of genetic algorithm （GA） are used to solve the problem. Our methods are evaluated by extensive simulations. The results show that these methods can greatly reduce the traveling length of MEs, and decrease the data collection latency.
文摘The first plan on data elements since the listing of the National Bureau of Data of China has been released.On December 15th,2023,the National Bureau of Data of China drafted the Three-year Plan for“Data Elements X”(2024-2026)(Exposure Draft),and solicited opinions from the public.
基金funded by the China Scholarship Council(grant number:202004910422)
文摘Concern for individual perception is essential to enhance greenspace management.Various landscape elements are key factors affecting visitors’perception engaging in greenspaces.Targeting Belgian public greenspaces,we develop a comprehensive approach to quantify visitors’perceptions from multiple dimensions.Applying user-generated data and unsupervised machine learning approach,we identified the landscape elements and classified the greenspaces to extract perception rates and detect dominant elements.The satisfaction of every landscape element was then analyzed by the natural language process approach and standardized major axis regression to discover their contributions to overall satisfaction.Furthermore,we calculated and visualized the positive and negative interactions between elements through network analysis.Integrating the perception rates and contributions,inconsistency was observed between the dominant element and the most contributing element.The perception rate of the human element was in an overwhelmingly dominant position,with 2.46.Despite the variations among the 5 greenspace groups,multiple natural elements highly contributed to overall satisfaction,especially animal and vegetation,which achieved contributions higher than 1.2 in most of the groups.Regarding the interactions,stronger negative interactions appeared generally,reaching up to 0.496.The coexistence of natural and artificial elements has a stronger collective effect on greenspace perception,regardless of positive or negative interaction.By providing an understanding of the landscape elements,our findings can assist greenspace planners in identifying key factors of different greenspace categories from various perspectives and support explicit and effective greenspace management.
文摘To analyze the errors of processing data, the testing principle for jet elements is introduced and the property of testing system is theoretically and experimentally studied. On the basis of the above, the method of processing data is presented and the error formulae, which are the functions of the testing system property, are derived. Finally, the methods of reducing the errors are provided. The measured results are in correspondence with the theoretical conclusion.
基金Supported by National Natural Science Foundation of China(Grant Nos.51205004,51475003)Beijing Municipal Natural Science Foundation of China(Grant No.3152010)Beijing Municipal Education Committee Science and Technology Program,China(Grant No.KM201510009004)
文摘Flexible roll forming is a promising manufacturing method for the production of variable cross section products. Considering the large plastic strain in this forming process which is much larger than that of uniform deformation phase of uniaxial tensile test, the widely adopted method of simulating the forming processes with non-supplemented material data from uniaxial tensile test will certainly lead to large error. To reduce this error, the material data is supplemented based on three constitutive models. Then a finite element model of a six passes flexible roll forming process is established based on the supplemented material data and the original material data from the uniaxial tensile test. The flexible roll forming experiment of a B pillar reinforcing plate is carried out to verify the proposed method. Final cross section shapes of the experimental and the simulated results are compared. It is shown that the simulation calculated with supplemented material data based on Swift model agrees well with the experimental results, while the simulation based on original material data could not predict the actual deformation accurately. The results indicate that this material supplement method is reliable and indispensible, and the simulation model can well reflect the real metal forming process. Detailed analysis of the distribution and history of plastic strain at different positions are performed. A new material data supplement method is proposed to tackle the problem which is ignored in other roll forming simulations, and thus the forming process simulation accuracy can be greatly improved.
基金Project(70572090) supported by the National Natural Science Foundation of China
文摘In order to construct the data mining frame for the generic project risk research, the basic definitions of the generic project risk element were given, and then a new model of the generic project risk element was presented with the definitions. From the model, data mining method was used to acquire the risk transmission matrix from the historical databases analysis. The quantitative calculation problem among the generic project risk elements was solved. This method deals with well the risk element transmission problems with limited states. And in order to get the limited states, fuzzy theory was used to discrete the historical data in historical databases. In an example, the controlling risk degree is chosen as P(Rs≥2) ≤0.1, it means that the probability of risk state which is not less than 2 in project is not more than 0.1, the risk element R3 is chosen to control the project, respectively. The result shows that three risk element transmission matrix can be acquired in 4 risk elements, and the frequency histogram and cumulative frequency histogram of each risk element are also given.
基金Item Sponsored by Spanish Ministry of Education and Science(DPI2007-61090)European Commission Research Programme of the Research Fund for Coal and Steel(RFS-PR-06035)
文摘An experience is presented using the finite element method （FEM） and data mining （DM） techniques to develop models that can be used to optimieze the skin-pass rolling process based on its operating conditions. A FE model based on a real skin-pass process is built and validated. Based on this model, a group of FE models is simulated with different adjustment parameters and with different materials for the sheet; both variables are chosen from pre-set ranges, From all FE model simulations, a database is generated; this database is made up of the above mentioned adjustment parameters, sheet properties and the variables of the process arising from the simulation of the model. Various types of data mining algorithms are used to develop predictive models for each of the variables of the process.The best predictive models can be used to predict experimentally hard-to-measure variables （internal stresses, internal straine, etc.） which are useful in the optimal design of the process or to be applied in real time control systems of a skin-pass process in -plant.
文摘For the regression model about longitudinal data, we combine the robust estimation equation with the elemental empirical likelihood method, and propose an efficient robust estimator, where the robust estimation equation is based on bounded scoring function and the covariate depended weight function. This method reduces the influence of outliers in response variables and covariates on parameter estimation, takes into account the correlation between data, and improves the efficiency of estimation. The simulation results show that the proposed method is robust and efficient.
文摘The concentrations of seven essential trace elements in 149 freshwater fish from eight fish species （European eel, bream, common carp, European catfish, roach, perch, pike and pikeperch） from five different French fishing areas from contaminated and control sites were measured by inductively coupled plasma mass spectrometry after microwave digestion under pressure. Differences in the concentration of elements in the muscles of these species were examined and the mean levels were compared for each species with previous French and European studies. The condition factor and the differences between the control and contaminated sites and between predatory and non-predatory groups, with respect to the concentration of these elements, were also studied.
