In order to provide a practicable solution to data confidentiality in cloud storage service,a data assured deletion scheme,which achieves the fine grained access control,hopping and sniffing attacks resistance,data dy...In order to provide a practicable solution to data confidentiality in cloud storage service,a data assured deletion scheme,which achieves the fine grained access control,hopping and sniffing attacks resistance,data dynamics and deduplication,is proposed.In our scheme,data blocks are encrypted by a two-level encryption approach,in which the control keys are generated from a key derivation tree,encrypted by an All-OrNothing algorithm and then distributed into DHT network after being partitioned by secret sharing.This guarantees that only authorized users can recover the control keys and then decrypt the outsourced data in an ownerspecified data lifetime.Besides confidentiality,data dynamics and deduplication are also achieved separately by adjustment of key derivation tree and convergent encryption.The analysis and experimental results show that our scheme can satisfy its security goal and perform the assured deletion with low cost.展开更多
A number of proposals have been suggested to tackle data integrity and privacy concerns in cloud storage in which some existing schemes suffer from vulnerabilities in data dynamics. In this paper, we propose an improv...A number of proposals have been suggested to tackle data integrity and privacy concerns in cloud storage in which some existing schemes suffer from vulnerabilities in data dynamics. In this paper, we propose an improved fairness and dynamic provable data possession scheme that supports public verification and batch auditing while preserves data privacy. The rb23Tree is utilized to facilitate data dynamics. Moreover, the fairness is considered to prevent a dishonest user from accusing the cloud service provider of manipulating the data. The scheme allows a third party auditor （TPA） to verify the data integrity without learning any information about the data content during the auditing process. Furthermore, our scheme also allows batch auditing, which greatly accelerates the auditing process when there are multiple auditing requests. Security analysis and extensive experimental evaluations show that our scheme is secure and efficient.展开更多
To check the remote data integrity in cloud computing,we have proposed an efficient and full data dynamic provable data possession（PDP） scheme that uses a SN（serial number）-BN（block number） table to support data...To check the remote data integrity in cloud computing,we have proposed an efficient and full data dynamic provable data possession（PDP） scheme that uses a SN（serial number）-BN（block number） table to support data block update.In this article,we first analyze and test its performance in detail.The result shows that our scheme is efficient with low computation,storage,and communication costs.Then,we discuss how to extend the dynamic scheme to support other features,including public auditability,privacy preservation,fairness,and multiple-replica checking.After being extended,a comprehensive PDP scheme that has high efficiency and satisfies all main requirements is provided.展开更多
Dynamic data driven simulation （DDDS） is proposed to improve the model by incorporaing real data from the practical systems into the model. Instead of giving a static input, multiple possible sets of inputs are fed ...Dynamic data driven simulation （DDDS） is proposed to improve the model by incorporaing real data from the practical systems into the model. Instead of giving a static input, multiple possible sets of inputs are fed into the model. And the computational errors are corrected using statistical approaches. It involves a variety of aspects, including the uncertainty modeling, the measurement evaluation, the system model and the measurement model coupling ,the computation complexity, and the performance issue. Authors intend to set up the architecture of DDDS for wildfire spread model, DEVS-FIRE, based on the discrete event speeification （DEVS） formalism. The experimental results show that the framework can track the dynamically changing fire front based on fire sen- sor data, thus, it provides more aecurate predictions.展开更多
Outlier in one variable will smear the estimation of other measurements in data reconciliation （DR）. In this article, a novel robust method is proposed for nonlinear dynamic data reconciliation, to reduce the influe...Outlier in one variable will smear the estimation of other measurements in data reconciliation （DR）. In this article, a novel robust method is proposed for nonlinear dynamic data reconciliation, to reduce the influence of outliers on the result of DR. This method introduces a penalty function matrix in a conventional least-square objective function, to assign small weights for outliers and large weights for normal measurements. To avoid the loss of data information, element-wise Mahalanobis distance is proposed, as an improvement on vector-wise distance, to construct a penalty function matrix. The correlation of measurement error is also considered in this article. The method introduces the robust statistical theory into conventional least square estimator by constructing the penalty weight matrix and gets not only good robustness but also simple calculation. Simulation of a continuous stirred tank reactor, verifies the effectiveness of the proposed algorithm.展开更多
Health monitoring data or the data about infectious diseases such as COVID-19 may need to be constantly updated and dynamically released,but they may contain user's sensitive information.Thus,how to preserve the u...Health monitoring data or the data about infectious diseases such as COVID-19 may need to be constantly updated and dynamically released,but they may contain user's sensitive information.Thus,how to preserve the user's privacy before their release is critically important yet challenging.Differential Privacy(DP)is well-known to provide effective privacy protection,and thus the dynamic DP preserving data release was designed to publish a histogram to meet DP guarantee.Unfortunately,this scheme may result in high cumulative errors and lower the data availability.To address this problem,in this paper,we apply Jensen-Shannon(JS)divergence to design the OPTICS(Ordering Points To Identify The Clustering Structure)scheme.It uses JS divergence to measure the difference between the updated data set at the current release time and private data set at the previous release time.By comparing the difference with a threshold,only when the difference is greater than the threshold,can we apply OPTICS to publish DP protected data sets.Our experimental results show that the absolute errors and average relative errors are significantly lower than those existing works.展开更多
Due to the development of 5G communication,many aspects of information technology(IT)services are changing.With the development of communication technologies such as 5G,it has become possible to provide IT services th...Due to the development of 5G communication,many aspects of information technology(IT)services are changing.With the development of communication technologies such as 5G,it has become possible to provide IT services that were difficult to provide in the past.One of the services made possible through this change is cloud-based collaboration.In order to support secure collaboration over cloud,encryption technology to securely manage dynamic data is essential.However,since the existing encryption technology is not suitable for encryption of dynamic data,a new technology that can provide encryption for dynamic data is required for secure cloudbased collaboration.In this paper,we propose a new encryption technology to support secure collaboration for dynamic data in the cloud.Specifically,we propose an encryption operation mode which can support data updates such as modification,addition,and deletion of encrypted data in an encrypted state.To support the dynamic update of encrypted data,we invent a new mode of operation technique named linked-block cipher(LBC).Basic idea of our work is to use an updatable random value so-called link to link two encrypted blocks.Due to the use of updatable random link values,we can modify,insert,and delete an encrypted data without decrypt it.展开更多
The experimental random error and desired valuse of non observed points in dynamic indexes were estimated by establishing the linear regression equations about variety regulations of dynamic indexes.The methods for d...The experimental random error and desired valuse of non observed points in dynamic indexes were estimated by establishing the linear regression equations about variety regulations of dynamic indexes.The methods for difference significant test among different treatments using dynamic point as indexes were presented without setting the replication on each dynamic point observed.展开更多
Nowadays, an increasing number of persons choose to outsource their computing demands and storage demands to the Cloud. In order to ensure the integrity of the data in the untrusted Cloud, especially the dynamic files...Nowadays, an increasing number of persons choose to outsource their computing demands and storage demands to the Cloud. In order to ensure the integrity of the data in the untrusted Cloud, especially the dynamic files which can be updated online, we propose an improved dynamic provable data possession model. We use some homomorphic tags to verify the integrity of the file and use some hash values generated by some secret values and tags to prevent replay attack and forgery attack. Compared with previous works, our proposal reduces the computational and communication complexity from O(logn) to O(1). We did some experiments to ensure this improvement and extended the model to file sharing situation.展开更多
Related factors for measuring urban agglomeration effect were studied firstly.Then,panel data of 283 prefecture level cities of China were collected to analyze the effect of agglomeration on employment density.Besides...Related factors for measuring urban agglomeration effect were studied firstly.Then,panel data of 283 prefecture level cities of China were collected to analyze the effect of agglomeration on employment density.Besides,fixed effect model was applied to analyze static panel data,and two-step generalized method of moments(GMM) estimator was employed to analyze dynamic panel data.Results reveal that per capita regional GDP,public medical care level,and population mobility have significant effect on employment density.Therefore,there exists effect of agglomeration economy in prefecture level cities of China in the current stage.展开更多
This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynami...This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections;secondly,with the proposed MBDLM,the dynamic correlation coefficients between any two performance functions can be predicted;finally,based on MBDLM and Gaussian copula technique,a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder,and the monitoring extreme deflection data from an actual bridge is provided to illustrated the feasibility and application of the proposed method.展开更多
Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol ...Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).展开更多
Dynamic flood disaster simulation is an emerging and promising technology significantly useful in urban planning,risk assessment,and integrated decision support systems.It is still an important issue to integrate the ...Dynamic flood disaster simulation is an emerging and promising technology significantly useful in urban planning,risk assessment,and integrated decision support systems.It is still an important issue to integrate the large assets such as dynamic observational data,numerical flood simulation models,geographic information technologies,and computing resources into a unified framework.For the intended end user,it is also a holistic solution to create computer interpretable representations and gain insightful understanding of the dynamic disaster processes,the complex impacts,and interactions of disaster factors.In particular,it is still difficult to access and join harmonized data,processing algorithms,and models that are provided by different environmental information infrastructures.In this paper,we demonstrate a virtual geographic environments-based integrated environmental simulation framework for flood disaster management based on the notion of interlinked resources,which is capable of automated accumulating and manipulating of sensor data,creating dynamic geo-analysis and three-dimensional visualizations of ongoing geo-process,and updating the contents of simulation models representing the real environment.The prototype system is evaluated by applying it as a proof of concept to integrate in situ weather observations,numerical weather and flood disaster simulation models,visualization,and analysis of the real time flood event.Case applications indicate that the developed framework can be adopted for use by decision-makers for short-term planning and control since the resulting simulation and visualization are completely based on the latest status of environment.展开更多
Although China’s urban floating population is mainly concentrated in developed cities,from the central and western cities to the eastern developed cities,but the characteristics of the floating population in differen...Although China’s urban floating population is mainly concentrated in developed cities,from the central and western cities to the eastern developed cities,but the characteristics of the floating population in different cities are significantly different.This paper systematically investigates the spatiotemporal characteristics and influencing factors of the floating population in different levels of cities.The results show that the regional imbalance to further strengthen,accumulation and dispersion trend has become increasingly obvious,liquidity is positively correlated and city level scale,and urban agglomeration and the core city is still polarization center of floating population.Flow range is closely related to urban hierarchy:the higher the intra-urban grade,the more tend to inter-provincial flow;the lower the city grade,the more tend to intra-urban mobility.Short-term(1-2 years)and long-term(more than 7 years)flow-time coexist.The short-term liquidity increases with the city grade,and the long-term liquidity decreases with the city level.Farmers are still the main body of the floating population.Younger age,lower education level,low-skilled,high gender ratio employees are the most basic demographic characteristics of the floating population,although there are differences between different cities.The main reason for affecting the floating population is seeking jobs and doing business.展开更多
Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon e...Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.展开更多
The aim of this paper is to provide a clear insight about the determinants of female employment rate in the European Union where we have used panel data analyses of 27 countries members of the European Union from 1995...The aim of this paper is to provide a clear insight about the determinants of female employment rate in the European Union where we have used panel data analyses of 27 countries members of the European Union from 1995 till 2009. Applying dynamic modeling, i.e, generalized method of moments （GMM） econometrics findings have driven us to system estimated model where the following institutional variables have been tested： maternity leave, child care facilities, college education, fertility rate, GDP growth, female unemployment rate and part-time employment. We expect these variables to have a positive impact on the female employment rate except for the female unemployment rate and maternity leave展开更多
The fast-growing demand of computational fluid dynamics（CFD） application for computing resources stimulates the development of high performance computing（HPC） and meanwhile raises new requirements for the technolo...The fast-growing demand of computational fluid dynamics（CFD） application for computing resources stimulates the development of high performance computing（HPC） and meanwhile raises new requirements for the technology of parallel application performance monitor and analysis.In response to large-scale and long-time running for the application of CFD,online and scalable performance analysis technology is required to optimize the parallel programs as well as to improve their operational efficiency.As a result,this research implements a scalable infrastructure for online performance analysis on CFD application with homogeneous or heterogeneous system.The infrastructure is part of the parallel application performance monitor and analysis system（PAPMAS） and is composed of two modules which are scalable data transmission module and data storage module.The paper analyzes and elaborates this infrastructure in detail with respect to its design and implementation.Furthermore,some experiments are carried out to verify the rationality and high efficiency of this infrastructure that could be adopted to meet the practical needs.展开更多
A physical-based particle system is employed for cloth modeling supported by two basic algorithms, between which one is the construction of the internal and external forces acting on the particle system in terms of KE...A physical-based particle system is employed for cloth modeling supported by two basic algorithms, between which one is the construction of the internal and external forces acting on the particle system in terms of KES-F bending and shearing tests, and the other is the collision algorithm of which the collision detection is carried by means of bi-section of time step and the collision response is handled according to the empirical law for frictionless collision With these algorithms. the geometric state of parcles can be expressed as ordinary differential equationswhich is numerically solved by fourth order Runge- Kutta integration. Different draping figures of cotton fabric and wool fabric prove that such a particle system is suitable for 3D cloth modeling and simulation.展开更多
The Ordovician fracture-vug carbonate reservoirs of Tarim Basin,are featured by developed vugs,caves and fractures.The strong heterogeneity results in huge uncertainty when these reservoirs are quantitatively characte...The Ordovician fracture-vug carbonate reservoirs of Tarim Basin,are featured by developed vugs,caves and fractures.The strong heterogeneity results in huge uncertainty when these reservoirs are quantitatively characterized using merely static seismic data.The effective quantitative characterization of the reservoirs has been an urgent problem to be solved.This study creatively proposes the"second quantitative characterization"technique with the combination of dynamic and static data based on the primary static quantitative characterization and fully considering lots of key influence factors when conducting characterization.In this technique,dynamic analysis methods such as well testing,production rate transient analysis,dynamic reserve evaluation and dynamic connectivity evaluation are used to get understandings on this kind of reservoir.These understandings are used as statistical parameters to constrain the inversion of seismic wave impedance to improve the relationship between wave impedance and porosity and determine the fracture-vug morphology,calculate dynamic reserves,and then a more accurate fracture-vugmodel can be selected and used to calculate the oil-water contact inversely based on the results of"second quantitative characterization".This method can lower the uncertainties in the primary quantitative characterization of fracture-vug reservoirs,enhance the accuracy of characterization results significantly,and has achieved good application results in the fracture-vug carbonate reservoirs of Tarim Basin.展开更多
The user control over the life cycle of data is of an extreme importance in clouds in order to determine whether the service provider adheres to the client’s pre-specified needs in the contract between them or n...The user control over the life cycle of data is of an extreme importance in clouds in order to determine whether the service provider adheres to the client’s pre-specified needs in the contract between them or not, significant clients concerns raise on some aspects like social, location and the laws to which the data are subject to. The problem is even magnified more with the lack of transparency by Cloud Service Providers (CSPs). Auditing and compliance enforcement introduce different set of challenges in cloud computing that are not yet resolved. In this paper, a conducted questionnaire showed that the data owners have real concerns about not just the secrecy and integrity of their data in cloud environment, but also for spatial, temporal, and legal issues related to their data especially for sensitive or personal data. The questionnaire results show the importance for the data owners to address mainly three major issues: Their ability to continue the work, the secrecy and integrity of their data, and the spatial, legal, temporal constraints related to their data. Although a good volume of work was dedicated for auditing in the literature, only little work was dedicated to the fulfillment of the contractual obligations of the CSPs. The paper contributes to knowledge by proposing an extension to the auditing models to include the fulfillment of contractual obligations aspects beside the important aspects of secrecy and integrity of client’s data.展开更多
基金supported by the National Key Basic Research Program of China(973 program) under Grant No.2012CB315901
文摘In order to provide a practicable solution to data confidentiality in cloud storage service,a data assured deletion scheme,which achieves the fine grained access control,hopping and sniffing attacks resistance,data dynamics and deduplication,is proposed.In our scheme,data blocks are encrypted by a two-level encryption approach,in which the control keys are generated from a key derivation tree,encrypted by an All-OrNothing algorithm and then distributed into DHT network after being partitioned by secret sharing.This guarantees that only authorized users can recover the control keys and then decrypt the outsourced data in an ownerspecified data lifetime.Besides confidentiality,data dynamics and deduplication are also achieved separately by adjustment of key derivation tree and convergent encryption.The analysis and experimental results show that our scheme can satisfy its security goal and perform the assured deletion with low cost.
基金Supported by the Doctoral Fund of the Ministry of Education priority Areas of Development Projects(20110141130006)the Natural Science Foundation of Hubei Province(ZRZ0041)
文摘A number of proposals have been suggested to tackle data integrity and privacy concerns in cloud storage in which some existing schemes suffer from vulnerabilities in data dynamics. In this paper, we propose an improved fairness and dynamic provable data possession scheme that supports public verification and batch auditing while preserves data privacy. The rb23Tree is utilized to facilitate data dynamics. Moreover, the fairness is considered to prevent a dishonest user from accusing the cloud service provider of manipulating the data. The scheme allows a third party auditor （TPA） to verify the data integrity without learning any information about the data content during the auditing process. Furthermore, our scheme also allows batch auditing, which greatly accelerates the auditing process when there are multiple auditing requests. Security analysis and extensive experimental evaluations show that our scheme is secure and efficient.
基金Supported by the National Basic"863"Research Program of China(2012CB315901)
文摘To check the remote data integrity in cloud computing,we have proposed an efficient and full data dynamic provable data possession（PDP） scheme that uses a SN（serial number）-BN（block number） table to support data block update.In this article,we first analyze and test its performance in detail.The result shows that our scheme is efficient with low computation,storage,and communication costs.Then,we discuss how to extend the dynamic scheme to support other features,including public auditability,privacy preservation,fairness,and multiple-replica checking.After being extended,a comprehensive PDP scheme that has high efficiency and satisfies all main requirements is provided.
文摘Dynamic data driven simulation （DDDS） is proposed to improve the model by incorporaing real data from the practical systems into the model. Instead of giving a static input, multiple possible sets of inputs are fed into the model. And the computational errors are corrected using statistical approaches. It involves a variety of aspects, including the uncertainty modeling, the measurement evaluation, the system model and the measurement model coupling ,the computation complexity, and the performance issue. Authors intend to set up the architecture of DDDS for wildfire spread model, DEVS-FIRE, based on the discrete event speeification （DEVS） formalism. The experimental results show that the framework can track the dynamically changing fire front based on fire sen- sor data, thus, it provides more aecurate predictions.
基金Supported by the National Natural Science Foundation of China （No.60504033）
文摘Outlier in one variable will smear the estimation of other measurements in data reconciliation （DR）. In this article, a novel robust method is proposed for nonlinear dynamic data reconciliation, to reduce the influence of outliers on the result of DR. This method introduces a penalty function matrix in a conventional least-square objective function, to assign small weights for outliers and large weights for normal measurements. To avoid the loss of data information, element-wise Mahalanobis distance is proposed, as an improvement on vector-wise distance, to construct a penalty function matrix. The correlation of measurement error is also considered in this article. The method introduces the robust statistical theory into conventional least square estimator by constructing the penalty weight matrix and gets not only good robustness but also simple calculation. Simulation of a continuous stirred tank reactor, verifies the effectiveness of the proposed algorithm.
基金supported in part by National Natural Science Foundation of China(No.61672106)in part by Natural Science Foundation of Beijing,China(L192023)in part by the project of promoting the Classified Development of Beijing Information Science and Technology University(No.5112211038,5112211039)。
文摘Health monitoring data or the data about infectious diseases such as COVID-19 may need to be constantly updated and dynamically released,but they may contain user's sensitive information.Thus,how to preserve the user's privacy before their release is critically important yet challenging.Differential Privacy(DP)is well-known to provide effective privacy protection,and thus the dynamic DP preserving data release was designed to publish a histogram to meet DP guarantee.Unfortunately,this scheme may result in high cumulative errors and lower the data availability.To address this problem,in this paper,we apply Jensen-Shannon(JS)divergence to design the OPTICS(Ordering Points To Identify The Clustering Structure)scheme.It uses JS divergence to measure the difference between the updated data set at the current release time and private data set at the previous release time.By comparing the difference with a threshold,only when the difference is greater than the threshold,can we apply OPTICS to publish DP protected data sets.Our experimental results show that the absolute errors and average relative errors are significantly lower than those existing works.
基金This work was partly supported by Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2021-0-00779Development of high-speed encryption data processing technology that guarantees privacy based hardware,50%)National R&D Program through the National Research Foundation of Korea(NRF)funded by Ministry of Science and ICT(NRF-2021R1F1A1056115,50%).
文摘Due to the development of 5G communication,many aspects of information technology(IT)services are changing.With the development of communication technologies such as 5G,it has become possible to provide IT services that were difficult to provide in the past.One of the services made possible through this change is cloud-based collaboration.In order to support secure collaboration over cloud,encryption technology to securely manage dynamic data is essential.However,since the existing encryption technology is not suitable for encryption of dynamic data,a new technology that can provide encryption for dynamic data is required for secure cloudbased collaboration.In this paper,we propose a new encryption technology to support secure collaboration for dynamic data in the cloud.Specifically,we propose an encryption operation mode which can support data updates such as modification,addition,and deletion of encrypted data in an encrypted state.To support the dynamic update of encrypted data,we invent a new mode of operation technique named linked-block cipher(LBC).Basic idea of our work is to use an updatable random value so-called link to link two encrypted blocks.Due to the use of updatable random link values,we can modify,insert,and delete an encrypted data without decrypt it.
文摘The experimental random error and desired valuse of non observed points in dynamic indexes were estimated by establishing the linear regression equations about variety regulations of dynamic indexes.The methods for difference significant test among different treatments using dynamic point as indexes were presented without setting the replication on each dynamic point observed.
基金supported by Major Program of Shanghai Science and Technology Commission under Grant No.10DZ1500200Collaborative Applied Research and Development Project between Morgan Stanley and Shanghai Jiao Tong University, China
文摘Nowadays, an increasing number of persons choose to outsource their computing demands and storage demands to the Cloud. In order to ensure the integrity of the data in the untrusted Cloud, especially the dynamic files which can be updated online, we propose an improved dynamic provable data possession model. We use some homomorphic tags to verify the integrity of the file and use some hash values generated by some secret values and tags to prevent replay attack and forgery attack. Compared with previous works, our proposal reduces the computational and communication complexity from O(logn) to O(1). We did some experiments to ensure this improvement and extended the model to file sharing situation.
基金Supported by Key Project of National Social Science Foundation(12&ZD100)Fundamental Research Funds for the Central Universities of Southwest University(SWU1309005)
文摘Related factors for measuring urban agglomeration effect were studied firstly.Then,panel data of 283 prefecture level cities of China were collected to analyze the effect of agglomeration on employment density.Besides,fixed effect model was applied to analyze static panel data,and two-step generalized method of moments(GMM) estimator was employed to analyze dynamic panel data.Results reveal that per capita regional GDP,public medical care level,and population mobility have significant effect on employment density.Therefore,there exists effect of agglomeration economy in prefecture level cities of China in the current stage.
基金This work was supported by Natural Science Foundation of Gansu Province of China(20JR10RA625,20JR10RA623)National Key Research and Development Project of China(Project No.2019YFC1511005)+1 种基金Fundamental Research Funds for the Central Universities(Grant No.lzujbky-2020-55)National Natural Science Foundation of China(Grant No.51608243).
文摘This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections;secondly,with the proposed MBDLM,the dynamic correlation coefficients between any two performance functions can be predicted;finally,based on MBDLM and Gaussian copula technique,a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder,and the monitoring extreme deflection data from an actual bridge is provided to illustrated the feasibility and application of the proposed method.
基金supported by the National Nature Science Foundation of China(U21A20166)the Science and Technology Development Foundation of Jilin Province(20230508095RC)+2 种基金the Major Science and Technology Projects of Jilin Province and Changchun City(20220301033GX)the Development and Reform Commission Foundation of Jilin Province(2023C034-3)the Interdisciplinary Integration and Innovation Project of JLU(JLUXKJC2020202).
文摘Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).
基金This study is supported by the National High Technology Research and Development Program of China(863 Program)(Nos.2012AA121305 and 2013AA120701)the National Natural Science Foundation of China(Nos.41471320 and 41201440).
文摘Dynamic flood disaster simulation is an emerging and promising technology significantly useful in urban planning,risk assessment,and integrated decision support systems.It is still an important issue to integrate the large assets such as dynamic observational data,numerical flood simulation models,geographic information technologies,and computing resources into a unified framework.For the intended end user,it is also a holistic solution to create computer interpretable representations and gain insightful understanding of the dynamic disaster processes,the complex impacts,and interactions of disaster factors.In particular,it is still difficult to access and join harmonized data,processing algorithms,and models that are provided by different environmental information infrastructures.In this paper,we demonstrate a virtual geographic environments-based integrated environmental simulation framework for flood disaster management based on the notion of interlinked resources,which is capable of automated accumulating and manipulating of sensor data,creating dynamic geo-analysis and three-dimensional visualizations of ongoing geo-process,and updating the contents of simulation models representing the real environment.The prototype system is evaluated by applying it as a proof of concept to integrate in situ weather observations,numerical weather and flood disaster simulation models,visualization,and analysis of the real time flood event.Case applications indicate that the developed framework can be adopted for use by decision-makers for short-term planning and control since the resulting simulation and visualization are completely based on the latest status of environment.
文摘Although China’s urban floating population is mainly concentrated in developed cities,from the central and western cities to the eastern developed cities,but the characteristics of the floating population in different cities are significantly different.This paper systematically investigates the spatiotemporal characteristics and influencing factors of the floating population in different levels of cities.The results show that the regional imbalance to further strengthen,accumulation and dispersion trend has become increasingly obvious,liquidity is positively correlated and city level scale,and urban agglomeration and the core city is still polarization center of floating population.Flow range is closely related to urban hierarchy:the higher the intra-urban grade,the more tend to inter-provincial flow;the lower the city grade,the more tend to intra-urban mobility.Short-term(1-2 years)and long-term(more than 7 years)flow-time coexist.The short-term liquidity increases with the city grade,and the long-term liquidity decreases with the city level.Farmers are still the main body of the floating population.Younger age,lower education level,low-skilled,high gender ratio employees are the most basic demographic characteristics of the floating population,although there are differences between different cities.The main reason for affecting the floating population is seeking jobs and doing business.
基金National Natural Science Foundation of China,No.41601151Guangdong Natural Science Foundation,No.2016A030310149
文摘Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.
文摘The aim of this paper is to provide a clear insight about the determinants of female employment rate in the European Union where we have used panel data analyses of 27 countries members of the European Union from 1995 till 2009. Applying dynamic modeling, i.e, generalized method of moments （GMM） econometrics findings have driven us to system estimated model where the following institutional variables have been tested： maternity leave, child care facilities, college education, fertility rate, GDP growth, female unemployment rate and part-time employment. We expect these variables to have a positive impact on the female employment rate except for the female unemployment rate and maternity leave
基金Aeronautical Science Foundation of China(2010ZA04001)National Natural Science Foundation of China (61073013,90818024)
文摘The fast-growing demand of computational fluid dynamics（CFD） application for computing resources stimulates the development of high performance computing（HPC） and meanwhile raises new requirements for the technology of parallel application performance monitor and analysis.In response to large-scale and long-time running for the application of CFD,online and scalable performance analysis technology is required to optimize the parallel programs as well as to improve their operational efficiency.As a result,this research implements a scalable infrastructure for online performance analysis on CFD application with homogeneous or heterogeneous system.The infrastructure is part of the parallel application performance monitor and analysis system（PAPMAS） and is composed of two modules which are scalable data transmission module and data storage module.The paper analyzes and elaborates this infrastructure in detail with respect to its design and implementation.Furthermore,some experiments are carried out to verify the rationality and high efficiency of this infrastructure that could be adopted to meet the practical needs.
文摘A physical-based particle system is employed for cloth modeling supported by two basic algorithms, between which one is the construction of the internal and external forces acting on the particle system in terms of KES-F bending and shearing tests, and the other is the collision algorithm of which the collision detection is carried by means of bi-section of time step and the collision response is handled according to the empirical law for frictionless collision With these algorithms. the geometric state of parcles can be expressed as ordinary differential equationswhich is numerically solved by fourth order Runge- Kutta integration. Different draping figures of cotton fabric and wool fabric prove that such a particle system is suitable for 3D cloth modeling and simulation.
基金Supported by the General Program of Natural Science Foundation of China(51874346).
文摘The Ordovician fracture-vug carbonate reservoirs of Tarim Basin,are featured by developed vugs,caves and fractures.The strong heterogeneity results in huge uncertainty when these reservoirs are quantitatively characterized using merely static seismic data.The effective quantitative characterization of the reservoirs has been an urgent problem to be solved.This study creatively proposes the"second quantitative characterization"technique with the combination of dynamic and static data based on the primary static quantitative characterization and fully considering lots of key influence factors when conducting characterization.In this technique,dynamic analysis methods such as well testing,production rate transient analysis,dynamic reserve evaluation and dynamic connectivity evaluation are used to get understandings on this kind of reservoir.These understandings are used as statistical parameters to constrain the inversion of seismic wave impedance to improve the relationship between wave impedance and porosity and determine the fracture-vug morphology,calculate dynamic reserves,and then a more accurate fracture-vugmodel can be selected and used to calculate the oil-water contact inversely based on the results of"second quantitative characterization".This method can lower the uncertainties in the primary quantitative characterization of fracture-vug reservoirs,enhance the accuracy of characterization results significantly,and has achieved good application results in the fracture-vug carbonate reservoirs of Tarim Basin.
文摘The user control over the life cycle of data is of an extreme importance in clouds in order to determine whether the service provider adheres to the client’s pre-specified needs in the contract between them or not, significant clients concerns raise on some aspects like social, location and the laws to which the data are subject to. The problem is even magnified more with the lack of transparency by Cloud Service Providers (CSPs). Auditing and compliance enforcement introduce different set of challenges in cloud computing that are not yet resolved. In this paper, a conducted questionnaire showed that the data owners have real concerns about not just the secrecy and integrity of their data in cloud environment, but also for spatial, temporal, and legal issues related to their data especially for sensitive or personal data. The questionnaire results show the importance for the data owners to address mainly three major issues: Their ability to continue the work, the secrecy and integrity of their data, and the spatial, legal, temporal constraints related to their data. Although a good volume of work was dedicated for auditing in the literature, only little work was dedicated to the fulfillment of the contractual obligations of the CSPs. The paper contributes to knowledge by proposing an extension to the auditing models to include the fulfillment of contractual obligations aspects beside the important aspects of secrecy and integrity of client’s data.
