On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on ...On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.The forum was organised by the China Writers Association and co-organised by China National Publications Import&Export(Group)Corporation.展开更多
Cervical cancer,a leading malignancy globally,poses a significant threat to women's health,with an estimated 604,000 new cases and 342,000 deaths reported in 2020^([1]).As cervical cancer is closely linked to huma...Cervical cancer,a leading malignancy globally,poses a significant threat to women's health,with an estimated 604,000 new cases and 342,000 deaths reported in 2020^([1]).As cervical cancer is closely linked to human papilloma virus(HPV)infection,early detection relies on HPV screening;however,late-stage prognosis remains poor,underscoring the need for novel diagnostic and therapeutic targets^([2]).展开更多
The existence and uniqueness of the global smooth solution to the initial-boundary valueproblem of a system of multi-dimensions SRWE are proved. The sufficient conditions of 'blowingup' of the solution are given.
Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility...Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility that considers multi-dimensional performance limit state parameters and makes a first attempt to develop fragility curves for a multi-span continuous (MSC) concrete girder bridge considering two performance limit state parameters: column ductility and transverse deformation in the abutments. The main purpose of this paper is to show that the performance limit states, which are compared with the seismic response parameters in the calculation of fragility, should be properly modeled as randomly interdependent variables instead of deterministic quantities. The sensitivity of fragility curves is also investigated when the dependency between the limit states is different. The results indicate that the proposed method can be used to describe the vulnerable behavior of bridges which are sensitive to multiple response parameters and that the fragility information generated by this method will be more reliable and likely to be implemented into transportation network loss estimation.展开更多
Heavy oil is a complicated mixture and a potential resource and has attracted much attention since the end of last century. It is important to characterize the composition of heavy oil to enhance its recovery efficien...Heavy oil is a complicated mixture and a potential resource and has attracted much attention since the end of last century. It is important to characterize the composition of heavy oil to enhance its recovery efficiency. A designed unilateral Nuclear Magnetic Resonance （NMR） sensor with a Larmor frequency of 20 MHz and a well-defined constant gradient of 23.25 T/m was employed to acquire three- dimensional （3D） data for three heavy oil samples. The highly-constant gradient is advantageous for diffusion coefficient measurement of heavy oil. A fast data-implementation procedure including specially designed 3D pulse sequence and Inversion Laplace Transform （ILT） algorithm was adopted to process the data and extract 3D T1-D-T2 probability function. It indicates that NMR relaxometry and diffusometry are useful to characterize the components of heavy oil samples. NMR results were compared with independent measurements of fractionation and gas chromatography analysis.展开更多
In this article, we get non-selfsimilar elementary waves of the conservation laws in another kind of view, which is different from the usual self-similar transformation. The solution has different global structure. Th...In this article, we get non-selfsimilar elementary waves of the conservation laws in another kind of view, which is different from the usual self-similar transformation. The solution has different global structure. This article is divided into three parts. The first part is introduction. In the second part, we discuss non-selfsimilar elementary waves and their interactions of a class of twodimensional conservation laws. In this case, we consider the case that the initial discontinuity is parabola with u＋ 〉 0, while explicit non-selfsirnilar rarefaction wave can be obtained. In the second part, we consider the solution structure of case u＋ 〈 0. The new solution structures are obtained by the interactions between different elementary waves, and will continue to interact with other states. Global solutions would be very different from the situation of one dimension.展开更多
In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the researc...In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.展开更多
A multi-dimensional conductive heterojunction structure,composited by TiO2,SnO2,and Ti3C2TX MXene,is facilely designed and applied as electron transport layer in efficient and stable planar perovskite solar cells.Base...A multi-dimensional conductive heterojunction structure,composited by TiO2,SnO2,and Ti3C2TX MXene,is facilely designed and applied as electron transport layer in efficient and stable planar perovskite solar cells.Based on an oxygen vacancy scramble effect,the zero-dimensional anatase TiO2 quantum dots,surrounding on two-dimensional conductive Ti3C2TX sheets,are in situ rooted on three-dimensional SnO2 nanoparticles,constructing nanoscale TiO2/SnO2 heterojunctions.The fabrication is implemented in a controlled lowtemperature anneal method in air and then in N2 atmospheres.With the optimal MXene content,the optical property,the crystallinity of perovskite layer,and internal interfaces are all facilitated,contributing more amount of carrier with effective and rapid transferring in device.The champion power conversion efficiency of resultant perovskite solar cells achieves 19.14%,yet that of counterpart is just 16.83%.In addition,it can also maintain almost 85%of its initial performance for more than 45 days in 30–40%humidity air;comparatively,the counterpart declines to just below 75%of its initial performance.展开更多
Traditional spatial clustering methods have the disadvantage of ＂hardware division＂, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a gen...Traditional spatial clustering methods have the disadvantage of ＂hardware division＂, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry. Based on infrastructures＇ classification and demarcation in Zhanjiang, a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering, the comparative study of Fuzzy C-means and a coupled analysis of residential land prices. General multi-dimensional cloud model reflects the integrated char- acteristics of spatial objects better, reveals the spatial distribution of potential information, and realizes spatial division more accurately in complex circumstances. However, due to the complexity of spatial interactions between geographical entities, the generation of cloud model is a specific and challenging task.展开更多
Through the estimates for Greens function of linearized system, we obtain L p estimates of the asymptotic behavior of solutions of the Cauchy problem for the Navier Stokes systems of compressible flow in seve...Through the estimates for Greens function of linearized system, we obtain L p estimates of the asymptotic behavior of solutions of the Cauchy problem for the Navier Stokes systems of compressible flow in several space dimensions.展开更多
In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boo...In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boosting cloud services are offered through the internet and some of them may be not reliable or even malicious, how to select trustworthy cloud services for cloud users is a big challenge. In this paper, we propose a multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning(ER) approach that integrates both perception-based trust value and reputation based trust value, which are derived from direct and indirect trust evidence respectively, to identify trustworthy services. Here, multi-dimensional trust evidence, which reflects the trustworthiness of cloud services from different aspects, is elicited in the form of historical users feedback ratings. Then, the ER approach is applied to aggregate the multi-dimensional trust ratings to obtain the real-time trust value and select the most trustworthy cloud service of certain type for the active users. Finally, the fresh feedback from the active users will update the trust evidence for other service users in the future.展开更多
In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and impl...In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.展开更多
Thermal maturation and petroleum generation modeling of shales is essential for suc- cessful exploration and exploitation of conventional and unconventional oil and gas plays. For basin- wide unconventional resource p...Thermal maturation and petroleum generation modeling of shales is essential for suc- cessful exploration and exploitation of conventional and unconventional oil and gas plays. For basin- wide unconventional resource plays such modeling, when well calibrated with direct maturity meas- urements from wells, can characterize and locate production sweet spots for oil, wet gas and dry gas. The transformation of kerogen to petroleum is associated with many chemical reactions, but models typically focus on first-order reactions with rates determined by the Arrhenius Equation. A miscon- ception has been perpetuated for many years that accurate thermal maturity modeling of vitrinite re- flectance using the Arrhenius Equation and a single activation energy, to derive a time-temperature index （~TTIARa）, as proposed by Wood （1988）, is flawed. This claim was initially made by Sweeney and Burnham （1990） in promoting their ＂EasyRo＂ method, and repeated by others. This paper dem- onstrates through detailed multi-dimensional burial and thermal modeling and direct comparison of the ~TTIARR and ＂EasyRo＂ methods that this is not the case. The ~TTIA^R method not only provides a very useful and sensitive maturity index, it can reproduce the calculated vitrinite reflectance values derived from models based on multiple activation energies （e.g., ＂EasyRo＂）. Through simple expres- sions the ~TTIAaa method can also provide oil and gas transformation factors that can be flexibly scaled and calibrated to match the oil, wet gas and dry gas generation windows. This is achieved in a more-computationally-efficient, flexible and transparent way by the ~TTIARR method than the ＂EasyRo＂ method. Analysis indicates that the ＂EasyRo＂ method, using twenty activation energies and a constant frequency factor, generates reaction rates and transformation factors that do not realisti- cally model observed kerogen behaviour and transformation factors over geologic time scales.展开更多
Intercepted signal blind separation is a research topic with high importance for both military and civilian communication systems. A blind separation method for space-time block code （STBC） systems is proposed by us...Intercepted signal blind separation is a research topic with high importance for both military and civilian communication systems. A blind separation method for space-time block code （STBC） systems is proposed by using the ordinary independent component analysis （ICA）. This method cannot work when specific complex modulations are employed since the assumption of mutual independence cannot be satisfied. The analysis shows that source signals, which are group-wise independent and use multi-dimensional ICA （MICA） instead of ordinary ICA, can be applied in this case. Utilizing the block-diagonal structure of the cumulant matrices, the JADE algorithm is generalized to the multidimensional case to separate the received data into mutually independent groups. Compared with ordinary ICA algorithms, the proposed method does not introduce additional ambiguities. Simulations show that the proposed method overcomes the drawback and achieves a better performance without utilizing coding information than channel estimation based algorithms.展开更多
In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0-1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding ...In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0-1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding feasible solutions. The Lagrangian relaxations were solved with the maximum-flow algorithm and the Lagrangian bounds was determined with the outer approximation method. Computational results show the efficiency of the proposed method for multi-dimensional quadratic 0-1 knapsack problems.展开更多
Based on China Family Panel Studies(CFPS) data and global MPI standard,this paper measures and analyzes multi-dimensional poverty in China. The study finds that the level of multi-dimensional poverty in China is not h...Based on China Family Panel Studies(CFPS) data and global MPI standard,this paper measures and analyzes multi-dimensional poverty in China. The study finds that the level of multi-dimensional poverty in China is not high and tends to decrease over time.Uneven regional development significantly affects multi-dimensional poverty. The poor are deprived in health, education and other aspects, but indicator contributions vary among specific groups of people. Overlap between economic poverty and multi-dimensional poverty has a trend of inter-temporal reduction. China's development-centered poverty reduction policy has achieved great results and significantly improved the development capabilities of the poor. Development-oriented approach is China's important experience in poverty reduction, and forebodes China's bright prospect of achieving its goal to complete building a moderately prosperous society by 2020.展开更多
The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for mul...The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for multi-dimensional copulas. A goodness-of-fit test based on Rosenblatt＇s transformation was mathematically expanded from two dimensions to three dimensions and procedures of a bootstrap version of the test were provided. Through stochastic copula simulation, an empirical application of historical drought data at the Lintong Gauge Station shows that the goodness-of-fit tests perform well, revealing that both trivariate Gaussian and Student t copulas are acceptable for modeling the dependence structures of the observed drought duration, severity, and peak. The goodness-of-fit tests for multi-dimensional copulas can provide further support and help a lot in the potential applications of a wider range of copulas to describe the associations of correlated hydrological variables. However, for the application of copulas with the number of dimensions larger than three, more complicated computational efforts as well as exploration and parameterization of corresponding copulas are required.展开更多
The study of multi-dimensional expansion of urban space(MEUS) addresses the laws of urban spatial expansion from all directions and angles. Using Nanjing as an example,this paper constructs multi-temporal, urban three...The study of multi-dimensional expansion of urban space(MEUS) addresses the laws of urban spatial expansion from all directions and angles. Using Nanjing as an example,this paper constructs multi-temporal, urban three-dimensional models based on RS and GIS technology and then conducts qualitative and quantitative analysis of MEUS using plot ratio change maps and MEUS quantitative index for built-up areas. Based especially on the concept of volume growth contribution rate, this paper analyzes the characteristics of MEUS in different stages. The results show that in 2000–2004, planar expansion played the main role,the internal potential development(IPD) intensity of the urban built-up areas was relatively large, and the volume growth contribution rate was low; in 2004–2008, planar expansion accelerated, and IPD slowed down; in 2008–2012, planar expansion slowed while IPD intensity increased; the contribution rates of volume growth of urban IPD for the three periods were 22.21%, 24.51% and 73.38%, respectively. This study expands the research perspective of urban spatial expansion, and the adopted methods are instructive and meaningful for MEUS research. In addition, the results of this study will deepen the understanding of MEUS laws and help improve scientific decision-making for urban planning and urban land use management.展开更多
In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly an...In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis, reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.展开更多
文摘On the evening of May 3Oth,the parallel forum"Equality and Inclusiveness&Harmonious Coexistence:Multi-dimensional Narratives of Civilisations from Writers'Perspective",as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.The forum was organised by the China Writers Association and co-organised by China National Publications Import&Export(Group)Corporation.
基金supported by a project funded by the Hebei Provincial Central Guidance Local Science and Technology Development Fund(236Z7714G)。
文摘Cervical cancer,a leading malignancy globally,poses a significant threat to women's health,with an estimated 604,000 new cases and 342,000 deaths reported in 2020^([1]).As cervical cancer is closely linked to human papilloma virus(HPV)infection,early detection relies on HPV screening;however,late-stage prognosis remains poor,underscoring the need for novel diagnostic and therapeutic targets^([2]).
文摘The existence and uniqueness of the global smooth solution to the initial-boundary valueproblem of a system of multi-dimensions SRWE are proved. The sufficient conditions of 'blowingup' of the solution are given.
基金National Natural Science Foundation of China Under Award Number 50878184National High Technology Research and Development Program (863 Program) of China Under Grant No. 2006AA04Z437Graduate Starting Seed Fund of Northwestern Polytechnical University Under the Grant No. Z2012059
文摘Fragility analysis for highway bridges has become increasingly important in the risk assessment of highway transportation networks exposed to seismic hazards. This study introduces a methodology to calculate fragility that considers multi-dimensional performance limit state parameters and makes a first attempt to develop fragility curves for a multi-span continuous (MSC) concrete girder bridge considering two performance limit state parameters: column ductility and transverse deformation in the abutments. The main purpose of this paper is to show that the performance limit states, which are compared with the seismic response parameters in the calculation of fragility, should be properly modeled as randomly interdependent variables instead of deterministic quantities. The sensitivity of fragility curves is also investigated when the dependency between the limit states is different. The results indicate that the proposed method can be used to describe the vulnerable behavior of bridges which are sensitive to multiple response parameters and that the fragility information generated by this method will be more reliable and likely to be implemented into transportation network loss estimation.
基金financial supports from the National Science Foundation of China (Grant No.41074102 and 41130417)"111 Program,Supported by the Programme of Introducing Talents of Discipline to Universities"(B13010)Program for Changjiang Scholars and Innovative Research Team in University
文摘Heavy oil is a complicated mixture and a potential resource and has attracted much attention since the end of last century. It is important to characterize the composition of heavy oil to enhance its recovery efficiency. A designed unilateral Nuclear Magnetic Resonance （NMR） sensor with a Larmor frequency of 20 MHz and a well-defined constant gradient of 23.25 T/m was employed to acquire three- dimensional （3D） data for three heavy oil samples. The highly-constant gradient is advantageous for diffusion coefficient measurement of heavy oil. A fast data-implementation procedure including specially designed 3D pulse sequence and Inversion Laplace Transform （ILT） algorithm was adopted to process the data and extract 3D T1-D-T2 probability function. It indicates that NMR relaxometry and diffusometry are useful to characterize the components of heavy oil samples. NMR results were compared with independent measurements of fractionation and gas chromatography analysis.
基金Sponsored by the National Natural Science Foundation of China (10671116,10871199, and 10001023)Hou Yingdong Fellowship (81004), The China Scholarship Council, Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, Natural Science Foundation of Guangdong (06027210 and 000804)Natural Science Foundation of Guangdong Education Bureau (200030)
文摘In this article, we get non-selfsimilar elementary waves of the conservation laws in another kind of view, which is different from the usual self-similar transformation. The solution has different global structure. This article is divided into three parts. The first part is introduction. In the second part, we discuss non-selfsimilar elementary waves and their interactions of a class of twodimensional conservation laws. In this case, we consider the case that the initial discontinuity is parabola with u＋ 〉 0, while explicit non-selfsirnilar rarefaction wave can be obtained. In the second part, we consider the solution structure of case u＋ 〈 0. The new solution structures are obtained by the interactions between different elementary waves, and will continue to interact with other states. Global solutions would be very different from the situation of one dimension.
基金supported by the National Natural Science Foundation of China(5110505261173163)the Liaoning Provincial Natural Science Foundation of China(201102037)
文摘In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.
基金supported by the Science & Technology Project of Anhui Province (16030701091)the Natural Science Research Project of Anhui Provincial Education Department (KJ2019A0030)+2 种基金the Support Project of Outstanding Young Talents in Anhui Provincial Universities (gxyqZD2018006)the National Natural Science Foundation of China(11704002, 31701323)the Anhui Provincial Natural Science Foundation (1908085QF251,1808085MF185)
文摘A multi-dimensional conductive heterojunction structure,composited by TiO2,SnO2,and Ti3C2TX MXene,is facilely designed and applied as electron transport layer in efficient and stable planar perovskite solar cells.Based on an oxygen vacancy scramble effect,the zero-dimensional anatase TiO2 quantum dots,surrounding on two-dimensional conductive Ti3C2TX sheets,are in situ rooted on three-dimensional SnO2 nanoparticles,constructing nanoscale TiO2/SnO2 heterojunctions.The fabrication is implemented in a controlled lowtemperature anneal method in air and then in N2 atmospheres.With the optimal MXene content,the optical property,the crystallinity of perovskite layer,and internal interfaces are all facilitated,contributing more amount of carrier with effective and rapid transferring in device.The champion power conversion efficiency of resultant perovskite solar cells achieves 19.14%,yet that of counterpart is just 16.83%.In addition,it can also maintain almost 85%of its initial performance for more than 45 days in 30–40%humidity air;comparatively,the counterpart declines to just below 75%of its initial performance.
基金National Natural Science Foundation of China, N0.40971102 Knowledge Innovation Project of the Chinese Academy of Sciences, No. KZCX2-YW-322 Special Grant for Postgraduates＇ Scientific Innovation and So- cial Practice in 2008
文摘Traditional spatial clustering methods have the disadvantage of ＂hardware division＂, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry. Based on infrastructures＇ classification and demarcation in Zhanjiang, a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering, the comparative study of Fuzzy C-means and a coupled analysis of residential land prices. General multi-dimensional cloud model reflects the integrated char- acteristics of spatial objects better, reveals the spatial distribution of potential information, and realizes spatial division more accurately in complex circumstances. However, due to the complexity of spatial interactions between geographical entities, the generation of cloud model is a specific and challenging task.
文摘Through the estimates for Greens function of linearized system, we obtain L p estimates of the asymptotic behavior of solutions of the Cauchy problem for the Navier Stokes systems of compressible flow in several space dimensions.
基金supported by National Natural Science Foundation of China(Nos.71131002,71071045,71231004 and 71201042)
文摘In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boosting cloud services are offered through the internet and some of them may be not reliable or even malicious, how to select trustworthy cloud services for cloud users is a big challenge. In this paper, we propose a multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning(ER) approach that integrates both perception-based trust value and reputation based trust value, which are derived from direct and indirect trust evidence respectively, to identify trustworthy services. Here, multi-dimensional trust evidence, which reflects the trustworthiness of cloud services from different aspects, is elicited in the form of historical users feedback ratings. Then, the ER approach is applied to aggregate the multi-dimensional trust ratings to obtain the real-time trust value and select the most trustworthy cloud service of certain type for the active users. Finally, the fresh feedback from the active users will update the trust evidence for other service users in the future.
文摘In order to discover the main causes of elevator group accidents in edge computing environment, a multi-dimensional data model of elevator accident data is established by using data cube technology, proposing and implementing a method by combining classical Apriori algorithm with the model, digging out frequent items of elevator accident data to explore the main reasons for the occurrence of elevator accidents. In addition, a collaborative edge model of elevator accidents is set to achieve data sharing, making it possible to check the detail of each cause to confirm the causes of elevator accidents. Lastly the association rules are applied to find the law of elevator Accidents.
文摘Thermal maturation and petroleum generation modeling of shales is essential for suc- cessful exploration and exploitation of conventional and unconventional oil and gas plays. For basin- wide unconventional resource plays such modeling, when well calibrated with direct maturity meas- urements from wells, can characterize and locate production sweet spots for oil, wet gas and dry gas. The transformation of kerogen to petroleum is associated with many chemical reactions, but models typically focus on first-order reactions with rates determined by the Arrhenius Equation. A miscon- ception has been perpetuated for many years that accurate thermal maturity modeling of vitrinite re- flectance using the Arrhenius Equation and a single activation energy, to derive a time-temperature index （~TTIARa）, as proposed by Wood （1988）, is flawed. This claim was initially made by Sweeney and Burnham （1990） in promoting their ＂EasyRo＂ method, and repeated by others. This paper dem- onstrates through detailed multi-dimensional burial and thermal modeling and direct comparison of the ~TTIARR and ＂EasyRo＂ methods that this is not the case. The ~TTIA^R method not only provides a very useful and sensitive maturity index, it can reproduce the calculated vitrinite reflectance values derived from models based on multiple activation energies （e.g., ＂EasyRo＂）. Through simple expres- sions the ~TTIAaa method can also provide oil and gas transformation factors that can be flexibly scaled and calibrated to match the oil, wet gas and dry gas generation windows. This is achieved in a more-computationally-efficient, flexible and transparent way by the ~TTIARR method than the ＂EasyRo＂ method. Analysis indicates that the ＂EasyRo＂ method, using twenty activation energies and a constant frequency factor, generates reaction rates and transformation factors that do not realisti- cally model observed kerogen behaviour and transformation factors over geologic time scales.
基金supported by the National Natural Science Foundation of China (61201282)
文摘Intercepted signal blind separation is a research topic with high importance for both military and civilian communication systems. A blind separation method for space-time block code （STBC） systems is proposed by using the ordinary independent component analysis （ICA）. This method cannot work when specific complex modulations are employed since the assumption of mutual independence cannot be satisfied. The analysis shows that source signals, which are group-wise independent and use multi-dimensional ICA （MICA） instead of ordinary ICA, can be applied in this case. Utilizing the block-diagonal structure of the cumulant matrices, the JADE algorithm is generalized to the multidimensional case to separate the received data into mutually independent groups. Compared with ordinary ICA algorithms, the proposed method does not introduce additional ambiguities. Simulations show that the proposed method overcomes the drawback and achieves a better performance without utilizing coding information than channel estimation based algorithms.
基金Project supported by the National Natural Science Foundation of China （Grant No.10571116）
文摘In this paper, a branch-and-bound method for solving multi-dimensional quadratic 0-1 knapsack problems was studied. The method was based on the Lagrangian relaxation and the surrogate constraint technique for finding feasible solutions. The Lagrangian relaxations were solved with the maximum-flow algorithm and the Lagrangian bounds was determined with the outer approximation method. Computational results show the efficiency of the proposed method for multi-dimensional quadratic 0-1 knapsack problems.
基金funded by the following projects:Major project of the National Social Science Fund of China(NSSFC) "Rural China’s Data Collection and Application Program"(Project No.18ZDA080)The National Natural Science Foundation of China(NSFC) "Measurement of Multi-Dimensional Poverty for Rural & Urban Residents and Pro-Poor Policy Evaluation"(Project No.71874089)Humanities and Social Sciences Fund Youth Project of the Ministry of Education "Study on Multi-Dimensional Poverty Micro Simulation Model under the Constraints of Poverty Reduction Targets"(Project No.18YJC910015)
文摘Based on China Family Panel Studies(CFPS) data and global MPI standard,this paper measures and analyzes multi-dimensional poverty in China. The study finds that the level of multi-dimensional poverty in China is not high and tends to decrease over time.Uneven regional development significantly affects multi-dimensional poverty. The poor are deprived in health, education and other aspects, but indicator contributions vary among specific groups of people. Overlap between economic poverty and multi-dimensional poverty has a trend of inter-temporal reduction. China's development-centered poverty reduction policy has achieved great results and significantly improved the development capabilities of the poor. Development-oriented approach is China's important experience in poverty reduction, and forebodes China's bright prospect of achieving its goal to complete building a moderately prosperous society by 2020.
基金supported by the Program of Introducing Talents of Disciplines to Universities of the Ministry of Education and State Administration of the Foreign Experts Affairs of China (the 111 Project, Grant No.B08048)the Special Basic Research Fund for Methodology in Hydrology of the Ministry of Sciences and Technology of China (Grant No. 2011IM011000)
文摘The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for multi-dimensional copulas. A goodness-of-fit test based on Rosenblatt＇s transformation was mathematically expanded from two dimensions to three dimensions and procedures of a bootstrap version of the test were provided. Through stochastic copula simulation, an empirical application of historical drought data at the Lintong Gauge Station shows that the goodness-of-fit tests perform well, revealing that both trivariate Gaussian and Student t copulas are acceptable for modeling the dependence structures of the observed drought duration, severity, and peak. The goodness-of-fit tests for multi-dimensional copulas can provide further support and help a lot in the potential applications of a wider range of copulas to describe the associations of correlated hydrological variables. However, for the application of copulas with the number of dimensions larger than three, more complicated computational efforts as well as exploration and parameterization of corresponding copulas are required.
基金National Natural Science Foundation of China,No.41871178,No.41671385,No.41371172
文摘The study of multi-dimensional expansion of urban space(MEUS) addresses the laws of urban spatial expansion from all directions and angles. Using Nanjing as an example,this paper constructs multi-temporal, urban three-dimensional models based on RS and GIS technology and then conducts qualitative and quantitative analysis of MEUS using plot ratio change maps and MEUS quantitative index for built-up areas. Based especially on the concept of volume growth contribution rate, this paper analyzes the characteristics of MEUS in different stages. The results show that in 2000–2004, planar expansion played the main role,the internal potential development(IPD) intensity of the urban built-up areas was relatively large, and the volume growth contribution rate was low; in 2004–2008, planar expansion accelerated, and IPD slowed down; in 2008–2012, planar expansion slowed while IPD intensity increased; the contribution rates of volume growth of urban IPD for the three periods were 22.21%, 24.51% and 73.38%, respectively. This study expands the research perspective of urban spatial expansion, and the adopted methods are instructive and meaningful for MEUS research. In addition, the results of this study will deepen the understanding of MEUS laws and help improve scientific decision-making for urban planning and urban land use management.
基金supported by the National Natural Science Foundation of China(U14352186140340161273189)
文摘In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis, reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.
