Burden distribution is one of the most important operations, and also an important upper regulation in blast furnace(BF) iron-making process. Burden distribution output behaviors(BDOB) at the throat of BF is a 3-dimen...Burden distribution is one of the most important operations, and also an important upper regulation in blast furnace(BF) iron-making process. Burden distribution output behaviors(BDOB) at the throat of BF is a 3-dimensional spatial distribution produced by burden distribution matrix(BDM),including burden surface output shape(BSOS) and material layer initial thickness distribution(MLITD). Due to the lack of effective model to describe the complex input-output relations,BDM optimization and adjustment is carried out by experienced foremen. Focusing on this practical challenge, this work studies complex burden distribution input-output relations, and gives a description of expected MLITD under specific integral constraint on the basis of engineering practice. Furthermore, according to the decision variables in different number fields, this work studies optimization of BDM with expected MLITD, and proposes a multi-mode based particle swarm optimization(PSO) procedure for optimization of decision variables. Finally, experiments using industrial data show that the proposed model is effective, and optimized BDM calculated by this multi-model based PSO method can be used for expected distribution tracking.展开更多
This paper exploits coding to speed up computation offloading in a multi-server mobile edge computing(MEC)network with straggling servers and channel fading.The specific task we consider is to compute the product betw...This paper exploits coding to speed up computation offloading in a multi-server mobile edge computing(MEC)network with straggling servers and channel fading.The specific task we consider is to compute the product between a user-generated input data matrix and a large-scale model matrix that is stored distributively across the multiple edge nodes.The key idea of coding is to introduce computation redundancy to improve robustness against straggling servers and to create communication redundancy to improve reliability against channel fading.We utilize the hybrid design of maximum distance separable(MDS)coding and repetition coding.Based on the hybrid coding scheme,we conduct theoretical analysis on the average task uploading time,average edge computing time,and average output downloading time,respectively and then obtain the end-to-end task execution time.Numerical results demonstrate that when the task uploading phase or the edge computing phase is the performance bottleneck,the hybrid coding reduces to MDS coding;when the downlink transmission is the bottleneck,the hybrid coding reduces to repetition coding.The hybrid coding also outperforms the entangled polynomial coding that causes higher uplink and downlink communication loads.展开更多
To improve the naphtha composition prediction model based on molecular type homologous series matrix （MTHS）, this paper puts forward a novel molecular matrix to characterize the naphtha composition and the norreal d...To improve the naphtha composition prediction model based on molecular type homologous series matrix （MTHS）, this paper puts forward a novel molecular matrix to characterize the naphtha composition and the norreal distribution hypothesis to better describe the molecular composition distribution within each homologous series of the molecular matrix. Through prediction calculation of eight groups of naphtha samples and eight groups of gasoline samples, it is verified that the normal distribution hypothesis is more applicable than gamma distribution hypothesis for the prediction model. According to the prediction results of the samples, the restrain range of normal distribution parameters during model computing process is summarized. With the bulk properties of naphtha samples and the value range of distribution parameters as input conditions, this study utilizes the improved novel molecular matrix to predict the composition of naphtha samples. As the results show, the novel molecular matrix can predict more detailed composition information of naphtha and improve prediction accuracy with less unknown parameters.展开更多
As far as the nonlinear regression method is concerned, the condition when both independent and dependent variable take the Fuzzy value, while the parameter, θ∈ΘR m the real value, have been discussed in . But for...As far as the nonlinear regression method is concerned, the condition when both independent and dependent variable take the Fuzzy value, while the parameter, θ∈ΘR m the real value, have been discussed in . But for most of actual conditions, the independent variable generally takes the real value, while both parameter and dependent variable take the Fuzzy value. This paper propounded a method for the latter and its relevant Fuzzy regreession model. In addition the Fuzzy observation, matrix distribution and the rational estimation of modeling parameter have also been discussed. Furthermore, the Max min estimation of modeling parameter and its corresponding calculating sequence have also been offered to and the calculating example shows the method is feasible.展开更多
In this paper, our discussion is based on Zeilberg＇s basic idea and use an elimination in the non-commutative Weyl algebra to get the differential operator. Thereby we can obtain the algorithm of proving identities o...In this paper, our discussion is based on Zeilberg＇s basic idea and use an elimination in the non-commutative Weyl algebra to get the differential operator. Thereby we can obtain the algorithm of proving identities of the form ∫∞ -∞F（x, y）dy = a（x）.展开更多
We propose a metapopulation model with two geographical scales. In a regional scale, the model describes the dynamics of a collection of habitats connected by migratory movements. In a local scale, we consider some gr...We propose a metapopulation model with two geographical scales. In a regional scale, the model describes the dynamics of a collection of habitats connected by migratory movements. In a local scale, we consider some granularity within each habitat, in the sense that each habitat is itself a collection of patches linked by dispersal. The whole ensemble can be seen as a metapopulation composed by local metapopulations. We analyze the synchronization of the model in the two geographical scales. We present an analytic criterion for synchronization where only the habitats in the regional scale evolve with the same dynamics. Through numerical simulations, we discuss the different synchronization modes. It depends on how the individuals are distributed in the local patches that compose a habitat after migration takes place in the regional scale.展开更多
We establish an identity for E f(Y)-E f(X),when X and Y both have matrix variate skew-normal distributions and the function f satisfies some weak conditions.The characteristic function of matrix variate skew normal dis...We establish an identity for E f(Y)-E f(X),when X and Y both have matrix variate skew-normal distributions and the function f satisfies some weak conditions.The characteristic function of matrix variate skew normal distribution is then derived.We then make use of it to derive some necessary and sufficient conditions for the comparison of matrix variate skew-normal distributions under six different orders,such as usual stochastic order,convex order,increasing convex order,upper orthant order,directionally convex order and supermodular order.展开更多
With the support by the National Natural Science Foundation of China and the Chinese Academy of Sciences,the research team led by Prof.Li Junbai(李峻柏)at the CAS Key Lab of Colloid,Interface and Thermodynamics,Instit...With the support by the National Natural Science Foundation of China and the Chinese Academy of Sciences,the research team led by Prof.Li Junbai(李峻柏)at the CAS Key Lab of Colloid,Interface and Thermodynamics,Institute of Chemistry,Chinese Academy of Sciences,revealed the distribution of proteins in the transformation of inorganic/protein hybrid crystals by super-resolution microscopy,which展开更多
Invariant polynomials with matrix arguments have been defined by the theory of group representation, generalizing the zonal polynomials. They have developed as a useful tool to evaluate certain integrals arising in mu...Invariant polynomials with matrix arguments have been defined by the theory of group representation, generalizing the zonal polynomials. They have developed as a useful tool to evaluate certain integrals arising in multivariate distribution theory, which were expanded as power series in terms of the invariant polynomials. Some interesting polynomials has been shown by people working in the field of econometric theory. In this paper. we derive the expected values of C (BR.BU). Ck (BR)C (BU) and Ck (B-1U), where Bd＝X′X and Xnxp is distributed according to an elliptical matrix distribution. We also give their applications in multivariate distribution theory including the related development in econometrics.展开更多
In this paper the density of the matrix variate beta distribution of rank lower than itsdimensionality is obtained with respect to a suitably defined differential form under the condi-tion that the difference between ...In this paper the density of the matrix variate beta distribution of rank lower than itsdimensionality is obtained with respect to a suitably defined differential form under the condi-tion that the difference between the identity and this matrix has full rank. As preliminaries,the Jacobian of a transformation related to decomposing a nonnegative-definite matrix into theproduct of a matrix of full column rank and its transpose and that of the transformation of anonnegative-definite matrix into its congruent matrix are established.展开更多
Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper,we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge...Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper,we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge graphs. Previous models such as Trans（E, H, R） and CTrans R are either insufficient for embedding hyper-relational data or focus on projecting an entity into multiple embeddings, which might not be effective for generalization nor accurately reflect real knowledge. To overcome these issues, we propose the novel model Trans HR, which transforms the hyper-relations in a pair of entities into an individual vector, serving as a translation between them. We experimentally evaluate our model on two typical tasks—link prediction and triple classification.The results demonstrate that Trans HR significantly outperforms Trans（E, H, R） and CTrans R, especially for hyperrelational data.展开更多
In this paper, the multivariate linear model Y = XB＋e, e ～ Nm×k（0, ImΣ） is considered from the Bayes perspective. Under the normal-inverse Wishart prior for （BΣ）, the Bayes estimators are derived. The sup...In this paper, the multivariate linear model Y = XB＋e, e ～ Nm×k（0, ImΣ） is considered from the Bayes perspective. Under the normal-inverse Wishart prior for （BΣ）, the Bayes estimators are derived. The superiority of the Bayes estimators of B and Σ over the least squares estimators under the criteria of Bayes mean squared error （BMSE） and Bayes mean squared error matrix （BMSEM） is shown. In addition, the Pitman Closeness （PC） criterion is also included to investigate the superiority of the Bayes estimator of B.展开更多
基金supported by the National Natural Science Foundation of China(61763038,61763039,61621004,61790572,61890934,61973137)the Fundamental Research Funds for the Central Universities(N180802003)
文摘Burden distribution is one of the most important operations, and also an important upper regulation in blast furnace(BF) iron-making process. Burden distribution output behaviors(BDOB) at the throat of BF is a 3-dimensional spatial distribution produced by burden distribution matrix(BDM),including burden surface output shape(BSOS) and material layer initial thickness distribution(MLITD). Due to the lack of effective model to describe the complex input-output relations,BDM optimization and adjustment is carried out by experienced foremen. Focusing on this practical challenge, this work studies complex burden distribution input-output relations, and gives a description of expected MLITD under specific integral constraint on the basis of engineering practice. Furthermore, according to the decision variables in different number fields, this work studies optimization of BDM with expected MLITD, and proposes a multi-mode based particle swarm optimization(PSO) procedure for optimization of decision variables. Finally, experiments using industrial data show that the proposed model is effective, and optimized BDM calculated by this multi-model based PSO method can be used for expected distribution tracking.
基金supported by NSF of China under grant U1908210National Key R&D Project of China under grant 2019YFB1802702。
文摘This paper exploits coding to speed up computation offloading in a multi-server mobile edge computing(MEC)network with straggling servers and channel fading.The specific task we consider is to compute the product between a user-generated input data matrix and a large-scale model matrix that is stored distributively across the multiple edge nodes.The key idea of coding is to introduce computation redundancy to improve robustness against straggling servers and to create communication redundancy to improve reliability against channel fading.We utilize the hybrid design of maximum distance separable(MDS)coding and repetition coding.Based on the hybrid coding scheme,we conduct theoretical analysis on the average task uploading time,average edge computing time,and average output downloading time,respectively and then obtain the end-to-end task execution time.Numerical results demonstrate that when the task uploading phase or the edge computing phase is the performance bottleneck,the hybrid coding reduces to MDS coding;when the downlink transmission is the bottleneck,the hybrid coding reduces to repetition coding.The hybrid coding also outperforms the entangled polynomial coding that causes higher uplink and downlink communication loads.
基金Supported by the National Natural Science Foundation of China(U1462206)
文摘To improve the naphtha composition prediction model based on molecular type homologous series matrix （MTHS）, this paper puts forward a novel molecular matrix to characterize the naphtha composition and the norreal distribution hypothesis to better describe the molecular composition distribution within each homologous series of the molecular matrix. Through prediction calculation of eight groups of naphtha samples and eight groups of gasoline samples, it is verified that the normal distribution hypothesis is more applicable than gamma distribution hypothesis for the prediction model. According to the prediction results of the samples, the restrain range of normal distribution parameters during model computing process is summarized. With the bulk properties of naphtha samples and the value range of distribution parameters as input conditions, this study utilizes the improved novel molecular matrix to predict the composition of naphtha samples. As the results show, the novel molecular matrix can predict more detailed composition information of naphtha and improve prediction accuracy with less unknown parameters.
文摘As far as the nonlinear regression method is concerned, the condition when both independent and dependent variable take the Fuzzy value, while the parameter, θ∈ΘR m the real value, have been discussed in . But for most of actual conditions, the independent variable generally takes the real value, while both parameter and dependent variable take the Fuzzy value. This paper propounded a method for the latter and its relevant Fuzzy regreession model. In addition the Fuzzy observation, matrix distribution and the rational estimation of modeling parameter have also been discussed. Furthermore, the Max min estimation of modeling parameter and its corresponding calculating sequence have also been offered to and the calculating example shows the method is feasible.
基金the Education Department Project Research Foundation of Hubei Province (2003A004)
文摘In this paper, our discussion is based on Zeilberg＇s basic idea and use an elimination in the non-commutative Weyl algebra to get the differential operator. Thereby we can obtain the algorithm of proving identities of the form ∫∞ -∞F（x, y）dy = a（x）.
文摘We propose a metapopulation model with two geographical scales. In a regional scale, the model describes the dynamics of a collection of habitats connected by migratory movements. In a local scale, we consider some granularity within each habitat, in the sense that each habitat is itself a collection of patches linked by dispersal. The whole ensemble can be seen as a metapopulation composed by local metapopulations. We analyze the synchronization of the model in the two geographical scales. We present an analytic criterion for synchronization where only the habitats in the regional scale evolve with the same dynamics. Through numerical simulations, we discuss the different synchronization modes. It depends on how the individuals are distributed in the local patches that compose a habitat after migration takes place in the regional scale.
基金supported by the National Natural Science Foundation of China(No.12071251,11571198,11701319).
文摘We establish an identity for E f(Y)-E f(X),when X and Y both have matrix variate skew-normal distributions and the function f satisfies some weak conditions.The characteristic function of matrix variate skew normal distribution is then derived.We then make use of it to derive some necessary and sufficient conditions for the comparison of matrix variate skew-normal distributions under six different orders,such as usual stochastic order,convex order,increasing convex order,upper orthant order,directionally convex order and supermodular order.
文摘With the support by the National Natural Science Foundation of China and the Chinese Academy of Sciences,the research team led by Prof.Li Junbai(李峻柏)at the CAS Key Lab of Colloid,Interface and Thermodynamics,Institute of Chemistry,Chinese Academy of Sciences,revealed the distribution of proteins in the transformation of inorganic/protein hybrid crystals by super-resolution microscopy,which
文摘Invariant polynomials with matrix arguments have been defined by the theory of group representation, generalizing the zonal polynomials. They have developed as a useful tool to evaluate certain integrals arising in multivariate distribution theory, which were expanded as power series in terms of the invariant polynomials. Some interesting polynomials has been shown by people working in the field of econometric theory. In this paper. we derive the expected values of C (BR.BU). Ck (BR)C (BU) and Ck (B-1U), where Bd＝X′X and Xnxp is distributed according to an elliptical matrix distribution. We also give their applications in multivariate distribution theory including the related development in econometrics.
文摘In this paper the density of the matrix variate beta distribution of rank lower than itsdimensionality is obtained with respect to a suitably defined differential form under the condi-tion that the difference between the identity and this matrix has full rank. As preliminaries,the Jacobian of a transformation related to decomposing a nonnegative-definite matrix into theproduct of a matrix of full column rank and its transpose and that of the transformation of anonnegative-definite matrix into its congruent matrix are established.
基金partially supported by National Council of Science and Technology(CONACYT)-Mexico,research grant 81512Research,Development and Innovation(IDI)-Spain,grant MTM2005-09209
文摘In this paper, we give alternative proofs of some results in [15] （Li R.,1997） about the expected value of zonal polynomials.
基金partially supported by the National Natural Science Foundation of China(Nos.61302077,61520106007,61421061,and 61602048)
文摘Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper,we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge graphs. Previous models such as Trans（E, H, R） and CTrans R are either insufficient for embedding hyper-relational data or focus on projecting an entity into multiple embeddings, which might not be effective for generalization nor accurately reflect real knowledge. To overcome these issues, we propose the novel model Trans HR, which transforms the hyper-relations in a pair of entities into an individual vector, serving as a translation between them. We experimentally evaluate our model on two typical tasks—link prediction and triple classification.The results demonstrate that Trans HR significantly outperforms Trans（E, H, R） and CTrans R, especially for hyperrelational data.
基金Supported by National Natural Science Foundation of China(Grant Nos.11201005,11071015)the Foundation of National Bureau of Statistics(Grant No.2013LZ17)the Natural Science Foundation of Anhui Province(Grant No.1308085QA13)
文摘In this paper, the multivariate linear model Y = XB＋e, e ～ Nm×k（0, ImΣ） is considered from the Bayes perspective. Under the normal-inverse Wishart prior for （BΣ）, the Bayes estimators are derived. The superiority of the Bayes estimators of B and Σ over the least squares estimators under the criteria of Bayes mean squared error （BMSE） and Bayes mean squared error matrix （BMSEM） is shown. In addition, the Pitman Closeness （PC） criterion is also included to investigate the superiority of the Bayes estimator of B.
