This article continues to study the research suggestions in depth made by M.Z.Nashed and G.F.Votruba in the journal"Bull.Amer.Math.Soc."in 1974.Concerned with the pricing of non-reachable"contingent cla...This article continues to study the research suggestions in depth made by M.Z.Nashed and G.F.Votruba in the journal"Bull.Amer.Math.Soc."in 1974.Concerned with the pricing of non-reachable"contingent claims"in an incomplete financial market,when constructing a specific bounded linear operator A:l_(1)^(n)→l_(2) from a non-reflexive Banach space l_(1)^(n) to a Hilbert space l_(2),the problem of non-reachable"contingent claims"pricing is reduced to researching the(single-valued)selection of the(set-valued)metric generalized inverse A■ of the operator A.In this paper,by using the Banach space structure theory and the generalized inverse method of operators,we obtain a bounded linear single-valued selection A^(σ)=A+of A■.展开更多
Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner.Further investigation of customer p...Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner.Further investigation of customer patterns helps thefirm to develop efficient decisions and in turn,helps to optimize the enter-prise’s business and maximizes consumer satisfaction correspondingly.To con-duct an effective assessment about the customers,Naive Bayes(also called Simple Bayes),a machine learning model is utilized.However,the efficacious of the simple Bayes model is utterly relying on the consumer data used,and the existence of uncertain and redundant attributes in the consumer data enables the simple Bayes model to attain the worst prediction in consumer data because of its presumption regarding the attributes applied.However,in practice,the NB pre-mise is not true in consumer data,and the analysis of these redundant attributes enables simple Bayes model to get poor prediction results.In this work,an ensem-ble attribute selection methodology is performed to overcome the problem with consumer data and to pick a steady uncorrelated attribute set to model with the NB classifier.In ensemble variable selection,two different strategies are applied:one is based upon data perturbation(or homogeneous ensemble,same feature selector is applied to a different subsamples derived from the same learning set)and the other one is based upon function perturbation(or heterogeneous ensemble different feature selector is utilized to the same learning set).Further-more,the feature set captured from both ensemble strategies is applied to NB indi-vidually and the outcome obtained is computed.Finally,the experimental outcomes show that the proposed ensemble strategies perform efficiently in choosing a steady attribute set and increasing NB classification performance efficiently.展开更多
In this paper, continuous homogeneous selections for the set-valued metric generalized inverses T^ of linear operators T in Banach spaces are investigated by means of the methods of geometry of Banach spaces. Necessar...In this paper, continuous homogeneous selections for the set-valued metric generalized inverses T^ of linear operators T in Banach spaces are investigated by means of the methods of geometry of Banach spaces. Necessary and sufficient conditions for bounded linear operators T to have continuous homogeneous selections for the set-valued metric generalized inverses T~ are given. The results are an answer to the problem posed by Nashed and Votruba.展开更多
Background:Previous studies have found that coastal eutrophication increases the influence of homogeneous selection on bacterial community assembly.However,whether seasonal changes affect the dominance of homogenous s...Background:Previous studies have found that coastal eutrophication increases the influence of homogeneous selection on bacterial community assembly.However,whether seasonal changes affect the dominance of homogenous selection in bacterial community assembly in eutrophic bays remains unclear.Sansha Bay is an enclosed bay with ongoing eutrophication,located in the southeast coast of China.We investigated the bacterial community composition at two depths of the enclosed bay across seasons and the seasonal variation in community assembly processes.Results:Diversity analyses revealed that the bacterial community composition among seasons differed significantly.By contrast,there was little difference in the community composition between the two depths.The temperature was the key environmental factor influencing the community composition.The null model indicated that the relative importance of homogeneous selection decreased in the following order:spring>winter>autumn>summer.Homogeneous selection did not always dominate the community assembly among seasons in the eutrophic bay.The effects of pure spatial variables on the community assembly were prominent in autumn and winter.Conclusions:Our results showed the seasonal influence of eutrophication on bacterial community diversity.The seasonal variation in composition and structure of bacterial communities eclipsed the vertical variability.Eutrophication could enhance the importance of homogeneous selection in the assembly processes,but the seasonal environmental differences interfered with the steady-state maintained by ongoing eutrophication and changed the community assembly processes.Homogeneous selection was not always important in bacterial community in the eutrophic enclosed bay.The bacterial community was the most complex in summer,because the composition differed from other seasons,and the assembly process was the most intricate.These findings have contributed to understanding bacterial community composition and assembly processes in eutrophic coastal ecosystems.展开更多
In the past two decades,extensive and in-depth research has been conducted on Time Series InSAR technology with the advancement of high-performance SAR satellites and the accumulation of big SAR data.The introduction ...In the past two decades,extensive and in-depth research has been conducted on Time Series InSAR technology with the advancement of high-performance SAR satellites and the accumulation of big SAR data.The introduction of distributed scatterers in Distributed Scatterers InSAR(DS-InSAR)has significantly expanded the application scenarios of InSAR geodetic measurement by increasing the number of measurement points.This study traces the history of DS-InSAR,presents the definition and characteristics of distributed scatterers,and focuses on exploring the relationships and distinctions among proposed algorithms in two crucial steps:statistically homogeneous pixel selection and phase optimization.Additionally,the latest research progress in this field is tracked and the possible development direction in the future is discussed.Through simulation experiments and two real InSAR case studies,the proposed algorithms are compared and verified,and the advantages of DS-InSAR in deformation measurement practice are demonstrated.This work not only offers insights into current trends and focal points for theoretical research on DS-InSAR but also provides practical cases and guidance for applied research.展开更多
基金supported by the National Science Foundation (12001142)Harbin Normal University doctoral initiation Fund (XKB201812)supported by the Science Foundation Grant of Heilongjiang Province (LH2019A017)
文摘This article continues to study the research suggestions in depth made by M.Z.Nashed and G.F.Votruba in the journal"Bull.Amer.Math.Soc."in 1974.Concerned with the pricing of non-reachable"contingent claims"in an incomplete financial market,when constructing a specific bounded linear operator A:l_(1)^(n)→l_(2) from a non-reflexive Banach space l_(1)^(n) to a Hilbert space l_(2),the problem of non-reachable"contingent claims"pricing is reduced to researching the(single-valued)selection of the(set-valued)metric generalized inverse A■ of the operator A.In this paper,by using the Banach space structure theory and the generalized inverse method of operators,we obtain a bounded linear single-valued selection A^(σ)=A+of A■.
文摘Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner.Further investigation of customer patterns helps thefirm to develop efficient decisions and in turn,helps to optimize the enter-prise’s business and maximizes consumer satisfaction correspondingly.To con-duct an effective assessment about the customers,Naive Bayes(also called Simple Bayes),a machine learning model is utilized.However,the efficacious of the simple Bayes model is utterly relying on the consumer data used,and the existence of uncertain and redundant attributes in the consumer data enables the simple Bayes model to attain the worst prediction in consumer data because of its presumption regarding the attributes applied.However,in practice,the NB pre-mise is not true in consumer data,and the analysis of these redundant attributes enables simple Bayes model to get poor prediction results.In this work,an ensem-ble attribute selection methodology is performed to overcome the problem with consumer data and to pick a steady uncorrelated attribute set to model with the NB classifier.In ensemble variable selection,two different strategies are applied:one is based upon data perturbation(or homogeneous ensemble,same feature selector is applied to a different subsamples derived from the same learning set)and the other one is based upon function perturbation(or heterogeneous ensemble different feature selector is utilized to the same learning set).Further-more,the feature set captured from both ensemble strategies is applied to NB indi-vidually and the outcome obtained is computed.Finally,the experimental outcomes show that the proposed ensemble strategies perform efficiently in choosing a steady attribute set and increasing NB classification performance efficiently.
基金supported by National Science Foundation of China (Grant No.11071051)Youth Science Foundation of Heilongjiang Province of China (Grant No.QC2009C73)+1 种基金the second author is supported by the State Committee for Scientific Research of Poland (Grant No.N N201 362236)the third author is supported by National Science Foundation of China (Grant No.11071051)
文摘In this paper, continuous homogeneous selections for the set-valued metric generalized inverses T^ of linear operators T in Banach spaces are investigated by means of the methods of geometry of Banach spaces. Necessary and sufficient conditions for bounded linear operators T to have continuous homogeneous selections for the set-valued metric generalized inverses T~ are given. The results are an answer to the problem posed by Nashed and Votruba.
基金funded by the National Natural Science Foundation of China(42176147)the Natural Science Foundation of Fujian Province of China(2021J01025)the National Key Research and Development Program of China(2018YFC1406306).
文摘Background:Previous studies have found that coastal eutrophication increases the influence of homogeneous selection on bacterial community assembly.However,whether seasonal changes affect the dominance of homogenous selection in bacterial community assembly in eutrophic bays remains unclear.Sansha Bay is an enclosed bay with ongoing eutrophication,located in the southeast coast of China.We investigated the bacterial community composition at two depths of the enclosed bay across seasons and the seasonal variation in community assembly processes.Results:Diversity analyses revealed that the bacterial community composition among seasons differed significantly.By contrast,there was little difference in the community composition between the two depths.The temperature was the key environmental factor influencing the community composition.The null model indicated that the relative importance of homogeneous selection decreased in the following order:spring>winter>autumn>summer.Homogeneous selection did not always dominate the community assembly among seasons in the eutrophic bay.The effects of pure spatial variables on the community assembly were prominent in autumn and winter.Conclusions:Our results showed the seasonal influence of eutrophication on bacterial community diversity.The seasonal variation in composition and structure of bacterial communities eclipsed the vertical variability.Eutrophication could enhance the importance of homogeneous selection in the assembly processes,but the seasonal environmental differences interfered with the steady-state maintained by ongoing eutrophication and changed the community assembly processes.Homogeneous selection was not always important in bacterial community in the eutrophic enclosed bay.The bacterial community was the most complex in summer,because the composition differed from other seasons,and the assembly process was the most intricate.These findings have contributed to understanding bacterial community composition and assembly processes in eutrophic coastal ecosystems.
基金National Natural Science Foundation of China(No.42374013)National Key Research and Development Program of China(Nos.2019YFC1509201,2021YFB3900604-03)。
文摘In the past two decades,extensive and in-depth research has been conducted on Time Series InSAR technology with the advancement of high-performance SAR satellites and the accumulation of big SAR data.The introduction of distributed scatterers in Distributed Scatterers InSAR(DS-InSAR)has significantly expanded the application scenarios of InSAR geodetic measurement by increasing the number of measurement points.This study traces the history of DS-InSAR,presents the definition and characteristics of distributed scatterers,and focuses on exploring the relationships and distinctions among proposed algorithms in two crucial steps:statistically homogeneous pixel selection and phase optimization.Additionally,the latest research progress in this field is tracked and the possible development direction in the future is discussed.Through simulation experiments and two real InSAR case studies,the proposed algorithms are compared and verified,and the advantages of DS-InSAR in deformation measurement practice are demonstrated.This work not only offers insights into current trends and focal points for theoretical research on DS-InSAR but also provides practical cases and guidance for applied research.
