The X-ray low angle reflectivity measurement is used to investigate single and bilayer films to determine the parameters of nanometer-scale structures,three effectual methods are presented by using X-ray reflectivity ...The X-ray low angle reflectivity measurement is used to investigate single and bilayer films to determine the parameters of nanometer-scale structures,three effectual methods are presented by using X-ray reflectivity analysis to provide an accurate estimation of the nanometer film structures. The parameters of tungsten (W) single layer, such as the material density, interface roughness and deposition rate, were obtained easily and speedily. The base metal layer was introduced to measure the profiles of single low Z material film. A 0.3 nm chromium (Cr) film was also studied by low angle reflectivity analysis.展开更多
According to the simulation of nitrogen sorption process in porous media with three-dimensional network model, and the analysis for such a process with percolation theory, a new method is proposed to determine a pore ...According to the simulation of nitrogen sorption process in porous media with three-dimensional network model, and the analysis for such a process with percolation theory, a new method is proposed to determine a pore structure parameter--mean coordination number of pore network, which represents the connectivity among a great number of pores. Here the 'chamber-throat' model and the Weibull distribution are used to describe the pore geometry and the pore size distribution respectively. This method is based on the scaling law of percolation theory after both effects of sorption thermodynamics and pore size on the sorption hysteresis loops are considered. The results show that it is an effective procedure to calculate the mean coordination number for micro- and meso-porous media.展开更多
Principal Component Analysis(PCA) can simplify the structure of database by replacing multi-dimensional parameters with relatively less comprehensive variables in order to ensure the minimum lost in initial data.In th...Principal Component Analysis(PCA) can simplify the structure of database by replacing multi-dimensional parameters with relatively less comprehensive variables in order to ensure the minimum lost in initial data.In this paper,eighteen black soil samples from different sites were tested and thirteen distinctive indexes were chosen to evaluate the degeneration of black soil.By using principal component analysis,variables of thirteen dimensions can be diminished to six unrelated principal indexes.Analysis shows that the soluble salt content,Fulvic acids(FA) and aggregation degree have a high weighing coefficient,indicating these three indexes are the major parts for the evaluation of black soil degradation.It also provides a new path to the degenerated black soil treatment in Northeast China.展开更多
This paper in the light of the structure parameters of the ramie fabric to research and evaluation it＇s heart-moisture comfort. Selected 15 kinds of ramie fabric to test the average density, the thickness, the tightn...This paper in the light of the structure parameters of the ramie fabric to research and evaluation it＇s heart-moisture comfort. Selected 15 kinds of ramie fabric to test the average density, the thickness, the tightness, the heat rate, the heat transfer coefficient, the Clo, the air permeability, the water vapor permeability and other performance index, used SPSS factor analysis to explore the main influence factors of porous ramie fabric＇s heat moisture comfort. Results shows that： the main influence factors of ramie fabric＇s heat-moisture is the heat preservation material, the air permeability and the moisture permeability, get the equation of porous ramie fabric＇ s heat-moisture comfort： F=0.45855y1＋0.30588y2＋0.13549y3, evaluated and sorted the sample fabric＇ s heat-moisture comfort.展开更多
Deep neural networks(DNNs)are effective in solving both forward and inverse problems for nonlinear partial differential equations(PDEs).However,conventional DNNs are not effective in handling problems such as delay di...Deep neural networks(DNNs)are effective in solving both forward and inverse problems for nonlinear partial differential equations(PDEs).However,conventional DNNs are not effective in handling problems such as delay differential equations(DDEs)and delay integrodifferential equations(DIDEs)with constant delays,primarily due to their low regularity at delayinduced breaking points.In this paper,a DNN method that combines multi-task learning(MTL)which is proposed to solve both the forward and inverse problems of DIDEs.The core idea of this approach is to divide the original equation into multiple tasks based on the delay,using auxiliary outputs to represent the integral terms,followed by the use of MTL to seamlessly incorporate the properties at the breaking points into the loss function.Furthermore,given the increased training dificulty associated with multiple tasks and outputs,we employ a sequential training scheme to reduce training complexity and provide reference solutions for subsequent tasks.This approach significantly enhances the approximation accuracy of solving DIDEs with DNNs,as demonstrated by comparisons with traditional DNN methods.We validate the effectiveness of this method through several numerical experiments,test various parameter sharing structures in MTL and compare the testing results of these structures.Finally,this method is implemented to solve the inverse problem of nonlinear DIDE and the results show that the unknown parameters of DIDE can be discovered with sparse or noisy data.展开更多
Groebner basis theory for parametric polynomial ideals is explored with the main objec- tive of nfinicking the Groebner basis theory for ideals. Given a parametric polynomial ideal, its basis is a comprehensive GrSbne...Groebner basis theory for parametric polynomial ideals is explored with the main objec- tive of nfinicking the Groebner basis theory for ideals. Given a parametric polynomial ideal, its basis is a comprehensive GrSbner basis if and only if for every specialization of its parameters in a given field, the specialization of the basis is a GrSbnerbasis of the associated specialized polynomial ideal. For various specializations of parameters, structure of specialized ideals becomes qualitatively different even though there are significant relationships as well because of finiteness properties. Key concepts foundational to GrSbner basis theory are reexamined and/or further developed for the parametric case： （i） Definition of a comprehensive Groebner basis, （ii） test for a comprehensive GrSbner basis, （iii） parameterized rewriting, （iv） S-polynomials among parametric polynomials, （v） completion algorithm for directly computing a comprehensive Groebner basis from a given basis of a parametric ideal. Elegant properties of Groebner bases in the classical ideal theory, such as for a fixed admissible term ordering, a unique GrSbner basis can be associated with every polynomial ideal as well as that such a basis can be computed from any Groebner basis of an ideal, turn out to be a major challenge to generalize for parametric ideals; issues related to these investigations are explored. A prototype implementation of the algorithm has been successfully tried on many examples from the literature.展开更多
A new structural parameter of shelterbelts, above-ground density of biomass volume, was putforward in this paper. Its practicality in managements of the shelterbelts and its physical meaning of windreduction were expo...A new structural parameter of shelterbelts, above-ground density of biomass volume, was putforward in this paper. Its practicality in managements of the shelterbelts and its physical meaning of windreduction were expounded. Analytical relations between the new parameter and often-used parameters(permeability and porosity) were deduced. An example was given to show the application of the newparameter in the management of shelterbelts.展开更多
基金This work was supported by the National Natural Science Foun-dation of China(10435050,60378021)the National 863-804Sustentation Fund(2006AA12Z139)+2 种基金the Program for New Cen-tury Excellent Talents in University(NCET-04-037)the RoyalSociety,London(NC/China/16660)Tongji University scien-tific fund.
文摘The X-ray low angle reflectivity measurement is used to investigate single and bilayer films to determine the parameters of nanometer-scale structures,three effectual methods are presented by using X-ray reflectivity analysis to provide an accurate estimation of the nanometer film structures. The parameters of tungsten (W) single layer, such as the material density, interface roughness and deposition rate, were obtained easily and speedily. The base metal layer was introduced to measure the profiles of single low Z material film. A 0.3 nm chromium (Cr) film was also studied by low angle reflectivity analysis.
基金Supported by the National Natural Science Foundation of China(No.29776038).
文摘According to the simulation of nitrogen sorption process in porous media with three-dimensional network model, and the analysis for such a process with percolation theory, a new method is proposed to determine a pore structure parameter--mean coordination number of pore network, which represents the connectivity among a great number of pores. Here the 'chamber-throat' model and the Weibull distribution are used to describe the pore geometry and the pore size distribution respectively. This method is based on the scaling law of percolation theory after both effects of sorption thermodynamics and pore size on the sorption hysteresis loops are considered. The results show that it is an effective procedure to calculate the mean coordination number for micro- and meso-porous media.
基金Supported by College Students Innovation Experiment Plan of Jilin University(No.2009A63066)the National Natural Science Foundation of China (No.406721800)the International Cooperation Projects of National Natural Science Funds(No.40911120044)
文摘Principal Component Analysis(PCA) can simplify the structure of database by replacing multi-dimensional parameters with relatively less comprehensive variables in order to ensure the minimum lost in initial data.In this paper,eighteen black soil samples from different sites were tested and thirteen distinctive indexes were chosen to evaluate the degeneration of black soil.By using principal component analysis,variables of thirteen dimensions can be diminished to six unrelated principal indexes.Analysis shows that the soluble salt content,Fulvic acids(FA) and aggregation degree have a high weighing coefficient,indicating these three indexes are the major parts for the evaluation of black soil degradation.It also provides a new path to the degenerated black soil treatment in Northeast China.
文摘This paper in the light of the structure parameters of the ramie fabric to research and evaluation it＇s heart-moisture comfort. Selected 15 kinds of ramie fabric to test the average density, the thickness, the tightness, the heat rate, the heat transfer coefficient, the Clo, the air permeability, the water vapor permeability and other performance index, used SPSS factor analysis to explore the main influence factors of porous ramie fabric＇s heat moisture comfort. Results shows that： the main influence factors of ramie fabric＇s heat-moisture is the heat preservation material, the air permeability and the moisture permeability, get the equation of porous ramie fabric＇ s heat-moisture comfort： F=0.45855y1＋0.30588y2＋0.13549y3, evaluated and sorted the sample fabric＇ s heat-moisture comfort.
文摘Deep neural networks(DNNs)are effective in solving both forward and inverse problems for nonlinear partial differential equations(PDEs).However,conventional DNNs are not effective in handling problems such as delay differential equations(DDEs)and delay integrodifferential equations(DIDEs)with constant delays,primarily due to their low regularity at delayinduced breaking points.In this paper,a DNN method that combines multi-task learning(MTL)which is proposed to solve both the forward and inverse problems of DIDEs.The core idea of this approach is to divide the original equation into multiple tasks based on the delay,using auxiliary outputs to represent the integral terms,followed by the use of MTL to seamlessly incorporate the properties at the breaking points into the loss function.Furthermore,given the increased training dificulty associated with multiple tasks and outputs,we employ a sequential training scheme to reduce training complexity and provide reference solutions for subsequent tasks.This approach significantly enhances the approximation accuracy of solving DIDEs with DNNs,as demonstrated by comparisons with traditional DNN methods.We validate the effectiveness of this method through several numerical experiments,test various parameter sharing structures in MTL and compare the testing results of these structures.Finally,this method is implemented to solve the inverse problem of nonlinear DIDE and the results show that the unknown parameters of DIDE can be discovered with sparse or noisy data.
基金supported by the National Science Foundation under Grant No.DMS-1217054
文摘Groebner basis theory for parametric polynomial ideals is explored with the main objec- tive of nfinicking the Groebner basis theory for ideals. Given a parametric polynomial ideal, its basis is a comprehensive GrSbner basis if and only if for every specialization of its parameters in a given field, the specialization of the basis is a GrSbnerbasis of the associated specialized polynomial ideal. For various specializations of parameters, structure of specialized ideals becomes qualitatively different even though there are significant relationships as well because of finiteness properties. Key concepts foundational to GrSbner basis theory are reexamined and/or further developed for the parametric case： （i） Definition of a comprehensive Groebner basis, （ii） test for a comprehensive GrSbner basis, （iii） parameterized rewriting, （iv） S-polynomials among parametric polynomials, （v） completion algorithm for directly computing a comprehensive Groebner basis from a given basis of a parametric ideal. Elegant properties of Groebner bases in the classical ideal theory, such as for a fixed admissible term ordering, a unique GrSbner basis can be associated with every polynomial ideal as well as that such a basis can be computed from any Groebner basis of an ideal, turn out to be a major challenge to generalize for parametric ideals; issues related to these investigations are explored. A prototype implementation of the algorithm has been successfully tried on many examples from the literature.
基金Supported by the Doctorial Foundation of Liaoning province and the Project of Institute of Applied Ecology, Chinese Academy ofSciences.
文摘A new structural parameter of shelterbelts, above-ground density of biomass volume, was putforward in this paper. Its practicality in managements of the shelterbelts and its physical meaning of windreduction were expounded. Analytical relations between the new parameter and often-used parameters(permeability and porosity) were deduced. An example was given to show the application of the newparameter in the management of shelterbelts.
