This paper shows that X is uniformly non-square iff P(η_o)】0 for someη_o∈(0,2).Thus X is super-reflexive if and only if for X there exists an equivalent normwhich meets the above condition.By virtue of the before ...This paper shows that X is uniformly non-square iff P(η_o)】0 for someη_o∈(0,2).Thus X is super-reflexive if and only if for X there exists an equivalent normwhich meets the above condition.By virtue of the before mentioned result,the author derives the necessary,and suffi-cient conditions for X and l^p(X_j)being uniformly non-square,respectively,and gives acharacterization of finite-dimensional spaces which are uniformly non-square.展开更多
The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in...The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in its application,weak signals are extracted from complex,overlapping and changing information.This study focused on the stability of NIR modeling.The Orthogonal Partial Least Squares(OPLS)and Successive Projections Algorithm(SPA)eliminates noise and extracts effective spectra,and an ensemble learning method MIX-PLS,is applied to establish the model.The elastic modulus of timber is taken as an example,and 201 wood samples of three species,Xylosmacongesta(Lour.)Merr.,Acer pictum subsp.mono,and Betula pendula,samples were divided into three groups to investigate modelling performance.The results show that OPLS can preprocess the near-infrared spectroscopy information according to the target object in the face of the system error and reduce errors to minimum.SPA finally selects 13 spectral bands,simplifies the NIR spectral data and improves model accuracy.The Pearson's correlation coefficient of Calibration(Rc)and the Pearson's correlation coefficient of Prediction(Rp)of Mix Partial Least Squares(MIX-PLS)were 0.95 and 0.90,and Root Mean Square Error of Calibration(RMSEC)and Root Mean Square Error of Prediction(RMSEP)are 2.075 and 6.001,respectively,which shows the model has good generalization abilities.展开更多
This study used near-infrared(NIR)spectroscopy to predict mechanical properties of wood.NIR spectra were collected in wavelengths 900–1700 nm,and spectra averaged by radial and tangential surface spectra were used to...This study used near-infrared(NIR)spectroscopy to predict mechanical properties of wood.NIR spectra were collected in wavelengths 900–1700 nm,and spectra averaged by radial and tangential surface spectra were used to establish a partial least square(PLS)model based on correlation local embedding(CLE).Mongolian oak(Quercus mongolica Fisch.ex Ledeb.)was used to test the eff ectiveness of the model.The cross-validation method was used to verify the robustness of the CLE–PLS model.Ninety samples were tested as the calibration set and forty-fi ve as the validation set.The results show that the prediction coeffi cient of determination(R2 p)is 0.80 for MOR,and 0.78 for MOE.The ratio of performance to deviation is 2.23 for MOR and 2.15 for MOE.展开更多
This paper considers three algorithms for the extraction of square roots of complex integers {called Gaussians} using arithmetic based on complex modulus p + iq. These algorithms are almost twice as fast as the analog...This paper considers three algorithms for the extraction of square roots of complex integers {called Gaussians} using arithmetic based on complex modulus p + iq. These algorithms are almost twice as fast as the analogous algorithms extracting square roots of either real or complex integers in arithmetic based on modulus p, where is a real prime. A cryptographic system based on these algorithms is provided in this paper. A procedure reducing the computational complexity is described as well. Main results are explained in several numeric illustrations.展开更多
文摘This paper shows that X is uniformly non-square iff P(η_o)】0 for someη_o∈(0,2).Thus X is super-reflexive if and only if for X there exists an equivalent normwhich meets the above condition.By virtue of the before mentioned result,the author derives the necessary,and suffi-cient conditions for X and l^p(X_j)being uniformly non-square,respectively,and gives acharacterization of finite-dimensional spaces which are uniformly non-square.
基金supported financially by the China State Forestry Administration“948”projects(2015-4-52)Heilongjiang Natural Science Foundation(C2017005)。
文摘The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in its application,weak signals are extracted from complex,overlapping and changing information.This study focused on the stability of NIR modeling.The Orthogonal Partial Least Squares(OPLS)and Successive Projections Algorithm(SPA)eliminates noise and extracts effective spectra,and an ensemble learning method MIX-PLS,is applied to establish the model.The elastic modulus of timber is taken as an example,and 201 wood samples of three species,Xylosmacongesta(Lour.)Merr.,Acer pictum subsp.mono,and Betula pendula,samples were divided into three groups to investigate modelling performance.The results show that OPLS can preprocess the near-infrared spectroscopy information according to the target object in the face of the system error and reduce errors to minimum.SPA finally selects 13 spectral bands,simplifies the NIR spectral data and improves model accuracy.The Pearson's correlation coefficient of Calibration(Rc)and the Pearson's correlation coefficient of Prediction(Rp)of Mix Partial Least Squares(MIX-PLS)were 0.95 and 0.90,and Root Mean Square Error of Calibration(RMSEC)and Root Mean Square Error of Prediction(RMSEP)are 2.075 and 6.001,respectively,which shows the model has good generalization abilities.
基金financially supported by the China State Forestry Administration“948”projects(2015-4-52)Fundamental Research Funds for the Central Universities(2572017DB05)Heilongjiang Natural Science Foundation(C2017005)。
文摘This study used near-infrared(NIR)spectroscopy to predict mechanical properties of wood.NIR spectra were collected in wavelengths 900–1700 nm,and spectra averaged by radial and tangential surface spectra were used to establish a partial least square(PLS)model based on correlation local embedding(CLE).Mongolian oak(Quercus mongolica Fisch.ex Ledeb.)was used to test the eff ectiveness of the model.The cross-validation method was used to verify the robustness of the CLE–PLS model.Ninety samples were tested as the calibration set and forty-fi ve as the validation set.The results show that the prediction coeffi cient of determination(R2 p)is 0.80 for MOR,and 0.78 for MOE.The ratio of performance to deviation is 2.23 for MOR and 2.15 for MOE.
文摘This paper considers three algorithms for the extraction of square roots of complex integers {called Gaussians} using arithmetic based on complex modulus p + iq. These algorithms are almost twice as fast as the analogous algorithms extracting square roots of either real or complex integers in arithmetic based on modulus p, where is a real prime. A cryptographic system based on these algorithms is provided in this paper. A procedure reducing the computational complexity is described as well. Main results are explained in several numeric illustrations.
