LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional...LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional Calder´on commutator defined by T*_(Ωa)f(x):=sup_(ε>0)|∫_(|x-y|>ε)^Ω(x-y)/|x-y|^(d+1)(a(x)-a(y))f(y)dy.In this paper,the authors establish bilinear sparse domination for T*_(Ω,a) under the assumption Ω∈L∞(Sd−1).As applications,some quantitative weighted bounds for T*_(Ω,a) are obtained.展开更多
This paper considers the following Marcinkiewicz type integrals■which can be regarded as an extension of the classical Marcinkiewicz integral po introduced by Stein in[Trans Amer Math Soc,88(1958):159-172],where Ω i...This paper considers the following Marcinkiewicz type integrals■which can be regarded as an extension of the classical Marcinkiewicz integral po introduced by Stein in[Trans Amer Math Soc,88(1958):159-172],where Ω is a homogeneous function of degree zero on R^(n)with mean value zero in the unit sphere S^(n-1),Under the assumption that Ω∈L^(∞)(S^(n-1)),the authors establish the L^(q)-estimate and weak(1,1)type estimate as well as the corresponding weighted estimates for po.s with 1<q<∞ and 0<β(q-1)n/q.Moreover,the bounds do not depend on β and the strong(q,q)type and weak(1,1)type estimates for the classical Marcinkiewicz integral po can be recovered from the above estimates of μΩ,β whenβ→0.展开更多
The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects acc...The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS.展开更多
Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogen...Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.展开更多
In this paper, we shall deal with the boundedness of the Littlewood-Paley operators with rough kernel. We prove the boundedness of the Lusin-area integral μΩs and Littlewood-Paley functions μΩ and μλ^＊ on the w...In this paper, we shall deal with the boundedness of the Littlewood-Paley operators with rough kernel. We prove the boundedness of the Lusin-area integral μΩs and Littlewood-Paley functions μΩ and μλ^＊ on the weighted amalgam spaces （Lω^q,L^p）^α（R^n）as 1〈q≤α〈p≤∞.展开更多
In this paper, for the multilinear oscillatory singular integral operators TA1,A2,...Ar defined by TA1,A2,...,Arf（x） = p.v.∫R^n ^e^iP（x,y）Ω（x - y）/｜x - y｜^n＋M r∏s=1 Rms＋1（As;x,y）f（y）dy, n≥2 where P...In this paper, for the multilinear oscillatory singular integral operators TA1,A2,...Ar defined by TA1,A2,...,Arf（x） = p.v.∫R^n ^e^iP（x,y）Ω（x - y）/｜x - y｜^n＋M r∏s=1 Rms＋1（As;x,y）f（y）dy, n≥2 where P（x,y） is a nontrivial and real-valued polynomial defined on R^n×R^n,Ω（x） is homogeneous of degree zero on R^n, As（x） has derivatives of order ms in ∧βs （0〈βs〈 1）, Rms＋1 （As;x, y） denotes the （ms＋1）-st remainder of the Taylor series of As at x expended about y （s = 1, 2, ..., r）, M = ∑s^r =1 ms, the author proves that if 0 〈=β1=∑s^r=1 βs〈1,and Ω∈L^q（S^n-1） for some q 〉 1/（1 -β）, then for any p∈（1, ∞）, and some appropriate 0 〈β〈 1, TA1,A2,...,Ar, is bounded on L^P（R^n）.展开更多
This paper studies the mixed radial-angular integrability of parametric Marcinkiewicz integrals along"polynomial curves".Under the assumption that the kernels satisfy certain rather weak size conditions on t...This paper studies the mixed radial-angular integrability of parametric Marcinkiewicz integrals along"polynomial curves".Under the assumption that the kernels satisfy certain rather weak size conditions on the unit sphere with radial roughness,the authors prove that such operators are bounded on the mixed radial-angular spaces.Meanwhile,corresponding vector-valued versions are also obtained.展开更多
Let n≥2. In this paper, the author establishes the L2 (Rx)-boundedness of some oscillatory singular integrals with variable rough kernels by means of some estimates on hyper geometric functions and confluent hyper ge...Let n≥2. In this paper, the author establishes the L2 (Rx)-boundedness of some oscillatory singular integrals with variable rough kernels by means of some estimates on hyper geometric functions and confluent hyper geometric funtions.展开更多
First, the date palm kernel is used to produce granular activated carbon （GAC） by a physiochemical activation process. The process involves six steps： washing, drying, crushing, sieving, carbonization, and activati...First, the date palm kernel is used to produce granular activated carbon （GAC） by a physiochemical activation process. The process involves six steps： washing, drying, crushing, sieving, carbonization, and activation. Secondly, the ability of the produced GAC to remove pollutants is examined through batch experiments of residual chlorine adsorption whereas the equilibrium isotherm experimental data are tested for the Langmuir and Freundlich isotherms equations. Thirdly, the experimental and theoretical study of dynamic adsorption process and the effect of major operating parameters on dynamic adsorption are investigated. The results show that the Langmuir isotherm gives the best fitting to experimental data, which indicates that the residual chlorine adsorption can be characterized by mono layer adsorption behavior. The produced GAC has a great potential as an adsorbent for residual chlorine in water systems and it can compete favorably with the conventional adsorbents. The Thomas extended model with combined mass transfer resistances is used for verifying the experimental results and the results show that the proposed model coincides well with the experimental data of the dynamic adsorption process.展开更多
A graft copolymer of polyacrylonitrile （PAN） with sodium salt of partially carboxymethylated tamarind kernel powder （Na-PCMTKP, DS ^-= 0.15） was synthesized by using ceric ammonium nitrate （CAN） as a redox initi...A graft copolymer of polyacrylonitrile （PAN） with sodium salt of partially carboxymethylated tamarind kernel powder （Na-PCMTKP, DS ^-= 0.15） was synthesized by using ceric ammonium nitrate （CAN） as a redox initiator in an aqueous medium. The optimum reaction conditions for affording maximum percentage of grafting were established by successively varying reaction conditions such as concentrations of nitric acid, CAN, monomer （AN） as well as reaction time, temperature and amount of substrate. The influence of these reaction conditions on the grafting yields was discussed. The kinetic scheme of free radical graft copolymerization was proposed and the experimental results were found to agree very well with the proposed kinetic scheme. The graft copolymer （Na-PCMTKP-g-PAN, percentage of grafting G = 413.76% and percentage of grafting efficiency GE = 96.48%） sample synthesized under the established optimized reaction conditions was hydrolyzed by 0.7 mol-L l NaOH solution at 90-95 ℃ to yield the superabsorbent hydrogel, H-Na-PCMTKP-g-PAN. The swelling behavior of the hydrogel was studied by carrying out its absorbency measurements in low conductivity water, 0.15 mol·L^-1 salt （NaCl, CaCl2 and AlCl3） solutions and simulated urine （SU） solution at different timings. FTIR, TGA and SEM techniques were used to characterize the products.展开更多
In this article, we consider a fast algorithm for first generation Calderon-Zygmund operators. First, we estimate the convergence speed of the relative approximation algorithm. Then, we establish the continuity on Bes...In this article, we consider a fast algorithm for first generation Calderon-Zygmund operators. First, we estimate the convergence speed of the relative approximation algorithm. Then, we establish the continuity on Besov spaces and Triebel-Lizorkin spaces for the oper- ators with rough kernel.展开更多
In this paper,the boundedness of the multilinear operators with rough kernel on the Herz-type spaces is discussed.It is proved that M A,Ω,T A,Ω are bounded on α,p q(Rn) while Mλ A,Ω,TL A,Ω are bou...In this paper,the boundedness of the multilinear operators with rough kernel on the Herz-type spaces is discussed.It is proved that M A,Ω,T A,Ω are bounded on α,p q(Rn) while Mλ A,Ω,TL A,Ω are bounded from α,p 1 q 1(Rn) to α,p 2 q 2(Rn),respectively.展开更多
In this paper, we will prove the Triebel-Lizorkin boundedness for some oscillatory singular integrals with the kernel （x） satisfying a condition introduced by Grafakos and Stefanov. Our theorems will be proved under...In this paper, we will prove the Triebel-Lizorkin boundedness for some oscillatory singular integrals with the kernel （x） satisfying a condition introduced by Grafakos and Stefanov. Our theorems will be proved under various conditions on the phase function, radial and nonradial. Since the L p boundedness of these operators is not complete yet, the theorems extend many known results.展开更多
A new algorithm for linear instantaneous independent component analysis is proposed based on maximizing the log-likelihood contrast function which can be changed into a gradient equation.An iterative method is introdu...A new algorithm for linear instantaneous independent component analysis is proposed based on maximizing the log-likelihood contrast function which can be changed into a gradient equation.An iterative method is introduced to solve this equation efficiently.The unknown probability density functions as well as their first and second derivatives in the gradient equation are estimated by kernel density method.Computer simulations on artificially generated signals and gray scale natural scene images confirm the efficiency and accuracy of the proposed algorithm.展开更多
The Fourier transform and the Littlewood-Paley theory are used to give the weighted boundedness of a strongly singular integral operator defined in this paper. The paper shows that the strongly singular integral opera...The Fourier transform and the Littlewood-Paley theory are used to give the weighted boundedness of a strongly singular integral operator defined in this paper. The paper shows that the strongly singular integral operator is bounded from the Sobolev space to the Lebesgue space.展开更多
This paper is concerning the commutators generated by the multilinear singular integral with rough kernels and BMO functions. The boundedness of the multilinear commutators Tb→ （f→） is established on the Morrey-He...This paper is concerning the commutators generated by the multilinear singular integral with rough kernels and BMO functions. The boundedness of the multilinear commutators Tb→ （f→） is established on the Morrey-Herz space by using the John-Nirenberg inequality.展开更多
The problem of classification in situations where the assumption of normality in the data is violated, and there are non-linear clustered structures in the dataset is addressed. A robust nonparametric kernel discrimin...The problem of classification in situations where the assumption of normality in the data is violated, and there are non-linear clustered structures in the dataset is addressed. A robust nonparametric kernel discriminant classification function, which is able to address this challenge, has been developed and the misclassification rates computed for various bandwidth matrices. A comparison with existing parametric classification functions such as the linear discriminant and quadratic discriminant is conducted to evaluate the performance of this classification function using simulated datasets. The results presented in this paper show good performance in terms of misclassification rates for the kernel discriminant classifier when the correct bandwidth is selected as compared to other identified existing classifiers. In this regard, the study recommends the use of the proposed kernel discriminant classification rule when one wishes to classify units into one of several categories or population groups where parametric classifiers might not be applicable.展开更多
A support vector machine time series forecasting model based on rough set data preprocessing was proposed by combining rough set attribute reduction and support vector machine regression algorithm. First, remove the r...A support vector machine time series forecasting model based on rough set data preprocessing was proposed by combining rough set attribute reduction and support vector machine regression algorithm. First, remove the redundant attribute for forecasting from condition attribute by rough set method; then use the minimum condition attribute set obtained after the reduction and the corresponding initial data, reform a new training sample set which only retain the important attributes influencing the forecasting accuracy; study and train the support vector machine with the training sample obtained after reduction, and then input the reformed testing sample set according to the minimum condition attribute and corresponding initial data. The model was tested and the mapping relation was got between the condition attribute and forecasting variable. Eventually, power supply and demand were forecasted in this model. The average absolute error rates of power consumption of the whole society and yearly maximum load are respectively 14.21% and 13.23%. It shows that RS-SVM time series forecasting model has high forecasting accuracy.展开更多
In this paper,copy-move forgery in image is detected for single image with multiple manipulations such as blurring,noise addition,gray scale conver-sion,brightness modifications,rotation,Hu adjustment,color adjustment,...In this paper,copy-move forgery in image is detected for single image with multiple manipulations such as blurring,noise addition,gray scale conver-sion,brightness modifications,rotation,Hu adjustment,color adjustment,contrast changes and JPEG Compression.However,traditional algorithms detect only copy-move attacks in image and never for different manipulation in single image.The proposed LLP(Laterally linked pixel)algorithm has two dimensional arrays and single layer is obtained through unit linking pulsed neural network for detec-tion of copied region and kernel tricks is applied for detection of multiple manip-ulations in single forged image.LLP algorithm consists of two channels such as feeding component(F-Channel)and linking component(L channel)for linking pixels.LLP algorithm linking pixels detects image with multiple manipulation and copy-move forgery due to one-to-one correspondence between pixel and neu-ron,where each pixel’s intensity is taken as input for F channel of neuron and connected for forgery identification.Furthermore,neuron is connected with neighboringfield of neuron by L channel for detecting forged images with multi-ple manipulations in the image along with copy-move,through kernel trick clas-sifier(KTC).From experimental results,proposed LLP algorithm performs better than traditional algorithms for multiple manipulated copy and paste images.The accuracy obtained through LLP algorithm is about 90%and further forgery detec-tion is improved based on optimized kernel selections in classification algorithm.展开更多
Statelessness is the absence of any Nationality. These include the Pemba, Shona, Galjeel, people of Burundi and Rwanda descent, and children born in Kenya to British Overseas Citizens after 1983. Frequently, they are ...Statelessness is the absence of any Nationality. These include the Pemba, Shona, Galjeel, people of Burundi and Rwanda descent, and children born in Kenya to British Overseas Citizens after 1983. Frequently, they are not only undocumented but also often overlooked and not included in National Administrative Registers. Accordingly, find it hard to participate in Social and Economic Affairs. There has been a major push by UNHCR and international partners to “map” the size of stateless populations and their demographic profile, as well as causes, potential solutions and human rights situation. One of the requirements by the UNHCR in their push is for countries to find a potential solution to statelessness which starts with classifying/associating a person from these communities to a particular local community that is recognized in Kenya. This paper addresses this problem by adopting a Robust Nonparametric Kernel Discriminant function to correctly classify the stateless communities in Kenya and compare the performance of this method with the existing techniques through their classification rates. This is because Non-parametric functions have proven to be more robust and useful especially when there exists auxiliary information which can be used to increase precision. The findings from this paper indicate that Nonparametric discriminant classifiers provide a good classification method for classifying the stateless communities in Kenya. This is because they exhibit lower classification rates compared to the parametric methods such as Linear and Quadratic discriminant functions. In addition, the finding shows that based on certain similarities in characteristics that exist in these communities that surround the Pemba Community, the Pemba community can be classified as Giriama or Rabai in which they seem to have a strong link. In this regard, the study recommends the use of the Kernel discriminant classifiers in classifying the stateless persons and that the Government of Kenya consider integrating/recognizing the Pemba community into Giriama or Rabai so that they can be issued with the National Identification Cards and be recognized as Kenyans.展开更多
文摘LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional Calder´on commutator defined by T*_(Ωa)f(x):=sup_(ε>0)|∫_(|x-y|>ε)^Ω(x-y)/|x-y|^(d+1)(a(x)-a(y))f(y)dy.In this paper,the authors establish bilinear sparse domination for T*_(Ω,a) under the assumption Ω∈L∞(Sd−1).As applications,some quantitative weighted bounds for T*_(Ω,a) are obtained.
文摘This paper considers the following Marcinkiewicz type integrals■which can be regarded as an extension of the classical Marcinkiewicz integral po introduced by Stein in[Trans Amer Math Soc,88(1958):159-172],where Ω is a homogeneous function of degree zero on R^(n)with mean value zero in the unit sphere S^(n-1),Under the assumption that Ω∈L^(∞)(S^(n-1)),the authors establish the L^(q)-estimate and weak(1,1)type estimate as well as the corresponding weighted estimates for po.s with 1<q<∞ and 0<β(q-1)n/q.Moreover,the bounds do not depend on β and the strong(q,q)type and weak(1,1)type estimates for the classical Marcinkiewicz integral po can be recovered from the above estimates of μΩ,β whenβ→0.
基金supported by the China Agriculture Research System of MOF and MARAthe National Natural Science Foundation of China (31872337 and 31501919)the Agricultural Science and Technology Innovation Project,China (ASTIP-IAS02)。
文摘The advantages of genome selection(GS) in animal and plant breeding are self-evident.Traditional parametric models have disadvantage in better fit the increasingly large sequencing data and capture complex effects accurately.Machine learning models have demonstrated remarkable potential in addressing these challenges.In this study,we introduced the concept of mixed kernel functions to explore the performance of support vector machine regression(SVR) in GS.Six single kernel functions(SVR_L,SVR_C,SVR_G,SVR_P,SVR_S,SVR_L) and four mixed kernel functions(SVR_GS,SVR_GP,SVR_LS,SVR_LP) were used to predict genome breeding values.The prediction accuracy,mean squared error(MSE) and mean absolute error(MAE) were used as evaluation indicators to compare with two traditional parametric models(GBLUP,BayesB) and two popular machine learning models(RF,KcRR).The results indicate that in most cases,the performance of the mixed kernel function model significantly outperforms that of GBLUP,BayesB and single kernel function.For instance,for T1 in the pig dataset,the predictive accuracy of SVR_GS is improved by 10% compared to GBLUP,and by approximately 4.4 and 18.6% compared to SVR_G and SVR_S respectively.For E1 in the wheat dataset,SVR_GS achieves 13.3% higher prediction accuracy than GBLUP.Among single kernel functions,the Laplacian and Gaussian kernel functions yield similar results,with the Gaussian kernel function performing better.The mixed kernel function notably reduces the MSE and MAE when compared to all single kernel functions.Furthermore,regarding runtime,SVR_GS and SVR_GP mixed kernel functions run approximately three times faster than GBLUP in the pig dataset,with only a slight increase in runtime compared to the single kernel function model.In summary,the mixed kernel function model of SVR demonstrates speed and accuracy competitiveness,and the model such as SVR_GS has important application potential for GS.
基金supported by the National Natural Science Foundation of China (Nos.42422705,42207175,42177117 and 42577170)the Ningbo Youth Leading Talent Project (No.2024QL051)+1 种基金the Chinese Academy of Engineering Science and Technology Strategy Consulting Project (No.2025-XZ-57)the Central Government Funding Program for Guiding Local Science and Technology Development (No.2025ZY01028)。
文摘Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.
基金supported in part by National Natural Foundation of China (Grant No. 11161042 and No. 11071250)
文摘In this paper, we shall deal with the boundedness of the Littlewood-Paley operators with rough kernel. We prove the boundedness of the Lusin-area integral μΩs and Littlewood-Paley functions μΩ and μλ^＊ on the weighted amalgam spaces （Lω^q,L^p）^α（R^n）as 1〈q≤α〈p≤∞.
文摘In this paper, for the multilinear oscillatory singular integral operators TA1,A2,...Ar defined by TA1,A2,...,Arf（x） = p.v.∫R^n ^e^iP（x,y）Ω（x - y）/｜x - y｜^n＋M r∏s=1 Rms＋1（As;x,y）f（y）dy, n≥2 where P（x,y） is a nontrivial and real-valued polynomial defined on R^n×R^n,Ω（x） is homogeneous of degree zero on R^n, As（x） has derivatives of order ms in ∧βs （0〈βs〈 1）, Rms＋1 （As;x, y） denotes the （ms＋1）-st remainder of the Taylor series of As at x expended about y （s = 1, 2, ..., r）, M = ∑s^r =1 ms, the author proves that if 0 〈=β1=∑s^r=1 βs〈1,and Ω∈L^q（S^n-1） for some q 〉 1/（1 -β）, then for any p∈（1, ∞）, and some appropriate 0 〈β〈 1, TA1,A2,...,Ar, is bounded on L^P（R^n）.
基金supported by the NSFC(11771358,11701333,11871101)。
文摘This paper studies the mixed radial-angular integrability of parametric Marcinkiewicz integrals along"polynomial curves".Under the assumption that the kernels satisfy certain rather weak size conditions on the unit sphere with radial roughness,the authors prove that such operators are bounded on the mixed radial-angular spaces.Meanwhile,corresponding vector-valued versions are also obtained.
基金Dachun Yang was supported by the Croucher Foundation Chinese Visitorships 1999-2000 of Hong Kong and me NNSF(19131080)of China
文摘Let n≥2. In this paper, the author establishes the L2 (Rx)-boundedness of some oscillatory singular integrals with variable rough kernels by means of some estimates on hyper geometric functions and confluent hyper geometric funtions.
基金The National Natural Science Foundation of China(No. 51078074)
文摘First, the date palm kernel is used to produce granular activated carbon （GAC） by a physiochemical activation process. The process involves six steps： washing, drying, crushing, sieving, carbonization, and activation. Secondly, the ability of the produced GAC to remove pollutants is examined through batch experiments of residual chlorine adsorption whereas the equilibrium isotherm experimental data are tested for the Langmuir and Freundlich isotherms equations. Thirdly, the experimental and theoretical study of dynamic adsorption process and the effect of major operating parameters on dynamic adsorption are investigated. The results show that the Langmuir isotherm gives the best fitting to experimental data, which indicates that the residual chlorine adsorption can be characterized by mono layer adsorption behavior. The produced GAC has a great potential as an adsorbent for residual chlorine in water systems and it can compete favorably with the conventional adsorbents. The Thomas extended model with combined mass transfer resistances is used for verifying the experimental results and the results show that the proposed model coincides well with the experimental data of the dynamic adsorption process.
文摘A graft copolymer of polyacrylonitrile （PAN） with sodium salt of partially carboxymethylated tamarind kernel powder （Na-PCMTKP, DS ^-= 0.15） was synthesized by using ceric ammonium nitrate （CAN） as a redox initiator in an aqueous medium. The optimum reaction conditions for affording maximum percentage of grafting were established by successively varying reaction conditions such as concentrations of nitric acid, CAN, monomer （AN） as well as reaction time, temperature and amount of substrate. The influence of these reaction conditions on the grafting yields was discussed. The kinetic scheme of free radical graft copolymerization was proposed and the experimental results were found to agree very well with the proposed kinetic scheme. The graft copolymer （Na-PCMTKP-g-PAN, percentage of grafting G = 413.76% and percentage of grafting efficiency GE = 96.48%） sample synthesized under the established optimized reaction conditions was hydrolyzed by 0.7 mol-L l NaOH solution at 90-95 ℃ to yield the superabsorbent hydrogel, H-Na-PCMTKP-g-PAN. The swelling behavior of the hydrogel was studied by carrying out its absorbency measurements in low conductivity water, 0.15 mol·L^-1 salt （NaCl, CaCl2 and AlCl3） solutions and simulated urine （SU） solution at different timings. FTIR, TGA and SEM techniques were used to characterize the products.
基金Supported by NNSF of China(11271209,1137105,11571261)and SRFDP(20130003110003)
文摘In this article, we consider a fast algorithm for first generation Calderon-Zygmund operators. First, we estimate the convergence speed of the relative approximation algorithm. Then, we establish the continuity on Besov spaces and Triebel-Lizorkin spaces for the oper- ators with rough kernel.
基金Supported by the National Natural Science Foundation of China( 1 9631 0 80,1 9971 0 1 0 ) ,the973terms:( 1 9990 75 1 0 5 ) and the Natural Science Foundation of the Zhejiang Province( RC971 0 7)
文摘In this paper,the boundedness of the multilinear operators with rough kernel on the Herz-type spaces is discussed.It is proved that M A,Ω,T A,Ω are bounded on α,p q(Rn) while Mλ A,Ω,TL A,Ω are bounded from α,p 1 q 1(Rn) to α,p 2 q 2(Rn),respectively.
基金Supported by the National Natural Science Foundation of China (11026104, 11201103, 11226108)
文摘In this paper, we will prove the Triebel-Lizorkin boundedness for some oscillatory singular integrals with the kernel （x） satisfying a condition introduced by Grafakos and Stefanov. Our theorems will be proved under various conditions on the phase function, radial and nonradial. Since the L p boundedness of these operators is not complete yet, the theorems extend many known results.
文摘A new algorithm for linear instantaneous independent component analysis is proposed based on maximizing the log-likelihood contrast function which can be changed into a gradient equation.An iterative method is introduced to solve this equation efficiently.The unknown probability density functions as well as their first and second derivatives in the gradient equation are estimated by kernel density method.Computer simulations on artificially generated signals and gray scale natural scene images confirm the efficiency and accuracy of the proposed algorithm.
基金Project supported by the National Natural Science Foundation of China (No. 10771110)the Major Project of the Ministry of Education of China (No. 309018)
文摘The Fourier transform and the Littlewood-Paley theory are used to give the weighted boundedness of a strongly singular integral operator defined in this paper. The paper shows that the strongly singular integral operator is bounded from the Sobolev space to the Lebesgue space.
基金supported by the China National Natural Since Foundation (11161042, 11071250)
文摘This paper is concerning the commutators generated by the multilinear singular integral with rough kernels and BMO functions. The boundedness of the multilinear commutators Tb→ （f→） is established on the Morrey-Herz space by using the John-Nirenberg inequality.
文摘The problem of classification in situations where the assumption of normality in the data is violated, and there are non-linear clustered structures in the dataset is addressed. A robust nonparametric kernel discriminant classification function, which is able to address this challenge, has been developed and the misclassification rates computed for various bandwidth matrices. A comparison with existing parametric classification functions such as the linear discriminant and quadratic discriminant is conducted to evaluate the performance of this classification function using simulated datasets. The results presented in this paper show good performance in terms of misclassification rates for the kernel discriminant classifier when the correct bandwidth is selected as compared to other identified existing classifiers. In this regard, the study recommends the use of the proposed kernel discriminant classification rule when one wishes to classify units into one of several categories or population groups where parametric classifiers might not be applicable.
基金Project(70373017) supported by the National Natural Science Foundation of China
文摘A support vector machine time series forecasting model based on rough set data preprocessing was proposed by combining rough set attribute reduction and support vector machine regression algorithm. First, remove the redundant attribute for forecasting from condition attribute by rough set method; then use the minimum condition attribute set obtained after the reduction and the corresponding initial data, reform a new training sample set which only retain the important attributes influencing the forecasting accuracy; study and train the support vector machine with the training sample obtained after reduction, and then input the reformed testing sample set according to the minimum condition attribute and corresponding initial data. The model was tested and the mapping relation was got between the condition attribute and forecasting variable. Eventually, power supply and demand were forecasted in this model. The average absolute error rates of power consumption of the whole society and yearly maximum load are respectively 14.21% and 13.23%. It shows that RS-SVM time series forecasting model has high forecasting accuracy.
文摘In this paper,copy-move forgery in image is detected for single image with multiple manipulations such as blurring,noise addition,gray scale conver-sion,brightness modifications,rotation,Hu adjustment,color adjustment,contrast changes and JPEG Compression.However,traditional algorithms detect only copy-move attacks in image and never for different manipulation in single image.The proposed LLP(Laterally linked pixel)algorithm has two dimensional arrays and single layer is obtained through unit linking pulsed neural network for detec-tion of copied region and kernel tricks is applied for detection of multiple manip-ulations in single forged image.LLP algorithm consists of two channels such as feeding component(F-Channel)and linking component(L channel)for linking pixels.LLP algorithm linking pixels detects image with multiple manipulation and copy-move forgery due to one-to-one correspondence between pixel and neu-ron,where each pixel’s intensity is taken as input for F channel of neuron and connected for forgery identification.Furthermore,neuron is connected with neighboringfield of neuron by L channel for detecting forged images with multi-ple manipulations in the image along with copy-move,through kernel trick clas-sifier(KTC).From experimental results,proposed LLP algorithm performs better than traditional algorithms for multiple manipulated copy and paste images.The accuracy obtained through LLP algorithm is about 90%and further forgery detec-tion is improved based on optimized kernel selections in classification algorithm.
文摘Statelessness is the absence of any Nationality. These include the Pemba, Shona, Galjeel, people of Burundi and Rwanda descent, and children born in Kenya to British Overseas Citizens after 1983. Frequently, they are not only undocumented but also often overlooked and not included in National Administrative Registers. Accordingly, find it hard to participate in Social and Economic Affairs. There has been a major push by UNHCR and international partners to “map” the size of stateless populations and their demographic profile, as well as causes, potential solutions and human rights situation. One of the requirements by the UNHCR in their push is for countries to find a potential solution to statelessness which starts with classifying/associating a person from these communities to a particular local community that is recognized in Kenya. This paper addresses this problem by adopting a Robust Nonparametric Kernel Discriminant function to correctly classify the stateless communities in Kenya and compare the performance of this method with the existing techniques through their classification rates. This is because Non-parametric functions have proven to be more robust and useful especially when there exists auxiliary information which can be used to increase precision. The findings from this paper indicate that Nonparametric discriminant classifiers provide a good classification method for classifying the stateless communities in Kenya. This is because they exhibit lower classification rates compared to the parametric methods such as Linear and Quadratic discriminant functions. In addition, the finding shows that based on certain similarities in characteristics that exist in these communities that surround the Pemba Community, the Pemba community can be classified as Giriama or Rabai in which they seem to have a strong link. In this regard, the study recommends the use of the Kernel discriminant classifiers in classifying the stateless persons and that the Government of Kenya consider integrating/recognizing the Pemba community into Giriama or Rabai so that they can be issued with the National Identification Cards and be recognized as Kenyans.
