Background: Components of height have been found to be positively associated with blood pressure (BP) both in developed and developing nations. However, amongst Cameroon secondary school adolescents, the relationship ...Background: Components of height have been found to be positively associated with blood pressure (BP) both in developed and developing nations. However, amongst Cameroon secondary school adolescents, the relationship between heights, SH and SH/H with BP has rarely been studied. The purpose of this study was to determine the proportion of secondary school adolescents with elevated BP and high BP and to evaluate the relationship between the different components of linear growth with BP. Methods: An institution-based cross-sectional study involving 602 adolescents (399 girls and 203 boys, mean age 14.9 ± 2.3 years) attending some public and private secondary schools in the Bamenda municipality of the North West Region of Cameroon. Anthropometric and BP measurements were carried out following standard procedures. Pearson correlation and linear regression were used to determine the relationship between the various components of height (height, SH, SH/H) with BP amongst the children. Results: The overall prevalence of elevated BP and hypertension amongst the study participants was 21.9% and 15.6% respectively (with 8.3% and 7.3% of the hypertensive children in Stage I and Stage II respectively). However, there were no significant gender differences in the prevalence of elevated BP and high BP (p = 0.497). Girls had a significantly (p Conclusion: This study has demonstrated that height was positively associated with SBP amongst children and adolescents. Thus, height can be used in predicting adolescents with a high risk of developing high BP in our setting.展开更多
The problem of stability for singular systems with two additive time-varying delay components is investigated. By constructing a simple type of Lyapunov-Krasovskii functional and utilizing free matrix variables in app...The problem of stability for singular systems with two additive time-varying delay components is investigated. By constructing a simple type of Lyapunov-Krasovskii functional and utilizing free matrix variables in approximating certain integral quadratic terms, a delay-dependent stability criterion is established for the considered systems to be regular, impulse free, and stable in terms of linear matrix inequalities （LMIs）. Based on this criterion, some new stability conditions for singular systems with a single delay in a range and regular systems with two additive time-varying delay components are proposed. These developed results have advantages over some previous ones in that they have fewer matrix variables yet less conservatism. Finally, two numerical examples are employed to illustrate the effectiveness of the obtained theoretical results.展开更多
Background: Although abduction of the acetabular component is considered to predict factors for polyethylene wear attributable to osteolysis, other radiographic factors have yet to be elucidated. The purpose of the pr...Background: Although abduction of the acetabular component is considered to predict factors for polyethylene wear attributable to osteolysis, other radiographic factors have yet to be elucidated. The purpose of the present study was to evaluate whether anteversion or change in implantation angle of the acetabular component influences polyethylene linear wear by using standing and supine radiographs of the hip joint. Methods: Standing and supine plain anteroposterior radiographs of 62 hip joints in which cementless total hip arthroplasty was performed were examined for polyethylene linear wear rate (mm/year), pelvic inclination, and radiological inclination and anatomic anteversion of the acetabular component. Results: All correlation coefficients of measurements of polyethylene linear wear, pelvic inclination angle, anatomical anteversion angle and radiological inclination angle were calculated highly. And by the three-dimensional numerical analysis, anatomic anteversion of the acetabular component had at least some effect on the degree of polyethylene wear. Conclusion: This study suggests that increased anteversion of the acetabular component reduces polyethylene linear wear in metal-on-polyethylene total hiparthroplasty.展开更多
As the market competition of steel mills is severe,deoxidization alloying is an important link in the metallurgical process.To solve this problem,principal component regression analysis is adopted to reduce the dimens...As the market competition of steel mills is severe,deoxidization alloying is an important link in the metallurgical process.To solve this problem,principal component regression analysis is adopted to reduce the dimension of influencing factors,and a reasonable and reliable prediction model of element yield is established.Based on the constraint conditions such as target cost function constraint,yield constraint and non-negative constraint,linear programming is adopted to design the lowest cost batting scheme that meets the national standards and production requirements.The research results provide a reliable optimization model for the deoxidization and alloying process of steel mills,which is of positive significance for improving the market competitiveness of steel mills,reducing waste discharge and protecting the environment.展开更多
An improved measurement method of circularly-polarized (CP) antennas based on linear-component amplitudes is proposed in this paper. By utilizing two sets of orthogonal linear polarization (LP) amplitudes, measurement...An improved measurement method of circularly-polarized (CP) antennas based on linear-component amplitudes is proposed in this paper. By utilizing two sets of orthogonal linear polarization (LP) amplitudes, measurement on axial ratio (AR) of CP antennas can be realized without phase information. However, the rotation sense of the co-polarization cannot be determined due to the absence of the phase information. Above problem is discussed here for the first time, and a solution is presented to determine the rotation sense of the co-polarization by using common auxiliary CP antennas. In addition, there will be some particular cases with large errors in actual measurement. Here a corresponding solution method is given. Finally, co-polarization and cross-polarization patterns can be further obtained from AR results. To verify this improved method, a self-developed CP microstrip array was measured. The measured results are in agreement with the simulated results, which prove this method is correct, effective and practical.展开更多
How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle co...How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle component analysis（PCA） is the most widely-used linear dimensionality reduction method at present.However,the relationships between seismic attributes and reservoir features are non-linear,so seismic attribute dimensionality reduction based on linear transforms can＇t solve non-linear problems well,reducing reservoir prediction precision.As a new non-linear learning method,manifold learning supplies a new method for seismic attribute analysis.It can discover the intrinsic features and rules hidden in the data by computing low-dimensional,neighborhood-preserving embeddings of high-dimensional inputs.In this paper,we try to extract seismic attributes using locally linear embedding（LLE）,realizing inter-horizon attributes dimensionality reduction of 3D seismic data first and discuss the optimization of its key parameters.Combining model analysis and case studies,we compare the dimensionality reduction and clustering effects of LLE and PCA,both of which indicate that LLE can retain the intrinsic structure of the inputs.The composite attributes and clustering results based on LLE better characterize the distribution of sedimentary facies,reservoir,and even reservoir fluids.展开更多
In principal component analysis （PCA） algorithms for face recognition, to reduce the influence of the eigenvectors which relate to the changes of the illumination on abstract features, a modified PCA （MPCA） algori...In principal component analysis （PCA） algorithms for face recognition, to reduce the influence of the eigenvectors which relate to the changes of the illumination on abstract features, a modified PCA （MPCA） algorithm is proposed. The method is based on the idea of reducing the influence of the eigenvectors associated with the large eigenvalues by normalizing the feature vector element by its corresponding standard deviation. The Yale face database and Yale face database B are used to verify the method. The simulation results show that, for front face and even under the condition of limited variation in the facial poses, the proposed method results in better performance than the conventional PCA and linear discriminant analysis （LDA） approaches, and the computational cost remains the same as that of the PCA, and much less than that of the LDA.展开更多
In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias es...In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.展开更多
This paper presents two novel algorithms for feature extraction-Subpattern Complete Two Dimensional Linear Discriminant Principal Component Analysis (SpC2DLDPCA) and Subpattern Complete Two Dimensional Locality Preser...This paper presents two novel algorithms for feature extraction-Subpattern Complete Two Dimensional Linear Discriminant Principal Component Analysis (SpC2DLDPCA) and Subpattern Complete Two Dimensional Locality Preserving Principal Component Analysis (SpC2DLPPCA). The modified SpC2DLDPCA and SpC2DLPPCA algorithm over their non-subpattern version and Subpattern Complete Two Dimensional Principal Component Analysis (SpC2DPCA) methods benefit greatly in the following four points: (1) SpC2DLDPCA and SpC2DLPPCA can avoid the failure that the larger dimension matrix may bring about more consuming time on computing their eigenvalues and eigenvectors. (2) SpC2DLDPCA and SpC2DLPPCA can extract local information to implement recognition. (3)The idea of subblock is introduced into Two Dimensional Principal Component Analysis (2DPCA) and Two Dimensional Linear Discriminant Analysis (2DLDA). SpC2DLDPCA combines a discriminant analysis and a compression technique with low energy loss. (4) The idea is also introduced into 2DPCA and Two Dimensional Locality Preserving projections (2DLPP), so SpC2DLPPCA can preserve local neighbor graph structure and compact feature expressions. Finally, the experiments on the CASIA(B) gait database show that SpC2DLDPCA and SpC2DLPPCA have higher recognition accuracies than their non-subpattern versions and SpC2DPCA.展开更多
The present paper daisses the relative efficiencies of the least square estimates in linear models. For Gauss-Markoff model: Y=Xe + e E(e)= 0, Cov(e)=V, an new efficiencyo f least square estimate for linearly estimabl...The present paper daisses the relative efficiencies of the least square estimates in linear models. For Gauss-Markoff model: Y=Xe + e E(e)= 0, Cov(e)=V, an new efficiencyo f least square estimate for linearly estimable function c'r is proposed and its lower bound is giv-en. For variance component model: Y=X + e, E(e)=0, Cov(e)=, an new efficiency of least square estimate for linearly estimable function C'r is introduced for the first timeand its lower bound, which is independent of unknown parameters, is also obtained.展开更多
Today, mammography is the best method for early detection of breast cancer. Radiologists failed to detect evident cancerous signs in approximately 20% of false negative mammograms. False negatives have been identified...Today, mammography is the best method for early detection of breast cancer. Radiologists failed to detect evident cancerous signs in approximately 20% of false negative mammograms. False negatives have been identified as the inability of the radiologist to detect the abnormalities due to several reasons such as poor image quality, image noise, or eye fatigue. This paper presents a framework for a computer aided detection system that integrates Principal Component Analysis (PCA), Fisher Linear Discriminant (FLD), and Nearest Neighbor Classifier (KNN) algorithms for the detection of abnormalities in mammograms. Using normal and abnormal mammograms from the MIAS database, the integrated algorithm achieved 93.06% classification accuracy. Also in this paper, we present an analysis of the integrated algorithm’s parameters and suggest selection criteria.展开更多
Iraq is located at the extreme northeastern part of the Arabian Plate, which is in collision with the Eurasian Plate. This collision is still onward, and has caused alignment of the evolved structures in NW-SE trend, ...Iraq is located at the extreme northeastern part of the Arabian Plate, which is in collision with the Eurasian Plate. This collision is still onward, and has caused alignment of the evolved structures in NW-SE trend, mainly, especially in the northern, northeastern and eastern sides of Iraq. However, many transversal linear features of NE-SW trend, represented by rivers, streams, valleys, playas, anticlines and offsets are developed, in parallel trend to the main compressional forces created by the aforementioned collision. Many examples from different parts of Iraq confirm the mechanism of their formation through the geological, geomorphological, tectonics and structural aspects. Although the existing linear features are tens of kilometers in length, but almost no surface displacements were reported, except very few, in some parts of Iraq. The given examples are selected to be the most obvious, when geophysical data are available, the surface and subsurface geology of the involved area is correlated to deduce whether the surface expression coincides with the subsurface or otherwise. A brief tectonic history is also given.展开更多
In this paper, we present continuous iteratively reweighted least squares algorithm (CIRLS) for solving the linear models problem by convex relaxation, and prove the convergence of this algorithm. Under some condition...In this paper, we present continuous iteratively reweighted least squares algorithm (CIRLS) for solving the linear models problem by convex relaxation, and prove the convergence of this algorithm. Under some conditions, we give an error bound for the algorithm. In addition, the numerical result shows the efficiency of the algorithm.展开更多
Impacts of the minimum purchase price policy for grain on the planting area of rice in Hubei Province were analyzed based on a mixed linear model.After the indicator system containing the minimum purchase price policy...Impacts of the minimum purchase price policy for grain on the planting area of rice in Hubei Province were analyzed based on a mixed linear model.After the indicator system containing the minimum purchase price policy and other factors influencing the planting area of rice was constructed,principal component analysis of the system was conducted,and then a mixed linear model where the planting area of rice was as the dependent variable was established.The results show that after the exclusion of the interference from other factors,the minimum purchase price policy for grain had a positive impact on the planting area of rice in Hubei Province.That is,the minimum purchase price policy significantly stimulated the growth of rice planting area in Hubei Province.展开更多
We consider a functional partially linear additive model that predicts a functional response by a scalar predictor and functional predictors. The B-spline and eigenbasis least squares estimator for both the parametric...We consider a functional partially linear additive model that predicts a functional response by a scalar predictor and functional predictors. The B-spline and eigenbasis least squares estimator for both the parametric and the nonparametric components proposed. In the final of this paper, as a result, we got the variance decomposition of the model and establish the asymptotic convergence rate for estimator.展开更多
Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of tre...Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.展开更多
A new algorithm for unsupervised hyperspectral data unmixing is investigated, which includes a modified minimum noise fraction （MNF） transformation and independent component analysis （ICA）. The modified MNF transf...A new algorithm for unsupervised hyperspectral data unmixing is investigated, which includes a modified minimum noise fraction （MNF） transformation and independent component analysis （ICA）. The modified MNF transformation is used to reduce noise and remove correlation between neighboring bands. Then the ICA is applied to unmix hyperspectral images, and independent endmembers are obtained from unmixed images by using post-processing which includes image segmentation based on statistical histograms and morphological operations. The experimental results demonstrate that this algorithm can identify endmembers resident in mixed pixels. Meanwhile, the results show the high computational efficiency of the modified MNF transformation. The time consumed by the modified method is almost one fifth of the traditional MNF transformation.展开更多
According to the hierarchical characteristics of monthly rainfall in different regions, the paper takes the geographical factors and seasonal factors into the hierarchical linear model as the level effect. Through clu...According to the hierarchical characteristics of monthly rainfall in different regions, the paper takes the geographical factors and seasonal factors into the hierarchical linear model as the level effect. Through clustering methods we select two more representative regional meteorological data. We establish three-layer model by transforming the interactive structure date into nested structure data. According the model theory we perform the corresponding model calculations, optimization and analysis, accordingly to interpret the level effects, and residual test. The results show that most of the difference in Monthly Rainfall was respectively explained by Variables (Meteorological factors, seasonal effects, geographic effects) in different levels.展开更多
Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed b...Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed based on linear aggregation degree of signal scatter plot without knowing sparsity,and the linear aggregation degree evaluation of observed signals is presented which obeys generalized Gaussian distribution(GGD).Both the GGD shape parameter and the signals' correlation features affect the observation signals sparsity and further affected the directionality of time-frequency scatter plot.So a new mixing matrix estimation method is proposed for different sparsity degrees,which especially focuses on unclear directionality of scatter plot and weak linear aggregation degree.Firstly,the direction of coefficient scatter plot by time-frequency transform is improved and then the single source coefficients in the case of weak linear clustering is processed finally the improved K-means clustering is applied to achieve the estimation of mixing matrix.The proposed algorithm reduces the requirements of signals sparsity and independence,and the mixing matrix can be estimated with high accuracy.The simulation results show the feasibility and effectiveness of the algorithm.展开更多
In this paper we are concerned with the oscillation criteria of second order non-linear homogeneous differential equation. Example have been given to illustrate the results.
文摘Background: Components of height have been found to be positively associated with blood pressure (BP) both in developed and developing nations. However, amongst Cameroon secondary school adolescents, the relationship between heights, SH and SH/H with BP has rarely been studied. The purpose of this study was to determine the proportion of secondary school adolescents with elevated BP and high BP and to evaluate the relationship between the different components of linear growth with BP. Methods: An institution-based cross-sectional study involving 602 adolescents (399 girls and 203 boys, mean age 14.9 ± 2.3 years) attending some public and private secondary schools in the Bamenda municipality of the North West Region of Cameroon. Anthropometric and BP measurements were carried out following standard procedures. Pearson correlation and linear regression were used to determine the relationship between the various components of height (height, SH, SH/H) with BP amongst the children. Results: The overall prevalence of elevated BP and hypertension amongst the study participants was 21.9% and 15.6% respectively (with 8.3% and 7.3% of the hypertensive children in Stage I and Stage II respectively). However, there were no significant gender differences in the prevalence of elevated BP and high BP (p = 0.497). Girls had a significantly (p Conclusion: This study has demonstrated that height was positively associated with SBP amongst children and adolescents. Thus, height can be used in predicting adolescents with a high risk of developing high BP in our setting.
基金supported by National Natural Science Foundation of China(No.11071193)Research Foundation of Education Bureau of Shan xi Province(No.11JK0509)Research Foundation of Baoji University of Arts and Sciences(No.ZK11044)
文摘The problem of stability for singular systems with two additive time-varying delay components is investigated. By constructing a simple type of Lyapunov-Krasovskii functional and utilizing free matrix variables in approximating certain integral quadratic terms, a delay-dependent stability criterion is established for the considered systems to be regular, impulse free, and stable in terms of linear matrix inequalities （LMIs）. Based on this criterion, some new stability conditions for singular systems with a single delay in a range and regular systems with two additive time-varying delay components are proposed. These developed results have advantages over some previous ones in that they have fewer matrix variables yet less conservatism. Finally, two numerical examples are employed to illustrate the effectiveness of the obtained theoretical results.
文摘Background: Although abduction of the acetabular component is considered to predict factors for polyethylene wear attributable to osteolysis, other radiographic factors have yet to be elucidated. The purpose of the present study was to evaluate whether anteversion or change in implantation angle of the acetabular component influences polyethylene linear wear by using standing and supine radiographs of the hip joint. Methods: Standing and supine plain anteroposterior radiographs of 62 hip joints in which cementless total hip arthroplasty was performed were examined for polyethylene linear wear rate (mm/year), pelvic inclination, and radiological inclination and anatomic anteversion of the acetabular component. Results: All correlation coefficients of measurements of polyethylene linear wear, pelvic inclination angle, anatomical anteversion angle and radiological inclination angle were calculated highly. And by the three-dimensional numerical analysis, anatomic anteversion of the acetabular component had at least some effect on the degree of polyethylene wear. Conclusion: This study suggests that increased anteversion of the acetabular component reduces polyethylene linear wear in metal-on-polyethylene total hiparthroplasty.
文摘As the market competition of steel mills is severe,deoxidization alloying is an important link in the metallurgical process.To solve this problem,principal component regression analysis is adopted to reduce the dimension of influencing factors,and a reasonable and reliable prediction model of element yield is established.Based on the constraint conditions such as target cost function constraint,yield constraint and non-negative constraint,linear programming is adopted to design the lowest cost batting scheme that meets the national standards and production requirements.The research results provide a reliable optimization model for the deoxidization and alloying process of steel mills,which is of positive significance for improving the market competitiveness of steel mills,reducing waste discharge and protecting the environment.
文摘An improved measurement method of circularly-polarized (CP) antennas based on linear-component amplitudes is proposed in this paper. By utilizing two sets of orthogonal linear polarization (LP) amplitudes, measurement on axial ratio (AR) of CP antennas can be realized without phase information. However, the rotation sense of the co-polarization cannot be determined due to the absence of the phase information. Above problem is discussed here for the first time, and a solution is presented to determine the rotation sense of the co-polarization by using common auxiliary CP antennas. In addition, there will be some particular cases with large errors in actual measurement. Here a corresponding solution method is given. Finally, co-polarization and cross-polarization patterns can be further obtained from AR results. To verify this improved method, a self-developed CP microstrip array was measured. The measured results are in agreement with the simulated results, which prove this method is correct, effective and practical.
基金National Key Science & Technology Special Projects(Grant No.2008ZX05000-004)CNPC Projects(Grant No.2008E-0610-10).
文摘How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle component analysis（PCA） is the most widely-used linear dimensionality reduction method at present.However,the relationships between seismic attributes and reservoir features are non-linear,so seismic attribute dimensionality reduction based on linear transforms can＇t solve non-linear problems well,reducing reservoir prediction precision.As a new non-linear learning method,manifold learning supplies a new method for seismic attribute analysis.It can discover the intrinsic features and rules hidden in the data by computing low-dimensional,neighborhood-preserving embeddings of high-dimensional inputs.In this paper,we try to extract seismic attributes using locally linear embedding（LLE）,realizing inter-horizon attributes dimensionality reduction of 3D seismic data first and discuss the optimization of its key parameters.Combining model analysis and case studies,we compare the dimensionality reduction and clustering effects of LLE and PCA,both of which indicate that LLE can retain the intrinsic structure of the inputs.The composite attributes and clustering results based on LLE better characterize the distribution of sedimentary facies,reservoir,and even reservoir fluids.
文摘In principal component analysis （PCA） algorithms for face recognition, to reduce the influence of the eigenvectors which relate to the changes of the illumination on abstract features, a modified PCA （MPCA） algorithm is proposed. The method is based on the idea of reducing the influence of the eigenvectors associated with the large eigenvalues by normalizing the feature vector element by its corresponding standard deviation. The Yale face database and Yale face database B are used to verify the method. The simulation results show that, for front face and even under the condition of limited variation in the facial poses, the proposed method results in better performance than the conventional PCA and linear discriminant analysis （LDA） approaches, and the computational cost remains the same as that of the PCA, and much less than that of the LDA.
文摘In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.
基金Sponsored by the National Science Foundation of China( Grant No. 61201370,61100103)the Independent Innovation Foundation of Shandong University( Grant No. 2012DX07)
文摘This paper presents two novel algorithms for feature extraction-Subpattern Complete Two Dimensional Linear Discriminant Principal Component Analysis (SpC2DLDPCA) and Subpattern Complete Two Dimensional Locality Preserving Principal Component Analysis (SpC2DLPPCA). The modified SpC2DLDPCA and SpC2DLPPCA algorithm over their non-subpattern version and Subpattern Complete Two Dimensional Principal Component Analysis (SpC2DPCA) methods benefit greatly in the following four points: (1) SpC2DLDPCA and SpC2DLPPCA can avoid the failure that the larger dimension matrix may bring about more consuming time on computing their eigenvalues and eigenvectors. (2) SpC2DLDPCA and SpC2DLPPCA can extract local information to implement recognition. (3)The idea of subblock is introduced into Two Dimensional Principal Component Analysis (2DPCA) and Two Dimensional Linear Discriminant Analysis (2DLDA). SpC2DLDPCA combines a discriminant analysis and a compression technique with low energy loss. (4) The idea is also introduced into 2DPCA and Two Dimensional Locality Preserving projections (2DLPP), so SpC2DLPPCA can preserve local neighbor graph structure and compact feature expressions. Finally, the experiments on the CASIA(B) gait database show that SpC2DLDPCA and SpC2DLPPCA have higher recognition accuracies than their non-subpattern versions and SpC2DPCA.
文摘The present paper daisses the relative efficiencies of the least square estimates in linear models. For Gauss-Markoff model: Y=Xe + e E(e)= 0, Cov(e)=V, an new efficiencyo f least square estimate for linearly estimable function c'r is proposed and its lower bound is giv-en. For variance component model: Y=X + e, E(e)=0, Cov(e)=, an new efficiency of least square estimate for linearly estimable function C'r is introduced for the first timeand its lower bound, which is independent of unknown parameters, is also obtained.
文摘Today, mammography is the best method for early detection of breast cancer. Radiologists failed to detect evident cancerous signs in approximately 20% of false negative mammograms. False negatives have been identified as the inability of the radiologist to detect the abnormalities due to several reasons such as poor image quality, image noise, or eye fatigue. This paper presents a framework for a computer aided detection system that integrates Principal Component Analysis (PCA), Fisher Linear Discriminant (FLD), and Nearest Neighbor Classifier (KNN) algorithms for the detection of abnormalities in mammograms. Using normal and abnormal mammograms from the MIAS database, the integrated algorithm achieved 93.06% classification accuracy. Also in this paper, we present an analysis of the integrated algorithm’s parameters and suggest selection criteria.
文摘Iraq is located at the extreme northeastern part of the Arabian Plate, which is in collision with the Eurasian Plate. This collision is still onward, and has caused alignment of the evolved structures in NW-SE trend, mainly, especially in the northern, northeastern and eastern sides of Iraq. However, many transversal linear features of NE-SW trend, represented by rivers, streams, valleys, playas, anticlines and offsets are developed, in parallel trend to the main compressional forces created by the aforementioned collision. Many examples from different parts of Iraq confirm the mechanism of their formation through the geological, geomorphological, tectonics and structural aspects. Although the existing linear features are tens of kilometers in length, but almost no surface displacements were reported, except very few, in some parts of Iraq. The given examples are selected to be the most obvious, when geophysical data are available, the surface and subsurface geology of the involved area is correlated to deduce whether the surface expression coincides with the subsurface or otherwise. A brief tectonic history is also given.
文摘In this paper, we present continuous iteratively reweighted least squares algorithm (CIRLS) for solving the linear models problem by convex relaxation, and prove the convergence of this algorithm. Under some conditions, we give an error bound for the algorithm. In addition, the numerical result shows the efficiency of the algorithm.
基金Supported by the Humanities and Social Sciences Foundation for Young Scholars of Ministry of Education of China(11y3jc630197)
文摘Impacts of the minimum purchase price policy for grain on the planting area of rice in Hubei Province were analyzed based on a mixed linear model.After the indicator system containing the minimum purchase price policy and other factors influencing the planting area of rice was constructed,principal component analysis of the system was conducted,and then a mixed linear model where the planting area of rice was as the dependent variable was established.The results show that after the exclusion of the interference from other factors,the minimum purchase price policy for grain had a positive impact on the planting area of rice in Hubei Province.That is,the minimum purchase price policy significantly stimulated the growth of rice planting area in Hubei Province.
文摘We consider a functional partially linear additive model that predicts a functional response by a scalar predictor and functional predictors. The B-spline and eigenbasis least squares estimator for both the parametric and the nonparametric components proposed. In the final of this paper, as a result, we got the variance decomposition of the model and establish the asymptotic convergence rate for estimator.
文摘Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.
基金Sponsored by the National Natural Science Foundation of China(Grant No. 60272073).
文摘A new algorithm for unsupervised hyperspectral data unmixing is investigated, which includes a modified minimum noise fraction （MNF） transformation and independent component analysis （ICA）. The modified MNF transformation is used to reduce noise and remove correlation between neighboring bands. Then the ICA is applied to unmix hyperspectral images, and independent endmembers are obtained from unmixed images by using post-processing which includes image segmentation based on statistical histograms and morphological operations. The experimental results demonstrate that this algorithm can identify endmembers resident in mixed pixels. Meanwhile, the results show the high computational efficiency of the modified MNF transformation. The time consumed by the modified method is almost one fifth of the traditional MNF transformation.
文摘According to the hierarchical characteristics of monthly rainfall in different regions, the paper takes the geographical factors and seasonal factors into the hierarchical linear model as the level effect. Through clustering methods we select two more representative regional meteorological data. We establish three-layer model by transforming the interactive structure date into nested structure data. According the model theory we perform the corresponding model calculations, optimization and analysis, accordingly to interpret the level effects, and residual test. The results show that most of the difference in Monthly Rainfall was respectively explained by Variables (Meteorological factors, seasonal effects, geographic effects) in different levels.
基金Supported by the National Natural Science Foundation of China(No.51204145)Natural Science Foundation of Hebei Province of China(No.2013203300)
文摘Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed based on linear aggregation degree of signal scatter plot without knowing sparsity,and the linear aggregation degree evaluation of observed signals is presented which obeys generalized Gaussian distribution(GGD).Both the GGD shape parameter and the signals' correlation features affect the observation signals sparsity and further affected the directionality of time-frequency scatter plot.So a new mixing matrix estimation method is proposed for different sparsity degrees,which especially focuses on unclear directionality of scatter plot and weak linear aggregation degree.Firstly,the direction of coefficient scatter plot by time-frequency transform is improved and then the single source coefficients in the case of weak linear clustering is processed finally the improved K-means clustering is applied to achieve the estimation of mixing matrix.The proposed algorithm reduces the requirements of signals sparsity and independence,and the mixing matrix can be estimated with high accuracy.The simulation results show the feasibility and effectiveness of the algorithm.
文摘In this paper we are concerned with the oscillation criteria of second order non-linear homogeneous differential equation. Example have been given to illustrate the results.
