Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materia...Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gr展开更多
为了实现了电容式传感器和其他信号处理电路之间的接口,提出了一种电容式传感器接口电路。该接口电路基于开关电容技术,采用采样电荷结构,并在其前端读出电路采用采样开关噪声消除技术,在0.35μm 2P-4 M CMOS标准工艺下设计并流片实现,...为了实现了电容式传感器和其他信号处理电路之间的接口,提出了一种电容式传感器接口电路。该接口电路基于开关电容技术,采用采样电荷结构,并在其前端读出电路采用采样开关噪声消除技术,在0.35μm 2P-4 M CMOS标准工艺下设计并流片实现,且特别适用于开环或力平衡闭环电容式微加速度计和振动角速度陀螺仪应用。测试结果表明:在1 MHz的采样时钟下,该接口电路取得了约5.35 aF的电容分辨率和约0.173 aF.Hz-1/2的噪声基底。展开更多
This work investigates a simple and practical bio-immune optimization approach to solve a kind of chance-constrained programming problem without known noisy attributes, after probing into a lower bound estimate of sam...This work investigates a simple and practical bio-immune optimization approach to solve a kind of chance-constrained programming problem without known noisy attributes, after probing into a lower bound estimate of sample size for any random variable. Such approach mainly consists of sample allocation, evaluation, proliferation and mutation. The former two, depending on a lower bound estimate acquired, not only decide the sample size of random variable and the importance level of each evolving B cell, but also ensure that such B cell is evaluated with low computational cost; the third makes diverse B cells participate in evolution and suppresses the influence of noise; the last, which associates with the information on population diversity and fitness inheritance, creates diverse and high-affinity B cells. Under such approach, three similar immune algorithms are derived after selecting different mutation rules. The experiments, by comparison against two valuable genetic algorithms, have illustrated that these immune algorithms are competitive optimizers capable of effectively executing noisy compensation and searching for the desired optimal reliable solution.展开更多
The Maximum Likelihood method estimates the parameter values of a statistical model that maximizes the corresponding likelihood function, given the sample information. This is the primal approach that, in this paper, ...The Maximum Likelihood method estimates the parameter values of a statistical model that maximizes the corresponding likelihood function, given the sample information. This is the primal approach that, in this paper, is presented as a mathematical programming specification whose solution requires the formulation of a Lagrange problem. A result of this setup is that the Lagrange multipliers associated with the linear statistical model (where sample observations are regarded as a set of constraints) are equal to the vector of residuals scaled by the variance of those residuals. The novel contribution of this paper consists in deriving the dual model of the Maximum Likelihood method under normality assumptions. This model minimizes a function of the variance of the error terms subject to orthogonality conditions between the model residuals and the space of explanatory variables. An intuitive interpretation of the dual problem appeals to basic elements of information theory and an economic interpretation of Lagrange multipliers to establish that the dual maximizes the net value of the sample information. This paper presents the dual ML model for a single regression and provides a numerical example of how to obtain maximum likelihood estimates of the parameters of a linear statistical model using the dual specification.展开更多
This paper presents the dual specification of the least-squares method. In other words, while the traditional (primal) formulation of the method minimizes the sum of squared residuals (noise), the dual specification m...This paper presents the dual specification of the least-squares method. In other words, while the traditional (primal) formulation of the method minimizes the sum of squared residuals (noise), the dual specification maximizes a quadratic function that can be interpreted as the value of sample information. The two specifications are equivalent. Before developing the methodology that describes the dual of the least-squares method, the paper gives a historical perspective of its origin that sheds light on the thinking of Gauss, its inventor. The least-squares method is firmly established as a scientific approach by Gauss, Legendre and Laplace within the space of a decade, at the beginning of the nineteenth century. Legendre was the first author to name the approach, in 1805, as “méthode des moindres carrés”, a “least-squares method”. Gauss, however, used the method as early as 1795, when he was 18 years old. Again, he adopted it in 1801 to calculate the orbit of the newly discovered planet Ceres. Gauss published his way of looking at the least-squares approach in 1809 and gave several hints that the least-squares algorithm was a minimum variance linear estimator and that it was derivable from maximum likelihood considerations. Laplace wrote a very substantial chapter about the method in his fundamental treatise on probability theory published in 1812.展开更多
In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is pr...In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is proposed for the hyperspectral remote sensing.In the proposed approach,the mineral identification is defined as the number of the minerals identified and the key imaging parameters employed include ground sample distance(GSD)and spectral resolution(SR).Certain limitations are found among parameters that are used for analyzing the imaging processes.The constraints include the industrial manufacturing level,application requirements and the quantitative relationship among the GSD,the SR and the signal-to-noise ratio(SNR).Regression analysis is used to investigate the quantitative relationship between the mineral identification and the key imaging system parameters.Then,an optimization model for the trade-off study is established by combining the regression equation with the constraints.The airborne hyperspectral image collected by Hymap is applied to evaluate the performance of the proposed approach.The experimental results reveal that the approach can achieve the evaluation of the mineral identification and the trade-off of key imaging system parameters.The error of the prediction is within one kind of mineral.展开更多
Objective A vacuum sample chamber for SAXS measurement of solutions was developed to improve the signal-to-noise ratio of the instrument at Beijing Synchrotron Radiation Facility(BSRF).Methods We developed a vacuum sa...Objective A vacuum sample chamber for SAXS measurement of solutions was developed to improve the signal-to-noise ratio of the instrument at Beijing Synchrotron Radiation Facility(BSRF).Methods We developed a vacuum sample chamber which could be connected to the upstream and the downstream vacuum tubes by bellows.Horizontal and vertical linear slides were mounted in the vacuum chamber to adjust the sample position by 35 mm in the horizontal and vertical directions to align the sample in the light path.The liquid sample holder of the chamber was sealed with polyimide film by squeezing instead of gluing to avoid the potential influence of sealant on the solution.Results The chamber had been used for SAXS measurements of water and bovine serum albumin solution at BSRF.The results showed that the background scattering intensity in air was much higher than that in vacuum,especially in the smallangle area near the beamstop.When the q value is 0.142 nm−1,1.01 nm−1 and 1.25 nm−1,the background scattering intensity in air is 45,6.8 and 4.6 times of that in vacuum,respectively.And the background-subtracted scattering curves of bovine serum albumin solution(10 mg/ml)in air and vacuum differ in intensity by a factor of about 2.When the q value is 2 nm−1,the signal-to-noise ratios of scattering intensity of BSA in air and vacuum are 0.79 and 8.51,respectively.Conclusion We designed a simple vacuum sample chamber to be used on the SAXS instrument at 1W2A station of BSRF.The scattering of the background and protein solution in air and vacuum was tested and compared,and the signal-to-noise ratio was clearly improved.展开更多
An Nd:YAG single pulse nanosecond laser of 532 nm wavelength with an 8 ns pulse width was projected on the soil samples collected from the campus of Bengbu College under 1 standard atmospheric pressure. Laser-induced ...An Nd:YAG single pulse nanosecond laser of 532 nm wavelength with an 8 ns pulse width was projected on the soil samples collected from the campus of Bengbu College under 1 standard atmospheric pressure. Laser-induced breakdown spectroscopy at different sample temperatures was achieved. The intensity and signal-to-noise ratio (SNR) changes of different characteristic spectral lines could be analyzed when the sample temperature changes.The evolution of plasma electron temperature and electron density with the sample temperature was analyzed through Boltzmann oblique line method and Stark broadening method.The cause of the radiation enhancement of laser-induced metal plasma was discussed. Experimental results demonstrated that the spectral intensity, SNR, the electron temperature and electron density of plasma are positively related to the sample temperature, and reach saturation at 100℃.展开更多
基金funded by the National Natural Science Foundation of China(42071014).
文摘Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gr
基金supported in part by National Natural Science Foundation of China(Nos.61563009 and 61065010)Doctoral Fund of Ministry of Education of China(No.20125201110003)
文摘This work investigates a simple and practical bio-immune optimization approach to solve a kind of chance-constrained programming problem without known noisy attributes, after probing into a lower bound estimate of sample size for any random variable. Such approach mainly consists of sample allocation, evaluation, proliferation and mutation. The former two, depending on a lower bound estimate acquired, not only decide the sample size of random variable and the importance level of each evolving B cell, but also ensure that such B cell is evaluated with low computational cost; the third makes diverse B cells participate in evolution and suppresses the influence of noise; the last, which associates with the information on population diversity and fitness inheritance, creates diverse and high-affinity B cells. Under such approach, three similar immune algorithms are derived after selecting different mutation rules. The experiments, by comparison against two valuable genetic algorithms, have illustrated that these immune algorithms are competitive optimizers capable of effectively executing noisy compensation and searching for the desired optimal reliable solution.
文摘The Maximum Likelihood method estimates the parameter values of a statistical model that maximizes the corresponding likelihood function, given the sample information. This is the primal approach that, in this paper, is presented as a mathematical programming specification whose solution requires the formulation of a Lagrange problem. A result of this setup is that the Lagrange multipliers associated with the linear statistical model (where sample observations are regarded as a set of constraints) are equal to the vector of residuals scaled by the variance of those residuals. The novel contribution of this paper consists in deriving the dual model of the Maximum Likelihood method under normality assumptions. This model minimizes a function of the variance of the error terms subject to orthogonality conditions between the model residuals and the space of explanatory variables. An intuitive interpretation of the dual problem appeals to basic elements of information theory and an economic interpretation of Lagrange multipliers to establish that the dual maximizes the net value of the sample information. This paper presents the dual ML model for a single regression and provides a numerical example of how to obtain maximum likelihood estimates of the parameters of a linear statistical model using the dual specification.
文摘This paper presents the dual specification of the least-squares method. In other words, while the traditional (primal) formulation of the method minimizes the sum of squared residuals (noise), the dual specification maximizes a quadratic function that can be interpreted as the value of sample information. The two specifications are equivalent. Before developing the methodology that describes the dual of the least-squares method, the paper gives a historical perspective of its origin that sheds light on the thinking of Gauss, its inventor. The least-squares method is firmly established as a scientific approach by Gauss, Legendre and Laplace within the space of a decade, at the beginning of the nineteenth century. Legendre was the first author to name the approach, in 1805, as “méthode des moindres carrés”, a “least-squares method”. Gauss, however, used the method as early as 1795, when he was 18 years old. Again, he adopted it in 1801 to calculate the orbit of the newly discovered planet Ceres. Gauss published his way of looking at the least-squares approach in 1809 and gave several hints that the least-squares algorithm was a minimum variance linear estimator and that it was derivable from maximum likelihood considerations. Laplace wrote a very substantial chapter about the method in his fundamental treatise on probability theory published in 1812.
基金supported by the National National Natural Science Foundation of China(Grant Nos.61177008 and 61008047)the China Geological Survey(Grant No.1212011120227)+2 种基金the National High Technology Research and Development Program("863"Program)(Grant Nos.2012AA12A30801 and 2012YQ05250)the Program for Changjiang Scholars and Innovative Research Team(Grant No.IRT0705)the National Public Foundation of China(Grant No.201311036)
文摘In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is proposed for the hyperspectral remote sensing.In the proposed approach,the mineral identification is defined as the number of the minerals identified and the key imaging parameters employed include ground sample distance(GSD)and spectral resolution(SR).Certain limitations are found among parameters that are used for analyzing the imaging processes.The constraints include the industrial manufacturing level,application requirements and the quantitative relationship among the GSD,the SR and the signal-to-noise ratio(SNR).Regression analysis is used to investigate the quantitative relationship between the mineral identification and the key imaging system parameters.Then,an optimization model for the trade-off study is established by combining the regression equation with the constraints.The airborne hyperspectral image collected by Hymap is applied to evaluate the performance of the proposed approach.The experimental results reveal that the approach can achieve the evaluation of the mineral identification and the trade-off of key imaging system parameters.The error of the prediction is within one kind of mineral.
基金National Key R&D Program of China(Grant No.2017YFA0403000the National Natural Science Foundation of China(Grant Nos.31600597,U1532105,21576005,21878006)the Foundation of State Key Laboratory of Coal Conversion(Grant No.J19-20-604).
文摘Objective A vacuum sample chamber for SAXS measurement of solutions was developed to improve the signal-to-noise ratio of the instrument at Beijing Synchrotron Radiation Facility(BSRF).Methods We developed a vacuum sample chamber which could be connected to the upstream and the downstream vacuum tubes by bellows.Horizontal and vertical linear slides were mounted in the vacuum chamber to adjust the sample position by 35 mm in the horizontal and vertical directions to align the sample in the light path.The liquid sample holder of the chamber was sealed with polyimide film by squeezing instead of gluing to avoid the potential influence of sealant on the solution.Results The chamber had been used for SAXS measurements of water and bovine serum albumin solution at BSRF.The results showed that the background scattering intensity in air was much higher than that in vacuum,especially in the smallangle area near the beamstop.When the q value is 0.142 nm−1,1.01 nm−1 and 1.25 nm−1,the background scattering intensity in air is 45,6.8 and 4.6 times of that in vacuum,respectively.And the background-subtracted scattering curves of bovine serum albumin solution(10 mg/ml)in air and vacuum differ in intensity by a factor of about 2.When the q value is 2 nm−1,the signal-to-noise ratios of scattering intensity of BSA in air and vacuum are 0.79 and 8.51,respectively.Conclusion We designed a simple vacuum sample chamber to be used on the SAXS instrument at 1W2A station of BSRF.The scattering of the background and protein solution in air and vacuum was tested and compared,and the signal-to-noise ratio was clearly improved.
基金supported by the National Natural Science Foundation of China(No.11604003)Anhui Province Key Laboratory of Optoelectronic Materials Science and Technology(OMST201703)the Natural Science Foundations of Bengbu College(No.2017ZR11zd)
文摘An Nd:YAG single pulse nanosecond laser of 532 nm wavelength with an 8 ns pulse width was projected on the soil samples collected from the campus of Bengbu College under 1 standard atmospheric pressure. Laser-induced breakdown spectroscopy at different sample temperatures was achieved. The intensity and signal-to-noise ratio (SNR) changes of different characteristic spectral lines could be analyzed when the sample temperature changes.The evolution of plasma electron temperature and electron density with the sample temperature was analyzed through Boltzmann oblique line method and Stark broadening method.The cause of the radiation enhancement of laser-induced metal plasma was discussed. Experimental results demonstrated that the spectral intensity, SNR, the electron temperature and electron density of plasma are positively related to the sample temperature, and reach saturation at 100℃.
