Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spect...Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spectral information. Therefore, there is a need to incorporate spatial structural and spatial association properties of the surfaces of objects into image processing to improve the accuracy of classification of remotely sensed imagery. In the current article, a new method is proposed on the basis of the principle of multiple-point statistics for combining spectral information and spatial information for image classification. The method was validated by applying to a case study on road extraction based on Landsat TM taken over the Chinese Yellow River delta on August 8, 1999. The classification results have shown that this new method provides overall better results than the traditional methods such as maximum likelihood classifier （MLC）.展开更多
First,statistics on the operational lines and mileage of urban rail transit in China are conducted.The results show that,as of Dec.31,2025,there were 60 cities with urban rail transit in operation nationwide,with a to...First,statistics on the operational lines and mileage of urban rail transit in China are conducted.The results show that,as of Dec.31,2025,there were 60 cities with urban rail transit in operation nationwide,with a total operational mileage of approximately 12837.8 km(excluding the electronic guideway rubber-tired system,there were 57 cities,with a total operational mileage of 12651.6 km).The metro system dominates,while low-capacity systems exhibit a multi-modal development pattern.Subsequently,the characteristics of China′s urban rail transit industry development are analyzed,indicating that:(1)It should closely align with the theme of urban intensive development,promote quality improvement and efficiency enhancement of existing lines,and focus on the supporting role of initial passenger flow for new line construction,multi-network integration,and economic and financial sustainability.(2)Significant innovative achievements have been made in safety resilience,green and low-carbon development,intelligent construction,and digital transformation.Finally,development recommendations for the"15th Five-Year Plan"period are proposed:promoting cost reduction and efficiency improvement in the rail transit industry,enhancing the operational efficiency of existing networks,continuously exploring railway services for urban commuting,strengthening external exchanges,and driving the"going global"strategy of the urban rail transit industry.展开更多
In the new era,the impact of emerging productive forces has permeated every sector of industry.As the core production factor of these forces,data plays a pivotal role in industrial transformation and social developmen...In the new era,the impact of emerging productive forces has permeated every sector of industry.As the core production factor of these forces,data plays a pivotal role in industrial transformation and social development.Consequently,many domestic universities have introduced majors or courses related to big data.Among these,the Big Data Management and Applications major stands out for its interdisciplinary approach and emphasis on practical skills.However,as an emerging field,it has not yet accumulated a robust foundation in teaching theory and practice.Current instructional practices face issues such as unclear training objectives,inconsistent teaching methods and course content,insufficient integration of practical components,and a shortage of qualified faculty-factors that hinder both the development of the major and the overall quality of education.Taking the statistics course within the Big Data Management and Applications major as an example,this paper examines the challenges faced by statistics education in the context of emerging productive forces and proposes corresponding improvement measures.By introducing innovative teaching concepts and strategies,the teaching system for professional courses is optimized,and authentic classroom scenarios are recreated through illustrative examples.Questionnaire surveys and statistical analyses of data collected before and after the teaching reforms indicate that the curriculum changes effectively enhance instructional outcomes,promote the development of the major,and improve the quality of talent cultivation.展开更多
With the implementation of General Senior High School Mathematics Curriculum Standards(2017 Edition,Revised in 2020),probability and statistics,as important carriers of the core mathematical competencies“mathematical...With the implementation of General Senior High School Mathematics Curriculum Standards(2017 Edition,Revised in 2020),probability and statistics,as important carriers of the core mathematical competencies“mathematical modeling”and“data analysis,”have increasingly highlighted their educational value.By summarizing the historical evolution of probability and statistics thinking and combining with teaching practice cases,this study explores its unique role in cultivating students’core mathematical competencies.The research proposes a project-based teaching strategy relying on real scenarios and empowered by technology.Through cases,it demonstrates how to use modern educational technology to realize the whole-process exploration of data collection,model construction,and conclusion verification,so as to promote the transformation of middle school probability and statistics teaching from knowledge imparting to competency development,and provide a practical reference for curriculum reform.展开更多
This paper focuses on the ideological and political construction of the course“Probability Theory and Mathematical Statistics.”Aiming at the current situation in teaching where emphasis is placed on knowledge impart...This paper focuses on the ideological and political construction of the course“Probability Theory and Mathematical Statistics.”Aiming at the current situation in teaching where emphasis is placed on knowledge imparting while value guidance is neglected,and combined with the requirements of ideological and political education policies in the new era,this paper explores the integration path between professional courses and ideological and political education.Through literature analysis,case comparison,and empirical research,the study proposes a systematic implementation plan covering the design of teaching objectives,the reconstruction of teaching content,and the optimization of the evaluation system.The purpose is to cultivate students’sense of social responsibility and innovative awareness by excavating the ideological and political elements in mathematics.The research results provide practical reference for colleges and universities to deepen the reform of ideological and political education in courses,and promote the implementation of the fundamental task of fostering virtue through education in STEM education.展开更多
Based on the analysis of the high-order compatibility optimization method proposed by predecessors, a new training image optimization method based on data event repetition probability is proposed. The basic idea is to...Based on the analysis of the high-order compatibility optimization method proposed by predecessors, a new training image optimization method based on data event repetition probability is proposed. The basic idea is to extract the data event contained in the condition data and calculate the number of repetitions of the extracted data events and their repetition probability in the training image to obtain two statistical indicators, unmatched ratio and repeated probability variance of data events. The two statistical indicators are used to characterize the diversity and stability of the sedimentary model in the training image and evaluate the matching of the geological volume spatial structure contained in data of the well block to be modeled. The unmatched ratio reflects the completeness of geological model in training image, which is the first choice index. The repeated probability variance reflects the stationarity index of geological model of each training image, and is an auxiliary index. Then, we can integrate the above two indexes to achieve the optimization of training image. Multiple sets of theoretical model tests show that the training image with small variance and low no-matching ratio is the optimal training image. The method is used to optimize the training image of turbidite channel in Plutonio oilfield in Angola. The geological model established by this method is in good agreement with the seismic attributes and can better reproduce the morphological characteristics of the channels and distribution pattern of sands.展开更多
To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-r...To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-ray computed tomography were combined to obtain the strain distribution over the sample surface and internal fractures of the samples.The Gini and skewness(G-S)coefficients were used to quantify strain localization during tests,where the Gini coefficient reflects the degree of clustering of elements with high strain values,i.e.,strain localization/delocalization.The strain localization-induced asymmetry of data distribution is quantified by the skewness coefficient.A precursor to granite failure is defined by the rapid and simultaneous increase of the G-S coefficients,which are calculated from strain increment,giving an earlier warning of failure by about 8%peak stress than those from absolute strain values.Moreover,the process of damage accumulation due to stress-driven crack propagation in Beishan granite is different at various confining pressures as the stress exceeds the crack initiation stress.Concretely,strain localization is continuous until brittle failure at higher confining pressure,while both strain localization and delocalization occur at lower confining pressure.Despite the different stress conditions,a similar statistical characteristic of strain localization during the creep stage is observed.The Gini coefficient increases,and the skewness coefficient decreases slightly as the creep stress is below 95%peak stress.When the accelerated strain localization begins,the Gini and skewness coefficients increase rapidly and simultaneously.展开更多
Vaginal delivery is a fascinating physiological process,but also a high-risk process.Up to 85%–90%of vaginal deliveries lead to perineal trauma,with nearly 11%of severe perineal tearing.It is a common occurrence,espe...Vaginal delivery is a fascinating physiological process,but also a high-risk process.Up to 85%–90%of vaginal deliveries lead to perineal trauma,with nearly 11%of severe perineal tearing.It is a common occurrence,especially for first-time mothers.Computational childbirth plays an essential role in the prediction and prevention of these traumas,but fast personalization of the pelvis and floor muscles is challenging due to their anatomical complexity.This study introduces a novel shape-prediction-based personalization of the pelvis and floor muscles for perineal tearing management and childbirth simulation.300 subjects were selected from public Computed Tomography(CT)databases.The pelvic bone nmjmeshes were generated using a coarse-to-fine non-rigid mesh alignment procedure.The floor muscle meshes were personalized using the bone mesh deformation information.A feature-to-pelvic structure reconstruction pipeline was proposed,incorporating various strategies.Ten-fold cross-validation helped determine the optimal reconstruction strategy,regression method,and feature sizes.The mesh-to-mesh distance metric was employed for evaluating.The statistical shape relation-based strategy,coupled with multi-output ridge regression,was the optimal approach for pelvic structure reconstruction.With a feature set ranging from 3 to 38,the mean errors were 2.672 to 1.613 mm,and 3.237 to 1.415 mm in muscle attachment regions.The best-and worst-case predictions had errors of 1.227±0.959 mm and 2.900±2.309 mm,respectively.This study provides a novel approach to achieving fast personalized childbirth modeling and simulation for perineal tearing management.展开更多
Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and ideal...Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.展开更多
Ocean waves are the core environmental elements affecting the movements and structure design of ships. Statistical analysis of wave parameters is the basis for the establishment of long-term ship environmental adaptab...Ocean waves are the core environmental elements affecting the movements and structure design of ships. Statistical analysis of wave parameters is the basis for the establishment of long-term ship environmental adaptability prediction model. The observations from coastal stations, buoys, altimeters and volunteer ships that cover from 1993 to 2011 were interpolated into miller Ion-lat grids by using bilinear method and the analytical fields of ocean waves were given. By using optimal interpolation, the analysis wave fields were assimilated into the WAVEWATCH III （WW3） simulation results. From the assimilated results, the wave rose statistics, the wave height of muitiyear return period and the extreme 2-D wave spectrum are related to the ship seakeeping were calculated. Finally, the wave statistics in China offshore were analyzed in detail.展开更多
In order to reduce the enormous pressure to environmental monitoring work brought by the false sewage monitoring data, Grubbs method, box plot, t test and other methods are used to make depth analysis to the data, pro...In order to reduce the enormous pressure to environmental monitoring work brought by the false sewage monitoring data, Grubbs method, box plot, t test and other methods are used to make depth analysis to the data, providing a set of technological process to identify the sewage monitoring data, which is convenient and simple.展开更多
With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save inst...With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save instructors' effort as well.And it is estimated that Monte Carlo Simulation technology will be one of the major teaching methods for Probability and Mathematical Statistics course in the future.展开更多
The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optima...The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optimal detector,which requires many processing channels.The structure of such optimal detector is complex.Therefore,a simpler quasi-optimal detector is then introduced.The quasi-optimal detector,called the strong scattering cells’ number dependent order statistics（SND-OS） detector,takes the form of an average of maximum strong scattering cells with a known number.If the number of strong scattering cells is unknown in real situation,the multi-channel order statistics（MC-OS） detector is used.In each channel,a various number of maximums scattered from target are averaged.Then,the false alarm probability analysis and thresholds sets for each channel are given,following the detection results presented by means of Monte Carlo simulation strategy based on simulated target model and three measured targets.In particular,the theoretical analysis and simulation results highlight that the MC-OS detector can efficiently detect range-spread targets in white Gaussian noise.展开更多
For radar targets flying at low altitude, multiple pathways produce fade or enhancement relative to the level that would be expected in a free-space environment. In this paper, a new detec- tion method based on a wide...For radar targets flying at low altitude, multiple pathways produce fade or enhancement relative to the level that would be expected in a free-space environment. In this paper, a new detec- tion method based on a wide-ranging multi-frequency radar for low angle targets is proposed. Sequential transmitting multiple pulses with different frequencies are first applied to decorrelate the cohe- rence of the direct and reflected echoes. After receiving all echoes, the multi-frequency samples are arranged in a sort descending ac- cording to the amplitude. Some high amplitude echoes in the same range cell are accumulated to improve the signal-to-noise ratio and the optimal number of high amplitude echoes is analyzed and given by experiments. Finally, simulation results are presented to verify the effectiveness of the method.展开更多
This paper focuses on a method to solve structural optimization problems using particle swarm optimization （PSO）, surrogate models and Bayesian statistics. PSO is a random/stochastic search algorithm designed to fin...This paper focuses on a method to solve structural optimization problems using particle swarm optimization （PSO）, surrogate models and Bayesian statistics. PSO is a random/stochastic search algorithm designed to find the global optimum. However, PSO needs many evaluations compared to gradient-based optimization. This means PSO increases the analysis costs of structural optimization. One of the methods to reduce computing costs in stochastic optimization is to use approximation techniques. In this work, surrogate models are used, including the response surface method （RSM） and Kriging. When surrogate models are used, there are some errors between exact values and approximated values. These errors decrease the reliability of the optimum values and discard the realistic approximation of using surrogate models. In this paper, Bayesian statistics is used to obtain more reliable results. To verify and confirm the efficiency of the proposed method using surrogate models and Bayesian statistics for stochastic structural optimization, two numerical examples are optimized, and the optimization of a hub sleeve is demonstrated as a practical problem.展开更多
The relationship between fractal point pattern modeling and statistical methods of pa- rameter estimation in point-process modeling is reviewed. Statistical estimation of the cluster fractal dimension by using Ripley...The relationship between fractal point pattern modeling and statistical methods of pa- rameter estimation in point-process modeling is reviewed. Statistical estimation of the cluster fractal dimension by using Ripley＇s K-function has advantages in comparison with the more commonly used methods of box-counting and cluster fractal dimension estimation because it corrects for edge effects, not only for rectangular study areas but also for study areas with curved boundaries determined by re- gional geology. Application of box-counting to estimate the fractal dimension of point patterns has the disadvantage that, in general, it is subject to relatively strong ＂roll-off＂ effects for smaller boxes. Point patterns used for example in this paper are mainly for gold deposits in the Abitibi volcanic belt on the Canadian Shield. Additionally, it is proposed that, worldwide, the local point patterns of podiform Cr, volcanogenic massive sulphide and porphyry copper deposits, which are spatially distributed within irregularly shaped favorable tracts, satisfy the fractal clustering model with similar fractal dimensions. The problem of deposit size （metal tonnage） is also considered. Several examples are provided of cases in which the Pareto distribution provides good results for the largest deposits in metal size-frequency distribution modeling.展开更多
This paper is mainly to deal with the problem of direction of arrival(DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive ...This paper is mainly to deal with the problem of direction of arrival(DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive noise as α-stable distribution, new methods which combine the sparse signal representation technique and fractional lower order statistics theory are proposed. In the new algorithms, the fractional lower order statistics vectors of the array output signal are sparsely represented on an overcomplete basis and the DOAs can be effectively estimated by searching the sparsest coefficients. To enhance the robustness performance of the proposed algorithms,the improved algorithms are advanced by eliminating the fractional lower order statistics of the noise from the fractional lower order statistics vector of the array output through a linear transformation. Simulation results have shown the effectiveness of the proposed methods for a wide range of highly impulsive environments.展开更多
基金supported by the National Natural Science Foundation of China (No. 40671136)the National High Technology Research and Development Program of China (Nos.2006AA06Z115, 2006AA120106)
文摘Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spectral information. Therefore, there is a need to incorporate spatial structural and spatial association properties of the surfaces of objects into image processing to improve the accuracy of classification of remotely sensed imagery. In the current article, a new method is proposed on the basis of the principle of multiple-point statistics for combining spectral information and spatial information for image classification. The method was validated by applying to a case study on road extraction based on Landsat TM taken over the Chinese Yellow River delta on August 8, 1999. The classification results have shown that this new method provides overall better results than the traditional methods such as maximum likelihood classifier （MLC）.
文摘First,statistics on the operational lines and mileage of urban rail transit in China are conducted.The results show that,as of Dec.31,2025,there were 60 cities with urban rail transit in operation nationwide,with a total operational mileage of approximately 12837.8 km(excluding the electronic guideway rubber-tired system,there were 57 cities,with a total operational mileage of 12651.6 km).The metro system dominates,while low-capacity systems exhibit a multi-modal development pattern.Subsequently,the characteristics of China′s urban rail transit industry development are analyzed,indicating that:(1)It should closely align with the theme of urban intensive development,promote quality improvement and efficiency enhancement of existing lines,and focus on the supporting role of initial passenger flow for new line construction,multi-network integration,and economic and financial sustainability.(2)Significant innovative achievements have been made in safety resilience,green and low-carbon development,intelligent construction,and digital transformation.Finally,development recommendations for the"15th Five-Year Plan"period are proposed:promoting cost reduction and efficiency improvement in the rail transit industry,enhancing the operational efficiency of existing networks,continuously exploring railway services for urban commuting,strengthening external exchanges,and driving the"going global"strategy of the urban rail transit industry.
文摘In the new era,the impact of emerging productive forces has permeated every sector of industry.As the core production factor of these forces,data plays a pivotal role in industrial transformation and social development.Consequently,many domestic universities have introduced majors or courses related to big data.Among these,the Big Data Management and Applications major stands out for its interdisciplinary approach and emphasis on practical skills.However,as an emerging field,it has not yet accumulated a robust foundation in teaching theory and practice.Current instructional practices face issues such as unclear training objectives,inconsistent teaching methods and course content,insufficient integration of practical components,and a shortage of qualified faculty-factors that hinder both the development of the major and the overall quality of education.Taking the statistics course within the Big Data Management and Applications major as an example,this paper examines the challenges faced by statistics education in the context of emerging productive forces and proposes corresponding improvement measures.By introducing innovative teaching concepts and strategies,the teaching system for professional courses is optimized,and authentic classroom scenarios are recreated through illustrative examples.Questionnaire surveys and statistical analyses of data collected before and after the teaching reforms indicate that the curriculum changes effectively enhance instructional outcomes,promote the development of the major,and improve the quality of talent cultivation.
基金2021 Annual Research Project of Yili Normal University(2021YSBS012)。
文摘With the implementation of General Senior High School Mathematics Curriculum Standards(2017 Edition,Revised in 2020),probability and statistics,as important carriers of the core mathematical competencies“mathematical modeling”and“data analysis,”have increasingly highlighted their educational value.By summarizing the historical evolution of probability and statistics thinking and combining with teaching practice cases,this study explores its unique role in cultivating students’core mathematical competencies.The research proposes a project-based teaching strategy relying on real scenarios and empowered by technology.Through cases,it demonstrates how to use modern educational technology to realize the whole-process exploration of data collection,model construction,and conclusion verification,so as to promote the transformation of middle school probability and statistics teaching from knowledge imparting to competency development,and provide a practical reference for curriculum reform.
基金Shaanxi Provincial 14th Five-Year Plan for Educational Science Research(SGH24Q481)。
文摘This paper focuses on the ideological and political construction of the course“Probability Theory and Mathematical Statistics.”Aiming at the current situation in teaching where emphasis is placed on knowledge imparting while value guidance is neglected,and combined with the requirements of ideological and political education policies in the new era,this paper explores the integration path between professional courses and ideological and political education.Through literature analysis,case comparison,and empirical research,the study proposes a systematic implementation plan covering the design of teaching objectives,the reconstruction of teaching content,and the optimization of the evaluation system.The purpose is to cultivate students’sense of social responsibility and innovative awareness by excavating the ideological and political elements in mathematics.The research results provide practical reference for colleges and universities to deepen the reform of ideological and political education in courses,and promote the implementation of the fundamental task of fostering virtue through education in STEM education.
基金Supported by the China National Science and Technology Major Project(2016ZX05015001-001,2016ZX05033-003-002)
文摘Based on the analysis of the high-order compatibility optimization method proposed by predecessors, a new training image optimization method based on data event repetition probability is proposed. The basic idea is to extract the data event contained in the condition data and calculate the number of repetitions of the extracted data events and their repetition probability in the training image to obtain two statistical indicators, unmatched ratio and repeated probability variance of data events. The two statistical indicators are used to characterize the diversity and stability of the sedimentary model in the training image and evaluate the matching of the geological volume spatial structure contained in data of the well block to be modeled. The unmatched ratio reflects the completeness of geological model in training image, which is the first choice index. The repeated probability variance reflects the stationarity index of geological model of each training image, and is an auxiliary index. Then, we can integrate the above two indexes to achieve the optimization of training image. Multiple sets of theoretical model tests show that the training image with small variance and low no-matching ratio is the optimal training image. The method is used to optimize the training image of turbidite channel in Plutonio oilfield in Angola. The geological model established by this method is in good agreement with the seismic attributes and can better reproduce the morphological characteristics of the channels and distribution pattern of sands.
基金supported by the National Natural Science Foundation of China(Grant No.52339001).
文摘To investigate the damage evolution caused by stress-driven and sub-critical crack propagation within the Beishan granite under multi-creep triaxial compressive conditions,the distributed optical fiber sensing and X-ray computed tomography were combined to obtain the strain distribution over the sample surface and internal fractures of the samples.The Gini and skewness(G-S)coefficients were used to quantify strain localization during tests,where the Gini coefficient reflects the degree of clustering of elements with high strain values,i.e.,strain localization/delocalization.The strain localization-induced asymmetry of data distribution is quantified by the skewness coefficient.A precursor to granite failure is defined by the rapid and simultaneous increase of the G-S coefficients,which are calculated from strain increment,giving an earlier warning of failure by about 8%peak stress than those from absolute strain values.Moreover,the process of damage accumulation due to stress-driven crack propagation in Beishan granite is different at various confining pressures as the stress exceeds the crack initiation stress.Concretely,strain localization is continuous until brittle failure at higher confining pressure,while both strain localization and delocalization occur at lower confining pressure.Despite the different stress conditions,a similar statistical characteristic of strain localization during the creep stage is observed.The Gini coefficient increases,and the skewness coefficient decreases slightly as the creep stress is below 95%peak stress.When the accelerated strain localization begins,the Gini and skewness coefficients increase rapidly and simultaneously.
基金funded by Vietnam National University Ho Chi Minh City(VNU-HCM)under grant number DS.C2025-28-06.
文摘Vaginal delivery is a fascinating physiological process,but also a high-risk process.Up to 85%–90%of vaginal deliveries lead to perineal trauma,with nearly 11%of severe perineal tearing.It is a common occurrence,especially for first-time mothers.Computational childbirth plays an essential role in the prediction and prevention of these traumas,but fast personalization of the pelvis and floor muscles is challenging due to their anatomical complexity.This study introduces a novel shape-prediction-based personalization of the pelvis and floor muscles for perineal tearing management and childbirth simulation.300 subjects were selected from public Computed Tomography(CT)databases.The pelvic bone nmjmeshes were generated using a coarse-to-fine non-rigid mesh alignment procedure.The floor muscle meshes were personalized using the bone mesh deformation information.A feature-to-pelvic structure reconstruction pipeline was proposed,incorporating various strategies.Ten-fold cross-validation helped determine the optimal reconstruction strategy,regression method,and feature sizes.The mesh-to-mesh distance metric was employed for evaluating.The statistical shape relation-based strategy,coupled with multi-output ridge regression,was the optimal approach for pelvic structure reconstruction.With a feature set ranging from 3 to 38,the mean errors were 2.672 to 1.613 mm,and 3.237 to 1.415 mm in muscle attachment regions.The best-and worst-case predictions had errors of 1.227±0.959 mm and 2.900±2.309 mm,respectively.This study provides a novel approach to achieving fast personalized childbirth modeling and simulation for perineal tearing management.
基金supported by the National Science and Technology Major Project(No.2011 ZX05007-006)the 973 Program of China(No.2013CB228604)the Major Project of Petrochina(No.2014B-0610)
文摘Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.
基金supports from National Natural Science Foundation of China (No. 41406032 and No. 41376014)Open Fund of State Key Laboratory of Satellite Ocean Environment Dynamics (No. SOED1305)
文摘Ocean waves are the core environmental elements affecting the movements and structure design of ships. Statistical analysis of wave parameters is the basis for the establishment of long-term ship environmental adaptability prediction model. The observations from coastal stations, buoys, altimeters and volunteer ships that cover from 1993 to 2011 were interpolated into miller Ion-lat grids by using bilinear method and the analytical fields of ocean waves were given. By using optimal interpolation, the analysis wave fields were assimilated into the WAVEWATCH III （WW3） simulation results. From the assimilated results, the wave rose statistics, the wave height of muitiyear return period and the extreme 2-D wave spectrum are related to the ship seakeeping were calculated. Finally, the wave statistics in China offshore were analyzed in detail.
文摘In order to reduce the enormous pressure to environmental monitoring work brought by the false sewage monitoring data, Grubbs method, box plot, t test and other methods are used to make depth analysis to the data, providing a set of technological process to identify the sewage monitoring data, which is convenient and simple.
文摘With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save instructors' effort as well.And it is estimated that Monte Carlo Simulation technology will be one of the major teaching methods for Probability and Mathematical Statistics course in the future.
基金supported by the Major Program of National Natural Science Foundation of China (10990012)the National Natural Science Foundation of China (61201296,61271024)+1 种基金the Fundamental Research Funds for the Central Universities (K5051202037)Guangxi Key Lab of Wireless Wideband Communication & Signal Processing (12205)
文摘The problem of two order statistics detection schemes for the detection of a spatially distributed target in white Gaussian noise are studied.When the number of strong scattering cells is known,we first show an optimal detector,which requires many processing channels.The structure of such optimal detector is complex.Therefore,a simpler quasi-optimal detector is then introduced.The quasi-optimal detector,called the strong scattering cells’ number dependent order statistics（SND-OS） detector,takes the form of an average of maximum strong scattering cells with a known number.If the number of strong scattering cells is unknown in real situation,the multi-channel order statistics（MC-OS） detector is used.In each channel,a various number of maximums scattered from target are averaged.Then,the false alarm probability analysis and thresholds sets for each channel are given,following the detection results presented by means of Monte Carlo simulation strategy based on simulated target model and three measured targets.In particular,the theoretical analysis and simulation results highlight that the MC-OS detector can efficiently detect range-spread targets in white Gaussian noise.
基金supported by the National Natural Science Foundation of China(6137213661372134+2 种基金61172137)the Fundamental Research Funds for the Central Universities(K5051202005)the China Scholarship Council(CSC)
文摘For radar targets flying at low altitude, multiple pathways produce fade or enhancement relative to the level that would be expected in a free-space environment. In this paper, a new detec- tion method based on a wide-ranging multi-frequency radar for low angle targets is proposed. Sequential transmitting multiple pulses with different frequencies are first applied to decorrelate the cohe- rence of the direct and reflected echoes. After receiving all echoes, the multi-frequency samples are arranged in a sort descending ac- cording to the amplitude. Some high amplitude echoes in the same range cell are accumulated to improve the signal-to-noise ratio and the optimal number of high amplitude echoes is analyzed and given by experiments. Finally, simulation results are presented to verify the effectiveness of the method.
文摘This paper focuses on a method to solve structural optimization problems using particle swarm optimization （PSO）, surrogate models and Bayesian statistics. PSO is a random/stochastic search algorithm designed to find the global optimum. However, PSO needs many evaluations compared to gradient-based optimization. This means PSO increases the analysis costs of structural optimization. One of the methods to reduce computing costs in stochastic optimization is to use approximation techniques. In this work, surrogate models are used, including the response surface method （RSM） and Kriging. When surrogate models are used, there are some errors between exact values and approximated values. These errors decrease the reliability of the optimum values and discard the realistic approximation of using surrogate models. In this paper, Bayesian statistics is used to obtain more reliable results. To verify and confirm the efficiency of the proposed method using surrogate models and Bayesian statistics for stochastic structural optimization, two numerical examples are optimized, and the optimization of a hub sleeve is demonstrated as a practical problem.
基金supported by Geological Survey of Canada and China University of Geosciences (Wuhan)
文摘The relationship between fractal point pattern modeling and statistical methods of pa- rameter estimation in point-process modeling is reviewed. Statistical estimation of the cluster fractal dimension by using Ripley＇s K-function has advantages in comparison with the more commonly used methods of box-counting and cluster fractal dimension estimation because it corrects for edge effects, not only for rectangular study areas but also for study areas with curved boundaries determined by re- gional geology. Application of box-counting to estimate the fractal dimension of point patterns has the disadvantage that, in general, it is subject to relatively strong ＂roll-off＂ effects for smaller boxes. Point patterns used for example in this paper are mainly for gold deposits in the Abitibi volcanic belt on the Canadian Shield. Additionally, it is proposed that, worldwide, the local point patterns of podiform Cr, volcanogenic massive sulphide and porphyry copper deposits, which are spatially distributed within irregularly shaped favorable tracts, satisfy the fractal clustering model with similar fractal dimensions. The problem of deposit size （metal tonnage） is also considered. Several examples are provided of cases in which the Pareto distribution provides good results for the largest deposits in metal size-frequency distribution modeling.
基金supported in part by the National Natural Science Foundation of China(61301228,61371091)the Fundamental Research Funds for the Central Universities(3132014212)
文摘This paper is mainly to deal with the problem of direction of arrival(DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive noise as α-stable distribution, new methods which combine the sparse signal representation technique and fractional lower order statistics theory are proposed. In the new algorithms, the fractional lower order statistics vectors of the array output signal are sparsely represented on an overcomplete basis and the DOAs can be effectively estimated by searching the sparsest coefficients. To enhance the robustness performance of the proposed algorithms,the improved algorithms are advanced by eliminating the fractional lower order statistics of the noise from the fractional lower order statistics vector of the array output through a linear transformation. Simulation results have shown the effectiveness of the proposed methods for a wide range of highly impulsive environments.
