Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious an...Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.展开更多
Dislocation creep at elevated temperatures plays an important role for plastic deformation in crystalline metals.When using traditional discrete dislocation dynamics(DDD)to capture this process,we often need to update...Dislocation creep at elevated temperatures plays an important role for plastic deformation in crystalline metals.When using traditional discrete dislocation dynamics(DDD)to capture this process,we often need to update the forces on N dislocations involving~N 2 interactions.In this letter,we introduce a multi-scale algorithm to speed up the calculations by dividing a sample of interest into sub-domain grids:dislocations within a characteristic area interact following the conventional way,but their interaction with dislocations in other grids are simplified by lumping all dislocations in another grid as a super one.Such a multi-scale algorithm lowers the computational load to~N 1.5.We employed this algorithm to model dislocation creep in Al-Mg alloy.The simulation leads to a power-law creep rate in consistent with experimental observations.The stress exponent of the power-law creep is a resultant of dislocations climb for~5 and viscous dislocations glide for~3.展开更多
Ocean observations are inherently characterized by irregular temporal and spatial distributions,as well as heterogeneous spatial resolutions and error characteristics arising from the use of diverse observational plat...Ocean observations are inherently characterized by irregular temporal and spatial distributions,as well as heterogeneous spatial resolutions and error characteristics arising from the use of diverse observational platforms and techniques.To enable their application across a broad range of scientific and practical problems,it is essential to map these heterogeneous datasets into temporally and spatially consistent gridded products.Optimal Interpolation remains the most widely adopted algorithm for the mapping of oceanographic data.Two principal implementations of the optimal interpolation algorithm are commonly employed.The first,known as the basic optimal interpolation,is derived from the theory of optimal estimation and involves computationally intensive matrix operations,posing significant challenges when applied to high-dimensional problems.The second,referred to as the point-wise optimal interpolation,reduces computational complexity through point-wise estimation,thereby circumventing high-dimensional operations;however,this approach results in a substantially higher overall computational cost.In this study,a novel optimal interpolation algorithm is proposed that utilizes the Kronecker product to approximate the background error covariance matrix.This formulation enables the decomposition of high-dimensional matrix operations into smaller,computationally tractable sub-problems,thereby improving the scalability of optimal interpolation for large spatial domains with dense observational coverage.Building upon this framework,a multi-scale optimal interpolation method is further developed to enhance the integration of observational datasets with widely varying spatial resolutions,thereby improving the accuracy and applicability of the resulting gridded products.展开更多
Based on the analysis of previous genetic algorithms (GAs) for TSP, a novel method called Ge- GA is proposed. It combines gene pool and GA so as to direct the evolution of the whole population. The core of Ge- GA is t...Based on the analysis of previous genetic algorithms (GAs) for TSP, a novel method called Ge- GA is proposed. It combines gene pool and GA so as to direct the evolution of the whole population. The core of Ge- GA is the construction of gene pool and how to apply it to GA. Different from standard GAs, Ge- GA aims to enhance the ability of exploration and exploitation by incorporating global search with local search. On one hand a local search called Ge- Lo-calSearch operator is proposed to improve the solution quality, on the other hand the modified Inver-Over operator called Ge InverOver is considered as a global search mechanism to expand solution space of local minimal. Both of these operators are based on the gene pool. Our algorithm is applied to 11 well-known traveling salesman problems whose numbers of cities are from 70 to 1577 cities. The experiments results indicate that Ge- GA has great robustness for TSP. For each test instance, the average value of solution quality, found in accepted time, stays within 0. 001% from the optimum.展开更多
In order to obtain good welding quality, it is necessary to apply quality control because there are many influencing factors in laser welding process. The key to realize welding quality control is to obtain the qualit...In order to obtain good welding quality, it is necessary to apply quality control because there are many influencing factors in laser welding process. The key to realize welding quality control is to obtain the quality information. Abundant weld quality information is contained in weld pool and keyhole. Aiming at Nd：YAG laser welding of stainless steel, a coaxial visual sensing system was constructed. The images of weld pool and keyhole were obtained. Based on the gray character of weld pool and keyhole in images, an image processing algorithm was designed. The search start point and search criteria of weld pool and keyhole edge were determined respectively.展开更多
Automatic on-line detection of welding deviation based on machine vision is one of the key technologies of arc welding robot tracking welding,in which obtaining high quality weld pool image and accurate welding deviat...Automatic on-line detection of welding deviation based on machine vision is one of the key technologies of arc welding robot tracking welding,in which obtaining high quality weld pool image and accurate welding deviation detection algorithm are two important steps of tracking welding.Through the research and analysis of the weld pool image of gas metal arc welding(GMAW),it was found that the weld pool contains abundant welding information.First,the average gray value of the weld pool image can reflect the interference degree of arc to weld pool image and the heat input of welding process.Secondly,the tip of the weld pool image contour can reflect the center of the groove gap.Finally,the horizontal distance between the center coordinate of the wire contour and the tip coordinate of the weld pool image contour can reflect the welding deviation.On the basis of analyzing the characteristics of weld pool image,this paper proposes a new method of weld seam deviation detection,which includes the collection of weld pool image,image preprocessing,contour extraction and deviation calculation.The results of the tests and analyses showed that the maximum error of the on-line welding deviation obtained was about 2 pixels(0.17 mm)when the welding speed was≤60 cm/min,and the algorithm was stable enough to meet the requirements of real-time deviation detection for I-groove butt welding.The method can be applied to the on-line automatic welding deviation detection of arc welding robot.展开更多
Often in longitudinal studies, some subjects complete their follow-up visits, but others miss their visits due to various reasons. For those who miss follow-up visits, some of them might learn that the event of intere...Often in longitudinal studies, some subjects complete their follow-up visits, but others miss their visits due to various reasons. For those who miss follow-up visits, some of them might learn that the event of interest has already happened when they come back. In this case, not only are their event times interval-censored, but also their time-dependent measurements are incomplete. This problem was motivated by a national longitudinal survey of youth data. Maximum likelihood estimation (MLE) method based on expectation-maximization (EM) algorithm is used for parameter estimation. Then missing information principle is applied to estimate the variance-covariance matrix of the MLEs. Simulation studies demonstrate that the proposed method works well in terms of bias, standard error, and power for samples of moderate size. The national longitudinal survey of youth 1997 (NLSY97) data is analyzed for illustration.展开更多
Laser welding is one of high efficiency, high energy density welding methods. Quality control should be applied to ensure good welding quality. Weld pool and keyhole contains abundant information of welding quality. G...Laser welding is one of high efficiency, high energy density welding methods. Quality control should be applied to ensure good welding quality. Weld pool and keyhole contains abundant information of welding quality. Good image processing algorithm is necessary in quality control system based on visual sensing. Aiming at the image captured by a coaxial visual sensing system for laser welding, an image processing algorithm is designed. An edge predicting method is proposed in image processing algorithm which is based on the fact that the local shape of weld pool can be fitted to a circle. The results show that the algorithm works well. It lays solid foundation for further quality control in laser welding.展开更多
A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response principle.The dynamic process of artificial immune response with operators such as immune cloning,mu...A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response principle.The dynamic process of artificial immune response with operators such as immune cloning,multi-scale variation and gradient-based diversity was modeled.Because the immune cloning operator was derived from a stimulation and suppression effect between antibodies and antigens,a sigmoid model that can clearly describe clonal proliferation was proposed.In addition,with the introduction of multiple populations and multi-scale variation,the algorithm can well maintain the population diversity during the dynamic searching process.Unlike traditional artificial immune algorithms,which require randomly generated cells added to the current population to explore its fitness landscape,AIDE uses a gradient-based diversity operator to speed up the optimization in the dynamic environments.Several reported algorithms were compared with AIDE by using Moving Peaks Benchmarks.Preliminary experiments show that AIDE can maintain high population diversity during the search process,simultaneously can speed up the optimization.Thus,AIDE is useful for the optimization of dynamic environments.展开更多
The healing temperature of suspen-dome with stacked arches(SDSA)and arch-supported single-layer lattice shell structures was investigated based on the genetic algorithm. The temperature field of arch under solar radia...The healing temperature of suspen-dome with stacked arches(SDSA)and arch-supported single-layer lattice shell structures was investigated based on the genetic algorithm. The temperature field of arch under solar radiation was derived by FLUENT to investigate the influence of solar radiation on the determination of the healing temperature. Moreover, a multi-scale model was established to apply the complex temperature field under solar radiation. The change in the mechanical response of these two kinds of structures with the healing temperature was discussed. It can be concluded that solar radiation has great influence on the healing temperature, and the genetic algorithm can be effectively used in the optimization of the healing temperature for hybrid structures.展开更多
基金the National Key Research and Development Program of China (Grant No.2022YFF0711400)the National Space Science Data Center Youth Open Project (Grant No. NSSDC2302001)
文摘Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.
基金support from the National Key Research and Development Program of China (Grant 2017YFB0202800)the National Natural Science Foundation of China, Basic Science Center for “Multiscale Problems in Nonlinear Mechanics” (Grant 11988102)+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant XDB22020200)the Chinese Academy of Sciences Center for Excellence in Complex System Mechanics
文摘Dislocation creep at elevated temperatures plays an important role for plastic deformation in crystalline metals.When using traditional discrete dislocation dynamics(DDD)to capture this process,we often need to update the forces on N dislocations involving~N 2 interactions.In this letter,we introduce a multi-scale algorithm to speed up the calculations by dividing a sample of interest into sub-domain grids:dislocations within a characteristic area interact following the conventional way,but their interaction with dislocations in other grids are simplified by lumping all dislocations in another grid as a super one.Such a multi-scale algorithm lowers the computational load to~N 1.5.We employed this algorithm to model dislocation creep in Al-Mg alloy.The simulation leads to a power-law creep rate in consistent with experimental observations.The stress exponent of the power-law creep is a resultant of dislocations climb for~5 and viscous dislocations glide for~3.
基金The National Key Research and Development Program of China under contract No.2022YFF0801404.
文摘Ocean observations are inherently characterized by irregular temporal and spatial distributions,as well as heterogeneous spatial resolutions and error characteristics arising from the use of diverse observational platforms and techniques.To enable their application across a broad range of scientific and practical problems,it is essential to map these heterogeneous datasets into temporally and spatially consistent gridded products.Optimal Interpolation remains the most widely adopted algorithm for the mapping of oceanographic data.Two principal implementations of the optimal interpolation algorithm are commonly employed.The first,known as the basic optimal interpolation,is derived from the theory of optimal estimation and involves computationally intensive matrix operations,posing significant challenges when applied to high-dimensional problems.The second,referred to as the point-wise optimal interpolation,reduces computational complexity through point-wise estimation,thereby circumventing high-dimensional operations;however,this approach results in a substantially higher overall computational cost.In this study,a novel optimal interpolation algorithm is proposed that utilizes the Kronecker product to approximate the background error covariance matrix.This formulation enables the decomposition of high-dimensional matrix operations into smaller,computationally tractable sub-problems,thereby improving the scalability of optimal interpolation for large spatial domains with dense observational coverage.Building upon this framework,a multi-scale optimal interpolation method is further developed to enhance the integration of observational datasets with widely varying spatial resolutions,thereby improving the accuracy and applicability of the resulting gridded products.
基金Supported by the National Natural Science Foundation of China(70071042,60073043,and 60133010)
文摘Based on the analysis of previous genetic algorithms (GAs) for TSP, a novel method called Ge- GA is proposed. It combines gene pool and GA so as to direct the evolution of the whole population. The core of Ge- GA is the construction of gene pool and how to apply it to GA. Different from standard GAs, Ge- GA aims to enhance the ability of exploration and exploitation by incorporating global search with local search. On one hand a local search called Ge- Lo-calSearch operator is proposed to improve the solution quality, on the other hand the modified Inver-Over operator called Ge InverOver is considered as a global search mechanism to expand solution space of local minimal. Both of these operators are based on the gene pool. Our algorithm is applied to 11 well-known traveling salesman problems whose numbers of cities are from 70 to 1577 cities. The experiments results indicate that Ge- GA has great robustness for TSP. For each test instance, the average value of solution quality, found in accepted time, stays within 0. 001% from the optimum.
基金Project (10776020) supported by the Joint Foundation of the National Natural Science Foundation of China and China Academy of Engineering Physics
文摘In order to obtain good welding quality, it is necessary to apply quality control because there are many influencing factors in laser welding process. The key to realize welding quality control is to obtain the quality information. Abundant weld quality information is contained in weld pool and keyhole. Aiming at Nd：YAG laser welding of stainless steel, a coaxial visual sensing system was constructed. The images of weld pool and keyhole were obtained. Based on the gray character of weld pool and keyhole in images, an image processing algorithm was designed. The search start point and search criteria of weld pool and keyhole edge were determined respectively.
基金supported by the National Natural Foundation of China(Grant No.51875384)the Natural Science Foundation of Shanxi Province(Grant No.201601D011036)the Natural Science Foundation of Shanxi Province(Grant No.201801D121082)
文摘Automatic on-line detection of welding deviation based on machine vision is one of the key technologies of arc welding robot tracking welding,in which obtaining high quality weld pool image and accurate welding deviation detection algorithm are two important steps of tracking welding.Through the research and analysis of the weld pool image of gas metal arc welding(GMAW),it was found that the weld pool contains abundant welding information.First,the average gray value of the weld pool image can reflect the interference degree of arc to weld pool image and the heat input of welding process.Secondly,the tip of the weld pool image contour can reflect the center of the groove gap.Finally,the horizontal distance between the center coordinate of the wire contour and the tip coordinate of the weld pool image contour can reflect the welding deviation.On the basis of analyzing the characteristics of weld pool image,this paper proposes a new method of weld seam deviation detection,which includes the collection of weld pool image,image preprocessing,contour extraction and deviation calculation.The results of the tests and analyses showed that the maximum error of the on-line welding deviation obtained was about 2 pixels(0.17 mm)when the welding speed was≤60 cm/min,and the algorithm was stable enough to meet the requirements of real-time deviation detection for I-groove butt welding.The method can be applied to the on-line automatic welding deviation detection of arc welding robot.
文摘Often in longitudinal studies, some subjects complete their follow-up visits, but others miss their visits due to various reasons. For those who miss follow-up visits, some of them might learn that the event of interest has already happened when they come back. In this case, not only are their event times interval-censored, but also their time-dependent measurements are incomplete. This problem was motivated by a national longitudinal survey of youth data. Maximum likelihood estimation (MLE) method based on expectation-maximization (EM) algorithm is used for parameter estimation. Then missing information principle is applied to estimate the variance-covariance matrix of the MLEs. Simulation studies demonstrate that the proposed method works well in terms of bias, standard error, and power for samples of moderate size. The national longitudinal survey of youth 1997 (NLSY97) data is analyzed for illustration.
文摘Laser welding is one of high efficiency, high energy density welding methods. Quality control should be applied to ensure good welding quality. Weld pool and keyhole contains abundant information of welding quality. Good image processing algorithm is necessary in quality control system based on visual sensing. Aiming at the image captured by a coaxial visual sensing system for laser welding, an image processing algorithm is designed. An edge predicting method is proposed in image processing algorithm which is based on the fact that the local shape of weld pool can be fitted to a circle. The results show that the algorithm works well. It lays solid foundation for further quality control in laser welding.
基金Project(60625302) supported by the National Natural Science Foundation for Distinguished Young Scholars of ChinaProject(2009CB320603) supported by the National Basic Research Program of China+5 种基金Projects(10dz1121900,10JC1403400) supported by Shanghai Key Technologies R & D ProgramProject supported by the Fundamental Research Funds for the Central Universities in ChinaProject(200802511011) supported by the New Teacher Program of Specialized Research Fund for the Doctoral Program of Higher Education in ChinaProject(Y1090548) supported by Zhejiang Provincial Natural Science Fund,ChinaProject(2011C21077) supported by Zhejiang Technology Programme,ChinaProject(2011A610173) supported by Ningbo Natural Science Fund,China
文摘A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response principle.The dynamic process of artificial immune response with operators such as immune cloning,multi-scale variation and gradient-based diversity was modeled.Because the immune cloning operator was derived from a stimulation and suppression effect between antibodies and antigens,a sigmoid model that can clearly describe clonal proliferation was proposed.In addition,with the introduction of multiple populations and multi-scale variation,the algorithm can well maintain the population diversity during the dynamic searching process.Unlike traditional artificial immune algorithms,which require randomly generated cells added to the current population to explore its fitness landscape,AIDE uses a gradient-based diversity operator to speed up the optimization in the dynamic environments.Several reported algorithms were compared with AIDE by using Moving Peaks Benchmarks.Preliminary experiments show that AIDE can maintain high population diversity during the search process,simultaneously can speed up the optimization.Thus,AIDE is useful for the optimization of dynamic environments.
基金Supported by the National Natural Science Foundation of China(No.51208355)
文摘The healing temperature of suspen-dome with stacked arches(SDSA)and arch-supported single-layer lattice shell structures was investigated based on the genetic algorithm. The temperature field of arch under solar radiation was derived by FLUENT to investigate the influence of solar radiation on the determination of the healing temperature. Moreover, a multi-scale model was established to apply the complex temperature field under solar radiation. The change in the mechanical response of these two kinds of structures with the healing temperature was discussed. It can be concluded that solar radiation has great influence on the healing temperature, and the genetic algorithm can be effectively used in the optimization of the healing temperature for hybrid structures.
