Two-dimensional energetic materials(2DEMs),characterized by their exceptional interlayer sliding properties,are recognized as exemplar of low-sensitivity energetic materials.However,the diversity of available 2DEMs is...Two-dimensional energetic materials(2DEMs),characterized by their exceptional interlayer sliding properties,are recognized as exemplar of low-sensitivity energetic materials.However,the diversity of available 2DEMs is severely constrained by the absence of efficient methods for rapidly predicting crystal packing modes from molecular structures,impeding the high-throughput rational design of such materials.In this study,we employed quantified indicators,such as hydrogen bond dimension and maximum planar separation,to quickly screen 172DEM and 16 non-2DEM crystal structures from a crystal database.They were subsequently compared and analyzed,focusing on hydrogen bond donor-acceptor combinations,skeleton features,and intermolecular interactions.Our findings suggest that theπ-πpacking interaction energy is a key determinant in the formation of layered packing modes by planar energetic molecules,with its magnitude primarily influenced by the strongest dimericπ-πinteraction(π-π2max).Consequently,we have delineated a critical threshold forπ-π2max to discern layered packing modes and formulated a theoretical model for predictingπ-π2max,grounded in molecular electrostatic potential and dipole moment analysis.The predictive efficacy of this model was substantiated through external validation on a test set comprising 31 planar energetic molecular crystals,achieving an accuracy of 84%and a recall of 75%.Furthermore,the proposed model shows superior classification predictive performance compared to typical machine learning methods,such as random forest,on the external validation samples.This contribution introduces a novel methodology for the identification of crystal packing modes in 2DEMs,potentially accelerating the design and synthesis of high-energy,low-sensitivity 2DEMs.展开更多
This study employs a data-driven methodology that embeds the principle of dimensional invariance into an artificial neural network to automatically identify dominant dimensionless quantities in the penetration of rod ...This study employs a data-driven methodology that embeds the principle of dimensional invariance into an artificial neural network to automatically identify dominant dimensionless quantities in the penetration of rod projectiles into semi-infinite metal targets from experimental measurements.The derived mathematical expressions of dimensionless quantities are simplified by the examination of the exponent matrix and coupling relationships between feature variables.As a physics-based dimension reduction methodology,this way reduces high-dimensional parameter spaces to descriptions involving only a few physically interpretable dimensionless quantities in penetrating cases.Then the relative importance of various dimensionless feature variables on the penetration efficiencies for four impacting conditions is evaluated through feature selection engineering.The results indicate that the selected critical dimensionless feature variables by this synergistic method,without referring to the complex theoretical equations and aiding in the detailed knowledge of penetration mechanics,are in accordance with those reported in the reference.Lastly,the determined dimensionless quantities can be efficiently applied to conduct semi-empirical analysis for the specific penetrating case,and the reliability of regression functions is validated.展开更多
We establish the Hausdorff dimension of the graph of general Markov processes on Rd based on some probability estimates of the processes staying or leaving small balls in small time.In particular,our results indicate ...We establish the Hausdorff dimension of the graph of general Markov processes on Rd based on some probability estimates of the processes staying or leaving small balls in small time.In particular,our results indicate that,for symmetric diffusion processes(withα=2)or symmetricα-stable-like processes(withα∈(0,2))on Rd,it holds almost surely that dimH GrX([0,1])=1{α<1}+(2−1/α)1{α≥1,d=1}+(d∧α)1{α≥1,d≥2}.We also systematically prove the corresponding results about the Hausdorff dimension of the range of the processes.展开更多
Massive amounts of data are acquired in modern and future information technology industries such as communication,radar,and remote sensing.The presence of large dimensionality and size in these data offers new opportu...Massive amounts of data are acquired in modern and future information technology industries such as communication,radar,and remote sensing.The presence of large dimensionality and size in these data offers new opportunities to enhance the performance of signal processing in such applications and even motivate new ones.However,the curse of dimensionality is always a challenge when processing such high-dimensional signals.In practical tasks,high-dimensional signals need to be acquired,processed,and analyzed with high accuracy,robustness,and computational efficiency.This special section aims to address these challenges,where articles attempt to develop new theories and methods that are best suited to the high dimensional nature of the signals involved,and explore modern and emerging applications in this area.展开更多
With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direc...With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment.展开更多
The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers...The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.展开更多
In the course of mechanical part designing, process p lanning and assembling designing, we often have to calculate and analyse a dimen sion chain. Traditionally, a dimension chain is established and calculated m anual...In the course of mechanical part designing, process p lanning and assembling designing, we often have to calculate and analyse a dimen sion chain. Traditionally, a dimension chain is established and calculated m anually. With wide computer application in the field of mechanical design and ma nufacture, people began to use a computer to acquire and calculate a dimension c hain automatically. In reported work, a dimension chain can be established and c alculated automatically. However, dimension text values of dimensions composing a dimension chain and these dimensions’ tolerance’s upper values and lower valu es are put into a computer manually, which is inefficient and easy to make mis takes. In order to overcome above difficulties. it is very important to acquir e noted dimensions automatically, furthermore analyse and calculate a dimens ion chain, then show results. At present AutoCAD softwares of Autodesk company h ave been used popularly in mechanical designing. For automatically acquiring noted dimensions, analyzing and calculating a dimension chain in a design draw in AutoCAD, this paper introduces the solvable scheme of automatic dimension acq uisition and dimension chain calculation in AutoCAD by ObjectARX. ObjectARX is a developing tool for AutoCAD. In this paper a dimension chain is expressed b y three matrixes, which respectively stand for dimension text value matrix, tole rance’s upper value matrix and tolerance’s lower value matrix. The developed p rogram can be used to both calculate a assembling dimension chain, and a process dimension chain. When the program running in AutoCAD, noted dimensions comp osing a dimension chain in AutoCAD are selected in turn with a mouse, then the c omputer begin to calculate the dimension chain and results are shown in a dialog box. A running example is given in this paper.展开更多
The split-Hopkinson pressure bar(SHPB)and digital image correlation(DIC)techniques are combined to analyze the dynamic compressive failure process of coal samples,and the box fractal dimension is used to quantitativel...The split-Hopkinson pressure bar(SHPB)and digital image correlation(DIC)techniques are combined to analyze the dynamic compressive failure process of coal samples,and the box fractal dimension is used to quantitatively analyze the dynamic changes in the coal sample cracks under impact load conditions with different loading rates.The experimental results show that the fractal dimension can quantitatively describe the evolution process of coal fractures under dynamic load.During the dynamic compression process,the evolution of the coal sample cracks presents distinct stages.In the crack propagation stage,the fractal dimension increases rapidly with the progress of loading,and in the crack widening stage,the fractal dimension increases slowly with the progress of loading.The initiation of the crack propagation phase of the coal samples gradually occurs more quickly with increasing loading rate;the initial cracks appear earlier.At the same loading time point,when the loading rate is greater,the fractal dimension of the cracks observed in the coal sample is greater.展开更多
In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the researc...In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.展开更多
We assembled approximately 328 seismic records. The data set was from 4 digitally recording long-period and broadband stations of CDSN. We carried out the inversion based on the partitioned waveform inversion (PWI). I...We assembled approximately 328 seismic records. The data set was from 4 digitally recording long-period and broadband stations of CDSN. We carried out the inversion based on the partitioned waveform inversion (PWI). It partitions the large-scale optimization problem into a number of independent small-scale problems. We adopted surface waveform inversion with an equal block (2((2() discretization in order to acquire the images of shear velocity structure at different depths (from surface to 430 km) in the crust and upper-mantle. The resolution of all these anomalies has been established with (check-board( resolution tests. These results show significant difference in velocity, lithosphere and asthenosphere structure between South China Sea and its adjacent regions.展开更多
In the reliability analysis of slope, the performance functions derived from the most available stability analysis procedures of slopes are usually implicit and cannot be solved by first-order second-moment approach. ...In the reliability analysis of slope, the performance functions derived from the most available stability analysis procedures of slopes are usually implicit and cannot be solved by first-order second-moment approach. A new reliability analysis approach was presented based on three-dimensional Morgenstem-Price method to investigate three-dimensional effect of landslide in stability analyses. To obtain the reliability index, Support Vector Machine （SVM） was applied to approximate the performance function. The time-consuming of this approach is only 0.028% of that using Monte-Carlo method at the same computation accuracy. Also, the influence of time effect of shearing strength parameters of slope soils on the long-term reliability of three-dimensional slopes was investigated by this new approach. It is found that the reliability index of the slope would decrease by 52.54% and the failure probability would increase from 0.000 705% to 1.966%. In the end, the impact of variation coefficients of c andfon reliability index of slopes was taken into discussion and the changing trend was observed.展开更多
Principles of dimensional analysis are applied in a new interpretation of penetration of ceramic targets subjected to hypervelocity impact. The analysis results in a power series representation – in terms of inverse ...Principles of dimensional analysis are applied in a new interpretation of penetration of ceramic targets subjected to hypervelocity impact. The analysis results in a power series representation – in terms of inverse velocity – of normalized depth of penetration that reduces to the hydrodynamic solution at high impact velocities. Specifically considered are test data from four literature sources involving penetration of confined thick ceramic targets by tungsten long rod projectiles. The ceramics are AD-995 alumina, aluminum nitride, silicon carbide, and boron carbide.Test data can be accurately represented by the linear form of the power series, whereby the same value of a single fitting parameter applies remarkably well for all four ceramics. Comparison of the present model with others in the literature(e.g., Tate's theory) demonstrates a target resistance stress that depends on impact velocity, linearly in the limiting case. Comparison of the present analysis with recent research involving penetration of thin ceramic tiles at lower typical impact velocities confirms the importance of target properties related to fracture and shear strength at the Hugoniot Elastic Limit(HEL) only in the latter. In contrast, in the former(i.e., hypervelocity and thick target) experiments, the current analysis demonstrates dominant dependence of penetration depth only by target mass density. Such comparisons suggest transitions from microstructure-controlled to density-controlled penetration resistance with increasing impact velocity and ceramic target thickness.Production and hosting by Elsevier B.V. on behalf of China Ordnance Society.展开更多
A fractal pore structure model of combustible cartridge cases was established by virtue of the fractal geometry. Pore structure information, such as backbone fractal dimension and pore fractal dimension, of four kinds...A fractal pore structure model of combustible cartridge cases was established by virtue of the fractal geometry. Pore structure information, such as backbone fractal dimension and pore fractal dimension, of four kinds of combustible cartridge case were obtained by mercury intrusion porosimetry (MIP) . The formation mechanism of fractal pore structure of combustible cartridge was studied. The results show that the backbone fractal dimension consists of the component and influenced by the component number and size of components; the pore percolation fractal dimension reflects the pore structures of components; and the fractal dimension of pore structure is positively relative to the tensile strength of combustible cartridge case.展开更多
Information analysis of high dimensional data was carried out through similarity measure application. High dimensional data were considered as the a typical structure. Additionally, overlapped and non-overlapped data ...Information analysis of high dimensional data was carried out through similarity measure application. High dimensional data were considered as the a typical structure. Additionally, overlapped and non-overlapped data were introduced, and similarity measure analysis was also illustrated and compared with conventional similarity measure. As a result, overlapped data comparison was possible to present similarity with conventional similarity measure. Non-overlapped data similarity analysis provided the clue to solve the similarity of high dimensional data. Considering high dimensional data analysis was designed with consideration of neighborhoods information. Conservative and strict solutions were proposed. Proposed similarity measure was applied to express financial fraud among multi dimensional datasets. In illustrative example, financial fraud similarity with respect to age, gender, qualification and job was presented. And with the proposed similarity measure, high dimensional personal data were calculated to evaluate how similar to the financial fraud. Calculation results show that the actual fraud has rather high similarity measure compared to the average, from minimal 0.0609 to maximal 0.1667.展开更多
The structure and working principle of a self-deigned high pressure electronic pneumatic pressure reducing valve (EPPRV) with slide pilot are introduced.The resistance value formulas and the relationship between the r...The structure and working principle of a self-deigned high pressure electronic pneumatic pressure reducing valve (EPPRV) with slide pilot are introduced.The resistance value formulas and the relationship between the resistance and pressure of three typical pneumatic resistances are obtained.Then,the method of static characteristics analysis only considering pneumatic resistances is proposed,the resistance network from gas supply to load is built up,and the mathematical model is derived from the flow rate formulas and flow conservation equations,with the compressibility of high pressure gas and temperature drop during the expansion considered in the model.Finally,the pilot spool displacement of 1.5 mm at an output pressure of 15MPa and the enlarging operating stroke of the pilot spool are taken as optimization targets,and the optimization is carried out based on genetic algorithm and the model mentioned above.The results show that the static characteristics of the EPPRV are significantly improved.The idea of static characteristics analysis and optimization based on pneumatic resistance network is valuable for the design of pneumatic components or system.展开更多
Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ri...Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ring's position is asymmetrical.All of these cause that the ring's dimensions cannot be measured directly.Through analyzing the relationships among the dimensions of ring blanks,the positions of rolls and the ring's inner and outer diameter,the soft measurement model of ring's dimensions is established based on the radial basis function neural network(RBFNN).A mass of data samples are obtained from VHRR finite element(FE) simulations to train and test the soft measurement NN model,and the model's structure parameters are deduced and optimized by genetic algorithm(GA).Finally,the soft measurement system of ring's dimensions is established and validated by the VHRR experiments.The ring's dimensions were measured artificially and calculated by the soft measurement NN model.The results show that the calculation values of GA-RBFNN model are close to the artificial measurement data.In addition,the calculation accuracy of GA-RBFNN model is higher than that of RBFNN model.The research results suggest that the soft measurement NN model has high precision and flexibility.The research can provide practical methods and theoretical guidance for the accurate measurement of VHRR process.展开更多
An event-triggered scheme is proposed to solve the problems of robust guaranteed cost control for a class of two-dimensional(2-D)discrete-time systems.Firstly,an eventtriggered scheme is proposed for 2-D discrete-time...An event-triggered scheme is proposed to solve the problems of robust guaranteed cost control for a class of two-dimensional(2-D)discrete-time systems.Firstly,an eventtriggered scheme is proposed for 2-D discrete-time systems with parameter uncertainties and sector nonlinearities.Then,according to the Lyapunov functional method,the sufficient conditions for the existence of event-triggered robust guaranteed cost controller for 2-D discrete-time systems with parameter uncertainties and sector nonlinearities are given.Furthermore,based on the sufficient conditions and the linear matrix inequality(LMI)technique,the problem of designing event-triggered robust guaranteed cost controller is transformed into a feasible solution problem of LMI.Finally,a numerical example is given to demonstrate that,under the proposed event-triggered robust guaranteed cost control,the closed-loop system is asymptotically stable and fewer communication resources are occupied.展开更多
The Confucianism has played a prominent role for thousands of years in boosting the tenacity of the Chinese nation towards innovation and development as well as in promoting and inheriting the traditional Chinese cult...The Confucianism has played a prominent role for thousands of years in boosting the tenacity of the Chinese nation towards innovation and development as well as in promoting and inheriting the traditional Chinese culture. Based on the five constant virtues of Confucianism,this paper analyzes the relationship between "benevolence,righteousness,etiquette,wisdom and credit"and creditability that We Media should construct,and elaborates the construction of value dimension system of We Media's creditability on talents, environments,orientations and innovations from four aspects. Namely,the cognitive and spiritual orientations that reinforce the five constant virtues,the propaganda cultivation that fuses them and the endogenous impetus stimulated by using them as reference.This paper is designed to tell all of the media and media practitioners to constantly remain vigilant of the social responsibilities they are taking and the social value they should create.T hey should take an initiative to guide their serving objects to foster a proper consensus outlook and value and meeting the mass audience's demands and desires on information.展开更多
基金support from National Natural Science Foundation of China(Grant Nos.22275145,22305189and 21875184)Natural Science Foundation of Shaanxi Province(Grant Nos.2022JC-10 and 2024JC-YBQN-0112).
文摘Two-dimensional energetic materials(2DEMs),characterized by their exceptional interlayer sliding properties,are recognized as exemplar of low-sensitivity energetic materials.However,the diversity of available 2DEMs is severely constrained by the absence of efficient methods for rapidly predicting crystal packing modes from molecular structures,impeding the high-throughput rational design of such materials.In this study,we employed quantified indicators,such as hydrogen bond dimension and maximum planar separation,to quickly screen 172DEM and 16 non-2DEM crystal structures from a crystal database.They were subsequently compared and analyzed,focusing on hydrogen bond donor-acceptor combinations,skeleton features,and intermolecular interactions.Our findings suggest that theπ-πpacking interaction energy is a key determinant in the formation of layered packing modes by planar energetic molecules,with its magnitude primarily influenced by the strongest dimericπ-πinteraction(π-π2max).Consequently,we have delineated a critical threshold forπ-π2max to discern layered packing modes and formulated a theoretical model for predictingπ-π2max,grounded in molecular electrostatic potential and dipole moment analysis.The predictive efficacy of this model was substantiated through external validation on a test set comprising 31 planar energetic molecular crystals,achieving an accuracy of 84%and a recall of 75%.Furthermore,the proposed model shows superior classification predictive performance compared to typical machine learning methods,such as random forest,on the external validation samples.This contribution introduces a novel methodology for the identification of crystal packing modes in 2DEMs,potentially accelerating the design and synthesis of high-energy,low-sensitivity 2DEMs.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272257,12102292,12032006)the special fund for Science and Technology Innovation Teams of Shanxi Province(Nos.202204051002006).
文摘This study employs a data-driven methodology that embeds the principle of dimensional invariance into an artificial neural network to automatically identify dominant dimensionless quantities in the penetration of rod projectiles into semi-infinite metal targets from experimental measurements.The derived mathematical expressions of dimensionless quantities are simplified by the examination of the exponent matrix and coupling relationships between feature variables.As a physics-based dimension reduction methodology,this way reduces high-dimensional parameter spaces to descriptions involving only a few physically interpretable dimensionless quantities in penetrating cases.Then the relative importance of various dimensionless feature variables on the penetration efficiencies for four impacting conditions is evaluated through feature selection engineering.The results indicate that the selected critical dimensionless feature variables by this synergistic method,without referring to the complex theoretical equations and aiding in the detailed knowledge of penetration mechanics,are in accordance with those reported in the reference.Lastly,the determined dimensionless quantities can be efficiently applied to conduct semi-empirical analysis for the specific penetrating case,and the reliability of regression functions is validated.
基金supported by Leshan Normal University Scientific Research Start-up Project for Introducing High-level Talents(Grand No.RC2024001).
文摘We establish the Hausdorff dimension of the graph of general Markov processes on Rd based on some probability estimates of the processes staying or leaving small balls in small time.In particular,our results indicate that,for symmetric diffusion processes(withα=2)or symmetricα-stable-like processes(withα∈(0,2))on Rd,it holds almost surely that dimH GrX([0,1])=1{α<1}+(2−1/α)1{α≥1,d=1}+(d∧α)1{α≥1,d≥2}.We also systematically prove the corresponding results about the Hausdorff dimension of the range of the processes.
文摘Massive amounts of data are acquired in modern and future information technology industries such as communication,radar,and remote sensing.The presence of large dimensionality and size in these data offers new opportunities to enhance the performance of signal processing in such applications and even motivate new ones.However,the curse of dimensionality is always a challenge when processing such high-dimensional signals.In practical tasks,high-dimensional signals need to be acquired,processed,and analyzed with high accuracy,robustness,and computational efficiency.This special section aims to address these challenges,where articles attempt to develop new theories and methods that are best suited to the high dimensional nature of the signals involved,and explore modern and emerging applications in this area.
基金supported by the National Basic Research Program of China。
文摘With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment.
基金This project was supported by the fundation of the Academy of Finland (201353)
文摘The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.
文摘In the course of mechanical part designing, process p lanning and assembling designing, we often have to calculate and analyse a dimen sion chain. Traditionally, a dimension chain is established and calculated m anually. With wide computer application in the field of mechanical design and ma nufacture, people began to use a computer to acquire and calculate a dimension c hain automatically. In reported work, a dimension chain can be established and c alculated automatically. However, dimension text values of dimensions composing a dimension chain and these dimensions’ tolerance’s upper values and lower valu es are put into a computer manually, which is inefficient and easy to make mis takes. In order to overcome above difficulties. it is very important to acquir e noted dimensions automatically, furthermore analyse and calculate a dimens ion chain, then show results. At present AutoCAD softwares of Autodesk company h ave been used popularly in mechanical designing. For automatically acquiring noted dimensions, analyzing and calculating a dimension chain in a design draw in AutoCAD, this paper introduces the solvable scheme of automatic dimension acq uisition and dimension chain calculation in AutoCAD by ObjectARX. ObjectARX is a developing tool for AutoCAD. In this paper a dimension chain is expressed b y three matrixes, which respectively stand for dimension text value matrix, tole rance’s upper value matrix and tolerance’s lower value matrix. The developed p rogram can be used to both calculate a assembling dimension chain, and a process dimension chain. When the program running in AutoCAD, noted dimensions comp osing a dimension chain in AutoCAD are selected in turn with a mouse, then the c omputer begin to calculate the dimension chain and results are shown in a dialog box. A running example is given in this paper.
基金Projects(51822403,51827901)supported by the National Natural Science Foundation of ChinaProject(2019ZT08G315)supported by the Department of Science and Technology of Guangdong Province,China。
文摘The split-Hopkinson pressure bar(SHPB)and digital image correlation(DIC)techniques are combined to analyze the dynamic compressive failure process of coal samples,and the box fractal dimension is used to quantitatively analyze the dynamic changes in the coal sample cracks under impact load conditions with different loading rates.The experimental results show that the fractal dimension can quantitatively describe the evolution process of coal fractures under dynamic load.During the dynamic compression process,the evolution of the coal sample cracks presents distinct stages.In the crack propagation stage,the fractal dimension increases rapidly with the progress of loading,and in the crack widening stage,the fractal dimension increases slowly with the progress of loading.The initiation of the crack propagation phase of the coal samples gradually occurs more quickly with increasing loading rate;the initial cracks appear earlier.At the same loading time point,when the loading rate is greater,the fractal dimension of the cracks observed in the coal sample is greater.
基金supported by the National Natural Science Foundation of China(5110505261173163)the Liaoning Provincial Natural Science Foundation of China(201102037)
文摘In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.
基金State Natural Scientific Foundation (49734150) and National High Performance Computation Foundation.
文摘We assembled approximately 328 seismic records. The data set was from 4 digitally recording long-period and broadband stations of CDSN. We carried out the inversion based on the partitioned waveform inversion (PWI). It partitions the large-scale optimization problem into a number of independent small-scale problems. We adopted surface waveform inversion with an equal block (2((2() discretization in order to acquire the images of shear velocity structure at different depths (from surface to 430 km) in the crust and upper-mantle. The resolution of all these anomalies has been established with (check-board( resolution tests. These results show significant difference in velocity, lithosphere and asthenosphere structure between South China Sea and its adjacent regions.
基金Project(50878082) supported by the National Natural Science Foundation of ChinaProject(200631880237) supported by the Science and Technology Program of West Transportation of the Ministry of Transportation of ChinaKey Project(09JJ3104) supported by the Natural Science Foundation of Hunan Province, China
文摘In the reliability analysis of slope, the performance functions derived from the most available stability analysis procedures of slopes are usually implicit and cannot be solved by first-order second-moment approach. A new reliability analysis approach was presented based on three-dimensional Morgenstem-Price method to investigate three-dimensional effect of landslide in stability analyses. To obtain the reliability index, Support Vector Machine （SVM） was applied to approximate the performance function. The time-consuming of this approach is only 0.028% of that using Monte-Carlo method at the same computation accuracy. Also, the influence of time effect of shearing strength parameters of slope soils on the long-term reliability of three-dimensional slopes was investigated by this new approach. It is found that the reliability index of the slope would decrease by 52.54% and the failure probability would increase from 0.000 705% to 1.966%. In the end, the impact of variation coefficients of c andfon reliability index of slopes was taken into discussion and the changing trend was observed.
文摘Principles of dimensional analysis are applied in a new interpretation of penetration of ceramic targets subjected to hypervelocity impact. The analysis results in a power series representation – in terms of inverse velocity – of normalized depth of penetration that reduces to the hydrodynamic solution at high impact velocities. Specifically considered are test data from four literature sources involving penetration of confined thick ceramic targets by tungsten long rod projectiles. The ceramics are AD-995 alumina, aluminum nitride, silicon carbide, and boron carbide.Test data can be accurately represented by the linear form of the power series, whereby the same value of a single fitting parameter applies remarkably well for all four ceramics. Comparison of the present model with others in the literature(e.g., Tate's theory) demonstrates a target resistance stress that depends on impact velocity, linearly in the limiting case. Comparison of the present analysis with recent research involving penetration of thin ceramic tiles at lower typical impact velocities confirms the importance of target properties related to fracture and shear strength at the Hugoniot Elastic Limit(HEL) only in the latter. In contrast, in the former(i.e., hypervelocity and thick target) experiments, the current analysis demonstrates dominant dependence of penetration depth only by target mass density. Such comparisons suggest transitions from microstructure-controlled to density-controlled penetration resistance with increasing impact velocity and ceramic target thickness.Production and hosting by Elsevier B.V. on behalf of China Ordnance Society.
基金Sponsored by Young Fund Programs of Explosives&Propellants ( HYZ08010202-4)
文摘A fractal pore structure model of combustible cartridge cases was established by virtue of the fractal geometry. Pore structure information, such as backbone fractal dimension and pore fractal dimension, of four kinds of combustible cartridge case were obtained by mercury intrusion porosimetry (MIP) . The formation mechanism of fractal pore structure of combustible cartridge was studied. The results show that the backbone fractal dimension consists of the component and influenced by the component number and size of components; the pore percolation fractal dimension reflects the pore structures of components; and the fractal dimension of pore structure is positively relative to the tensile strength of combustible cartridge case.
基金Project(RDF 11-02-03)supported by the Research Development Fund of XJTLU,China
文摘Information analysis of high dimensional data was carried out through similarity measure application. High dimensional data were considered as the a typical structure. Additionally, overlapped and non-overlapped data were introduced, and similarity measure analysis was also illustrated and compared with conventional similarity measure. As a result, overlapped data comparison was possible to present similarity with conventional similarity measure. Non-overlapped data similarity analysis provided the clue to solve the similarity of high dimensional data. Considering high dimensional data analysis was designed with consideration of neighborhoods information. Conservative and strict solutions were proposed. Proposed similarity measure was applied to express financial fraud among multi dimensional datasets. In illustrative example, financial fraud similarity with respect to age, gender, qualification and job was presented. And with the proposed similarity measure, high dimensional personal data were calculated to evaluate how similar to the financial fraud. Calculation results show that the actual fraud has rather high similarity measure compared to the average, from minimal 0.0609 to maximal 0.1667.
基金Project(50575202) supported by the National Natural Science Foundation of China
文摘The structure and working principle of a self-deigned high pressure electronic pneumatic pressure reducing valve (EPPRV) with slide pilot are introduced.The resistance value formulas and the relationship between the resistance and pressure of three typical pneumatic resistances are obtained.Then,the method of static characteristics analysis only considering pneumatic resistances is proposed,the resistance network from gas supply to load is built up,and the mathematical model is derived from the flow rate formulas and flow conservation equations,with the compressibility of high pressure gas and temperature drop during the expansion considered in the model.Finally,the pilot spool displacement of 1.5 mm at an output pressure of 15MPa and the enlarging operating stroke of the pilot spool are taken as optimization targets,and the optimization is carried out based on genetic algorithm and the model mentioned above.The results show that the static characteristics of the EPPRV are significantly improved.The idea of static characteristics analysis and optimization based on pneumatic resistance network is valuable for the design of pneumatic components or system.
基金Project(51205299)supported by the National Natural Science Foundation of ChinaProject(2015M582643)supported by the China Postdoctoral Science Foundation+2 种基金Project(2014BAA008)supported by the Science and Technology Support Program of Hubei Province,ChinaProject(2014-IV-144)supported by the Fundamental Research Funds for the Central Universities of ChinaProject(2012AAA07-01)supported by the Major Science and Technology Achievements Transformation&Industrialization Program of Hubei Province,China
文摘Vertical hot ring rolling(VHRR) process has the characteristics of nonlinearity,time-variation and being susceptible to disturbance.Furthermore,the ring's growth is quite fast within a short time,and the rolled ring's position is asymmetrical.All of these cause that the ring's dimensions cannot be measured directly.Through analyzing the relationships among the dimensions of ring blanks,the positions of rolls and the ring's inner and outer diameter,the soft measurement model of ring's dimensions is established based on the radial basis function neural network(RBFNN).A mass of data samples are obtained from VHRR finite element(FE) simulations to train and test the soft measurement NN model,and the model's structure parameters are deduced and optimized by genetic algorithm(GA).Finally,the soft measurement system of ring's dimensions is established and validated by the VHRR experiments.The ring's dimensions were measured artificially and calculated by the soft measurement NN model.The results show that the calculation values of GA-RBFNN model are close to the artificial measurement data.In addition,the calculation accuracy of GA-RBFNN model is higher than that of RBFNN model.The research results suggest that the soft measurement NN model has high precision and flexibility.The research can provide practical methods and theoretical guidance for the accurate measurement of VHRR process.
基金supported by the National Natural Science Foundation of China(61573129 U1804147)+2 种基金the Innovative Scientists and Technicians Team of Henan Provincial High Education(20IRTSTHN019)the Innovative Scientists and Technicians Team of Henan Polytechnic University(T2019-2 T2017-1)
文摘An event-triggered scheme is proposed to solve the problems of robust guaranteed cost control for a class of two-dimensional(2-D)discrete-time systems.Firstly,an eventtriggered scheme is proposed for 2-D discrete-time systems with parameter uncertainties and sector nonlinearities.Then,according to the Lyapunov functional method,the sufficient conditions for the existence of event-triggered robust guaranteed cost controller for 2-D discrete-time systems with parameter uncertainties and sector nonlinearities are given.Furthermore,based on the sufficient conditions and the linear matrix inequality(LMI)technique,the problem of designing event-triggered robust guaranteed cost controller is transformed into a feasible solution problem of LMI.Finally,a numerical example is given to demonstrate that,under the proposed event-triggered robust guaranteed cost control,the closed-loop system is asymptotically stable and fewer communication resources are occupied.
基金the rusult of the project of the Five Constant Virtues of Confucianism and Value Dimension Construction of Mainstream’s Credibility(Sk2014A440)
文摘The Confucianism has played a prominent role for thousands of years in boosting the tenacity of the Chinese nation towards innovation and development as well as in promoting and inheriting the traditional Chinese culture. Based on the five constant virtues of Confucianism,this paper analyzes the relationship between "benevolence,righteousness,etiquette,wisdom and credit"and creditability that We Media should construct,and elaborates the construction of value dimension system of We Media's creditability on talents, environments,orientations and innovations from four aspects. Namely,the cognitive and spiritual orientations that reinforce the five constant virtues,the propaganda cultivation that fuses them and the endogenous impetus stimulated by using them as reference.This paper is designed to tell all of the media and media practitioners to constantly remain vigilant of the social responsibilities they are taking and the social value they should create.T hey should take an initiative to guide their serving objects to foster a proper consensus outlook and value and meeting the mass audience's demands and desires on information.
