A segmented predictor-corrector method is proposed for hypersonic glide vehicles to address the issue of the slow computational speed of obtaining guidance commands using the traditional predictor-corrector guidance m...A segmented predictor-corrector method is proposed for hypersonic glide vehicles to address the issue of the slow computational speed of obtaining guidance commands using the traditional predictor-corrector guidance method.Firstly,an altitude-energy profile is designed,and the bank angle is derived analytically as the initial iteration value for the predictor-corrector method.The predictor-corrector guidance method has been improved by deriving an analytical form for predicting the range-to-go error,which greatly accelerates the iterative speed.Then,a segmented guidance algorithm is proposed.The above analytically predictor-corrector guidance method is adopted when the energy exceeds an energy threshold.When the energy is less than the threshold,the equidistant test method is used to calculate the bank angle command,which ensures guidance accuracy as well as computational efficiency.Additionally,an adaptive guidance cycle strategy is applied to reduce the computational time of the reentry guidance trajectory.Finally,the accuracy and robustness of the proposed method are verified through a series of simulations and Monte-Carlo experiments.Compared with the traditional integral method,the proposed method requires 75%less computation time on average and achieves a lower landing error.展开更多
Soft rock is one of the common geological conditions in coal mine underground water reservoir engineering.The cross-scale correlation analysis of water erosion soft lithology deterioration is very important for the sa...Soft rock is one of the common geological conditions in coal mine underground water reservoir engineering.The cross-scale correlation analysis of water erosion soft lithology deterioration is very important for the safety and stability of coal mine underground reservoir(CMUR)engineering.To address the issues of grain crowding and segmentation difficulties in cross-scale corelation analysis,as well as the limitations of traditional etching methods,this study proposes an image grain segmentation method based on deep learning algorithms,utilizing scanning electron microscopy and image process-ing techniques.The method successfully segments crowded grains and eliminates the interference from misplaced particles.In addition,indoor uniaxial compression tests were conducted to obtain the mechanical properties of sandstone samples with different water content.By quantitatively characterizing the macroscopic and microscopic deterioration degree of red sandstone samples with different water contents,the relationship between the strength changes of rock samples and the pet-rographic parameters such as grain size and grain shape is analyzed,and the influence law of soft lithology deterioration in CMUR engineering is revealed.The results indicate:(1)Water significantly weakens the mechanical properties and stability of soft rock.With increasing water content,the strength of sandstone samples continuously decreases,and the failure mode transitions from brittle to ductile failure.(2)The deterioration of micro-micro structures is the main cause of the decrease in mechanical properties of water-eroded soft rock.Grain size,grain area,and aspect ratio are negatively correlated with water content,indicating that hydrophilic minerals in soft rock dissolve under the action of water,leading to rock damage.(3)Grain size,area,and aspect ratio can serve as significant indicators for quantifying the strength changes of water-eroded soft rock.The research findings can be applied to stability assessment and disaster prevention in CMUR engineering.展开更多
AIM:To evaluate alterations in conjunctival vascular density(CVD)and macular capillary density(MCD)in female patients with type 2 diabetes mellitus(T2DM)and gestational diabetes mellitus(GDM)using optical coherence to...AIM:To evaluate alterations in conjunctival vascular density(CVD)and macular capillary density(MCD)in female patients with type 2 diabetes mellitus(T2DM)and gestational diabetes mellitus(GDM)using optical coherence tomography angiography(OCTA).METHODS:A total of 60 female participants were recruited,comprising 20 patients with T2DM,20 patients with GDM,and 20 healthy age-matched controls(HCs).OCTA was used to assess superficial and deep retinal and conjunctival capillary plexuses.Subsequently,changes in MCD were analyzed using a circular segmentation method(C1-C6),a hemispheric quadrant segmentation method[superior right(SR),superior left(SL),inferior left(IL),and inferior right(IR)],and the early treatment diabetic retinopathy study(ETDRS)segmentation method(S,I,R,L).RESULTS:OCTA unequivocally demonstrated that the variations in CVD among HCs,T2DM,and GDM groups were statistically significant(P<0.001).In the superficial retinal capillary plexus(sRCP),significant differences were observed in the densities of total microvascular(TMI),microvasculature(MIR),and macrovascular(MAR)between patients with T2DM and HCs(P<0.05).Furthermore,the GDM group exhibited a more substantial reduction in MIR density compared to the T2DM group(P<0.01).In the deep retinal capillary plexus(dRCP),significant differences in the densities of TMI and MIR were identified between the T2DM group and HCs(P<0.05),with a notable difference in TMI density also observed between the GDM and T2DM groups(P<0.01).In the receiver operating characteristic(ROC)curve analysis,the area under the ROC curve(AUC)for TMI in sRCP between the T2DM group and HCs was 0.975,with a 95%confidence interval(CI)of 0.941–1.The AUC for MIR was highest in dRCP,with an AUC value of 0.914 and a 95%CI ranging from 0.847 to 0.981.In comparing the GDM and T2DM groups,the AUC for I region was maximized in sRCP,achieving a value of 0.978 with a 95%CI of 0.953–1.Additionally,the AUC for R region was maximized in dRCP,reaching a value of 0.99 with a 95%CI of 0.975 to 1.CONCLUSION:The sRCP and dRCP densities show higher diagnostic sensitivity for T2DM and GDM.OCTA holds potential as a significant instrument for the early diagnosis and differentiation of T2DM and GDM.展开更多
Volume parameter is the basic content of a spatial body object morphology analysis.However,the challenge lies in the volume calculation of irregular objects.The point cloud slicing method proposed in this study effect...Volume parameter is the basic content of a spatial body object morphology analysis.However,the challenge lies in the volume calculation of irregular objects.The point cloud slicing method proposed in this study effectively works in calculating the volume of the point cloud of the spatial object obtained through three-dimensional laser scanning(3DLS).In this method,a uniformly spaced sequent slicing process is first conducted in a specific direction on the point cloud of the spatial object obtained through 3DLS.A series of discrete point cloud slices corresponding to the point cloud bodies are then obtained.Subsequently,the outline boundary polygon of the point cloud slicing is searched one by one in accordance with the slicing sequence and areas of the polygon.The point cloud slice is also calculated.Finally,the individual point cloud section volume is calculated through the slicing areas and the adjacent slicing gap.Thus,the total volume of the scanned spatial object can be calculated by summing up the individual volumes.According to the results and analysis of the calculated examples,the slice-based volume-calculating method for the point cloud of irregular objects obtained through 3DLS is correct,concise in process,reliable in results,efficient in calculation methods,and controllable on accuracy.This method comes as a good solution to the volume calculation of irregular objects.展开更多
Based on the multi-rigid body discretization model, namely, finite segment model,a chain multi-rigid-body-hinge-spring system model of a beam was presented, then a nonlinear parametrically exacted vibration equation o...Based on the multi-rigid body discretization model, namely, finite segment model,a chain multi-rigid-body-hinge-spring system model of a beam was presented, then a nonlinear parametrically exacted vibration equation of multi-degrees of freedom system was established using the coordination transformation method, and its resonance fields were derived by the restriction parameter method, that is, the dynamical buckling analysis of the beam. Because the deformation of a beam is not restricted by the discrete model and dynamic equation, the post buckling analysis can be done in above math model. The numerical solutions of a few examples were obtained by direct integrated method, which shows that the mechanical and math model gotten is correct.展开更多
The sequential rock remote sensing information is a group of rocks that are correlative in space or in space and time. For the sake of plottiug them, someone had brought forward the optimization segn.entotion metkod. ...The sequential rock remote sensing information is a group of rocks that are correlative in space or in space and time. For the sake of plottiug them, someone had brought forward the optimization segn.entotion metkod. We have ased this method to plot the sequential rock remote sensing information at tbe remote sensing hyperspetral test field of Daqing mountain, Inner Mongolia Autonomous Region, China, and found some disadvantages of this method. Therefore, we put forward the optimization dichotomy to plot them, and get better results. Finally we make a conclusion.展开更多
The principle and method of flexible multibody system dynamics is presented. The dynamic equation have been developed by means of Huston's method based on Kane's equation. In which the flexible members with g...The principle and method of flexible multibody system dynamics is presented. The dynamic equation have been developed by means of Huston's method based on Kane's equation. In which the flexible members with general cross-section characters were divided into finite segment models under the assumption of small strain. In order to decrease the degrees of freedom of the system and increase the efficiency of numerical calculation. the mode transformation has been introduced. A typical example is presented. and the foregoing method has been perfectly verified.展开更多
To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method propose...To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method proposed by the authors promotes the application of slope units.However,LSP modeling based on these slope units has not been performed.Moreover,the heterogeneity of conditioning factors in slope units is neglected,leading to incomplete input variables of LSP modeling.In this study,the slope units extracted by the MSS method are used to construct LSP modeling,and the heterogeneity of conditioning factors is represented by the internal variations of conditioning factors within slope unit using the descriptive statistics features of mean,standard deviation and range.Thus,slope units-based machine learning models considering internal variations of conditioning factors(variant slope-machine learning)are proposed.The Chongyi County is selected as the case study and is divided into 53,055 slope units.Fifteen original slope unit-based conditioning factors are expanded to 38 slope unit-based conditioning factors through considering their internal variations.Random forest(RF)and multi-layer perceptron(MLP)machine learning models are used to construct variant Slope-RF and Slope-MLP models.Meanwhile,the Slope-RF and Slope-MLP models without considering the internal variations of conditioning factors,and conventional grid units-based machine learning(Grid-RF and MLP)models are built for comparisons through the LSP performance assessments.Results show that the variant Slopemachine learning models have higher LSP performances than Slope-machine learning models;LSP results of variant Slope-machine learning models have stronger directivity and practical application than Grid-machine learning models.It is concluded that slope units extracted by MSS method can be appropriate for LSP modeling,and the heterogeneity of conditioning factors within slope units can more comprehensively reflect the relationships between conditioning factors and landslides.The research results have important reference significance for land use and landslide prevention.展开更多
With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significan...With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significant to achieve the goal of national carbon neutrality. However, most investigations focus on the on-board predictive cruise control(PCC) system,lack of research on CPCC architecture under CCS. Besides, the current PCC algorithms have the problems of a single control target and high computational complexity, which hinders the improvement of the control effect. In this paper, a layered architecture based on CCS is proposed to effectively address the realtime computing of CPCC system and the deployment of its algorithm on vehicle-cloud. In addition, based on the dynamic programming principle and the proposed road point segmentation method(RPSM), a PCC algorithm is designed to optimize the speed and gear of heavy trucks with slope information. Simulation results show that the CPCC system can adaptively control vehicle driving through the slope prediction, with fuel-saving rate of 6.17% in comparison with the constant cruise control. Also,compared with other similar algorithms, the PCC algorithm can make the engine operate more in the efficient zone by cooperatively optimizing the gear and speed. Moreover, the RPSM algorithm can reconfigure the road in advance, with a 91% roadpoint reduction rate, significantly reducing algorithm complexity.Therefore, this study has essential research significance for the economic driving of heavy trucks and the promotion of the CPCC system.展开更多
AIM：To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS：Fifty volunteers were enrolled in ...AIM：To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS：Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca,Romania,between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images,corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms,applying the standard boxcounting method. Statistical analyses were performed using the Graph Pad In Stat software.RESULTS：The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions（D_q）for q=0,1,2,the width of the multifractal spectrum（Δα=α_（max）-α_（min））and the spectrum arms＇ heights difference（│Δf│）of the normal images were expressed as mean±standard deviation（SD）：for segmented versions,D_0=1.7014±0.0057; D_1=1.6507±0.0058; D_2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions,D_0=1.6303±0.0051; D_1=1.6012±0.0059; D_2=1.5531± 0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions（D_q）for q=0,1,2,the width of the multifractal spectrum（Δα）and the spectrum arms＇ heights difference（│Δf│）of the segmented versions was slightly greater than the skeletonised versions.CONCLUSION：The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases.展开更多
Rainfall variability associated with climate change has enormous impacts on ecosystems, agriculture and people in West Africa but few studies have been devoted to it. Monthly rainfall data from 1901 to 2013, provided ...Rainfall variability associated with climate change has enormous impacts on ecosystems, agriculture and people in West Africa but few studies have been devoted to it. Monthly rainfall data from 1901 to 2013, provided by the Global Precipitation Climatology Center dataset, were analyzed using segmentation and empirical modal decomposition (EMD) methods to increase our knowledge on past and recent spatio-temporal rainfall trends and their impacts on the West African region. The results obtained showed that the peak of rainfall during the short rainy season is observed in September in Côte d’Ivoire, Ghana and Liberia. The temporal variability of this rainfall is marked by several breakpoints whose durations range from 2 to 70 years. The periods of change in the rainfall regime, characterized by the appearance of breakpoints, vary from one country to another and are of unequal duration. The main breakpoint appears after 1960. Periods of relative or normal increase or decrease in precipitation are observed before and after 1960. The long-term variability of this rainfall is characterized by a decrease in the amount of rainfall over all West African countries. The results of this study can be used as a tool to help raise awareness among populations for sustainable management of water resources in response to climate change and its adverse effects.展开更多
This paper analyses the characters of different bases of market segmentation and classes the bases into four kinds： observable general bases, observable product-specific bases, unobservable general bases and unobserv...This paper analyses the characters of different bases of market segmentation and classes the bases into four kinds： observable general bases, observable product-specific bases, unobservable general bases and unobservable product-specific bases. The result can be used in the future research of market segmentation.展开更多
In this paper, the exact analytical solution of the rectangular plate having simplysupported segments mixed with free segments of straight edges are first given by means of the method of reciprocal theorem.By comparis...In this paper, the exact analytical solution of the rectangular plate having simplysupported segments mixed with free segments of straight edges are first given by means of the method of reciprocal theorem.By comparison .we calculate the same question by finite element method.Thecomparison shows that the analytical solution is correct.展开更多
The appearanee of blood vessels is an important biomarker to distinguish diseased from healthy tissues in several fields of medical applications. Photoacoustie microangiography has the advantage of directly visualizin...The appearanee of blood vessels is an important biomarker to distinguish diseased from healthy tissues in several fields of medical applications. Photoacoustie microangiography has the advantage of directly visualizing blood vessel networks within mierocireulatory tissue. Usually these images are interpreted qualitatively. However, a quantitative analysis is needed to better describe the characteristics of the blood vessels. This Letter addresses this problem by leveraging an efficient multiscale Hessian filter-based segmentation method, and four measure- ment parameters are acquired. The feasibility of our approach is demonstrated on experimental data and we expect the proposed method to be beneficial for several microcireulatory disease studies.展开更多
To aid the magnetic anomaly detection(MAD)of underground ferromagnetic pipelines,this paper proposes a geometric modeling method based on the magnetic dipole reconstruction method(MDRM).First,the numerical modeling of...To aid the magnetic anomaly detection(MAD)of underground ferromagnetic pipelines,this paper proposes a geometric modeling method based on the magnetic dipole reconstruction method(MDRM).First,the numerical modeling of basic pipe components such as straight sections,bends and elbows,and tee joints are discussed and the relevant mathematical formulations for these components are derived.Next,after analyzing the function of MDRM and various element division strategies,the sectional division and blocked division methods are introduced and applied to the appropriate pipeline components to determine the volume and center coordinates of each element,establishing the general models for the three typical pipeline components considered.The resulting volume and center coordinates of each component are the fundamental parameters for determining the MAD forwarding of underground ferromagnetic pipelines using the MDRM.Finally,based on the combination and transformation of the basic pipeline components considered,the visualized geometric models of typical pipeline layouts including parallel pipelines,pipelines with elbows,and a pipeline with a tee joint are constructed.The results demonstrate the feasibility of the proposed method of geometric modeling for the MDRM,which can be further applied to the finite element modeling of these and other components when analyzing MAD data.Furthermore,the models with output parameters proposed in this paper establish a foundation for the inversion of MAD.展开更多
基金National Natural Science Foundation of China(Nos.61773387 and 62022061).
文摘A segmented predictor-corrector method is proposed for hypersonic glide vehicles to address the issue of the slow computational speed of obtaining guidance commands using the traditional predictor-corrector guidance method.Firstly,an altitude-energy profile is designed,and the bank angle is derived analytically as the initial iteration value for the predictor-corrector method.The predictor-corrector guidance method has been improved by deriving an analytical form for predicting the range-to-go error,which greatly accelerates the iterative speed.Then,a segmented guidance algorithm is proposed.The above analytically predictor-corrector guidance method is adopted when the energy exceeds an energy threshold.When the energy is less than the threshold,the equidistant test method is used to calculate the bank angle command,which ensures guidance accuracy as well as computational efficiency.Additionally,an adaptive guidance cycle strategy is applied to reduce the computational time of the reentry guidance trajectory.Finally,the accuracy and robustness of the proposed method are verified through a series of simulations and Monte-Carlo experiments.Compared with the traditional integral method,the proposed method requires 75%less computation time on average and achieves a lower landing error.
基金supported by the National Natural Science Foundation of China(51774196,52304093)China Postdoctoral Science Foundation(2023M741968)Shandong Provincial Natural Science Foundation(ZR2023ME086).
文摘Soft rock is one of the common geological conditions in coal mine underground water reservoir engineering.The cross-scale correlation analysis of water erosion soft lithology deterioration is very important for the safety and stability of coal mine underground reservoir(CMUR)engineering.To address the issues of grain crowding and segmentation difficulties in cross-scale corelation analysis,as well as the limitations of traditional etching methods,this study proposes an image grain segmentation method based on deep learning algorithms,utilizing scanning electron microscopy and image process-ing techniques.The method successfully segments crowded grains and eliminates the interference from misplaced particles.In addition,indoor uniaxial compression tests were conducted to obtain the mechanical properties of sandstone samples with different water content.By quantitatively characterizing the macroscopic and microscopic deterioration degree of red sandstone samples with different water contents,the relationship between the strength changes of rock samples and the pet-rographic parameters such as grain size and grain shape is analyzed,and the influence law of soft lithology deterioration in CMUR engineering is revealed.The results indicate:(1)Water significantly weakens the mechanical properties and stability of soft rock.With increasing water content,the strength of sandstone samples continuously decreases,and the failure mode transitions from brittle to ductile failure.(2)The deterioration of micro-micro structures is the main cause of the decrease in mechanical properties of water-eroded soft rock.Grain size,grain area,and aspect ratio are negatively correlated with water content,indicating that hydrophilic minerals in soft rock dissolve under the action of water,leading to rock damage.(3)Grain size,area,and aspect ratio can serve as significant indicators for quantifying the strength changes of water-eroded soft rock.The research findings can be applied to stability assessment and disaster prevention in CMUR engineering.
基金Supported by National Natural Science Foundation of China(No.82160195,No.82460203)The Science and Technology Innovation Program of Changde City(No.2023YD25).
文摘AIM:To evaluate alterations in conjunctival vascular density(CVD)and macular capillary density(MCD)in female patients with type 2 diabetes mellitus(T2DM)and gestational diabetes mellitus(GDM)using optical coherence tomography angiography(OCTA).METHODS:A total of 60 female participants were recruited,comprising 20 patients with T2DM,20 patients with GDM,and 20 healthy age-matched controls(HCs).OCTA was used to assess superficial and deep retinal and conjunctival capillary plexuses.Subsequently,changes in MCD were analyzed using a circular segmentation method(C1-C6),a hemispheric quadrant segmentation method[superior right(SR),superior left(SL),inferior left(IL),and inferior right(IR)],and the early treatment diabetic retinopathy study(ETDRS)segmentation method(S,I,R,L).RESULTS:OCTA unequivocally demonstrated that the variations in CVD among HCs,T2DM,and GDM groups were statistically significant(P<0.001).In the superficial retinal capillary plexus(sRCP),significant differences were observed in the densities of total microvascular(TMI),microvasculature(MIR),and macrovascular(MAR)between patients with T2DM and HCs(P<0.05).Furthermore,the GDM group exhibited a more substantial reduction in MIR density compared to the T2DM group(P<0.01).In the deep retinal capillary plexus(dRCP),significant differences in the densities of TMI and MIR were identified between the T2DM group and HCs(P<0.05),with a notable difference in TMI density also observed between the GDM and T2DM groups(P<0.01).In the receiver operating characteristic(ROC)curve analysis,the area under the ROC curve(AUC)for TMI in sRCP between the T2DM group and HCs was 0.975,with a 95%confidence interval(CI)of 0.941–1.The AUC for MIR was highest in dRCP,with an AUC value of 0.914 and a 95%CI ranging from 0.847 to 0.981.In comparing the GDM and T2DM groups,the AUC for I region was maximized in sRCP,achieving a value of 0.978 with a 95%CI of 0.953–1.Additionally,the AUC for R region was maximized in dRCP,reaching a value of 0.99 with a 95%CI of 0.975 to 1.CONCLUSION:The sRCP and dRCP densities show higher diagnostic sensitivity for T2DM and GDM.OCTA holds potential as a significant instrument for the early diagnosis and differentiation of T2DM and GDM.
文摘Volume parameter is the basic content of a spatial body object morphology analysis.However,the challenge lies in the volume calculation of irregular objects.The point cloud slicing method proposed in this study effectively works in calculating the volume of the point cloud of the spatial object obtained through three-dimensional laser scanning(3DLS).In this method,a uniformly spaced sequent slicing process is first conducted in a specific direction on the point cloud of the spatial object obtained through 3DLS.A series of discrete point cloud slices corresponding to the point cloud bodies are then obtained.Subsequently,the outline boundary polygon of the point cloud slicing is searched one by one in accordance with the slicing sequence and areas of the polygon.The point cloud slice is also calculated.Finally,the individual point cloud section volume is calculated through the slicing areas and the adjacent slicing gap.Thus,the total volume of the scanned spatial object can be calculated by summing up the individual volumes.According to the results and analysis of the calculated examples,the slice-based volume-calculating method for the point cloud of irregular objects obtained through 3DLS is correct,concise in process,reliable in results,efficient in calculation methods,and controllable on accuracy.This method comes as a good solution to the volume calculation of irregular objects.
文摘Based on the multi-rigid body discretization model, namely, finite segment model,a chain multi-rigid-body-hinge-spring system model of a beam was presented, then a nonlinear parametrically exacted vibration equation of multi-degrees of freedom system was established using the coordination transformation method, and its resonance fields were derived by the restriction parameter method, that is, the dynamical buckling analysis of the beam. Because the deformation of a beam is not restricted by the discrete model and dynamic equation, the post buckling analysis can be done in above math model. The numerical solutions of a few examples were obtained by direct integrated method, which shows that the mechanical and math model gotten is correct.
文摘The sequential rock remote sensing information is a group of rocks that are correlative in space or in space and time. For the sake of plottiug them, someone had brought forward the optimization segn.entotion metkod. We have ased this method to plot the sequential rock remote sensing information at tbe remote sensing hyperspetral test field of Daqing mountain, Inner Mongolia Autonomous Region, China, and found some disadvantages of this method. Therefore, we put forward the optimization dichotomy to plot them, and get better results. Finally we make a conclusion.
文摘The principle and method of flexible multibody system dynamics is presented. The dynamic equation have been developed by means of Huston's method based on Kane's equation. In which the flexible members with general cross-section characters were divided into finite segment models under the assumption of small strain. In order to decrease the degrees of freedom of the system and increase the efficiency of numerical calculation. the mode transformation has been introduced. A typical example is presented. and the foregoing method has been perfectly verified.
基金funded by the Natural Science Foundation of China(Grant Nos.41807285,41972280 and 52179103).
文摘To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method proposed by the authors promotes the application of slope units.However,LSP modeling based on these slope units has not been performed.Moreover,the heterogeneity of conditioning factors in slope units is neglected,leading to incomplete input variables of LSP modeling.In this study,the slope units extracted by the MSS method are used to construct LSP modeling,and the heterogeneity of conditioning factors is represented by the internal variations of conditioning factors within slope unit using the descriptive statistics features of mean,standard deviation and range.Thus,slope units-based machine learning models considering internal variations of conditioning factors(variant slope-machine learning)are proposed.The Chongyi County is selected as the case study and is divided into 53,055 slope units.Fifteen original slope unit-based conditioning factors are expanded to 38 slope unit-based conditioning factors through considering their internal variations.Random forest(RF)and multi-layer perceptron(MLP)machine learning models are used to construct variant Slope-RF and Slope-MLP models.Meanwhile,the Slope-RF and Slope-MLP models without considering the internal variations of conditioning factors,and conventional grid units-based machine learning(Grid-RF and MLP)models are built for comparisons through the LSP performance assessments.Results show that the variant Slopemachine learning models have higher LSP performances than Slope-machine learning models;LSP results of variant Slope-machine learning models have stronger directivity and practical application than Grid-machine learning models.It is concluded that slope units extracted by MSS method can be appropriate for LSP modeling,and the heterogeneity of conditioning factors within slope units can more comprehensively reflect the relationships between conditioning factors and landslides.The research results have important reference significance for land use and landslide prevention.
基金supported by the National Key Research and Development Program (2021YFB2501003)the Key Research and Development Program of Guangdong Province (2019B090912001)the China Postdoctoral Science Foundation (2020M680531)。
文摘With the advantage of fast calculation and map resources on cloud control system(CCS), cloud-based predictive cruise control(CPCC) for heavy trucks has great potential to improve energy efficiency, which is significant to achieve the goal of national carbon neutrality. However, most investigations focus on the on-board predictive cruise control(PCC) system,lack of research on CPCC architecture under CCS. Besides, the current PCC algorithms have the problems of a single control target and high computational complexity, which hinders the improvement of the control effect. In this paper, a layered architecture based on CCS is proposed to effectively address the realtime computing of CPCC system and the deployment of its algorithm on vehicle-cloud. In addition, based on the dynamic programming principle and the proposed road point segmentation method(RPSM), a PCC algorithm is designed to optimize the speed and gear of heavy trucks with slope information. Simulation results show that the CPCC system can adaptively control vehicle driving through the slope prediction, with fuel-saving rate of 6.17% in comparison with the constant cruise control. Also,compared with other similar algorithms, the PCC algorithm can make the engine operate more in the efficient zone by cooperatively optimizing the gear and speed. Moreover, the RPSM algorithm can reconfigure the road in advance, with a 91% roadpoint reduction rate, significantly reducing algorithm complexity.Therefore, this study has essential research significance for the economic driving of heavy trucks and the promotion of the CPCC system.
基金the Program"Partnerships in priority domains"with the support of the National Education Ministry,the Executive Agency for Higher Education,Research,Development and Innovation Funding (UEFISCDI),Romania (Project code:PN-II-PT-PCCA-2013-4-1232)
文摘AIM：To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina.METHODS：Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca,Romania,between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images,corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms,applying the standard boxcounting method. Statistical analyses were performed using the Graph Pad In Stat software.RESULTS：The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions（D_q）for q=0,1,2,the width of the multifractal spectrum（Δα=α_（max）-α_（min））and the spectrum arms＇ heights difference（│Δf│）of the normal images were expressed as mean±standard deviation（SD）：for segmented versions,D_0=1.7014±0.0057; D_1=1.6507±0.0058; D_2=1.5772±0.0059; Δα=0.92441±0.0085; │Δf│= 0.1453±0.0051; for skeletonised versions,D_0=1.6303±0.0051; D_1=1.6012±0.0059; D_2=1.5531± 0.0058; Δα=0.65032±0.0162; │Δf│= 0.0238±0.0161. The average of generalized dimensions（D_q）for q=0,1,2,the width of the multifractal spectrum（Δα）and the spectrum arms＇ heights difference（│Δf│）of the segmented versions was slightly greater than the skeletonised versions.CONCLUSION：The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases.
文摘Rainfall variability associated with climate change has enormous impacts on ecosystems, agriculture and people in West Africa but few studies have been devoted to it. Monthly rainfall data from 1901 to 2013, provided by the Global Precipitation Climatology Center dataset, were analyzed using segmentation and empirical modal decomposition (EMD) methods to increase our knowledge on past and recent spatio-temporal rainfall trends and their impacts on the West African region. The results obtained showed that the peak of rainfall during the short rainy season is observed in September in Côte d’Ivoire, Ghana and Liberia. The temporal variability of this rainfall is marked by several breakpoints whose durations range from 2 to 70 years. The periods of change in the rainfall regime, characterized by the appearance of breakpoints, vary from one country to another and are of unequal duration. The main breakpoint appears after 1960. Periods of relative or normal increase or decrease in precipitation are observed before and after 1960. The long-term variability of this rainfall is characterized by a decrease in the amount of rainfall over all West African countries. The results of this study can be used as a tool to help raise awareness among populations for sustainable management of water resources in response to climate change and its adverse effects.
文摘This paper analyses the characters of different bases of market segmentation and classes the bases into four kinds： observable general bases, observable product-specific bases, unobservable general bases and unobservable product-specific bases. The result can be used in the future research of market segmentation.
文摘In this paper, the exact analytical solution of the rectangular plate having simplysupported segments mixed with free segments of straight edges are first given by means of the method of reciprocal theorem.By comparison .we calculate the same question by finite element method.Thecomparison shows that the analytical solution is correct.
基金supported by the National Natural Science Foundation of China(Nos.61201307,61371045,and 61171197)the Fundamental Research Funds for the Central Universities(No.HIT.NSRIF.2013132)
文摘The appearanee of blood vessels is an important biomarker to distinguish diseased from healthy tissues in several fields of medical applications. Photoacoustie microangiography has the advantage of directly visualizing blood vessel networks within mierocireulatory tissue. Usually these images are interpreted qualitatively. However, a quantitative analysis is needed to better describe the characteristics of the blood vessels. This Letter addresses this problem by leveraging an efficient multiscale Hessian filter-based segmentation method, and four measure- ment parameters are acquired. The feasibility of our approach is demonstrated on experimental data and we expect the proposed method to be beneficial for several microcireulatory disease studies.
基金This work is supported by the National Natural Science Foundation of China[No.41374151]the Sichuan Province Applied Basic Research Project of China[No.2017JY0162]the Young Scholars Development Fund of SWPU[No.201599010079].
文摘To aid the magnetic anomaly detection(MAD)of underground ferromagnetic pipelines,this paper proposes a geometric modeling method based on the magnetic dipole reconstruction method(MDRM).First,the numerical modeling of basic pipe components such as straight sections,bends and elbows,and tee joints are discussed and the relevant mathematical formulations for these components are derived.Next,after analyzing the function of MDRM and various element division strategies,the sectional division and blocked division methods are introduced and applied to the appropriate pipeline components to determine the volume and center coordinates of each element,establishing the general models for the three typical pipeline components considered.The resulting volume and center coordinates of each component are the fundamental parameters for determining the MAD forwarding of underground ferromagnetic pipelines using the MDRM.Finally,based on the combination and transformation of the basic pipeline components considered,the visualized geometric models of typical pipeline layouts including parallel pipelines,pipelines with elbows,and a pipeline with a tee joint are constructed.The results demonstrate the feasibility of the proposed method of geometric modeling for the MDRM,which can be further applied to the finite element modeling of these and other components when analyzing MAD data.Furthermore,the models with output parameters proposed in this paper establish a foundation for the inversion of MAD.
