针对菇房内杏鲍菇表型参数测量任务中,由于扫描设备视角受限,扫描的杏鲍菇点云出现残缺问题,基于AdaPoinTr(Adaptive geometry-aware point transformers)提出了改进的SwinPoinTr模型,实现了对残缺杏鲍菇点云的准确补全和杏鲍菇表型参...针对菇房内杏鲍菇表型参数测量任务中,由于扫描设备视角受限,扫描的杏鲍菇点云出现残缺问题,基于AdaPoinTr(Adaptive geometry-aware point transformers)提出了改进的SwinPoinTr模型,实现了对残缺杏鲍菇点云的准确补全和杏鲍菇表型参数的测量。该方法在使用提出的特征重塑模块的基础上,构建具有几何感知能力的层次化Transformer编码模块,提高了模型对输入点云的利用率和模型捕捉点云细节特征的能力。然后基于泊松重建方法完成了补全点云表面重建,并测量到杏鲍菇表型参数。实验结果表明,本文所提算法在残缺杏鲍菇点云补全任务中,模型倒角距离为1.316×10^(-4),地球移动距离为21.3282,F1分数为87.87%。在表型参数估测任务中,模型对杏鲍菇菌高、体积、表面积估测结果的决定系数分别为0.9582、0.9596、0.9605,均方根误差分别为4.4213 mm、10.8185 cm^(3)、7.5778 cm^(2)。结果证实了该研究方法可以有效地补全残缺的杏鲍菇点云,可以为菇房内杏鲍菇表型参数测量提供基础。展开更多
In this paper,we establish common fixed point theorems for expansive map?pings on b-metric-like space and coincidence point for f-weakly isotone increasing mappings in partially ordered b-metric-like space.The main re...In this paper,we establish common fixed point theorems for expansive map?pings on b-metric-like space and coincidence point for f-weakly isotone increasing mappings in partially ordered b-metric-like space.The main results generalize and extend several well-known comparable results from the existing literature.Moreover,some examples are provided to illustrate the main results.展开更多
Accurately forecasting the triple point(TP)path is essential for analyzing blast loads and assessing the destructive effectiveness of the height of burst explosion.Empirical models that describe the TP path under norm...Accurately forecasting the triple point(TP)path is essential for analyzing blast loads and assessing the destructive effectiveness of the height of burst explosion.Empirical models that describe the TP path under normal temperature and pressure environments are commonly employed;however,in certain configurations,such as at high-altitudes(HAs),the environment may involve low temperature and pressure conditions.The present study develops a theoretical prediction model for the TP path under reduced pressure and temperature conditions,utilizing the image bursts method,reflected polar analysis,and dimensional analysis.The model's accuracy is evaluated through numerical simulations and experimental data.Results indicate that the prediction model effectively evaluates the TP path under diminished temperature and pressure conditions,with most predictions falling within a±15%deviation.It was found that the TP height increases with altitude.As the altitude rises from 0 m to 10,000 m,the average TP height increases by 61.7%,87.9%,109.0%,and 134.3%for the scaled height of burst of 1.5 m,2.0 m,2.5 m,and 3.0 m,respectively.Moreover,the variation in TP height under HA environments closely mirrors that observed under corresponding reduced pressure conditions.In HA environments,only the effect of low-pressure conditions on the TP path needs to be considered,as the environmental lowtemperature has a minimal effect.展开更多
输电线路的关键部位包括塔身、导线、绝缘子、避雷线以及引流线,无人机精细化导航的首要任务是构造输电线路的点云地图并从中分割出上述部位。为解决现有算法在输电线路的绝缘子、引流线等精细结构分割时精度低的问题,通过改进PointNet+...输电线路的关键部位包括塔身、导线、绝缘子、避雷线以及引流线,无人机精细化导航的首要任务是构造输电线路的点云地图并从中分割出上述部位。为解决现有算法在输电线路的绝缘子、引流线等精细结构分割时精度低的问题,通过改进PointNet++算法,提出了一种面向输电线路精细结构的点云分割方法。首先,基于无人机机载激光雷达在现场采集的点云数据,构造了输电线路点云分割数据集;其次,通过对比实验,筛选出在本输电线路场景下合理的数据增强方法,并对数据集进行了数据增强;最后,将自注意力机制以及倒置残差结构和PointNet++相结合,设计了输电线路关键部位点云语义分割算法。实验结果表明:该改进PointNet++算法在全场景输电线路现场点云数据作为输入的前提下,首次实现了对引流线、绝缘子等输电线路中精细结构和导线、杆塔塔身以及输电线路无关背景点的同时分割,平均交并比(mean intersection over union,mIoU)达80.79%,所有类别分割的平均F_(1)值(F1 score)达88.99%。展开更多
Singular point(SP)extraction is a key component in automatic fingerprint identification system(AFIS).A new method was proposed for fingerprint singular points extraction,based on orientation tensor field and Laurent s...Singular point(SP)extraction is a key component in automatic fingerprint identification system(AFIS).A new method was proposed for fingerprint singular points extraction,based on orientation tensor field and Laurent series.First,fingerprint orientation flow field was obtained,using the gradient of fingerprint image.With these gradients,fingerprint orientation tensor field was calculated.Then,candidate SPs were detected by the cross-correlation energy in multi-scale Gaussian space.The energy was calculated between fingerprint orientation tensor field and Laurent polynomial model.As a global descriptor,the Laurent polynomial coefficients were allowed for rotational invariance.Furthermore,a support vector machine(SVM)classifier was trained to remove spurious SPs,using cross-correlation coefficient as a feature vector.Finally,experiments were performed on Singular Point Detection Competition 2010(SPD2010)database.Compared to the winner algorithm of SPD2010 which has best accuracy of 31.90%,the accuracy of proposed algorithm is 45.34%.The results show that the proposed method outperforms the state-of-the-art detection algorithms by large margin,and the detection is invariant to rotational transformations.展开更多
Because of the low convergence efficiency of the typical Vicsek model,a Vicsek with static summoning points(VSSP)algorithm based on the Vicsek model considering static summoning points is proposed.Firstly,the mathemat...Because of the low convergence efficiency of the typical Vicsek model,a Vicsek with static summoning points(VSSP)algorithm based on the Vicsek model considering static summoning points is proposed.Firstly,the mathematical model of the individual movement total cost on each summoning point is established.Then the individual classification rule is designed according to the initial state of the cluster to obtain the subclusters guided by each summoning point.Finally,the summoning factor is introduced to modify the course angle updating formula of the Vicsek model.To verify the effectiveness of the proposed algorithm and study the effect of the cluster summoning factor on the convergence rate,three groups of simulation experiments under different summoning factors are designed in this paper.To verify the superiority of the VSSP algorithm,the performance of the VSSP algorithm is compared with the classic algorithm by designing the algorithm performance comparison verification experiment.The results show that the algorithm proposed in this paper has good convergence and course angle consistency.The summoning factor is the sensitive factor of cluster convergence.This algorithm can provide a reference for efficient cluster segmentation movement.展开更多
Discuss a class of real planar cubic systems with a critical point O (0,0) of nine orders and obtain the conditions for its limit cycle surrounding the origin, and prove that when small pertubations of coefficients ar...Discuss a class of real planar cubic systems with a critical point O (0,0) of nine orders and obtain the conditions for its limit cycle surrounding the origin, and prove that when small pertubations of coefficients are made, the critical point O (0,0) of nine orders is split into nine real simple critical points and the limit cycle surrounding the origin becomes the limit cycle containing nine critical points in its interior.展开更多
基金Supported by the National Natural Science Foundation of China(12001249)the Natural Science Foundation of Jiangxi Province(20232BAB211004)the Educational Commission Science Programm of Jiangxi Province(GJJ2200523)。
文摘In this paper,we establish common fixed point theorems for expansive map?pings on b-metric-like space and coincidence point for f-weakly isotone increasing mappings in partially ordered b-metric-like space.The main results generalize and extend several well-known comparable results from the existing literature.Moreover,some examples are provided to illustrate the main results.
基金funding from Anhui Engineering Laboratory of Explosive Materials and Technology Foundation(No.AHBP2022B-04)Natural Science Research Project of Anhui Educational Committee(No.2023AH051221)+1 种基金Anhui Provincial Natural Science Foundation(No.2208085QA26)Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology for the project related to this work.
文摘Accurately forecasting the triple point(TP)path is essential for analyzing blast loads and assessing the destructive effectiveness of the height of burst explosion.Empirical models that describe the TP path under normal temperature and pressure environments are commonly employed;however,in certain configurations,such as at high-altitudes(HAs),the environment may involve low temperature and pressure conditions.The present study develops a theoretical prediction model for the TP path under reduced pressure and temperature conditions,utilizing the image bursts method,reflected polar analysis,and dimensional analysis.The model's accuracy is evaluated through numerical simulations and experimental data.Results indicate that the prediction model effectively evaluates the TP path under diminished temperature and pressure conditions,with most predictions falling within a±15%deviation.It was found that the TP height increases with altitude.As the altitude rises from 0 m to 10,000 m,the average TP height increases by 61.7%,87.9%,109.0%,and 134.3%for the scaled height of burst of 1.5 m,2.0 m,2.5 m,and 3.0 m,respectively.Moreover,the variation in TP height under HA environments closely mirrors that observed under corresponding reduced pressure conditions.In HA environments,only the effect of low-pressure conditions on the TP path needs to be considered,as the environmental lowtemperature has a minimal effect.
文摘输电线路的关键部位包括塔身、导线、绝缘子、避雷线以及引流线,无人机精细化导航的首要任务是构造输电线路的点云地图并从中分割出上述部位。为解决现有算法在输电线路的绝缘子、引流线等精细结构分割时精度低的问题,通过改进PointNet++算法,提出了一种面向输电线路精细结构的点云分割方法。首先,基于无人机机载激光雷达在现场采集的点云数据,构造了输电线路点云分割数据集;其次,通过对比实验,筛选出在本输电线路场景下合理的数据增强方法,并对数据集进行了数据增强;最后,将自注意力机制以及倒置残差结构和PointNet++相结合,设计了输电线路关键部位点云语义分割算法。实验结果表明:该改进PointNet++算法在全场景输电线路现场点云数据作为输入的前提下,首次实现了对引流线、绝缘子等输电线路中精细结构和导线、杆塔塔身以及输电线路无关背景点的同时分割,平均交并比(mean intersection over union,mIoU)达80.79%,所有类别分割的平均F_(1)值(F1 score)达88.99%。
基金Project(11JJ3080)supported by Natural Science Foundation of Hunan Province,ChinaProject(11CY012)supported by Cultivation in Hunan Colleges and Universities,ChinaProject(ET51007)supported by Youth Talent in Hunan University,China
文摘Singular point(SP)extraction is a key component in automatic fingerprint identification system(AFIS).A new method was proposed for fingerprint singular points extraction,based on orientation tensor field and Laurent series.First,fingerprint orientation flow field was obtained,using the gradient of fingerprint image.With these gradients,fingerprint orientation tensor field was calculated.Then,candidate SPs were detected by the cross-correlation energy in multi-scale Gaussian space.The energy was calculated between fingerprint orientation tensor field and Laurent polynomial model.As a global descriptor,the Laurent polynomial coefficients were allowed for rotational invariance.Furthermore,a support vector machine(SVM)classifier was trained to remove spurious SPs,using cross-correlation coefficient as a feature vector.Finally,experiments were performed on Singular Point Detection Competition 2010(SPD2010)database.Compared to the winner algorithm of SPD2010 which has best accuracy of 31.90%,the accuracy of proposed algorithm is 45.34%.The results show that the proposed method outperforms the state-of-the-art detection algorithms by large margin,and the detection is invariant to rotational transformations.
基金supported by the National Natural Science Foundation of China(51979193)the China Scholarship Council(201506290080)+1 种基金the China Postdoctoral Science Foundation(2019M653652)the Natural Science Basic Research Plan in Shaanxi Province of China(2019JQ-607).
文摘Because of the low convergence efficiency of the typical Vicsek model,a Vicsek with static summoning points(VSSP)algorithm based on the Vicsek model considering static summoning points is proposed.Firstly,the mathematical model of the individual movement total cost on each summoning point is established.Then the individual classification rule is designed according to the initial state of the cluster to obtain the subclusters guided by each summoning point.Finally,the summoning factor is introduced to modify the course angle updating formula of the Vicsek model.To verify the effectiveness of the proposed algorithm and study the effect of the cluster summoning factor on the convergence rate,three groups of simulation experiments under different summoning factors are designed in this paper.To verify the superiority of the VSSP algorithm,the performance of the VSSP algorithm is compared with the classic algorithm by designing the algorithm performance comparison verification experiment.The results show that the algorithm proposed in this paper has good convergence and course angle consistency.The summoning factor is the sensitive factor of cluster convergence.This algorithm can provide a reference for efficient cluster segmentation movement.
基金The Natural Science Foundation of Hunan Province !(No .97JJN 70 )
文摘Discuss a class of real planar cubic systems with a critical point O (0,0) of nine orders and obtain the conditions for its limit cycle surrounding the origin, and prove that when small pertubations of coefficients are made, the critical point O (0,0) of nine orders is split into nine real simple critical points and the limit cycle surrounding the origin becomes the limit cycle containing nine critical points in its interior.
