Radiometric normalization,as an essential step for multi-source and multi-temporal data processing,has received critical attention.Relative Radiometric Normalization(RRN)method has been primarily used for eliminating ...Radiometric normalization,as an essential step for multi-source and multi-temporal data processing,has received critical attention.Relative Radiometric Normalization(RRN)method has been primarily used for eliminating the radiometric inconsistency.The radiometric trans-forming relation between the subject image and the reference image is an essential aspect of RRN.Aimed at accurate radiometric transforming relation modeling,the learning-based nonlinear regression method,Support Vector machine Regression(SVR)is used for fitting the complicated radiometric transforming relation for the coarse-resolution data-referenced RRN.To evaluate the effectiveness of the proposed method,a series of experiments are performed,including two synthetic data experiments and one real data experiment.And the proposed method is compared with other methods that use linear regression,Artificial Neural Network(ANN)or Random Forest(RF)for radiometric transforming relation modeling.The results show that the proposed method performs well on fitting the radiometric transforming relation and could enhance the RRN performance.展开更多
Monocular 3D object detection is challenging due to the lack of accurate depth information.Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input t...Monocular 3D object detection is challenging due to the lack of accurate depth information.Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB images.Depth-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and depth fusion learning.However,they demonstrate limited performance and efficiency as a result of depth inaccuracy and complex fusion mode with convolutions.Different from these approaches,our proposed depth-guided vision transformer with a normalizing flows(NF-DVT)network uses normalizing flows to build priors in depth maps to achieve more accurate depth information.Then we develop a novel Swin-Transformer-based backbone with a fusion module to process RGB image patches and depth map patches with two separate branches and fuse them using cross-attention to exchange information with each other.Furthermore,with the help of pixel-wise relative depth values in depth maps,we develop new relative position embeddings in the cross-attention mechanism to capture more accurate sequence ordering of input tokens.Our method is the first Swin-Transformer-based backbone architecture for monocular 3D object detection.The experimental results on the KITTI and the challenging Waymo Open datasets show the effectiveness of our proposed method and superior performance over previous counterparts.展开更多
The simplest normal form of resonant double Hopf bifurcation was studied based on Lie operator. The coefficients of the simplest normal forms of resonant double Hopf bifurcation and the nonlinear transformations in te...The simplest normal form of resonant double Hopf bifurcation was studied based on Lie operator. The coefficients of the simplest normal forms of resonant double Hopf bifurcation and the nonlinear transformations in terms of the original system coefficients were given explicitly. The nonlinear transformations were used for reducing the lower- and higher-order normal forms, and the rank of system matrix was used to determine the coefficient of normal form which could be reduced. These make the gained normal form simpler than the traditional one. A general program was compiled with Mathematica. This program can compute the simplest normal form of resonant double Hopf bifurcation and the non-resonant form up to the 7th order.展开更多
We present new connections among linear anomalous diffusion (AD), normal diffusion (ND) and the Central Limit Theorem (CLT). This is done by defining a point transformation to a new position variable, which we postula...We present new connections among linear anomalous diffusion (AD), normal diffusion (ND) and the Central Limit Theorem (CLT). This is done by defining a point transformation to a new position variable, which we postulate to be Cartesian, motivated by considerations from super-symmetric quantum mechanics. Canonically quantizing in the new position and momentum variables according to Dirac gives rise to generalized negative semi-definite and self-adjoint Laplacian operators. These lead to new generalized Fourier transformations and associated probability distributions, which are form invariant under the corresponding transform. The new Laplacians also lead us to generalized diffusion equations, which imply a connection to the CLT. We show that the derived diffusion equations capture all of the Fractal and Non-Fractal Anomalous Diffusion equations of O’Shaughnessy and Procaccia. However, we also obtain new equations that cannot (so far as we can tell) be expressed as examples of the O’Shaughnessy and Procaccia equations. The results show, in part, that experimentally measuring the diffusion scaling law can determine the point transformation (for monomial point transformations). We also show that AD in the original, physical position is actually ND when viewed in terms of displacements in an appropriately transformed position variable. We illustrate the ideas both analytically and with a detailed computational example for a non-trivial choice of point transformation. Finally, we summarize our results.展开更多
We show that the technique of integration within an ordered product of operators can be extended to Hilbert transform. In so doing we derive normally ordered expansion of Coulomb potential-type operators directly by u...We show that the technique of integration within an ordered product of operators can be extended to Hilbert transform. In so doing we derive normally ordered expansion of Coulomb potential-type operators directly by using the mathematical Hilbert transform formula.展开更多
This paper investigates topological transformation during normal grain growth by carrying out a computer vertex simulation. Results show that topological correlation agrees with the models proposed by Blanc et al. and...This paper investigates topological transformation during normal grain growth by carrying out a computer vertex simulation. Results show that topological correlation agrees with the models proposed by Blanc et al. and Weaire. Topological transformation occurs more often on grains with some topological classes instead of equal probability on each boundary. This can be qualitatively explained by topological correlation.展开更多
This paper analyzes the three big impact in the development of Chinese banking industry and discusses the limitations of financial innovation of Chinese banking industry.The results showed that:(1)deepening the bankin...This paper analyzes the three big impact in the development of Chinese banking industry and discusses the limitations of financial innovation of Chinese banking industry.The results showed that:(1)deepening the banking system innovation to adapt to the new situation;(2)improving customers’experience by deepening model innovation of the internet financial;(3)improving intensive of bank branch operation and the intelligent of network service with the aid of informatization;(4)Providing individualized,characteristic and differentiated services for high-quality customers of banks and enhancing customer value through lightweight network outlets;and(5)Adapting to the development of new entity economy by comprehensive management,optimizing the operation mode of outlets,and strengthening the supply side reform of commercial banks themselves.展开更多
In May 2014,Chairman Xi Jinping mentioned the "new normal" for the first time during his inspection of Henan,and proposed that China's development is still in an important period of strategic opportunity...In May 2014,Chairman Xi Jinping mentioned the "new normal" for the first time during his inspection of Henan,and proposed that China's development is still in an important period of strategic opportunity. It was advocated to promote the transformation and development of China's green economy and to go out an ecological path of green innovation,green production and green consumption. This paper mainly explains the current situation,problems,corresponding countermeasures and suggestions of the transformation and development of China's green economy under the new normal to let readers understand the necessity of the transformation and development of China's green economy.展开更多
In this case study, we would like to illustrate the utility of characteristic functions, using an example of a sample statistic defined for samples from Cauchy distribution. The derivation of the corresponding asympto...In this case study, we would like to illustrate the utility of characteristic functions, using an example of a sample statistic defined for samples from Cauchy distribution. The derivation of the corresponding asymptotic probability density function is based on [1], elaborating and expanding the individual steps of their presentation, and including a small extension;our reason for such a plagiarism is to make the technique, its mathematical tools and ingenious arguments available to the widest possible audience.展开更多
Under the new normal, geological prospecting units are required to re-examine their current development model, observe the deficiencies in the financial management process, and take this as a guide to transform, upgra...Under the new normal, geological prospecting units are required to re-examine their current development model, observe the deficiencies in the financial management process, and take this as a guide to transform, upgrade and optimize the management model. This requires geological prospecting units to grasp the direction and focus of the transformation, for example, from the aspects of budget execution, supervision and audit to strengthen the control of financial management of enterprises, and effectively play the macro guidance and control role of the units, so as to play a greater value and effectiveness of the financial management model. This paper discusses and analyzes the necessity and ways of the transformation of the financial management mode of geological prospecting units under the new normal.展开更多
Deep learning has emerged as a powerful tool for predicting the remaining useful life(RUL)of batteries,contingent upon access to ample data.However,the inherent limitations of data availability from traditional or acc...Deep learning has emerged as a powerful tool for predicting the remaining useful life(RUL)of batteries,contingent upon access to ample data.However,the inherent limitations of data availability from traditional or accelerated life testing pose significant challenges.To mitigate the prediction accuracy issues arising from small sample sizes in existing intelligent methods,we introduce a novel data augmentation framework for RUL prediction.This framework harnesses the inherent high coincidence of degradation patterns exhibited by lithium-ion batteries to pinpoint the knee point,a critical juncture marking a significant shift in the degradation trajectory.By focusing on this critical knee point,we leverage the power of normalizing flow models to generate virtual data,effectively augmenting the training sample size.Additionally,we integrate a Bayesian Long Short-Term Memory network,optimized with Box-Cox transformation,to address the inherent uncertainty associated with predictions based on augmented data.This integration allows for a more nuanced understanding of RUL prediction uncertainties,offering valuable confidence intervals.The efficacy and superiority of the proposed framework are validated through extensive experiments on the CS2 dataset from the University of Maryland and the CrFeMnNiCo dataset from our laboratory.The results clearly demonstrate a substantial improvement in the confidence interval of RUL predictions compared to pre-optimization,highlighting the ability of the framework to achieve high-precision RUL predictions even with limited data.展开更多
特快速暂态过电压(very fast transient overvoltage,VFTO)包含的频率成分与变压器等绕组类设备的谐振频率匹配时,会在其内部产生谐振过电压,威胁其绝缘安全,因此有必要对VFTO的频谱特征进行分析。从信号分析的角度看,VFTO波形是一种非...特快速暂态过电压(very fast transient overvoltage,VFTO)包含的频率成分与变压器等绕组类设备的谐振频率匹配时,会在其内部产生谐振过电压,威胁其绝缘安全,因此有必要对VFTO的频谱特征进行分析。从信号分析的角度看,VFTO波形是一种非平稳信号,傅里叶变换无法描述其频率随时间的变化情况,因此提出采用归一化短时傅里叶变换-魏格纳威尔分布(normalized STFT-WVD,NSTFT-WVD)分析VFTO的频谱特征。首先介绍了NSTFT-WVD变换的原理及实现步骤,然后比较了NSTFT-WVD变换与其他时频变换方法的性能,并采用该变换分析了VFTO现场试验波形,验证了该变换用于VFTO频谱分析的有效性,最后基于NSTFT-WVD变换定量分析了隔离开关类型和避雷器对VFTO频谱的影响,验证了该变换用于VFTO频谱分析的优良性能。展开更多
基金This research was funded by the National Natural Science Fund of China[grant number 41701415]Science fund project of Wuhan Institute of Technology[grant number K201724]Science and Technology Development Funds Project of Department of Transportation of Hubei Province[grant number 201900001].
文摘Radiometric normalization,as an essential step for multi-source and multi-temporal data processing,has received critical attention.Relative Radiometric Normalization(RRN)method has been primarily used for eliminating the radiometric inconsistency.The radiometric trans-forming relation between the subject image and the reference image is an essential aspect of RRN.Aimed at accurate radiometric transforming relation modeling,the learning-based nonlinear regression method,Support Vector machine Regression(SVR)is used for fitting the complicated radiometric transforming relation for the coarse-resolution data-referenced RRN.To evaluate the effectiveness of the proposed method,a series of experiments are performed,including two synthetic data experiments and one real data experiment.And the proposed method is compared with other methods that use linear regression,Artificial Neural Network(ANN)or Random Forest(RF)for radiometric transforming relation modeling.The results show that the proposed method performs well on fitting the radiometric transforming relation and could enhance the RRN performance.
基金supported in part by the Major Project for New Generation of AI (2018AAA0100400)the National Natural Science Foundation of China (61836014,U21B2042,62072457,62006231)the InnoHK Program。
文摘Monocular 3D object detection is challenging due to the lack of accurate depth information.Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB images.Depth-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and depth fusion learning.However,they demonstrate limited performance and efficiency as a result of depth inaccuracy and complex fusion mode with convolutions.Different from these approaches,our proposed depth-guided vision transformer with a normalizing flows(NF-DVT)network uses normalizing flows to build priors in depth maps to achieve more accurate depth information.Then we develop a novel Swin-Transformer-based backbone with a fusion module to process RGB image patches and depth map patches with two separate branches and fuse them using cross-attention to exchange information with each other.Furthermore,with the help of pixel-wise relative depth values in depth maps,we develop new relative position embeddings in the cross-attention mechanism to capture more accurate sequence ordering of input tokens.Our method is the first Swin-Transformer-based backbone architecture for monocular 3D object detection.The experimental results on the KITTI and the challenging Waymo Open datasets show the effectiveness of our proposed method and superior performance over previous counterparts.
基金Supported by National Natural Science Foundation of China(No. 10372068).
文摘The simplest normal form of resonant double Hopf bifurcation was studied based on Lie operator. The coefficients of the simplest normal forms of resonant double Hopf bifurcation and the nonlinear transformations in terms of the original system coefficients were given explicitly. The nonlinear transformations were used for reducing the lower- and higher-order normal forms, and the rank of system matrix was used to determine the coefficient of normal form which could be reduced. These make the gained normal form simpler than the traditional one. A general program was compiled with Mathematica. This program can compute the simplest normal form of resonant double Hopf bifurcation and the non-resonant form up to the 7th order.
文摘We present new connections among linear anomalous diffusion (AD), normal diffusion (ND) and the Central Limit Theorem (CLT). This is done by defining a point transformation to a new position variable, which we postulate to be Cartesian, motivated by considerations from super-symmetric quantum mechanics. Canonically quantizing in the new position and momentum variables according to Dirac gives rise to generalized negative semi-definite and self-adjoint Laplacian operators. These lead to new generalized Fourier transformations and associated probability distributions, which are form invariant under the corresponding transform. The new Laplacians also lead us to generalized diffusion equations, which imply a connection to the CLT. We show that the derived diffusion equations capture all of the Fractal and Non-Fractal Anomalous Diffusion equations of O’Shaughnessy and Procaccia. However, we also obtain new equations that cannot (so far as we can tell) be expressed as examples of the O’Shaughnessy and Procaccia equations. The results show, in part, that experimentally measuring the diffusion scaling law can determine the point transformation (for monomial point transformations). We also show that AD in the original, physical position is actually ND when viewed in terms of displacements in an appropriately transformed position variable. We illustrate the ideas both analytically and with a detailed computational example for a non-trivial choice of point transformation. Finally, we summarize our results.
基金The project supported by the President Foundation of the Chinese Academy of Sciences and National Natural Science Foundation of China under Grant No. 10475056.
文摘We show that the technique of integration within an ordered product of operators can be extended to Hilbert transform. In so doing we derive normally ordered expansion of Coulomb potential-type operators directly by using the mathematical Hilbert transform formula.
基金We also thank the support from State Key Program for Basic Research of China(No.2003CB314702,No.2003CB314706)NSFC(No.10347125)+1 种基金the foundation of Doctoral Program of Ministrv of Education(No.20030286003)the foundation of Science and Technology of Southeast University(No.9206001270,No.9206001271)
文摘This paper investigates topological transformation during normal grain growth by carrying out a computer vertex simulation. Results show that topological correlation agrees with the models proposed by Blanc et al. and Weaire. Topological transformation occurs more often on grains with some topological classes instead of equal probability on each boundary. This can be qualitatively explained by topological correlation.
文摘This paper analyzes the three big impact in the development of Chinese banking industry and discusses the limitations of financial innovation of Chinese banking industry.The results showed that:(1)deepening the banking system innovation to adapt to the new situation;(2)improving customers’experience by deepening model innovation of the internet financial;(3)improving intensive of bank branch operation and the intelligent of network service with the aid of informatization;(4)Providing individualized,characteristic and differentiated services for high-quality customers of banks and enhancing customer value through lightweight network outlets;and(5)Adapting to the development of new entity economy by comprehensive management,optimizing the operation mode of outlets,and strengthening the supply side reform of commercial banks themselves.
文摘In May 2014,Chairman Xi Jinping mentioned the "new normal" for the first time during his inspection of Henan,and proposed that China's development is still in an important period of strategic opportunity. It was advocated to promote the transformation and development of China's green economy and to go out an ecological path of green innovation,green production and green consumption. This paper mainly explains the current situation,problems,corresponding countermeasures and suggestions of the transformation and development of China's green economy under the new normal to let readers understand the necessity of the transformation and development of China's green economy.
文摘In this case study, we would like to illustrate the utility of characteristic functions, using an example of a sample statistic defined for samples from Cauchy distribution. The derivation of the corresponding asymptotic probability density function is based on [1], elaborating and expanding the individual steps of their presentation, and including a small extension;our reason for such a plagiarism is to make the technique, its mathematical tools and ingenious arguments available to the widest possible audience.
文摘Under the new normal, geological prospecting units are required to re-examine their current development model, observe the deficiencies in the financial management process, and take this as a guide to transform, upgrade and optimize the management model. This requires geological prospecting units to grasp the direction and focus of the transformation, for example, from the aspects of budget execution, supervision and audit to strengthen the control of financial management of enterprises, and effectively play the macro guidance and control role of the units, so as to play a greater value and effectiveness of the financial management model. This paper discusses and analyzes the necessity and ways of the transformation of the financial management mode of geological prospecting units under the new normal.
基金supported by the National Natural Science Foundation of China(Grant No.62227814,52205040,22279070,and U21A20170)the Natural Science Basic Research Program of Shaanxi(2023-JC-QN-0140)+3 种基金the Young Talent Fund of Xi’an Association for Science and Technology(Grant No.959202313096)the Key Projects of the Shaanxi Province Natural Science Foundation(Grant No.2025JC-QYXQ-038)the Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems(Grant No.GZKF-202430)the National Key Research and Development Program of China(Grant No.2024YFB3311204)。
文摘Deep learning has emerged as a powerful tool for predicting the remaining useful life(RUL)of batteries,contingent upon access to ample data.However,the inherent limitations of data availability from traditional or accelerated life testing pose significant challenges.To mitigate the prediction accuracy issues arising from small sample sizes in existing intelligent methods,we introduce a novel data augmentation framework for RUL prediction.This framework harnesses the inherent high coincidence of degradation patterns exhibited by lithium-ion batteries to pinpoint the knee point,a critical juncture marking a significant shift in the degradation trajectory.By focusing on this critical knee point,we leverage the power of normalizing flow models to generate virtual data,effectively augmenting the training sample size.Additionally,we integrate a Bayesian Long Short-Term Memory network,optimized with Box-Cox transformation,to address the inherent uncertainty associated with predictions based on augmented data.This integration allows for a more nuanced understanding of RUL prediction uncertainties,offering valuable confidence intervals.The efficacy and superiority of the proposed framework are validated through extensive experiments on the CS2 dataset from the University of Maryland and the CrFeMnNiCo dataset from our laboratory.The results clearly demonstrate a substantial improvement in the confidence interval of RUL predictions compared to pre-optimization,highlighting the ability of the framework to achieve high-precision RUL predictions even with limited data.
文摘特快速暂态过电压(very fast transient overvoltage,VFTO)包含的频率成分与变压器等绕组类设备的谐振频率匹配时,会在其内部产生谐振过电压,威胁其绝缘安全,因此有必要对VFTO的频谱特征进行分析。从信号分析的角度看,VFTO波形是一种非平稳信号,傅里叶变换无法描述其频率随时间的变化情况,因此提出采用归一化短时傅里叶变换-魏格纳威尔分布(normalized STFT-WVD,NSTFT-WVD)分析VFTO的频谱特征。首先介绍了NSTFT-WVD变换的原理及实现步骤,然后比较了NSTFT-WVD变换与其他时频变换方法的性能,并采用该变换分析了VFTO现场试验波形,验证了该变换用于VFTO频谱分析的有效性,最后基于NSTFT-WVD变换定量分析了隔离开关类型和避雷器对VFTO频谱的影响,验证了该变换用于VFTO频谱分析的优良性能。
