The Fringe Projection Profilometry(FPP)system with a single exposure time or a single projection intensity is limited by the dynamic range of the camera,which can lead to overexposure and underexposure of the image,re...The Fringe Projection Profilometry(FPP)system with a single exposure time or a single projection intensity is limited by the dynamic range of the camera,which can lead to overexposure and underexposure of the image,resulting in point cloud loss or reduced accuracy.To address this issue,unlike the pixel modulation method of projectors,we utilize the characteristics of color projectors where the intensity of the three-channel LED can be controlled independently.We propose a method for separating the projector's three-channel light intensity,combined with a color camera,to achieve single exposure and multi-intensity image acquisition.Further,the crosstalk coefficient is applied to predict the three-channel reflectance of the measured object.By integrating clustering and channel mapping,we establish a pixel-level mapping model between the projector's three-channel current and the camera's three-channel image intensity,which realizes the optimal projection current prediction and the high dynamic range(HDR)image acquisition.The proposed method allows for high-precision three-dimensional(3D)data acquisition of HDR scenes with a single exposure.The effectiveness of this method has been validated through experiments with standard planes and standard steps,showing a significant reduction in mean absolute error(44.6%)compared to existing singleexposure HDR methods.Additionally,the number of images required for acquisition is significantly reduced(by 70.8%)compared to multi-exposure fusion methods.This proposed method has great potential in various FPP-related fields.展开更多
[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of...[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of fish resources and the characteristics of their diversity is crucial for the ecological management of the Pinglu Canal.[Methods]During the spring and autumn in 2021 and 2022,a survey of fish resources and species diversity in the Pinglu Canal was conducted using multi-mesh gill nets.A total of 125 fish species were collected,belonging to 10 orders,34 families,and 89 genera.[Results]The result showed that the Pinglu Canal contained three nationally protected Class II species,two endemic species of the Qinjiang River,three anadromous/migratory species,and eight invasive species,accounting for 2.4%,1.6%,2.4%,and 6.4%of the total species,respectively.The fish community primarily consisted of mid-and bottom-dwelling,adhesive-egg-laying,and omnivorous species.The Shannon-Wiener,Simpson,Margalef,and Pielou indices of the fish community in the Pinglu Canal ranged from 2.347 to 2.757,0.081 to 0.151,3.493 to 4.382,and 0.812 to 0.892,respectively.These indices showed relatively uniform distribution across different river reaches.[Conclusion]The result indicate that the fish community structure in the Pinglu Canal is relatively uniform.The reach from the Yujiang River to the Shaping River shows higher stability,while other river reaches experience moderate or severe disturbances.This study provides supplementary baseline data on the fish community structure in the Pinglu Canal and explores the potential impact of inter-basin connectivity on fish resources,aiming to provide a scientific basis for habitat restoration assessments after the channel straightening project.展开更多
Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often comple...Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often complex and inadequate,making it challenging for researchers to conduct in-depth data mining to improve policies or management.To address this problem,this paper adopts a top-down approach to construct a knowledge graph(KG)for research projects.Firstly,we construct an integrated ontology by referring to the metamodel of various architectures,which is called the meta-model integration conceptual reference model.Subsequently,we use the dependency parsing method to extract knowledge from unstructured textual data and use the entity alignment method based on weakly supervised learning to classify the extracted entities,completing the construction of the KG for the research projects.In addition,a knowledge inference model based on representation learning is employed to achieve knowledge completion and improve the KG.Finally,experiments are conducted on the KG for research projects and the results demonstrate the effectiveness of the proposed method in enriching incomplete data within the KG.展开更多
Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and ev...Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.展开更多
Semantic segmentation of eye images is a complex task with important applications in human–computer interaction,cognitive science,and neuroscience.Achieving real-time,accurate,and robust segmentation algorithms is cr...Semantic segmentation of eye images is a complex task with important applications in human–computer interaction,cognitive science,and neuroscience.Achieving real-time,accurate,and robust segmentation algorithms is crucial for computationally limited portable devices such as augmented reality and virtual reality.With the rapid advancements in deep learning,many network models have been developed specifically for eye image segmentation.Some methods divide the segmentation process into multiple stages to achieve model parameter miniaturization while enhancing output through post processing techniques to improve segmentation accuracy.These approaches significantly increase the inference time.Other networks adopt more complex encoding and decoding modules to achieve end-to-end output,which requires substantial computation.Therefore,balancing the model’s size,accuracy,and computational complexity is essential.To address these challenges,we propose a lightweight asymmetric UNet architecture and a projection loss function.We utilize ResNet-3 layer blocks to enhance feature extraction efficiency in the encoding stage.In the decoding stage,we employ regular convolutions and skip connections to upscale the feature maps from the latent space to the original image size,balancing the model size and segmentation accuracy.In addition,we leverage the geometric features of the eye region and design a projection loss function to further improve the segmentation accuracy without adding any additional inference computational cost.We validate our approach on the OpenEDS2019 dataset for virtual reality and achieve state-of-the-art performance with 95.33%mean intersection over union(mIoU).Our model has only 0.63M parameters and 350 FPS,which are 68%and 200%of the state-of-the-art model RITNet,respectively.展开更多
Based on the fabricated 12-element cavity-backed microstrip sector cylinder array,a novel hybrid alternate projection algorithm（HAPA）,which combines analytical method with numerical techniques effectively,is propose...Based on the fabricated 12-element cavity-backed microstrip sector cylinder array,a novel hybrid alternate projection algorithm（HAPA）,which combines analytical method with numerical techniques effectively,is proposed for synthesizing the pattern of practical conformal array.The algorithm applies the variable direction aperture projection method with mutual coupling correction techniques to provide the good initial excitations of elements to the enhanced alternate projection algorithm（EAPA）.In order to do further optimization,which improves the convergent speed of the algorithm significantly.Finally,the HAPA has been applied to the fabricated sector cylinder array with mutual coupling considered.The results of synthesized patterns,such as low sidelobe with null points formed pattern,beam scanning with low sidelobe pattern and the shaped beam pattern are presented.It demonstrates the validity of HAPA in practical conformal array synthesis.展开更多
Weapon project planning(WPP) plays a critical role in the process of national defense development and establishment of the future national defense force. WPP faces the backgrounds of various uncertainties, intense int...Weapon project planning(WPP) plays a critical role in the process of national defense development and establishment of the future national defense force. WPP faces the backgrounds of various uncertainties, intense inter-influence of weapon systems and involves modelling, assessment, and optimization procedures.The contents of this paper are mainly divided into three parts: first,the WPP processes are analyzed, and related elements are formulated to transform the qualitative problem to mathematics form;second, the value evaluation model of WPP solutions is proposed based on two criteria of total capability gap and total capability dispersion; third, two robustness optimization models are constructed based on the absolute robustness criterion and the robustness deviation criterion to support the robustness optimization process under multi-scenario. Finally, a case is studied to examine the feasibility and effectiveness of the proposed models and approaches.展开更多
In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support...In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support provided by wartime military material support powers can be more effective. When the principles,requirements, influencing factors and goals of military material support forces are deployed in wartime, an evaluation indicator system is established. Thus, a new combined empowerment method based on an analytic hierarchy process（AHP） is developed to calculate the subjective weights, and the rough entropy method is used to calculate the objective weights. Combination weights can be obtained by calculating the weight preference coefficient error, which is determined by combining the cooperative game method and the minimum deviation into objectives. This approach can determine the grey relation projection coefficient and synthesize the measure scheme superiority to finally optimize the deployment plan using the grey relation projection decision-making method. The results show that the method is feasible and effective;it can provide a more scientific and practical decision-making basis for the military material support power deployment in wartime.展开更多
文摘The Fringe Projection Profilometry(FPP)system with a single exposure time or a single projection intensity is limited by the dynamic range of the camera,which can lead to overexposure and underexposure of the image,resulting in point cloud loss or reduced accuracy.To address this issue,unlike the pixel modulation method of projectors,we utilize the characteristics of color projectors where the intensity of the three-channel LED can be controlled independently.We propose a method for separating the projector's three-channel light intensity,combined with a color camera,to achieve single exposure and multi-intensity image acquisition.Further,the crosstalk coefficient is applied to predict the three-channel reflectance of the measured object.By integrating clustering and channel mapping,we establish a pixel-level mapping model between the projector's three-channel current and the camera's three-channel image intensity,which realizes the optimal projection current prediction and the high dynamic range(HDR)image acquisition.The proposed method allows for high-precision three-dimensional(3D)data acquisition of HDR scenes with a single exposure.The effectiveness of this method has been validated through experiments with standard planes and standard steps,showing a significant reduction in mean absolute error(44.6%)compared to existing singleexposure HDR methods.Additionally,the number of images required for acquisition is significantly reduced(by 70.8%)compared to multi-exposure fusion methods.This proposed method has great potential in various FPP-related fields.
文摘[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of fish resources and the characteristics of their diversity is crucial for the ecological management of the Pinglu Canal.[Methods]During the spring and autumn in 2021 and 2022,a survey of fish resources and species diversity in the Pinglu Canal was conducted using multi-mesh gill nets.A total of 125 fish species were collected,belonging to 10 orders,34 families,and 89 genera.[Results]The result showed that the Pinglu Canal contained three nationally protected Class II species,two endemic species of the Qinjiang River,three anadromous/migratory species,and eight invasive species,accounting for 2.4%,1.6%,2.4%,and 6.4%of the total species,respectively.The fish community primarily consisted of mid-and bottom-dwelling,adhesive-egg-laying,and omnivorous species.The Shannon-Wiener,Simpson,Margalef,and Pielou indices of the fish community in the Pinglu Canal ranged from 2.347 to 2.757,0.081 to 0.151,3.493 to 4.382,and 0.812 to 0.892,respectively.These indices showed relatively uniform distribution across different river reaches.[Conclusion]The result indicate that the fish community structure in the Pinglu Canal is relatively uniform.The reach from the Yujiang River to the Shaping River shows higher stability,while other river reaches experience moderate or severe disturbances.This study provides supplementary baseline data on the fish community structure in the Pinglu Canal and explores the potential impact of inter-basin connectivity on fish resources,aiming to provide a scientific basis for habitat restoration assessments after the channel straightening project.
基金supported by the National Natural Science Foundation of China(72101263).
文摘Tracking and analyzing data from research projects is critical for understanding research trends and supporting the development of science and technology strategies.However,the data from these projects is often complex and inadequate,making it challenging for researchers to conduct in-depth data mining to improve policies or management.To address this problem,this paper adopts a top-down approach to construct a knowledge graph(KG)for research projects.Firstly,we construct an integrated ontology by referring to the metamodel of various architectures,which is called the meta-model integration conceptual reference model.Subsequently,we use the dependency parsing method to extract knowledge from unstructured textual data and use the entity alignment method based on weakly supervised learning to classify the extracted entities,completing the construction of the KG for the research projects.In addition,a knowledge inference model based on representation learning is employed to achieve knowledge completion and improve the KG.Finally,experiments are conducted on the KG for research projects and the results demonstrate the effectiveness of the proposed method in enriching incomplete data within the KG.
基金Supported by the National Natural Science Foundation of China (11161027)。
文摘Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.
基金supported by the HFIPS Director’s Foundation(YZJJ202207-TS),the National Natural Science Foundation of China(82371931)the Natural Science Foundation of Anhui Province(2008085MC69)+3 种基金the Natural Science Foundation of Hefei City(2021033)the General Scientific Research Project of Anhui Provincial Health Commission(AHWJ2021b150)the Collaborative Innovation Program of Hefei Science Center,CAS(2021HSC-CIP013)the Anhui Province Key Research and Development Project(202204295107020004).
文摘Semantic segmentation of eye images is a complex task with important applications in human–computer interaction,cognitive science,and neuroscience.Achieving real-time,accurate,and robust segmentation algorithms is crucial for computationally limited portable devices such as augmented reality and virtual reality.With the rapid advancements in deep learning,many network models have been developed specifically for eye image segmentation.Some methods divide the segmentation process into multiple stages to achieve model parameter miniaturization while enhancing output through post processing techniques to improve segmentation accuracy.These approaches significantly increase the inference time.Other networks adopt more complex encoding and decoding modules to achieve end-to-end output,which requires substantial computation.Therefore,balancing the model’s size,accuracy,and computational complexity is essential.To address these challenges,we propose a lightweight asymmetric UNet architecture and a projection loss function.We utilize ResNet-3 layer blocks to enhance feature extraction efficiency in the encoding stage.In the decoding stage,we employ regular convolutions and skip connections to upscale the feature maps from the latent space to the original image size,balancing the model size and segmentation accuracy.In addition,we leverage the geometric features of the eye region and design a projection loss function to further improve the segmentation accuracy without adding any additional inference computational cost.We validate our approach on the OpenEDS2019 dataset for virtual reality and achieve state-of-the-art performance with 95.33%mean intersection over union(mIoU).Our model has only 0.63M parameters and 350 FPS,which are 68%and 200%of the state-of-the-art model RITNet,respectively.
文摘Based on the fabricated 12-element cavity-backed microstrip sector cylinder array,a novel hybrid alternate projection algorithm（HAPA）,which combines analytical method with numerical techniques effectively,is proposed for synthesizing the pattern of practical conformal array.The algorithm applies the variable direction aperture projection method with mutual coupling correction techniques to provide the good initial excitations of elements to the enhanced alternate projection algorithm（EAPA）.In order to do further optimization,which improves the convergent speed of the algorithm significantly.Finally,the HAPA has been applied to the fabricated sector cylinder array with mutual coupling considered.The results of synthesized patterns,such as low sidelobe with null points formed pattern,beam scanning with low sidelobe pattern and the shaped beam pattern are presented.It demonstrates the validity of HAPA in practical conformal array synthesis.
基金supported by the National Social Science Foundation of China(15GJ003-278)the National Natural Science Foundation of China(71501182)
文摘Weapon project planning(WPP) plays a critical role in the process of national defense development and establishment of the future national defense force. WPP faces the backgrounds of various uncertainties, intense inter-influence of weapon systems and involves modelling, assessment, and optimization procedures.The contents of this paper are mainly divided into three parts: first,the WPP processes are analyzed, and related elements are formulated to transform the qualitative problem to mathematics form;second, the value evaluation model of WPP solutions is proposed based on two criteria of total capability gap and total capability dispersion; third, two robustness optimization models are constructed based on the absolute robustness criterion and the robustness deviation criterion to support the robustness optimization process under multi-scenario. Finally, a case is studied to examine the feasibility and effectiveness of the proposed models and approaches.
基金supported by the Education Science Fund of the Military Science Institute of Beijing,China(2015JY320)
文摘In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support provided by wartime military material support powers can be more effective. When the principles,requirements, influencing factors and goals of military material support forces are deployed in wartime, an evaluation indicator system is established. Thus, a new combined empowerment method based on an analytic hierarchy process（AHP） is developed to calculate the subjective weights, and the rough entropy method is used to calculate the objective weights. Combination weights can be obtained by calculating the weight preference coefficient error, which is determined by combining the cooperative game method and the minimum deviation into objectives. This approach can determine the grey relation projection coefficient and synthesize the measure scheme superiority to finally optimize the deployment plan using the grey relation projection decision-making method. The results show that the method is feasible and effective;it can provide a more scientific and practical decision-making basis for the military material support power deployment in wartime.
