Background Owing to the limitations of the working principle of three-dimensional(3D) scanning equipment, the point clouds obtained by 3D scanning are usually sparse and unevenly distributed. Method In this paper, we ...Background Owing to the limitations of the working principle of three-dimensional(3D) scanning equipment, the point clouds obtained by 3D scanning are usually sparse and unevenly distributed. Method In this paper, we propose a new generative adversarial network(GAN) that extends PU-GAN for upsampling of point clouds. Its core architecture aims to replace the traditional self-attention(SA) module with an implicit Laplacian offset attention(OA) module and to aggregate the adjacency features using a multiscale offset attention(MSOA)module, which adaptively adjusts the receptive field to learn various structural features. Finally, residual links are added to create our residual multiscale offset attention(RMSOA) module, which utilizes multiscale structural relationships to generate finer details. Result The results of several experiments show that our method outperforms existing methods and is highly robust.展开更多
A method for the determination of trace mercury in water samples by hydride generation atomic absorption spectrophotometry after cloud point extraction was proposed in the present work. The effects of pH, concentratio...A method for the determination of trace mercury in water samples by hydride generation atomic absorption spectrophotometry after cloud point extraction was proposed in the present work. The effects of pH, concentration of surfactant, and equilibration time on cloud point extraction were discussed. The enhancement factor of 20 and the detection limit of 0.039 μg/L were obtained for mercury with relative standard deviation of 4.8% （n = 11）.展开更多
The binocular stereo vision is the lowest cost sensor for obtaining 3D information.Considering the weakness of long‐distance measurement and stability,the improvement of accuracy and stability of stereo vision is urg...The binocular stereo vision is the lowest cost sensor for obtaining 3D information.Considering the weakness of long‐distance measurement and stability,the improvement of accuracy and stability of stereo vision is urgently required for application of precision agriculture.To address the challenges of stereo vision long‐distance measurement and stable perception without hardware upgrade,inspired by hawk eyes,higher resolution perception and the adaptive HDR(High Dynamic Range)were introduced in this paper.Simulating the function from physiological structure of‘deep fovea’and‘shallow fovea’of hawk eye,the higher resolution reconstruction method in this paper was aimed at ac-curacy improving.Inspired by adjustment of pupils,the adaptive HDR method was proposed for high dynamic range optimisation and stable perception.In various light conditions,compared with default stereo vision,the accuracy of proposed algorithm was improved by 28.0%evaluated by error ratio,and the stability was improved by 26.56%by disparity accuracy.For fixed distance measurement,the maximum improvement was 78.6%by standard deviation.Based on the hawk‐eye‐inspired perception algorithm,the point cloud of orchard was improved both in quality and quantity.The hawk‐eye‐inspired perception algorithm contributed great advance in binocular 3D point cloud recon-struction in orchard navigation map.展开更多
A conservative constraint on the rest mass of the photon can be estimated under the assump- tion that the frequency dependence of dispersion from astronomical sources is mainly contributed by the nonzero photon mass e...A conservative constraint on the rest mass of the photon can be estimated under the assump- tion that the frequency dependence of dispersion from astronomical sources is mainly contributed by the nonzero photon mass effect. Photon mass limits have been set earlier through the optical emissions of the Crab Nebula pulsar, but we demonstrate that these limits can be significantly improved with the dispersion measure （DM） measurements of radio pulsars in the Large and Small Magellanic Clouds. The combination of DM measurements of pulsars and distances of the Magellanic Clouds provides a strict upper limit on the photon mass as low as mγ≤2.0 ～ 10-45 g, which is at least four orders of magnitude smaller than the constraint from the Crab Nebula pulsar. Although our limit is not as tight as the current best result （～ 10-47 g） from a fast radio burst （FRB 150418） at a cosmological distance, the cosmological origin of FRB 150418 remains under debate; and our limit can reach the same high precision of FRB 150418 when it has an extragalactic origin （ ～10-45 g）.展开更多
Background Cumulus clouds are important elements in creating virtual outdoor scenes.Modeling cumulus clouds that have a specific shape is difficult owing to the fluid nature of the cloud.Image-based modeling is an eff...Background Cumulus clouds are important elements in creating virtual outdoor scenes.Modeling cumulus clouds that have a specific shape is difficult owing to the fluid nature of the cloud.Image-based modeling is an efficient method to solve this problem.Because of the complexity of cloud shapes,the task of modeling the cloud from a single image remains in the development phase.Methods In this study,a deep learning-based method was developed to address the problem of modeling 3D cumulus clouds from a single image.The method employs a three-dimensional autoencoder network that combines the variational autoencoder and the generative adversarial network.First,a 3D cloud shape is mapped into a unique hidden space using the proposed autoencoder.Then,the parameters of the decoder are fixed.A shape reconstruction network is proposed for use instead of the encoder part,and it is trained with rendered images.To train the presented models,we constructed a 3D cumulus dataset that included 2003D cumulus models.These cumulus clouds were rendered under different lighting parameters.Results The qualitative experiments showed that the proposed autoencoder method can learn more structural details of 3D cumulus shapes than existing approaches.Furthermore,some modeling experiments on rendering images demonstrated the effectiveness of the reconstruction model.Conclusion The proposed autoencoder network learns the latent space of 3D cumulus cloud shapes.The presented reconstruction architecture models a cloud from a single image.Experiments demonstrated the effectiveness of the two models.展开更多
The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity d...The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.展开更多
Distributed Denial of Service (DDoS) attacks are performed from multiple agents towards a single victim. Essentially, all attacking agents generate multiple packets towards the victim to overwhelm it with requests, th...Distributed Denial of Service (DDoS) attacks are performed from multiple agents towards a single victim. Essentially, all attacking agents generate multiple packets towards the victim to overwhelm it with requests, thereby overloading the resources of the victim. Since it is very complex and expensive to conduct a real DDoS attack, most organizations and researchers result in using simulations to mimic an actual attack. The researchers come up with diverse algorithms and mechanisms for attack detection and prevention. Further, simulation is good practice for determining the efficacy of an intrusive detective measure against DDoS attacks. However, some mechanisms are ineffective and thus not applied in real life attacks. Nowadays, DDoS attack has become more complex and modern for most IDS to detect. Adjustable and configurable traffic generator is becoming more and more important. This paper first details the available datasets that scholars use for DDoS attack detection. The paper further depicts the a few tools that exist freely and commercially for use in the simulation programs of DDoS attacks. In addition, a traffic generator for normal and different types of DDoS attack has been developed. The aim of the paper is to simulate a cloud environment by OMNET++ simulation tool, with different DDoS attack types. Generation normal and attack traffic can be useful to evaluate developing IDS for DDoS attacks detection. Moreover, the result traffic can be useful to test an effective algorithm, techniques and procedures of DDoS attacks.展开更多
This study presents a clear evolution of computing and its key applications. Cloud computing services evolved from distributed, grid, and utility computing. Critical companies such as Salesforce,Amazon, Google, and Mi...This study presents a clear evolution of computing and its key applications. Cloud computing services evolved from distributed, grid, and utility computing. Critical companies such as Salesforce,Amazon, Google, and Microsoft play important roles in cloud computing. Dramatic changes in the technology environment have created new challenges for current information technologies. This study discusses four significant challenges for cloud computing services,including the next-generation Internet, data synchronization, cloud security, and competitive advantages.And then it also discusses how managers can learn about the future of cloud computing services.展开更多
[Objective] The aim was to summarize the characteristics of refelectivity factors of Doppler radar of the cold front cloud system. [Method] Judging from the characteristics of reflectivity factors, by dint of the new ...[Objective] The aim was to summarize the characteristics of refelectivity factors of Doppler radar of the cold front cloud system. [Method] Judging from the characteristics of reflectivity factors, by dint of the new generation weather radar in Harbin from 2002 to 2007, the features of the reflectivity factors of the cold front cloud system were summarized. [Result] The cloud formed by the cold front was in banded form in general. However, there was void in the cloud and its intensity was uneven. Most fast moving cold front was long and narrow banded echo and basically the radial velocity turned from northwest wind to southwest. With the changes of month, the feature of the reflective rate also changed. In winter, the cold front cloud was in layer form. The feature of the reflectivity factors was weak and in large area. However, the structure was loose and there was space in the echo. Among them, there were several strong echoes. Strong convection cell echo formed in the two sides of the cold front, and it moved with the entire cloud belt. When the dry cold front moved, regional strong convective current formed, mainly by convective cloud and small echo area. Generally, the changes of the wind direction can not be expounded from the radial velocity. However, the intensity of the convection cell was distinct, 'three-body scattering', 'side lobe echo', and 'weak echo', as well as features of super convection cell. [Conclusion] The study provided positive role for the application of Doppler radar in the surveillance of weather in Heilongjiang Province.展开更多
基金Supported by the National Natural Science Foundation of China (61901308)。
文摘Background Owing to the limitations of the working principle of three-dimensional(3D) scanning equipment, the point clouds obtained by 3D scanning are usually sparse and unevenly distributed. Method In this paper, we propose a new generative adversarial network(GAN) that extends PU-GAN for upsampling of point clouds. Its core architecture aims to replace the traditional self-attention(SA) module with an implicit Laplacian offset attention(OA) module and to aggregate the adjacency features using a multiscale offset attention(MSOA)module, which adaptively adjusts the receptive field to learn various structural features. Finally, residual links are added to create our residual multiscale offset attention(RMSOA) module, which utilizes multiscale structural relationships to generate finer details. Result The results of several experiments show that our method outperforms existing methods and is highly robust.
文摘A method for the determination of trace mercury in water samples by hydride generation atomic absorption spectrophotometry after cloud point extraction was proposed in the present work. The effects of pH, concentration of surfactant, and equilibration time on cloud point extraction were discussed. The enhancement factor of 20 and the detection limit of 0.039 μg/L were obtained for mercury with relative standard deviation of 4.8% （n = 11）.
基金funded by the National Natural Science Foundation of China(No.51979275)Key Laboratory of Spatial‐temporal Big Data Analysis and Application of Nat-ural Resources in Megacities,MNR(No.KFKT‐2022‐05)+3 种基金Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources(No.KF‐2021‐06‐115)Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems,Bei-hang University(No.VRLAB2022C10)Jiangsu Province and Education Ministry Co‐sponsored Synergistic Innovation Center of Modern Agricultural Equipment(No.XTCX2002)2115 Talent Development Program of China Agricultural University and Chinese Universities Scientific Fund(No.2021TC105).
文摘The binocular stereo vision is the lowest cost sensor for obtaining 3D information.Considering the weakness of long‐distance measurement and stability,the improvement of accuracy and stability of stereo vision is urgently required for application of precision agriculture.To address the challenges of stereo vision long‐distance measurement and stable perception without hardware upgrade,inspired by hawk eyes,higher resolution perception and the adaptive HDR(High Dynamic Range)were introduced in this paper.Simulating the function from physiological structure of‘deep fovea’and‘shallow fovea’of hawk eye,the higher resolution reconstruction method in this paper was aimed at ac-curacy improving.Inspired by adjustment of pupils,the adaptive HDR method was proposed for high dynamic range optimisation and stable perception.In various light conditions,compared with default stereo vision,the accuracy of proposed algorithm was improved by 28.0%evaluated by error ratio,and the stability was improved by 26.56%by disparity accuracy.For fixed distance measurement,the maximum improvement was 78.6%by standard deviation.Based on the hawk‐eye‐inspired perception algorithm,the point cloud of orchard was improved both in quality and quantity.The hawk‐eye‐inspired perception algorithm contributed great advance in binocular 3D point cloud recon-struction in orchard navigation map.
基金partially supported by the National Basic Research Program of China(973 Program,Grant Nos.2014CB845800 and 2013CB834900)the National Natural Science Foundation of China(Grant Nos.11322328,11433009,11673068 and 11603076)+4 种基金the Youth Innovation Promotion Association(2011231)the Key Research Program of Frontier Sciences(QYZDBSSW-SYS005)the Strategic Priority Research Program“The Emergence of Cosmological Structures”(Grant No.XDB09000000)of the Chinese Academy of Sciencesthe Natural Science Foundation of Jiangsu Province(Grant No.BK20161096)the Guangxi Key Laboratory for Relativistic Astrophysics
文摘A conservative constraint on the rest mass of the photon can be estimated under the assump- tion that the frequency dependence of dispersion from astronomical sources is mainly contributed by the nonzero photon mass effect. Photon mass limits have been set earlier through the optical emissions of the Crab Nebula pulsar, but we demonstrate that these limits can be significantly improved with the dispersion measure （DM） measurements of radio pulsars in the Large and Small Magellanic Clouds. The combination of DM measurements of pulsars and distances of the Magellanic Clouds provides a strict upper limit on the photon mass as low as mγ≤2.0 ～ 10-45 g, which is at least four orders of magnitude smaller than the constraint from the Crab Nebula pulsar. Although our limit is not as tight as the current best result （～ 10-47 g） from a fast radio burst （FRB 150418） at a cosmological distance, the cosmological origin of FRB 150418 remains under debate; and our limit can reach the same high precision of FRB 150418 when it has an extragalactic origin （ ～10-45 g）.
基金the National Key R&D Program of China(2017YFB1002702).
文摘Background Cumulus clouds are important elements in creating virtual outdoor scenes.Modeling cumulus clouds that have a specific shape is difficult owing to the fluid nature of the cloud.Image-based modeling is an efficient method to solve this problem.Because of the complexity of cloud shapes,the task of modeling the cloud from a single image remains in the development phase.Methods In this study,a deep learning-based method was developed to address the problem of modeling 3D cumulus clouds from a single image.The method employs a three-dimensional autoencoder network that combines the variational autoencoder and the generative adversarial network.First,a 3D cloud shape is mapped into a unique hidden space using the proposed autoencoder.Then,the parameters of the decoder are fixed.A shape reconstruction network is proposed for use instead of the encoder part,and it is trained with rendered images.To train the presented models,we constructed a 3D cumulus dataset that included 2003D cumulus models.These cumulus clouds were rendered under different lighting parameters.Results The qualitative experiments showed that the proposed autoencoder method can learn more structural details of 3D cumulus shapes than existing approaches.Furthermore,some modeling experiments on rendering images demonstrated the effectiveness of the reconstruction model.Conclusion The proposed autoencoder network learns the latent space of 3D cumulus cloud shapes.The presented reconstruction architecture models a cloud from a single image.Experiments demonstrated the effectiveness of the two models.
基金funded by the Natural Science Foundation Committee,China(41364001,41371435)
文摘The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its gener- alized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.
文摘Distributed Denial of Service (DDoS) attacks are performed from multiple agents towards a single victim. Essentially, all attacking agents generate multiple packets towards the victim to overwhelm it with requests, thereby overloading the resources of the victim. Since it is very complex and expensive to conduct a real DDoS attack, most organizations and researchers result in using simulations to mimic an actual attack. The researchers come up with diverse algorithms and mechanisms for attack detection and prevention. Further, simulation is good practice for determining the efficacy of an intrusive detective measure against DDoS attacks. However, some mechanisms are ineffective and thus not applied in real life attacks. Nowadays, DDoS attack has become more complex and modern for most IDS to detect. Adjustable and configurable traffic generator is becoming more and more important. This paper first details the available datasets that scholars use for DDoS attack detection. The paper further depicts the a few tools that exist freely and commercially for use in the simulation programs of DDoS attacks. In addition, a traffic generator for normal and different types of DDoS attack has been developed. The aim of the paper is to simulate a cloud environment by OMNET++ simulation tool, with different DDoS attack types. Generation normal and attack traffic can be useful to evaluate developing IDS for DDoS attacks detection. Moreover, the result traffic can be useful to test an effective algorithm, techniques and procedures of DDoS attacks.
基金supported by the NSC under Grant No.102-2410-H-130-038
文摘This study presents a clear evolution of computing and its key applications. Cloud computing services evolved from distributed, grid, and utility computing. Critical companies such as Salesforce,Amazon, Google, and Microsoft play important roles in cloud computing. Dramatic changes in the technology environment have created new challenges for current information technologies. This study discusses four significant challenges for cloud computing services,including the next-generation Internet, data synchronization, cloud security, and competitive advantages.And then it also discusses how managers can learn about the future of cloud computing services.
文摘[Objective] The aim was to summarize the characteristics of refelectivity factors of Doppler radar of the cold front cloud system. [Method] Judging from the characteristics of reflectivity factors, by dint of the new generation weather radar in Harbin from 2002 to 2007, the features of the reflectivity factors of the cold front cloud system were summarized. [Result] The cloud formed by the cold front was in banded form in general. However, there was void in the cloud and its intensity was uneven. Most fast moving cold front was long and narrow banded echo and basically the radial velocity turned from northwest wind to southwest. With the changes of month, the feature of the reflective rate also changed. In winter, the cold front cloud was in layer form. The feature of the reflectivity factors was weak and in large area. However, the structure was loose and there was space in the echo. Among them, there were several strong echoes. Strong convection cell echo formed in the two sides of the cold front, and it moved with the entire cloud belt. When the dry cold front moved, regional strong convective current formed, mainly by convective cloud and small echo area. Generally, the changes of the wind direction can not be expounded from the radial velocity. However, the intensity of the convection cell was distinct, 'three-body scattering', 'side lobe echo', and 'weak echo', as well as features of super convection cell. [Conclusion] The study provided positive role for the application of Doppler radar in the surveillance of weather in Heilongjiang Province.
