Data are limitless. But those are usually not formed or created in our needs. Most of data providers deliver their data in Microsoft Excel spreadsheet, which is compatible with ArcGIS, the most widely used GIS （Geogr...Data are limitless. But those are usually not formed or created in our needs. Most of data providers deliver their data in Microsoft Excel spreadsheet, which is compatible with ArcGIS, the most widely used GIS （Geographic Information System） software in GIS sector. However, those table data contain much unnecessary information that do not need for a certain project. Using the raw data can increase processing times and reduce performance of geoprocessing tools. This study shows steps of how the raw data are being processed using ArcGIS ModelBuilder and Python script.展开更多
Based on former studies on weather simulator modules in IPMist laboratory, study on visual programming of stochastic weather generator(VS-WGEN)was continued. In this study, Markov Chain, Monte Carlo, Fourier Series, a...Based on former studies on weather simulator modules in IPMist laboratory, study on visual programming of stochastic weather generator(VS-WGEN)was continued. In this study, Markov Chain, Monte Carlo, Fourier Series, and weak stationary process were used to generate the daily weather data in software Matlab 6. 0, with the data input from 40 years' weather data recorded by Beijing Weather Station. The generated data includes daily maximum temperature, minimum temperature, precipitation and solar radiation. It has been verified that the weather data generated by the VS-WGEN were more accurate than that by the old WGEN, when twenty new model parameters were included. VS-WGEN has wide software applications, such as pest risk analysis, pest forecast and management. It can be implemented in hardware development as well, such as weather control in weather chamber and greenhouse for researches on ecological adaptation of crop varieties to a given location over time and space. Overall, VS-WGEN is a very useful tool for studies on theoretical and applied ecology.展开更多
Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emerg...Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emergency medicine poses a significant challenge.To address this,we propose a novel approach based on the inter-learning of visual features between global and local information.Specifically,our method enhances the perception capabilities of the visual feature extractor by strategically leveraging the strengths of convolutional neural network(CNN),which are adept at capturing local features,and visual transformers which perform well at perceiving global features.Furthermore,to mitigate the issue of overfitting caused by the limited availability of sign language data for emergency medical applications,we introduce an enhanced short temporal module for data augmentation through additional subsequences.Experimental results on three publicly available sign language datasets demonstrate the efficacy of the proposed approach.展开更多
This research investigates the application of digital images in military contexts by utilizing analytical equations to augment human visual capabilities.A comparable filter is used to improve the visual quality of the...This research investigates the application of digital images in military contexts by utilizing analytical equations to augment human visual capabilities.A comparable filter is used to improve the visual quality of the photographs by reducing truncations in the existing images.Furthermore,the collected images undergo processing using histogram gradients and a flexible threshold value that may be adjusted in specific situations.Thus,it is possible to reduce the occurrence of overlapping circumstances in collective picture characteristics by substituting grey-scale photos with colorized factors.The proposed method offers additional robust feature representations by imposing a limiting factor to reduce overall scattering values.This is achieved by visualizing a graphical function.Moreover,to derive valuable insights from a series of photos,both the separation and in-version processes are conducted.This involves analyzing comparison results across four different scenarios.The results of the comparative analysis show that the proposed method effectively reduces the difficulties associated with time and space to 1 s and 3%,respectively.In contrast,the existing strategy exhibits higher complexities of 3 s and 9.1%,respectively.展开更多
In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.Ho...In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.However,existing image sensors—such as CMOS and CCD devices—intrinsically suffer from the limitation of fixed spectral response.Especially in environments with strong glare,haze,or dust,external spectral conditions often severely mismatch the device's design range,leading to significant degradation in image quality and a sharp drop in target recognition accuracy.While algorithmic post-processing(such as color bias correction or background suppression)can mitigate these issues,algorithm approaches typically introduce computational latency and increased energy consumption,making them unsuitable for edge computing or high-speed scenarios.展开更多
This paper describes an extendable graphical framework,aflak,which provides a visualization and provenance management environment for the analysis of multi-spectral astronomical datasets.Via its node editor interface,...This paper describes an extendable graphical framework,aflak,which provides a visualization and provenance management environment for the analysis of multi-spectral astronomical datasets.Via its node editor interface,aflak allows the astronomer to compose transforms on input datasets queryable from public astronomical data repositories,then to export the results of the analysis as Flexible Image Transport System(FITS)files,in a manner such that the full provenance of the output data be preserved and reviewable,and that the exported file be usable by other common astronomical analysis software.FITS is the standard of data interchange in astronomy.By embedding aflak’s provenance data into FITS files,we both achieve interoperability with existing software and full reproducibility of the process by which astronomers make discoveries.展开更多
Since the specifications of most of the existing context-sensitive graph grammars tend to be either too intricate or not intuitive, a novel context-sensitive graph grammar formalism, called context-attributed graph gr...Since the specifications of most of the existing context-sensitive graph grammars tend to be either too intricate or not intuitive, a novel context-sensitive graph grammar formalism, called context-attributed graph grammar（CAGG）, is proposed. In order to resolve the embedding problem, context information of a graph production in the CAGG is represented in the form of context attributes of the nodes involved. Moreover, several properties of a set of confluent CAGG productions are characterized, and then an algorithm based on them is developed to decide whether or not a set of productions is confluent, which provides the foundation for the design of efficient parsing algorithms. It can also be shown through the comparison of CAGG with several typical context-sensitive graph grammars that CAGG is more succinct and, at the same time, more intuitive than the others, making it more suitably and effortlessly applicable to the specification of visual languages.展开更多
The purpose of this research is the design and implementation of a support system for learning programming. To archive this purpose, in this article, we propose a Puzzle Programming System that uses jigsaw puzzles as ...The purpose of this research is the design and implementation of a support system for learning programming. To archive this purpose, in this article, we propose a Puzzle Programming System that uses jigsaw puzzles as an example of the application of physical visualization, which visualizes logical constraints to physical ones. This Puzzle Programming System aims to teach basic programming concepts by presenting the invisible constraints of programming language syntax using the visual constraints of jigsaw puzzle pieces. This system runs on an Apple iPad and was developed using the Unity game engine. We used YAML as a data format for serializing structured data for data management. By inviting high school students to try out a prototype, we could confirm the usefulness of the Puzzle Programming System. The experimental evaluation results also shed light on aspects of the game that need to be redesigned and parts where the visual programming model needs to be modified and expanded.展开更多
Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for rese...Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.展开更多
INTRODUCTION Although visual programming is being broadly implemented in other disciplines,it has only relatively recently become an important supplement to three-dimensional modeling programs in the architecture,engi...INTRODUCTION Although visual programming is being broadly implemented in other disciplines,it has only relatively recently become an important supplement to three-dimensional modeling programs in the architecture,engineering,and construction industry.Currently,Grasshopper in conjunction with Rhino is a leading example of a visual programming environment that is strongly supported by a user community that is developing additional functionality,but Grasshopper does not yet work directly with building information modeling(BIM)software.Dynamo is relatively new,but shows considerable promise in becoming a constructive tool to complement BIM,3D modeling,and analysis programs because it includes parametric geom-etries and works with Revit,a leading BIM software program.Three case studies are described:extensibility of Dynamo through the use of a building energy simu-lation package,controlling a virtual model’s response through light level sensors,and interactively updating shading components for a building facade based on solar angles.They demonstrate that one can work directly within building information models(BIM)using a visual programming language through updating component parameters.These case studies demonstrate the feasibility of a workflow for sustain-able design simulations that is different than that more commonly used--having a separation between design and analysis models and using a neutral file format exchange such as IFC or gbXML to transfer data.As visual programming languages are still a bit uncommon in the building industry,a short background is provided to place them within the tool set of other customizable tools that designers have been developing.展开更多
Purpose: Diabetes Mellitus (DM) is a prevalent metabolic disorder associated with significant complications, including visual impairment. This study aimed to assess the prevalence and severity of visual impairment and...Purpose: Diabetes Mellitus (DM) is a prevalent metabolic disorder associated with significant complications, including visual impairment. This study aimed to assess the prevalence and severity of visual impairment and its associated factors in diabetic patients in Libya. Methods: This cross-sectional study included 2365 DM patients (4730 eyes). Most participants were aged 30 - 49 (38.3%) and 50 - 69 (50.8%) with a nearly equal gender distribution (47.8% males, 52.2% females). Type 2 diabetes was predominant (92.6%), and 62.9% had HbA1c levels of 7.5% or higher. Results: Diabetic retinopathy (DR) was present in 2068 eyes (43.8%), with mild non-proliferative diabetic retinopathy (NPDR) affecting 1178 eyes (25%), moderate NPDR 476 eyes (10.1%), severe NPDR 228 eyes (4.8%), and proliferative diabetic retinopathy (PDR) 186 eyes (3.9%). Diabetic maculopathy was observed in 621 eyes (13.1%), with CSME in 287 eyes (6.07%) and non-CSME in 334 eyes (7.06%). Non-retinal conditions included cataracts in 1938 eyes (41%) and glaucoma in 252 eyes (5.3%). Visual impairment was observed in 1159 patients (49%), with 534 (23%) experiencing mild impairment, 382 (18%) moderate impairment, and 243 (12%) severe impairment;142 patients (6%) were classified as legally blind. DR showed a strong association with visual impairment severity (p Conclusions: These findings underscore the urgency for targeted public health interventions to mitigate visual impairment in Libyan individuals with DM.展开更多
Visual Attention Prediction(VAP)is widely applied in GIS research,such as navigation task identification and driver assistance systems.Previous studies commonly took color information to detect the visual saliency of ...Visual Attention Prediction(VAP)is widely applied in GIS research,such as navigation task identification and driver assistance systems.Previous studies commonly took color information to detect the visual saliency of natural scene images.However,these studies rarely considered adaptively feature integration to different geospatial scenes in specific tasks.To better predict visual attention while driving tasks,in this paper,we firstly propose an Adaptive Feature Integration Fully Convolutional Network(AdaFI-FCN)using Scene-Adaptive Weights(SAW)to integrate RGB-D,motion and semantic features.The quantitative comparison results on the DR(eye)VE dataset show that the proposed framework achieved the best accuracy and robustness performance compared with state-of-the-art models(AUC-Judd=0.971,CC=0.767,KL=1.046,SIM=0.579).In addition,the experimental results of the ablation study demonstrated the positive effect of the SAW method on the prediction robustness in response to scene changes.The proposed model has the potential to benefit adaptive VAP research in universal geospatial scenes,such as AR-aided navigation,indoor navigation,and street-view image reading.展开更多
This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization.The research background is that with the increasing amount and complexity of data,tradit...This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization.The research background is that with the increasing amount and complexity of data,traditional data analysis methods have been unable to meet the needs.Research methods include building neural networks and deep learning models,optimizing and improving them through Bayesian analysis,and applying them to the visualization of large-scale data sets.The results show that the neural network combined with Bayesian analysis and deep learning method can effectively improve the accuracy and efficiency of data visualization,and enhance the intuitiveness and depth of data interpretation.The significance of the research is that it provides a new solution for data visualization in the big data environment and helps to further promote the development and application of data science.展开更多
A great number of visual simultaneous localization and mapping(VSLAM)systems need to assume static features in the environment.However,moving objects can vastly impair the performance of a VSLAM system which relies on...A great number of visual simultaneous localization and mapping(VSLAM)systems need to assume static features in the environment.However,moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption.To cope with this challenging topic,a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed.To reduce the influence of dynamic content,we incorporate the deep-learning-based object detection method in the visual odometry,then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system.Experiment with both on the TUM and KITTI benchmark dataset,as well as in a real-world environment,the results clarify that our method can significantly reduce the tracking error or drift,enhance the robustness,accuracy and stability of the VSLAM system in dynamic scenes.展开更多
To simulate the process of cold roll-forming process, a new method isadopted. The theoretical foundation of this method is an elastic-plastic large deformation splinefinite strip method based on object-oriented progra...To simulate the process of cold roll-forming process, a new method isadopted. The theoretical foundation of this method is an elastic-plastic large deformation splinefinite strip method based on object-oriented programming. Combined with the computer graphicstechnology, the visual simulation of cold roll-forming is completed and the system is established.By analyzing common channel steel, the process is shown and explained including theory method, modeland result display. So the simulation system is already a kind of mature and effective tool toanalyze the process of cold roll forming.展开更多
This paper presents a hierarchical simultaneous localization and mapping（SLAM） system for a small unmanned aerial vehicle（UAV） using the output of an inertial measurement unit（IMU） and the bearing-only observati...This paper presents a hierarchical simultaneous localization and mapping（SLAM） system for a small unmanned aerial vehicle（UAV） using the output of an inertial measurement unit（IMU） and the bearing-only observations from an onboard monocular camera.A homography based approach is used to calculate the motion of the vehicle in 6 degrees of freedom by image feature match.This visual measurement is fused with the inertial outputs by an indirect extended Kalman filter（EKF） for attitude and velocity estimation.Then,another EKF is employed to estimate the position of the vehicle and the locations of the features in the map.Both simulations and experiments are carried out to test the performance of the proposed system.The result of the comparison with the referential global positioning system/inertial navigation system（GPS/INS） navigation indicates that the proposed SLAM can provide reliable and stable state estimation for small UAVs in GPS-denied environments.展开更多
文摘Data are limitless. But those are usually not formed or created in our needs. Most of data providers deliver their data in Microsoft Excel spreadsheet, which is compatible with ArcGIS, the most widely used GIS （Geographic Information System） software in GIS sector. However, those table data contain much unnecessary information that do not need for a certain project. Using the raw data can increase processing times and reduce performance of geoprocessing tools. This study shows steps of how the raw data are being processed using ArcGIS ModelBuilder and Python script.
基金supported jointly by the grant of Project“973”:Fundamental Studies on Invasion and Control of Extra Pest(2002CB111400)the grant of Key Project of Ministry of Science and Technology of China:Development of New Technologies for Pest Forecasting(2001BA50PB01).
文摘Based on former studies on weather simulator modules in IPMist laboratory, study on visual programming of stochastic weather generator(VS-WGEN)was continued. In this study, Markov Chain, Monte Carlo, Fourier Series, and weak stationary process were used to generate the daily weather data in software Matlab 6. 0, with the data input from 40 years' weather data recorded by Beijing Weather Station. The generated data includes daily maximum temperature, minimum temperature, precipitation and solar radiation. It has been verified that the weather data generated by the VS-WGEN were more accurate than that by the old WGEN, when twenty new model parameters were included. VS-WGEN has wide software applications, such as pest risk analysis, pest forecast and management. It can be implemented in hardware development as well, such as weather control in weather chamber and greenhouse for researches on ecological adaptation of crop varieties to a given location over time and space. Overall, VS-WGEN is a very useful tool for studies on theoretical and applied ecology.
基金supported by the National Natural Science Foundation of China(No.62376197)the Tianjin Science and Technology Program(No.23JCYBJC00360)the Tianjin Health Research Project(No.TJWJ2025MS045).
文摘Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emergency medicine poses a significant challenge.To address this,we propose a novel approach based on the inter-learning of visual features between global and local information.Specifically,our method enhances the perception capabilities of the visual feature extractor by strategically leveraging the strengths of convolutional neural network(CNN),which are adept at capturing local features,and visual transformers which perform well at perceiving global features.Furthermore,to mitigate the issue of overfitting caused by the limited availability of sign language data for emergency medical applications,we introduce an enhanced short temporal module for data augmentation through additional subsequences.Experimental results on three publicly available sign language datasets demonstrate the efficacy of the proposed approach.
基金financially supported by Ongoing Research Funding Program(ORF-2025-846),King Saud University,Riyadh,Saudi Arabia.
文摘This research investigates the application of digital images in military contexts by utilizing analytical equations to augment human visual capabilities.A comparable filter is used to improve the visual quality of the photographs by reducing truncations in the existing images.Furthermore,the collected images undergo processing using histogram gradients and a flexible threshold value that may be adjusted in specific situations.Thus,it is possible to reduce the occurrence of overlapping circumstances in collective picture characteristics by substituting grey-scale photos with colorized factors.The proposed method offers additional robust feature representations by imposing a limiting factor to reduce overall scattering values.This is achieved by visualizing a graphical function.Moreover,to derive valuable insights from a series of photos,both the separation and in-version processes are conducted.This involves analyzing comparison results across four different scenarios.The results of the comparative analysis show that the proposed method effectively reduces the difficulties associated with time and space to 1 s and 3%,respectively.In contrast,the existing strategy exhibits higher complexities of 3 s and 9.1%,respectively.
基金supported in part by STI 2030-Major Projects(2022ZD0209200)in part by National Natural Science Foundation of China(62374099)+2 种基金in part by Beijing Natural Science Foundation−Xiaomi Innovation Joint Fund(L233009)Beijing Natural Science Foundation(L248104)in part by Independent Research Program of School of Integrated Circuits,Tsinghua University,in part by Tsinghua University Fuzhou Data Technology Joint Research Institute.
文摘In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.However,existing image sensors—such as CMOS and CCD devices—intrinsically suffer from the limitation of fixed spectral response.Especially in environments with strong glare,haze,or dust,external spectral conditions often severely mismatch the device's design range,leading to significant degradation in image quality and a sharp drop in target recognition accuracy.While algorithmic post-processing(such as color bias correction or background suppression)can mitigate these issues,algorithm approaches typically introduce computational latency and increased energy consumption,making them unsuitable for edge computing or high-speed scenarios.
基金JSPS KAKENHI(Japan)Grant Numbers 17K00173 and 17H00737.
文摘This paper describes an extendable graphical framework,aflak,which provides a visualization and provenance management environment for the analysis of multi-spectral astronomical datasets.Via its node editor interface,aflak allows the astronomer to compose transforms on input datasets queryable from public astronomical data repositories,then to export the results of the analysis as Flexible Image Transport System(FITS)files,in a manner such that the full provenance of the output data be preserved and reviewable,and that the exported file be usable by other common astronomical analysis software.FITS is the standard of data interchange in astronomy.By embedding aflak’s provenance data into FITS files,we both achieve interoperability with existing software and full reproducibility of the process by which astronomers make discoveries.
基金The National Natural Science Foundation of China(No.60571048,60673186,60736015)the National High Technology Researchand Development Program of China(863Program)(No.2007AA01Z178)
文摘Since the specifications of most of the existing context-sensitive graph grammars tend to be either too intricate or not intuitive, a novel context-sensitive graph grammar formalism, called context-attributed graph grammar（CAGG）, is proposed. In order to resolve the embedding problem, context information of a graph production in the CAGG is represented in the form of context attributes of the nodes involved. Moreover, several properties of a set of confluent CAGG productions are characterized, and then an algorithm based on them is developed to decide whether or not a set of productions is confluent, which provides the foundation for the design of efficient parsing algorithms. It can also be shown through the comparison of CAGG with several typical context-sensitive graph grammars that CAGG is more succinct and, at the same time, more intuitive than the others, making it more suitably and effortlessly applicable to the specification of visual languages.
文摘The purpose of this research is the design and implementation of a support system for learning programming. To archive this purpose, in this article, we propose a Puzzle Programming System that uses jigsaw puzzles as an example of the application of physical visualization, which visualizes logical constraints to physical ones. This Puzzle Programming System aims to teach basic programming concepts by presenting the invisible constraints of programming language syntax using the visual constraints of jigsaw puzzle pieces. This system runs on an Apple iPad and was developed using the Unity game engine. We used YAML as a data format for serializing structured data for data management. By inviting high school students to try out a prototype, we could confirm the usefulness of the Puzzle Programming System. The experimental evaluation results also shed light on aspects of the game that need to be redesigned and parts where the visual programming model needs to be modified and expanded.
文摘Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.
文摘INTRODUCTION Although visual programming is being broadly implemented in other disciplines,it has only relatively recently become an important supplement to three-dimensional modeling programs in the architecture,engineering,and construction industry.Currently,Grasshopper in conjunction with Rhino is a leading example of a visual programming environment that is strongly supported by a user community that is developing additional functionality,but Grasshopper does not yet work directly with building information modeling(BIM)software.Dynamo is relatively new,but shows considerable promise in becoming a constructive tool to complement BIM,3D modeling,and analysis programs because it includes parametric geom-etries and works with Revit,a leading BIM software program.Three case studies are described:extensibility of Dynamo through the use of a building energy simu-lation package,controlling a virtual model’s response through light level sensors,and interactively updating shading components for a building facade based on solar angles.They demonstrate that one can work directly within building information models(BIM)using a visual programming language through updating component parameters.These case studies demonstrate the feasibility of a workflow for sustain-able design simulations that is different than that more commonly used--having a separation between design and analysis models and using a neutral file format exchange such as IFC or gbXML to transfer data.As visual programming languages are still a bit uncommon in the building industry,a short background is provided to place them within the tool set of other customizable tools that designers have been developing.
文摘Purpose: Diabetes Mellitus (DM) is a prevalent metabolic disorder associated with significant complications, including visual impairment. This study aimed to assess the prevalence and severity of visual impairment and its associated factors in diabetic patients in Libya. Methods: This cross-sectional study included 2365 DM patients (4730 eyes). Most participants were aged 30 - 49 (38.3%) and 50 - 69 (50.8%) with a nearly equal gender distribution (47.8% males, 52.2% females). Type 2 diabetes was predominant (92.6%), and 62.9% had HbA1c levels of 7.5% or higher. Results: Diabetic retinopathy (DR) was present in 2068 eyes (43.8%), with mild non-proliferative diabetic retinopathy (NPDR) affecting 1178 eyes (25%), moderate NPDR 476 eyes (10.1%), severe NPDR 228 eyes (4.8%), and proliferative diabetic retinopathy (PDR) 186 eyes (3.9%). Diabetic maculopathy was observed in 621 eyes (13.1%), with CSME in 287 eyes (6.07%) and non-CSME in 334 eyes (7.06%). Non-retinal conditions included cataracts in 1938 eyes (41%) and glaucoma in 252 eyes (5.3%). Visual impairment was observed in 1159 patients (49%), with 534 (23%) experiencing mild impairment, 382 (18%) moderate impairment, and 243 (12%) severe impairment;142 patients (6%) were classified as legally blind. DR showed a strong association with visual impairment severity (p Conclusions: These findings underscore the urgency for targeted public health interventions to mitigate visual impairment in Libyan individuals with DM.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant No.42230103the State Key Laboratory of Geographic Information Engineering and the Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of the Ministry of Natural Resources Jointly Funded Project under Grant No.2021-04-03.
文摘Visual Attention Prediction(VAP)is widely applied in GIS research,such as navigation task identification and driver assistance systems.Previous studies commonly took color information to detect the visual saliency of natural scene images.However,these studies rarely considered adaptively feature integration to different geospatial scenes in specific tasks.To better predict visual attention while driving tasks,in this paper,we firstly propose an Adaptive Feature Integration Fully Convolutional Network(AdaFI-FCN)using Scene-Adaptive Weights(SAW)to integrate RGB-D,motion and semantic features.The quantitative comparison results on the DR(eye)VE dataset show that the proposed framework achieved the best accuracy and robustness performance compared with state-of-the-art models(AUC-Judd=0.971,CC=0.767,KL=1.046,SIM=0.579).In addition,the experimental results of the ablation study demonstrated the positive effect of the SAW method on the prediction robustness in response to scene changes.The proposed model has the potential to benefit adaptive VAP research in universal geospatial scenes,such as AR-aided navigation,indoor navigation,and street-view image reading.
文摘This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization.The research background is that with the increasing amount and complexity of data,traditional data analysis methods have been unable to meet the needs.Research methods include building neural networks and deep learning models,optimizing and improving them through Bayesian analysis,and applying them to the visualization of large-scale data sets.The results show that the neural network combined with Bayesian analysis and deep learning method can effectively improve the accuracy and efficiency of data visualization,and enhance the intuitiveness and depth of data interpretation.The significance of the research is that it provides a new solution for data visualization in the big data environment and helps to further promote the development and application of data science.
基金the National Natural Science Foundation of China(No.61671470).
文摘A great number of visual simultaneous localization and mapping(VSLAM)systems need to assume static features in the environment.However,moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption.To cope with this challenging topic,a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed.To reduce the influence of dynamic content,we incorporate the deep-learning-based object detection method in the visual odometry,then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system.Experiment with both on the TUM and KITTI benchmark dataset,as well as in a real-world environment,the results clarify that our method can significantly reduce the tracking error or drift,enhance the robustness,accuracy and stability of the VSLAM system in dynamic scenes.
基金This project is supported by Provincial Natural Science Foundation of Hebei (No.502214).
文摘To simulate the process of cold roll-forming process, a new method isadopted. The theoretical foundation of this method is an elastic-plastic large deformation splinefinite strip method based on object-oriented programming. Combined with the computer graphicstechnology, the visual simulation of cold roll-forming is completed and the system is established.By analyzing common channel steel, the process is shown and explained including theory method, modeland result display. So the simulation system is already a kind of mature and effective tool toanalyze the process of cold roll forming.
基金supported by National High Technology Research Development Program of China (863 Program) (No.2011AA040202)National Science Foundation of China (No.51005008)
文摘This paper presents a hierarchical simultaneous localization and mapping（SLAM） system for a small unmanned aerial vehicle（UAV） using the output of an inertial measurement unit（IMU） and the bearing-only observations from an onboard monocular camera.A homography based approach is used to calculate the motion of the vehicle in 6 degrees of freedom by image feature match.This visual measurement is fused with the inertial outputs by an indirect extended Kalman filter（EKF） for attitude and velocity estimation.Then,another EKF is employed to estimate the position of the vehicle and the locations of the features in the map.Both simulations and experiments are carried out to test the performance of the proposed system.The result of the comparison with the referential global positioning system/inertial navigation system（GPS/INS） navigation indicates that the proposed SLAM can provide reliable and stable state estimation for small UAVs in GPS-denied environments.
