Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution...Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution sparse compound-eye camera(CEC)based on dual-end collaborative optimization is proposed,which provides a cost-effective way to break through the trade-off among the field of view,resolution,and imaging speed.In the optical end,a sparse CEC based on liquid lenses is designed,which can realize large-field-of-view imaging in real time,and fast zooming within 5 ms.In the computational end,a disturbed degradation model driven super-resolution network(DDMDSR-Net)is proposed to deal with complex image degradation issues in actual imaging situations,achieving high-robustness and high-fidelity resolution enhancement.Based on the proposed dual-end collaborative optimization framework,the angular resolution of the CEC can be enhanced from 71.6"to 26.0",which provides a solution to realize high-resolution imaging for array camera dispensing with high optical hardware complexity and data transmission bandwidth.Experiments verify the advantages of the CEC based on dual-end collaborative optimization in high-fidelity reconstruction of real scene images,kilometer-level long-distance detection,and dynamic imaging and precise recognition of targets of interest.展开更多
This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,an...This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.展开更多
With the rapid development of artificial intelligence technology,AIGC(Artificial Intelligence-Generated Content)has triggered profound changes in the field of high-level language programming courses.This paper deeply ...With the rapid development of artificial intelligence technology,AIGC(Artificial Intelligence-Generated Content)has triggered profound changes in the field of high-level language programming courses.This paper deeply explored the application principles,advantages,and limitations of AIGC in intelligent code generation,analyzed the new mode of human-computer collaboration in high-level language programming courses driven by AIGC,discussed the impact of human-computer collaboration on programming efficiency and code quality through practical case studies,and looks forward to future development trends.This research aims to provide theoretical and practical guidance for high-level language programming courses and promote innovative development of high-level language programming courses under the human-computer collaboration paradigm.展开更多
In the current era marked by energy shortages,the advancement of nuclear energy stands as an inevitable progression.The reprocessing of spent nuclear fuel plays a crucial role in determining the sustainability of nucl...In the current era marked by energy shortages,the advancement of nuclear energy stands as an inevitable progression.The reprocessing of spent nuclear fuel plays a crucial role in determining the sustainability of nuclear energy as a viable energy source.Among these processes,the separation and recovery of Pu(Ⅳ)from high-level liquid waste(HLLW)hold paramount significance in terms of safety and strategic implications.Herein,this work focused on the synthesis of two acid-and radiation-resistant pyridine-based sp^(2)c-COFs(COF-IHEP3 and COF-IHEP4),followed by the creation of two pyridine-based ionized sp^(2)c-COFs named COF-IHEP3-CH_(3)NO_(3)and COF-IHEP4-CH3NO3through post-modification.These materials have potential anion exchange capacity for the selective separation of Pu(Ⅳ)in highly acidic conditions.Notably,in 8 mol/L nitric acid solution,COF-IHEP3-CH3NO3demonstrated the capability to eliminate plutonium within 20 min in 98%removal efficiency with a Kdvalue of 2450 m L/g.Experimental and theoretical analysis suggest that the ionized sp^(2)c-COFs exhibit exceptional stability,selectivity,and prevention of secondary contamination towards Pu(Ⅳ)in the presence of multiple ions environments.In short,this work provides an appropriate anion exchange strategy to design ionic sp^(2)c-COFs as a promising platform for Pu(Ⅳ)recovery from HLLW.展开更多
With the widespread application of large language models(LLMs)in natural language processing and code generation,traditional High-Level Language Programming courses are facing unprecedented challenges and opportunitie...With the widespread application of large language models(LLMs)in natural language processing and code generation,traditional High-Level Language Programming courses are facing unprecedented challenges and opportunities.As a core programming language for computer science majors,C language remains irreplaceable due to its foundational nature and engineering adaptability.This paper,based on the rapid development of large model technologies,proposes a systematic reform design for C language teaching,focusing on teaching objectives,content structure,teaching methods,and evaluation systems.The article suggests a teaching framework centered on“human-computer collaborative programming,”integrating prompt training,AI-assisted debugging,and code generation analysis,aiming to enhance students’problem modeling ability,programming expression skills,and AI collaboration literacy.展开更多
Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned a...Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned aerial vehicles.Localizing moving targets is crucial for analyzing their motion characteristics and dynamic properties.Reconstructing the trajectories of points from asynchronous cameras is a significant challenge.It encompasses two coupled sub-problems:Trajectory reconstruction and camera synchronization.Present methods typically address only one of these sub-problems individually.This paper proposes a 3D trajectory reconstruction method for point targets based on asynchronous cameras,simultaneously solving both sub-problems.Firstly,we extend the trajectory intersection method to asynchronous cameras to resolve the limitation of traditional triangulation that requires camera synchronization.Secondly,we develop models for camera temporal information and target motion,based on imaging mechanisms and target dynamics characteristics.The parameters are optimized simultaneously to achieve trajectory reconstruction without accurate time parameters.Thirdly,we optimize the camera rotations alongside the camera time information and target motion parameters,using tighter and more continuous constraints on moving points.The reconstruction accuracy is significantly improved,especially when the camera rotations are inaccurate.Finally,the simulated and real-world experimental results demonstrate the feasibility and accuracy of the proposed method.The real-world results indicate that the proposed algorithm achieved a localization error of 112.95 m at an observation distance range of 15-20 km.展开更多
Observatories typically deploy all-sky cameras for monitoring cloud cover and weather conditions.However,many of these cameras lack scientific-grade sensors,r.esulting in limited photometric precision,which makes calc...Observatories typically deploy all-sky cameras for monitoring cloud cover and weather conditions.However,many of these cameras lack scientific-grade sensors,r.esulting in limited photometric precision,which makes calculating the sky area visibility distribution via extinction measurement challenging.To address this issue,we propose the Photometry-Free Sky Area Visibility Estimation(PFSAVE)method.This method uses the standard magnitude of the faintest star observed within a given sky area to estimate visibility.By employing a pertransformation refitting optimization strategy,we achieve a high-precision coordinate transformation model with an accuracy of 0.42 pixels.Using the results of HEALPix segmentation is also introduced to achieve high spatial resolution.Comprehensive analysis based on real allsky images demonstrates that our method exhibits higher accuracy than the extinction-based method.Our method supports both manual and robotic dynamic scheduling,especially under partially cloudy conditions.展开更多
It is important to understand the development of joints and fractures in rock masses to ensure drilling stability and blasting effectiveness.Traditional manual observation techniques for identifying and extracting fra...It is important to understand the development of joints and fractures in rock masses to ensure drilling stability and blasting effectiveness.Traditional manual observation techniques for identifying and extracting fracture characteristics have been proven to be inefficient and prone to subjective interpretation.Moreover,conventional image processing algorithms and classical deep learning models often encounter difficulties in accurately identifying fracture areas,resulting in unclear contours.This study proposes an intelligent method for detecting internal fractures in mine rock masses to address these challenges.The proposed approach captures a nodal fracture map within the targeted blast area and integrates channel and spatial attention mechanisms into the ResUnet(RU)model.The channel attention mechanism dynamically recalibrates the importance of each feature channel,and the spatial attention mechanism enhances feature representation in key areas while minimizing background noise,thus improving segmentation accuracy.A dynamic serpentine convolution module is also introduced that adaptively adjusts the shape and orientation of the convolution kernel based on the local structure of the input feature map.Furthermore,this method enables the automatic extraction and quantification of borehole nodal fracture information by fitting sinusoidal curves to the boundaries of the fracture contours using the least squares method.In comparison to other advanced deep learning models,our enhanced RU demonstrates superior performance across evaluation metrics,including accuracy,pixel accuracy(PA),and intersection over union(IoU).Unlike traditional manual extraction methods,our intelligent detection approach provides considerable time and cost savings,with an average error rate of approximately 4%.This approach has the potential to greatly improve the efficiency of geological surveys of borehole fractures.展开更多
This study presents a drone-based aerial imaging method for automated rice seedling detection and counting in paddy fields.Utilizing a drone equipped with a high-resolution camera,images are captured 14 days postsowin...This study presents a drone-based aerial imaging method for automated rice seedling detection and counting in paddy fields.Utilizing a drone equipped with a high-resolution camera,images are captured 14 days postsowing at a consistent altitude of six meters,employing autonomous flight for uniform data acquisition.The approach effectively addresses the distinct growth patterns of both single and clustered rice seedlings at this early stage.The methodology follows a two-step process:first,the GoogleNet deep learning network identifies the location and center points of rice plants.Then,the U-Net deep learning network performs classification and counting of individual plants and clusters.This combination of deep learning models achieved a 90%accuracy rate in classifying and counting both single and clustered seedlings.To validate the method’s effectiveness,results were compared against traditional manual counting conducted by agricultural experts.The comparison revealed minimal discrepancies,with a variance of only 2–4 clumps per square meter,confirming the reliability of the proposed method.This automated approach offers significant benefits by providing an efficient,accurate,and scalable solution for monitoring seedling growth.It enables farmers to optimize fertilizer and pesticide application,improve resource allocation,and enhance overall crop management,ultimately contributing to increased agricultural productivity.展开更多
Closed thoracic drainage can be performed using a steel-needle-guided chest tube to treat pleural effusion or pneumothorax in clinics.However,the puncture procedure during surgery is invisible,increasing the risk of s...Closed thoracic drainage can be performed using a steel-needle-guided chest tube to treat pleural effusion or pneumothorax in clinics.However,the puncture procedure during surgery is invisible,increasing the risk of surgical failure.Therefore,it is necessary to design a visualization system for closed thoracic drainage.Augmented reality(AR)technology can assist in visualizing the internal anatomical structure and determining the insertion point on the body surface.The structure of the currently used steel-needle-guided chest tube was modified by integrating it with an ultrafine diameter camera to provide real-time visualization of the puncture process.After simulation experiments,the overall registration error of the AR method was measured to be within(3.59±0.53)mm,indicating its potential for clinical application.The ultrafine diameter camera module and improved steel-needle-guided chest tube can timely reflect the position of the needle tip in the human body.A comparative experiment showed that video guidance could improve the safety of the puncture process compared to the traditional method.Finally,a qualitative evaluation of the usability of the system was conducted through a questionnaire.This system facilitates the visualization of closed thoracic drainage puncture procedure and pro-vides an implementation scheme to enhance the accuracy and safety of the operative step,which is conducive to reducing the learning curve and improving the proficiency of the doctors.展开更多
As a major principle underlying the Communist Party of China's(CPC)governance in the new era and a core piece of its holistic approach to national security,ensuring both development and security emphasizes compreh...As a major principle underlying the Communist Party of China's(CPC)governance in the new era and a core piece of its holistic approach to national security,ensuring both development and security emphasizes comprehensive governance from a long-term perspective and influences the world with its global vision.It keeps pace with the times by prioritizing innovative areas and is of great theoretical and practical significance.On the new journey ahead,we must firmly ensure both development and security.More importantly,we must ensure both high-quality development and high-level security,safeguarding the former through the latter.This is an urgent requirement we face in today's world,which has entered a period of turbulence and transformation characterized by increasing complexity.Confronted with the formidable tasks of promoting reform and development while maintaining stability at home and the grave challenges brought about by international turbulence and changes,we must earnestly implement the guiding principles of the 20th CPC National Congress and the third plenary session of the 20th Party Central Committee.We should ensure secure and sustainable development,accelerate efforts to modernize China's national security system and capacity,foster high-level security,and improve the mechanisms for preserving national security in foreign-related affairs.In short,we should strive to achieve a positive interplay between high-quality development and high-level security,so as to effectively safeguard Chinese modernization.展开更多
The estimation of orientation parameters and correction of lens distortion are crucial problems in the field of Unmanned Aerial Vehicles(UAVs)photogrammetry.In recent years,the utilization of UAVs for aerial photogram...The estimation of orientation parameters and correction of lens distortion are crucial problems in the field of Unmanned Aerial Vehicles(UAVs)photogrammetry.In recent years,the utilization of UAVs for aerial photogrammetry has witnessed a surge in popularity.Typically,UAVs are equipped with low-cost non-metric cameras and a Position and Orientation System(POS).Unfortunately,the Interior Orientation Parameters(IOPs)of the non-metric cameras are not fixed.Whether the lens distortions are large or small,they effect the image coordinates accordingly.Additionally,Inertial Measurement Units(IMUs)often have observation errors.To address these challenges and improve parameter estimation for UAVs Light Detection and Ranging(LiDAR)and photogrammetry,this paper analyzes the accuracy of POS observations obtained from Global Navigation Satellite System Real Time Kinematic(GNSS-RTK)and IMU data.A method that incorporates additional known conditions for parameter estimation,a series of algorithms to simultaneously solve for IOPs,Exterior Orientation Parameters(EOPs),and camera lens distortion correction parameters are proposed.Extensive experiments demonstrate that the coordinates measured by GNSS-RTK can be directly used as linear EOPs;however,angular EOP measurements from IMUs exhibit relatively large errors compared to adjustment results and require correction during the adjustment process.The IOPs of non-metric cameras vary slightly between images but need to be treated as unknown parameters in high precision applications.Furthermore,it is found that the Ebner systematic error model is sensitive to the choice of the magnification parameter of the photographic baseline length in images,it should be set as less than or equal to one third of the photographic baseline to ensure stable solutions.展开更多
During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and...During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and polarization of which depends on the Sun’s location.If a cloud contains spatially oriented ice particles,then it becomes anisotropic,that is,the coefficients of directional light scattering of such a cloud depend on the Sun’s zenith and azimuth angles.In this work,the possibility of using the effect of anisotropic scattering of solar radiation on the predictive ability of machine learning algorithms in solving the problem of predicting the HLC backscattering phase matrix(BSPM)was evaluated.The hypothesis that solar radiation scattered on HLCs has no effect on the BSPM elements of such clouds determined with a polarization lidar was tested.The operation of two algorithms for predicting the BSPM elements is evaluated.To train the first one,meteorological data were used as input parameters;for the second algorithm,the azi-muthal and zenith angles of the Sun’s position were added to the meteorological parameters.It is shown that there is no significant improvement in the predictive ability of the algorithm.展开更多
Deep metal mines are often mined using the high-level pillars with subsequent cementation backfilling(HLSCB)mining method.At the design stage,it is therefore important to have a reasonable method for determining the s...Deep metal mines are often mined using the high-level pillars with subsequent cementation backfilling(HLSCB)mining method.At the design stage,it is therefore important to have a reasonable method for determining the shear strength of the high-level pillars(i.e.cohesion and internal friction angle)when they are supported by cemented backfilling.In this study,a formula was derived for the upper limit of the confining pressure σ3max on a high-level pillar supported by cemented backfilling in a deep metal mine.A new method of estimating the shear strength of such pillars was then proposed based on the Hoek eBrown failure criterion.Our analysis indicates that the horizontal stress σhh acting on the cemented backfill pillar can be simplified by expressing it as a constant value.A reasonable and effective value for σ3max can then be determined.The value of s3max predicted using the proposed method is generally less than 3 MPa.Within this range,the shear strength of the high-level pillar is accurately calculated using the equivalent MohreCoulomb theory.The proposed method can effectively avoid the calculation of inaccurate shear strength values for the high-level pillars when the original HoekeBrown criterion is used in the presence of large confining pressures,i.e.the situation in which the cohesion value is too large and the friction angle is too small can effectively be avoided.The proposed method is applied to a deep metal mine in China that is being excavated using the HLSCB method.The shear strength parameters of the high-level pillars obtained using the proposed method were input in the numerical simulations.The numerical results show that the recommended level heights and sizes of the high-level pillars and rooms in the mine are rational.展开更多
An ultrafast framing camera with a pulse-dilation device,a microchannel plate(MCP)imager,and an electronic imaging system were reported.The camera achieved a temporal resolution of 10 ps by using a pulse-dilation devi...An ultrafast framing camera with a pulse-dilation device,a microchannel plate(MCP)imager,and an electronic imaging system were reported.The camera achieved a temporal resolution of 10 ps by using a pulse-dilation device and gated MCP imager,and a spatial resolution of 100μm by using an electronic imaging system comprising combined magnetic lenses.The spatial resolution characteristics of the camera were studied both theoretically and experimentally.The results showed that the camera with combined magnetic lenses reduced the field curvature and acquired a larger working area.A working area with a diameter of 53 mm was created by applying four magnetic lenses to the camera.Furthermore,the camera was used to detect the X-rays produced by the laser-targeting device.The diagnostic results indicated that the width of the X-ray pulse was approximately 18 ps.展开更多
In visual measurement,high-precision camera calibration often employs circular targets.To address issues in mainstream methods,such as the eccentricity error of the circle from using the circle’s center for calibrati...In visual measurement,high-precision camera calibration often employs circular targets.To address issues in mainstream methods,such as the eccentricity error of the circle from using the circle’s center for calibration,overfitting or local minimum from fullparameter optimization,and calibration errors due to neglecting the center of distortion,a stepwise camera calibration method incorporating compensation for eccentricity error was proposed to enhance monocular camera calibration precision.Initially,the multiimage distortion correction method calculated the common center of distortion and coefficients,improving precision,stability,and efficiency compared to single-image distortion correction methods.Subsequently,the projection point of the circle’s center was compared with the center of the contour’s projection to iteratively correct the eccentricity error,leading to more precise and stable calibration.Finally,nonlinear optimization refined the calibration parameters to minimize reprojection error and boosts precision.These processes achieved stepwise camera calibration,which enhanced robustness.In addition,the module comparison experiment showed that both the eccentricity error compensation and the camera parameter optimization could improve the calibration precision,but the latter had a greater impact.The combined use of the two methods further improved the precision and stability.Simulations and experiments confirmed that the proposed method achieved high precision,stability,and robustness,suitable for high-precision visual measurements.展开更多
A novel single color camera trichromatic mask 3D-PIV technique suitable for measurement of complex flow fields in confined spaces is presented in this paper.By using a trichromatic mask to modulate the imaging optical...A novel single color camera trichromatic mask 3D-PIV technique suitable for measurement of complex flow fields in confined spaces is presented in this paper.By using a trichromatic mask to modulate the imaging optical path of a color camera,the RGB(Red,Green,and Blue)channels of the photosensitive chip were used to record full-frame full-resolution images of tracer particles from three viewing angles.The MLOS-SMART particle reconstruction algorithm was used to obtain three-dimensional particle distribution matrix from particle trichromatic mask images.The impact of parameters such as the inter-hole spacing and hole diameter of the trichromatic mask on the quality of particle reconstruction was analyzed.Through numerical simulation experiments on artificially synthesized three-dimensional flow fields of Gaussian vortex rings,the practicality of this technique in measuring three-dimensional transient velocity fields and the accuracy of velocity measurements were examined.The accuracy and feasibility of the technique are illustrated based on experimental measurements of a zero-net-mass-flux jet.展开更多
基金financial supports from National Natural Science Foundation of China(Grant Nos.U23A20368 and 62175006)Academic Excellence Foundation of BUAA for PhD Students.
文摘Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution sparse compound-eye camera(CEC)based on dual-end collaborative optimization is proposed,which provides a cost-effective way to break through the trade-off among the field of view,resolution,and imaging speed.In the optical end,a sparse CEC based on liquid lenses is designed,which can realize large-field-of-view imaging in real time,and fast zooming within 5 ms.In the computational end,a disturbed degradation model driven super-resolution network(DDMDSR-Net)is proposed to deal with complex image degradation issues in actual imaging situations,achieving high-robustness and high-fidelity resolution enhancement.Based on the proposed dual-end collaborative optimization framework,the angular resolution of the CEC can be enhanced from 71.6"to 26.0",which provides a solution to realize high-resolution imaging for array camera dispensing with high optical hardware complexity and data transmission bandwidth.Experiments verify the advantages of the CEC based on dual-end collaborative optimization in high-fidelity reconstruction of real scene images,kilometer-level long-distance detection,and dynamic imaging and precise recognition of targets of interest.
基金Supported by the Fundamental Research Funds for the Central Universities(2024300443)the Natural Science Foundation of Jiangsu Province(BK20241224).
文摘This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.
基金Education and Teaching Research Project of Beijing University of Technology(ER2024KCB08)。
文摘With the rapid development of artificial intelligence technology,AIGC(Artificial Intelligence-Generated Content)has triggered profound changes in the field of high-level language programming courses.This paper deeply explored the application principles,advantages,and limitations of AIGC in intelligent code generation,analyzed the new mode of human-computer collaboration in high-level language programming courses driven by AIGC,discussed the impact of human-computer collaboration on programming efficiency and code quality through practical case studies,and looks forward to future development trends.This research aims to provide theoretical and practical guidance for high-level language programming courses and promote innovative development of high-level language programming courses under the human-computer collaboration paradigm.
基金supported by the National Natural Science Foundation of China(Nos.U2067212,22176191)the National Science Fund for Distinguished Young Scholars(No.21925603)。
文摘In the current era marked by energy shortages,the advancement of nuclear energy stands as an inevitable progression.The reprocessing of spent nuclear fuel plays a crucial role in determining the sustainability of nuclear energy as a viable energy source.Among these processes,the separation and recovery of Pu(Ⅳ)from high-level liquid waste(HLLW)hold paramount significance in terms of safety and strategic implications.Herein,this work focused on the synthesis of two acid-and radiation-resistant pyridine-based sp^(2)c-COFs(COF-IHEP3 and COF-IHEP4),followed by the creation of two pyridine-based ionized sp^(2)c-COFs named COF-IHEP3-CH_(3)NO_(3)and COF-IHEP4-CH3NO3through post-modification.These materials have potential anion exchange capacity for the selective separation of Pu(Ⅳ)in highly acidic conditions.Notably,in 8 mol/L nitric acid solution,COF-IHEP3-CH3NO3demonstrated the capability to eliminate plutonium within 20 min in 98%removal efficiency with a Kdvalue of 2450 m L/g.Experimental and theoretical analysis suggest that the ionized sp^(2)c-COFs exhibit exceptional stability,selectivity,and prevention of secondary contamination towards Pu(Ⅳ)in the presence of multiple ions environments.In short,this work provides an appropriate anion exchange strategy to design ionic sp^(2)c-COFs as a promising platform for Pu(Ⅳ)recovery from HLLW.
基金Education and Teaching Research Project of Beijing University of Technology(ER2024KCB08)。
文摘With the widespread application of large language models(LLMs)in natural language processing and code generation,traditional High-Level Language Programming courses are facing unprecedented challenges and opportunities.As a core programming language for computer science majors,C language remains irreplaceable due to its foundational nature and engineering adaptability.This paper,based on the rapid development of large model technologies,proposes a systematic reform design for C language teaching,focusing on teaching objectives,content structure,teaching methods,and evaluation systems.The article suggests a teaching framework centered on“human-computer collaborative programming,”integrating prompt training,AI-assisted debugging,and code generation analysis,aiming to enhance students’problem modeling ability,programming expression skills,and AI collaboration literacy.
基金supported by the Hunan Provin〓〓cial Natural Science Foundation for Excellent Young Scholars(Grant No.2023JJ20045)the National Natural Science Foundation of China(Grant No.12372189)。
文摘Photomechanics is a crucial branch of solid mechanics.The localization of point targets constitutes a fundamental problem in optical experimental mechanics,with extensive applications in various missions of unmanned aerial vehicles.Localizing moving targets is crucial for analyzing their motion characteristics and dynamic properties.Reconstructing the trajectories of points from asynchronous cameras is a significant challenge.It encompasses two coupled sub-problems:Trajectory reconstruction and camera synchronization.Present methods typically address only one of these sub-problems individually.This paper proposes a 3D trajectory reconstruction method for point targets based on asynchronous cameras,simultaneously solving both sub-problems.Firstly,we extend the trajectory intersection method to asynchronous cameras to resolve the limitation of traditional triangulation that requires camera synchronization.Secondly,we develop models for camera temporal information and target motion,based on imaging mechanisms and target dynamics characteristics.The parameters are optimized simultaneously to achieve trajectory reconstruction without accurate time parameters.Thirdly,we optimize the camera rotations alongside the camera time information and target motion parameters,using tighter and more continuous constraints on moving points.The reconstruction accuracy is significantly improved,especially when the camera rotations are inaccurate.Finally,the simulated and real-world experimental results demonstrate the feasibility and accuracy of the proposed method.The real-world results indicate that the proposed algorithm achieved a localization error of 112.95 m at an observation distance range of 15-20 km.
基金supported by Natural Science Foundation of Jilin Province(20210101468JC)Chinese Academy of Sciences and Local Government Cooperation Project(2023SYHZ0027,23SH04)National Natural Science Foundation of China(12273063&12203078)。
文摘Observatories typically deploy all-sky cameras for monitoring cloud cover and weather conditions.However,many of these cameras lack scientific-grade sensors,r.esulting in limited photometric precision,which makes calculating the sky area visibility distribution via extinction measurement challenging.To address this issue,we propose the Photometry-Free Sky Area Visibility Estimation(PFSAVE)method.This method uses the standard magnitude of the faintest star observed within a given sky area to estimate visibility.By employing a pertransformation refitting optimization strategy,we achieve a high-precision coordinate transformation model with an accuracy of 0.42 pixels.Using the results of HEALPix segmentation is also introduced to achieve high spatial resolution.Comprehensive analysis based on real allsky images demonstrates that our method exhibits higher accuracy than the extinction-based method.Our method supports both manual and robotic dynamic scheduling,especially under partially cloudy conditions.
基金supported by the National Natural Science Foundation of China(No.52474172).
文摘It is important to understand the development of joints and fractures in rock masses to ensure drilling stability and blasting effectiveness.Traditional manual observation techniques for identifying and extracting fracture characteristics have been proven to be inefficient and prone to subjective interpretation.Moreover,conventional image processing algorithms and classical deep learning models often encounter difficulties in accurately identifying fracture areas,resulting in unclear contours.This study proposes an intelligent method for detecting internal fractures in mine rock masses to address these challenges.The proposed approach captures a nodal fracture map within the targeted blast area and integrates channel and spatial attention mechanisms into the ResUnet(RU)model.The channel attention mechanism dynamically recalibrates the importance of each feature channel,and the spatial attention mechanism enhances feature representation in key areas while minimizing background noise,thus improving segmentation accuracy.A dynamic serpentine convolution module is also introduced that adaptively adjusts the shape and orientation of the convolution kernel based on the local structure of the input feature map.Furthermore,this method enables the automatic extraction and quantification of borehole nodal fracture information by fitting sinusoidal curves to the boundaries of the fracture contours using the least squares method.In comparison to other advanced deep learning models,our enhanced RU demonstrates superior performance across evaluation metrics,including accuracy,pixel accuracy(PA),and intersection over union(IoU).Unlike traditional manual extraction methods,our intelligent detection approach provides considerable time and cost savings,with an average error rate of approximately 4%.This approach has the potential to greatly improve the efficiency of geological surveys of borehole fractures.
基金funded by the Ministry of Education and Training Project(code number:B2023-TCT-08).
文摘This study presents a drone-based aerial imaging method for automated rice seedling detection and counting in paddy fields.Utilizing a drone equipped with a high-resolution camera,images are captured 14 days postsowing at a consistent altitude of six meters,employing autonomous flight for uniform data acquisition.The approach effectively addresses the distinct growth patterns of both single and clustered rice seedlings at this early stage.The methodology follows a two-step process:first,the GoogleNet deep learning network identifies the location and center points of rice plants.Then,the U-Net deep learning network performs classification and counting of individual plants and clusters.This combination of deep learning models achieved a 90%accuracy rate in classifying and counting both single and clustered seedlings.To validate the method’s effectiveness,results were compared against traditional manual counting conducted by agricultural experts.The comparison revealed minimal discrepancies,with a variance of only 2–4 clumps per square meter,confirming the reliability of the proposed method.This automated approach offers significant benefits by providing an efficient,accurate,and scalable solution for monitoring seedling growth.It enables farmers to optimize fertilizer and pesticide application,improve resource allocation,and enhance overall crop management,ultimately contributing to increased agricultural productivity.
基金the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant(No.20172005)。
文摘Closed thoracic drainage can be performed using a steel-needle-guided chest tube to treat pleural effusion or pneumothorax in clinics.However,the puncture procedure during surgery is invisible,increasing the risk of surgical failure.Therefore,it is necessary to design a visualization system for closed thoracic drainage.Augmented reality(AR)technology can assist in visualizing the internal anatomical structure and determining the insertion point on the body surface.The structure of the currently used steel-needle-guided chest tube was modified by integrating it with an ultrafine diameter camera to provide real-time visualization of the puncture process.After simulation experiments,the overall registration error of the AR method was measured to be within(3.59±0.53)mm,indicating its potential for clinical application.The ultrafine diameter camera module and improved steel-needle-guided chest tube can timely reflect the position of the needle tip in the human body.A comparative experiment showed that video guidance could improve the safety of the puncture process compared to the traditional method.Finally,a qualitative evaluation of the usability of the system was conducted through a questionnaire.This system facilitates the visualization of closed thoracic drainage puncture procedure and pro-vides an implementation scheme to enhance the accuracy and safety of the operative step,which is conducive to reducing the learning curve and improving the proficiency of the doctors.
文摘As a major principle underlying the Communist Party of China's(CPC)governance in the new era and a core piece of its holistic approach to national security,ensuring both development and security emphasizes comprehensive governance from a long-term perspective and influences the world with its global vision.It keeps pace with the times by prioritizing innovative areas and is of great theoretical and practical significance.On the new journey ahead,we must firmly ensure both development and security.More importantly,we must ensure both high-quality development and high-level security,safeguarding the former through the latter.This is an urgent requirement we face in today's world,which has entered a period of turbulence and transformation characterized by increasing complexity.Confronted with the formidable tasks of promoting reform and development while maintaining stability at home and the grave challenges brought about by international turbulence and changes,we must earnestly implement the guiding principles of the 20th CPC National Congress and the third plenary session of the 20th Party Central Committee.We should ensure secure and sustainable development,accelerate efforts to modernize China's national security system and capacity,foster high-level security,and improve the mechanisms for preserving national security in foreign-related affairs.In short,we should strive to achieve a positive interplay between high-quality development and high-level security,so as to effectively safeguard Chinese modernization.
基金Natural Science Foundation of Hunan Province,China(No.2024JJ8335)Open Topic of Hunan Geospatial Information Engineering and Technology Research Center,China(No.HNGIET2023004).
文摘The estimation of orientation parameters and correction of lens distortion are crucial problems in the field of Unmanned Aerial Vehicles(UAVs)photogrammetry.In recent years,the utilization of UAVs for aerial photogrammetry has witnessed a surge in popularity.Typically,UAVs are equipped with low-cost non-metric cameras and a Position and Orientation System(POS).Unfortunately,the Interior Orientation Parameters(IOPs)of the non-metric cameras are not fixed.Whether the lens distortions are large or small,they effect the image coordinates accordingly.Additionally,Inertial Measurement Units(IMUs)often have observation errors.To address these challenges and improve parameter estimation for UAVs Light Detection and Ranging(LiDAR)and photogrammetry,this paper analyzes the accuracy of POS observations obtained from Global Navigation Satellite System Real Time Kinematic(GNSS-RTK)and IMU data.A method that incorporates additional known conditions for parameter estimation,a series of algorithms to simultaneously solve for IOPs,Exterior Orientation Parameters(EOPs),and camera lens distortion correction parameters are proposed.Extensive experiments demonstrate that the coordinates measured by GNSS-RTK can be directly used as linear EOPs;however,angular EOP measurements from IMUs exhibit relatively large errors compared to adjustment results and require correction during the adjustment process.The IOPs of non-metric cameras vary slightly between images but need to be treated as unknown parameters in high precision applications.Furthermore,it is found that the Ebner systematic error model is sensitive to the choice of the magnification parameter of the photographic baseline length in images,it should be set as less than or equal to one third of the photographic baseline to ensure stable solutions.
基金supported by the Government of the Russian Federation grant number 075-15-2025-009 of 28 February 2025 and by the Russian Science Foundation,Grant No.24-72-10127.
文摘During daylight laser polarization sensing of high-level clouds(HLCs),the lidar receiving system generates a signal caused by not only backscattered laser radiation,but also scattered solar radiation,the intensity and polarization of which depends on the Sun’s location.If a cloud contains spatially oriented ice particles,then it becomes anisotropic,that is,the coefficients of directional light scattering of such a cloud depend on the Sun’s zenith and azimuth angles.In this work,the possibility of using the effect of anisotropic scattering of solar radiation on the predictive ability of machine learning algorithms in solving the problem of predicting the HLC backscattering phase matrix(BSPM)was evaluated.The hypothesis that solar radiation scattered on HLCs has no effect on the BSPM elements of such clouds determined with a polarization lidar was tested.The operation of two algorithms for predicting the BSPM elements is evaluated.To train the first one,meteorological data were used as input parameters;for the second algorithm,the azi-muthal and zenith angles of the Sun’s position were added to the meteorological parameters.It is shown that there is no significant improvement in the predictive ability of the algorithm.
基金Financial support for this work was provided by the General Program and Youth Fund Program of the National Natural Science Foundation of China(Grant Nos.42377175 and 42002292).
文摘Deep metal mines are often mined using the high-level pillars with subsequent cementation backfilling(HLSCB)mining method.At the design stage,it is therefore important to have a reasonable method for determining the shear strength of the high-level pillars(i.e.cohesion and internal friction angle)when they are supported by cemented backfilling.In this study,a formula was derived for the upper limit of the confining pressure σ3max on a high-level pillar supported by cemented backfilling in a deep metal mine.A new method of estimating the shear strength of such pillars was then proposed based on the Hoek eBrown failure criterion.Our analysis indicates that the horizontal stress σhh acting on the cemented backfill pillar can be simplified by expressing it as a constant value.A reasonable and effective value for σ3max can then be determined.The value of s3max predicted using the proposed method is generally less than 3 MPa.Within this range,the shear strength of the high-level pillar is accurately calculated using the equivalent MohreCoulomb theory.The proposed method can effectively avoid the calculation of inaccurate shear strength values for the high-level pillars when the original HoekeBrown criterion is used in the presence of large confining pressures,i.e.the situation in which the cohesion value is too large and the friction angle is too small can effectively be avoided.The proposed method is applied to a deep metal mine in China that is being excavated using the HLSCB method.The shear strength parameters of the high-level pillars obtained using the proposed method were input in the numerical simulations.The numerical results show that the recommended level heights and sizes of the high-level pillars and rooms in the mine are rational.
基金National Natural Science Foundation of China(NSFC)(No.11775147)Guangdong Basic and Applied Basic Research Foundation(Nos.2019A1515110130 and 2024A1515011832)+1 种基金Shenzhen Key Laboratory of Photonics and Biophotonics(ZDSYS20210623092006020)Shenzhen Science and Technology Program(Nos.JCYJ20210324095007020,JCYJ20200109105201936 and JCYJ20230808105019039).
文摘An ultrafast framing camera with a pulse-dilation device,a microchannel plate(MCP)imager,and an electronic imaging system were reported.The camera achieved a temporal resolution of 10 ps by using a pulse-dilation device and gated MCP imager,and a spatial resolution of 100μm by using an electronic imaging system comprising combined magnetic lenses.The spatial resolution characteristics of the camera were studied both theoretically and experimentally.The results showed that the camera with combined magnetic lenses reduced the field curvature and acquired a larger working area.A working area with a diameter of 53 mm was created by applying four magnetic lenses to the camera.Furthermore,the camera was used to detect the X-rays produced by the laser-targeting device.The diagnostic results indicated that the width of the X-ray pulse was approximately 18 ps.
文摘In visual measurement,high-precision camera calibration often employs circular targets.To address issues in mainstream methods,such as the eccentricity error of the circle from using the circle’s center for calibration,overfitting or local minimum from fullparameter optimization,and calibration errors due to neglecting the center of distortion,a stepwise camera calibration method incorporating compensation for eccentricity error was proposed to enhance monocular camera calibration precision.Initially,the multiimage distortion correction method calculated the common center of distortion and coefficients,improving precision,stability,and efficiency compared to single-image distortion correction methods.Subsequently,the projection point of the circle’s center was compared with the center of the contour’s projection to iteratively correct the eccentricity error,leading to more precise and stable calibration.Finally,nonlinear optimization refined the calibration parameters to minimize reprojection error and boosts precision.These processes achieved stepwise camera calibration,which enhanced robustness.In addition,the module comparison experiment showed that both the eccentricity error compensation and the camera parameter optimization could improve the calibration precision,but the latter had a greater impact.The combined use of the two methods further improved the precision and stability.Simulations and experiments confirmed that the proposed method achieved high precision,stability,and robustness,suitable for high-precision visual measurements.
基金co-supported by the National Natural Science Foundation of China(Nos.12102284,12172242,12332017)the Shanxi Province Science Foundation for Youths,China(No.20210302124262)the Chunhui Project Foundation of the Education Department of China(No.202200257)。
文摘A novel single color camera trichromatic mask 3D-PIV technique suitable for measurement of complex flow fields in confined spaces is presented in this paper.By using a trichromatic mask to modulate the imaging optical path of a color camera,the RGB(Red,Green,and Blue)channels of the photosensitive chip were used to record full-frame full-resolution images of tracer particles from three viewing angles.The MLOS-SMART particle reconstruction algorithm was used to obtain three-dimensional particle distribution matrix from particle trichromatic mask images.The impact of parameters such as the inter-hole spacing and hole diameter of the trichromatic mask on the quality of particle reconstruction was analyzed.Through numerical simulation experiments on artificially synthesized three-dimensional flow fields of Gaussian vortex rings,the practicality of this technique in measuring three-dimensional transient velocity fields and the accuracy of velocity measurements were examined.The accuracy and feasibility of the technique are illustrated based on experimental measurements of a zero-net-mass-flux jet.
