Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results ca...Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.展开更多
Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materia...Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.展开更多
This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by...This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by normal tensor voting theory,(2)co ntraction of trace feature points,(3)connection of trace feature points,(4)linearization of trace segments,and(5)connection of trace segments.A sensitivity analysis was then conducted to identify the optimal parameters of the proposed method.Three field cases,a natural rock mass outcrop and two excavated rock tunnel surfaces,were analyzed using the proposed method to evaluate its validity and efficiency.The results show that the proposed method is more efficient and accurate than the traditional trace mapping method,and the efficiency enhancement is more robust as the number of feature points increases.展开更多
The spatial distribution of discontinuities and the size of rock blocks are the key indicators for rock mass quality evaluation and rockfall risk assessment.Traditional manual measurement is often dangerous or unreach...The spatial distribution of discontinuities and the size of rock blocks are the key indicators for rock mass quality evaluation and rockfall risk assessment.Traditional manual measurement is often dangerous or unreachable at some high-steep rock slopes.In contrast,unmanned aerial vehicle(UAV)photogrammetry is not limited by terrain conditions,and can efficiently collect high-precision three-dimensional(3D)point clouds of rock masses through all-round and multiangle photography for rock mass characterization.In this paper,a new method based on a 3D point cloud is proposed for discontinuity identification and refined rock block modeling.The method is based on four steps:(1)Establish a point cloud spatial topology,and calculate the point cloud normal vector and average point spacing based on several machine learning algorithms;(2)Extract discontinuities using the density-based spatial clustering of applications with noise(DBSCAN)algorithm and fit the discontinuity plane by combining principal component analysis(PCA)with the natural breaks(NB)method;(3)Propose a method of inserting points in the line segment to generate an embedded discontinuity point cloud;and(4)Adopt a Poisson reconstruction method for refined rock block modeling.The proposed method was applied to an outcrop of an ultrahigh steep rock slope and compared with the results of previous studies and manual surveys.The results show that the method can eliminate the influence of discontinuity undulations on the orientation measurement and describe the local concave-convex characteristics on the modeling of rock blocks.The calculation results are accurate and reliable,which can meet the practical requirements of engineering.展开更多
An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, clo...An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.展开更多
Using the spatial coordinates of detection stations and the time of arrival of lightning wave, the observation equations can be expressed. For the large lightning detection network, the least square method is used to ...Using the spatial coordinates of detection stations and the time of arrival of lightning wave, the observation equations can be expressed. For the large lightning detection network, the least square method is used to process the adjustment of observation data to find the most probable value of lightning position, and the result is assessed by the mean error and dilution of precision. Lightning location precision is affected by figure factor. The conclusion can be used in the design of location network, data processing, and data analysis.展开更多
In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for ...In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.展开更多
To objectively obtain the three-dimensional coordinates of the projectile fuze proximity explosion when projectile intersects the head of missile target, we propose a dynamic seven photoelectric detection screen test ...To objectively obtain the three-dimensional coordinates of the projectile fuze proximity explosion when projectile intersects the head of missile target, we propose a dynamic seven photoelectric detection screen test method, which is made up of six plane detection screens and a flash photoelectric dynamic detection screen. The three-dimensional coordinates calculation model of the projectile proximity explosion position based on seven plane detection screens with dynamic characteristics is established.According to the relation of the dynamic seven photoelectric detection screen planes and the time values,the analytical function of the projectile proximity explosion position parameters under non-linear motion is derived. The projectile signal filtering method based on discrete wavelet transform is explored in this work. Additionally, the projectile signal recognition algorithm using an improved particle swarm is proposed. Based on the characteristics of the time duration and the signal peak error for the projectile passing through the detection screen, the signals attribution of the same projectile passing through six detection screens are analyzed for obtaining precise time values of the same projectile passing through the detection screens. On the basis of the projectile fuze proximity explosion test, the linear motion model and the proposed non-linear motion model are used to calculate and compare the same group of projectiles proximity explosion position parameters. The comparison of test results verifies that the proposed test method and calculation model in this work accurately obtain the actual projectile proximity explosion position parameters.展开更多
Flash Crowd attacks are a form of Distributed Denial of Service(DDoS)attack that is becoming increasingly difficult to detect due to its ability to imitate normal user behavior in Cloud Computing(CC).Botnets are often...Flash Crowd attacks are a form of Distributed Denial of Service(DDoS)attack that is becoming increasingly difficult to detect due to its ability to imitate normal user behavior in Cloud Computing(CC).Botnets are often used by attackers to perform a wide range of DDoS attacks.With advancements in technology,bots are now able to simulate DDoS attacks as flash crowd events,making them difficult to detect.When it comes to application layer DDoS attacks,the Flash Crowd attack that occurs during a Flash Event is viewed as the most intricate issue.This is mainly because it can imitate typical user behavior,leading to a substantial influx of requests that can overwhelm the server by consuming either its network bandwidth or resources.Therefore,identifying these types of attacks on web servers has become crucial,particularly in the CC.In this article,an efficient intrusion detection method is proposed based on White Shark Optimizer and ensemble classifier(Convolutional Neural Network(CNN)and LighGBM).Experiments were conducted using a CICIDS 2017 dataset to evaluate the performance of the proposed method in real-life situations.The proposed IDS achieved superior results,with 95.84%accuracy,96.15%precision,95.54%recall,and 95.84%F1 measure.Flash crowd attacks are challenging to detect,but the proposed IDS has proven its effectiveness in identifying such attacks in CC and holds potential for future improvement.展开更多
Accurate and rapid wheat morphology reconstruction and trait collection are essential for selecting varieties,scientific cultivation,and precise management.A single perspective is limited by environmental obstructions...Accurate and rapid wheat morphology reconstruction and trait collection are essential for selecting varieties,scientific cultivation,and precise management.A single perspective is limited by environmental obstructions,hindering the collection of high-throughput phenotype data for wheat plants.Therefore,a rapid reconstruction method of multi-view threedimensional point cloud is proposed to realize the high-throughput and accurate identification of wheat phenotype.Firstly,taking wheat at the tillering stage as the experimental object,a multi-view acquisition system based on a RealSense sensor was constructed,and the point cloud data of wheat were obtained from 16 views.Secondly,a joint photometric and geometric objective was optimized,and space location was registered by colored Point Cloud Registration(colored)and Iterative Closest Point(ICP)algorithms.Furthermore,the Multiple View Stereo(MVS)algorithm was used to combine the depth image,RGB image,and spatial position obtained by coarse registration to enable the fine registration of multi-viewpoint clouds.Compared with the traditional Structure From Motion(SFM)-MVS algorithm,our proposed method is much faster,with an average reconstruction time of 33.82 s.Moreover,the wheat plant height,leaf length,leaf width,leaf area,and leaf angle of wheat were calculated based on the three-dimensional point cloud of the wheat plant.The experimental results showed that the determination coefficients of the method are 0.996,0.958,0.956,0.984,and 0.849,respectively.Finally,phenotypic information such as compact degree,convex hull volume,and average leaf area of different wheat varieties was analyzed and identified,proving that the method could capture the phenotypic differences between varieties and individuals.The proposed method provides a rapid approach to quantify wheat phenotypic traits,aiding breeding,scientific cultivation,and environmental management.展开更多
Fusing three-dimensional(3D)and multispectral(MS)imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge.Acquiring high-quality 3D MS point clouds(3DM...Fusing three-dimensional(3D)and multispectral(MS)imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge.Acquiring high-quality 3D MS point clouds(3DMPCs)of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with a complex canopy structure.Here,we present a novel 3D spatial–spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view planning for adaptive data acquisition and neural reference field(NeREF)for radiometric calibration.This approach was used to acquire 3DMPCs of perilla,tomato,and rapeseed plants with diverse plant architecture and leaf morphological features evaluated by the accuracy of chlorophyll content and equivalent water thickness(EWT)estimation.The results showed that the completeness of plant point clouds collected by this approach was improved by an average of 23.6%compared with the fixed viewpoints alone.The NeREF-based radiometric calibration with the hemispherical reference outperformed the conventional calibration method by reducing the root mean square error(RMSE)of 58.93%for extracted reflectance spectra.The RMSE for chlorophyll content and EWT predictions decreased by 21.25%and 14.13%using partial least squares regression with the generated 3DMPCs.Collectively,our study provides an effective and efficient way to collect high-quality 3DMPCs of plants under natural light conditions,which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits,and thus will facilitate plant biology and genetic studies as well as crop breeding.展开更多
The electrical characteristics of thunderstorms in three different altitude regions of the Chinese inland plateau have been analyzed in this paper. The results show, according to the polarity of the surface electric ...The electrical characteristics of thunderstorms in three different altitude regions of the Chinese inland plateau have been analyzed in this paper. The results show, according to the polarity of the surface electric （E） field, that the thunderstorms can be divided into two categories in the study regions： one showing the normal tripole electrical charge structure （normal-type）, and the other showing the special tripole charge structure with a larger-than-usual lower positive charge center （LPCC） at the base of thunderstorm （special-type）, where the induced surface E field is controlled by the LPCC when a thunderstorm is overhead. We find that the two types of thunderstorms have different occurrences in different regions, and the percentage of special-type thunderstorms increases with the altitude. On the whole, the flash rate of thunderstorms is quite low, and the mean value is about 1-3 fl/min, while the flash rate of special-type is slightly greater than that of the normal-type thunderstorm. The statistical results of cloud-to-ground flash （CG） numbers indicate that the ratio of ＋CG flash increases with the altitude, with the value about 14.7 percent through 25.4 percent.展开更多
The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the cloud...The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the clouds to the stage of studying the formation of macro- and microstructural characteristics of clouds as a whole, taking into account their system properties. The main directions of the development of cloud physics at the upcoming stage of its development are discussed. The paper points out that one of these areas is the determination of the structure-forming factors for the clouds and the study of their influence on their formation and evolution. It is noted that one of such factors is the interaction of clouds with their surrounding atmosphere, and the main method of studying its role in the processes of cloud formation is mathematical modeling. A three-dimensional nonstationary model of convective clouds is presented with a detailed account of the processes of thermohydrodynamics and microphysics, which is used for research. The results of modeling the influence of the wind field structure in the atmosphere on the formation and evolution of clouds are presented. It is shown that the dynamic characteristics of the atmosphere have a significant effect on the formation of macro- and microstructural characteristics of convective clouds: the more complex the structure of the wind field in the atmosphere (i.e., the more intense the interaction of the atmosphere and the cloud), the less powerful the clouds are formed.展开更多
基金supported by the National Key R&D Program of China(No.2023YFC3081200)the National Natural Science Foundation of China(No.42077264)the Scientific Research Project of PowerChina Huadong Engineering Corporation Limited(HDEC-2022-0301).
文摘Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
基金funded by the National Natural Science Foundation of China(42071014).
文摘Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.
基金supported by the Special Fund for Basic Research on Scientific Instruments of the National Natural Science Foundation of China(Grant No.4182780021)Emeishan-Hanyuan Highway ProgramTaihang Mountain Highway Program。
文摘This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by normal tensor voting theory,(2)co ntraction of trace feature points,(3)connection of trace feature points,(4)linearization of trace segments,and(5)connection of trace segments.A sensitivity analysis was then conducted to identify the optimal parameters of the proposed method.Three field cases,a natural rock mass outcrop and two excavated rock tunnel surfaces,were analyzed using the proposed method to evaluate its validity and efficiency.The results show that the proposed method is more efficient and accurate than the traditional trace mapping method,and the efficiency enhancement is more robust as the number of feature points increases.
基金supported by the National Natural Science Foundation of China(Grant Nos.41941017 and 42177139)Graduate Innovation Fund of Jilin University(Grant No.2024CX099)。
文摘The spatial distribution of discontinuities and the size of rock blocks are the key indicators for rock mass quality evaluation and rockfall risk assessment.Traditional manual measurement is often dangerous or unreachable at some high-steep rock slopes.In contrast,unmanned aerial vehicle(UAV)photogrammetry is not limited by terrain conditions,and can efficiently collect high-precision three-dimensional(3D)point clouds of rock masses through all-round and multiangle photography for rock mass characterization.In this paper,a new method based on a 3D point cloud is proposed for discontinuity identification and refined rock block modeling.The method is based on four steps:(1)Establish a point cloud spatial topology,and calculate the point cloud normal vector and average point spacing based on several machine learning algorithms;(2)Extract discontinuities using the density-based spatial clustering of applications with noise(DBSCAN)algorithm and fit the discontinuity plane by combining principal component analysis(PCA)with the natural breaks(NB)method;(3)Propose a method of inserting points in the line segment to generate an embedded discontinuity point cloud;and(4)Adopt a Poisson reconstruction method for refined rock block modeling.The proposed method was applied to an outcrop of an ultrahigh steep rock slope and compared with the results of previous studies and manual surveys.The results show that the method can eliminate the influence of discontinuity undulations on the orientation measurement and describe the local concave-convex characteristics on the modeling of rock blocks.The calculation results are accurate and reliable,which can meet the practical requirements of engineering.
基金Project(51274250)supported by the National Natural Science Foundation of ChinaProject(2012BAK09B02-05)supported by the National Key Technology R&D Program during the 12th Five-year Plan of China
文摘An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.
基金Supported by the National Key Technologies R&D Program of China (2008BAC36B00)
文摘Using the spatial coordinates of detection stations and the time of arrival of lightning wave, the observation equations can be expressed. For the large lightning detection network, the least square method is used to process the adjustment of observation data to find the most probable value of lightning position, and the result is assessed by the mean error and dilution of precision. Lightning location precision is affected by figure factor. The conclusion can be used in the design of location network, data processing, and data analysis.
基金funded by the U.S.National Institute for Occupational Safety and Health(NIOSH)under the Contract No.75D30119C06044。
文摘In the last two decades,significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional(3D)models.This provides several methodologies for acquiring discontinuity measurements from 3D models,such as point clouds generated using laser scanning or photogrammetry.However,even with numerous automated and semiautomated methods presented in the literature,there is not one single method that can automatically characterize discontinuities accurately in a minimum of time.In this paper,we critically review all the existing methods proposed in the literature for the extraction of discontinuity characteristics such as joint sets and orientations,persistence,joint spacing,roughness and block size using point clouds,digital elevation maps,or meshes.As a result of this review,we identify the strengths and drawbacks of each method used for extracting those characteristics.We found that the approaches based on voxels and region growing are superior in extracting joint planes from 3D point clouds.Normal tensor voting with trace growth algorithm is a robust method for measuring joint trace length from 3D meshes.Spacing is estimated by calculating the perpendicular distance between joint planes.Several independent roughness indices are presented to quantify roughness from 3D surface models,but there is a need to incorporate these indices into automated methodologies.There is a lack of efficient algorithms for direct computation of block size from 3D rock mass surface models.
基金supported by Project of the National Natural Science Foundation of China (No.62073256, 61773305)the Key Science and Technology Program of Shaanxi Province (No.2020GY-125)Xi’an Science and Technology Innovation talent service enterprise project (No.2020KJRC0041)。
文摘To objectively obtain the three-dimensional coordinates of the projectile fuze proximity explosion when projectile intersects the head of missile target, we propose a dynamic seven photoelectric detection screen test method, which is made up of six plane detection screens and a flash photoelectric dynamic detection screen. The three-dimensional coordinates calculation model of the projectile proximity explosion position based on seven plane detection screens with dynamic characteristics is established.According to the relation of the dynamic seven photoelectric detection screen planes and the time values,the analytical function of the projectile proximity explosion position parameters under non-linear motion is derived. The projectile signal filtering method based on discrete wavelet transform is explored in this work. Additionally, the projectile signal recognition algorithm using an improved particle swarm is proposed. Based on the characteristics of the time duration and the signal peak error for the projectile passing through the detection screen, the signals attribution of the same projectile passing through six detection screens are analyzed for obtaining precise time values of the same projectile passing through the detection screens. On the basis of the projectile fuze proximity explosion test, the linear motion model and the proposed non-linear motion model are used to calculate and compare the same group of projectiles proximity explosion position parameters. The comparison of test results verifies that the proposed test method and calculation model in this work accurately obtain the actual projectile proximity explosion position parameters.
基金The authors gratefully acknowledge the approval and the support of this research study by grant no.SCIA-2022-11-1551 from the Deanship of Scientific Research at Northern Border University,Arar,K.S.A.
文摘Flash Crowd attacks are a form of Distributed Denial of Service(DDoS)attack that is becoming increasingly difficult to detect due to its ability to imitate normal user behavior in Cloud Computing(CC).Botnets are often used by attackers to perform a wide range of DDoS attacks.With advancements in technology,bots are now able to simulate DDoS attacks as flash crowd events,making them difficult to detect.When it comes to application layer DDoS attacks,the Flash Crowd attack that occurs during a Flash Event is viewed as the most intricate issue.This is mainly because it can imitate typical user behavior,leading to a substantial influx of requests that can overwhelm the server by consuming either its network bandwidth or resources.Therefore,identifying these types of attacks on web servers has become crucial,particularly in the CC.In this article,an efficient intrusion detection method is proposed based on White Shark Optimizer and ensemble classifier(Convolutional Neural Network(CNN)and LighGBM).Experiments were conducted using a CICIDS 2017 dataset to evaluate the performance of the proposed method in real-life situations.The proposed IDS achieved superior results,with 95.84%accuracy,96.15%precision,95.54%recall,and 95.84%F1 measure.Flash crowd attacks are challenging to detect,but the proposed IDS has proven its effectiveness in identifying such attacks in CC and holds potential for future improvement.
基金financially supported by Shandong Provincial Key Research and Development Program(Grant No.2022LZGCQY002,2021LZGC013,2023TZXD004).
文摘Accurate and rapid wheat morphology reconstruction and trait collection are essential for selecting varieties,scientific cultivation,and precise management.A single perspective is limited by environmental obstructions,hindering the collection of high-throughput phenotype data for wheat plants.Therefore,a rapid reconstruction method of multi-view threedimensional point cloud is proposed to realize the high-throughput and accurate identification of wheat phenotype.Firstly,taking wheat at the tillering stage as the experimental object,a multi-view acquisition system based on a RealSense sensor was constructed,and the point cloud data of wheat were obtained from 16 views.Secondly,a joint photometric and geometric objective was optimized,and space location was registered by colored Point Cloud Registration(colored)and Iterative Closest Point(ICP)algorithms.Furthermore,the Multiple View Stereo(MVS)algorithm was used to combine the depth image,RGB image,and spatial position obtained by coarse registration to enable the fine registration of multi-viewpoint clouds.Compared with the traditional Structure From Motion(SFM)-MVS algorithm,our proposed method is much faster,with an average reconstruction time of 33.82 s.Moreover,the wheat plant height,leaf length,leaf width,leaf area,and leaf angle of wheat were calculated based on the three-dimensional point cloud of the wheat plant.The experimental results showed that the determination coefficients of the method are 0.996,0.958,0.956,0.984,and 0.849,respectively.Finally,phenotypic information such as compact degree,convex hull volume,and average leaf area of different wheat varieties was analyzed and identified,proving that the method could capture the phenotypic differences between varieties and individuals.The proposed method provides a rapid approach to quantify wheat phenotypic traits,aiding breeding,scientific cultivation,and environmental management.
基金funded by the National Natural Science Foundation of China(32371985)the Fundamental Research Funds for the Central Universities,China(226-2022-00217).
文摘Fusing three-dimensional(3D)and multispectral(MS)imaging data holds promise for high-throughput and comprehensive plant phenotyping to decipher genome-to-phenome knowledge.Acquiring high-quality 3D MS point clouds(3DMPCs)of plants remains challenging because of poor 3D data quality and limited radiometric calibration methods for plants with a complex canopy structure.Here,we present a novel 3D spatial–spectral data fusion approach to collect high-quality 3DMPCs of plants by integrating the next-best-view planning for adaptive data acquisition and neural reference field(NeREF)for radiometric calibration.This approach was used to acquire 3DMPCs of perilla,tomato,and rapeseed plants with diverse plant architecture and leaf morphological features evaluated by the accuracy of chlorophyll content and equivalent water thickness(EWT)estimation.The results showed that the completeness of plant point clouds collected by this approach was improved by an average of 23.6%compared with the fixed viewpoints alone.The NeREF-based radiometric calibration with the hemispherical reference outperformed the conventional calibration method by reducing the root mean square error(RMSE)of 58.93%for extracted reflectance spectra.The RMSE for chlorophyll content and EWT predictions decreased by 21.25%and 14.13%using partial least squares regression with the generated 3DMPCs.Collectively,our study provides an effective and efficient way to collect high-quality 3DMPCs of plants under natural light conditions,which improves the accuracy and comprehensiveness of phenotyping plant morphological and physiological traits,and thus will facilitate plant biology and genetic studies as well as crop breeding.
基金supported by National Natural Science Foundation of China (Grant No. 40905001, 40775004)the Main Direction Program of the Knowledge Innovation of Chinese Academy of Sciences (Grant No.KZCX2-YW-206)
文摘The electrical characteristics of thunderstorms in three different altitude regions of the Chinese inland plateau have been analyzed in this paper. The results show, according to the polarity of the surface electric （E） field, that the thunderstorms can be divided into two categories in the study regions： one showing the normal tripole electrical charge structure （normal-type）, and the other showing the special tripole charge structure with a larger-than-usual lower positive charge center （LPCC） at the base of thunderstorm （special-type）, where the induced surface E field is controlled by the LPCC when a thunderstorm is overhead. We find that the two types of thunderstorms have different occurrences in different regions, and the percentage of special-type thunderstorms increases with the altitude. On the whole, the flash rate of thunderstorms is quite low, and the mean value is about 1-3 fl/min, while the flash rate of special-type is slightly greater than that of the normal-type thunderstorm. The statistical results of cloud-to-ground flash （CG） numbers indicate that the ratio of ＋CG flash increases with the altitude, with the value about 14.7 percent through 25.4 percent.
文摘The state of the physics of convective clouds and cloud seeding is discussed briefly. It is noted that at the present time there is a transition from the stage of investigation of “elementary” processes in the clouds to the stage of studying the formation of macro- and microstructural characteristics of clouds as a whole, taking into account their system properties. The main directions of the development of cloud physics at the upcoming stage of its development are discussed. The paper points out that one of these areas is the determination of the structure-forming factors for the clouds and the study of their influence on their formation and evolution. It is noted that one of such factors is the interaction of clouds with their surrounding atmosphere, and the main method of studying its role in the processes of cloud formation is mathematical modeling. A three-dimensional nonstationary model of convective clouds is presented with a detailed account of the processes of thermohydrodynamics and microphysics, which is used for research. The results of modeling the influence of the wind field structure in the atmosphere on the formation and evolution of clouds are presented. It is shown that the dynamic characteristics of the atmosphere have a significant effect on the formation of macro- and microstructural characteristics of convective clouds: the more complex the structure of the wind field in the atmosphere (i.e., the more intense the interaction of the atmosphere and the cloud), the less powerful the clouds are formed.
