In order to improve lesion localisation in small-bowel capsule endoscopy,a modified capsule design has been proposed incorporating localisation and-in theorystabilization capabilities.The proposed design consists of a...In order to improve lesion localisation in small-bowel capsule endoscopy,a modified capsule design has been proposed incorporating localisation and-in theorystabilization capabilities.The proposed design consists of a capsule fitted with protruding wheels attached to a spring-mechanism.This would act as a miniature odometer,leading to more accurate lesion localization information in relation to the onset of the investigation(spring expansion e.g.,pyloric opening).Furthermore,this capsule could allow stabilization of the recorded video as any erratic,non-forward movement through the gut is minimised.Three-dimensional(3-D)printing technology was used to build a capsule prototype.Thereafter,miniature wheels were also 3-D printed and mounted on a spring which was attached to conventional capsule endoscopes for the purpose of this proof-of-concept experiment.In vitro and ex vivo experiments with porcine small-bowel are presented herein.Further experiments have been scheduled.展开更多
To disclose the grain crushing effects on the weathered granular soil rheological behavior,a series of rheological tests (odometer compression and triaxial shearing) were carried out.At the same time,the sieving analy...To disclose the grain crushing effects on the weathered granular soil rheological behavior,a series of rheological tests (odometer compression and triaxial shearing) were carried out.At the same time,the sieving analysis tests of these specimens were also executed before and after tests,and the grain crushing degree,Br and n5,were collectively adopted to estimate the grain crushing.The grain crushing degree depends on the stress path,stress level,and load time,especially,the longer load time and more intensive gradient shearing path will increase the grain crushing quantity.The Hardin crushing degrees Br are 0.191,0.118 and 0.085 in the ordinary compression,rheological compression and triaxial rheological shearing,respectively;The grain crushing degrees n5 are 1.9,1.4 and 1.32,respectively.The strain softening phase indicates the grain crushing and diffusive collapse,and the strain hardening phase indicates the rearrangement of these crushed grains and formation of new bearing soil skeleton.The rheological deformation of granular soil can be attributed to the coarse grain crushing and the filling external porosity with crushed fragments.展开更多
Positioning and mapping technology is a difficult and hot topic in autonomous driving environment sensing systems.In a complex traffic environment,the signal of the Global Navigation Satellite System(GNSS)will be bloc...Positioning and mapping technology is a difficult and hot topic in autonomous driving environment sensing systems.In a complex traffic environment,the signal of the Global Navigation Satellite System(GNSS)will be blocked,leading to inaccurate vehicle positioning.To ensure the security of automatic electric campus vehicles,this study is based on the Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain(LEGO-LOAM)algorithm with a monocular vision system added.An algorithm framework based on Lidar-IMU-Camera(Lidar means light detection and ranging)fusion was proposed.A lightweight monocular vision odometer model was used,and the LEGO-LOAM system was employed to initialize monocular vision.The visual odometer information was taken as the initial value of the laser odometer.At the back-end opti9mization phase error state,the Kalman filtering fusion algorithm was employed to fuse the visual odometer and LEGO-LOAM system for positioning.The visual word bag model was applied to perform loopback detection.Taking the test results into account,the laser radar loopback detection was further optimized,reducing the accumulated positioning error.The real car experiment results showed that our algorithm could improve the mapping quality and positioning accuracy in the campus environment.The Lidar-IMU-Camera algorithm framework was verified on the Hong Kong city dataset UrbanNav.Compared with the LEGO-LOAM algorithm,the results show that the proposed algorithm can effectively reduce map drift,improve map resolution,and output more accurate driving trajectory information.展开更多
The paper proposes an economical and fast algorithm for deriving trajectories from sporadic tracking points collected in location-based services (LBS). Although many traffic studies or applications can benefit from th...The paper proposes an economical and fast algorithm for deriving trajectories from sporadic tracking points collected in location-based services (LBS). Although many traffic studies or applications can benefit from the derived trajectories, the sporadic tracking points are always implicitly overlooked by most of existing map-matching algorithms. The algorithm proposed in this paper finds network paths or trajectories traveled by vehicles through augmenting GPS data with odometer data. An odometer can provide data of traveled distance which are compared with the lengths of candidate network paths in order to find the most approximate network path approaching the trajectory of a vehicle. Tracking points are classified into anchor points and non-anchor points. The former are used to divide trajectories, and the latter screen candidate network paths. An elliptic selection zone and a reduction process are applied to the selection of possible road segments composing candidate network paths. A brute-force searching algorithm is developed to find candidate network paths and calculate their lengths. A two-step screening process is designed to select the final result from candidate network paths. Finally, a series of experiments are conducted to validate the proposed algorithm.展开更多
基金Supported by SynMed UK related to this workDr.Koulaouzidis A has also received lecture honoraria from Dr Falk PharmaUnited kingdom
文摘In order to improve lesion localisation in small-bowel capsule endoscopy,a modified capsule design has been proposed incorporating localisation and-in theorystabilization capabilities.The proposed design consists of a capsule fitted with protruding wheels attached to a spring-mechanism.This would act as a miniature odometer,leading to more accurate lesion localization information in relation to the onset of the investigation(spring expansion e.g.,pyloric opening).Furthermore,this capsule could allow stabilization of the recorded video as any erratic,non-forward movement through the gut is minimised.Three-dimensional(3-D)printing technology was used to build a capsule prototype.Thereafter,miniature wheels were also 3-D printed and mounted on a spring which was attached to conventional capsule endoscopes for the purpose of this proof-of-concept experiment.In vitro and ex vivo experiments with porcine small-bowel are presented herein.Further experiments have been scheduled.
基金Project(50908233) supported by the National Natural Science Foundation of ChinaProject(200413) supported by Communication Science and Technology Fund of Hunan Province,China
文摘To disclose the grain crushing effects on the weathered granular soil rheological behavior,a series of rheological tests (odometer compression and triaxial shearing) were carried out.At the same time,the sieving analysis tests of these specimens were also executed before and after tests,and the grain crushing degree,Br and n5,were collectively adopted to estimate the grain crushing.The grain crushing degree depends on the stress path,stress level,and load time,especially,the longer load time and more intensive gradient shearing path will increase the grain crushing quantity.The Hardin crushing degrees Br are 0.191,0.118 and 0.085 in the ordinary compression,rheological compression and triaxial rheological shearing,respectively;The grain crushing degrees n5 are 1.9,1.4 and 1.32,respectively.The strain softening phase indicates the grain crushing and diffusive collapse,and the strain hardening phase indicates the rearrangement of these crushed grains and formation of new bearing soil skeleton.The rheological deformation of granular soil can be attributed to the coarse grain crushing and the filling external porosity with crushed fragments.
基金supported by the National Natural Science Foundation of China(Grant Nos.51975088 and 51975089).
文摘Positioning and mapping technology is a difficult and hot topic in autonomous driving environment sensing systems.In a complex traffic environment,the signal of the Global Navigation Satellite System(GNSS)will be blocked,leading to inaccurate vehicle positioning.To ensure the security of automatic electric campus vehicles,this study is based on the Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain(LEGO-LOAM)algorithm with a monocular vision system added.An algorithm framework based on Lidar-IMU-Camera(Lidar means light detection and ranging)fusion was proposed.A lightweight monocular vision odometer model was used,and the LEGO-LOAM system was employed to initialize monocular vision.The visual odometer information was taken as the initial value of the laser odometer.At the back-end opti9mization phase error state,the Kalman filtering fusion algorithm was employed to fuse the visual odometer and LEGO-LOAM system for positioning.The visual word bag model was applied to perform loopback detection.Taking the test results into account,the laser radar loopback detection was further optimized,reducing the accumulated positioning error.The real car experiment results showed that our algorithm could improve the mapping quality and positioning accuracy in the campus environment.The Lidar-IMU-Camera algorithm framework was verified on the Hong Kong city dataset UrbanNav.Compared with the LEGO-LOAM algorithm,the results show that the proposed algorithm can effectively reduce map drift,improve map resolution,and output more accurate driving trajectory information.
基金Supported by the National Natural Science Foundation of China (No40701142)the Scientific Research Starting Foundation for Returned Overseas Chinese Scholars, Ministry of Education, China
文摘The paper proposes an economical and fast algorithm for deriving trajectories from sporadic tracking points collected in location-based services (LBS). Although many traffic studies or applications can benefit from the derived trajectories, the sporadic tracking points are always implicitly overlooked by most of existing map-matching algorithms. The algorithm proposed in this paper finds network paths or trajectories traveled by vehicles through augmenting GPS data with odometer data. An odometer can provide data of traveled distance which are compared with the lengths of candidate network paths in order to find the most approximate network path approaching the trajectory of a vehicle. Tracking points are classified into anchor points and non-anchor points. The former are used to divide trajectories, and the latter screen candidate network paths. An elliptic selection zone and a reduction process are applied to the selection of possible road segments composing candidate network paths. A brute-force searching algorithm is developed to find candidate network paths and calculate their lengths. A two-step screening process is designed to select the final result from candidate network paths. Finally, a series of experiments are conducted to validate the proposed algorithm.
