Background:Individual tree extraction from terrestrial laser scanning(TLS)data is a prerequisite for tree-scale estimations of forest biophysical properties.This task currently is undertaken through laborious and time...Background:Individual tree extraction from terrestrial laser scanning(TLS)data is a prerequisite for tree-scale estimations of forest biophysical properties.This task currently is undertaken through laborious and time-consuming manual assistance and quality control.This study presents a new fully automatic approach to extract single trees from large-area TLS data.This data-driven method operates exclusively on a point cloud graph by path finding,which makes our method computationally efficient and universally applicable to data from various forest types.Results:We demonstrated the proposed method on two openly available datasets.First,we achieved state-of-the-art performance on locating single trees on a benchmark dataset by significantly improving the mean accuracy by over 10% especially for difficult forest plots.Second,we successfully extracted 270 trees from one hectare temperate forest.Quantitative validation resulted in a mean Intersection over Union(mIoU)of 0.82 for single crown segmentation,which further led to a relative root mean square error(RMSE%)of 21.2% and 23.5% for crown area and tree volume estimations,respectively.Conclusions:Our method allows automated access to individual tree level information from TLS point clouds.The proposed method is free from restricted assumptions of forest types.It is also computationally efficient with an average processing time of several seconds for one million points.It is expected and hoped that our method would contribute to TLS-enabled wide-area forest qualifications,ranging from stand volume and carbon stocks modelling to derivation of tree functional traits as part of the global ecosystem understanding.展开更多
Discussions on Chinese modernization are offering African countries both conceptual inspiration and practical references as they explore their own sustainable development paths.
To deal with a polluted by-product of coal production,central China’s Shanxi Province has explored a governance path that addresses both the symptoms and root causes.
China is carving out a distinctive development path which features urban-rural integration.This approach has not only yielded tangible results domestically but also drawn the attention of other countries.
With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths ha...With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.展开更多
Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lowe...Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lower machining efficiency and longer machining time due to its time-varying cutter-workpiece engagement angle and a high percentage of non-cutting tool paths.To address these issues,this paper introduces a parameter-variant trochoidal-like(PVTR)tool path planning method for chatter-free and high-efficiency milling.This method ensures a constant engagement angle for each tool path period by adjusting the trochoidal radius and step.Initially,the nonlinear equation for the PVTR toolpath is established.Then,a segmented recurrence method is proposed to plan tool paths based on the desired engagement angle.The impact of trochoidal tool path parameters on the engagement angle is analyzed and coupled this information with the milling stability model based on spindle speed and engagement angle to determine the desired engagement angle throughout the machining process.Finally,several experimental tests are carried out using the bull-nose end mill to validate the feasibility and effectiveness of the proposed method.展开更多
In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms...In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.展开更多
The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving...The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving timely and compatible solutions to treat diverse skin injuries.In situ bioprinting has emerged as a key new technology,since it reduces risks during the implantation of printed scaffolds and demonstrates superior therapeutic effects.However,maintaining printing fidelity during in situ bioprinting remains a critical challenge,particularly with respect to model layering and path planning.This study proposes a novel optimization-based conformal path planning strategy for in situ bioprinting-based repair of complex skin injuries.This strategy employs constrained optimization to identify optimal waypoints on a point cloud-approximated curved surface,thereby ensuring a high degree of similarity between predesigned planar and surface-mapped 3D paths.Furthermore,this method is applicable for skin wound treatments,since it generates 3D-equidistant zigzag curves along surface tangents and enables multi-layer conformal path planning to facilitate the treatment of volumetric injuries.Furthermore,the proposed algorithm was found to be a feasible and effective treatment in a murine back injury model as well as in other complex models,thereby showcasing its potential to guide in situ bioprinting,enhance bioprinting fidelity,and facilitate improvement of clinical outcomes.展开更多
To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The...To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.展开更多
Unmanned aerial vehicles(UAVs)are widely used in situations with uncertain and risky areas lacking network coverage.In natural disasters,timely delivery of first aid supplies is crucial.Current UAVs face risks such as...Unmanned aerial vehicles(UAVs)are widely used in situations with uncertain and risky areas lacking network coverage.In natural disasters,timely delivery of first aid supplies is crucial.Current UAVs face risks such as crashing into birds or unexpected structures.Airdrop systems with parachutes risk dispersing payloads away from target locations.The objective here is to use multiple UAVs to distribute payloads cooperatively to assigned locations.The civil defense department must balance coverage,accurate landing,and flight safety while considering battery power and capability.Deep Q-network(DQN)models are commonly used in multi-UAV path planning to effectively represent the surroundings and action spaces.Earlier strategies focused on advanced DQNs for UAV path planning in different configurations,but rarely addressed non-cooperative scenarios and disaster environments.This paper introduces a new DQN framework to tackle challenges in disaster environments.It considers unforeseen structures and birds that could cause UAV crashes and assumes urgent landing zones and winch-based airdrop systems for precise delivery and return.A new DQN model is developed,which incorporates the battery life,safe flying distance between UAVs,and remaining delivery points to encode surrounding hazards into the state space and Q-networks.Additionally,a unique reward system is created to improve UAV action sequences for better delivery coverage and safe landings.The experimental results demonstrate that multi-UAV first aid delivery in disaster environments can achieve advanced performance.展开更多
This study investigates the mechanical response of an underground cavern subjected to cyclic high gas pressure,aiming to establish a theoretical foundation for the design of lined rock caverns(LRCs)for energy storage ...This study investigates the mechanical response of an underground cavern subjected to cyclic high gas pressure,aiming to establish a theoretical foundation for the design of lined rock caverns(LRCs)for energy storage with high internal pressure,e.g.compressed air energy storage(CAES)underground caverns or hydrogen storage caverns.Initially,the stress paths of the surrounding rock during the excavation,pressurization,and depressurization processes are delineated.Analytical expressions for the stress and deformation of the surrounding rock are derived based on the MohreCoulomb criterion.These expressions are then employed to evaluate the displacement of cavern walls under varying qualities of surrounding rock,the contact pressure between the steel lining and the surrounding rock subject to different gas storage pressures,the load-bearing ratio of the surrounding rock,and the impact of lining thickness on the critical gas pressure.Furthermore,the deformation paths of the surrounding rock are evaluated,along with the effects of tunnel depth and diameter on residual deformation of the surrounding rock,and the critical minimum gas pressure at which the surrounding rock and the lining do not detach.The results indicate that residual deformation of the surrounding rock occurs after depressurization under higher internal pressure for higher-quality rock masses,leading to detachment between the surrounding rock and the steel lining.The findings indicate that thicker linings correspond to higher critical minimum gas pressures.However,for lower-quality surrounding rock,thicker linings correspond to lower critical minimum gas pressures.These findings will provide invaluable insights for the design of LRCs for underground energy storage caverns.展开更多
This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later step...This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later steps depend on earlier ones successively,despite the ineradicable chance in their respective formation.In this paper,a token-oriented retrospective approach is proposed to overcome the limitation of the type-oriented approach in explaining path-related phenomena.My argument for the validity and utility of this approach is largely based on the elements of(PD),a definitional schema for diachronic sequences subject to a recursive counterfactual formula.I explore certain aspects of path individuation that have so far not been discussed,despite(PD)’s formal congeniality with Lewis’s‘causal chain’.Two basic patterns of path generation are examined:the first is for distinguishing actual vs possible branching paths,while the second introduces a metaphysical theme regarding the retrospective grounding of the causal status of an upstream event by its downstream(joint)effect.A central example of the paper,viz.,the Gobang game,is used to illustrate how the token-oriented approach works for path individuation.展开更多
Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous...Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous control process of SMR can be divided into three stages,say,state diagnosis,autonomous decision-making and coordinated control.In this paper,the autonomous state recognition and task planning of unmanned SMR are investigated.An operating condition recognition method based on the knowledge base of SMR operation is proposed by using the artificial neural network(ANN)technology,which constructs a basis for the state judgment of intelligent reactor control path planning.An improved reinforcement learning path planning algorithm is utilized to implement the path transfer decision-makingThis algorithm performs condition transitions with minimal cost under specified modes.In summary,the full range control path intelligent decision-planning technology of SMR is realized,thus provides some theoretical basis for the design and build of unmanned SMR in the future.展开更多
The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of th...The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of the diesel engine air path system,assuming that the system may simultaneously be affected by actuator faults and external random disturbances,a disturbance observer-based sliding mode controller is designed.Through the linear matrix inequality technique for solving observer and controller gains,optimal gain matrices can be obtained,eliminating the manual adjustment process of controller parameters and reducing the chattering phenomenon of the sliding mode surface.Finally,the effectiveness of the proposed method is verified through simulation analysis.展开更多
The selective hydrogenation ofα,β-unsaturated aldehydes/ketones enables precise control over product structures and properties by regulating hydrogen transport pathways and bond cleavage sequences to selectively red...The selective hydrogenation ofα,β-unsaturated aldehydes/ketones enables precise control over product structures and properties by regulating hydrogen transport pathways and bond cleavage sequences to selectively reduce C=C or C=O bonds while preserving other functional groups within the molecule.This approach serves as a critical strategy for the directional synthesis of high-value molecules.However,achieving such selectivity remains challenging due to the thermodynamic equilibrium and kinetic competition between C=O and C=C bonds inα,β-unsaturated systems.Consequently,constructing precisely targeted catalytic systems is essential to overcome these limitations,offering both fundamental scientific significance and industrial application potential.Metal-organic frameworks(MOFs)and their derivatives have emerged as innovative platforms for designing such systems,owing to their programmable topology,tunable pore microenvironments,spatially controllable active sites,and modifiable electronic structures.This review systematically summarizes the research progress of MOF-based catalysts for selec-tive hydrogenation ofα,β-unsaturated aldehydes/ketones in the last decade,with emphasis on the design strategy,conformational relationship,and catalytic mechanism,aiming to provide new ideas for the design of targeted catalyt-ic systems for the selective hydrogenation ofα,β-unsaturated aldehydes/ketones.展开更多
Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,redu...Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,reducing the system's adaptability to high-speed reversal scanning and decreasing scanning efficiency.This study proposes a novel sinusoidal variable-speed roll scanning strategy,which reduces abrupt changes in speed and acceleration,minimizing time loss during reversals.Based on the forward image motion compensation strategy in the pitch direction,we establish a line-of-sight(LOS)position calculation model with vertical flight path correction(VFPC),ensuring that the central LOS of the scanned image remains stable on the same horizontal line,facilitating accurate image stitching in whisk-broom imaging.Through theoretical analysis and simulation experiments,the proposed method improves the scanning efficiency by approximately 18.6%at a 90o whiskbroom imaging angle under the same speed height ratio conditions.The new VFPC method enables wide-field,high-resolution imaging,achieving single-line LOS horizontal stability with an accuracy of better than O.4 mrad.The research is of great significance to promote the further development of airborne area-array whisk-broom imaging technology toward wider fields of view,higher speed height ratios,and greater scanning efficiency.展开更多
An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengt...An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengths,using temporal models to estimate travel time,idealized integration of global and local motion planners,and omission of external environmental disturbances.These rudimentary criteria cannot adequately capture real-world operations.To address these shortcomings,this study introduces a simulation framework for evaluating navigation modules designed for ASVs.The proposed framework is implemented on a prototype ASV using the Robot Operating System(ROS)and the Gazebo simulation platform.The implementation processes replicated satellite images with the extended Kalman filter technique to acquire localized location data.Cost minimization for global trajectories is achieved through the application of Dijkstra and A*algorithms,while local obstacle avoidance is managed by the dynamic window approach algorithm.The results demonstrate the distinctions and intricacies of the metrics provided by the proposed simulation framework compared with the rudimentary criteria commonly utilized in conventional path planning works.展开更多
A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path...A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.展开更多
Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds tha...Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds that the low-altitude economy can effectively promote the development of high-end and diversified tourism in Zhejiang by innovating tourism formats,optimizing resource allocation,and enhancing tourist experiences.Besides,it analyzes the current development status of the low-altitude economy in Zhejiang and its potential for integration with tourism,revealing specific enabling pathways for tourism transformation,including low-altitude sightseeing,aviation tourism,and low-altitude sports.Finally,it proposes policy recommendations such as strengthening policy support,enhancing infrastructure development,and cultivating market entities.The findings aim to provide theoretical references and practical guidance for the high-quality development of tourism in Zhejiang Province.展开更多
Under the background of"Digital Commerce for Rural Vitalization",rural E-commerce has experienced rapid development.However,agricultural products like strawberries,often produced by small-scale,fragmented,an...Under the background of"Digital Commerce for Rural Vitalization",rural E-commerce has experienced rapid development.However,agricultural products like strawberries,often produced by small-scale,fragmented,and less competitive individual farmers,struggle to meet the compliance and scalability demands of E-commerce,thereby constraining high-quality local economic development.Aiming to address this issue,this paper,guided by relevant policies and strategies,employs case analysis and logical deduction to explore the industrialization path of the"Cooperative+E-commerce"model for the strawberry industry.The research finds that by optimizing the cooperative's organizational structure,implementing multi-channel E-commerce strategies,upgrading the supply chain(including cold chain and quality traceability),and engaging in collaborative brand building,a robust industrial system can be formed.Supplemented by benefit evaluation,policy support,and regulatory oversight,this system can effectively bridge small-scale production with the broader market.This study concludes that this pathway can enhance the added value of the strawberry industry,increase farmer incomes,and provide practical insights for promoting high-quality local economic development.展开更多
基金partially funded by the Scientific Research Foundation of Xidian Universitypart of 3DForMod project(ANR-17-EGAS-0002-01)funded in the frame of the JPI FACCE ERA-GAS call funded under European Union’s Horizon 2020 research and innovation program(grant agreement No.696356).
文摘Background:Individual tree extraction from terrestrial laser scanning(TLS)data is a prerequisite for tree-scale estimations of forest biophysical properties.This task currently is undertaken through laborious and time-consuming manual assistance and quality control.This study presents a new fully automatic approach to extract single trees from large-area TLS data.This data-driven method operates exclusively on a point cloud graph by path finding,which makes our method computationally efficient and universally applicable to data from various forest types.Results:We demonstrated the proposed method on two openly available datasets.First,we achieved state-of-the-art performance on locating single trees on a benchmark dataset by significantly improving the mean accuracy by over 10% especially for difficult forest plots.Second,we successfully extracted 270 trees from one hectare temperate forest.Quantitative validation resulted in a mean Intersection over Union(mIoU)of 0.82 for single crown segmentation,which further led to a relative root mean square error(RMSE%)of 21.2% and 23.5% for crown area and tree volume estimations,respectively.Conclusions:Our method allows automated access to individual tree level information from TLS point clouds.The proposed method is free from restricted assumptions of forest types.It is also computationally efficient with an average processing time of several seconds for one million points.It is expected and hoped that our method would contribute to TLS-enabled wide-area forest qualifications,ranging from stand volume and carbon stocks modelling to derivation of tree functional traits as part of the global ecosystem understanding.
文摘Discussions on Chinese modernization are offering African countries both conceptual inspiration and practical references as they explore their own sustainable development paths.
文摘To deal with a polluted by-product of coal production,central China’s Shanxi Province has explored a governance path that addresses both the symptoms and root causes.
文摘China is carving out a distinctive development path which features urban-rural integration.This approach has not only yielded tangible results domestically but also drawn the attention of other countries.
基金The 2024 Guangdong University of Science and Technology Teaching,Science and Innovation Project(GKJXXZ2024028)。
文摘With the rapid development of artificial intelligence(AI)technology,the teaching mode in the field of education is undergoing profound changes.Especially the design and implementation of personalized learning paths have become an important direction of intelligent teaching reform.The traditional“one-size-fits-all”teaching model has gradually failed to meet the individualized learning needs of students.However,through the advantages of data analysis and real-time feedback,AI technology can provide tailor-made teaching content and learning paths based on students’learning progress,interests,and abilities.This study explores the innovation of the personalized learning path model based on AI technology,and analyzes the potential and challenges of this model in improving teaching effectiveness,promoting the all-round development of students,and optimizing the interaction between teachers and students.Through case analysis and empirical research,this paper summarizes the implementation methods of the AI-driven personalized learning path,the innovation of teaching models,and their application prospects in educational reform.Meanwhile,the research also discussed the ethical issues of AI technology in education,data privacy protection,and its impact on the teacher-student relationship,and proposed corresponding solutions.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22A20202 and 52275477).
文摘Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lower machining efficiency and longer machining time due to its time-varying cutter-workpiece engagement angle and a high percentage of non-cutting tool paths.To address these issues,this paper introduces a parameter-variant trochoidal-like(PVTR)tool path planning method for chatter-free and high-efficiency milling.This method ensures a constant engagement angle for each tool path period by adjusting the trochoidal radius and step.Initially,the nonlinear equation for the PVTR toolpath is established.Then,a segmented recurrence method is proposed to plan tool paths based on the desired engagement angle.The impact of trochoidal tool path parameters on the engagement angle is analyzed and coupled this information with the milling stability model based on spindle speed and engagement angle to determine the desired engagement angle throughout the machining process.Finally,several experimental tests are carried out using the bull-nose end mill to validate the feasibility and effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(No.62373027).
文摘In disaster relief operations,multiple UAVs can be used to search for trapped people.In recent years,many researchers have proposed machine le arning-based algorithms,sampling-based algorithms,and heuristic algorithms to solve the problem of multi-UAV path planning.The Dung Beetle Optimization(DBO)algorithm has been widely applied due to its diverse search patterns in the above algorithms.However,the update strategies for the rolling and thieving dung beetles of the DBO algorithm are overly simplistic,potentially leading to an inability to fully explore the search space and a tendency to converge to local optima,thereby not guaranteeing the discovery of the optimal path.To address these issues,we propose an improved DBO algorithm guided by the Landmark Operator(LODBO).Specifically,we first use tent mapping to update the population strategy,which enables the algorithm to generate initial solutions with enhanced diversity within the search space.Second,we expand the search range of the rolling ball dung beetle by using the landmark factor.Finally,by using the adaptive factor that changes with the number of iterations.,we improve the global search ability of the stealing dung beetle,making it more likely to escape from local optima.To verify the effectiveness of the proposed method,extensive simulation experiments are conducted,and the result shows that the LODBO algorithm can obtain the optimal path using the shortest time compared with the Genetic Algorithm(GA),the Gray Wolf Optimizer(GWO),the Whale Optimization Algorithm(WOA)and the original DBO algorithm in the disaster search and rescue task set.
基金supported in part by the National Natural Science Foundation of China(Nos.52205532 and 624B2077)the National Key Research and Development Program of China(No.2023YFB4302003).
文摘The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving timely and compatible solutions to treat diverse skin injuries.In situ bioprinting has emerged as a key new technology,since it reduces risks during the implantation of printed scaffolds and demonstrates superior therapeutic effects.However,maintaining printing fidelity during in situ bioprinting remains a critical challenge,particularly with respect to model layering and path planning.This study proposes a novel optimization-based conformal path planning strategy for in situ bioprinting-based repair of complex skin injuries.This strategy employs constrained optimization to identify optimal waypoints on a point cloud-approximated curved surface,thereby ensuring a high degree of similarity between predesigned planar and surface-mapped 3D paths.Furthermore,this method is applicable for skin wound treatments,since it generates 3D-equidistant zigzag curves along surface tangents and enables multi-layer conformal path planning to facilitate the treatment of volumetric injuries.Furthermore,the proposed algorithm was found to be a feasible and effective treatment in a murine back injury model as well as in other complex models,thereby showcasing its potential to guide in situ bioprinting,enhance bioprinting fidelity,and facilitate improvement of clinical outcomes.
文摘To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.
基金supported by the Committee of Science of the Ministry of Education and Science of the Republic of Kazakhstan under Grant No.249015/0224.
文摘Unmanned aerial vehicles(UAVs)are widely used in situations with uncertain and risky areas lacking network coverage.In natural disasters,timely delivery of first aid supplies is crucial.Current UAVs face risks such as crashing into birds or unexpected structures.Airdrop systems with parachutes risk dispersing payloads away from target locations.The objective here is to use multiple UAVs to distribute payloads cooperatively to assigned locations.The civil defense department must balance coverage,accurate landing,and flight safety while considering battery power and capability.Deep Q-network(DQN)models are commonly used in multi-UAV path planning to effectively represent the surroundings and action spaces.Earlier strategies focused on advanced DQNs for UAV path planning in different configurations,but rarely addressed non-cooperative scenarios and disaster environments.This paper introduces a new DQN framework to tackle challenges in disaster environments.It considers unforeseen structures and birds that could cause UAV crashes and assumes urgent landing zones and winch-based airdrop systems for precise delivery and return.A new DQN model is developed,which incorporates the battery life,safe flying distance between UAVs,and remaining delivery points to encode surrounding hazards into the state space and Q-networks.Additionally,a unique reward system is created to improve UAV action sequences for better delivery coverage and safe landings.The experimental results demonstrate that multi-UAV first aid delivery in disaster environments can achieve advanced performance.
基金supported by the State Key Laboratory of Disaster Reduction in Civil Engineering(Grant No.SLDRCE23-02)Ningbo PublicWelfare Fund Project(Grant No.2023S100)the National Key Research and Development Program of China(Grant No.2024YFE0105800).
文摘This study investigates the mechanical response of an underground cavern subjected to cyclic high gas pressure,aiming to establish a theoretical foundation for the design of lined rock caverns(LRCs)for energy storage with high internal pressure,e.g.compressed air energy storage(CAES)underground caverns or hydrogen storage caverns.Initially,the stress paths of the surrounding rock during the excavation,pressurization,and depressurization processes are delineated.Analytical expressions for the stress and deformation of the surrounding rock are derived based on the MohreCoulomb criterion.These expressions are then employed to evaluate the displacement of cavern walls under varying qualities of surrounding rock,the contact pressure between the steel lining and the surrounding rock subject to different gas storage pressures,the load-bearing ratio of the surrounding rock,and the impact of lining thickness on the critical gas pressure.Furthermore,the deformation paths of the surrounding rock are evaluated,along with the effects of tunnel depth and diameter on residual deformation of the surrounding rock,and the critical minimum gas pressure at which the surrounding rock and the lining do not detach.The results indicate that residual deformation of the surrounding rock occurs after depressurization under higher internal pressure for higher-quality rock masses,leading to detachment between the surrounding rock and the steel lining.The findings indicate that thicker linings correspond to higher critical minimum gas pressures.However,for lower-quality surrounding rock,thicker linings correspond to lower critical minimum gas pressures.These findings will provide invaluable insights for the design of LRCs for underground energy storage caverns.
文摘This paper purports to expound a special(technical)notion of paths.A neglected fundamental fact(especially under indeterminism)is that the path-dependent direction of any diachronic outcome is backward,i.e.,later steps depend on earlier ones successively,despite the ineradicable chance in their respective formation.In this paper,a token-oriented retrospective approach is proposed to overcome the limitation of the type-oriented approach in explaining path-related phenomena.My argument for the validity and utility of this approach is largely based on the elements of(PD),a definitional schema for diachronic sequences subject to a recursive counterfactual formula.I explore certain aspects of path individuation that have so far not been discussed,despite(PD)’s formal congeniality with Lewis’s‘causal chain’.Two basic patterns of path generation are examined:the first is for distinguishing actual vs possible branching paths,while the second introduces a metaphysical theme regarding the retrospective grounding of the causal status of an upstream event by its downstream(joint)effect.A central example of the paper,viz.,the Gobang game,is used to illustrate how the token-oriented approach works for path individuation.
文摘Small modular reactor(SMR)belongs to the research forefront of nuclear reactor technology.Nowadays,advancement of intelligent control technologies paves a new way to the design and build of unmanned SMR.The autonomous control process of SMR can be divided into three stages,say,state diagnosis,autonomous decision-making and coordinated control.In this paper,the autonomous state recognition and task planning of unmanned SMR are investigated.An operating condition recognition method based on the knowledge base of SMR operation is proposed by using the artificial neural network(ANN)technology,which constructs a basis for the state judgment of intelligent reactor control path planning.An improved reinforcement learning path planning algorithm is utilized to implement the path transfer decision-makingThis algorithm performs condition transitions with minimal cost under specified modes.In summary,the full range control path intelligent decision-planning technology of SMR is realized,thus provides some theoretical basis for the design and build of unmanned SMR in the future.
基金Supported by the National Key R&D Program of China(2021YFB2011300)the National Natural Science Foundation of China(52275044,52205299)+1 种基金the Zhejiang Provincial Natural Science Foundation of China(Z23E050032)the China Postdoctoral Science Foundation(2022M710304).
文摘The operating environment of the diesel engine air path system is complex and may be affected by external random disturbances.Potentially leading to faults.This paper addresses the fault-tolerant control problem of the diesel engine air path system,assuming that the system may simultaneously be affected by actuator faults and external random disturbances,a disturbance observer-based sliding mode controller is designed.Through the linear matrix inequality technique for solving observer and controller gains,optimal gain matrices can be obtained,eliminating the manual adjustment process of controller parameters and reducing the chattering phenomenon of the sliding mode surface.Finally,the effectiveness of the proposed method is verified through simulation analysis.
文摘The selective hydrogenation ofα,β-unsaturated aldehydes/ketones enables precise control over product structures and properties by regulating hydrogen transport pathways and bond cleavage sequences to selectively reduce C=C or C=O bonds while preserving other functional groups within the molecule.This approach serves as a critical strategy for the directional synthesis of high-value molecules.However,achieving such selectivity remains challenging due to the thermodynamic equilibrium and kinetic competition between C=O and C=C bonds inα,β-unsaturated systems.Consequently,constructing precisely targeted catalytic systems is essential to overcome these limitations,offering both fundamental scientific significance and industrial application potential.Metal-organic frameworks(MOFs)and their derivatives have emerged as innovative platforms for designing such systems,owing to their programmable topology,tunable pore microenvironments,spatially controllable active sites,and modifiable electronic structures.This review systematically summarizes the research progress of MOF-based catalysts for selec-tive hydrogenation ofα,β-unsaturated aldehydes/ketones in the last decade,with emphasis on the design strategy,conformational relationship,and catalytic mechanism,aiming to provide new ideas for the design of targeted catalyt-ic systems for the selective hydrogenation ofα,β-unsaturated aldehydes/ketones.
基金Supported by the National Key Research and Development Program(2023YFC3107602)。
文摘Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,reducing the system's adaptability to high-speed reversal scanning and decreasing scanning efficiency.This study proposes a novel sinusoidal variable-speed roll scanning strategy,which reduces abrupt changes in speed and acceleration,minimizing time loss during reversals.Based on the forward image motion compensation strategy in the pitch direction,we establish a line-of-sight(LOS)position calculation model with vertical flight path correction(VFPC),ensuring that the central LOS of the scanned image remains stable on the same horizontal line,facilitating accurate image stitching in whisk-broom imaging.Through theoretical analysis and simulation experiments,the proposed method improves the scanning efficiency by approximately 18.6%at a 90o whiskbroom imaging angle under the same speed height ratio conditions.The new VFPC method enables wide-field,high-resolution imaging,achieving single-line LOS horizontal stability with an accuracy of better than O.4 mrad.The research is of great significance to promote the further development of airborne area-array whisk-broom imaging technology toward wider fields of view,higher speed height ratios,and greater scanning efficiency.
基金Supported by the funding from RMIT Internal Research Grant R1.
文摘An efficient algorithm for path planning is crucial for guiding autonomous surface vehicles(ASVs)through designated waypoints.However,current evaluations of ASV path planning mainly focus on comparing total path lengths,using temporal models to estimate travel time,idealized integration of global and local motion planners,and omission of external environmental disturbances.These rudimentary criteria cannot adequately capture real-world operations.To address these shortcomings,this study introduces a simulation framework for evaluating navigation modules designed for ASVs.The proposed framework is implemented on a prototype ASV using the Robot Operating System(ROS)and the Gazebo simulation platform.The implementation processes replicated satellite images with the extended Kalman filter technique to acquire localized location data.Cost minimization for global trajectories is achieved through the application of Dijkstra and A*algorithms,while local obstacle avoidance is managed by the dynamic window approach algorithm.The results demonstrate the distinctions and intricacies of the metrics provided by the proposed simulation framework compared with the rudimentary criteria commonly utilized in conventional path planning works.
基金supported by the National Science Fund for Distinguished Young Scholars(52425211)BIT Research Fund Program for Young Scholars(XSQD-202201005).
文摘A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles(UAVs)while avoiding collisions.The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocityobstacle strategy for satisfying timeliness and effectiveness.The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing.Subsequently,the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the threedimensional velocity obstacle method,which describes the maneuvering space of collision avoidance as the intersection space of half space.To further handle the dynamic and collisionavoidance constraints,a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs.Simulation experiments demonstrate the effectiveness of the proposed method.
文摘Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds that the low-altitude economy can effectively promote the development of high-end and diversified tourism in Zhejiang by innovating tourism formats,optimizing resource allocation,and enhancing tourist experiences.Besides,it analyzes the current development status of the low-altitude economy in Zhejiang and its potential for integration with tourism,revealing specific enabling pathways for tourism transformation,including low-altitude sightseeing,aviation tourism,and low-altitude sports.Finally,it proposes policy recommendations such as strengthening policy support,enhancing infrastructure development,and cultivating market entities.The findings aim to provide theoretical references and practical guidance for the high-quality development of tourism in Zhejiang Province.
基金General Project of Philosophy and Social Sciences Research in Universities of Jiangsu Province,2024(2024SJYB1650).
文摘Under the background of"Digital Commerce for Rural Vitalization",rural E-commerce has experienced rapid development.However,agricultural products like strawberries,often produced by small-scale,fragmented,and less competitive individual farmers,struggle to meet the compliance and scalability demands of E-commerce,thereby constraining high-quality local economic development.Aiming to address this issue,this paper,guided by relevant policies and strategies,employs case analysis and logical deduction to explore the industrialization path of the"Cooperative+E-commerce"model for the strawberry industry.The research finds that by optimizing the cooperative's organizational structure,implementing multi-channel E-commerce strategies,upgrading the supply chain(including cold chain and quality traceability),and engaging in collaborative brand building,a robust industrial system can be formed.Supplemented by benefit evaluation,policy support,and regulatory oversight,this system can effectively bridge small-scale production with the broader market.This study concludes that this pathway can enhance the added value of the strawberry industry,increase farmer incomes,and provide practical insights for promoting high-quality local economic development.
