The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-d...The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.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
As the development of new power systems accelerates and the impacts of high renewable energy integration and extreme weather intensify,grid-alternative energy storage is garnering increasing attention for its grid-int...As the development of new power systems accelerates and the impacts of high renewable energy integration and extreme weather intensify,grid-alternative energy storage is garnering increasing attention for its grid-interaction benefits and clear business models.Consequently,assessing the value of grid-alternative energy storage in the systemtransition has become critically important.Considering the performance characteristics of storage,we propose a value assessment frame-work for grid-alternative energy storage,quantifying its non-wires-alternative effects from both cost and benefit perspectives.Building on this,we developed a collaborative planning model for energy storage and transmission grids,aimed at maximizing the economic benefits of storage systems while balancing investment and operational costs.The model considers regional grid interconnections and their interactions with system operation.By participating in system operations,grid-alternative energy storage not only maximizes its own economic benefits but also generates social welfare transfer effects.Furthermore,based on multi-regional interconnected planning,grid-alternative energy storage can reduce system costs by approximately 35%,with the most significant changes observed in generation costs.Multi-regional coordinated planning significantly enhances the sys-tem’s flexibility in regulation.However,when the load factor of interconnection lines between regions remains constant,system operational flexibility tends to decrease,leading to a roughly 28.9%increase in storage investment.Additionally,under regional coordinated planning,the greater the disparity in wind power integration across interconnected regions,the more noticeable the reduction in system costs.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
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
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
To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distrib...To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is proposed.Firstly,the spatio-temporal correlation of large-scale wind-photovoltaic energy is modeled based on the Vine Copula model,and the spatial correlation of the generated wind-photovoltaic power generation is corrected to get the spatio-temporal correlation of wind-photovoltaic power generation scenarios.Finally,considering the subsequent development of new energy on demand for high-voltage distribution network peaking margin and the economy of the system peaking,we propose the optimization model of high-voltage distribution network energy storage plant siting and capacity setting for source-storage cooperative peaking.The simulation results show that the proposed energy storage plant planning method can effectively alleviate the branch circuit blockage,promote new energy consumption,reduce the burden of the main grid peak shifting,and leave sufficient peak shifting margin for the subsequent development of a new energy distribution network while ensuring the economy.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
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
Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN ...Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN planning remains a challenge,especially in scenarios where traditional search algorithms struggle to navigate the vast solution space efficiently.This research proposes a novel technique to enhance HTN planning by integrating the Ant Colony Optimization(ACO)algorithm into the refinement process.The Ant System algorithm,inspired by the foraging behavior of ants,is well-suited for addressing optimization problems by efficiently exploring solution spaces.By incorporating ACO into the refinement phase of HTN planning,the authors aim to leverage its adaptive nature and decentralized decision-making to improve plan generation.This paper involves the development of a hybrid strategy called ACO-HTN,which combines HTN planning with ACO-based plan selection.This technique enables the system to adaptively refine plans by guiding the search towards optimal solutions.To evaluate the effectiveness of the proposed technique,this paper conducts empirical experiments on various domains and benchmark datasets.Our results demonstrate that the ACO-HTN strategy enhances the efficiency and effectiveness of HTN planning,outperforming traditional methods in terms of solution quality and computational performance.展开更多
This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to minimize the overall digiti...This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to minimize the overall digitization time while considering various constraints and process dependencies. The book digitization process involves three key steps: cutting, scanning, and binding. Each step has specific requirements and limitations such as the number of pages that can be processed simultaneously and potential bottlenecks. To address these complexities, we formulate the problem as a one-machine job shop scheduling problem with additional constraints to capture the unique characteristics of book digitization. We conducted a series of experiments to evaluate the performance of our proposed approach. By comparing the optimized schedules with the baseline approach, we demonstrated significant reductions in the overall processing time. In addition, we analyzed the impact of different weighting schemes on the optimization results, highlighting the importance of identifying and prioritizing critical processes. Our findings suggest that MIP-based optimization can be a valuable tool for improving the efficiency of individual work schedules, even in seemingly simple tasks, such as book digitization. By carefully considering specific constraints and objectives, we can save time and leverage resources by carefully considering specific constraints and objectives.展开更多
BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonanc...BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonance imaging(MRI),although helpful,fail to provide three-dimensional(3D)relationships of these structures,which are critical for planning and executing complicated surgeries.AIM To explore the use of 3D imaging and virtual surgical planning(VSP)technologies to improve surgical accuracy,reduce complications,and enhance patient recovery in hepatobiliary surgeries.METHODS A comprehensive review of studies published between 2017 and 2024 was conducted through PubMed,Scopus,Google Scholar,and Web of Science.Studies selected focused on 3D imaging and VSP applications in hepatobiliary surgery,assessing surgical precision,complications,and patient outcomes.Thirty studies,including randomized controlled trials,cohort studies,and case reports,were included in the final analysis.RESULTS Various 3D imaging modalities,including multidetector CT,MRI,and 3D rotational angiography,provide high-resolution views of the liver’s vascular and biliary anatomy.VSP allows surgeons to simulate complex surgeries,improving preoperative planning and reducing complications like bleeding and bile leaks.Several studies have demonstrated improved surgical precision,reduced complications,and faster recovery times when 3D imaging and VSP were used in complex surgeries.CONCLUSION 3D imaging and VSP technologies significantly enhance the accuracy and outcomes of hepatobiliary surgeries by providing individualized preoperative planning.While promising,further research,particularly randomized controlled trials,is needed to standardize protocols and evaluate long-term efficacy.展开更多
The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertai...The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertainties. This study identifies 20 complexity factors through expert interviews and literature, categorising them into six groups. The Analytical Hierarchy Process evaluated the significance of different factors, establishing their corresponding weights to enhance adaptive project scheduling. A system dynamics (SD) model is developed and tested to evaluate the dynamic behaviour of identified complexity factors. The model simulates the impact of complexity on total project duration (TPD), revealing significant deviations from initial deterministic estimates. Data collection and analysis for reliability tests, including normality and Cronbach alpha, to validate the model’s components and expert feedback. Sensitivity analysis confirmed a positive relationship between complexity and project duration, with higher complexity levels resulting in increased TPD. This relationship highlights the inadequacy of static planning approaches and underscores the importance of addressing complexity dynamically. The study provides a framework for enhancing planning systems through system dynamics and recommends expanding the model to ensure broader applicability in diverse construction projects.展开更多
Spanish scholars decode China’s five-year planning as a strategic governance model that ensures long-term national development through continuity,popular participation,and adaptability,offering valuable insights for ...Spanish scholars decode China’s five-year planning as a strategic governance model that ensures long-term national development through continuity,popular participation,and adaptability,offering valuable insights for global governance.展开更多
Based on the outcome-based education concept,the integrated teaching of professional courses for land space planning in the human geography and urban and rural planning majors was reformed and practiced.Focusing on th...Based on the outcome-based education concept,the integrated teaching of professional courses for land space planning in the human geography and urban and rural planning majors was reformed and practiced.Focusing on the fundamental task of“establishing morality and cultivating people,”the reform of the teaching mode was proposed to clarify the industry needs,revise and improve the training program and teaching syllabus,innovate the teaching mode,and optimize the practical teaching resources and conditions.A new“multi-dimensional,interactive,and three-dimensional”teaching mode was constructed,and the integrated teaching method of enterprise projects,professional internships,and scientific research training was innovated,realizing the talent training mechanism of“demand-driven and integration of industry and education.”展开更多
Effective forest regeneration is essential for sustainable forestry practices.In Sweden,mechanical site preparation and manual planting is the dominating method,but sourcing labour for the physically demanding work is...Effective forest regeneration is essential for sustainable forestry practices.In Sweden,mechanical site preparation and manual planting is the dominating method,but sourcing labour for the physically demanding work is difficult.An autonomous scarifying and planting system(Autoplant)could meet the requirements of the forest industry and,for this,a tool for regeneration planning and routing is needed.The tool,Pathfinder,plans the regeneration and routes based on the harvested production(hpr)files,soil moisture and parent material maps,no-go areas(for culture or nature conservation),digital elevation models(DEM),and machine data(e.g.,working width,critical slope,time taken for different turn angles).The overall planting solution is either a set of capacity constrained routes or a continuous route and could be used for any planting machine as well as for traditional scarifiers as disc trenchers or mounders pulled by forwarders.Pathfinder was tested on eleven regeneration areas throughout Sweden,both with continuous routes and routes based on a carrying capacity of 1500 seedlings.The net operation area,species and seedling density suggestions were deemed relevant by expert judgement in the field.The routes provided by Pathfinder were compared with solutions given by two experienced drivers and a third solution based on the actual soil scarification at the site.Total driving distance did not differ significantly between the suggestions,but Pathfinder included less side-slope driving on steep slopes(≥27%or 15°)and medium slopes(15–27%).The chosen threshold value for steep slopes(where side-slope driving should be avoided)affects the routing,and a lower threshold means more turning and longer driving distance.Pathfinder is not only a tool for routing of planting machines,but also helps in planning of traditional regeneration by providing a more correct net area and tree species suggestions based on the growth of the previous stand.It also diminishes the risk of severe soil disturbance by excluding the wettest area in the planning.展开更多
Rational laboratory layout design and scientific management systems are key to improving overall laboratory efficiency and safety,providing a solid foundation and guarantee for the smooth progress of scientific resear...Rational laboratory layout design and scientific management systems are key to improving overall laboratory efficiency and safety,providing a solid foundation and guarantee for the smooth progress of scientific research.This article addresses a series of issues such as low testing efficiency caused by unreasonable laboratory layouts,incomplete or outdated equipment configurations affecting testing accuracy,and safety hazards arising from the lack of effective laboratory management systems.It conducts an in-depth exploration of the design and planning strategies for physicochemical laboratories.By proposing specific designs and guidelines for the location selection,functional zoning,and layout requirements of physicochemical laboratories,the aim is to optimize laboratory space utilization,enhance testing efficiency,and ensure the advancement of equipment configurations and the accuracy of testing precision.Simultaneously,it emphasizes the establishment of an effective laboratory management system to prevent and control safety hazards,safeguarding the lives of laboratory personnel and ensuring stable laboratory operations.展开更多
Today city planners are confronted with two global trends:on one hand,living space is getting less due to urbanization;on the other hand,demands on living space are constantly rising as for example through stricter cl...Today city planners are confronted with two global trends:on one hand,living space is getting less due to urbanization;on the other hand,demands on living space are constantly rising as for example through stricter climate and energy political objectives based on the Paris Agreement.Therefore,it will be necessary to take into account—near urban planning and social aspects—also the climate compatibility as one central aspect in the construction of buildings,settlements,districts or neighborhoods.To identify and to push successful concepts,Austria has developed a planning tool that allows planning,assessing and ensuring high quality standards of neighborhoods.As the tool has been highly successful,additional planning tools are being developed for specific topics such as“PED—Positive Energy Districts”,“NEB—New European Bauhaus”and“CND—Climate Neutral Districts”.Central quantitative and qualitative criteria—which have been elaborated in the recent years—will be presented in this paper.展开更多
Objective:This study aimed to describe the implementation of advance care planning(ACP)in patients with stroke.Methods:A scoping review was conducted according to the Arksey and O'Malley framework.Accordingly,we s...Objective:This study aimed to describe the implementation of advance care planning(ACP)in patients with stroke.Methods:A scoping review was conducted according to the Arksey and O'Malley framework.Accordingly,we searched for articles published in ScienceDirect,PubMed,Scopus,ProQuest,and Medline.The inclusion criteria were original research on ACP among adult or elderly stroke patients,hospital-or community-based studies,and those published in English or Indonesian.Qualitative analysis was then used to identify keywords,categories,and themes.Results:Among the 1,050 articles identified,only 8 satisfied the inclusion criteria,indicating that limited studies were available for ACP interventions among stroke patients.Four themes were ultimately identified:the strategy implementation of AC,the challenges of ACP implementation,the benefits of ACP,and the factors influencing ACP.Strategy ACP implementation included the ACP method,the communication style,participation role,media used,and ACP documentation.Lack of information about ACP,facilities,incapacitated patients,and reluctance to implement have become challenges to implementation in stroke.The benefits of ACP,particularly the outcomes of the ACP program,included awareness of ACP engagement,patients can express their wishes,and increased advance directive(AD)documentation.The factors influencing ACP included patient condition,knowledge,and appropriate ACP methods.Conclusion:ACP has not been widely used when providing interventions for stroke patients.The implementation of ACP in stroke patients is full of challenges due to various patient conditions.Effective strategies are needed to improve ACP in stroke patients.It is necessary to develop an ACP for stroke patients'method that involves interprofessional collaboration,and studies on AcP in stroke patients need to be further conducted through interprofessional collaboration.展开更多
The world is being swept by the wave of smart cities,and Geographic Information System(GIS)technology plays a key role in it.This article explores the application status and development trend of GIS technology in urba...The world is being swept by the wave of smart cities,and Geographic Information System(GIS)technology plays a key role in it.This article explores the application status and development trend of GIS technology in urban planning from the perspective of smart cities.By sorting out the application value of GIS in urban strategic layout,multi system collaboration,and precise services,it explains the necessity of promoting the transformation of planning towards intelligence.We have summarized and organized the practical points of GIS in areas such as overall planning,underground space,landscape,and transportation,including spatial simulation,3D management,ecological integration,and dynamic optimization.Looking ahead to the future,the cross integration of GIS with artificial intelligence,3D modeling,carbon neutrality monitoring,data collaboration,and other technologies will drive planning towards a new stage of development that is more intelligent,refined,open,and green.With the empowerment of GIS,we aim to create sustainable cities that are resilient,low-carbon,and inclusive,making urban life better.展开更多
基金supported by the National Key R&D Program of China(No.2022YFB3104502)the National Natural Science Foundation of China(No.62301251)+2 种基金the Natural Science Foundation of Jiangsu Province of China under Project(No.BK20220883)the open research fund of National Mobile Communications Research Laboratory,Southeast University,China(No.2024D04)the Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001).
文摘The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.
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.
基金funded by the Technology Project of State Grid Jibei Electric Power Supply Co.,Ltd.(Grant Number:52018F240001).
文摘As the development of new power systems accelerates and the impacts of high renewable energy integration and extreme weather intensify,grid-alternative energy storage is garnering increasing attention for its grid-interaction benefits and clear business models.Consequently,assessing the value of grid-alternative energy storage in the systemtransition has become critically important.Considering the performance characteristics of storage,we propose a value assessment frame-work for grid-alternative energy storage,quantifying its non-wires-alternative effects from both cost and benefit perspectives.Building on this,we developed a collaborative planning model for energy storage and transmission grids,aimed at maximizing the economic benefits of storage systems while balancing investment and operational costs.The model considers regional grid interconnections and their interactions with system operation.By participating in system operations,grid-alternative energy storage not only maximizes its own economic benefits but also generates social welfare transfer effects.Furthermore,based on multi-regional interconnected planning,grid-alternative energy storage can reduce system costs by approximately 35%,with the most significant changes observed in generation costs.Multi-regional coordinated planning significantly enhances the sys-tem’s flexibility in regulation.However,when the load factor of interconnection lines between regions remains constant,system operational flexibility tends to decrease,leading to a roughly 28.9%increase in storage investment.Additionally,under regional coordinated planning,the greater the disparity in wind power integration across interconnected regions,the more noticeable the reduction in system costs.
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.
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 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 by State Grid Anhui Electric Power Co.,Ltd.Research Program(B3120923000C).
文摘To adapt to the uncertainty of new energy,increase new energy consumption,and reduce carbon emissions,a high-voltage distribution network energy storage planning model based on robustness-oriented planning and distributed new energy consumption is proposed.Firstly,the spatio-temporal correlation of large-scale wind-photovoltaic energy is modeled based on the Vine Copula model,and the spatial correlation of the generated wind-photovoltaic power generation is corrected to get the spatio-temporal correlation of wind-photovoltaic power generation scenarios.Finally,considering the subsequent development of new energy on demand for high-voltage distribution network peaking margin and the economy of the system peaking,we propose the optimization model of high-voltage distribution network energy storage plant siting and capacity setting for source-storage cooperative peaking.The simulation results show that the proposed energy storage plant planning method can effectively alleviate the branch circuit blockage,promote new energy consumption,reduce the burden of the main grid peak shifting,and leave sufficient peak shifting margin for the subsequent development of a new energy distribution network while ensuring the economy.
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.
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 Ministry of Science and High Education of the Russian Federation by the grant 075-15-2022-1137supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R323),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN planning remains a challenge,especially in scenarios where traditional search algorithms struggle to navigate the vast solution space efficiently.This research proposes a novel technique to enhance HTN planning by integrating the Ant Colony Optimization(ACO)algorithm into the refinement process.The Ant System algorithm,inspired by the foraging behavior of ants,is well-suited for addressing optimization problems by efficiently exploring solution spaces.By incorporating ACO into the refinement phase of HTN planning,the authors aim to leverage its adaptive nature and decentralized decision-making to improve plan generation.This paper involves the development of a hybrid strategy called ACO-HTN,which combines HTN planning with ACO-based plan selection.This technique enables the system to adaptively refine plans by guiding the search towards optimal solutions.To evaluate the effectiveness of the proposed technique,this paper conducts empirical experiments on various domains and benchmark datasets.Our results demonstrate that the ACO-HTN strategy enhances the efficiency and effectiveness of HTN planning,outperforming traditional methods in terms of solution quality and computational performance.
文摘This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to minimize the overall digitization time while considering various constraints and process dependencies. The book digitization process involves three key steps: cutting, scanning, and binding. Each step has specific requirements and limitations such as the number of pages that can be processed simultaneously and potential bottlenecks. To address these complexities, we formulate the problem as a one-machine job shop scheduling problem with additional constraints to capture the unique characteristics of book digitization. We conducted a series of experiments to evaluate the performance of our proposed approach. By comparing the optimized schedules with the baseline approach, we demonstrated significant reductions in the overall processing time. In addition, we analyzed the impact of different weighting schemes on the optimization results, highlighting the importance of identifying and prioritizing critical processes. Our findings suggest that MIP-based optimization can be a valuable tool for improving the efficiency of individual work schedules, even in seemingly simple tasks, such as book digitization. By carefully considering specific constraints and objectives, we can save time and leverage resources by carefully considering specific constraints and objectives.
文摘BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonance imaging(MRI),although helpful,fail to provide three-dimensional(3D)relationships of these structures,which are critical for planning and executing complicated surgeries.AIM To explore the use of 3D imaging and virtual surgical planning(VSP)technologies to improve surgical accuracy,reduce complications,and enhance patient recovery in hepatobiliary surgeries.METHODS A comprehensive review of studies published between 2017 and 2024 was conducted through PubMed,Scopus,Google Scholar,and Web of Science.Studies selected focused on 3D imaging and VSP applications in hepatobiliary surgery,assessing surgical precision,complications,and patient outcomes.Thirty studies,including randomized controlled trials,cohort studies,and case reports,were included in the final analysis.RESULTS Various 3D imaging modalities,including multidetector CT,MRI,and 3D rotational angiography,provide high-resolution views of the liver’s vascular and biliary anatomy.VSP allows surgeons to simulate complex surgeries,improving preoperative planning and reducing complications like bleeding and bile leaks.Several studies have demonstrated improved surgical precision,reduced complications,and faster recovery times when 3D imaging and VSP were used in complex surgeries.CONCLUSION 3D imaging and VSP technologies significantly enhance the accuracy and outcomes of hepatobiliary surgeries by providing individualized preoperative planning.While promising,further research,particularly randomized controlled trials,is needed to standardize protocols and evaluate long-term efficacy.
文摘The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertainties. This study identifies 20 complexity factors through expert interviews and literature, categorising them into six groups. The Analytical Hierarchy Process evaluated the significance of different factors, establishing their corresponding weights to enhance adaptive project scheduling. A system dynamics (SD) model is developed and tested to evaluate the dynamic behaviour of identified complexity factors. The model simulates the impact of complexity on total project duration (TPD), revealing significant deviations from initial deterministic estimates. Data collection and analysis for reliability tests, including normality and Cronbach alpha, to validate the model’s components and expert feedback. Sensitivity analysis confirmed a positive relationship between complexity and project duration, with higher complexity levels resulting in increased TPD. This relationship highlights the inadequacy of static planning approaches and underscores the importance of addressing complexity dynamically. The study provides a framework for enhancing planning systems through system dynamics and recommends expanding the model to ensure broader applicability in diverse construction projects.
文摘Spanish scholars decode China’s five-year planning as a strategic governance model that ensures long-term national development through continuity,popular participation,and adaptability,offering valuable insights for global governance.
文摘Based on the outcome-based education concept,the integrated teaching of professional courses for land space planning in the human geography and urban and rural planning majors was reformed and practiced.Focusing on the fundamental task of“establishing morality and cultivating people,”the reform of the teaching mode was proposed to clarify the industry needs,revise and improve the training program and teaching syllabus,innovate the teaching mode,and optimize the practical teaching resources and conditions.A new“multi-dimensional,interactive,and three-dimensional”teaching mode was constructed,and the integrated teaching method of enterprise projects,professional internships,and scientific research training was innovated,realizing the talent training mechanism of“demand-driven and integration of industry and education.”
基金funded by Vinnova,the Swedish Innovation Agency as a part of the Autoplant project(Dnr 2020-04202 and 2023-02747).
文摘Effective forest regeneration is essential for sustainable forestry practices.In Sweden,mechanical site preparation and manual planting is the dominating method,but sourcing labour for the physically demanding work is difficult.An autonomous scarifying and planting system(Autoplant)could meet the requirements of the forest industry and,for this,a tool for regeneration planning and routing is needed.The tool,Pathfinder,plans the regeneration and routes based on the harvested production(hpr)files,soil moisture and parent material maps,no-go areas(for culture or nature conservation),digital elevation models(DEM),and machine data(e.g.,working width,critical slope,time taken for different turn angles).The overall planting solution is either a set of capacity constrained routes or a continuous route and could be used for any planting machine as well as for traditional scarifiers as disc trenchers or mounders pulled by forwarders.Pathfinder was tested on eleven regeneration areas throughout Sweden,both with continuous routes and routes based on a carrying capacity of 1500 seedlings.The net operation area,species and seedling density suggestions were deemed relevant by expert judgement in the field.The routes provided by Pathfinder were compared with solutions given by two experienced drivers and a third solution based on the actual soil scarification at the site.Total driving distance did not differ significantly between the suggestions,but Pathfinder included less side-slope driving on steep slopes(≥27%or 15°)and medium slopes(15–27%).The chosen threshold value for steep slopes(where side-slope driving should be avoided)affects the routing,and a lower threshold means more turning and longer driving distance.Pathfinder is not only a tool for routing of planting machines,but also helps in planning of traditional regeneration by providing a more correct net area and tree species suggestions based on the growth of the previous stand.It also diminishes the risk of severe soil disturbance by excluding the wettest area in the planning.
文摘Rational laboratory layout design and scientific management systems are key to improving overall laboratory efficiency and safety,providing a solid foundation and guarantee for the smooth progress of scientific research.This article addresses a series of issues such as low testing efficiency caused by unreasonable laboratory layouts,incomplete or outdated equipment configurations affecting testing accuracy,and safety hazards arising from the lack of effective laboratory management systems.It conducts an in-depth exploration of the design and planning strategies for physicochemical laboratories.By proposing specific designs and guidelines for the location selection,functional zoning,and layout requirements of physicochemical laboratories,the aim is to optimize laboratory space utilization,enhance testing efficiency,and ensure the advancement of equipment configurations and the accuracy of testing precision.Simultaneously,it emphasizes the establishment of an effective laboratory management system to prevent and control safety hazards,safeguarding the lives of laboratory personnel and ensuring stable laboratory operations.
文摘Today city planners are confronted with two global trends:on one hand,living space is getting less due to urbanization;on the other hand,demands on living space are constantly rising as for example through stricter climate and energy political objectives based on the Paris Agreement.Therefore,it will be necessary to take into account—near urban planning and social aspects—also the climate compatibility as one central aspect in the construction of buildings,settlements,districts or neighborhoods.To identify and to push successful concepts,Austria has developed a planning tool that allows planning,assessing and ensuring high quality standards of neighborhoods.As the tool has been highly successful,additional planning tools are being developed for specific topics such as“PED—Positive Energy Districts”,“NEB—New European Bauhaus”and“CND—Climate Neutral Districts”.Central quantitative and qualitative criteria—which have been elaborated in the recent years—will be presented in this paper.
基金funded by the Center for Education Financial Service(Puslapdik)and the Indonesia Endowment Fund for Education(LPDP)(Grant number:02651/J5.2.3/BPI.06/9/2022).
文摘Objective:This study aimed to describe the implementation of advance care planning(ACP)in patients with stroke.Methods:A scoping review was conducted according to the Arksey and O'Malley framework.Accordingly,we searched for articles published in ScienceDirect,PubMed,Scopus,ProQuest,and Medline.The inclusion criteria were original research on ACP among adult or elderly stroke patients,hospital-or community-based studies,and those published in English or Indonesian.Qualitative analysis was then used to identify keywords,categories,and themes.Results:Among the 1,050 articles identified,only 8 satisfied the inclusion criteria,indicating that limited studies were available for ACP interventions among stroke patients.Four themes were ultimately identified:the strategy implementation of AC,the challenges of ACP implementation,the benefits of ACP,and the factors influencing ACP.Strategy ACP implementation included the ACP method,the communication style,participation role,media used,and ACP documentation.Lack of information about ACP,facilities,incapacitated patients,and reluctance to implement have become challenges to implementation in stroke.The benefits of ACP,particularly the outcomes of the ACP program,included awareness of ACP engagement,patients can express their wishes,and increased advance directive(AD)documentation.The factors influencing ACP included patient condition,knowledge,and appropriate ACP methods.Conclusion:ACP has not been widely used when providing interventions for stroke patients.The implementation of ACP in stroke patients is full of challenges due to various patient conditions.Effective strategies are needed to improve ACP in stroke patients.It is necessary to develop an ACP for stroke patients'method that involves interprofessional collaboration,and studies on AcP in stroke patients need to be further conducted through interprofessional collaboration.
文摘The world is being swept by the wave of smart cities,and Geographic Information System(GIS)technology plays a key role in it.This article explores the application status and development trend of GIS technology in urban planning from the perspective of smart cities.By sorting out the application value of GIS in urban strategic layout,multi system collaboration,and precise services,it explains the necessity of promoting the transformation of planning towards intelligence.We have summarized and organized the practical points of GIS in areas such as overall planning,underground space,landscape,and transportation,including spatial simulation,3D management,ecological integration,and dynamic optimization.Looking ahead to the future,the cross integration of GIS with artificial intelligence,3D modeling,carbon neutrality monitoring,data collaboration,and other technologies will drive planning towards a new stage of development that is more intelligent,refined,open,and green.With the empowerment of GIS,we aim to create sustainable cities that are resilient,low-carbon,and inclusive,making urban life better.
