Servicing is applied periodically in practice with the aim of restoring the system state and prolonging the lifetime. It is generally seen as an imperfect maintenance action which has a chief influence on the maintena...Servicing is applied periodically in practice with the aim of restoring the system state and prolonging the lifetime. It is generally seen as an imperfect maintenance action which has a chief influence on the maintenance strategy. In order to model the maintenance effect of servicing, this study analyzes the deterioration characteristics of system under scheduled servicing. And then the deterioration model is established from the failure mechanism by compound Poisson process. On the basis of the system damage value and failure mechanism, the failure rate refresh factor is proposed to describe the maintenance effect of servicing. A maintenance strategy is developed which combines the benefits of scheduled servicing and preventive maintenance. Then the optimization model is given to determine the optimal servicing period and preventive maintenance time, with an objective to minimize the system expected life-cycle cost per unit time and a constraint on system survival probability for the duration of mission time. Subject to mission time, it can control the ability of accomplishing the mission at any time so as to ensure the high dependability. An example of water pump rotor relating to scheduled servicing is introduced to illustrate the failure rate refresh factor and the proposed maintenance strategy. Compared with traditional methods, the numerical results show that the failure rate refresh factor can describe the maintenance effect of servicing more intuitively and objectively. It also demonstrates that this maintenance strategy can prolong the lifetime, reduce the total lifetime maintenance cost and guarantee the dependability of system.展开更多
This paper deals with a type of servicing machines model, which service station has a life time of the kth Er-langian distribution and can be repaired just like a new one. The cyclic time and the inefficiency quantiti...This paper deals with a type of servicing machines model, which service station has a life time of the kth Er-langian distribution and can be repaired just like a new one. The cyclic time and the inefficiency quantities of this system in equilibrium are obtained.展开更多
Effectiveness-based system development is an essential technology developing concept advanced by some countries,such as the U.S.A.Making use of Analytic Hierarchy Process,this paper brings forward a methodology for or...Effectiveness-based system development is an essential technology developing concept advanced by some countries,such as the U.S.A.Making use of Analytic Hierarchy Process,this paper brings forward a methodology for orbital optimization based on effectiveness in the case of the orbital deployment for the Servicing Spacecraft(SSC),which needs to accomplish many types of tasks and whose orbit is affected by kinds of factors with contradictions in orbital parameter selection.Firstly,the possible tasks of SSC are decomposed and their degrees of importance are given by the times,probabilities,values of their applications.Then,the supporting capabilities are discussed from the viewpoint of orbit design,and the determination of their weights is put forward.Finally,the relationships between the orbital parameters and the effectiveness are established by using effective function,and three synthesizing methods for a single task and its capabilities are presented.展开更多
On-orbit servicing, such as spacecraft maintenance, on-orbit assembly, refueling, and de-orbiting, can reduce the cost of space missions, improve the performance of spacecraft, and extend its life span. The relative s...On-orbit servicing, such as spacecraft maintenance, on-orbit assembly, refueling, and de-orbiting, can reduce the cost of space missions, improve the performance of spacecraft, and extend its life span. The relative state between the servicing and target spacecraft is vital for on-orbit servicing missions, especially the final approaching stage. The major challenge of this stage is that the observed features of the target are incomplete or are constantly changing due to the short distance and limited Field of View (FOV) of camera. Different from cooperative spacecraft, non-cooperative target does not have artificial feature markers. Therefore, contour features, including triangle supports of solar array, docking ring, and corner points of the spacecraft body, are used as the measuring features. To overcome the drawback of FOV limitation and imaging ambiguity of the camera, a "selfie stick" structure and a self-calibration strategy were implemented, ensuring that part of the contour features could be observed precisely when the two spacecraft approached each other. The observed features were constantly changing as the relative distance shortened. It was difficult to build a unified measurement model for different types of features, including points, line segments, and circle. Therefore, dual quaternion was implemented to model the relative dynamics and measuring features. With the consideration of state uncertainty of the target, a fuzzy adaptive strong tracking filter( FASTF) combining fuzzy logic adaptive controller (FLAC) with strong tracking filter(STF) was designed to robustly estimate the relative states between the servicing spacecraft and the target. Finally, the effectiveness of the strategy was verified by mathematical simulation. The achievement of this research provides a theoretical and technical foundation for future on-orbit servicing missions.展开更多
Randomization-based motion planning algorithms are presented to solve problems of servicing spacecraft maneuvering in proximity to servicing targets on an elliptical orbit.The feasible trajectories of position and att...Randomization-based motion planning algorithms are presented to solve problems of servicing spacecraft maneuvering in proximity to servicing targets on an elliptical orbit.The feasible trajectories of position and attitude for spacecraft are obtained by these algorithms under a variety of constraints.The state transition matrix is applied to computation of relative motion on elliptical orbits without performing numerical integration.The pseudo body coordinate system is built for identifying the planners on three coordinate axes with different functions.Finally,motion planning algorithm for translation and attitude taking account of the dependent variable (i.e.time) is used to obtain feasible trajectories.As the simulation examples indicate,the effectiveness of these methods is verified for relative motion while getting close to large structures,and the paper concludes with a detailed analysis of the results.展开更多
The multi-body dynamics in the launch process of a space platform deploying a server,as well as the optimal double impulse rendezvous guidance law between the server and the target spacecraft,are studied.Firstly,the s...The multi-body dynamics in the launch process of a space platform deploying a server,as well as the optimal double impulse rendezvous guidance law between the server and the target spacecraft,are studied.Firstly,the space platform enters into orbit around the target,keeping its launch tube axis aiming at it.After receiving the launch command,the server shoots out from the launch tube,flying to the target.Due to body coupling,the platform’s attitude is disturbed,preventing the server from accurately aiming at the target during separation.The server uses its small rocket engine to apply two velocity pulses:the first one to adjust its trajectory for rendezvous,and the second near the target to reduce relative velocity to zero for soft docking.A two-body dynamics model is established using the Newton-Euler method,and a virtual prototype is developed in ADAMS for validation.To solve the multi-objective optimization subject to energy consumption and flight time for rendezvous,an improved non-dominated sorting genetic algorithm II(NSGA-II)algorithm is proposed.Simulation results show that launch-induced perturbations are non-negligible,and the proposed algorithm effectively derives the optimal guidance law that balances energy use and flight time.展开更多
The increasing demand for on-orbit servicing(OOS)tasks,such as satellite repair,space debris removal,refueling,and upgrades,has driven the need for advanced robotic systems capable of autonomous and precise operations...The increasing demand for on-orbit servicing(OOS)tasks,such as satellite repair,space debris removal,refueling,and upgrades,has driven the need for advanced robotic systems capable of autonomous and precise operations in space.At the core of these tasks are unmanned spacecraft equipped with robotic manipulators designed to execute critical capture and manipulation maneuvers.This paper presents a comprehensive review of space robotic missions and methodologies for effective OOS and space debris removal.It examines control strategies applied across different phases of these missions,with a focus on their implementation in 2 operational modes:free-floating and free-flying.Detailed discussions are provided on methodologies for the pre-capture phase,covering both motion planning and vision-based estimation.For the post-capture phase,the paper explores control methods designed to stabilize captured targets.Additionally,it investigates ground verification experiments,which are crucial for validating the performance of space robots under microgravity-like conditions.These experiments yield valuable insights into the dynamic behavior of space robotic systems and play an important role in advancing space robotics research.By consolidating recent advancements and identifying key technological gaps,this review highlights future research directions aimed at improving the reliability,adaptability,and safety of robotic manipulators in addressing the challenges of OOS and space debris removal.展开更多
Recently,with the rapid development of aerospace technology,an increasing number of spacecraft is being launched into space.Additionally,the demands for on-orbit servicing(OOS)missions are rapidly increasing.Space rob...Recently,with the rapid development of aerospace technology,an increasing number of spacecraft is being launched into space.Additionally,the demands for on-orbit servicing(OOS)missions are rapidly increasing.Space robotics is one of the most promising approaches for various OOS missions;thus,research on space robotics technologies for OOS has attracted increased attention from space agencies and universities worldwide.In this paper,we review the structures,ground verification,and onorbit kinematics calibration technologies of space robotic systems for OOS.First,we systematically summarize the development of space robotic systems and OOS programs based on space robotics.Then,according to the structures and applications,these systems are divided into three categories:large space manipulators,humanoid space robots,and small space manipulators.According to the capture mechanisms adopted,the end-effectors are systematically analyzed.Furthermore,the ground verification facilities used to simulate a microgravity environment are summarized and compared.Additionally,the on-orbit kinematics calibration technologies are discussed and analyzed compared with the kinematics calibration technologies of industrial manipulators with regard to four aspects.Finally,the development trends of the structures,verification,and calibration technologies are discussed to extend this review work.展开更多
This review paper presents a comprehensive evaluation and forward-looking perspective on the underexplored topic of servicing target objects using spacecraft swarms.Such targets can be known or unknown,cooperative or ...This review paper presents a comprehensive evaluation and forward-looking perspective on the underexplored topic of servicing target objects using spacecraft swarms.Such targets can be known or unknown,cooperative or uncooperative,and pose significant challenges in modern space operations due to their inherent complexity and unpredictability.Successfully servicing space objects is vital for active debris removal and broader on-orbit servicing tasks such as satellite maintenance,repair,refueling,orbital assembly,and construction.Significant effort has been invested in the literature to explore the servicing of targets using a single spacecraft.Given its advantages and benefits,this paper expands the discussion to encompass a swarm approach to the problem.This review covers various single-spacecraft approaches and presents a critical examination of the existing,although limited,body of work dedicated to servicing orbital objects using multiple spacecraft.The focus is also broadened to include some influential studies concerning the characterization,capture,and manipulation of physical objects by general multiagent systems,a subject with significant parallels to the core interest of this manuscript.Furthermore,this article also delves into the realm of simultaneous localization and mapping,highlighting its application within close-proximity operations in space,especially when dealing with unknown uncooperative targets.Special attention is paid to the benefits that this field can receive from distributed multiagent architectures.Finally,an exploration of the promising field of swarm robotics is presented,with an emphasis on its potential to revolutionize the servicing of orbital target objects.Concurrently,a survey of general research directly engaging swarms in the orbital context is conducted.This review aims to bridge the knowledge gap and stimulate further research in the underexplored domain of servicing space targets with spacecraft swarms.展开更多
Amazon Web Services(AWS)Cloud Trail auditing service provides detailed records of operational and security events,enabling cloud administrators to monitor user activity and manage compliance.Although signaturebased th...Amazon Web Services(AWS)Cloud Trail auditing service provides detailed records of operational and security events,enabling cloud administrators to monitor user activity and manage compliance.Although signaturebased threat detection methods have been enhanced with machine learning and Large Language Models(LLMs),these approaches remain limited in addressing emerging threats.This study evaluates a two-step Retrieval Augmented Generation(RAG)approach using Gemini 2.5 Pro to enhance threat detection accuracy and contextual relevance.The RAG system integrates external cybersecurity knowledge sources including the MITRE ATT&CK framework,AWS Threat Technique Catalogue,and threat reports to overcome limitations of static pre-trained LLMs.We constructed an evaluation dataset of 200 unique CloudTrail events(122 malicious,78 benign)using the Stratus Red Team adversary emulation framework,covering 9 MITRE ATT&CK techniques across 8 tactics.Events were sampled from 1724 total events using stratified sampling.Ground truth labels were created through systematic expert annotation with 90%inter-annotator agreement.The RAG-enabled model achieved estimated 78%accuracy,85%precision,and 79%F1-score,representing 70.5%accuracy improvement and 76.4%F1-score improvement over baseline Gemini 2.5 Pro(46%accuracy,45%F1-score).Performance are based on evaluation results on 200-event dataset.Cost-latency analysis revealed processing time of 4.1 s and cost of$0.00376 per event,comparable to commercial SIEM solutions while providing superior MITRE ATT&CK attribution.The findings demonstrate that RAG substantially enhances context-aware threat detection,providing actionable insights for cloud security operations.展开更多
Saud Khan,a Pakistani physician,collected his work and residence permits at the Yangpu Government Service Centre in Danzhou City,Hainan Province,on 18 December 2025.Khan had arrived in Hainan three months earlier to p...Saud Khan,a Pakistani physician,collected his work and residence permits at the Yangpu Government Service Centre in Danzhou City,Hainan Province,on 18 December 2025.Khan had arrived in Hainan three months earlier to participate in a medical training programme at Hainan Western Central Hospital.By the time the programme concluded,he had made up his mind to stay and broaden his professional experience and long-term career prospects in Hainan.展开更多
Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by ...Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by the Hepatobiliary&Pancreatic Diseases International.展开更多
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ...In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.展开更多
As the sunlight scattered on the sea of Guanyinshan in Xiamen,a space that bridges creativity and industry opened its door to the world.On December 15th,following a ribbon-cutting and unveiling ceremony,YKK Xiamen Gua...As the sunlight scattered on the sea of Guanyinshan in Xiamen,a space that bridges creativity and industry opened its door to the world.On December 15th,following a ribbon-cutting and unveiling ceremony,YKK Xiamen Guanyinshan Showroom,the brand's second and largest comprehensive showroom,was officially inaugurated.This showroom is more than a product display window,it is an"Inspiration Hub"integrating exhibition,co-creation,and service.Its launch signifies YKK's progression in the Chinese market from“building an efficient product proposal system”to a new stage of“deep collaborative co-creation.”展开更多
Common mental disorders(CMDs),such as depressive and anxiety disorders,constitute a significant public health problem in low-and middle-income countries,such as India,where they rank among the leading causes of disabi...Common mental disorders(CMDs),such as depressive and anxiety disorders,constitute a significant public health problem in low-and middle-income countries,such as India,where they rank among the leading causes of disability and impaired quality of life.Outcomes are further compromised by a large treatment gap,poor adherence to therapeutic regimens,and high attrition rates.The prevalence and severity of CMDs are disproportionately higher in women.Additionally,structural factors influencing healthcare access,along with sociocultural factors,such as gender-based violence,limited autonomy in healthcare decisions,and greater levels of discrimination and stigma,result in poorer outcomes among women with CMDs.Therefore,there is a pressing need for care packages that are culturally sensitive,gender-responsive,and designed to address these structural and sociocultural factors,as highlighted in the literature from India.展开更多
Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review s...Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review synthesizes recent research and developments in the application of AI agents across core financial domains.Specifically,it covers the deployment of agent-based AI in algorithmic trading,fraud detection,credit risk assessment,roboadvisory,and regulatory compliance(RegTech).The review focuses on advanced agent-based methodologies,including reinforcement learning,multi-agent systems,and autonomous decision-making frameworks,particularly those leveraging large language models(LLMs),contrasting these with traditional AI or purely statistical models.Our primary goals are to consolidate current knowledge,identify significant trends and architectural approaches,review the practical efficiency and impact of current applications,and delineate key challenges and promising future research directions.The increasing sophistication of AI agents offers unprecedented opportunities for innovation in finance,yet presents complex technical,ethical,and regulatory challenges that demand careful consideration and proactive strategies.This review aims to provide a comprehensive understanding of this rapidly evolving landscape,highlighting the role of agent-based AI in the ongoing transformation of the financial industry,and is intended to serve financial institutions,regulators,investors,analysts,researchers,and other key stakeholders in the financial ecosystem.展开更多
Lhasa,one of the world's highest cities,confronts the challenge of harmonizing cultural heritage preservation with ecological protection.Assessing the spatiotemporal dynamics of ecosystem service value(ESV)in its ...Lhasa,one of the world's highest cities,confronts the challenge of harmonizing cultural heritage preservation with ecological protection.Assessing the spatiotemporal dynamics of ecosystem service value(ESV)in its central urban area is therefore critical for informing future urban planning and land management.This study systematically analyzed land use evolution,the spatiotemporal characteristics of ecosystem services,and ecological network construction within Lhasa's central urban area.It integrated multi-source data,including Landsat remote sensing imagery from 2000,2010,and 2023,with multiple modeling methods such as the InVEST model,MaxEnt for cultural service assessment,the Minimum Cumulative Resistance(MCR)model,and circuit theory.Based on these analyses,optimization strategies were proposed.The results indicate that from 2000 to 2023,areas of cultivated land,grassland,and water bodies decreased by 7.47%,6.85%,and 0.68%,respectively,while wetland and forest areas expanded by 1.44%and 0.64%.Construction land exhibited significant expansion(12.94%),leading to an overall ESV reduction of 462.8×10^(5)yuan.Vegetation coverage was identified as the pivotal factor influencing ESV distribution,with higher values concentrated in the Lhasa River Basin and near the Lhalu Wetland,diminishing towards the urban core.Furthermore,spatial autocorrelation analysis revealed significant positive spatial clustering,with low-low aggregation in the eastern and central regions and high-high aggregation in the Lhasa River Basin and its surrounding water bodies.Moreover,based on a comprehensive ecosystem service assessment,11 ecological source sites were identified,primarily in the southwestern mountains and northeastern foothills.A comprehensive resistance surface,incorporating factors such as elevation,Normalized Difference Vegetation Index(NDVI),and land use,facilitated the extraction of 23 potential ecological corridors totaling 124.96 km in length.Topological network analysis indicated high redundancy and connectivity;however,marginal source sites relying on single connections exhibited significant vulnerability to rupture.Additionally,the application of circuit theory identified 30 ecological pinch points(current density≥1.5 A/km^(2))and 23 obstacle points,revealing significant blockages to ecological flow along the Qinghai-Xizang Highway,within the old city,and in other areas of high-intensity human activity.To address the identified network deficiencies—‘scattered cores,fragmented corridors,and insufficient resilience’—this study proposes an optimization strategy conceptualized as‘one vein,three corridors,and multiple cores’.Recommendations for enhancing network resilience include the delineation of ecological protection red lines,the integration of plateau-adapted technologies,and the fostering of community governance mechanisms.This approach aims to provide a scientific basis for constructing an ecological security pattern and promoting sustainable development in plateau cities.Ultimately,this research contributes to the enhancement of ecological well-being in the Himalayan region.展开更多
Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for so...Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for social networks due to significant limitations.Specifically,most approaches depend mainly on user-user structural links while overlooking service-centric,semantic,and multi-attribute drivers of community formation,and they also lack flexible filtering mechanisms for large-scale,service-oriented settings.Our proposed approach,called community discovery-based service(CDBS),leverages user profiles and their interactions with consulted web services.The method introduces a novel similarity measure,global similarity interaction profile(GSIP),which goes beyond typical similarity measures by unifying user and service profiles for all attributes types into a coherent representation,thereby clarifying its novelty and contribution.It applies multiple filtering criteria related to user attributes,accessed services,and interaction patterns.Experimental comparisons against Louvain,Hierarchical Agglomerative Clustering,Label Propagation and Infomap show that CDBS reveals the higher performance as it achieves 0.74 modularity,0.13 conductance,0.77 coverage,and significantly fast response time of 9.8 s,even with 10,000 users and 400 services.Moreover,community discoverybased service consistently detects a larger number of communities with distinct topics of interest,underscoring its capacity to generate detailed and efficient structures in complex networks.These results confirm both the efficiency and effectiveness of the proposed method.Beyond controlled evaluation,communities discovery based service is applicable to targeted recommendations,group-oriented marketing,access control,and service personalization,where communities are shaped not only by user links but also by service engagement.展开更多
The Internet of Things(IoT)ecosystem is inherently heterogeneous,comprising diverse devices that must interoperate seamlessly to enable federated message and data exchange.However,as the number of service requests gro...The Internet of Things(IoT)ecosystem is inherently heterogeneous,comprising diverse devices that must interoperate seamlessly to enable federated message and data exchange.However,as the number of service requests grows,existing approaches suffer from increased discovery time and degraded Quality of Service(QoS).Moreover,the massive data generated by heterogeneous IoT devices often contain redundancy and noise,posing challenges to efficient data management.To address these issues,this paper proposes a lightweight ontology-based architecture that enhances service discovery and QoS-aware semantic data management.The architecture employs Modified-Ordered Points to Identify theClustering Structure(M-OPTICS)to cluster and eliminate redundant IoT data.The clustered data are then modelled into a lightweight ontology,enabling semantic relationship inference and rule generation through an embedded inference engine.User requests,transmitted via theConstrainedApplication Protocol(CoAP),are semantically enriched and matched to QoS parameters using Dynamic Shannon Entropy optimized with the Salp Swarm Algorithm.Semantic matching is further refined using a bidirectional recurrent neural network(Bi-RNN),while a State–Action–Reward–State–Action(SARSA)reinforcement learning model dynamically defines and updates semantic rules to retrieve themost recent and relevant data across heterogeneous devices.Experimental results demonstrate that the proposed architecture outperforms existing methods in terms of response time,service delay,execution time,precision,recall,and F-score under varying CoAP request loads and communication overheads.The results confirm the effectiveness of the proposed lightweight ontology architecture for service discovery and data management in heterogeneous IoT environments.展开更多
基金supported by the National Defence Preresearch Foundation of China(Nos.51327020105,51304010206)
文摘Servicing is applied periodically in practice with the aim of restoring the system state and prolonging the lifetime. It is generally seen as an imperfect maintenance action which has a chief influence on the maintenance strategy. In order to model the maintenance effect of servicing, this study analyzes the deterioration characteristics of system under scheduled servicing. And then the deterioration model is established from the failure mechanism by compound Poisson process. On the basis of the system damage value and failure mechanism, the failure rate refresh factor is proposed to describe the maintenance effect of servicing. A maintenance strategy is developed which combines the benefits of scheduled servicing and preventive maintenance. Then the optimization model is given to determine the optimal servicing period and preventive maintenance time, with an objective to minimize the system expected life-cycle cost per unit time and a constraint on system survival probability for the duration of mission time. Subject to mission time, it can control the ability of accomplishing the mission at any time so as to ensure the high dependability. An example of water pump rotor relating to scheduled servicing is introduced to illustrate the failure rate refresh factor and the proposed maintenance strategy. Compared with traditional methods, the numerical results show that the failure rate refresh factor can describe the maintenance effect of servicing more intuitively and objectively. It also demonstrates that this maintenance strategy can prolong the lifetime, reduce the total lifetime maintenance cost and guarantee the dependability of system.
文摘This paper deals with a type of servicing machines model, which service station has a life time of the kth Er-langian distribution and can be repaired just like a new one. The cyclic time and the inefficiency quantities of this system in equilibrium are obtained.
基金Sponsored by the National High Technology Research and Development Program of China(Grant No. 2008AA7045007)
文摘Effectiveness-based system development is an essential technology developing concept advanced by some countries,such as the U.S.A.Making use of Analytic Hierarchy Process,this paper brings forward a methodology for orbital optimization based on effectiveness in the case of the orbital deployment for the Servicing Spacecraft(SSC),which needs to accomplish many types of tasks and whose orbit is affected by kinds of factors with contradictions in orbital parameter selection.Firstly,the possible tasks of SSC are decomposed and their degrees of importance are given by the times,probabilities,values of their applications.Then,the supporting capabilities are discussed from the viewpoint of orbit design,and the determination of their weights is put forward.Finally,the relationships between the orbital parameters and the effectiveness are established by using effective function,and three synthesizing methods for a single task and its capabilities are presented.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61973153)
文摘On-orbit servicing, such as spacecraft maintenance, on-orbit assembly, refueling, and de-orbiting, can reduce the cost of space missions, improve the performance of spacecraft, and extend its life span. The relative state between the servicing and target spacecraft is vital for on-orbit servicing missions, especially the final approaching stage. The major challenge of this stage is that the observed features of the target are incomplete or are constantly changing due to the short distance and limited Field of View (FOV) of camera. Different from cooperative spacecraft, non-cooperative target does not have artificial feature markers. Therefore, contour features, including triangle supports of solar array, docking ring, and corner points of the spacecraft body, are used as the measuring features. To overcome the drawback of FOV limitation and imaging ambiguity of the camera, a "selfie stick" structure and a self-calibration strategy were implemented, ensuring that part of the contour features could be observed precisely when the two spacecraft approached each other. The observed features were constantly changing as the relative distance shortened. It was difficult to build a unified measurement model for different types of features, including points, line segments, and circle. Therefore, dual quaternion was implemented to model the relative dynamics and measuring features. With the consideration of state uncertainty of the target, a fuzzy adaptive strong tracking filter( FASTF) combining fuzzy logic adaptive controller (FLAC) with strong tracking filter(STF) was designed to robustly estimate the relative states between the servicing spacecraft and the target. Finally, the effectiveness of the strategy was verified by mathematical simulation. The achievement of this research provides a theoretical and technical foundation for future on-orbit servicing missions.
基金Sponsored by the Harbin Technological Innovative Talent Foundation (Grant No. 2008RFQXG047)
文摘Randomization-based motion planning algorithms are presented to solve problems of servicing spacecraft maneuvering in proximity to servicing targets on an elliptical orbit.The feasible trajectories of position and attitude for spacecraft are obtained by these algorithms under a variety of constraints.The state transition matrix is applied to computation of relative motion on elliptical orbits without performing numerical integration.The pseudo body coordinate system is built for identifying the planners on three coordinate axes with different functions.Finally,motion planning algorithm for translation and attitude taking account of the dependent variable (i.e.time) is used to obtain feasible trajectories.As the simulation examples indicate,the effectiveness of these methods is verified for relative motion while getting close to large structures,and the paper concludes with a detailed analysis of the results.
基金supported by the Postgraduate Research and Practice Innovation Program of Jiangsu Province(KYCX25_0587).
文摘The multi-body dynamics in the launch process of a space platform deploying a server,as well as the optimal double impulse rendezvous guidance law between the server and the target spacecraft,are studied.Firstly,the space platform enters into orbit around the target,keeping its launch tube axis aiming at it.After receiving the launch command,the server shoots out from the launch tube,flying to the target.Due to body coupling,the platform’s attitude is disturbed,preventing the server from accurately aiming at the target during separation.The server uses its small rocket engine to apply two velocity pulses:the first one to adjust its trajectory for rendezvous,and the second near the target to reduce relative velocity to zero for soft docking.A two-body dynamics model is established using the Newton-Euler method,and a virtual prototype is developed in ADAMS for validation.To solve the multi-objective optimization subject to energy consumption and flight time for rendezvous,an improved non-dominated sorting genetic algorithm II(NSGA-II)algorithm is proposed.Simulation results show that launch-induced perturbations are non-negligible,and the proposed algorithm effectively derives the optimal guidance law that balances energy use and flight time.
基金supported by the Discovery Grant(RGPIN-2024-06290)the Collaborative Research and Training Experience Program Grant—SMART-ART(555425-2021)of the Natural Sciences and Engineering Research Council of Canada.
文摘The increasing demand for on-orbit servicing(OOS)tasks,such as satellite repair,space debris removal,refueling,and upgrades,has driven the need for advanced robotic systems capable of autonomous and precise operations in space.At the core of these tasks are unmanned spacecraft equipped with robotic manipulators designed to execute critical capture and manipulation maneuvers.This paper presents a comprehensive review of space robotic missions and methodologies for effective OOS and space debris removal.It examines control strategies applied across different phases of these missions,with a focus on their implementation in 2 operational modes:free-floating and free-flying.Detailed discussions are provided on methodologies for the pre-capture phase,covering both motion planning and vision-based estimation.For the post-capture phase,the paper explores control methods designed to stabilize captured targets.Additionally,it investigates ground verification experiments,which are crucial for validating the performance of space robots under microgravity-like conditions.These experiments yield valuable insights into the dynamic behavior of space robotic systems and play an important role in advancing space robotics research.By consolidating recent advancements and identifying key technological gaps,this review highlights future research directions aimed at improving the reliability,adaptability,and safety of robotic manipulators in addressing the challenges of OOS and space debris removal.
基金the National Key R&D Program of China(Grant No.2017YFB1300400)the National Natural Science Foundation of China(Grant Nos.91748201 and 51775011)Beijing Natural Science Foundation(Gran No.3192017)。
文摘Recently,with the rapid development of aerospace technology,an increasing number of spacecraft is being launched into space.Additionally,the demands for on-orbit servicing(OOS)missions are rapidly increasing.Space robotics is one of the most promising approaches for various OOS missions;thus,research on space robotics technologies for OOS has attracted increased attention from space agencies and universities worldwide.In this paper,we review the structures,ground verification,and onorbit kinematics calibration technologies of space robotic systems for OOS.First,we systematically summarize the development of space robotic systems and OOS programs based on space robotics.Then,according to the structures and applications,these systems are divided into three categories:large space manipulators,humanoid space robots,and small space manipulators.According to the capture mechanisms adopted,the end-effectors are systematically analyzed.Furthermore,the ground verification facilities used to simulate a microgravity environment are summarized and compared.Additionally,the on-orbit kinematics calibration technologies are discussed and analyzed compared with the kinematics calibration technologies of industrial manipulators with regard to four aspects.Finally,the development trends of the structures,verification,and calibration technologies are discussed to extend this review work.
基金supported by the Discovery Grant(RGPIN-2018-05991)Collaborative Research and Training Experience Program Grant(555425-2021)the Natural Sciences and Engineering Research Council of Canada.
文摘This review paper presents a comprehensive evaluation and forward-looking perspective on the underexplored topic of servicing target objects using spacecraft swarms.Such targets can be known or unknown,cooperative or uncooperative,and pose significant challenges in modern space operations due to their inherent complexity and unpredictability.Successfully servicing space objects is vital for active debris removal and broader on-orbit servicing tasks such as satellite maintenance,repair,refueling,orbital assembly,and construction.Significant effort has been invested in the literature to explore the servicing of targets using a single spacecraft.Given its advantages and benefits,this paper expands the discussion to encompass a swarm approach to the problem.This review covers various single-spacecraft approaches and presents a critical examination of the existing,although limited,body of work dedicated to servicing orbital objects using multiple spacecraft.The focus is also broadened to include some influential studies concerning the characterization,capture,and manipulation of physical objects by general multiagent systems,a subject with significant parallels to the core interest of this manuscript.Furthermore,this article also delves into the realm of simultaneous localization and mapping,highlighting its application within close-proximity operations in space,especially when dealing with unknown uncooperative targets.Special attention is paid to the benefits that this field can receive from distributed multiagent architectures.Finally,an exploration of the promising field of swarm robotics is presented,with an emphasis on its potential to revolutionize the servicing of orbital target objects.Concurrently,a survey of general research directly engaging swarms in the orbital context is conducted.This review aims to bridge the knowledge gap and stimulate further research in the underexplored domain of servicing space targets with spacecraft swarms.
文摘Amazon Web Services(AWS)Cloud Trail auditing service provides detailed records of operational and security events,enabling cloud administrators to monitor user activity and manage compliance.Although signaturebased threat detection methods have been enhanced with machine learning and Large Language Models(LLMs),these approaches remain limited in addressing emerging threats.This study evaluates a two-step Retrieval Augmented Generation(RAG)approach using Gemini 2.5 Pro to enhance threat detection accuracy and contextual relevance.The RAG system integrates external cybersecurity knowledge sources including the MITRE ATT&CK framework,AWS Threat Technique Catalogue,and threat reports to overcome limitations of static pre-trained LLMs.We constructed an evaluation dataset of 200 unique CloudTrail events(122 malicious,78 benign)using the Stratus Red Team adversary emulation framework,covering 9 MITRE ATT&CK techniques across 8 tactics.Events were sampled from 1724 total events using stratified sampling.Ground truth labels were created through systematic expert annotation with 90%inter-annotator agreement.The RAG-enabled model achieved estimated 78%accuracy,85%precision,and 79%F1-score,representing 70.5%accuracy improvement and 76.4%F1-score improvement over baseline Gemini 2.5 Pro(46%accuracy,45%F1-score).Performance are based on evaluation results on 200-event dataset.Cost-latency analysis revealed processing time of 4.1 s and cost of$0.00376 per event,comparable to commercial SIEM solutions while providing superior MITRE ATT&CK attribution.The findings demonstrate that RAG substantially enhances context-aware threat detection,providing actionable insights for cloud security operations.
文摘Saud Khan,a Pakistani physician,collected his work and residence permits at the Yangpu Government Service Centre in Danzhou City,Hainan Province,on 18 December 2025.Khan had arrived in Hainan three months earlier to participate in a medical training programme at Hainan Western Central Hospital.By the time the programme concluded,he had made up his mind to stay and broaden his professional experience and long-term career prospects in Hainan.
文摘Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by the Hepatobiliary&Pancreatic Diseases International.
文摘In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.
文摘As the sunlight scattered on the sea of Guanyinshan in Xiamen,a space that bridges creativity and industry opened its door to the world.On December 15th,following a ribbon-cutting and unveiling ceremony,YKK Xiamen Guanyinshan Showroom,the brand's second and largest comprehensive showroom,was officially inaugurated.This showroom is more than a product display window,it is an"Inspiration Hub"integrating exhibition,co-creation,and service.Its launch signifies YKK's progression in the Chinese market from“building an efficient product proposal system”to a new stage of“deep collaborative co-creation.”
文摘Common mental disorders(CMDs),such as depressive and anxiety disorders,constitute a significant public health problem in low-and middle-income countries,such as India,where they rank among the leading causes of disability and impaired quality of life.Outcomes are further compromised by a large treatment gap,poor adherence to therapeutic regimens,and high attrition rates.The prevalence and severity of CMDs are disproportionately higher in women.Additionally,structural factors influencing healthcare access,along with sociocultural factors,such as gender-based violence,limited autonomy in healthcare decisions,and greater levels of discrimination and stigma,result in poorer outcomes among women with CMDs.Therefore,there is a pressing need for care packages that are culturally sensitive,gender-responsive,and designed to address these structural and sociocultural factors,as highlighted in the literature from India.
基金supported by the Ministry of Education and Science of the Republic of North Macedonia through the project“Utilizing AI and National Large Language Models to Advance Macedonian Language Capabilties”。
文摘Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review synthesizes recent research and developments in the application of AI agents across core financial domains.Specifically,it covers the deployment of agent-based AI in algorithmic trading,fraud detection,credit risk assessment,roboadvisory,and regulatory compliance(RegTech).The review focuses on advanced agent-based methodologies,including reinforcement learning,multi-agent systems,and autonomous decision-making frameworks,particularly those leveraging large language models(LLMs),contrasting these with traditional AI or purely statistical models.Our primary goals are to consolidate current knowledge,identify significant trends and architectural approaches,review the practical efficiency and impact of current applications,and delineate key challenges and promising future research directions.The increasing sophistication of AI agents offers unprecedented opportunities for innovation in finance,yet presents complex technical,ethical,and regulatory challenges that demand careful consideration and proactive strategies.This review aims to provide a comprehensive understanding of this rapidly evolving landscape,highlighting the role of agent-based AI in the ongoing transformation of the financial industry,and is intended to serve financial institutions,regulators,investors,analysts,researchers,and other key stakeholders in the financial ecosystem.
基金National Natural Science Foundation of China Youth Fund Project:Research on the Construction of Ecological Security Pattern in the Transition Zone of Nature Reserves along the Sichuan-Xizang Railway(Western Sichuan Section)(51908470).
文摘Lhasa,one of the world's highest cities,confronts the challenge of harmonizing cultural heritage preservation with ecological protection.Assessing the spatiotemporal dynamics of ecosystem service value(ESV)in its central urban area is therefore critical for informing future urban planning and land management.This study systematically analyzed land use evolution,the spatiotemporal characteristics of ecosystem services,and ecological network construction within Lhasa's central urban area.It integrated multi-source data,including Landsat remote sensing imagery from 2000,2010,and 2023,with multiple modeling methods such as the InVEST model,MaxEnt for cultural service assessment,the Minimum Cumulative Resistance(MCR)model,and circuit theory.Based on these analyses,optimization strategies were proposed.The results indicate that from 2000 to 2023,areas of cultivated land,grassland,and water bodies decreased by 7.47%,6.85%,and 0.68%,respectively,while wetland and forest areas expanded by 1.44%and 0.64%.Construction land exhibited significant expansion(12.94%),leading to an overall ESV reduction of 462.8×10^(5)yuan.Vegetation coverage was identified as the pivotal factor influencing ESV distribution,with higher values concentrated in the Lhasa River Basin and near the Lhalu Wetland,diminishing towards the urban core.Furthermore,spatial autocorrelation analysis revealed significant positive spatial clustering,with low-low aggregation in the eastern and central regions and high-high aggregation in the Lhasa River Basin and its surrounding water bodies.Moreover,based on a comprehensive ecosystem service assessment,11 ecological source sites were identified,primarily in the southwestern mountains and northeastern foothills.A comprehensive resistance surface,incorporating factors such as elevation,Normalized Difference Vegetation Index(NDVI),and land use,facilitated the extraction of 23 potential ecological corridors totaling 124.96 km in length.Topological network analysis indicated high redundancy and connectivity;however,marginal source sites relying on single connections exhibited significant vulnerability to rupture.Additionally,the application of circuit theory identified 30 ecological pinch points(current density≥1.5 A/km^(2))and 23 obstacle points,revealing significant blockages to ecological flow along the Qinghai-Xizang Highway,within the old city,and in other areas of high-intensity human activity.To address the identified network deficiencies—‘scattered cores,fragmented corridors,and insufficient resilience’—this study proposes an optimization strategy conceptualized as‘one vein,three corridors,and multiple cores’.Recommendations for enhancing network resilience include the delineation of ecological protection red lines,the integration of plateau-adapted technologies,and the fostering of community governance mechanisms.This approach aims to provide a scientific basis for constructing an ecological security pattern and promoting sustainable development in plateau cities.Ultimately,this research contributes to the enhancement of ecological well-being in the Himalayan region.
文摘Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for social networks due to significant limitations.Specifically,most approaches depend mainly on user-user structural links while overlooking service-centric,semantic,and multi-attribute drivers of community formation,and they also lack flexible filtering mechanisms for large-scale,service-oriented settings.Our proposed approach,called community discovery-based service(CDBS),leverages user profiles and their interactions with consulted web services.The method introduces a novel similarity measure,global similarity interaction profile(GSIP),which goes beyond typical similarity measures by unifying user and service profiles for all attributes types into a coherent representation,thereby clarifying its novelty and contribution.It applies multiple filtering criteria related to user attributes,accessed services,and interaction patterns.Experimental comparisons against Louvain,Hierarchical Agglomerative Clustering,Label Propagation and Infomap show that CDBS reveals the higher performance as it achieves 0.74 modularity,0.13 conductance,0.77 coverage,and significantly fast response time of 9.8 s,even with 10,000 users and 400 services.Moreover,community discoverybased service consistently detects a larger number of communities with distinct topics of interest,underscoring its capacity to generate detailed and efficient structures in complex networks.These results confirm both the efficiency and effectiveness of the proposed method.Beyond controlled evaluation,communities discovery based service is applicable to targeted recommendations,group-oriented marketing,access control,and service personalization,where communities are shaped not only by user links but also by service engagement.
文摘The Internet of Things(IoT)ecosystem is inherently heterogeneous,comprising diverse devices that must interoperate seamlessly to enable federated message and data exchange.However,as the number of service requests grows,existing approaches suffer from increased discovery time and degraded Quality of Service(QoS).Moreover,the massive data generated by heterogeneous IoT devices often contain redundancy and noise,posing challenges to efficient data management.To address these issues,this paper proposes a lightweight ontology-based architecture that enhances service discovery and QoS-aware semantic data management.The architecture employs Modified-Ordered Points to Identify theClustering Structure(M-OPTICS)to cluster and eliminate redundant IoT data.The clustered data are then modelled into a lightweight ontology,enabling semantic relationship inference and rule generation through an embedded inference engine.User requests,transmitted via theConstrainedApplication Protocol(CoAP),are semantically enriched and matched to QoS parameters using Dynamic Shannon Entropy optimized with the Salp Swarm Algorithm.Semantic matching is further refined using a bidirectional recurrent neural network(Bi-RNN),while a State–Action–Reward–State–Action(SARSA)reinforcement learning model dynamically defines and updates semantic rules to retrieve themost recent and relevant data across heterogeneous devices.Experimental results demonstrate that the proposed architecture outperforms existing methods in terms of response time,service delay,execution time,precision,recall,and F-score under varying CoAP request loads and communication overheads.The results confirm the effectiveness of the proposed lightweight ontology architecture for service discovery and data management in heterogeneous IoT environments.
