This paper presents component importance analysis for virtualized system with live migration. The component importance analysis is significant to determine the system design of virtualized system from availability and...This paper presents component importance analysis for virtualized system with live migration. The component importance analysis is significant to determine the system design of virtualized system from availability and cost points of view. This paper discusses the importance of components with respect to system availability. Specifically, we introduce two different component importance analyses for hybrid model (fault trees and continuous-time Markov chains) and continuous-time Markov chains, and show the analysis for existing probabilistic models for virtualized system. In numerical examples, we illustrate the quantitative component importance analysis for virtualized system with live migration.展开更多
With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Further...With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.展开更多
Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential f...Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A^(*)path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH^(*))technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A^(*)algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH^(*)uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications.展开更多
Latest digital advancements have intensified the necessity for adaptive,data-driven and socially-centered learning ecosystems.This paper presents the formulation of a cross-platform,innovative,gamified and personalize...Latest digital advancements have intensified the necessity for adaptive,data-driven and socially-centered learning ecosystems.This paper presents the formulation of a cross-platform,innovative,gamified and personalized Learning Ecosystem,which integrates 3D/VR environments,as well as machine learning algorithms,and business intelligence frameworks to enhance learner-centered education and inferenced decision-making.This Learning System makes use of immersive,analytically assessed virtual learning spaces,therefore facilitating real-time monitoring of not just learning performance,but also overall engagement and behavioral patterns,via a comprehensive set of sustainability-oriented ESG-aligned Key Performance Indicators(KPIs).Machine learning models support predictive analysis,personalized feedback,and hybrid recommendation mechanisms,whilst dedicated dashboards translate complex educational data into actionable insights for all Use Cases of the System(Educational Institutions,Educators and Learners).Additionally,the presented Learning System introduces a structured Mentoring and Consulting Subsystem,thence reinforcing human-centered guidance alongside automated intelligence.The Platform’s modular architecture and simulation-centered evaluation approach actively support personalized,and continuously optimized learning pathways.Thence,it exemplifies a mature,adaptive Learning Ecosystem,supporting immersive technologies,analytics,and pedagogical support,hence,contributing to contemporary digital learning innovation and sociotechnical transformation in education.展开更多
Storage class memory （SCM） has the potential to revolutionize the memory landscape by its non-volatile and byte-addressable properties. However, there is little published work about exploring its usage for modem vir...Storage class memory （SCM） has the potential to revolutionize the memory landscape by its non-volatile and byte-addressable properties. However, there is little published work about exploring its usage for modem virtualized cloud infrastructure. We propose SCM-vWrite, a novel architecture designed around SCM, to ease the performance interference of virtualized storage subsystem. Through a case study on a typical virtualized cloud system, we first describe why cur- rent writeback manners are not suitable for a virtualized en- vironment, then design and implement SCM-vWrite to im- prove this problem. We also use typical benchmarks and re- alistic workloads to evaluate its performance. Compared with the traditional method on a conventional architecture, the ex- perimental result shows that SCM-vWrite can coordinate the writeback flows more effectively among multiple co-located vip operating systems, achieving a better disk I/O perfor- mance without any loss of reliability.展开更多
This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)syste...This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.展开更多
To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for con...To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for constructing an industrial robot assembly system based on virtual reality technology.Focusing on the shaft hole assembly,the mechanical characteristics of the industrial robot shaft hole assembly process are analyzed and a dynamic model is established for shaft hole assembly operations.The key elements of virtual assembly operations for industrial robots are summarized and a five-dimensional model is proposed for industrial robot virtual operations.Utilizing the Unity3D engine based on the 5-D model for industrial robot virtual operations,an industrial robot shaft hole assembly system is developed.This system enables virtual assembly operations,displays physical attributes,and provides valuable references for the research of virtual systems.展开更多
Objective:Critically appraise the current state of alternate temporal bone training techniques(virtual reality(VR)simulation,3D-printed models,and mental practice(MP))compared to traditional and cadaver methods.Databa...Objective:Critically appraise the current state of alternate temporal bone training techniques(virtual reality(VR)simulation,3D-printed models,and mental practice(MP))compared to traditional and cadaver methods.Databases Reviewed:PubMed,Cochrane,Web of Science.Methods:Search terms utilized“temporal bone training”,“temporal bone surgical modalities”,and“training modalities temporal bone surgery”with“3D”,“rapid prototyp*”,“stereolithography”,“additive manufact*”,“plaster”,“VR”,“virtual reality”,“animal model”,“animal temporal bone”,and“synthetic”with“AND”for all literature.Exclusion criteria:non-ENT,non-English,and did not compare against alternative/traditional methods.Results:10 studies were included with 322 participants(83.9%ENT residents and 16.1%medical students).Costs include the FDM printer($300),materials($5/3D model),and<$5,000 for freeware simulator hardware.The Welling scale was used in 50%of studies.Alternate methods produced comparable or improved assessment scores to traditional and cadaver methods.Injuries were reported in three VR studies,with two reported significantly lower injury scores in the intervention groups.Time to completion was not significantly different in four VR studies,except for one finding that the time to visualize the incus was significantly lower in the intervention group.Performance after MP was not statistically different.Conclusion:More data are needed to assess whether the alternate methods are comparable to cadaveric dissection in temporal bone training.3D models and VR simulation demonstrate promising potential for novel trainees to acquire the basic skills and produce performance comparable to or significantly better than traditional methods of lectures,textbooks,CT images,and operative videos.展开更多
This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we id...This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we identify several avenues for enhancing existing methods.This survey describes some models of robots and commonly considered control objec-tives,followed by an in-depth analysis of four types of algo-rithms that can be employed for passing-through control:leader-follower formation control,multi-robot trajectory planning,con-trol-based methods,and virtual tube planning and control.Fur-thermore,we conduct a comparative analysis of these tech-niques and provide some subjective and general evaluations.展开更多
Objective:We aimed to perform a systematic review and meta-analysis to assess the efficacy of virtual reality(VR)distraction technologies in managing pain and anxiety in patients undergoing cystoscopy procedures.Metho...Objective:We aimed to perform a systematic review and meta-analysis to assess the efficacy of virtual reality(VR)distraction technologies in managing pain and anxiety in patients undergoing cystoscopy procedures.Methods:We searched PubMed,Embase,and the Cochrane Central Register of Controlled Trials from inception to July 2024,for studies comparing the use of VR distraction technologies versus no VR distraction in patients undergoing cystoscopy.The primary endpoints evaluated were patient-reported anxiety and procedural pain scores,and post-procedural heart rate(HR).Standardized mean differences(SMDs)and their 95%confidence intervals(CIs)were computed with the use of a random-effects model.The statistical analysis was conducted using Review Manager 5.4.Results:A total of 575 patients from four randomized controlled trials were included,of whom 289(50%)underwent the cystoscopy procedure using VR distraction technologies.The mean age of all patients was 57.25 years old,and 395(69%)of them were male.In our pooled analysis,we did not observe a statistically significant reduction in patient-reported procedural pain(SMD=0.16;95%CI=0.32-0.00;p=0.060;I^(2)=0%),anxiety(SMD=0.37;95%CI=1.65-0.90;p=0.6;I^(2)=93%),or post-procedural HR(SMD=0.58;95%CI=1.62-0.45;p=0.3;I^(2)=97%).Conclusion:In this comprehensive meta-analysis comprising 575 patients who underwent cystoscopy,the use of VR was not associated with a significant difference in pain,anxiety,or HR levels.展开更多
BACKGROUND Cognitive impairment is a major cause of disability in patients who have suffered from a stroke,and cognitive rehabilitation interventions show promise for improving memory.AIM To examine the effectiveness ...BACKGROUND Cognitive impairment is a major cause of disability in patients who have suffered from a stroke,and cognitive rehabilitation interventions show promise for improving memory.AIM To examine the effectiveness of virtual reality(VR)and non-VR(NVR)cognitive rehabilitation techniques for improving memory in patients after stroke.METHODS An extensive and thorough search was executed across five pertinent electronic databases:Cumulative Index to Nursing and Allied Health Literature;MEDLINE(PubMed);Scopus;ProQuest Central;and Google Scholar.This systematic review was conducted following the preferred reporting items for systematic reviews and meta-analyses guideline.Studies that recruited participants who experienced a stroke,utilized cognitive rehabilitation interventions,and published in the last 10 years were included in the review.RESULTS Thirty studies met the inclusion criteria.VR interventions significantly improved memory and cognitive function(mean difference:4.2±1.3,P<0.05),whereas NVR(including cognitive training,music,and exercise)moderately improved memory.Compared with traditional methods,technology-driven VR approaches were particularly beneficial for enhancing daily cognitive tasks.CONCLUSION VR and NVR reality interventions are beneficial for post-stroke cognitive recovery,with VR providing enhanced immersive experiences.Both approaches hold transformative potential for post-stroke rehabilitation.展开更多
The integration of Human-Robot Collaboration(HRC)into Virtual Reality(VR)technology is transforming industries by enhancing workforce skills,improving safety,and optimizing operational processes and efficiency through...The integration of Human-Robot Collaboration(HRC)into Virtual Reality(VR)technology is transforming industries by enhancing workforce skills,improving safety,and optimizing operational processes and efficiency through realistic simulations of industry-specific scenarios.Despite the growing adoption of VR integrated with HRC,comprehensive reviews of current research in HRC-VR within the construction and manufacturing fields are lacking.This review examines the latest advances in designing and implementing HRC using VR technology in these industries.The aim is to address the application domains of HRC-VR,types of robots used,VR setups,and software solutions used.To achieve this,a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology was conducted on the Web of Science and Google Scholar databases,analyzing 383 articles and selecting 53 papers that met the established selection criteria.The findings emphasize a significant focus on enhancing human-robot interaction with a trend toward using immersive VR experiences and interactive 3D content creation tools.However,the integration of HRC with VR,especially in the dynamic construction environment,presents unique challenges and opportunities for future research,including developing more realistic simulations and adaptable robot systems.This paper offers insights for researchers,practitioners,educators,industry professionals,and policymakers interested in leveraging the integration of HRC with VR in construction and manufacturing industries.展开更多
This article discusses the detailed examination of the engineering design and implementation process for direct Train-to-Train(T2T)communication within a wireless train backbone network in the context of a virtual cou...This article discusses the detailed examination of the engineering design and implementation process for direct Train-to-Train(T2T)communication within a wireless train backbone network in the context of a virtual coupling scenario.The article proposed several critical aspects,including the optimization of transmission data requirements,which is essential to ensure that communication between trains is efficient and reliable.The design of the T2T wireless communication subsystem is discussed in detail,outlining the technical specifications,protocols,and technologies employed to facilitate wireless communication between multiple trains.Additionally,the article presents a thorough analysis of the data collected during real-world train experiments,highlighting the performance metrics and challenges encountered during testing.This empirical data not only validates the effectiveness of the proposed design but also serves as a crucial reference for future advancements in T2T wireless communication systems.By combining both theoretical principles and practical outcomes,the article offers insights that will aid engineers and researchers in developing robust and efficient wireless communication systems for next-generation train operations.展开更多
Virtual reality(VR)technology revitalises rehabilitation training by creating rich,interactive virtual rehabilitation scenes and tasks that deeply engage patients.Robotics with immersive VR environments have the poten...Virtual reality(VR)technology revitalises rehabilitation training by creating rich,interactive virtual rehabilitation scenes and tasks that deeply engage patients.Robotics with immersive VR environments have the potential to significantly enhance the sense of immersion for patients during training.This paper proposes a rehabilitation robot system.The system integrates a VR environment,the exoskeleton entity,and research on rehabilitation assessment metrics derived from surface electromyographic signal(sEMG).Employing more realistic and engaging virtual stimuli,this method guides patients to actively participate,thereby enhancing the effectiveness of neural connection reconstruction—an essential aspect of rehabilitation.Furthermore,this study introduces a muscle activation model that merges linear and non-linear states of muscle,avoiding the impact of non-linear shape factors on model accuracy present in traditional models.A muscle strength assessment model based on optimised generalised regression(WOAGRNN)is also proposed,with a root mean square error of 0.017,347 and a mean absolute percentage error of 1.2461%,serving as critical assessment indicators for the effectiveness of rehabilitation.Finally,the system is preliminarily applied in human movement experiments,validating the practicality and potential effectiveness of VRcentred rehabilitation strategies in medical recovery.展开更多
This paper presents a space network emulation system based on a user-space network stack named Nos to solve space networks'unique architecture and routing issues and kernel stacks'inefficiency and development ...This paper presents a space network emulation system based on a user-space network stack named Nos to solve space networks'unique architecture and routing issues and kernel stacks'inefficiency and development complexity.Our low Earth orbit satellite scenario emulation verifies the dynamic routing function of the protocol stack.The proposed system uses technologies like Open vSwitch(OVS)and traffic control(TC)to emulate the space network's highly dynamic topology and time-varying link characteristics.The emulation results demonstrate the system's high reliability,and the user-space network stack reduces development complexity and debugging difficulty,providing convenience for the development of space network protocols and network functions.展开更多
This paper introduces the experience and practice in constructing the practical teaching system for the course“Electric Machine and Drive.”In response to the current status of cultivating innovative practical abilit...This paper introduces the experience and practice in constructing the practical teaching system for the course“Electric Machine and Drive.”In response to the current status of cultivating innovative practical abilities among electrical engineering majors,based on the independently developed virtual simulation experimental teaching platform for Electric Machine and Drive,a stepped practical teaching process consisting of“classroom teaching-experimental teaching-comprehensive training-scientific inquiry”has been elaborately designed.A hierarchical practical teaching model for the second classroom has also been established.With teaching objectives as the optimization index,the teaching content,methods and means have been optimized;the teaching process has been organized and implemented in the form of team collaboration,thus constructing a comprehensive,stepped,hierarchical,and closed-loop innovative practical teaching system.This achievement provides references and assistance for the practical teaching of the same or similar majors in other colleges and universities.展开更多
The problem of high-performance tracking controlfor the lower-triangular systems with unknown sign-switchingvirtual control coefficients as well as unmatched disturbances isinvestigated in this paper.Instead of the on...The problem of high-performance tracking controlfor the lower-triangular systems with unknown sign-switchingvirtual control coefficients as well as unmatched disturbances isinvestigated in this paper.Instead of the online estimation algorithm,the sliding mode method and the Nussbaum gain technique,a group of orientation functions are employed to handlethe unknown sign-switching virtual control coefficients.The controllaw is combined with the orientation functions and the barrierfunctions lumped in a recursive manner.It achieves outputtracking with the preassigned rate,overshoot,and accuracy.Incontrast with the existing solutions,it is effective for the nearlymodel-free case,with the requirement for information of neitherthe system nonlinearities nor their bounding functions of theplant,nor the bounds of the disturbances.In addition,our controllerexhibits significant simplicity,without parameter identification,disturbance estimation,function approximation,derivativecalculation,dynamic surfaces,or command filtering.Twosimulation examples are conducted to substantiate the efficacyand advantages of our approach.展开更多
The rapid development of artificial intelligence(AI)technology,particularly breakthroughs in branches such as deep learning,reinforcement learning,and federated learning,has provided powerful technical tools for addre...The rapid development of artificial intelligence(AI)technology,particularly breakthroughs in branches such as deep learning,reinforcement learning,and federated learning,has provided powerful technical tools for addressing these core bottlenecks.This paper provides a systematic review of the research background,technological evolution,core systems,key challenges,and future directions of AI technology in the field of distributed photovoltaic power generation system optimization.At the same time,this paper analyzes the current technical bottlenecks and cutting-edge response strategies.Finally,it explores fusion innovation directions such as quantum-classical hybrid algorithms and neural symbolic systems,as well as business model expansion paths such as carbon finance integration and community energy autonomy.展开更多
In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges whe...In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges when datasets lack the comprehensive information necessary for addressing complex scenarios,which hampers adaptability.Thus,enhancing data completeness is essential.Knowledge-guided virtual sample generation transforms domain knowledge into extensive virtual datasets,thereby reducing dependence on limited real samples and enabling zero-sample fault diagnosis.This study used building air conditioning systems as a case study.We innovatively used the large language model(LLM)to acquire domain knowledge for sample generation,significantly lowering knowledge acquisition costs and establishing a generalized framework for knowledge acquisition in engineering applications.This acquired knowledge guided the design of diffusion boundaries in mega-trend diffusion(MTD),while the Monte Carlo method was used to sample within the diffusion function to create information-rich virtual samples.Additionally,a noise-adding technique was introduced to enhance the information entropy of these samples,thereby improving the robustness of neural networks trained with them.Experimental results showed that training the diagnostic model exclusively with virtual samples achieved an accuracy of 72.80%,significantly surpassing traditional small-sample supervised learning in terms of generalization.This underscores the quality and completeness of the generated virtual samples.展开更多
With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as...With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as promising technologies for mitigating grid oscillations and enhancing system flexibility.However,the excitation converters in DFVS-PSUs are prone to significant issues such as elevated common-mode voltage(CMV)and neutral-point voltage(NPV)fluctuations,which can lead to electromagnetic interference and degrade transient performance.To address these challenges,an optimized virtual space vector pulse width modulation(OVSVPWM)strategy is proposed,aiming to suppress CMV and NPV simultaneously through coordinated multi-objective control.Specifically,a dynamic feedback mechanism is introduced to adjust the balancing factor of basic vectors in the synthesized virtual small vector in real-time,achieving autonomous balancing of the NPV.To address the excessive switching actions introduced by the OVSVPWM strategy,a phase duty ratio-based sequence reconstruction method is adopted,which reduces the total number of switching actions to half of the original.A zero-level buffering scheme is employed to reconstruct the single-phase voltage-level output sequence,achieving peak CMV suppression down to udc/6.Simulation results demonstrate that the proposed strategy significantly improves electromagnetic compatibility and operational stability while maintaining high power quality.展开更多
文摘This paper presents component importance analysis for virtualized system with live migration. The component importance analysis is significant to determine the system design of virtualized system from availability and cost points of view. This paper discusses the importance of components with respect to system availability. Specifically, we introduce two different component importance analyses for hybrid model (fault trees and continuous-time Markov chains) and continuous-time Markov chains, and show the analysis for existing probabilistic models for virtualized system. In numerical examples, we illustrate the quantitative component importance analysis for virtualized system with live migration.
基金supported by the National Natural Science Foundation of China under Grant 62471493supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066。
文摘With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.
文摘Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A^(*)path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH^(*))technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A^(*)algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH^(*)uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications.
文摘Latest digital advancements have intensified the necessity for adaptive,data-driven and socially-centered learning ecosystems.This paper presents the formulation of a cross-platform,innovative,gamified and personalized Learning Ecosystem,which integrates 3D/VR environments,as well as machine learning algorithms,and business intelligence frameworks to enhance learner-centered education and inferenced decision-making.This Learning System makes use of immersive,analytically assessed virtual learning spaces,therefore facilitating real-time monitoring of not just learning performance,but also overall engagement and behavioral patterns,via a comprehensive set of sustainability-oriented ESG-aligned Key Performance Indicators(KPIs).Machine learning models support predictive analysis,personalized feedback,and hybrid recommendation mechanisms,whilst dedicated dashboards translate complex educational data into actionable insights for all Use Cases of the System(Educational Institutions,Educators and Learners).Additionally,the presented Learning System introduces a structured Mentoring and Consulting Subsystem,thence reinforcing human-centered guidance alongside automated intelligence.The Platform’s modular architecture and simulation-centered evaluation approach actively support personalized,and continuously optimized learning pathways.Thence,it exemplifies a mature,adaptive Learning Ecosystem,supporting immersive technologies,analytics,and pedagogical support,hence,contributing to contemporary digital learning innovation and sociotechnical transformation in education.
文摘Storage class memory （SCM） has the potential to revolutionize the memory landscape by its non-volatile and byte-addressable properties. However, there is little published work about exploring its usage for modem virtualized cloud infrastructure. We propose SCM-vWrite, a novel architecture designed around SCM, to ease the performance interference of virtualized storage subsystem. Through a case study on a typical virtualized cloud system, we first describe why cur- rent writeback manners are not suitable for a virtualized en- vironment, then design and implement SCM-vWrite to im- prove this problem. We also use typical benchmarks and re- alistic workloads to evaluate its performance. Compared with the traditional method on a conventional architecture, the ex- perimental result shows that SCM-vWrite can coordinate the writeback flows more effectively among multiple co-located vip operating systems, achieving a better disk I/O perfor- mance without any loss of reliability.
文摘This research pioneers the integration of geographic information systems(GIS)and 3D modeling within a virtual reality(VR)framework to assess the viability and planning of a 20 MW hybrid wind-solarphotovoltaic(PV)system connected to the local grid.The study focuses on Dakhla,Morocco,a region with vast untapped renewable energy potential.By leveraging GIS,we are innovatively analyzing geographical and environmental factors that influence optimal site selection and system design.The incorporation of VR technologies offers an unprecedented level of realism and immersion,allowing stakeholders to virtually experience the project's impact and design in a dynamic,interactive environment.This novel methodology includes extensive data collection,advanced modeling,and simulations,ensuring that the hybrid system is precisely tailored to the unique climatic and environmental conditions of Dakhla.Our analysis reveals that the region possesses a photovoltaic solar potential of approximately2400 k Wh/m^(2) per year,with an average annual wind power density of about 434 W/m^(2) at an 80-meter hub height.Productivity simulations indicate that the 20 MW hybrid system could generate approximately 60 GWh of energy per year and 1369 GWh over its 25-year lifespan.To validate these findings,we employed the System Advisor Model(SAM)software and the Global Solar Photovoltaic Atlas platform.This comprehensive and interdisciplinary approach not only provides a robust assessment of the system's feasibility but also offers valuable insights into its potential socio-economic and environmental impact.
基金Sponsored by the National Natural Science Foundation of China(Grant No.52005003)the Science and Technology Planning Project of Wuhu City(Grant No.2022jc41)。
文摘To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for constructing an industrial robot assembly system based on virtual reality technology.Focusing on the shaft hole assembly,the mechanical characteristics of the industrial robot shaft hole assembly process are analyzed and a dynamic model is established for shaft hole assembly operations.The key elements of virtual assembly operations for industrial robots are summarized and a five-dimensional model is proposed for industrial robot virtual operations.Utilizing the Unity3D engine based on the 5-D model for industrial robot virtual operations,an industrial robot shaft hole assembly system is developed.This system enables virtual assembly operations,displays physical attributes,and provides valuable references for the research of virtual systems.
文摘Objective:Critically appraise the current state of alternate temporal bone training techniques(virtual reality(VR)simulation,3D-printed models,and mental practice(MP))compared to traditional and cadaver methods.Databases Reviewed:PubMed,Cochrane,Web of Science.Methods:Search terms utilized“temporal bone training”,“temporal bone surgical modalities”,and“training modalities temporal bone surgery”with“3D”,“rapid prototyp*”,“stereolithography”,“additive manufact*”,“plaster”,“VR”,“virtual reality”,“animal model”,“animal temporal bone”,and“synthetic”with“AND”for all literature.Exclusion criteria:non-ENT,non-English,and did not compare against alternative/traditional methods.Results:10 studies were included with 322 participants(83.9%ENT residents and 16.1%medical students).Costs include the FDM printer($300),materials($5/3D model),and<$5,000 for freeware simulator hardware.The Welling scale was used in 50%of studies.Alternate methods produced comparable or improved assessment scores to traditional and cadaver methods.Injuries were reported in three VR studies,with two reported significantly lower injury scores in the intervention groups.Time to completion was not significantly different in four VR studies,except for one finding that the time to visualize the incus was significantly lower in the intervention group.Performance after MP was not statistically different.Conclusion:More data are needed to assess whether the alternate methods are comparable to cadaveric dissection in temporal bone training.3D models and VR simulation demonstrate promising potential for novel trainees to acquire the basic skills and produce performance comparable to or significantly better than traditional methods of lectures,textbooks,CT images,and operative videos.
文摘This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we identify several avenues for enhancing existing methods.This survey describes some models of robots and commonly considered control objec-tives,followed by an in-depth analysis of four types of algo-rithms that can be employed for passing-through control:leader-follower formation control,multi-robot trajectory planning,con-trol-based methods,and virtual tube planning and control.Fur-thermore,we conduct a comparative analysis of these tech-niques and provide some subjective and general evaluations.
文摘Objective:We aimed to perform a systematic review and meta-analysis to assess the efficacy of virtual reality(VR)distraction technologies in managing pain and anxiety in patients undergoing cystoscopy procedures.Methods:We searched PubMed,Embase,and the Cochrane Central Register of Controlled Trials from inception to July 2024,for studies comparing the use of VR distraction technologies versus no VR distraction in patients undergoing cystoscopy.The primary endpoints evaluated were patient-reported anxiety and procedural pain scores,and post-procedural heart rate(HR).Standardized mean differences(SMDs)and their 95%confidence intervals(CIs)were computed with the use of a random-effects model.The statistical analysis was conducted using Review Manager 5.4.Results:A total of 575 patients from four randomized controlled trials were included,of whom 289(50%)underwent the cystoscopy procedure using VR distraction technologies.The mean age of all patients was 57.25 years old,and 395(69%)of them were male.In our pooled analysis,we did not observe a statistically significant reduction in patient-reported procedural pain(SMD=0.16;95%CI=0.32-0.00;p=0.060;I^(2)=0%),anxiety(SMD=0.37;95%CI=1.65-0.90;p=0.6;I^(2)=93%),or post-procedural HR(SMD=0.58;95%CI=1.62-0.45;p=0.3;I^(2)=97%).Conclusion:In this comprehensive meta-analysis comprising 575 patients who underwent cystoscopy,the use of VR was not associated with a significant difference in pain,anxiety,or HR levels.
文摘BACKGROUND Cognitive impairment is a major cause of disability in patients who have suffered from a stroke,and cognitive rehabilitation interventions show promise for improving memory.AIM To examine the effectiveness of virtual reality(VR)and non-VR(NVR)cognitive rehabilitation techniques for improving memory in patients after stroke.METHODS An extensive and thorough search was executed across five pertinent electronic databases:Cumulative Index to Nursing and Allied Health Literature;MEDLINE(PubMed);Scopus;ProQuest Central;and Google Scholar.This systematic review was conducted following the preferred reporting items for systematic reviews and meta-analyses guideline.Studies that recruited participants who experienced a stroke,utilized cognitive rehabilitation interventions,and published in the last 10 years were included in the review.RESULTS Thirty studies met the inclusion criteria.VR interventions significantly improved memory and cognitive function(mean difference:4.2±1.3,P<0.05),whereas NVR(including cognitive training,music,and exercise)moderately improved memory.Compared with traditional methods,technology-driven VR approaches were particularly beneficial for enhancing daily cognitive tasks.CONCLUSION VR and NVR reality interventions are beneficial for post-stroke cognitive recovery,with VR providing enhanced immersive experiences.Both approaches hold transformative potential for post-stroke rehabilitation.
基金Supported by National Science Foundation under Grant No.2222881.
文摘The integration of Human-Robot Collaboration(HRC)into Virtual Reality(VR)technology is transforming industries by enhancing workforce skills,improving safety,and optimizing operational processes and efficiency through realistic simulations of industry-specific scenarios.Despite the growing adoption of VR integrated with HRC,comprehensive reviews of current research in HRC-VR within the construction and manufacturing fields are lacking.This review examines the latest advances in designing and implementing HRC using VR technology in these industries.The aim is to address the application domains of HRC-VR,types of robots used,VR setups,and software solutions used.To achieve this,a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology was conducted on the Web of Science and Google Scholar databases,analyzing 383 articles and selecting 53 papers that met the established selection criteria.The findings emphasize a significant focus on enhancing human-robot interaction with a trend toward using immersive VR experiences and interactive 3D content creation tools.However,the integration of HRC with VR,especially in the dynamic construction environment,presents unique challenges and opportunities for future research,including developing more realistic simulations and adaptable robot systems.This paper offers insights for researchers,practitioners,educators,industry professionals,and policymakers interested in leveraging the integration of HRC with VR in construction and manufacturing industries.
基金supported by the National Key R&D Program of China(2021YFF0501103).
文摘This article discusses the detailed examination of the engineering design and implementation process for direct Train-to-Train(T2T)communication within a wireless train backbone network in the context of a virtual coupling scenario.The article proposed several critical aspects,including the optimization of transmission data requirements,which is essential to ensure that communication between trains is efficient and reliable.The design of the T2T wireless communication subsystem is discussed in detail,outlining the technical specifications,protocols,and technologies employed to facilitate wireless communication between multiple trains.Additionally,the article presents a thorough analysis of the data collected during real-world train experiments,highlighting the performance metrics and challenges encountered during testing.This empirical data not only validates the effectiveness of the proposed design but also serves as a crucial reference for future advancements in T2T wireless communication systems.By combining both theoretical principles and practical outcomes,the article offers insights that will aid engineers and researchers in developing robust and efficient wireless communication systems for next-generation train operations.
基金National Key Research and Development Program of China,Grant/Award Number:2022YFB4700701National Outstanding Youth Science Fund Project of National Natural Science Foundation of China,Grant/Award Number:52025054。
文摘Virtual reality(VR)technology revitalises rehabilitation training by creating rich,interactive virtual rehabilitation scenes and tasks that deeply engage patients.Robotics with immersive VR environments have the potential to significantly enhance the sense of immersion for patients during training.This paper proposes a rehabilitation robot system.The system integrates a VR environment,the exoskeleton entity,and research on rehabilitation assessment metrics derived from surface electromyographic signal(sEMG).Employing more realistic and engaging virtual stimuli,this method guides patients to actively participate,thereby enhancing the effectiveness of neural connection reconstruction—an essential aspect of rehabilitation.Furthermore,this study introduces a muscle activation model that merges linear and non-linear states of muscle,avoiding the impact of non-linear shape factors on model accuracy present in traditional models.A muscle strength assessment model based on optimised generalised regression(WOAGRNN)is also proposed,with a root mean square error of 0.017,347 and a mean absolute percentage error of 1.2461%,serving as critical assessment indicators for the effectiveness of rehabilitation.Finally,the system is preliminarily applied in human movement experiments,validating the practicality and potential effectiveness of VRcentred rehabilitation strategies in medical recovery.
基金supported by the National Natural Science Foundation of China under Grant No.62131012ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20230712005。
文摘This paper presents a space network emulation system based on a user-space network stack named Nos to solve space networks'unique architecture and routing issues and kernel stacks'inefficiency and development complexity.Our low Earth orbit satellite scenario emulation verifies the dynamic routing function of the protocol stack.The proposed system uses technologies like Open vSwitch(OVS)and traffic control(TC)to emulate the space network's highly dynamic topology and time-varying link characteristics.The emulation results demonstrate the system's high reliability,and the user-space network stack reduces development complexity and debugging difficulty,providing convenience for the development of space network protocols and network functions.
基金Project of the 14th Five-Year Plan for Educational Science in Liaoning Province(JG24DB234)Project of Graduate Education and Teaching Reform Research in Liaoning Province(LNYJG2023115)。
文摘This paper introduces the experience and practice in constructing the practical teaching system for the course“Electric Machine and Drive.”In response to the current status of cultivating innovative practical abilities among electrical engineering majors,based on the independently developed virtual simulation experimental teaching platform for Electric Machine and Drive,a stepped practical teaching process consisting of“classroom teaching-experimental teaching-comprehensive training-scientific inquiry”has been elaborately designed.A hierarchical practical teaching model for the second classroom has also been established.With teaching objectives as the optimization index,the teaching content,methods and means have been optimized;the teaching process has been organized and implemented in the form of team collaboration,thus constructing a comprehensive,stepped,hierarchical,and closed-loop innovative practical teaching system.This achievement provides references and assistance for the practical teaching of the same or similar majors in other colleges and universities.
基金supported in part by the National Natural Science Foundation of China(61991404,62473089)the Research Program of the Liaoning Liaohe Laboratory(LLL23ZZ-05-01)+6 种基金the Key Research and Development Program of Liaoning Province of China(2023JH26/10200011)the 111 Project 2.0 of China(B08015)the National Key Research and Development Program of China(2022YFB3305905)the Xingliao Talent Program of Liaoning Province of China(XLYC2203130)the Natural Science Foundation of Liaoning Province of China(2024JH3/10200012,2023-MS-087)the Open Research Project of the State Key Laboratory of Industrial Control Technology of China(ICT2024B12)the Fundamental Research Funds for the Central Universities of China(N2108003,N2424004).
文摘The problem of high-performance tracking controlfor the lower-triangular systems with unknown sign-switchingvirtual control coefficients as well as unmatched disturbances isinvestigated in this paper.Instead of the online estimation algorithm,the sliding mode method and the Nussbaum gain technique,a group of orientation functions are employed to handlethe unknown sign-switching virtual control coefficients.The controllaw is combined with the orientation functions and the barrierfunctions lumped in a recursive manner.It achieves outputtracking with the preassigned rate,overshoot,and accuracy.Incontrast with the existing solutions,it is effective for the nearlymodel-free case,with the requirement for information of neitherthe system nonlinearities nor their bounding functions of theplant,nor the bounds of the disturbances.In addition,our controllerexhibits significant simplicity,without parameter identification,disturbance estimation,function approximation,derivativecalculation,dynamic surfaces,or command filtering.Twosimulation examples are conducted to substantiate the efficacyand advantages of our approach.
文摘The rapid development of artificial intelligence(AI)technology,particularly breakthroughs in branches such as deep learning,reinforcement learning,and federated learning,has provided powerful technical tools for addressing these core bottlenecks.This paper provides a systematic review of the research background,technological evolution,core systems,key challenges,and future directions of AI technology in the field of distributed photovoltaic power generation system optimization.At the same time,this paper analyzes the current technical bottlenecks and cutting-edge response strategies.Finally,it explores fusion innovation directions such as quantum-classical hybrid algorithms and neural symbolic systems,as well as business model expansion paths such as carbon finance integration and community energy autonomy.
基金supported by the National Natural Science Foundation of China(No.62306281)the Natural Science Foundation of Zhejiang Province(Nos.LQ23E060006 and LTGG24E050005)the Key Research Plan of Jiaxing City(No.2024BZ20016).
文摘In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges when datasets lack the comprehensive information necessary for addressing complex scenarios,which hampers adaptability.Thus,enhancing data completeness is essential.Knowledge-guided virtual sample generation transforms domain knowledge into extensive virtual datasets,thereby reducing dependence on limited real samples and enabling zero-sample fault diagnosis.This study used building air conditioning systems as a case study.We innovatively used the large language model(LLM)to acquire domain knowledge for sample generation,significantly lowering knowledge acquisition costs and establishing a generalized framework for knowledge acquisition in engineering applications.This acquired knowledge guided the design of diffusion boundaries in mega-trend diffusion(MTD),while the Monte Carlo method was used to sample within the diffusion function to create information-rich virtual samples.Additionally,a noise-adding technique was introduced to enhance the information entropy of these samples,thereby improving the robustness of neural networks trained with them.Experimental results showed that training the diagnostic model exclusively with virtual samples achieved an accuracy of 72.80%,significantly surpassing traditional small-sample supervised learning in terms of generalization.This underscores the quality and completeness of the generated virtual samples.
文摘With the rapid integration of renewable energy sources,modern power systems are increasingly challenged by heightened volatility and uncertainty.Doubly-fed variable-speed pumped storage units(DFVS-PSUs)have emerged as promising technologies for mitigating grid oscillations and enhancing system flexibility.However,the excitation converters in DFVS-PSUs are prone to significant issues such as elevated common-mode voltage(CMV)and neutral-point voltage(NPV)fluctuations,which can lead to electromagnetic interference and degrade transient performance.To address these challenges,an optimized virtual space vector pulse width modulation(OVSVPWM)strategy is proposed,aiming to suppress CMV and NPV simultaneously through coordinated multi-objective control.Specifically,a dynamic feedback mechanism is introduced to adjust the balancing factor of basic vectors in the synthesized virtual small vector in real-time,achieving autonomous balancing of the NPV.To address the excessive switching actions introduced by the OVSVPWM strategy,a phase duty ratio-based sequence reconstruction method is adopted,which reduces the total number of switching actions to half of the original.A zero-level buffering scheme is employed to reconstruct the single-phase voltage-level output sequence,achieving peak CMV suppression down to udc/6.Simulation results demonstrate that the proposed strategy significantly improves electromagnetic compatibility and operational stability while maintaining high power quality.
