Loday introduced di-associative algebras and tri-associative algebras motivated by periodicity phenomena in algebraic K-theory.The purpose of this paper is to study the splittings of operations on di-associative algeb...Loday introduced di-associative algebras and tri-associative algebras motivated by periodicity phenomena in algebraic K-theory.The purpose of this paper is to study the splittings of operations on di-associative algebras and tri-associative algebras.We introduce the notion of a quad-dendriform algebra,which is a splitting of a di-associative algebra.We show that a relative averaging operator on dendriform algebras gives rise to a quad-dendriform algebra.Furthermore,we introduce the notion of six-dendriform algebras,which are splittings of the tri-associative algebras,and demonstrate that homomorphic relative averaging operators induce six-dendriform algebras.展开更多
The global public HPC(high-power charging)network for EVs(electric vehicles)is rapidly expanding.This growth is crucial for supporting the increasing adoption of EVs but highlights the industry’s early stage.Regional...The global public HPC(high-power charging)network for EVs(electric vehicles)is rapidly expanding.This growth is crucial for supporting the increasing adoption of EVs but highlights the industry’s early stage.Regional maturity varies,with China leading due to strong government support,followed by Europe and the United States.A significant challenge is the lack of industry standards,causing inconsistencies in charger types and payment systems.Efforts are underway,to ensure interoperability and reliability.Interoperability is crucial for the success of EV HPC infrastructure,ensuring seamless integration among charge points,management systems,and service providers.Despite the use of protocols like the OCPP(Open Charge Point Protocol),variations in implementation create complexities.Ensuring uniform standards across the ecosystem is essential for reliability and efficiency.Vendor-specific error codes,which are more detailed than standardized codes,are vital for diagnosing issues but lack standardization,adding complexity.Addressing these challenges is key to supporting widespread EV adoption and enhancing user experience.To provide a compelling driver value proposition,EV charging services must be reliable and seamless.The operations and maintenance of the HPC network must be cost-effective and leverage the intelligence of the integrated ecosystem.The technical complexity of managing high-power DC charging,combined with diverse authentication and payment systems,results in numerous potential issues.Moving from reactive to predictive maintenance is essential for undisrupted operations and a smooth driver experience.Shell’s Intelligent Operations Technology Strategy incorporates GenAI elements in its advanced analytics and operational performance management tools.By ingesting big data from multiple sources across the EV ecosystem,Shell engineers can perform detailed pattern recognition and targeted troubleshooting.Monitoring,configurable alerting,and remote fixing based on auto-healing and targeted auto-allocation enhance charger availability and reduce downtime.This automation has evolved Shell’s maintenance and operations strategy from reactive to predictive,improving overall charger performance and user satisfaction.Key achievements include transitioning to prescriptive and preventive asset management approaches,significantly improving uptime and charging experience,and increasing commercial value through cost reduction and enhanced revenue.Future challenges include evolving OCPP,integrating data from non-OCPP systems,and ensuring interoperability across diverse systems.Standardization and cross-collaboration within the industry are essential for smooth interoperability,higher uptime,and increased CSR(charging success rate).Technological innovations will further shape the industry,promoting stabilization and efficiency as it matures.展开更多
Accurate recognition of flight deck operations for carrier-based aircraft, based on operation trajectories, is critical for optimizing carrier-based aircraft performance. This recognition involves understanding short-...Accurate recognition of flight deck operations for carrier-based aircraft, based on operation trajectories, is critical for optimizing carrier-based aircraft performance. This recognition involves understanding short-term and long-term spatial collaborative relationships among support agents and positions from long spatial–temporal trajectories. While the existing methods excel at recognizing collaborative behaviors from short trajectories, they often struggle with long spatial–temporal trajectories. To address this challenge, this paper introduces a dynamic graph method to enhance flight deck operation recognition. First, spatial–temporal collaborative relationships are modeled as a dynamic graph. Second, a discretized and compressed method is proposed to assign values to the states of this dynamic graph. To extract features that represent diverse collaborative relationships among agents and account for the duration of these relationships, a biased random walk is then conducted. Subsequently, the Swin Transformer is employed to comprehend spatial–temporal collaborative relationships, and a fully connected layer is applied to deck operation recognition. Finally, to address the scarcity of real datasets, a simulation pipeline is introduced to generate deck operations in virtual flight deck scenarios. Experimental results on the simulation dataset demonstrate the superior performance of the proposed method.展开更多
Our concern is to investigate controlled remote implementation of partially unknown operations with multiple layers.We first propose a scheme to realize the remote implementation of singlequbit operations belonging to...Our concern is to investigate controlled remote implementation of partially unknown operations with multiple layers.We first propose a scheme to realize the remote implementation of singlequbit operations belonging to the restricted sets.Then,the proposed scheme is extended to the case of single-qudit operations.As long as the controller and the higher-layer senders consent,the receiver can restore the desired state remotely operated by the sender.It is worth mentioning that the recovery operation is deduced by general formulas which clearly reveal the relationship with the measurement outcomes.For the sake of clarity,two specific examples with two levels are given respectively.In addition,we discuss the influence of amplitude-damping noise and utilize weak measurement and measurement reversal to effectively resist noise.展开更多
Digital twin shows broad application prospects in the aerospace field.This paper introduces a generalized satellite digital twin system in detail.With the innovative design concepts of modularization,generalization an...Digital twin shows broad application prospects in the aerospace field.This paper introduces a generalized satellite digital twin system in detail.With the innovative design concepts of modularization,generalization and modeling,on the one hand,the system has successfully achieved the reuse of software modules among different satellite models;on the other hand,it has achieved the reuse of software modules between the digital twin and the testing system,significantly improving the development efficiency of the digital twin system.The paper elaborates on the technical architecture and application fields of this digital twin system,and further prospects its future development.At the same time,through a real inorbit case,the engineering value of the digital twin system is strongly demonstrated.展开更多
In this article,we conduct a study on mixed quasi-martingale Hardy spaces that are defined by means of the mixed L_(p)-norm.By utilizing Doob’s inequalities,we explore the atomic decomposition and quasi-martingale in...In this article,we conduct a study on mixed quasi-martingale Hardy spaces that are defined by means of the mixed L_(p)-norm.By utilizing Doob’s inequalities,we explore the atomic decomposition and quasi-martingale inequalities of mixed quasi-martingale Hardy spaces.Moreover,we furnish sufficient conditions for the boundedness ofσ-sublinear operators in these spaces.These findings extend the existing conclusions regarding mixed quasi-martingale Hardy spaces defined with the help of the mixed L_(p)-norm.展开更多
Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challeng...Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.展开更多
In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→...In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→∞)x′(t)e^(t)=0,where t_(0) and ψ_(0) are real constants,φ(s)=s/√1−s^(2),s∈R with s∈(−1,1),f:[t_(0),∞)×R→R satisfies the Lipschitz or Osgood-type conditions.展开更多
基金Supported by the Science and Technology Program of Guizhou Province(Grant No.QKHJC QN[2025]362)the National Natural Science Foundation of China(Grant No.12361005).
文摘Loday introduced di-associative algebras and tri-associative algebras motivated by periodicity phenomena in algebraic K-theory.The purpose of this paper is to study the splittings of operations on di-associative algebras and tri-associative algebras.We introduce the notion of a quad-dendriform algebra,which is a splitting of a di-associative algebra.We show that a relative averaging operator on dendriform algebras gives rise to a quad-dendriform algebra.Furthermore,we introduce the notion of six-dendriform algebras,which are splittings of the tri-associative algebras,and demonstrate that homomorphic relative averaging operators induce six-dendriform algebras.
文摘The global public HPC(high-power charging)network for EVs(electric vehicles)is rapidly expanding.This growth is crucial for supporting the increasing adoption of EVs but highlights the industry’s early stage.Regional maturity varies,with China leading due to strong government support,followed by Europe and the United States.A significant challenge is the lack of industry standards,causing inconsistencies in charger types and payment systems.Efforts are underway,to ensure interoperability and reliability.Interoperability is crucial for the success of EV HPC infrastructure,ensuring seamless integration among charge points,management systems,and service providers.Despite the use of protocols like the OCPP(Open Charge Point Protocol),variations in implementation create complexities.Ensuring uniform standards across the ecosystem is essential for reliability and efficiency.Vendor-specific error codes,which are more detailed than standardized codes,are vital for diagnosing issues but lack standardization,adding complexity.Addressing these challenges is key to supporting widespread EV adoption and enhancing user experience.To provide a compelling driver value proposition,EV charging services must be reliable and seamless.The operations and maintenance of the HPC network must be cost-effective and leverage the intelligence of the integrated ecosystem.The technical complexity of managing high-power DC charging,combined with diverse authentication and payment systems,results in numerous potential issues.Moving from reactive to predictive maintenance is essential for undisrupted operations and a smooth driver experience.Shell’s Intelligent Operations Technology Strategy incorporates GenAI elements in its advanced analytics and operational performance management tools.By ingesting big data from multiple sources across the EV ecosystem,Shell engineers can perform detailed pattern recognition and targeted troubleshooting.Monitoring,configurable alerting,and remote fixing based on auto-healing and targeted auto-allocation enhance charger availability and reduce downtime.This automation has evolved Shell’s maintenance and operations strategy from reactive to predictive,improving overall charger performance and user satisfaction.Key achievements include transitioning to prescriptive and preventive asset management approaches,significantly improving uptime and charging experience,and increasing commercial value through cost reduction and enhanced revenue.Future challenges include evolving OCPP,integrating data from non-OCPP systems,and ensuring interoperability across diverse systems.Standardization and cross-collaboration within the industry are essential for smooth interoperability,higher uptime,and increased CSR(charging success rate).Technological innovations will further shape the industry,promoting stabilization and efficiency as it matures.
基金co-supported by the National Key Research and Development Program of China(No. 2021YFB3301504)the National Natural Science Foundation of China (Nos. 62072415, 62036010, 42301526, 62372416 and 62472389)the National Natural Science Foundation of Henan Province, China (No. 242300421215)
文摘Accurate recognition of flight deck operations for carrier-based aircraft, based on operation trajectories, is critical for optimizing carrier-based aircraft performance. This recognition involves understanding short-term and long-term spatial collaborative relationships among support agents and positions from long spatial–temporal trajectories. While the existing methods excel at recognizing collaborative behaviors from short trajectories, they often struggle with long spatial–temporal trajectories. To address this challenge, this paper introduces a dynamic graph method to enhance flight deck operation recognition. First, spatial–temporal collaborative relationships are modeled as a dynamic graph. Second, a discretized and compressed method is proposed to assign values to the states of this dynamic graph. To extract features that represent diverse collaborative relationships among agents and account for the duration of these relationships, a biased random walk is then conducted. Subsequently, the Swin Transformer is employed to comprehend spatial–temporal collaborative relationships, and a fully connected layer is applied to deck operation recognition. Finally, to address the scarcity of real datasets, a simulation pipeline is introduced to generate deck operations in virtual flight deck scenarios. Experimental results on the simulation dataset demonstrate the superior performance of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant Nos.62172341,12071132)the Natural Science Foundation of Henan Province of China(Grant No.242300420276)the Joint Fund of Henan Province Science and Technology R&D Program(Grant No.225200810032)。
文摘Our concern is to investigate controlled remote implementation of partially unknown operations with multiple layers.We first propose a scheme to realize the remote implementation of singlequbit operations belonging to the restricted sets.Then,the proposed scheme is extended to the case of single-qudit operations.As long as the controller and the higher-layer senders consent,the receiver can restore the desired state remotely operated by the sender.It is worth mentioning that the recovery operation is deduced by general formulas which clearly reveal the relationship with the measurement outcomes.For the sake of clarity,two specific examples with two levels are given respectively.In addition,we discuss the influence of amplitude-damping noise and utilize weak measurement and measurement reversal to effectively resist noise.
文摘Digital twin shows broad application prospects in the aerospace field.This paper introduces a generalized satellite digital twin system in detail.With the innovative design concepts of modularization,generalization and modeling,on the one hand,the system has successfully achieved the reuse of software modules among different satellite models;on the other hand,it has achieved the reuse of software modules between the digital twin and the testing system,significantly improving the development efficiency of the digital twin system.The paper elaborates on the technical architecture and application fields of this digital twin system,and further prospects its future development.At the same time,through a real inorbit case,the engineering value of the digital twin system is strongly demonstrated.
基金Supported by the National Natural Science Foundation of China(11871195)。
文摘In this article,we conduct a study on mixed quasi-martingale Hardy spaces that are defined by means of the mixed L_(p)-norm.By utilizing Doob’s inequalities,we explore the atomic decomposition and quasi-martingale inequalities of mixed quasi-martingale Hardy spaces.Moreover,we furnish sufficient conditions for the boundedness ofσ-sublinear operators in these spaces.These findings extend the existing conclusions regarding mixed quasi-martingale Hardy spaces defined with the help of the mixed L_(p)-norm.
文摘Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems.However,the inspection of underwater pipelines presents a challenge due to factors such as light scattering,absorption,restricted visibility,and ambient noise.The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments.This study evaluated the efficacy of the You Only Look Once(YOLO)algorithm,a real-time object detection and localization model based on convolutional neural networks,in identifying and classifying various types of pipeline defects in underwater settings.YOLOv8,the latest evolution in the YOLO family,integrates advanced capabilities,such as anchor-free detection,a cross-stage partial network backbone for efficient feature extraction,and a feature pyramid network+path aggregation network neck for robust multi-scale object detection,which make it particularly well-suited for complex underwater environments.Due to the lack of suitable open-access datasets for underwater pipeline defects,a custom dataset was captured using a remotely operated vehicle in a controlled environment.This application has the following assets available for use.Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks,rust,corners,defective welds,flanges,tapes,and holes.This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12361040,12061064)the Na-tional Science Foundation of Gansu Province(Grant No.22JR5RA264)State Scholarship Fund(Grant No.20230862021).
文摘In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→∞)x′(t)e^(t)=0,where t_(0) and ψ_(0) are real constants,φ(s)=s/√1−s^(2),s∈R with s∈(−1,1),f:[t_(0),∞)×R→R satisfies the Lipschitz or Osgood-type conditions.
