Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastruc...Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastructure. This letter proposes an Secure Active Tracing System (SATS) to implementing security for active networking in Internet. Unlike currently existing schemes, SATS reduces the computational overloads by executing the filtering operation on selected packet streams only when needed.展开更多
An algorithm of traffic distribution called active multi-path routing(AMR)in active network is proposed.AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic amon...An algorithm of traffic distribution called active multi-path routing(AMR)in active network is proposed.AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths.It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly.The frame of AMR includes adaptive trafficallocation model,the conception of supply bandwidth and its'allocation model,the principle ofcongestion restraint and its'model,and the implement of AMR based on multi-agents system in activenetwork.Through simulations,AMR has distinct effects on network performance.The results show AMRisa valid traffic regulation algorithm.展开更多
This paper presents a data processing strategy for GPS kinematic positioning by using a GPS active network to model the GPS errors in double difference observable.Firstly,the double difference residuals are estimated ...This paper presents a data processing strategy for GPS kinematic positioning by using a GPS active network to model the GPS errors in double difference observable.Firstly,the double difference residuals are estimated between the reference stations in the active network.Then the errors at a user station are predicted as the network corrections to user measurements,based on the location of the user.Finally conventional kinematic positioning algorithms can be applied to determine the position of the user station.As an example,continuous 24_hour GPS data in March 2001 has been processed by this method.It clearly demonstrates that,after applying these corrections to a user within the network,both the success rate for ambiguity resolution and the positioning accuracy have been significantly improved.展开更多
We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or tru...We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallely processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.展开更多
Active networks are a new kind of packet-switched networks in which packets have code fragments that are executed on the intermediary nodes (routers). The code can extend or modify the foundation architecture of a net...Active networks are a new kind of packet-switched networks in which packets have code fragments that are executed on the intermediary nodes (routers). The code can extend or modify the foundation architecture of a network. In this paper, the authors present a novel active network architecture combined with advantages of two major active networks technology based on extensible services router. The architecture consists of extensible service router, active extensible components server and key distribution center (KDC). Users can write extensible service components with programming interface. At the present time, we have finished the extensible services router prototype system based on Highly Efficient Router Operating System (HEROS), active extensible components server and KDC prototype system based on Linux.展开更多
In this paper,an active network measurement platform is proposed which is a combination of hardware and software.Its innovation lies in the high performance of hardware combined with features that the software is easy...In this paper,an active network measurement platform is proposed which is a combination of hardware and software.Its innovation lies in the high performance of hardware combined with features that the software is easy to program,which retains software flexibility at the same time.By improving the precision of packet timestamp programmable hardware equipment,it provides packet sending control more accurately and supports the microsecond packet interval.We have implemented a model on the NetMagic platform,and done some experiments to analyze the accuracy difference of the user,the kernel and hardware timestamp.展开更多
An active thermo-acoustic network model of regenerator which is a key component to accomplish the con-version between thermal-and acoustic power in thermo-acoustic system has been established in this paper. The experi...An active thermo-acoustic network model of regenerator which is a key component to accomplish the con-version between thermal-and acoustic power in thermo-acoustic system has been established in this paper. The experiment was carried out to quantify the network. A method called least square is employed in order to identify the H matrix describing the system. The results obtained here show that the active thermo-acoustic network can reliably depict the characteristics of a thermo-acoustic system.展开更多
An efficient method for the optimization of linear networks is presented.Thecomputation cost in circuit optimization mainly depends on the simulation of network;in general,the simulation of a linear network needs to s...An efficient method for the optimization of linear networks is presented.Thecomputation cost in circuit optimization mainly depends on the simulation of network;in general,the simulation of a linear network needs to solve a high dimension linear algebra equation.Animportant characteristic in circuit optimization is that the number of independently tunableparameters is small.In terms of the property of linear networks,the circuit is described by amultiport network in the presented method,and the hybrid matrix is established.The dimensionof the equation to be solved is the same as the number of optimization parameters in objectivefunction evaluations,which provides a fast simulation tool for optimization.展开更多
This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relativ...This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.展开更多
Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power o...Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.展开更多
Dear Editor,Active magnetic bearings(AMBs)are of considerable interest and significance in smart manufacturing due to their zero-friction and adaptivity to noncontact rotor rotations.This paper proposes an active levi...Dear Editor,Active magnetic bearings(AMBs)are of considerable interest and significance in smart manufacturing due to their zero-friction and adaptivity to noncontact rotor rotations.This paper proposes an active levitation control algorithm based on adaptive sliding mode control(ASMC)equipped with linear extended state observer(LESO).Sufficient conditions are derived to guarantee the asymptotical stability of the associated closed-loop system.Experiments are conducted on a real AMB-rotor platform to demonstrate the effectiveness and superiority of the proposed algorithm.展开更多
Chrysanthemum is rich in active compounds such as flavonoids and phenolic acids,and its dried head flowers are commonly used for tea and medicinal purposes.However,the genetic determinism underlying chrysanthemum acti...Chrysanthemum is rich in active compounds such as flavonoids and phenolic acids,and its dried head flowers are commonly used for tea and medicinal purposes.However,the genetic determinism underlying chrysanthemum active compounds remains elusive.In this study,we evaluated a panel of 137 chrysanthemum accessions for total flavonoids,chlorogenic acid,luteolin,and isochlorogenic acid A across two consecutive years.The four active compounds exhibited considerable variation,with a coefficient of variation ranging from 44.96%to 76.30%.Significant differences were observed in genotype and environments,and the broad-sense heritability was estimated at 0.5-0.63 for all examined traits.Significant pair-wise correlation was found between the four active compounds.Several accessions showing the highest active compounds were figured out for breeding use by integrating the membership function and hierarchical cluster analysis methods.Based on the327042 high-quality SNPs,a genome-wide association study(GWAS)captured 59 significant SNPs for the four active compounds,of which 24elite alleles exhibited pyramiding effects.A total of 18 potential candidate genes were mined,among which evm.model.scaffold_1149.273(QUA1)has one linkage disequilibrium(LD)block corresponding to Hap4 with the highest luteolin content.The findings are beneficial to understanding the genetic basis of the active compounds and provide parental materials and valuable markers for the genetic improvement of active compounds in chrysanthemums.展开更多
The traditional detailed model of the dual active bridge(DAB)power electronic transformer is characterized by the high dimensionality of its nodal admittance matrix and the need for a small simulation step size,which ...The traditional detailed model of the dual active bridge(DAB)power electronic transformer is characterized by the high dimensionality of its nodal admittance matrix and the need for a small simulation step size,which limits the speed of electromagnetic transient(EMT)simulations.To overcome these limitations,a novel EMT equivalent model based on a generalized branch-cutting method is proposed to improve the simulation efficiency of the DAB model.The DAB topology is first decomposed into two subnetworks through branch-cutting and node-tearing methods without the introduction of a one-time-step delay.Sub-sequently,the internal nodes of each sub-network are eliminated through network simplification,and the equivalent circuit for the port cascade module is derived.The model is then validated through simulations across various operating conditions.The results demonstrate that the model avoids the loss of accuracy associated with one-time-step delay,the relative error across different conditions remains below 1%,and the simulation acceleration ratios improve as the number of modules increases.展开更多
This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar ...This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.展开更多
Objective:Deep learning(DL)has become the prevailing method in chest radiograph analysis,yet its performance heavily depends on large quantities of annotated images.To mitigate the cost,cold-start active learning(AL),...Objective:Deep learning(DL)has become the prevailing method in chest radiograph analysis,yet its performance heavily depends on large quantities of annotated images.To mitigate the cost,cold-start active learning(AL),comprising an initialization followed by subsequent learning,selects a small subset of informative data points for labeling.Recent advancements in pretrained models by supervised or self-supervised learning tailored to chest radiograph have shown broad applicability to diverse downstream tasks.However,their potential in cold-start AL remains unexplored.Methods:To validate the efficacy of domain-specific pretraining,we compared two foundation models:supervised TXRV and self-supervised REMEDIS with their general domain counterparts pretrained on ImageNet.Model performance was evaluated at both initialization and subsequent learning stages on two diagnostic tasks:psychiatric pneumonia and COVID-19.For initialization,we assessed their integration with three strategies:diversity,uncertainty,and hybrid sampling.For subsequent learning,we focused on uncertainty sampling powered by different pretrained models.We also conducted statistical tests to compare the foundation models with ImageNet counterparts,investigate the relationship between initialization and subsequent learning,examine the performance of one-shot initialization against the full AL process,and investigate the influence of class balance in initialization samples on initialization and subsequent learning.Results:First,domain-specific foundation models failed to outperform ImageNet counterparts in six out of eight experiments on informative sample selection.Both domain-specific and general pretrained models were unable to generate representations that could substitute for the original images as model inputs in seven of the eight scenarios.However,pretrained model-based initialization surpassed random sampling,the default approach in cold-start AL.Second,initialization performance was positively correlated with subsequent learning performance,highlighting the importance of initialization strategies.Third,one-shot initialization performed comparably to the full AL process,demonstrating the potential of reducing experts'repeated waiting during AL iterations.Last,a U-shaped correlation was observed between the class balance of initialization samples and model performance,suggesting that the class balance is more strongly associated with performance at middle budget levels than at low or high budgets.Conclusions:In this study,we highlighted the limitations of medical pretraining compared to general pretraining in the context of cold-start AL.We also identified promising outcomes related to cold-start AL,including initialization based on pretrained models,the positive influence of initialization on subsequent learning,the potential for one-shot initialization,and the influence of class balance on middle-budget AL.Researchers are encouraged to improve medical pretraining for versatile DL foundations and explore novel AL methods.展开更多
1.Colors of chemical reaction engineering models Kinetic models of chemical reactions are a crucial asset for understanding and optimizing chemical processes[1].These models are critical for reactor design,process opt...1.Colors of chemical reaction engineering models Kinetic models of chemical reactions are a crucial asset for understanding and optimizing chemical processes[1].These models are critical for reactor design,process optimization,catalyst design,scale-up,and process control,making them indispensable in the chemical industry.Kinetic models predict the change in temperature and concentration of the relevant species,given an actual concentration and temperature.Reaction predictions are made by integrating the kinetic model with a reactor model,which accounts for external constraints,such as flow,inlet concentration。展开更多
BACKGROUND Most patients with non-alcoholic fatty liver disease(NAFLD)exhibit mild symptoms;however,without timely intervention,the condition may progress to cirrhosis or even liver cancer.The development of internet-...BACKGROUND Most patients with non-alcoholic fatty liver disease(NAFLD)exhibit mild symptoms;however,without timely intervention,the condition may progress to cirrhosis or even liver cancer.The development of internet-based proactive follow-up management models has provided new avenues for medical services,allowing patients to access online consultations and enabling doctors to efficiently manage patient information.These models have particular significance for NAFLD patients,as they can enhance compliance and facilitate timely intervention.AIM To explore the effect of an internet-based proactive follow-up management model on the prognosis management of patients with NAFLD.METHODS This study collected data from 145 patients diagnosed with NAFLD.The patients were randomly divided into the internet-based proactive follow-up group(71 patients)and the traditional follow-up group(74 patients).The traditional followup group underwent routine outpatient and telephone follow-up,while the internet-based proactive follow-up group used the WeChat applet for active reminding,health education and follow-up.During the follow-up period,patients’compliance,disease control status,and quality of life score were recorded.RESULTS The follow-up compliance of patients in the internet-based proactive follow-up group was significantly higher than that in the traditional follow-up group(85.6%vs 68.4%,P<0.01),and the quality of life score was significantly improved(78.9±7.6 vs 72.5±8.4,P<0.01).CONCLUSION The internet-based proactive follow-up management model can provide personalized health management plans and reduce the risk of disease deterioration,making it worthy of promotion in a broader healthcare context.展开更多
This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical sy...This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical systems,ADNs are characterized by widespread structural and functional interdependen-cies between cyber(communication,computing,and control)and physical(electric power)subsystems and thus present complex hazardous-weather-related resilience issues.To bridge current research gaps,this paper first classifies diverse hazardous weather events for ADNs according to different time spans and degrees of hazard,with model-based and data-driven methods being utilized to characterize weather evolutions.Then,the adverse impacts of hazardous weather on all aspects of ADNs’sources,physical/cyber networks,and loads are analyzed.This paper further emphasizes the importance of situational awareness and cyber-physical collaboration throughout hazardous weather events,as these enhance the implementation of preventive dispatches,corrective actions,and coordinated restorations.In addition,a generalized quantitative resilience evaluation process is proposed regarding additional considerations about cyber subsystems and cyber-physical connections.Finally,potential hazardous-weather-related resilience challenges for both physical and cyber subsystems are discussed.展开更多
Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing o...Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing offers a transformative approach to solve ADN planning.To fully leverage the potential of quantum computing,this paper proposes a photonic quantum acceleration algorithm.First,a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers.The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process.The photonic quantum-embedded adaptive alternating direction method of multipliers(PQA-ADMM)algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model,enabling its deployment on a photonic quantum computer.Finally,a comparative analysis with various solvers,including Gurobi,demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems,highlighting its effectiveness.展开更多
During the startup of the hydraulic turbine generators,the hybrid magnetic bearing support system exhibits displacement fluctuations,and the nonlinearity and strong coupling characteristics of the magnetic bearings li...During the startup of the hydraulic turbine generators,the hybrid magnetic bearing support system exhibits displacement fluctuations,and the nonlinearity and strong coupling characteristics of the magnetic bearings limit the accuracy of rotor modeling,making traditional control methods difficult to adapt to parameter variations.To suppress startup disturbances and achieve a control strategy with low computational complexity and high precision,this paper proposes a five-degree-of-freedom hybrid magnetic bearing control strategy based on an improved cascaded reduced-order linear active disturbance rejection controller(CRLADRC).The front-stage reduced-order linear extended state observer(FRLESO)reduces the system’s computational complexity,enabling the system to maintain stability during motor startup disturbances.The second-stage reduced-order linear extended state observer(SRLESO)further enhances the system’s disturbance estimation accuracy while maintaining low computational complexity.Furthermore,the disturbance rejection and noise suppression capabilities are analyzed in the frequency domain and the stability of the proposed control method is proven using Lyapunov theory.Experimental results indicate that the proposed strategy effectively reduces displacement fluctuations in the hybrid magnetic bearing support system during motor startup,significantly enhancing the system’s robustness.展开更多
文摘Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastructure. This letter proposes an Secure Active Tracing System (SATS) to implementing security for active networking in Internet. Unlike currently existing schemes, SATS reduces the computational overloads by executing the filtering operation on selected packet streams only when needed.
基金Supported by the National Natural Science Foun dation of China(90204008)
文摘An algorithm of traffic distribution called active multi-path routing(AMR)in active network is proposed.AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths.It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly.The frame of AMR includes adaptive trafficallocation model,the conception of supply bandwidth and its'allocation model,the principle ofcongestion restraint and its'model,and the implement of AMR based on multi-agents system in activenetwork.Through simulations,AMR has distinct effects on network performance.The results show AMRisa valid traffic regulation algorithm.
文摘This paper presents a data processing strategy for GPS kinematic positioning by using a GPS active network to model the GPS errors in double difference observable.Firstly,the double difference residuals are estimated between the reference stations in the active network.Then the errors at a user station are predicted as the network corrections to user measurements,based on the location of the user.Finally conventional kinematic positioning algorithms can be applied to determine the position of the user station.As an example,continuous 24_hour GPS data in March 2001 has been processed by this method.It clearly demonstrates that,after applying these corrections to a user within the network,both the success rate for ambiguity resolution and the positioning accuracy have been significantly improved.
文摘We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallely processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.
文摘Active networks are a new kind of packet-switched networks in which packets have code fragments that are executed on the intermediary nodes (routers). The code can extend or modify the foundation architecture of a network. In this paper, the authors present a novel active network architecture combined with advantages of two major active networks technology based on extensible services router. The architecture consists of extensible service router, active extensible components server and key distribution center (KDC). Users can write extensible service components with programming interface. At the present time, we have finished the extensible services router prototype system based on Highly Efficient Router Operating System (HEROS), active extensible components server and KDC prototype system based on Linux.
基金Supported by the National High Technology Research and Development Programme of China(No.2007AA01Z416)"New Start" Academic Research Projects of Beijing Union University(No.ZK201204)
文摘In this paper,an active network measurement platform is proposed which is a combination of hardware and software.Its innovation lies in the high performance of hardware combined with features that the software is easy to program,which retains software flexibility at the same time.By improving the precision of packet timestamp programmable hardware equipment,it provides packet sending control more accurately and supports the microsecond packet interval.We have implemented a model on the NetMagic platform,and done some experiments to analyze the accuracy difference of the user,the kernel and hardware timestamp.
文摘An active thermo-acoustic network model of regenerator which is a key component to accomplish the con-version between thermal-and acoustic power in thermo-acoustic system has been established in this paper. The experiment was carried out to quantify the network. A method called least square is employed in order to identify the H matrix describing the system. The results obtained here show that the active thermo-acoustic network can reliably depict the characteristics of a thermo-acoustic system.
文摘An efficient method for the optimization of linear networks is presented.Thecomputation cost in circuit optimization mainly depends on the simulation of network;in general,the simulation of a linear network needs to solve a high dimension linear algebra equation.Animportant characteristic in circuit optimization is that the number of independently tunableparameters is small.In terms of the property of linear networks,the circuit is described by amultiport network in the presented method,and the hybrid matrix is established.The dimensionof the equation to be solved is the same as the number of optimization parameters in objectivefunction evaluations,which provides a fast simulation tool for optimization.
文摘This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.
基金funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.
文摘Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.
基金supported in part by the National Natural Science Foundation of China(62225306,U2141235,52188102).
文摘Dear Editor,Active magnetic bearings(AMBs)are of considerable interest and significance in smart manufacturing due to their zero-friction and adaptivity to noncontact rotor rotations.This paper proposes an active levitation control algorithm based on adaptive sliding mode control(ASMC)equipped with linear extended state observer(LESO).Sufficient conditions are derived to guarantee the asymptotical stability of the associated closed-loop system.Experiments are conducted on a real AMB-rotor platform to demonstrate the effectiveness and superiority of the proposed algorithm.
基金supported by the National Key Research and Development Program of China(2022YFD1200504)the National Natural Science Foundation of China(32171857)+2 种基金China Agriculture Research System(CARS-23-A18)The“JBGS”Project of Seed Industry Revitalization in Jiangsu Province(JBGS[2021]094)the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Chrysanthemum is rich in active compounds such as flavonoids and phenolic acids,and its dried head flowers are commonly used for tea and medicinal purposes.However,the genetic determinism underlying chrysanthemum active compounds remains elusive.In this study,we evaluated a panel of 137 chrysanthemum accessions for total flavonoids,chlorogenic acid,luteolin,and isochlorogenic acid A across two consecutive years.The four active compounds exhibited considerable variation,with a coefficient of variation ranging from 44.96%to 76.30%.Significant differences were observed in genotype and environments,and the broad-sense heritability was estimated at 0.5-0.63 for all examined traits.Significant pair-wise correlation was found between the four active compounds.Several accessions showing the highest active compounds were figured out for breeding use by integrating the membership function and hierarchical cluster analysis methods.Based on the327042 high-quality SNPs,a genome-wide association study(GWAS)captured 59 significant SNPs for the four active compounds,of which 24elite alleles exhibited pyramiding effects.A total of 18 potential candidate genes were mined,among which evm.model.scaffold_1149.273(QUA1)has one linkage disequilibrium(LD)block corresponding to Hap4 with the highest luteolin content.The findings are beneficial to understanding the genetic basis of the active compounds and provide parental materials and valuable markers for the genetic improvement of active compounds in chrysanthemums.
基金The Technology Project of State Grid Corporation of China Headquarters(No.5400-202318547A-3-2-ZN).
文摘The traditional detailed model of the dual active bridge(DAB)power electronic transformer is characterized by the high dimensionality of its nodal admittance matrix and the need for a small simulation step size,which limits the speed of electromagnetic transient(EMT)simulations.To overcome these limitations,a novel EMT equivalent model based on a generalized branch-cutting method is proposed to improve the simulation efficiency of the DAB model.The DAB topology is first decomposed into two subnetworks through branch-cutting and node-tearing methods without the introduction of a one-time-step delay.Sub-sequently,the internal nodes of each sub-network are eliminated through network simplification,and the equivalent circuit for the port cascade module is derived.The model is then validated through simulations across various operating conditions.The results demonstrate that the model avoids the loss of accuracy associated with one-time-step delay,the relative error across different conditions remains below 1%,and the simulation acceleration ratios improve as the number of modules increases.
基金supported in part by the National Nat-ural Science Foundation of China(No.51977012,No.52307080).
文摘This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.
文摘Objective:Deep learning(DL)has become the prevailing method in chest radiograph analysis,yet its performance heavily depends on large quantities of annotated images.To mitigate the cost,cold-start active learning(AL),comprising an initialization followed by subsequent learning,selects a small subset of informative data points for labeling.Recent advancements in pretrained models by supervised or self-supervised learning tailored to chest radiograph have shown broad applicability to diverse downstream tasks.However,their potential in cold-start AL remains unexplored.Methods:To validate the efficacy of domain-specific pretraining,we compared two foundation models:supervised TXRV and self-supervised REMEDIS with their general domain counterparts pretrained on ImageNet.Model performance was evaluated at both initialization and subsequent learning stages on two diagnostic tasks:psychiatric pneumonia and COVID-19.For initialization,we assessed their integration with three strategies:diversity,uncertainty,and hybrid sampling.For subsequent learning,we focused on uncertainty sampling powered by different pretrained models.We also conducted statistical tests to compare the foundation models with ImageNet counterparts,investigate the relationship between initialization and subsequent learning,examine the performance of one-shot initialization against the full AL process,and investigate the influence of class balance in initialization samples on initialization and subsequent learning.Results:First,domain-specific foundation models failed to outperform ImageNet counterparts in six out of eight experiments on informative sample selection.Both domain-specific and general pretrained models were unable to generate representations that could substitute for the original images as model inputs in seven of the eight scenarios.However,pretrained model-based initialization surpassed random sampling,the default approach in cold-start AL.Second,initialization performance was positively correlated with subsequent learning performance,highlighting the importance of initialization strategies.Third,one-shot initialization performed comparably to the full AL process,demonstrating the potential of reducing experts'repeated waiting during AL iterations.Last,a U-shaped correlation was observed between the class balance of initialization samples and model performance,suggesting that the class balance is more strongly associated with performance at middle budget levels than at low or high budgets.Conclusions:In this study,we highlighted the limitations of medical pretraining compared to general pretraining in the context of cold-start AL.We also identified promising outcomes related to cold-start AL,including initialization based on pretrained models,the positive influence of initialization on subsequent learning,the potential for one-shot initialization,and the influence of class balance on middle-budget AL.Researchers are encouraged to improve medical pretraining for versatile DL foundations and explore novel AL methods.
基金Yannick Ureel and Maarten Dobbelaere acknowledge financial support from the Fund for Scientific Research Flanders(FWO Flanders)respectively through doctoral fellowship grants(1185822N and 1S45522N)The authors acknowledge funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme/ERC(818607).
文摘1.Colors of chemical reaction engineering models Kinetic models of chemical reactions are a crucial asset for understanding and optimizing chemical processes[1].These models are critical for reactor design,process optimization,catalyst design,scale-up,and process control,making them indispensable in the chemical industry.Kinetic models predict the change in temperature and concentration of the relevant species,given an actual concentration and temperature.Reaction predictions are made by integrating the kinetic model with a reactor model,which accounts for external constraints,such as flow,inlet concentration。
文摘BACKGROUND Most patients with non-alcoholic fatty liver disease(NAFLD)exhibit mild symptoms;however,without timely intervention,the condition may progress to cirrhosis or even liver cancer.The development of internet-based proactive follow-up management models has provided new avenues for medical services,allowing patients to access online consultations and enabling doctors to efficiently manage patient information.These models have particular significance for NAFLD patients,as they can enhance compliance and facilitate timely intervention.AIM To explore the effect of an internet-based proactive follow-up management model on the prognosis management of patients with NAFLD.METHODS This study collected data from 145 patients diagnosed with NAFLD.The patients were randomly divided into the internet-based proactive follow-up group(71 patients)and the traditional follow-up group(74 patients).The traditional followup group underwent routine outpatient and telephone follow-up,while the internet-based proactive follow-up group used the WeChat applet for active reminding,health education and follow-up.During the follow-up period,patients’compliance,disease control status,and quality of life score were recorded.RESULTS The follow-up compliance of patients in the internet-based proactive follow-up group was significantly higher than that in the traditional follow-up group(85.6%vs 68.4%,P<0.01),and the quality of life score was significantly improved(78.9±7.6 vs 72.5±8.4,P<0.01).CONCLUSION The internet-based proactive follow-up management model can provide personalized health management plans and reduce the risk of disease deterioration,making it worthy of promotion in a broader healthcare context.
基金supported by the National Natural Science Foundation of China(52477132 and U2066601).
文摘This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical systems,ADNs are characterized by widespread structural and functional interdependen-cies between cyber(communication,computing,and control)and physical(electric power)subsystems and thus present complex hazardous-weather-related resilience issues.To bridge current research gaps,this paper first classifies diverse hazardous weather events for ADNs according to different time spans and degrees of hazard,with model-based and data-driven methods being utilized to characterize weather evolutions.Then,the adverse impacts of hazardous weather on all aspects of ADNs’sources,physical/cyber networks,and loads are analyzed.This paper further emphasizes the importance of situational awareness and cyber-physical collaboration throughout hazardous weather events,as these enhance the implementation of preventive dispatches,corrective actions,and coordinated restorations.In addition,a generalized quantitative resilience evaluation process is proposed regarding additional considerations about cyber subsystems and cyber-physical connections.Finally,potential hazardous-weather-related resilience challenges for both physical and cyber subsystems are discussed.
基金supported in part by the National Natural Science Foundation of China under Grant 52307134the Fundamental Research Funds for the Central Universities(xzy012025022)。
文摘Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing offers a transformative approach to solve ADN planning.To fully leverage the potential of quantum computing,this paper proposes a photonic quantum acceleration algorithm.First,a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers.The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process.The photonic quantum-embedded adaptive alternating direction method of multipliers(PQA-ADMM)algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model,enabling its deployment on a photonic quantum computer.Finally,a comparative analysis with various solvers,including Gurobi,demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems,highlighting its effectiveness.
基金supported by the National Natural Science Foundation of China under Grant 52302458the CAS Project for Young Scientists in Basic Research,Grant No.YSBR-045.
文摘During the startup of the hydraulic turbine generators,the hybrid magnetic bearing support system exhibits displacement fluctuations,and the nonlinearity and strong coupling characteristics of the magnetic bearings limit the accuracy of rotor modeling,making traditional control methods difficult to adapt to parameter variations.To suppress startup disturbances and achieve a control strategy with low computational complexity and high precision,this paper proposes a five-degree-of-freedom hybrid magnetic bearing control strategy based on an improved cascaded reduced-order linear active disturbance rejection controller(CRLADRC).The front-stage reduced-order linear extended state observer(FRLESO)reduces the system’s computational complexity,enabling the system to maintain stability during motor startup disturbances.The second-stage reduced-order linear extended state observer(SRLESO)further enhances the system’s disturbance estimation accuracy while maintaining low computational complexity.Furthermore,the disturbance rejection and noise suppression capabilities are analyzed in the frequency domain and the stability of the proposed control method is proven using Lyapunov theory.Experimental results indicate that the proposed strategy effectively reduces displacement fluctuations in the hybrid magnetic bearing support system during motor startup,significantly enhancing the system’s robustness.
