As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilienc...As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS.First,a unified resilience-driven coopera-tive reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement.Subsequently,a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence,combining the cooperative pair resilience contribution index(CPRCI)and coop-erative pair importance index(CPII).At last,the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include differ-ent attack modes and intensities.The analysis results can pro-vide a reference for decision-makers to manage UWSoS.展开更多
With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization p...With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.展开更多
With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provi...With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.展开更多
Maximizing the utilization of lithium-ion battery capacity is an important means to alleviate the range anxiety of electric vehicles.Battery pack inconsistency is the main limiting factor for improving battery pack ca...Maximizing the utilization of lithium-ion battery capacity is an important means to alleviate the range anxiety of electric vehicles.Battery pack inconsistency is the main limiting factor for improving battery pack capacity utilization,and poses major safety hazards to energy storage systems.To solve this problem,a maximum capacity utilization scheme based on a path planning algorithm is proposed.Specifically,the reconfigurable topology proposed is highly flexible and fault-tolerant,enabling battery pack consistency through alternating cell discharge and reducing the increased risk of short circuits due to relay error.The Dijkstra algorithm is used to find the optimal energy path,which can effectively remove faulty cells and find the current path with the best consistency of the battery pack and the lowest relay loss.Finally,the effectiveness of the scheme is verified by hardware-in-the-loop experiments,and the experimental results show that the state-of-charge SOC consistency of the battery pack at the end of discharge is increased by 34.18%,the relay energy loss is reduced by 0.16%,and the fault unit is effectively isolated.展开更多
Low-carbon hydrogen can play a significant role in decarbonizing the world. Hydrogen is currently mainly produced from fossil sources,requiring additional CO_(2)capture to decarbonize, which energy intense and costly....Low-carbon hydrogen can play a significant role in decarbonizing the world. Hydrogen is currently mainly produced from fossil sources,requiring additional CO_(2)capture to decarbonize, which energy intense and costly. In a recent Green Energy & Environment paper, Cheng and Di et al. proposed a novel integration process referred to as SECLR_(HC) to generate high-purity H_(2) by in-situ separation of H_(2)and CO without using any additional separation unit. Theoretically, the proposed process can essentially achieve the separation of C and H in gaseous fuel via a reconfigured reaction process, and thus attaining high-purity hydrogen of ~99%, as well as good carbon and hydrogen utilization rates and economic feasibility. It displays an optimistic prospect that industrial decarbonization is not necessarily expensive, as long as a suitable CCS measure can be integrated into the industrial manufacturing process.展开更多
Reconfiguration of formation flying around a halo orbit of the Sun-Earth restricted three body system is investigated with impulse maneuvers. For a short time reconfiguration, the two-impulse maneuver is investigated ...Reconfiguration of formation flying around a halo orbit of the Sun-Earth restricted three body system is investigated with impulse maneuvers. For a short time reconfiguration, the two-impulse maneuver is investigated with both analytical and numerical methods and the Beginning-Ending (BE) method is proven to be an energy-optimal one of all two-impulse (TI) reconfigurations, and the energy consumption of BE is independent of the position of the chief spacecraft, and decreases with the reconfiguration time. Then, genetic algorithm is adopted to optimize the energy consumption. The results show that the optimal energy increases with radius difference between the initial and final orbits, and decreases with the reconfiguration time.展开更多
In order to accommodate the variety of algorithms with different performance in specific application and improve power efficiency,reconfigurable architecture has become an effective methodology in academia and industr...In order to accommodate the variety of algorithms with different performance in specific application and improve power efficiency,reconfigurable architecture has become an effective methodology in academia and industry.However,existing architectures suffer from performance bottleneck due to slow updating of contexts and inadequate flexibility.This paper presents an H-tree based reconfiguration mechanism(HRM)with Huffman-coding-like and mask addressing method in a homogeneous processing element(PE)array,which supports both programmable and data-driven modes.The proposed HRM can transfer reconfiguration instructions/contexts to a particular PE or associated PEs simultaneously in one clock cycle in unicast,multicast and broadcast mode,and shut down the unnecessary PE/PEs according to the current configuration.To verify the correctness and efficiency,we implement it in RTL synthesis and FPGA prototype.Compared to prior works,the experiment results show that the HRM has improved the work frequency by an average of 23.4%,increased the updating speed by 2×,and reduced the area by 36.9%;HRM can also power off the unnecessary PEs which reduced 51%of dynamic power dissipation in certain application configuration.Furthermore,in the data-driven mode,the system frequency can reach 214 MHz,which is 1.68×higher compared with the programmable mode.展开更多
Reconfiguration is the key to produce an applicable ternary optical computer (TOC). The method to implement the reconfiguration function determines whether a TOC can step into applied fields or not. In this work, a ...Reconfiguration is the key to produce an applicable ternary optical computer (TOC). The method to implement the reconfiguration function determines whether a TOC can step into applied fields or not. In this work, a design of the reconfiguration circuit based on field programmable gates array (FPGA) is proposed, and the structure of the entire hardware system is discussed.展开更多
In this paper,an active fault accommodate strategy is proposed for the plant in the presence of actuator fault and input constraints,which is a combination of a direct adaptive control algorithm with multiple model sw...In this paper,an active fault accommodate strategy is proposed for the plant in the presence of actuator fault and input constraints,which is a combination of a direct adaptive control algorithm with multiple model switching.The μ-modification is introduced in the model reference architecture to construct the adaptive controller.The proof of stability is based on the candidate Lyapunov function,while appropriate switching of multiple models guarantees asymptotic tracking of the system states and the boundedness of all signals.Simulation results illustrate the efficiency of the proposed method.展开更多
Most of the existing approaches focus on identifying mismatches and synthesizing adaptors at design-time or recently at run-time. However, few works have been proposed to support adaptor reconfiguration when services ...Most of the existing approaches focus on identifying mismatches and synthesizing adaptors at design-time or recently at run-time. However, few works have been proposed to support adaptor reconfiguration when services in the composition evolve due to changes in business needs. To address the deficiencies, the problem of adaptor reconfiguration is targeted in the context of service composition. Firstly, the formal models for describing services and adaptors are presented. Then, under this formalization,the notion of reconfiguration compliance is proposed to determine the validity of an adaptor instance with respect to its history executions and future executions. Based on the notion,the algorithm for reconfiguration analysis of adaptors is presented and it can be used for determining the migratability of an adaptor instance and the corresponding target state of reconfiguration if migratable.Finally,feasibility of the proposed approach is validated on a realistic case study. The proposed approach improves the flexibility of adaptor-based service composition by equipping adaptors with reconfiguration capabilities.展开更多
Summary:The corona virus disease 2019(COVID-19)is an emerging respiratory infectious disease caused by SARS-CoV-2,which first occurred in December 2019 in Wuhan,China.These days,in China,chest CT is used for diagnosis...Summary:The corona virus disease 2019(COVID-19)is an emerging respiratory infectious disease caused by SARS-CoV-2,which first occurred in December 2019 in Wuhan,China.These days,in China,chest CT is used for diagnosis of COVID-19,as an important complement to the reverse-transcription polymerase chain reaction(RT-PCR)test.Because of contacting with a large number of suspected or probable cases closely during chest CT examination,radiographers are easily infected with COVID-19.This article included the rearrangement of CT examination room in fever clinic,the rearrangement of human resources in radiology department,and the drafting of new operating procedures for radiologists who carry out CT examination on COVID-19 patients.This article also introduced the emergency management procedures of the department of radiology during the outbreak,and the experience of infection prevention for the staff of the department of radiology.展开更多
Constellation reconfiguration is a critical issue to recover from the satellite failure,maintain the regular operation,and enhance the overall performance.The constellation reconfiguration problem faces the difficulti...Constellation reconfiguration is a critical issue to recover from the satellite failure,maintain the regular operation,and enhance the overall performance.The constellation reconfiguration problem faces the difficulties of high dimensionality of design variables and extremely large decision space due to the great and continuously growing constellation size.To solve such real-world problems that can be hardly solved by traditional algorithms,the evolutionary operators should be promoted with available domain knowledge to guide the algorithm to explore the promising regions of the trade space.An adaptive innovationdriven multi-objective evolutionary algorithm(MOEA-AI)employing automated innovation(AI)and adaptive operator selection(AOS)is proposed to extract and apply domain knowledge.The available knowledge is extracted from the final or intermediate solution sets and integrated into an operator by the automated innovation mechanism.To prevent the overuse of knowledgedependent operators,AOS provides top-level management between the knowledge-dependent operators and conventional evolutionary operators.It evaluates and selects operators according to their actual performance,which helps to identify useful operators from the candidate set.The efficacy of the MOEAAI framework is demonstrated by the simulation of emergency missions.It was verified that the proposed algorithm can discover a non-dominant solution set with better quality,more homogeneous distribution,and better adaptation to practical situations.展开更多
Two common problems for a typical Power distribution system are voltage collapse & instability. Challenge is to identify the vulnerable nodes and apply the effective corrective actions. This paper presents a proba...Two common problems for a typical Power distribution system are voltage collapse & instability. Challenge is to identify the vulnerable nodes and apply the effective corrective actions. This paper presents a probabilistic fuzzy approach to assess the node status and proposes feeder reconfiguration as a method to address the same. Feeder reconfiguration is altering the topological structures of distribution feeders by changing the open/closed states of the sectionalizing and ties switches. The solution is converge using a probabilistic fuzzy modeled solution, which defines the nodal vulnerability index (VI) as a function of node voltage and node voltage stability index and predicts nodes critical to voltage collapse. The information is further used to plan best combination of feeders from each loop in distribution system to be switched out such that the resulting configuration gives the optimal performance i.e. best voltage profile and minimal kW losses. The proposed method is tested on established radial distribution system and results are presented.展开更多
The multi-modes feature, the measure of the manipulating flexibility, andself-reconfiguration control method of the underactuated redundant manipulators are investigatedbased on the optimizing technology. The relation...The multi-modes feature, the measure of the manipulating flexibility, andself-reconfiguration control method of the underactuated redundant manipulators are investigatedbased on the optimizing technology. The relationship between the configuration of the joint spaceand the manipulating flexibility of the underactuated redundant manipulator is analyzed, a newmeasure of manipulating flexibility ellipsoid for the underactuated redundant manipulator withpassive joints in locked mode is proposed, which can be used to get the optimal configuration forthe realization of the self-reconfiguration control. Furthermore, a time-varying nonlinear controlmethod based on harmonic inputs is suggested for fulfilling the self-reconfiguration. A simulationexample of a three-DOFs underactuated manipulator with one passive joint features some aspects ofthe investigations.展开更多
Electric power is widely used as the main energy source of ship integrated power system(SIPS), which contains power network and electric power network. SIPS network reconfiguration is a non-linear large-scale problem....Electric power is widely used as the main energy source of ship integrated power system(SIPS), which contains power network and electric power network. SIPS network reconfiguration is a non-linear large-scale problem. The reconfiguration solution influences the safety and stable operation of the power system. According to the operational characteristics of SIPS, a simplified model of power network and a mathematical model for network reconfiguration are established. Based on these models, a multi-agent and ant colony optimization(MAACO) is proposed to solve the problem of network reconfiguration. The simulations are carried out to demonstrate that the optimization method can reconstruct the integrated power system network accurately and efficiently.展开更多
Optimal distribution feeder reconfiguration (DFR) is a valuable and costless approach to increase the load balance, reduce the amount of power losses, and improve the voltage of the buses. In this way, this paper ai...Optimal distribution feeder reconfiguration (DFR) is a valuable and costless approach to increase the load balance, reduce the amount of power losses, and improve the voltage of the buses. In this way, this paper aims to investigate the optimal DFR strategy as a proper tool to improve the reliability of the radial distribution networks. The idea of failure rate reduction is employed to see the effect of feeder current reduction on the reliability of the system more accurately. The objects to be investigated are system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), average energy not supplied (AENS) and total active power losses. The problem is then formulated in a stochastic framework based on the point estimate method (PEM) to handle the uncertainty effects. The feasibility and satisfying performance of the proposed method is examined on a standard IEEE test system.展开更多
Compactly supported radial basis function can enable the coefficient matrix of solving weigh linear system to have a sparse banded structure, thereby reducing the complexity of the algorithm. Firstly, based on the com...Compactly supported radial basis function can enable the coefficient matrix of solving weigh linear system to have a sparse banded structure, thereby reducing the complexity of the algorithm. Firstly, based on the compactly supported radial basis function, the paper makes the complex quadratic function (Multiquadric, MQ for short) to be transformed and proposes a class of compactly supported MQ function. Secondly, the paper describes a method that interpolates discrete motion capture data to solve the motion vectors of the interpolation points and they are used in facial expression reconstruction. Finally, according to this characteris- tic of the uneven distribution of the face markers, the markers are numbered and grouped in accordance with the density level, and then be interpolated in line with each group. The approach not only ensures the accuracy of the deformation of face local area and smoothness, but also reduces the time complexity of computing.展开更多
This paper presents a reconfiguration of electric power distribution network based on the symbiotic organism search algorithm (SOS). The goal here is to come out with an optimal reconfiguration of a power distribution...This paper presents a reconfiguration of electric power distribution network based on the symbiotic organism search algorithm (SOS). The goal here is to come out with an optimal reconfiguration of a power distribution network that minimises the active power losses for a good power flow. This method is applied to IEEE 33 bus and the results show a significant reduction of active power losses. The execution time for this algorithm is found to be smaller compared to other metaheuristic algorithms.展开更多
The state-of-art Web services composition approaches are facing more and more serious bottlenecks of effectiveness and stability with the increasing diversity and real-time requirements of applications, since new web ...The state-of-art Web services composition approaches are facing more and more serious bottlenecks of effectiveness and stability with the increasing diversity and real-time requirements of applications, since new web service chain must be generated from “scratch” for each application. To break these bottlenecks, this paper presents a Min-Conflict Heuristic-Based Web Service Chain Reconfiguration Approach(MCHRC) to maximal reuse relative web services chain: a min-conflict heuristic based regression search algorithms is proposed to implement the web services chain reconfiguration based on the formal definition of process constraint and integrity constraint to guarantee the correctness and integrality of the reconfiguration. This benefits the service reuse and then can relieve the time complexity of web service composition and improve web services chain executing stability by reduce service provider load. Experimental results show that this approach makes significant improvement on the effectiveness of web services composition.展开更多
基金This work was supported by Ph.D.Intelligent Innovation Foundation Project(201-CXCY-A01-08-19-01)Science and Technology on Information System Engineering Laboratory(05202007).
文摘As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS.First,a unified resilience-driven coopera-tive reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement.Subsequently,a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence,combining the cooperative pair resilience contribution index(CPRCI)and coop-erative pair importance index(CPII).At last,the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include differ-ent attack modes and intensities.The analysis results can pro-vide a reference for decision-makers to manage UWSoS.
基金This research is supported by the Science and Technology Program of Gansu Province(No.23JRRA880).
文摘With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.
基金supported by the National Natural Science Foundation of China under Grant 52077146.
文摘With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.
基金supported in part by the National Natural Science Foundation of China(62203352,U2003110)in part by the Key Laboratory Project of Shaanxi Provincial Department of Education(20JS110)in part by the Thousand Talents Plan of Shaanxi Province for Young Professionals。
文摘Maximizing the utilization of lithium-ion battery capacity is an important means to alleviate the range anxiety of electric vehicles.Battery pack inconsistency is the main limiting factor for improving battery pack capacity utilization,and poses major safety hazards to energy storage systems.To solve this problem,a maximum capacity utilization scheme based on a path planning algorithm is proposed.Specifically,the reconfigurable topology proposed is highly flexible and fault-tolerant,enabling battery pack consistency through alternating cell discharge and reducing the increased risk of short circuits due to relay error.The Dijkstra algorithm is used to find the optimal energy path,which can effectively remove faulty cells and find the current path with the best consistency of the battery pack and the lowest relay loss.Finally,the effectiveness of the scheme is verified by hardware-in-the-loop experiments,and the experimental results show that the state-of-charge SOC consistency of the battery pack at the end of discharge is increased by 34.18%,the relay energy loss is reduced by 0.16%,and the fault unit is effectively isolated.
文摘Low-carbon hydrogen can play a significant role in decarbonizing the world. Hydrogen is currently mainly produced from fossil sources,requiring additional CO_(2)capture to decarbonize, which energy intense and costly. In a recent Green Energy & Environment paper, Cheng and Di et al. proposed a novel integration process referred to as SECLR_(HC) to generate high-purity H_(2) by in-situ separation of H_(2)and CO without using any additional separation unit. Theoretically, the proposed process can essentially achieve the separation of C and H in gaseous fuel via a reconfigured reaction process, and thus attaining high-purity hydrogen of ~99%, as well as good carbon and hydrogen utilization rates and economic feasibility. It displays an optimistic prospect that industrial decarbonization is not necessarily expensive, as long as a suitable CCS measure can be integrated into the industrial manufacturing process.
基金The project supported by the National Natural Science Foundation of China(10672084 and 10672084)The Special Science Foundation of the Doctoral Discipline of the Minstry of Education of China(20060003097)
文摘Reconfiguration of formation flying around a halo orbit of the Sun-Earth restricted three body system is investigated with impulse maneuvers. For a short time reconfiguration, the two-impulse maneuver is investigated with both analytical and numerical methods and the Beginning-Ending (BE) method is proven to be an energy-optimal one of all two-impulse (TI) reconfigurations, and the energy consumption of BE is independent of the position of the chief spacecraft, and decreases with the reconfiguration time. Then, genetic algorithm is adopted to optimize the energy consumption. The results show that the optimal energy increases with radius difference between the initial and final orbits, and decreases with the reconfiguration time.
基金supported by the National Natural Science Foundation of China (Nos. 61834005, 61602377, 61772417, 61802304, 61874087)the Shaanxi International Science and Technology Cooperation Program No. 2018KW-006+1 种基金Shaanxi Provincial Key R&D Plan under Grant No. 2017GY-060Shaanxi Province Co-ordination Innovation Project of Science and Technology under Grant No. 2016KTZDGY02-04-02
文摘In order to accommodate the variety of algorithms with different performance in specific application and improve power efficiency,reconfigurable architecture has become an effective methodology in academia and industry.However,existing architectures suffer from performance bottleneck due to slow updating of contexts and inadequate flexibility.This paper presents an H-tree based reconfiguration mechanism(HRM)with Huffman-coding-like and mask addressing method in a homogeneous processing element(PE)array,which supports both programmable and data-driven modes.The proposed HRM can transfer reconfiguration instructions/contexts to a particular PE or associated PEs simultaneously in one clock cycle in unicast,multicast and broadcast mode,and shut down the unnecessary PE/PEs according to the current configuration.To verify the correctness and efficiency,we implement it in RTL synthesis and FPGA prototype.Compared to prior works,the experiment results show that the HRM has improved the work frequency by an average of 23.4%,increased the updating speed by 2×,and reduced the area by 36.9%;HRM can also power off the unnecessary PEs which reduced 51%of dynamic power dissipation in certain application configuration.Furthermore,in the data-driven mode,the system frequency can reach 214 MHz,which is 1.68×higher compared with the programmable mode.
基金Project supported by the National Natural Science Foundation of China(Grant No.61073049)the Shanghai Leading Academic Discipline Project(Grant No.J50103)the Doctorate Foundation of Education Ministry of China(Grant No.20093108110016)
文摘Reconfiguration is the key to produce an applicable ternary optical computer (TOC). The method to implement the reconfiguration function determines whether a TOC can step into applied fields or not. In this work, a design of the reconfiguration circuit based on field programmable gates array (FPGA) is proposed, and the structure of the entire hardware system is discussed.
基金supported by the Aeronautics Science Foundation of China(No.2007ZC52039)the National Natural Science Foundation of China(No.90816023)
文摘In this paper,an active fault accommodate strategy is proposed for the plant in the presence of actuator fault and input constraints,which is a combination of a direct adaptive control algorithm with multiple model switching.The μ-modification is introduced in the model reference architecture to construct the adaptive controller.The proof of stability is based on the candidate Lyapunov function,while appropriate switching of multiple models guarantees asymptotic tracking of the system states and the boundedness of all signals.Simulation results illustrate the efficiency of the proposed method.
基金National Natural Science Foundations of China(Nos.61272083,61262002,61170043)China Postdoctoral Science Foundation(Nos.20110491411,2014M562177)The Science Foundations of Nanjing Institute of Technology,China(Nos.QKJB201304,YKJ201420)
文摘Most of the existing approaches focus on identifying mismatches and synthesizing adaptors at design-time or recently at run-time. However, few works have been proposed to support adaptor reconfiguration when services in the composition evolve due to changes in business needs. To address the deficiencies, the problem of adaptor reconfiguration is targeted in the context of service composition. Firstly, the formal models for describing services and adaptors are presented. Then, under this formalization,the notion of reconfiguration compliance is proposed to determine the validity of an adaptor instance with respect to its history executions and future executions. Based on the notion,the algorithm for reconfiguration analysis of adaptors is presented and it can be used for determining the migratability of an adaptor instance and the corresponding target state of reconfiguration if migratable.Finally,feasibility of the proposed approach is validated on a realistic case study. The proposed approach improves the flexibility of adaptor-based service composition by equipping adaptors with reconfiguration capabilities.
文摘Summary:The corona virus disease 2019(COVID-19)is an emerging respiratory infectious disease caused by SARS-CoV-2,which first occurred in December 2019 in Wuhan,China.These days,in China,chest CT is used for diagnosis of COVID-19,as an important complement to the reverse-transcription polymerase chain reaction(RT-PCR)test.Because of contacting with a large number of suspected or probable cases closely during chest CT examination,radiographers are easily infected with COVID-19.This article included the rearrangement of CT examination room in fever clinic,the rearrangement of human resources in radiology department,and the drafting of new operating procedures for radiologists who carry out CT examination on COVID-19 patients.This article also introduced the emergency management procedures of the department of radiology during the outbreak,and the experience of infection prevention for the staff of the department of radiology.
基金supported by the National Natural Science Foundation of China(11802333)the Scientific Research Program of the National University of Defence Technology(ZK18-03-34)。
文摘Constellation reconfiguration is a critical issue to recover from the satellite failure,maintain the regular operation,and enhance the overall performance.The constellation reconfiguration problem faces the difficulties of high dimensionality of design variables and extremely large decision space due to the great and continuously growing constellation size.To solve such real-world problems that can be hardly solved by traditional algorithms,the evolutionary operators should be promoted with available domain knowledge to guide the algorithm to explore the promising regions of the trade space.An adaptive innovationdriven multi-objective evolutionary algorithm(MOEA-AI)employing automated innovation(AI)and adaptive operator selection(AOS)is proposed to extract and apply domain knowledge.The available knowledge is extracted from the final or intermediate solution sets and integrated into an operator by the automated innovation mechanism.To prevent the overuse of knowledgedependent operators,AOS provides top-level management between the knowledge-dependent operators and conventional evolutionary operators.It evaluates and selects operators according to their actual performance,which helps to identify useful operators from the candidate set.The efficacy of the MOEAAI framework is demonstrated by the simulation of emergency missions.It was verified that the proposed algorithm can discover a non-dominant solution set with better quality,more homogeneous distribution,and better adaptation to practical situations.
文摘Two common problems for a typical Power distribution system are voltage collapse & instability. Challenge is to identify the vulnerable nodes and apply the effective corrective actions. This paper presents a probabilistic fuzzy approach to assess the node status and proposes feeder reconfiguration as a method to address the same. Feeder reconfiguration is altering the topological structures of distribution feeders by changing the open/closed states of the sectionalizing and ties switches. The solution is converge using a probabilistic fuzzy modeled solution, which defines the nodal vulnerability index (VI) as a function of node voltage and node voltage stability index and predicts nodes critical to voltage collapse. The information is further used to plan best combination of feeders from each loop in distribution system to be switched out such that the resulting configuration gives the optimal performance i.e. best voltage profile and minimal kW losses. The proposed method is tested on established radial distribution system and results are presented.
基金This project is supported by National Natural Science Foundation of China (No.50375007,No.50475177).
文摘The multi-modes feature, the measure of the manipulating flexibility, andself-reconfiguration control method of the underactuated redundant manipulators are investigatedbased on the optimizing technology. The relationship between the configuration of the joint spaceand the manipulating flexibility of the underactuated redundant manipulator is analyzed, a newmeasure of manipulating flexibility ellipsoid for the underactuated redundant manipulator withpassive joints in locked mode is proposed, which can be used to get the optimal configuration forthe realization of the self-reconfiguration control. Furthermore, a time-varying nonlinear controlmethod based on harmonic inputs is suggested for fulfilling the self-reconfiguration. A simulationexample of a three-DOFs underactuated manipulator with one passive joint features some aspects ofthe investigations.
基金supported by the National Natural Science Foundation of China (4177402141974005)。
文摘Electric power is widely used as the main energy source of ship integrated power system(SIPS), which contains power network and electric power network. SIPS network reconfiguration is a non-linear large-scale problem. The reconfiguration solution influences the safety and stable operation of the power system. According to the operational characteristics of SIPS, a simplified model of power network and a mathematical model for network reconfiguration are established. Based on these models, a multi-agent and ant colony optimization(MAACO) is proposed to solve the problem of network reconfiguration. The simulations are carried out to demonstrate that the optimization method can reconstruct the integrated power system network accurately and efficiently.
文摘Optimal distribution feeder reconfiguration (DFR) is a valuable and costless approach to increase the load balance, reduce the amount of power losses, and improve the voltage of the buses. In this way, this paper aims to investigate the optimal DFR strategy as a proper tool to improve the reliability of the radial distribution networks. The idea of failure rate reduction is employed to see the effect of feeder current reduction on the reliability of the system more accurately. The objects to be investigated are system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), average energy not supplied (AENS) and total active power losses. The problem is then formulated in a stochastic framework based on the point estimate method (PEM) to handle the uncertainty effects. The feasibility and satisfying performance of the proposed method is examined on a standard IEEE test system.
基金Supported by the National Natural Science Foundation of China (No.60875046)by Program for Changjiang Scholars and Innovative Research Team in University(No.IRT1109)+5 种基金the Key Project of Chinese Ministry of Education (No.209029)the Program for Liaoning Excellent Talents in University(No.LR201003)the Program for Liaoning Science and Technology Research in University (No.LS2010008,2009S008,2009S009,LS2010179)the Program for Liaoning Innovative Research Team in University(Nos.2009T005,LT2010005,LT2011018)Natural Science Foundation of Liaoning Province (201102008)by "Liaoning BaiQianWan Talents Program(2010921010,2011921009)"
文摘Compactly supported radial basis function can enable the coefficient matrix of solving weigh linear system to have a sparse banded structure, thereby reducing the complexity of the algorithm. Firstly, based on the compactly supported radial basis function, the paper makes the complex quadratic function (Multiquadric, MQ for short) to be transformed and proposes a class of compactly supported MQ function. Secondly, the paper describes a method that interpolates discrete motion capture data to solve the motion vectors of the interpolation points and they are used in facial expression reconstruction. Finally, according to this characteris- tic of the uneven distribution of the face markers, the markers are numbered and grouped in accordance with the density level, and then be interpolated in line with each group. The approach not only ensures the accuracy of the deformation of face local area and smoothness, but also reduces the time complexity of computing.
文摘This paper presents a reconfiguration of electric power distribution network based on the symbiotic organism search algorithm (SOS). The goal here is to come out with an optimal reconfiguration of a power distribution network that minimises the active power losses for a good power flow. This method is applied to IEEE 33 bus and the results show a significant reduction of active power losses. The execution time for this algorithm is found to be smaller compared to other metaheuristic algorithms.
文摘The state-of-art Web services composition approaches are facing more and more serious bottlenecks of effectiveness and stability with the increasing diversity and real-time requirements of applications, since new web service chain must be generated from “scratch” for each application. To break these bottlenecks, this paper presents a Min-Conflict Heuristic-Based Web Service Chain Reconfiguration Approach(MCHRC) to maximal reuse relative web services chain: a min-conflict heuristic based regression search algorithms is proposed to implement the web services chain reconfiguration based on the formal definition of process constraint and integrity constraint to guarantee the correctness and integrality of the reconfiguration. This benefits the service reuse and then can relieve the time complexity of web service composition and improve web services chain executing stability by reduce service provider load. Experimental results show that this approach makes significant improvement on the effectiveness of web services composition.