As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crud...As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.展开更多
Attention is concentrated on how to perform the innovative design during the process of pumping unit conceptual design, and how to enhance design efficiency and inspire creativity. Aiming at the shortages of conceptua...Attention is concentrated on how to perform the innovative design during the process of pumping unit conceptual design, and how to enhance design efficiency and inspire creativity. Aiming at the shortages of conceptual design, introducing the theory of inventive problem solving （TRIZ） into the mechanical product design for producing innovative ideas, and using the advanced computer-aided technique, the intelligent decision support system （IDSS） based on TRIZ （TRIZ-IDSS） has been constructed. The construction method, system structure, conceptual production, decisionmaking and evaluation of the problem solving subsystem are discussed. The innovative conceptual design of pumping units indicates that the system can help the engineers open up a new space of thinking, overcome the thinking inertia, and put forward innovative design concepts. This system also can offer the scientific instructions for the innovative design of mechanical products.展开更多
It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only b...It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.展开更多
The Janus fabrics designed for personal moisture/thermal regulation have garnered significant attention for their potential to enhance human comfort.However,the development of smart and dynamic fabrics capable of mana...The Janus fabrics designed for personal moisture/thermal regulation have garnered significant attention for their potential to enhance human comfort.However,the development of smart and dynamic fabrics capable of managing personal moisture/thermal comfort in response to changing external environments remains a challenge.Herein,a smart cellulose-based Janus fabric was designed to dynamically manage personal moisture/heat.The cotton fabric was grafted with N-isopropylacrylamide to construct a temperature-stimulated transport channel.Subsequently,hydrophobic ethyl cellulose and hydrophilic cellulose nanofiber were sprayed on the bottom and top sides of the fabric to obtain wettability gradient.The fabric exhibits anti-gravity directional liquid transportation from hydrophobic side to hydrophilic side,and can dynamically and continuously control the transportation time in a wide range of 3–66 s as the temperature increases from 10 to 40℃.This smart fabric can quickly dissipate heat at high temperatures,while at low temperatures,it can slow down the heat dissipation rate and prevent the human from becoming too cold.In addition,the fabric has UV shielding and photodynamic antibacterial properties through depositing graphitic carbon nitride nanosheets on the hydrophilic side.This smart fabric offers an innovative approach to maximizing personal comfort in environments with significant temperature variations.展开更多
The multi-mode integrated railway system,anchored by the high-speed railway,caters to the diverse travel requirements both within and between cities,offering safe,comfortable,punctual,and eco-friendly transportation s...The multi-mode integrated railway system,anchored by the high-speed railway,caters to the diverse travel requirements both within and between cities,offering safe,comfortable,punctual,and eco-friendly transportation services.With the expansion of the railway networks,enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation.In light of the prevailing application of artificial intelligence technologies within railway systems,this study leverages large model technology characterized by robust learning capabilities,efficient associative abilities,and linkage analysis to propose an Artificial-intelligent(AI)-powered railway control and dispatching system.This system is elaborately designed with four core functions,including global optimum unattended dispatching,synergetic transportation in multiple modes,high-speed automatic control,and precise maintenance decision and execution.The deployment pathway and essential tasks of the system are further delineated,alongside the challenges and obstacles encountered.The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system,ensuring a more effective alignment between transportation services and passenger demands.展开更多
Quantum battery exploits the principle of quantum mechanics to transport and store energy. We study the energy transportation of the central-spin quantum battery, which is composed of N_b spins serving as the battery ...Quantum battery exploits the principle of quantum mechanics to transport and store energy. We study the energy transportation of the central-spin quantum battery, which is composed of N_b spins serving as the battery cells, and surrounded by N_c spins serving as the charger cells. We apply the invariant subspace method to solve the dynamics of the central-spin battery with a large number of spins. We establish a universal inverse relationship between the battery capacity and the battery–charger entanglement, which persists in any size of the battery and charger cells. Moreover, we find that when N_b= N_c, the central-spin battery has the optimal energy transportation, corresponding to the minimal battery–charger entanglement. Surprisingly, the central-spin battery has a uniform energy transportation behaviors in certain battery–charger scales. Our results reveal a nonmonotonic relationship between the battery–charger size and the energy transportation efficiency, which may provide more insights on designing other types of quantum batteries.展开更多
Intelligent vehicle applications provide convenience but raise privacy and security concerns.Misuse of sensitive data,including vehicle location,and facial recognition information,poses a threat to user privacy.Hence,...Intelligent vehicle applications provide convenience but raise privacy and security concerns.Misuse of sensitive data,including vehicle location,and facial recognition information,poses a threat to user privacy.Hence,traffic classification is vital for promptly overseeing and controlling applications with sensitive information.In this paper,we propose ETNet,a framework that combines multiple features and leverages self-attention mechanisms to learn deep relationships between packets.ET-Net employs a multisimilarity triplet network to extract features from raw bytes,and exploits self-attention to capture long-range dependencies within packets in a session and contextual information features.Additionally,we utilizing the loss function to more effectively integrate information acquired from both byte sequences and their corresponding lengths.Through simulated evaluations on datasets with similar attributes,ET-Net demonstrates the ability to finely distinguish between nine categories of applications,achieving superior results compared to existing methods.展开更多
In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In...In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In the context of important physical characteristics of the backscattering polarization of RIS,the modeling of the RIS wireless channel requires a tradeoff between complexity and accuracy,as well as usability and simplicity.For channel modeling of RIS systems,RIS is modelled as multi-equivalent virtual base stations(BSs)induced by multi polarized electromagnetic waves from different incident directions.The comparison between test and simulation results demonstrates that the proposed algorithm effectively captures the key characteristics of the general RIS element polarization physical model and provides accurate results.展开更多
Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth...Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.展开更多
This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration s...This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function.展开更多
This study presents novel findings on the potential of phloretin,an apple polyphenol,to enhance the effectiveness of anti-human epidermal growth factor receptor-2(HER2)antibody therapy in HER2-positive breast cancer p...This study presents novel findings on the potential of phloretin,an apple polyphenol,to enhance the effectiveness of anti-human epidermal growth factor receptor-2(HER2)antibody therapy in HER2-positive breast cancer patients.Our research reveals that phloretin inhibits typeⅡglucose transporter(GLUT2)activity,significantly reducing cancer cell glucose uptake.We confirmed the overexpression of GLUT1 and GLUT2 mRNA in paired human breast tumor tissues,with GLUT2 overexpression associated explicitly with poorer survival rates in breast cancer patients.Treatment with phloretin was observed to increase the interaction between GLUT2 and HER2 proteins,attenuate glycolysis,and enhance the binding affinity of anti-HER2 antibody drugs to target human breast cancer cells.Furthermore,the efficacy of the combination therapy involving phloretin and antibody drugs was reaffirmed in a cell-derived xenograft tumor animal model,particularly in suppressing the growth of trastuzumab-resistant HER2-positive(HER2+)breast cancer.These significant findings suggest that targeting GLUT2 activity with phloretin in combination with anti-HER2 antibody drugs may help mitigate the development of drug-resistant breast cancer,offering valuable insights for enhancing tumor treatment strategies and contributing to developing more effective therapies.展开更多
The unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)has been deemed a promising solution for energy-constrained devices to run smart applications with computationintensive and latency-sensitive require...The unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)has been deemed a promising solution for energy-constrained devices to run smart applications with computationintensive and latency-sensitive requirements,especially in some infrastructure-limited areas or some emergency scenarios.However,the multi-UAVassisted MEC network remains largely unexplored.In this paper,the dynamic trajectory optimization and computation offloading are studied in a multi-UAVassisted MEC system where multiple UAVs fly over a target area with different trajectories to serve ground users.By considering the dynamic channel condition and random task arrival and jointly optimizing UAVs'trajectories,user association,and subchannel assignment,the average long-term sum of the user energy consumption minimization problem is formulated.To address the problem involving both discrete and continuous variables,a hybrid decision deep reinforcement learning(DRL)-based intelligent energyefficient resource allocation and trajectory optimization algorithm is proposed,named HDRT algorithm,where deep Q network(DQN)and deep deterministic policy gradient(DDPG)are invoked to process discrete and continuous variables,respectively.Simulation results show that the proposed HDRT algorithm converges fast and outperforms other benchmarks in the aspect of user energy consumption and latency.展开更多
The central air conditioning system in an intelligent building (IB) was analyzed and modeled in order to perform the optimization scheduling strategy of the central air conditioning system. A set of models proposed ...The central air conditioning system in an intelligent building (IB) was analyzed and modeled in order to perform the optimization scheduling strategy of the central air conditioning system. A set of models proposed and a type of periodically autoregressive model (PAR) based on the improved genetic algorithms (IGA) were used to perform the optimum energy saving scheduling. The example of the Liangmahe Plaza was taken to show the effectiveness of the methods.展开更多
The principle and the constitution of an intelligent system for on-line and real-time montitoring tool cutting state were discussed and a synthetic sensors schedule combined a new type fluid acoustic emission sens...The principle and the constitution of an intelligent system for on-line and real-time montitoring tool cutting state were discussed and a synthetic sensors schedule combined a new type fluid acoustic emission sensor (AE) with motor current sensor was presented. The parallel communication between control system of machine tools, the monitoring intelligent system,and several decision-making systems for identifying tool cutting state was established It can auto - matically select the sensor way ,monitoring mode and identifying method in machining process- ing so as to build a successful and effective intelligent system for on -line and real-time moni- toring cutting tool states in FMS.展开更多
An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system w...An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system was established. The periodically autoregressive models (PARM) based on genetic algorithms (GA) were used to predict the next day’s cold load. The improved genetic algorithms (IGA) with stochastic real number coding were used to finish the optimum energy saving scheduling of the system. The simulation results for the building of the Liangmahe Plaza show that the proposed strategy can save energy up to about 24 5%.展开更多
Reconfigurable intelligent surface(RIS)can manipulate the wireless propagation environment by smartly adjusting the amplitude/phase in a programmable panel,enjoying the improved performance.The accurate acquisition of...Reconfigurable intelligent surface(RIS)can manipulate the wireless propagation environment by smartly adjusting the amplitude/phase in a programmable panel,enjoying the improved performance.The accurate acquisition of the instantaneous channel state information(CSI)in the cascaded RIS chain makes an indispensable contribution to the performance gains.However,it is quite challenging to estimate the CSI in a time-variant scenario due to the limited signal processing capability of the passive elements embedded in a RIS pannel.In this work,a channel estimation scheme for the RIS-assisted wireless communication system is proposed,which is demonstrated to perform well in a time-variant scenario.The cascaded RIS channel is modeled as a state-space model based upon the mobility situations.In addition,to fully exploit the time correlation of channel,Kalman filter is employed by taking the prior information of channels into account.Further,the optimal reflection coefficients are derived according to the minimum mean square error(MMSE)criterion.Numerical results show that the proposed methods exhibit superior performance if compared with a conventional channel estimation scheme.展开更多
A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search wha...A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search what they need. The system consists of four main components: interface agent, information retrieval agent, broker agent and learning agent. They collaborate to implement system functions. The agents apply learning mechanisms based on an improved ID3 algorithm.展开更多
In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose ...In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.展开更多
Multiple objects decision is used widely in many complex fields. In this paper an idea is provided to construct a train diagram intelligent multiple objects decision support system (TDIMODSS). And the reference point ...Multiple objects decision is used widely in many complex fields. In this paper an idea is provided to construct a train diagram intelligent multiple objects decision support system (TDIMODSS). And the reference point method is used to solve the complicated and large scale problems of making and adjusting train schedule. This paper focuses on the principle and framework of the model base, knowledge base of train diagram. It is shown that the TDIMODSS can solve the problems and their uncertainty in making train diagram, and can combine the expert knowledge, experience and judgement of a decision maker into the system. In addition to that, a friendly working environment is also presented, which brings together the human judgement, the adaptability to environment and the computerised information.展开更多
基金This work was financially supported by the National Natural Science Foundation of China(52074089 and 52104064)Natural Science Foundation of Heilongjiang Province of China(LH2019E019).
文摘As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.
文摘Attention is concentrated on how to perform the innovative design during the process of pumping unit conceptual design, and how to enhance design efficiency and inspire creativity. Aiming at the shortages of conceptual design, introducing the theory of inventive problem solving （TRIZ） into the mechanical product design for producing innovative ideas, and using the advanced computer-aided technique, the intelligent decision support system （IDSS） based on TRIZ （TRIZ-IDSS） has been constructed. The construction method, system structure, conceptual production, decisionmaking and evaluation of the problem solving subsystem are discussed. The innovative conceptual design of pumping units indicates that the system can help the engineers open up a new space of thinking, overcome the thinking inertia, and put forward innovative design concepts. This system also can offer the scientific instructions for the innovative design of mechanical products.
文摘It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.
基金support of this work by National Key Research and Development Program of China(2019YFC19059003)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(23KJB430024)+1 种基金Jiangsu Funding Program for Excellent Postdoctoral Talent(2023ZB680)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)are gratefully acknowledged.
文摘The Janus fabrics designed for personal moisture/thermal regulation have garnered significant attention for their potential to enhance human comfort.However,the development of smart and dynamic fabrics capable of managing personal moisture/thermal comfort in response to changing external environments remains a challenge.Herein,a smart cellulose-based Janus fabric was designed to dynamically manage personal moisture/heat.The cotton fabric was grafted with N-isopropylacrylamide to construct a temperature-stimulated transport channel.Subsequently,hydrophobic ethyl cellulose and hydrophilic cellulose nanofiber were sprayed on the bottom and top sides of the fabric to obtain wettability gradient.The fabric exhibits anti-gravity directional liquid transportation from hydrophobic side to hydrophilic side,and can dynamically and continuously control the transportation time in a wide range of 3–66 s as the temperature increases from 10 to 40℃.This smart fabric can quickly dissipate heat at high temperatures,while at low temperatures,it can slow down the heat dissipation rate and prevent the human from becoming too cold.In addition,the fabric has UV shielding and photodynamic antibacterial properties through depositing graphitic carbon nitride nanosheets on the hydrophilic side.This smart fabric offers an innovative approach to maximizing personal comfort in environments with significant temperature variations.
基金supported by the National Key R&D Program of China(2022YFB4300500).
文摘The multi-mode integrated railway system,anchored by the high-speed railway,caters to the diverse travel requirements both within and between cities,offering safe,comfortable,punctual,and eco-friendly transportation services.With the expansion of the railway networks,enhancing the efficiency and safety of the comprehensive system has become a crucial issue in the advanced development of railway transportation.In light of the prevailing application of artificial intelligence technologies within railway systems,this study leverages large model technology characterized by robust learning capabilities,efficient associative abilities,and linkage analysis to propose an Artificial-intelligent(AI)-powered railway control and dispatching system.This system is elaborately designed with four core functions,including global optimum unattended dispatching,synergetic transportation in multiple modes,high-speed automatic control,and precise maintenance decision and execution.The deployment pathway and essential tasks of the system are further delineated,alongside the challenges and obstacles encountered.The AI-powered system promises a significant enhancement in the operational efficiency and safety of the composite railway system,ensuring a more effective alignment between transportation services and passenger demands.
基金Project supported by the National Natural Science Foundation (Grant Nos. 12275215,12305028,and 12247103)the Major Basic Research Program of the Natural Science of Shaanxi Province,China (Grant No. 2021JCW-19)Shaanxi Fundamental Science Research Project for Mathematics and Physics (Grant No. 22JSZ005)。
文摘Quantum battery exploits the principle of quantum mechanics to transport and store energy. We study the energy transportation of the central-spin quantum battery, which is composed of N_b spins serving as the battery cells, and surrounded by N_c spins serving as the charger cells. We apply the invariant subspace method to solve the dynamics of the central-spin battery with a large number of spins. We establish a universal inverse relationship between the battery capacity and the battery–charger entanglement, which persists in any size of the battery and charger cells. Moreover, we find that when N_b= N_c, the central-spin battery has the optimal energy transportation, corresponding to the minimal battery–charger entanglement. Surprisingly, the central-spin battery has a uniform energy transportation behaviors in certain battery–charger scales. Our results reveal a nonmonotonic relationship between the battery–charger size and the energy transportation efficiency, which may provide more insights on designing other types of quantum batteries.
基金supported by National Key Research and Development Program of China(2022YFB3104903)S&T Program of Hebei(No.SZX2020034).
文摘Intelligent vehicle applications provide convenience but raise privacy and security concerns.Misuse of sensitive data,including vehicle location,and facial recognition information,poses a threat to user privacy.Hence,traffic classification is vital for promptly overseeing and controlling applications with sensitive information.In this paper,we propose ETNet,a framework that combines multiple features and leverages self-attention mechanisms to learn deep relationships between packets.ET-Net employs a multisimilarity triplet network to extract features from raw bytes,and exploits self-attention to capture long-range dependencies within packets in a session and contextual information features.Additionally,we utilizing the loss function to more effectively integrate information acquired from both byte sequences and their corresponding lengths.Through simulated evaluations on datasets with similar attributes,ET-Net demonstrates the ability to finely distinguish between nine categories of applications,achieving superior results compared to existing methods.
基金supported by Ministry of Science and Technology of the People’s Republic of China(2020YFB1808101)the Project“5G evolution wireless air interface intelligent R&D and verification public platform project”supported by Ministry of Industry and Information Technology of the People’s Republic of China(TC220A04M).
文摘In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In the context of important physical characteristics of the backscattering polarization of RIS,the modeling of the RIS wireless channel requires a tradeoff between complexity and accuracy,as well as usability and simplicity.For channel modeling of RIS systems,RIS is modelled as multi-equivalent virtual base stations(BSs)induced by multi polarized electromagnetic waves from different incident directions.The comparison between test and simulation results demonstrates that the proposed algorithm effectively captures the key characteristics of the general RIS element polarization physical model and provides accurate results.
基金supported by the National Natural Science Foundation of China(62122064,62331021,62371410)the Natural Science Foundation of Fujian Province of China(2023J02005 and 2021J011184)+1 种基金the President Fund of Xiamen University(20720220063)the Nanqiang Outstanding Talents Program of Xiamen University.
文摘Magnetic resonance imaging(MRI)plays an important role in medical diagnosis,generating petabytes of image data annually in large hospitals.This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure.Additionally,local data processing demands substantial manpower and hardware investments.Data isolation across different healthcare institutions hinders crossinstitutional collaboration in clinics and research.In this work,we anticipate an innovative MRI system and its four generations that integrate emerging distributed cloud computing,6G bandwidth,edge computing,federated learning,and blockchain technology.This system is called Cloud-MRI,aiming at solving the problems of MRI data storage security,transmission speed,artificial intelligence(AI)algorithm maintenance,hardware upgrading,and collaborative work.The workflow commences with the transformation of k-space raw data into the standardized Imaging Society for Magnetic Resonance in Medicine Raw Data(ISMRMRD)format.Then,the data are uploaded to the cloud or edge nodes for fast image reconstruction,neural network training,and automatic analysis.Then,the outcomes are seamlessly transmitted to clinics or research institutes for diagnosis and other services.The Cloud-MRI system will save the raw imaging data,reduce the risk of data loss,facilitate inter-institutional medical collaboration,and finally improve diagnostic accuracy and work efficiency.
基金funded by the National Natural Science Foundation of China(12102487)Basic and Applied Basic Research Foundation of Guangdong Province,China(2023A1515012339)+1 种基金Shenzhen Science and Technology Program(ZDSYS20210623091808026)the Discovery Grant(RGPIN-2024-06290)of the Natural Sciences and Engineering Research Council of Canada。
文摘This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function.
基金supported by the Science and Technology Council,Taiwan,China(NSTC 112-2320-B-039-057 and MOST 111-2320-B-039-067-MY3)the China Medical University,Taiwan,China(CMU112-S-18),awarded to Yuan-Soon Ho+1 种基金the China Medical University,Taiwan,China(CMU112-N-02),awarded to Li-Ching Chenthe Science and Technology Council,Taiwan,China(MOST 110-2320B-039-079)。
文摘This study presents novel findings on the potential of phloretin,an apple polyphenol,to enhance the effectiveness of anti-human epidermal growth factor receptor-2(HER2)antibody therapy in HER2-positive breast cancer patients.Our research reveals that phloretin inhibits typeⅡglucose transporter(GLUT2)activity,significantly reducing cancer cell glucose uptake.We confirmed the overexpression of GLUT1 and GLUT2 mRNA in paired human breast tumor tissues,with GLUT2 overexpression associated explicitly with poorer survival rates in breast cancer patients.Treatment with phloretin was observed to increase the interaction between GLUT2 and HER2 proteins,attenuate glycolysis,and enhance the binding affinity of anti-HER2 antibody drugs to target human breast cancer cells.Furthermore,the efficacy of the combination therapy involving phloretin and antibody drugs was reaffirmed in a cell-derived xenograft tumor animal model,particularly in suppressing the growth of trastuzumab-resistant HER2-positive(HER2+)breast cancer.These significant findings suggest that targeting GLUT2 activity with phloretin in combination with anti-HER2 antibody drugs may help mitigate the development of drug-resistant breast cancer,offering valuable insights for enhancing tumor treatment strategies and contributing to developing more effective therapies.
基金supported by National Natural Science Foundation of China(No.62471254)National Natural Science Foundation of China(No.92367302)。
文摘The unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)has been deemed a promising solution for energy-constrained devices to run smart applications with computationintensive and latency-sensitive requirements,especially in some infrastructure-limited areas or some emergency scenarios.However,the multi-UAVassisted MEC network remains largely unexplored.In this paper,the dynamic trajectory optimization and computation offloading are studied in a multi-UAVassisted MEC system where multiple UAVs fly over a target area with different trajectories to serve ground users.By considering the dynamic channel condition and random task arrival and jointly optimizing UAVs'trajectories,user association,and subchannel assignment,the average long-term sum of the user energy consumption minimization problem is formulated.To address the problem involving both discrete and continuous variables,a hybrid decision deep reinforcement learning(DRL)-based intelligent energyefficient resource allocation and trajectory optimization algorithm is proposed,named HDRT algorithm,where deep Q network(DQN)and deep deterministic policy gradient(DDPG)are invoked to process discrete and continuous variables,respectively.Simulation results show that the proposed HDRT algorithm converges fast and outperforms other benchmarks in the aspect of user energy consumption and latency.
文摘The central air conditioning system in an intelligent building (IB) was analyzed and modeled in order to perform the optimization scheduling strategy of the central air conditioning system. A set of models proposed and a type of periodically autoregressive model (PAR) based on the improved genetic algorithms (IGA) were used to perform the optimum energy saving scheduling. The example of the Liangmahe Plaza was taken to show the effectiveness of the methods.
文摘The principle and the constitution of an intelligent system for on-line and real-time montitoring tool cutting state were discussed and a synthetic sensors schedule combined a new type fluid acoustic emission sensor (AE) with motor current sensor was presented. The parallel communication between control system of machine tools, the monitoring intelligent system,and several decision-making systems for identifying tool cutting state was established It can auto - matically select the sensor way ,monitoring mode and identifying method in machining process- ing so as to build a successful and effective intelligent system for on -line and real-time moni- toring cutting tool states in FMS.
文摘An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system was established. The periodically autoregressive models (PARM) based on genetic algorithms (GA) were used to predict the next day’s cold load. The improved genetic algorithms (IGA) with stochastic real number coding were used to finish the optimum energy saving scheduling of the system. The simulation results for the building of the Liangmahe Plaza show that the proposed strategy can save energy up to about 24 5%.
基金supported in part by National Natural Science Foundation of China(Grant Nos.61921003,61925101,61831002 and 61901315)in part by the Beijing Natural Science Foundation under(Grant No.JQ18016)in part by the Fundamental Research Funds for the Central Universities(Grant No.2020RC08).
文摘Reconfigurable intelligent surface(RIS)can manipulate the wireless propagation environment by smartly adjusting the amplitude/phase in a programmable panel,enjoying the improved performance.The accurate acquisition of the instantaneous channel state information(CSI)in the cascaded RIS chain makes an indispensable contribution to the performance gains.However,it is quite challenging to estimate the CSI in a time-variant scenario due to the limited signal processing capability of the passive elements embedded in a RIS pannel.In this work,a channel estimation scheme for the RIS-assisted wireless communication system is proposed,which is demonstrated to perform well in a time-variant scenario.The cascaded RIS channel is modeled as a state-space model based upon the mobility situations.In addition,to fully exploit the time correlation of channel,Kalman filter is employed by taking the prior information of channels into account.Further,the optimal reflection coefficients are derived according to the minimum mean square error(MMSE)criterion.Numerical results show that the proposed methods exhibit superior performance if compared with a conventional channel estimation scheme.
文摘A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search what they need. The system consists of four main components: interface agent, information retrieval agent, broker agent and learning agent. They collaborate to implement system functions. The agents apply learning mechanisms based on an improved ID3 algorithm.
基金supported in part by the National Natural Science Foundation of China under Grants 61971126 and 61921004ZTE CorporationState Key Laboratory of Mobile Network and Mobile Multimedia Technology.
文摘In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.
文摘Multiple objects decision is used widely in many complex fields. In this paper an idea is provided to construct a train diagram intelligent multiple objects decision support system (TDIMODSS). And the reference point method is used to solve the complicated and large scale problems of making and adjusting train schedule. This paper focuses on the principle and framework of the model base, knowledge base of train diagram. It is shown that the TDIMODSS can solve the problems and their uncertainty in making train diagram, and can combine the expert knowledge, experience and judgement of a decision maker into the system. In addition to that, a friendly working environment is also presented, which brings together the human judgement, the adaptability to environment and the computerised information.
