Core power is a key parameter of nuclear reactor.Traditionally,the proportional-integralderivative(PID)controllers are used to control the core power.Fractional-order PID(FOPID)controller represents the cutting edge i...Core power is a key parameter of nuclear reactor.Traditionally,the proportional-integralderivative(PID)controllers are used to control the core power.Fractional-order PID(FOPID)controller represents the cutting edge in core power control research.In comparing with the integer-order models,fractional-order models describe the variation of core power more accurately,thus provide a comprehensive and realistic depiction for the power and state changes of reactor core.However,current fractional-order controllers cannot adjust their parameters dynamically to response the environmental changes or demands.In this paper,we aim at the stable control and dynamic responsiveness of core power.Based on the strong selflearning ability of artificial neural network(ANN),we propose a composite controller combining the ANN and FOPID controller.The FOPID controller is firstly designed and a back propagation neural network(BPNN)is then utilized to optimize the parameters of FOPID.It is shown by simulation that the composite controller enables the real-time parameter tuning via ANN and retains the advantage of FOPID controller.展开更多
With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN ...With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN and data security by proposing a novel framework based on blockchain technology that is specifically designed for communication networks.Traditional centralized network architectures are vulnerable to Distributed Denial of Service(DDoS)attacks,particularly in roaming scenarios where there is also a risk of private data leakage,which imposes significant operational demands.To address these issues,we introduce the Blockchain-Enhanced Core Network Architecture(BECNA)and the Secure Decentralized Identity Authentication Scheme(SDIDAS).The BECNA utilizes blockchain technology to decentralize data storage,enhancing network security,stability,and reliability by mitigating Single Points of Failure(SPoF).The SDIDAS utilizes Decentralized Identity(DID)technology to secure user identity data and streamline authentication in roaming scenarios,significantly reducing the risk of data breaches during cross-network transmissions.Our framework employs Ethereum,free5GC,Wireshark,and UERANSIM tools to create a robust,tamper-evident system model.A comprehensive security analysis confirms substantial improvements in user privacy and network security.Simulation results indicate that our approach enhances communication CNs security and reliability,while also ensuring data security.展开更多
Synergistically and simultaneously enhancing strength and ductility has been a major challenge for the development and applications of titanium matrix composites.Herein,a new design methodology for Ti_(2)Cu/Ti_(6)Al4V...Synergistically and simultaneously enhancing strength and ductility has been a major challenge for the development and applications of titanium matrix composites.Herein,a new design methodology for Ti_(2)Cu/Ti_(6)Al4V composites with superior strength and ductility is reported.展开更多
The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to case...The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.展开更多
Many networks exhibit the core/periphery structure.Core/periphery structure is a type of meso-scale structure that consists of densely connected core nodes and sparsely connected peripheral nodes.Core nodes tend to be...Many networks exhibit the core/periphery structure.Core/periphery structure is a type of meso-scale structure that consists of densely connected core nodes and sparsely connected peripheral nodes.Core nodes tend to be well-connected,both among themselves and to peripheral nodes,which tend not to be well-connected to other nodes.In this brief report,we propose a new method to detect the core of a network by the centrality of each node.It is discovered that such nodes with non-negative centralities often consist in the core of the networks.The simulation is carried out on different real networks.The results are checked by the objective function.The checked results may show the effectiveness of the simulation results by the centralities of the nodes on the real networks.Furthermore,we discuss the characters of networks with the single core/periphery structure and point out the scope of the application of our method at the end of this paper.展开更多
With the rapid development of low-orbit satellite com-munication networks both domestically and internationally,space-terrestrial integrated networks will become the future development trend.For space and terrestrial ...With the rapid development of low-orbit satellite com-munication networks both domestically and internationally,space-terrestrial integrated networks will become the future development trend.For space and terrestrial networks with limi-ted resources,the utilization efficiency of the entire space-terres-trial integrated networks resources can be affected by the core network indirectly.In order to improve the response efficiency of core networks expansion construction,early warning of the core network elements capacity is necessary.Based on the inte-grated architecture of space and terrestrial network,multidimen-sional factors are considered in this paper,including the number of terminals,login users,and the rules of users’migration during holidays.Using artifical intelligence(AI)technologies,the regis-tered users of the access and mobility management function(AMF),authorization users of the unified data management(UDM),protocol data unit(PDU)sessions of session manage-ment function(SMF)are predicted in combination with the num-ber of login users,the number of terminals.Therefore,the core network elements capacity can be predicted in advance.The proposed method is proven to be effective based on the data from real network.展开更多
Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostat...Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.展开更多
The most reliable archive of atmospheric CO_(2) information comprises ice core records spanning the last 800 ka(thousand years ago).The connection between temperature and greenhouse gases,as deduced from ice core reco...The most reliable archive of atmospheric CO_(2) information comprises ice core records spanning the last 800 ka(thousand years ago).The connection between temperature and greenhouse gases,as deduced from ice core records,may help better simulate CO_(2) variations.This research aimed to explore the model methods to precisely predict the atmospheric CO_(2) concentrations and fill the CO_(2) data gaps with CH4 concentration and temperature proxies(δD andδ18O)from Antarctica ice cores,employing Artificial Neural Network(ANN)and Wavelet Transform(WT)techniques.This study was divided into three sections to examine various timescales and resolutions.First,coarse-resolution CO_(2) records from the Vostok and EPICA Dronning Maud Land cores from 70–120 ka were used.Second,the models were applied to the Dome Fuji core for 9–120 ka.Finally,a high-resolution West Antarctic Ice Sheet(WAIS)Divide ice core record,focusing on the 9–70 ka,was employed.The results showed that between 70–120 ka,the hybrid method surpasses the traditional ANN approach.The hybrid method maintained superior performance in the last phase by utilizing high-resolution WAIS record.The results indicated improved accuracy(r=0.98),reinforcing the notion that hybrid methods yield better outcomes than those relying solely on AI methods.展开更多
The proliferation of heterogeneous networks,such as the Internet of Things(IoT),unmanned aerial vehicle(UAV)networks,and edge networks,has increased the complexity of network operation and administration,driving the e...The proliferation of heterogeneous networks,such as the Internet of Things(IoT),unmanned aerial vehicle(UAV)networks,and edge networks,has increased the complexity of network operation and administration,driving the emergence of digital twin networks(DTNs)that create digital-physical network mappings.While DTNs enable performance analysis through emulation testbeds,current research focuses on network-level systems,neglecting equipment-level emulation of critical components like core switches and routers.To address this issue,we propose v Fabric(short for virtual switch),a digital twin emulator for high-capacity core switching equipment.This solution implements virtual switching and network processor(NP)chip models through specialized processes,deployable on single or distributed servers via socket communication.The v Fabric emulator can realize the accurate emulation for the core switching equipment with 720 ports and 100 Gbit/s per port on the largest scale.To our knowledge,this represents the first digital twin emulation framework specifically designed for large-capacity core switching equipment in communication networks.展开更多
BACKGROUND A psychological sense of coherence(SOC)in percutaneous coronary intervention(PCI)patients is important for disease prognosis,and there is considerable variation between their symptoms.In contrast,network an...BACKGROUND A psychological sense of coherence(SOC)in percutaneous coronary intervention(PCI)patients is important for disease prognosis,and there is considerable variation between their symptoms.In contrast,network analysis provides a new approach to gaining insight into the complex nature of symptoms and symptom clusters and identifying core symptoms.AIM To explore the psychological coherence of symptoms experienced by PCI patients,we aim to analyze differences in their associated factors and employ network analysis to characterize the symptom networks.METHODS A total of 472 patients who underwent PCI were selected for a cross-sectional study.The objective was to investigate the association between general patient demographics,medical coping styles,perceived stress status,and symptoms of psychological coherence.Data analysis was conducted using a linear regression model and a network model to visualize psychological coherence and calculate a centrality index.RESULTSPost-PCI patients exhibited low levels of psychological coherence, which correlated with factors such as education,income, age, place of residence, adherence to medical examinations, perceived stress, and medical coping style.Network analysis revealed that symptoms within the sense of psychological coherence were strongly interconnected,particularly with SOC2 and SOC8, demonstrating the strongest correlations. Among these, SOC10 emergedas the symptom with the highest intensity, centrality, and proximity, identifying it as the most central symptom.CONCLUSIONThe network model has strong explanatory power in describing the psychological consistency symptoms ofpatients after PCI, identifying the central SOC symptoms, among which SOC10 is the key to overall SOCenhancement, and there is a strong positive correlation between SOC2 and SOC8, emphasizing the need to considerthe synergistic effect of symptoms in intervention measures.展开更多
In order to identify the development characteristics of fracture network in tight conglomerate reservoir of Mahu after hydraulic fracturing,a hydraulic fracturing test site was set up in the second and third members o...In order to identify the development characteristics of fracture network in tight conglomerate reservoir of Mahu after hydraulic fracturing,a hydraulic fracturing test site was set up in the second and third members of Triassic Baikouquan Formation(T1b2 and T1b3)in Ma-131 well area,which learned from the successful experience of hydraulic fracturing test sites in North America(HFTS-1).Twelve horizontal wells and a high-angle coring well MaJ02 were drilled.The orientation,connection,propagation law and major controlling factors of hydraulic fractures were analyzed by comparing results of CT scans,imaging logs,direct observation of cores from Well MaJ02,and combined with tracer monitoring data.Results indicate that:(1)Two types of fractures have developed by hydraulic fracturing,i.e.tensile fractures and shear fractures.Tensile fractures are approximately parallel to the direction of the maximum horizontal principal stress,and propagate less than 50 m from perforation clusters.Shear fractures are distributed among tensile fractures and mainly in the strike-slip mode due to the induced stress field among tensile fractures,and some of them are in conjugated pairs.Overall,tensile fractures alternate with shear fractures,with shear fractures dominated and activated after tensile ones.(2)Tracer monitoring results indicate that communication between wells was prevalent in the early stage of production,and the static pressure in the fracture gradually decreased and the connectivity between wells reduced as production progressed.(3)Density of hydraulic fractures is mainly affected by the lithology and fracturing parameters,which is smaller in the mudstone than the conglomerate.Larger fracturing scale and smaller cluster spacing lead to a higher fracture density,which are important directions to improve the well productivity.展开更多
A new core-based shared tree algorithm, viz core-cluster combination-based shared tree （CCST） algorithm and the weighted version （i.e. w-CCST algorithm） are proposed in order to resolve the channel resources waste...A new core-based shared tree algorithm, viz core-cluster combination-based shared tree （CCST） algorithm and the weighted version （i.e. w-CCST algorithm） are proposed in order to resolve the channel resources waste problem in typical source-based multicast routing algorithms in low earth orbit （LEO） satellite IP networks. The CCST algorithm includes the dynamic approximate center （DAC） core selection method and the core-cluster combination multicast route construction scheme. Without complicated onboard computation, the DAC method is uniquely developed for highly dynamic networks of periodical and regular movement. The core-cluster combination method takes core node as the initial core-cluster, and expands it stepwise to construct an entire multicast tree at the lowest tree cost by a shortest path scheme between the newly-generated core-cluster and surplus group members, which results in great bandwidth utilization. Moreover, the w-CCST algorithm is able to strike a balance between performance of tree cost and that of end-to-end propagation delay by adjusting the weighted factor to meet strict end-to-end delay requirements of some real-time multicast services at the expense of a slight increase in tree cost. Finally, performance comparison is conducted between the proposed algorithms and typical algorithms in LEO satellite IP networks. Simulation results show that the CCST algorithm significantly decreases the average tree cost against to the others, and also the average end-to-end propagation delay ofw-CCST algorithm is lower than that of the CCST algorithm.展开更多
The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5 G era,...The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5 G era, service based architecture is introduced into mobile networks. The monolithic network elements(e.g., MME, PGW, etc.) are split into smaller network functions to provide customized services. However, the management and deployment of network functions in service based 5 G core network are still big challenges. In this paper, we propose a novel management architecture for 5 G service based core network based on NFV and SDN. Combined with SDN, NFV and edge computing, the proposed framework can provide distributed and on-demand deployment of network functions, service guaranteed network slicing, flexible orchestration of network functions and optimal workload allocation. Simulations are conducted to show that the proposed framework and algorithm are effective in terms of reducing network operating cost.展开更多
Recent developments in the aerospace industry have led to a dramatic reduction in the manufacturing and launch costs of low Earth orbit satellites.The new trend enables the paradigm shift of satelliteterrestrial integ...Recent developments in the aerospace industry have led to a dramatic reduction in the manufacturing and launch costs of low Earth orbit satellites.The new trend enables the paradigm shift of satelliteterrestrial integrated networks with global coverage.In particular,the integration of 5G communication systems and satellites has the potential to restructure nextgeneration mobile networks.By leveraging the network function virtualization and network slicing,the satellite 5G core networks will facilitate the coordination and management of network functions in satellite-terrestrial integrated networks.We are the first to deploy a 5G core network on a real-world satellite to investigate its feasibility.We conducted experiments to validate the satellite 5G core network functions.The validated procedures include registration and session setup procedures.The results show that the satellite 5G core network can function normally and generate correct signaling.展开更多
To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data....To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data.In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network,so that the accuracy of the measurement system was optimized.The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network,and the corresponding actual concentration value was used as the output value of the network,and the optimal network structure was trained.This paper discovers a preferable correlation between the predicted value and the actual value,where the former is approximately equal to the latter.The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94;similarly,correlations of0.999 51 and 1.018 8 for a glucose concentration were observed.The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.展开更多
Optical network is the infrastructure of telecommunicationnetwork. More than 95% of information istransported over optical network in China, wherecore network is the main trunk. How to increase thebit rate of the sing...Optical network is the infrastructure of telecommunicationnetwork. More than 95% of information istransported over optical network in China, wherecore network is the main trunk. How to increase thebit rate of the single wavelength channel, raise thetotal capacity of the DWDM system, extend theoptical transportation distance of electrical repeaterfree of the DWDM system and optical network intelligenceare key problems demanding high attention.The evolution trend of the optical core network isdescribed with some examples in this paper.展开更多
In this paper, an artificial neural network method that can predict the chemical composition of deposited weld metal by CO 2 Shielded Flux Cored Wire Surfacing was studied. It is found that artificial neural networ...In this paper, an artificial neural network method that can predict the chemical composition of deposited weld metal by CO 2 Shielded Flux Cored Wire Surfacing was studied. It is found that artificial neural network is a good approach on studying welding metallurgy processes that cannot be described by conventional mathematical methods. In the same time we explored a new way to study the no equilibrium welding metallurgy processes.展开更多
Secure authentication between user equipment and 5G core network is a critical issue for 5G system.However,the traditional authentication protocol 5 G-AKA and the centralized key database are at risk of several securi...Secure authentication between user equipment and 5G core network is a critical issue for 5G system.However,the traditional authentication protocol 5 G-AKA and the centralized key database are at risk of several security problems,e.g.key leakage,impersonation attack,MitM attack and single point of failure.In this paper,a blockchain based asymmetric authentication and key agreement protocol(BC-AKA)is proposed for distributed 5G core network.In particular,the key used in the authentication process is replaced from a symmetric key to an asymmetric key,and the database used to store keys in conventional 5G core network is replaced with a blockchain network.A proof of concept system for distributed 5G core network is built based on Ethereum and ECC-Secp256 k1,and the efficiency and effectiveness of the proposed scheme are verified by the experiment results.展开更多
This paper, concerning uneven development in China, empirically analyzes the core-periphery gradient of manufacturing industries across provinces （autonomous regions, municipalities）, and assesses the extent to whic...This paper, concerning uneven development in China, empirically analyzes the core-periphery gradient of manufacturing industries across provinces （autonomous regions, municipalities）, and assesses the extent to which these provinces have changed in recent years. Since China＇s reform and opening-up, the spatial structure of the economy has pre- sented a significant core-periphery pattern, the core evidently skewing towards east-coastal areas. With the deepening of market reforms and expansion of globalization, industrial loca- tion is gradually in line with the development advantages of provinces. The core provinces specialize in those industries characterized by strong forward and backward linkages, as well as a high consumption ratio, a high degree of increasing returns to scale, and labor or hu- man-capital intensity. However, it is the opposite with regard to peripheral provinces, in addi- tion, energy intensive industries are gradually concentrating in these areas. To a certain de- gree, the comparative advantage theory and new economic geography identify the underlying forces that determine the spatial distribution of manufacturing industries in China. This paper indicates that the industrialization of regions along different gradients becomes unsynchro- nized will be a long-term trend. Within a certain period, regions are bound to develop indus- trial sectors in line with their respective characteristics and development stage. A core-periphery pattern of industries also indicates that industrial development differentials across regions arise because of not only the uneven distribution of industries but also the inconsistent evolving trends of industrial structure for each province.展开更多
In this paper, the complete process of constructing 3D digital core by fullconvolutional neural network is described carefully. A large number of sandstone computedtomography (CT) images are used as training input for...In this paper, the complete process of constructing 3D digital core by fullconvolutional neural network is described carefully. A large number of sandstone computedtomography (CT) images are used as training input for a fully convolutional neural networkmodel. This model is used to reconstruct the three-dimensional (3D) digital core of Bereasandstone based on a small number of CT images. The Hamming distance together with theMinkowski functions for porosity, average volume specifi c surface area, average curvature,and connectivity of both the real core and the digital reconstruction are used to evaluate theaccuracy of the proposed method. The results show that the reconstruction achieved relativeerrors of 6.26%, 1.40%, 6.06%, and 4.91% for the four Minkowski functions and a Hammingdistance of 0.04479. This demonstrates that the proposed method can not only reconstructthe physical properties of real sandstone but can also restore the real characteristics of poredistribution in sandstone, is the ability to which is a new way to characterize the internalmicrostructure of rocks.展开更多
文摘Core power is a key parameter of nuclear reactor.Traditionally,the proportional-integralderivative(PID)controllers are used to control the core power.Fractional-order PID(FOPID)controller represents the cutting edge in core power control research.In comparing with the integer-order models,fractional-order models describe the variation of core power more accurately,thus provide a comprehensive and realistic depiction for the power and state changes of reactor core.However,current fractional-order controllers cannot adjust their parameters dynamically to response the environmental changes or demands.In this paper,we aim at the stable control and dynamic responsiveness of core power.Based on the strong selflearning ability of artificial neural network(ANN),we propose a composite controller combining the ANN and FOPID controller.The FOPID controller is firstly designed and a back propagation neural network(BPNN)is then utilized to optimize the parameters of FOPID.It is shown by simulation that the composite controller enables the real-time parameter tuning via ANN and retains the advantage of FOPID controller.
基金supported by the Beijing Natural Science Foundation(L223025,4242003)Qin Xin Talents Cultivation Program of Beijing Information Science&Technology University(QXTCP B202405)。
文摘With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN and data security by proposing a novel framework based on blockchain technology that is specifically designed for communication networks.Traditional centralized network architectures are vulnerable to Distributed Denial of Service(DDoS)attacks,particularly in roaming scenarios where there is also a risk of private data leakage,which imposes significant operational demands.To address these issues,we introduce the Blockchain-Enhanced Core Network Architecture(BECNA)and the Secure Decentralized Identity Authentication Scheme(SDIDAS).The BECNA utilizes blockchain technology to decentralize data storage,enhancing network security,stability,and reliability by mitigating Single Points of Failure(SPoF).The SDIDAS utilizes Decentralized Identity(DID)technology to secure user identity data and streamline authentication in roaming scenarios,significantly reducing the risk of data breaches during cross-network transmissions.Our framework employs Ethereum,free5GC,Wireshark,and UERANSIM tools to create a robust,tamper-evident system model.A comprehensive security analysis confirms substantial improvements in user privacy and network security.Simulation results indicate that our approach enhances communication CNs security and reliability,while also ensuring data security.
基金supported by the National Natural Science Foundation of China(NSFC,No.52271138)the Key Research and Development Projects of Shaanxi Province(Nos.2023-YBGY-433 and 2024GX-YBXM-356)+1 种基金Xi'an Talent Program Young Innovative Talents(No.XAYC 2023030)the Science and Technology Development Plan Project of Shaanxi Province(No.S2024-JC-QN-2642).
文摘Synergistically and simultaneously enhancing strength and ductility has been a major challenge for the development and applications of titanium matrix composites.Herein,a new design methodology for Ti_(2)Cu/Ti_(6)Al4V composites with superior strength and ductility is reported.
基金supported by the National Natural Science Foundation of China(No.12305344)the 2023 Anhui university research project of China(No.2023AH052179).
文摘The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.
基金Project supported by the National Natural Science Foundation of China (Gant No.11872323)。
文摘Many networks exhibit the core/periphery structure.Core/periphery structure is a type of meso-scale structure that consists of densely connected core nodes and sparsely connected peripheral nodes.Core nodes tend to be well-connected,both among themselves and to peripheral nodes,which tend not to be well-connected to other nodes.In this brief report,we propose a new method to detect the core of a network by the centrality of each node.It is discovered that such nodes with non-negative centralities often consist in the core of the networks.The simulation is carried out on different real networks.The results are checked by the objective function.The checked results may show the effectiveness of the simulation results by the centralities of the nodes on the real networks.Furthermore,we discuss the characters of networks with the single core/periphery structure and point out the scope of the application of our method at the end of this paper.
基金This work was supported by the National Key Research Plan(2021YFB2900602).
文摘With the rapid development of low-orbit satellite com-munication networks both domestically and internationally,space-terrestrial integrated networks will become the future development trend.For space and terrestrial networks with limi-ted resources,the utilization efficiency of the entire space-terres-trial integrated networks resources can be affected by the core network indirectly.In order to improve the response efficiency of core networks expansion construction,early warning of the core network elements capacity is necessary.Based on the inte-grated architecture of space and terrestrial network,multidimen-sional factors are considered in this paper,including the number of terminals,login users,and the rules of users’migration during holidays.Using artifical intelligence(AI)technologies,the regis-tered users of the access and mobility management function(AMF),authorization users of the unified data management(UDM),protocol data unit(PDU)sessions of session manage-ment function(SMF)are predicted in combination with the num-ber of login users,the number of terminals.Therefore,the core network elements capacity can be predicted in advance.The proposed method is proven to be effective based on the data from real network.
基金supported by the National Science Foundation of China(Grant No.42230606)。
文摘Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical core.The NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer time.Recent advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic relationship.In this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the NAS.The NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)model.The forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,respectively.Finally,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic tendency.Corrected by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.
基金supported by the Brain Pool Program through the National Research Foundation of Korea(NRF)and funded by the Ministry of Science and ICT[Grant numbers:2020H1D3A1A04081353,2020M1A5A1110607,2018R1A5A1024958,and RS-2023-00291696].
文摘The most reliable archive of atmospheric CO_(2) information comprises ice core records spanning the last 800 ka(thousand years ago).The connection between temperature and greenhouse gases,as deduced from ice core records,may help better simulate CO_(2) variations.This research aimed to explore the model methods to precisely predict the atmospheric CO_(2) concentrations and fill the CO_(2) data gaps with CH4 concentration and temperature proxies(δD andδ18O)from Antarctica ice cores,employing Artificial Neural Network(ANN)and Wavelet Transform(WT)techniques.This study was divided into three sections to examine various timescales and resolutions.First,coarse-resolution CO_(2) records from the Vostok and EPICA Dronning Maud Land cores from 70–120 ka were used.Second,the models were applied to the Dome Fuji core for 9–120 ka.Finally,a high-resolution West Antarctic Ice Sheet(WAIS)Divide ice core record,focusing on the 9–70 ka,was employed.The results showed that between 70–120 ka,the hybrid method surpasses the traditional ANN approach.The hybrid method maintained superior performance in the last phase by utilizing high-resolution WAIS record.The results indicated improved accuracy(r=0.98),reinforcing the notion that hybrid methods yield better outcomes than those relying solely on AI methods.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant Nos.62171085,62272428,62001087,U20A20156,and 61871097the ZTE Industry-University-Institute Cooperation Funds under Grant No.HC-CN-20220722010。
文摘The proliferation of heterogeneous networks,such as the Internet of Things(IoT),unmanned aerial vehicle(UAV)networks,and edge networks,has increased the complexity of network operation and administration,driving the emergence of digital twin networks(DTNs)that create digital-physical network mappings.While DTNs enable performance analysis through emulation testbeds,current research focuses on network-level systems,neglecting equipment-level emulation of critical components like core switches and routers.To address this issue,we propose v Fabric(short for virtual switch),a digital twin emulator for high-capacity core switching equipment.This solution implements virtual switching and network processor(NP)chip models through specialized processes,deployable on single or distributed servers via socket communication.The v Fabric emulator can realize the accurate emulation for the core switching equipment with 720 ports and 100 Gbit/s per port on the largest scale.To our knowledge,this represents the first digital twin emulation framework specifically designed for large-capacity core switching equipment in communication networks.
基金Supported by the Self-funded Research Project of Health Commission of Guangxi Zhuang Autonomous Region,No.Z-A20220509.
文摘BACKGROUND A psychological sense of coherence(SOC)in percutaneous coronary intervention(PCI)patients is important for disease prognosis,and there is considerable variation between their symptoms.In contrast,network analysis provides a new approach to gaining insight into the complex nature of symptoms and symptom clusters and identifying core symptoms.AIM To explore the psychological coherence of symptoms experienced by PCI patients,we aim to analyze differences in their associated factors and employ network analysis to characterize the symptom networks.METHODS A total of 472 patients who underwent PCI were selected for a cross-sectional study.The objective was to investigate the association between general patient demographics,medical coping styles,perceived stress status,and symptoms of psychological coherence.Data analysis was conducted using a linear regression model and a network model to visualize psychological coherence and calculate a centrality index.RESULTSPost-PCI patients exhibited low levels of psychological coherence, which correlated with factors such as education,income, age, place of residence, adherence to medical examinations, perceived stress, and medical coping style.Network analysis revealed that symptoms within the sense of psychological coherence were strongly interconnected,particularly with SOC2 and SOC8, demonstrating the strongest correlations. Among these, SOC10 emergedas the symptom with the highest intensity, centrality, and proximity, identifying it as the most central symptom.CONCLUSIONThe network model has strong explanatory power in describing the psychological consistency symptoms ofpatients after PCI, identifying the central SOC symptoms, among which SOC10 is the key to overall SOCenhancement, and there is a strong positive correlation between SOC2 and SOC8, emphasizing the need to considerthe synergistic effect of symptoms in intervention measures.
基金Supported by the National Natural Science Foundation of China(52274051)CNPC-China University of Petroleum(Beijing)Strategic Cooperative Project(ZLZX2020-01).
文摘In order to identify the development characteristics of fracture network in tight conglomerate reservoir of Mahu after hydraulic fracturing,a hydraulic fracturing test site was set up in the second and third members of Triassic Baikouquan Formation(T1b2 and T1b3)in Ma-131 well area,which learned from the successful experience of hydraulic fracturing test sites in North America(HFTS-1).Twelve horizontal wells and a high-angle coring well MaJ02 were drilled.The orientation,connection,propagation law and major controlling factors of hydraulic fractures were analyzed by comparing results of CT scans,imaging logs,direct observation of cores from Well MaJ02,and combined with tracer monitoring data.Results indicate that:(1)Two types of fractures have developed by hydraulic fracturing,i.e.tensile fractures and shear fractures.Tensile fractures are approximately parallel to the direction of the maximum horizontal principal stress,and propagate less than 50 m from perforation clusters.Shear fractures are distributed among tensile fractures and mainly in the strike-slip mode due to the induced stress field among tensile fractures,and some of them are in conjugated pairs.Overall,tensile fractures alternate with shear fractures,with shear fractures dominated and activated after tensile ones.(2)Tracer monitoring results indicate that communication between wells was prevalent in the early stage of production,and the static pressure in the fracture gradually decreased and the connectivity between wells reduced as production progressed.(3)Density of hydraulic fractures is mainly affected by the lithology and fracturing parameters,which is smaller in the mudstone than the conglomerate.Larger fracturing scale and smaller cluster spacing lead to a higher fracture density,which are important directions to improve the well productivity.
基金National Natural Science Foundation of China （60532030, 10577005, 60625102） Innovation Foundation of Aerospace Science and Technology of China
文摘A new core-based shared tree algorithm, viz core-cluster combination-based shared tree （CCST） algorithm and the weighted version （i.e. w-CCST algorithm） are proposed in order to resolve the channel resources waste problem in typical source-based multicast routing algorithms in low earth orbit （LEO） satellite IP networks. The CCST algorithm includes the dynamic approximate center （DAC） core selection method and the core-cluster combination multicast route construction scheme. Without complicated onboard computation, the DAC method is uniquely developed for highly dynamic networks of periodical and regular movement. The core-cluster combination method takes core node as the initial core-cluster, and expands it stepwise to construct an entire multicast tree at the lowest tree cost by a shortest path scheme between the newly-generated core-cluster and surplus group members, which results in great bandwidth utilization. Moreover, the w-CCST algorithm is able to strike a balance between performance of tree cost and that of end-to-end propagation delay by adjusting the weighted factor to meet strict end-to-end delay requirements of some real-time multicast services at the expense of a slight increase in tree cost. Finally, performance comparison is conducted between the proposed algorithms and typical algorithms in LEO satellite IP networks. Simulation results show that the CCST algorithm significantly decreases the average tree cost against to the others, and also the average end-to-end propagation delay ofw-CCST algorithm is lower than that of the CCST algorithm.
基金supported by China Ministry of Education-CMCC Research Fund Project No.MCM20160104National Science and Technology Major Project No.No.2018ZX03001016+1 种基金Beijing Municipal Science and technology Commission Research Fund Project No.Z171100005217001Fundamental Research Funds for Central Universities NO.2018RC06
文摘The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5 G era, service based architecture is introduced into mobile networks. The monolithic network elements(e.g., MME, PGW, etc.) are split into smaller network functions to provide customized services. However, the management and deployment of network functions in service based 5 G core network are still big challenges. In this paper, we propose a novel management architecture for 5 G service based core network based on NFV and SDN. Combined with SDN, NFV and edge computing, the proposed framework can provide distributed and on-demand deployment of network functions, service guaranteed network slicing, flexible orchestration of network functions and optimal workload allocation. Simulations are conducted to show that the proposed framework and algorithm are effective in terms of reducing network operating cost.
基金supported by the National Key R&D Program of China(2020YFB1805500)National Natural Science Foundation of China(61922017,62032003 and 61921003)。
文摘Recent developments in the aerospace industry have led to a dramatic reduction in the manufacturing and launch costs of low Earth orbit satellites.The new trend enables the paradigm shift of satelliteterrestrial integrated networks with global coverage.In particular,the integration of 5G communication systems and satellites has the potential to restructure nextgeneration mobile networks.By leveraging the network function virtualization and network slicing,the satellite 5G core networks will facilitate the coordination and management of network functions in satellite-terrestrial integrated networks.We are the first to deploy a 5G core network on a real-world satellite to investigate its feasibility.We conducted experiments to validate the satellite 5G core network functions.The validated procedures include registration and session setup procedures.The results show that the satellite 5G core network can function normally and generate correct signaling.
基金Supported by the National Natural Science Foundation of China(61307122)the University Science and Technology Innovation Team Support Project of Henan Province(13IRTTHN016)the Innovative and Training Project of Post Graduate Funding from the Henan Normal University(201310476046)
文摘To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data.In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network,so that the accuracy of the measurement system was optimized.The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network,and the corresponding actual concentration value was used as the output value of the network,and the optimal network structure was trained.This paper discovers a preferable correlation between the predicted value and the actual value,where the former is approximately equal to the latter.The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94;similarly,correlations of0.999 51 and 1.018 8 for a glucose concentration were observed.The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.
文摘Optical network is the infrastructure of telecommunicationnetwork. More than 95% of information istransported over optical network in China, wherecore network is the main trunk. How to increase thebit rate of the single wavelength channel, raise thetotal capacity of the DWDM system, extend theoptical transportation distance of electrical repeaterfree of the DWDM system and optical network intelligenceare key problems demanding high attention.The evolution trend of the optical core network isdescribed with some examples in this paper.
文摘In this paper, an artificial neural network method that can predict the chemical composition of deposited weld metal by CO 2 Shielded Flux Cored Wire Surfacing was studied. It is found that artificial neural network is a good approach on studying welding metallurgy processes that cannot be described by conventional mathematical methods. In the same time we explored a new way to study the no equilibrium welding metallurgy processes.
基金supported by National Key Research and Development Program of China under Grant 2021YFE0205300Tianjin Natural Science Foundation(19JCYBJC15700)。
文摘Secure authentication between user equipment and 5G core network is a critical issue for 5G system.However,the traditional authentication protocol 5 G-AKA and the centralized key database are at risk of several security problems,e.g.key leakage,impersonation attack,MitM attack and single point of failure.In this paper,a blockchain based asymmetric authentication and key agreement protocol(BC-AKA)is proposed for distributed 5G core network.In particular,the key used in the authentication process is replaced from a symmetric key to an asymmetric key,and the database used to store keys in conventional 5G core network is replaced with a blockchain network.A proof of concept system for distributed 5G core network is built based on Ethereum and ECC-Secp256 k1,and the efficiency and effectiveness of the proposed scheme are verified by the experiment results.
基金National Science and Technology Infrastructure Program of China,No.2007FY110300
文摘This paper, concerning uneven development in China, empirically analyzes the core-periphery gradient of manufacturing industries across provinces （autonomous regions, municipalities）, and assesses the extent to which these provinces have changed in recent years. Since China＇s reform and opening-up, the spatial structure of the economy has pre- sented a significant core-periphery pattern, the core evidently skewing towards east-coastal areas. With the deepening of market reforms and expansion of globalization, industrial loca- tion is gradually in line with the development advantages of provinces. The core provinces specialize in those industries characterized by strong forward and backward linkages, as well as a high consumption ratio, a high degree of increasing returns to scale, and labor or hu- man-capital intensity. However, it is the opposite with regard to peripheral provinces, in addi- tion, energy intensive industries are gradually concentrating in these areas. To a certain de- gree, the comparative advantage theory and new economic geography identify the underlying forces that determine the spatial distribution of manufacturing industries in China. This paper indicates that the industrialization of regions along different gradients becomes unsynchro- nized will be a long-term trend. Within a certain period, regions are bound to develop indus- trial sectors in line with their respective characteristics and development stage. A core-periphery pattern of industries also indicates that industrial development differentials across regions arise because of not only the uneven distribution of industries but also the inconsistent evolving trends of industrial structure for each province.
基金the National Natural Science Foundation of China(No.41274129)Chuan Qing Drilling Engineering Company's Scientific Research Project:Seismic detection technology and application of complex carbonate reservoir in Sulige Majiagou Formation and the 2018 Central Supporting Local Co-construction Fund(No.80000-18Z0140504)the Construction and Development of Universities in 2019-Joint Support for Geophysics(Double First-Class center,80000-19Z0204)。
文摘In this paper, the complete process of constructing 3D digital core by fullconvolutional neural network is described carefully. A large number of sandstone computedtomography (CT) images are used as training input for a fully convolutional neural networkmodel. This model is used to reconstruct the three-dimensional (3D) digital core of Bereasandstone based on a small number of CT images. The Hamming distance together with theMinkowski functions for porosity, average volume specifi c surface area, average curvature,and connectivity of both the real core and the digital reconstruction are used to evaluate theaccuracy of the proposed method. The results show that the reconstruction achieved relativeerrors of 6.26%, 1.40%, 6.06%, and 4.91% for the four Minkowski functions and a Hammingdistance of 0.04479. This demonstrates that the proposed method can not only reconstructthe physical properties of real sandstone but can also restore the real characteristics of poredistribution in sandstone, is the ability to which is a new way to characterize the internalmicrostructure of rocks.
