Carbon can change the phase components of low-density steels and influence the mechanical properties.In this study,a new method to control the carbon content and avoid the formation ofδ-ferrite by decarburization tre...Carbon can change the phase components of low-density steels and influence the mechanical properties.In this study,a new method to control the carbon content and avoid the formation ofδ-ferrite by decarburization treatment was proposed.The microstructural changes and mechanical characteristics with carbon content induced by decarburization were systematically examined.Crussard-Jaoul(C-J)analysis was employed to examine the work hardening characteristics during the tensile test.During decarburization by heat treatments,the carbon content within the austenite phase decreased,while Mn and Al were almost unchanged;this made the steel with full austenite transform into the austenite and ferrite dual phase.Meanwhile,(Ti,V)C carbides existed in both matrix phase and the mole fraction almost the same.In addition,the formation of other carbides restrained.Carbon loss induced a decrease in strength due to the weakening of the carbon solid solution.For the steel with the single austinite,the deformation mode of austenite was the dislocation planar glide,resulting in the formation of microbands.For the dual-phase steel,the deformation occurred by the dislocation planar glide of austenite first,with the increase in strain,the cross slip of ferrite took place,forming dislocation cells in ferrite.At the late stage of deformation,the work hardening of austinite increased rapidly,while that of ferrite increased slightly.展开更多
In order to achieve the large-scale application of manufactured sand in railway high-strength concrete structure,a series of high-strength manufactured sand concrete(HMC)are prepared by taking the manufactured sand li...In order to achieve the large-scale application of manufactured sand in railway high-strength concrete structure,a series of high-strength manufactured sand concrete(HMC)are prepared by taking the manufactured sand lithology(tuff,limestone,basalt,granite),stone powder content(0,5%,10%,15%)and concrete strength grade(C60,C80,C100)as variables.The evolution of mechanical properties of HMC and the correlation between cubic compressive strength and other mechanical properties are studied.Compared to river sand,manufactured sand enhances the cubic compressive strength,axial compressive strength and elastic modulus of concrete,while its potential microcracks weaken the flexural strength and splitting tensile strength of concrete.Stone powder content displays both positive and negative effects on mechanical properties of HMC,and the stone powder content is suggested to be less than 10%.The empirical formulas between cubic compressive strength and other mechanical properties are proposed.展开更多
This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain an...This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical content.The participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security weaknesses.This multi faceted exploration led to an indepth evaluation of the model’s performance and security.Notably,the correlation between accuracy,detection rate,and error rate was scrutinized.This analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance variability.The study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical applications.Applying blockchain to generative AI-created medical content addresses key personal information protection issues.By utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical images.This approach not only enhances security but also enables transparent and tamperproof record-keeping.Additionally,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient privacy.In conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient privacy.The proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content management.Further research and advancements in this area will undoubtedly contribute to the development of robust and privacy-preserving healthcare systems,and visual diagnostic systems.展开更多
The iron content is one of the most critical parameters affecting the microstructure and mechanical properties of recycled aluminum alloy.This study aimed to compare the microstructure and tensile properties of alloys...The iron content is one of the most critical parameters affecting the microstructure and mechanical properties of recycled aluminum alloy.This study aimed to compare the microstructure and tensile properties of alloys with varying iron content to ascertain the optimal iron content for formulating a recycled Al-Si-Mg aluminum alloy.Additionally,the effects of aging temperature and aging time on the microstructure and mechanical properties of recycled aluminum alloy were investigated.With increasing aging temperature and time,both tensile strength and yield strength are improved,while elongation is decreased.Specifically,when subject to a heat treatment consisting of a solution treatment at 535℃for 5 h followed by an aging treatment at 170℃for5.5 h,the newly designed recycled aluminum alloy achieves a tensile strength of 291 MPa and a yield strength of 238 MPa.These findings hold significant implications for the further development and broader application of recycled aluminum alloys.展开更多
Understanding water dynamics under the effect of climatic conditions is important to improve water sustainability over the medium-and long-term.Clay content can affect soil hydrothermal properties,and hence modify wat...Understanding water dynamics under the effect of climatic conditions is important to improve water sustainability over the medium-and long-term.Clay content can affect soil hydrothermal properties,and hence modify water and heat exchange between soil and atmosphere,e.g.evapotranspiration and infiltration.This work aims to develop a numerical approach to explore the influence of clay content on soil hydrothermal response to the timely climatic conditions in the Lake Chad region,Sahel Region of west-central Africa.The meteorological information at the studied points,i.e.points A and B with a clay content of 8.3%and 25%,during the year 2008 is collected from ERA5-Land hourly data.The numerical results allow for understanding the effect of clay content on the hydrothermal response of the surface soil layer.Specifically,the soil surface temperature under point A is lower than that under point B during the dry season due to the dominant effect of heat conduction.However,the converse tendency is observed during the wet season because of the combined effect of heat conduction and latent heat.The variations of soil volumetric water content are closely related to the timely interaction between the soil and atmosphere,in addition to the hydrothermal properties of soil.Moreover,the outcomes of this work improve the understanding of the heat and water dynamics under the effect of climatic conditions and clay content,and provide further insights into the potential water protection in arid and semi-arid regions in the future.展开更多
In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits...In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits.Consumers now frequently rely on external sources to make well-informed purchasing decisions,leading to the emergence of live shopping as a prominent avenue for gathering product information and completing transactions.E-commerce live streaming has experienced rapid growth,leveraging its ability to generate traffic and capture consumer attention.The integration of content and live streaming not only meets users’psychological needs but also facilitates seamless communication between buyers and sellers.From the perspective of content marketing typologies,this paper examines content marketing across three key dimensions:informational content,entertainment content,and emotional content.It further explores the impact of content marketing on consumers’purchase intentions within the context of e-commerce live streaming.展开更多
This work focuses on the influence of Al content on the precipitation of nanoprecipitates,growth of prior austenite grains(PAGs),and impact toughness in simulated coarse-grained heat-affected zones (CGHAZs) of two exp...This work focuses on the influence of Al content on the precipitation of nanoprecipitates,growth of prior austenite grains(PAGs),and impact toughness in simulated coarse-grained heat-affected zones (CGHAZs) of two experimental shipbuilding steels after being subjected to high-heat input welding at 400 kJ·cm^(-1).The base metals (BMs) of both steels contained three types of precipitates Type Ⅰ:cubic (Ti,Nb)(C,N),Type Ⅱ:precipitate with cubic (Ti,Nb)(C,N) core and Nb-rich cap,and Type Ⅲ:ellipsoidal Nb-rich precipitate.In the BM of 60Al and 160Al steels,the number densities of the precipitates were 11.37×10^(5) and 13.88×10^(5) mm^(-2),respectively The 60Al and 160Al steel contained 38.12% and 6.39% Type Ⅲ precipitates,respectively.The difference in the content of Type Ⅲ precipitates in the 60Al steel reduced the pinning effect at the elevated temperature of the CGHAZ,which facilitated the growth of PAGs The average PAG sizes in the CGHAZ of the 60Al and 160Al steels were 189.73 and 174.7μm,respectively.In the 60Al steel,the low lattice mismatch among Cu_(2)S,TiN,and γ-Al_(2)O_(3)facilitated the precipitation of Cu_(2)S and TiN onto γ-Al_(2)O_(3)during welding,which decreased the number density of independently precipitated (Ti,Nb)(C,N) particles but increased that of γ-Al_(2)O_(3)–Ti N–Cu_(2)S particles.Thus abnormally large PAGs formed in the CGHAZ of the 60Al steel,and they reached a maximum size of 1 mm.These PAGs greatly reduced the microstructural homogeneity and consequently decreased the impact toughness from 134 (0.016wt%Al) to 54 J (0.006wt%Al)at-40℃.展开更多
As an emerging form of media,integrated media not only enriches the expression and dissemination of information,but integrates various forms,both online and offline,to enable resource flow and cross-platform communica...As an emerging form of media,integrated media not only enriches the expression and dissemination of information,but integrates various forms,both online and offline,to enable resource flow and cross-platform communication.With the development and application of information technology and 5G technology,the information needs of the broad audience have undergone a shift from a single media format to more diversified and personalized integrated media content.The rapid development of Artificial Intelligence(AI)technology has provided strong support for the generation and innovation of integrated media content.Through automation,multimodal content generation,immersive experience,and other ways,the application of Artificial Intelligence technology can not only improve the efficiency of content creation and enrich creative expression forms,but also provide users with more diversified and personalized information.展开更多
The Fe_(1−x)Ni_(x)VO_(4)(x=0,0.05,0.10,and 0.20)nanoparticles in this work were successfully synthesized via a co-precipitation method.The structural,magnetic and electrochemical properties of the prepared Fe_(1−x)Ni_...The Fe_(1−x)Ni_(x)VO_(4)(x=0,0.05,0.10,and 0.20)nanoparticles in this work were successfully synthesized via a co-precipitation method.The structural,magnetic and electrochemical properties of the prepared Fe_(1−x)Ni_(x)VO_(4) nanoparticles were studied as a function of Ni content.The experimental results show that the prepared Ni-doped FeVO_(4) samples have a triclinic structure.Scanning electron microscopy(SEM)images reveal a decrease in average nanoparticle size with increasing Ni content,leading to an enhancement in both specific surface area and magnetization values.X-ray absorption near edge structure(XANES)analysis confirms the substitution of Ni^(2+)ions into Fe^(3+)sites.The magnetic investigation reveals that Ni-doped FeVO_(4) exhibits weak ferromagnetic behavior at room temperature,in contrast to the antiferromagnetic behavior observed in the undoped FeVO_(4).Electrochemical studies demonstrate that the Fe_(0.95)Ni_(0.05)VO_(4) electrode achieves the highest specific capacitance of 334.05 F·g^(−1) at a current density of 1 A·g^(−1),which is attributed to its smallest average pore diameter.In addition,the enhanced specific surface of the Fe_(0.8)Ni_(0.2)VO_(4) electrode is responsible for its outstanding cyclic stability.Overall,our results suggest that the magnetic and electrochemical properties of FeVO_(4) nanoparticles could be effectively tuned by varying Ni doping contents.展开更多
Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes...Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.展开更多
Content delivery networks(CDNs)lead to fast content distribution through content caching at specific CDN servers near end users.However,existing CDNs based on infrastructure cannot be employed in special cases,such as...Content delivery networks(CDNs)lead to fast content distribution through content caching at specific CDN servers near end users.However,existing CDNs based on infrastructure cannot be employed in special cases,such as military operations.Thus,a temporary CDN without an existing infrastructure is required.To achieve this goal,we introduce a new CDN for drone-aided ad hoc networks,whereby multiple drones form ad hoc networks and quickly store specific content according to new caching algorithms.Unlike the typical CDN server,the content-caching algorithm in the proposed architecture considers the limited storage capacity of the drone.We present three content distribution algorithms that consider the constraints and mobility of drones.The main contribution of content caching for drone-aided ad hoc networks is to keep partial segments rather than whole content as well as move the drone near to area with a high volume of requests.The proposed scheme is evaluated to demonstrate its feasibility in terms of content acquisition time and utilization in several practical scenarios through simulations.Consequently,acquisition time in CDN to support drone movement is improved by approximately 50%and 40%rather than one in the proposed naive greedy approach as a function of content request interval and size,respectively.展开更多
This study aimed to examine the surface and content validity of the Mentoring Function Scale for Novice Nurses, used to assess the mentoring of entry-level nurses, and to refine the scale items. In Study 1, six nurse ...This study aimed to examine the surface and content validity of the Mentoring Function Scale for Novice Nurses, used to assess the mentoring of entry-level nurses, and to refine the scale items. In Study 1, six nurse education researchers, selected using convenience sampling, with five or more years of nursing experience and experience teaching novice nurses, were invited to an expert meeting in July 2015. A group interview was conducted that lasted approximately 120 minutes. Study 2 examined the content validity index. Between September and November 2015, we distributed a self-administered questionnaire survey to 11 participants selected by convenience sampling. The participants included five nurse education researchers with a minimum of five years of nursing experience and experience teaching novice nurses, as well as six clinical nurses with a master’s degree or higher. Finally, 81 questionnaire items were retained from the initial 125 items. The 81-item Mentoring Function Scale for Novice Nurses had higher content validity than the original scale. To further increase the scale’s applicability, future studies should assess its reliability, construct validity, and criterion-related validity.展开更多
[Objective]The aim of this study was to set up a high performance liquid chromatography for rapid determination of isoflavones from soybean and analyze the correlation between isofalvone content and protein or fat con...[Objective]The aim of this study was to set up a high performance liquid chromatography for rapid determination of isoflavones from soybean and analyze the correlation between isofalvone content and protein or fat content. [Method]The isoflavones were firstly extracted by 80% methanol and then hydrolyzed at 100 ℃. The chromatographic separation adopted a reversed-phase C18 analytical column with binary high-pressure gradient elution,while its analysis time was 25 min and column temperature was 40 ℃. The diode array detector was used for monitoring with wavelength of 260 nm. The correlation between isofalvone content and protein or fat content was analyzed by data processing system Origin 6.0. [Result]The high performance liquid chromatograph for determination of isoflavones from soybean was verified to be accurate and reliable by methodology. The isoflavones of 85 soybean lines cultivated in Jilin Province were determined,and the results primarily showed the characters and ranges of isoflavones from soybean lines cultivated in Jilin Province,while the isoflavone content of soybeans ranged from 2.29 to 4.89 mg/g,and the average content was 3.36 mg/g. The isoflavone content of 5 soybean lines exceeded 4 mg/g,while there was a remarkably negative correlation between isoflavone content and protein content,and there was no significant positive correlation between isoflavone content and fat content. [Conclusion]The isoflavone content of soybean lines cultivated in Jilin Province is higher,so it is feasible for breeding the soybean lines with high isoflavone content and fat contetnt.展开更多
Uniaxial compression tests and cyclic loading acoustic emission tests were conducted on 20%,40%,60%,80%,dry and saturated muddy sandstone by using a creep impact loading system to investigate the mechanical properties...Uniaxial compression tests and cyclic loading acoustic emission tests were conducted on 20%,40%,60%,80%,dry and saturated muddy sandstone by using a creep impact loading system to investigate the mechanical properties and acoustic emission characteristics of soft rocks with different water contents under dynamic disturbance.The mechanical properties and acoustic emission characteristics of muddy sandstones at different water contents were analysed.Results of experimental studies show that water is a key factor in the mechanical properties of rocks,softening them,increasing their porosity,reducing their brittleness and increasing their plasticity.Under uniaxial compression,the macroscopic damage characteristics of the muddy sandstone change from mono-bevel shear damage and‘X’type conjugate bevel shear damage to a roadway bottom-drum type damage as the water content increases.Dynamic perturbation has a strengthening effect on the mechanical properties of samples with 60%and less water content,and a weakening effect on samples with 80%and more water content,but the weakening effect is not obvious.Macroscopic damage characteristics of dry samples remain unchanged,water samples from shear damage and tensile–shear composite damage gradually transformed into cleavage damage,until saturation transformation monoclinic shear damage.The evolution of acoustic emission energy and event number is mainly divided into four stages:loading stage(Ⅰ),dynamic loading stage(Ⅱ),yield failure stage(Ⅲ),and post-peak stage(Ⅳ),the acoustic emission characteristics of the stages were different for different water contents.The characteristic value of acoustic emission key point frequency gradually decreases,and the damage degree of the specimen increases,corresponding to low water content—high main frequency—low damage and high water content—low main frequency—high damage.展开更多
Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can a...Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.展开更多
[Objectives]This study was conducted to optimize the extraction process of total flavonoids from Penthorum chinense Pursh and compare their contents from different parts.[Methods]Single factor and orthogonal experimen...[Objectives]This study was conducted to optimize the extraction process of total flavonoids from Penthorum chinense Pursh and compare their contents from different parts.[Methods]Single factor and orthogonal experiments were designed to optimize the extraction process of total flavonoids from P.chinense Pursh with the volume fraction of ethanol,the ratio of material to liquid,heating reflux extraction time and extraction times as factors,and the content of total flavonoids as the index.A verification test was carried out.The optimized extraction process was adopted to compare the contents of total flavonoids from different parts of P.chinense Pursh.[Results]The best extraction process was extracting the powder of P.chinense Pursh for 2.0 h with 20 times of 55%ethanol by reflux twice.Under this condition,the contents of total flavonoids were 3.63%,8.90%,11.28%,and 4.36%from stems,leaves,flowers and whole grass of P.chinense Pursh,respectively.[Conclusions]The process is reasonable,feasible and stable,and can effectively extract total flavonoids from P.chinense Pursh.The contents of total flavonoids from different parts of P.chinense Pursh were quite different,and the value was higher in the leaves and flowers,so the proportions of leaves and flowers should be paid attention to in the industrial processing of P.chinense Pursh.展开更多
In-network caching and Interest packets aggregation are two important features of Content-Centric Networking(CCN).CCN routers can directly respond to the Interest request by Content Store(CS)and aggregate the same Int...In-network caching and Interest packets aggregation are two important features of Content-Centric Networking(CCN).CCN routers can directly respond to the Interest request by Content Store(CS)and aggregate the same Interest packets by Pending Interest Table(PIT).In this way,most popular content requests will not reach the origin content server.Thus,content providers will be unaware of the actual usages of their contents in network.This new network paradigm presents content providers with unprecedented challenge.It will bring a great impact on existing mature business model of content providers,such as advertising revenue model based on hits amount.To leverage the advantages of CCN and the realistic business needs of content providers,we explore the hits-based content provisioning mechanism in CCN.The proposed approaches can avoid the unprecedented impact on content providers' existing business model and promote content providers to embrace the real deployment of CCN network.展开更多
The longitudinal dependence of the behavior of ionospheric parameters has been the subject of a number of works where significant variations are discovered.This also applies to the prediction of the ionospheric total ...The longitudinal dependence of the behavior of ionospheric parameters has been the subject of a number of works where significant variations are discovered.This also applies to the prediction of the ionospheric total electron content(TEC),which neural network methods have recently been widely used.However,the results are mainly presented for a limited set of meridians.This paper examines the longitudinal dependence of the TEC forecast accuracy in the equatorial zone.In this case,the methods are used that provided the best accuracy on three meridians:European(30°E),Southeastern(110°E)and American(75°W).Results for the stations considered are analyzed as a function of longitude using the Jet Propulsion Laboratory Global Ionosphere Map(JPL GIM)for 2015.These results are for 2 h ahead and 24 h ahead forecast.It was found that in this case,based on the metric values,three groups of architectures can be distinguished.The first group included long short-term memory(LSTM),gated recurrent unit(GRU),and temporal convolutional networks(TCN)models as a part of unidirectional deep learning models;the second group is based on the recurrent models from the first group,which were supplemented with a bidirectional algorithm,increasing the TEC forecasting accuracy by 2-3 times.The third group,which includes the bidirectional TCN architecture(BiTCN),provided the highest accuracy.For this architecture,according to data obtained for 9 equatorial stations,practical independence of the TEC prediction accuracy from longitude was observed under the following metrics(Mean Absolute Error MAE,Root Mean Square Error RMSE,Mean Absolute Percentage Error MAPE):MAE(2 h)is 0.2 TECU approximately;MAE(24 h)is 0.4 TECU approximately;RMSE(2 h)is less than 0.5 TECU except Niue station(RMSE(2 h)is 1 TECU approximately);RMSE(24 h)is in the range of 1.0-1.7 TECU;MAPE(2 h)<1%except Darwin station,MAPE(24 h)<2%.This result was confirmed by data from additional 5 stations that formed latitudinal chains in the equatorial part of the three meridians.The complete correspondence of the observational and predicted TEC values is illustrated using several stations for disturbed conditions on December 19-22,2015,which included the strongest magnetic storm in the second half of the year(min Dst=-155 nT).展开更多
The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.Howeve...The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.However,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content delivery.This challenge can be eased by sinking some critical content from cloud to edge.In this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new challenges.This work focuses on establishing a highly efficient content delivery framework in the IoE environment.In particular,the IoE environment is re-constructed as an end-edge-cloud collaborative system,in which the concept of digital twin is applied to promote the collaboration.Based on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)model.Then,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)technology.Finally,a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead.The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.U2141207,52171111,and 52001083)the Youth Talent Project of China National Nuclear Corporation(No.CNNC2021Y-TEPHEU01)+3 种基金the China Postdoctoral Science Foundation(No.2020M681077)the Natural Science Foundation of Heilongjiang,China(No.LH2019E030)the Heilongjiang Postdoctoral Science Foundation,China(No.LBH-Z19125)he Heilongjiang Touyan Innovation Team Program,China,and the Natural Science Foundation of Heilongjiang(No.LH2020E060)。
文摘Carbon can change the phase components of low-density steels and influence the mechanical properties.In this study,a new method to control the carbon content and avoid the formation ofδ-ferrite by decarburization treatment was proposed.The microstructural changes and mechanical characteristics with carbon content induced by decarburization were systematically examined.Crussard-Jaoul(C-J)analysis was employed to examine the work hardening characteristics during the tensile test.During decarburization by heat treatments,the carbon content within the austenite phase decreased,while Mn and Al were almost unchanged;this made the steel with full austenite transform into the austenite and ferrite dual phase.Meanwhile,(Ti,V)C carbides existed in both matrix phase and the mole fraction almost the same.In addition,the formation of other carbides restrained.Carbon loss induced a decrease in strength due to the weakening of the carbon solid solution.For the steel with the single austinite,the deformation mode of austenite was the dislocation planar glide,resulting in the formation of microbands.For the dual-phase steel,the deformation occurred by the dislocation planar glide of austenite first,with the increase in strain,the cross slip of ferrite took place,forming dislocation cells in ferrite.At the late stage of deformation,the work hardening of austinite increased rapidly,while that of ferrite increased slightly.
基金Funded by the National Natural Science Foundation of China(Nos.U1934206,52108260)China Academy of Railway Sciences Fund(No.2021YJ078)+1 种基金Railway Engineering Construction Standard Project(No.2023-BZWW-006)New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘In order to achieve the large-scale application of manufactured sand in railway high-strength concrete structure,a series of high-strength manufactured sand concrete(HMC)are prepared by taking the manufactured sand lithology(tuff,limestone,basalt,granite),stone powder content(0,5%,10%,15%)and concrete strength grade(C60,C80,C100)as variables.The evolution of mechanical properties of HMC and the correlation between cubic compressive strength and other mechanical properties are studied.Compared to river sand,manufactured sand enhances the cubic compressive strength,axial compressive strength and elastic modulus of concrete,while its potential microcracks weaken the flexural strength and splitting tensile strength of concrete.Stone powder content displays both positive and negative effects on mechanical properties of HMC,and the stone powder content is suggested to be less than 10%.The empirical formulas between cubic compressive strength and other mechanical properties are proposed.
文摘This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical content.The participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security weaknesses.This multi faceted exploration led to an indepth evaluation of the model’s performance and security.Notably,the correlation between accuracy,detection rate,and error rate was scrutinized.This analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance variability.The study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical applications.Applying blockchain to generative AI-created medical content addresses key personal information protection issues.By utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical images.This approach not only enhances security but also enables transparent and tamperproof record-keeping.Additionally,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient privacy.In conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient privacy.The proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content management.Further research and advancements in this area will undoubtedly contribute to the development of robust and privacy-preserving healthcare systems,and visual diagnostic systems.
基金support from funded project:Key Industrial R&D Projects of Chongqing Technology Innovation and Application Demonstration (cstc2020jscx-dxwtBX0023)。
文摘The iron content is one of the most critical parameters affecting the microstructure and mechanical properties of recycled aluminum alloy.This study aimed to compare the microstructure and tensile properties of alloys with varying iron content to ascertain the optimal iron content for formulating a recycled Al-Si-Mg aluminum alloy.Additionally,the effects of aging temperature and aging time on the microstructure and mechanical properties of recycled aluminum alloy were investigated.With increasing aging temperature and time,both tensile strength and yield strength are improved,while elongation is decreased.Specifically,when subject to a heat treatment consisting of a solution treatment at 535℃for 5 h followed by an aging treatment at 170℃for5.5 h,the newly designed recycled aluminum alloy achieves a tensile strength of 291 MPa and a yield strength of 238 MPa.These findings hold significant implications for the further development and broader application of recycled aluminum alloys.
基金the National Natural Science Foundation of China(Grant No.42207171).
文摘Understanding water dynamics under the effect of climatic conditions is important to improve water sustainability over the medium-and long-term.Clay content can affect soil hydrothermal properties,and hence modify water and heat exchange between soil and atmosphere,e.g.evapotranspiration and infiltration.This work aims to develop a numerical approach to explore the influence of clay content on soil hydrothermal response to the timely climatic conditions in the Lake Chad region,Sahel Region of west-central Africa.The meteorological information at the studied points,i.e.points A and B with a clay content of 8.3%and 25%,during the year 2008 is collected from ERA5-Land hourly data.The numerical results allow for understanding the effect of clay content on the hydrothermal response of the surface soil layer.Specifically,the soil surface temperature under point A is lower than that under point B during the dry season due to the dominant effect of heat conduction.However,the converse tendency is observed during the wet season because of the combined effect of heat conduction and latent heat.The variations of soil volumetric water content are closely related to the timely interaction between the soil and atmosphere,in addition to the hydrothermal properties of soil.Moreover,the outcomes of this work improve the understanding of the heat and water dynamics under the effect of climatic conditions and clay content,and provide further insights into the potential water protection in arid and semi-arid regions in the future.
文摘In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits.Consumers now frequently rely on external sources to make well-informed purchasing decisions,leading to the emergence of live shopping as a prominent avenue for gathering product information and completing transactions.E-commerce live streaming has experienced rapid growth,leveraging its ability to generate traffic and capture consumer attention.The integration of content and live streaming not only meets users’psychological needs but also facilitates seamless communication between buyers and sellers.From the perspective of content marketing typologies,this paper examines content marketing across three key dimensions:informational content,entertainment content,and emotional content.It further explores the impact of content marketing on consumers’purchase intentions within the context of e-commerce live streaming.
基金support from the National Natural Science Foundation of China (No. U1960202)the Opening Foundation from Shanghai Engineering Research Center of Hot Manufacturing, China (No. 18DZ2253400)。
文摘This work focuses on the influence of Al content on the precipitation of nanoprecipitates,growth of prior austenite grains(PAGs),and impact toughness in simulated coarse-grained heat-affected zones (CGHAZs) of two experimental shipbuilding steels after being subjected to high-heat input welding at 400 kJ·cm^(-1).The base metals (BMs) of both steels contained three types of precipitates Type Ⅰ:cubic (Ti,Nb)(C,N),Type Ⅱ:precipitate with cubic (Ti,Nb)(C,N) core and Nb-rich cap,and Type Ⅲ:ellipsoidal Nb-rich precipitate.In the BM of 60Al and 160Al steels,the number densities of the precipitates were 11.37×10^(5) and 13.88×10^(5) mm^(-2),respectively The 60Al and 160Al steel contained 38.12% and 6.39% Type Ⅲ precipitates,respectively.The difference in the content of Type Ⅲ precipitates in the 60Al steel reduced the pinning effect at the elevated temperature of the CGHAZ,which facilitated the growth of PAGs The average PAG sizes in the CGHAZ of the 60Al and 160Al steels were 189.73 and 174.7μm,respectively.In the 60Al steel,the low lattice mismatch among Cu_(2)S,TiN,and γ-Al_(2)O_(3)facilitated the precipitation of Cu_(2)S and TiN onto γ-Al_(2)O_(3)during welding,which decreased the number density of independently precipitated (Ti,Nb)(C,N) particles but increased that of γ-Al_(2)O_(3)–Ti N–Cu_(2)S particles.Thus abnormally large PAGs formed in the CGHAZ of the 60Al steel,and they reached a maximum size of 1 mm.These PAGs greatly reduced the microstructural homogeneity and consequently decreased the impact toughness from 134 (0.016wt%Al) to 54 J (0.006wt%Al)at-40℃.
文摘As an emerging form of media,integrated media not only enriches the expression and dissemination of information,but integrates various forms,both online and offline,to enable resource flow and cross-platform communication.With the development and application of information technology and 5G technology,the information needs of the broad audience have undergone a shift from a single media format to more diversified and personalized integrated media content.The rapid development of Artificial Intelligence(AI)technology has provided strong support for the generation and innovation of integrated media content.Through automation,multimodal content generation,immersive experience,and other ways,the application of Artificial Intelligence technology can not only improve the efficiency of content creation and enrich creative expression forms,but also provide users with more diversified and personalized information.
文摘The Fe_(1−x)Ni_(x)VO_(4)(x=0,0.05,0.10,and 0.20)nanoparticles in this work were successfully synthesized via a co-precipitation method.The structural,magnetic and electrochemical properties of the prepared Fe_(1−x)Ni_(x)VO_(4) nanoparticles were studied as a function of Ni content.The experimental results show that the prepared Ni-doped FeVO_(4) samples have a triclinic structure.Scanning electron microscopy(SEM)images reveal a decrease in average nanoparticle size with increasing Ni content,leading to an enhancement in both specific surface area and magnetization values.X-ray absorption near edge structure(XANES)analysis confirms the substitution of Ni^(2+)ions into Fe^(3+)sites.The magnetic investigation reveals that Ni-doped FeVO_(4) exhibits weak ferromagnetic behavior at room temperature,in contrast to the antiferromagnetic behavior observed in the undoped FeVO_(4).Electrochemical studies demonstrate that the Fe_(0.95)Ni_(0.05)VO_(4) electrode achieves the highest specific capacitance of 334.05 F·g^(−1) at a current density of 1 A·g^(−1),which is attributed to its smallest average pore diameter.In addition,the enhanced specific surface of the Fe_(0.8)Ni_(0.2)VO_(4) electrode is responsible for its outstanding cyclic stability.Overall,our results suggest that the magnetic and electrochemical properties of FeVO_(4) nanoparticles could be effectively tuned by varying Ni doping contents.
基金Under the auspices of the National Key Research and Development Program of China(No.2019YFA0606603)。
文摘Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.
基金supported by“Regional Innovation Strategy(RIS)”through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(MOE)(2021RIS-004)the Institute for Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korean government(MSIT)(No.RS-2022-II221200,Convergence Security Core Talent Training Business(Chungnam National University)).
文摘Content delivery networks(CDNs)lead to fast content distribution through content caching at specific CDN servers near end users.However,existing CDNs based on infrastructure cannot be employed in special cases,such as military operations.Thus,a temporary CDN without an existing infrastructure is required.To achieve this goal,we introduce a new CDN for drone-aided ad hoc networks,whereby multiple drones form ad hoc networks and quickly store specific content according to new caching algorithms.Unlike the typical CDN server,the content-caching algorithm in the proposed architecture considers the limited storage capacity of the drone.We present three content distribution algorithms that consider the constraints and mobility of drones.The main contribution of content caching for drone-aided ad hoc networks is to keep partial segments rather than whole content as well as move the drone near to area with a high volume of requests.The proposed scheme is evaluated to demonstrate its feasibility in terms of content acquisition time and utilization in several practical scenarios through simulations.Consequently,acquisition time in CDN to support drone movement is improved by approximately 50%and 40%rather than one in the proposed naive greedy approach as a function of content request interval and size,respectively.
文摘This study aimed to examine the surface and content validity of the Mentoring Function Scale for Novice Nurses, used to assess the mentoring of entry-level nurses, and to refine the scale items. In Study 1, six nurse education researchers, selected using convenience sampling, with five or more years of nursing experience and experience teaching novice nurses, were invited to an expert meeting in July 2015. A group interview was conducted that lasted approximately 120 minutes. Study 2 examined the content validity index. Between September and November 2015, we distributed a self-administered questionnaire survey to 11 participants selected by convenience sampling. The participants included five nurse education researchers with a minimum of five years of nursing experience and experience teaching novice nurses, as well as six clinical nurses with a master’s degree or higher. Finally, 81 questionnaire items were retained from the initial 125 items. The 81-item Mentoring Function Scale for Novice Nurses had higher content validity than the original scale. To further increase the scale’s applicability, future studies should assess its reliability, construct validity, and criterion-related validity.
文摘[Objective]The aim of this study was to set up a high performance liquid chromatography for rapid determination of isoflavones from soybean and analyze the correlation between isofalvone content and protein or fat content. [Method]The isoflavones were firstly extracted by 80% methanol and then hydrolyzed at 100 ℃. The chromatographic separation adopted a reversed-phase C18 analytical column with binary high-pressure gradient elution,while its analysis time was 25 min and column temperature was 40 ℃. The diode array detector was used for monitoring with wavelength of 260 nm. The correlation between isofalvone content and protein or fat content was analyzed by data processing system Origin 6.0. [Result]The high performance liquid chromatograph for determination of isoflavones from soybean was verified to be accurate and reliable by methodology. The isoflavones of 85 soybean lines cultivated in Jilin Province were determined,and the results primarily showed the characters and ranges of isoflavones from soybean lines cultivated in Jilin Province,while the isoflavone content of soybeans ranged from 2.29 to 4.89 mg/g,and the average content was 3.36 mg/g. The isoflavone content of 5 soybean lines exceeded 4 mg/g,while there was a remarkably negative correlation between isoflavone content and protein content,and there was no significant positive correlation between isoflavone content and fat content. [Conclusion]The isoflavone content of soybean lines cultivated in Jilin Province is higher,so it is feasible for breeding the soybean lines with high isoflavone content and fat contetnt.
基金National Natural Science Foundation of China (No. 52204101)Natural Science Foundation of Shandong Province (No. ZR2022QE137)Open Project of State Key Laboratory for Geomechanics and Deep Underground Engineering in CUMTB (No. SKLGDUEK2023).
文摘Uniaxial compression tests and cyclic loading acoustic emission tests were conducted on 20%,40%,60%,80%,dry and saturated muddy sandstone by using a creep impact loading system to investigate the mechanical properties and acoustic emission characteristics of soft rocks with different water contents under dynamic disturbance.The mechanical properties and acoustic emission characteristics of muddy sandstones at different water contents were analysed.Results of experimental studies show that water is a key factor in the mechanical properties of rocks,softening them,increasing their porosity,reducing their brittleness and increasing their plasticity.Under uniaxial compression,the macroscopic damage characteristics of the muddy sandstone change from mono-bevel shear damage and‘X’type conjugate bevel shear damage to a roadway bottom-drum type damage as the water content increases.Dynamic perturbation has a strengthening effect on the mechanical properties of samples with 60%and less water content,and a weakening effect on samples with 80%and more water content,but the weakening effect is not obvious.Macroscopic damage characteristics of dry samples remain unchanged,water samples from shear damage and tensile–shear composite damage gradually transformed into cleavage damage,until saturation transformation monoclinic shear damage.The evolution of acoustic emission energy and event number is mainly divided into four stages:loading stage(Ⅰ),dynamic loading stage(Ⅱ),yield failure stage(Ⅲ),and post-peak stage(Ⅳ),the acoustic emission characteristics of the stages were different for different water contents.The characteristic value of acoustic emission key point frequency gradually decreases,and the damage degree of the specimen increases,corresponding to low water content—high main frequency—low damage and high water content—low main frequency—high damage.
基金financial supports from National Natural Science Foundation of China(No.62205172)Huaneng Group Science and Technology Research Project(No.HNKJ22-H105)Tsinghua University Initiative Scientific Research Program and the International Joint Mission on Climate Change and Carbon Neutrality。
文摘Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.
基金Supported by Key Research and Development Program of Sichuan Province(2022YFS0436)Natural Science Foundation of Sichuan Province(2022NSFSC1738)+4 种基金Science and Technology Planning Project of Luzhou City(2021-JYJ-109,2023SYF120)Special Project of Traditional Chinese Medicine Scientific Research of Sichuan Provincial Administration of Traditional Chinese Medicine(2020CP0029)Southwest Medical University-Luzhou Hospital of Traditional Chinese Medicine Base Project(2019-LH003)Open Subject of Luzhou Key Laboratory of Fine Chemical Application Technology(HYJY-2106-B)Southwest Medical University Undergraduate Student Innovation and Entrepreneurship Training Program(202310632074).
文摘[Objectives]This study was conducted to optimize the extraction process of total flavonoids from Penthorum chinense Pursh and compare their contents from different parts.[Methods]Single factor and orthogonal experiments were designed to optimize the extraction process of total flavonoids from P.chinense Pursh with the volume fraction of ethanol,the ratio of material to liquid,heating reflux extraction time and extraction times as factors,and the content of total flavonoids as the index.A verification test was carried out.The optimized extraction process was adopted to compare the contents of total flavonoids from different parts of P.chinense Pursh.[Results]The best extraction process was extracting the powder of P.chinense Pursh for 2.0 h with 20 times of 55%ethanol by reflux twice.Under this condition,the contents of total flavonoids were 3.63%,8.90%,11.28%,and 4.36%from stems,leaves,flowers and whole grass of P.chinense Pursh,respectively.[Conclusions]The process is reasonable,feasible and stable,and can effectively extract total flavonoids from P.chinense Pursh.The contents of total flavonoids from different parts of P.chinense Pursh were quite different,and the value was higher in the leaves and flowers,so the proportions of leaves and flowers should be paid attention to in the industrial processing of P.chinense Pursh.
基金This work was supported by National Key Basic Research Program of China （973 Program） under Grant No. 2012CB315802 National Natural Science Foundation of China under Grant No. 61171102 and No. 61132001 Prospective Research on Future Networks of Jiangsu Future Networks Innovation institute under Grant No. BY2013095-4-01. Beijing Nova Program under Grant No.2008B50 and Beijing Higher Education Young Elite Teacher Project under Grant No.YETP0478.
文摘In-network caching and Interest packets aggregation are two important features of Content-Centric Networking(CCN).CCN routers can directly respond to the Interest request by Content Store(CS)and aggregate the same Interest packets by Pending Interest Table(PIT).In this way,most popular content requests will not reach the origin content server.Thus,content providers will be unaware of the actual usages of their contents in network.This new network paradigm presents content providers with unprecedented challenge.It will bring a great impact on existing mature business model of content providers,such as advertising revenue model based on hits amount.To leverage the advantages of CCN and the realistic business needs of content providers,we explore the hits-based content provisioning mechanism in CCN.The proposed approaches can avoid the unprecedented impact on content providers' existing business model and promote content providers to embrace the real deployment of CCN network.
基金financially supported by the Ministry of Science and Higher Education of the Russian Federation(State contract GZ0110/23-10-IF)。
文摘The longitudinal dependence of the behavior of ionospheric parameters has been the subject of a number of works where significant variations are discovered.This also applies to the prediction of the ionospheric total electron content(TEC),which neural network methods have recently been widely used.However,the results are mainly presented for a limited set of meridians.This paper examines the longitudinal dependence of the TEC forecast accuracy in the equatorial zone.In this case,the methods are used that provided the best accuracy on three meridians:European(30°E),Southeastern(110°E)and American(75°W).Results for the stations considered are analyzed as a function of longitude using the Jet Propulsion Laboratory Global Ionosphere Map(JPL GIM)for 2015.These results are for 2 h ahead and 24 h ahead forecast.It was found that in this case,based on the metric values,three groups of architectures can be distinguished.The first group included long short-term memory(LSTM),gated recurrent unit(GRU),and temporal convolutional networks(TCN)models as a part of unidirectional deep learning models;the second group is based on the recurrent models from the first group,which were supplemented with a bidirectional algorithm,increasing the TEC forecasting accuracy by 2-3 times.The third group,which includes the bidirectional TCN architecture(BiTCN),provided the highest accuracy.For this architecture,according to data obtained for 9 equatorial stations,practical independence of the TEC prediction accuracy from longitude was observed under the following metrics(Mean Absolute Error MAE,Root Mean Square Error RMSE,Mean Absolute Percentage Error MAPE):MAE(2 h)is 0.2 TECU approximately;MAE(24 h)is 0.4 TECU approximately;RMSE(2 h)is less than 0.5 TECU except Niue station(RMSE(2 h)is 1 TECU approximately);RMSE(24 h)is in the range of 1.0-1.7 TECU;MAPE(2 h)<1%except Darwin station,MAPE(24 h)<2%.This result was confirmed by data from additional 5 stations that formed latitudinal chains in the equatorial part of the three meridians.The complete correspondence of the observational and predicted TEC values is illustrated using several stations for disturbed conditions on December 19-22,2015,which included the strongest magnetic storm in the second half of the year(min Dst=-155 nT).
基金supported by the National Key Research and Development Program of China under Grant No.2019YFB1802800the National Natural Science Foundation of China under Grant No.62002055,62032013,61872073,62202247.
文摘The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.However,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content delivery.This challenge can be eased by sinking some critical content from cloud to edge.In this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new challenges.This work focuses on establishing a highly efficient content delivery framework in the IoE environment.In particular,the IoE environment is re-constructed as an end-edge-cloud collaborative system,in which the concept of digital twin is applied to promote the collaboration.Based on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)model.Then,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)technology.Finally,a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead.The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.
