FY-3G is the first polar-orbiting satellite equipped with a precipitation measurement radar(PMR)operating at Ku-andKa-band frequencies in China.In this study,we compare the reflectivity data from the FY-3G PMR Ku prod...FY-3G is the first polar-orbiting satellite equipped with a precipitation measurement radar(PMR)operating at Ku-andKa-band frequencies in China.In this study,we compare the reflectivity data from the FY-3G PMR Ku product and groundbasedradars(GRs)during 2024.Also,the FY-3G PMR is used as a third-party reference to evaluate the reflectivityconsistency among different GRs.The FY-3G PMR and GRs share similarities in their general distribution,characteristics,and intensity of reflectivity in strong precipitation cloud systems,though the former presents less detailed system structure.Systematic deviations between the FY-3G PMR and GRs and between GRs are comparable,albeit the reflectivity of the FY-3G PMR is generally slightly stronger than that of GRs(especially X-band GRs),with a mean bias ranging from 0.7 to 1.7dB.S-band GRs exhibit the smallest systematic deviation(STD=3.09 dB)from the FY-3G PMR,whereas the X-band GRsshow the largest(STD=3.61 dB),indirectly indicating the highest internal consistency among S-band GRs and the lowestamong X-band GRs.Besides,both S-and C-band GRs display similar deviations when paired with the FY-3G PMR as wellas when paired with their adjacent S/C-band GRs,suggesting good consistency between these two bands.In contrast,XbandGRs exhibit relatively poor consistency with S-band GRs and the FY-3G PMR,showing a deviation ranging from 3.0to 4.6 dB.展开更多
The Active Particle-induced X-ray Spectrometer（APXS） is one of the payloads on board the Yutu rover of the Chang＇E-3 mission. In order to assess the instrumental performance of APXS, a ground verification test was ...The Active Particle-induced X-ray Spectrometer（APXS） is one of the payloads on board the Yutu rover of the Chang＇E-3 mission. In order to assess the instrumental performance of APXS, a ground verification test was performed for two unknown samples（basaltic rock, mixed powder sample）. In this paper, the details of the experiment configurations and data analysis method are presented. The results show that the elemental abundance of major elements can be well determined by the APXS with relative deviations 〈15 wt.%（detection distance=30 mm,acquisition time=30 min）. The derived detection limit of each major element is inversely proportional to acquisition time and directly proportional to detection distance, suggesting that the appropriate distance should be 〈50 mm.展开更多
The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflect...The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflectivity observed by GPM Ku PR is compared quantitatively against GR networks from CINRAD of China and NEXRAD of the United States,and the volume matching method is used for spatial matching.Additionally,a novel frequency correction method for all phases as well as precipitation types is used to correct the GPM Ku PR radar frequency to the GR frequency.A total of 20 GRs(including 10 from CINRAD and 10 from NEXRAD)are included in this comparative analysis.The results indicate that,compared with CINRAD matched data,NEXRAD exhibits larger biases in reflectivity when compared with the frequency-corrected Ku PR.The root-mean-square difference for CINRAD is calculated at 2.38 d B,whereas for NEXRAD it is 3.23 d B.The mean bias of CINRAD matched data is-0.16 d B,while the mean bias of NEXRAD is-2.10 d B.The mean standard deviation of bias for CINRAD is 2.15 d B,while for NEXRAD it is 2.29 d B.This study effectively assesses weather radar data in both the United States and China,which is crucial for improving the overall consistency of global precipitation estimates.展开更多
Improving the accuracy of anthropogenic volatile organic compounds(VOCs)emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution.In this study,an anthropogenic s...Improving the accuracy of anthropogenic volatile organic compounds(VOCs)emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution.In this study,an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km×3 km spatial resolution based on the emission factormethod.The 2019 VOCs emission in Henan Provincewas 1003.5 Gg,while industrial process source(33.7%)was the highest emission source,Zhengzhou(17.9%)was the city with highest emission and April and August were the months with the more emissions.High VOCs emission regions were concentrated in downtown areas and industrial parks.Alkanes and aromatic hydrocarbons were the main VOCs contribution groups.The species composition,source contribution and spatial distribution were verified and evaluated through tracer ratio method(TR),Positive Matrix Factorization Model(PMF)and remote sensing inversion(RSI).Results show that both the emission results by emission inventory(EI)(15.7 Gg)and by TRmethod(13.6 Gg)and source contribution by EI and PMF are familiar.The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of 0.73.The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.展开更多
Kinship verification is a key biometric recognition task that determines biological relationships based on physical features.Traditional methods predominantly use facial recognition,leveraging established techniques a...Kinship verification is a key biometric recognition task that determines biological relationships based on physical features.Traditional methods predominantly use facial recognition,leveraging established techniques and extensive datasets.However,recent research has highlighted ear recognition as a promising alternative,offering advantages in robustness against variations in facial expressions,aging,and occlusions.Despite its potential,a significant challenge in ear-based kinship verification is the lack of large-scale datasets necessary for training deep learning models effectively.To address this challenge,we introduce the EarKinshipVN dataset,a novel and extensive collection of ear images designed specifically for kinship verification.This dataset consists of 4876 high-resolution color images from 157 multiracial families across different regions,forming 73,220 kinship pairs.EarKinshipVN,a diverse and large-scale dataset,advances kinship verification research using ear features.Furthermore,we propose the Mixer Attention Inception(MAI)model,an improved architecture that enhances feature extraction and classification accuracy.The MAI model fuses Inceptionv4 and MLP Mixer,integrating four attention mechanisms to enhance spatial and channel-wise feature representation.Experimental results demonstrate that MAI significantly outperforms traditional backbone architectures.It achieves an accuracy of 98.71%,surpassing Vision Transformer models while reducing computational complexity by up to 95%in parameter usage.These findings suggest that ear-based kinship verification,combined with an optimized deep learning model and a comprehensive dataset,holds significant promise for biometric applications.展开更多
In the foundry industries,process design has traditionally relied on manuals and complex theoretical calculations.With the advent of 3D design in casting,computer-aided design(CAD)has been applied to integrate the fea...In the foundry industries,process design has traditionally relied on manuals and complex theoretical calculations.With the advent of 3D design in casting,computer-aided design(CAD)has been applied to integrate the features of casting process,thereby expanding the scope of design options.These technologies use parametric model design techniques for rapid component creation and use databases to access standard process parameters and design specifications.However,3D models are currently still created through inputting or calling parameters,which requires numerous verifications through calculations to ensure the design rationality.This process may be significantly slowed down due to repetitive modifications and extended design time.As a result,there are increasingly urgent demands for a real-time verification mechanism to address this issue.Therefore,this study proposed a novel closed-loop model and software development method that integrated contextual design with real-time verification,dynamically verifying relevant rules for designing 3D casting components.Additionally,the study analyzed three typical closed-loop scenarios of agile design in an independent developed intelligent casting process system.It is believed that foundry industries can potentially benefit from favorably reduced design cycles to yield an enhanced competitive product market.展开更多
Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects s...Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.展开更多
Edit distance is an algorithm to measure the difference between two strings,usually represented as the minimum number of editing operations required to transform one string into another.The edit distance algorithm inv...Edit distance is an algorithm to measure the difference between two strings,usually represented as the minimum number of editing operations required to transform one string into another.The edit distance algorithm involves complex dependencies and constraints,making state management and verification work tedious.This paper proposes a derivation and verification method that avoids directly handling dependencies and constraints by proving the equivalence between the edit distance algorithm and existing functional modeling.First,the derivation process of edit distance algorithm mainly includes 1)describing problem specifications,2)inductively deducing recursive relations,3)formally constructing loop invariants using the optimization theory(memorization technology and optimal decision table)and properties(optimal substructure property and subproblems overlapping property)of the edit distance algorithm,4)generating the Minimalistic Imperative Programming Language(IMP)code based on the recursive relations.Second,the problem specification,loop invariants,and generated IMP code are input into Verification Condition Generator(VCG),which automatically generate five verification conditions,and then the correctness of edit distance algorithm is verified in the Isabelle/HOL theorem prover.The method utilizes formal technologies and theorem prover to complete the derivation and verification of the edit distance algorithm,and it can be applied to linear and nonlinear dynamic programming problems.展开更多
Accurate cloud classification plays a crucial role in aviation safety,climate monitoring,and localized weather forecasting.Current research has been focusing on machine learning techniques,particularly deep learning b...Accurate cloud classification plays a crucial role in aviation safety,climate monitoring,and localized weather forecasting.Current research has been focusing on machine learning techniques,particularly deep learning based model,for the types identification.However,traditional approaches such as convolutional neural networks(CNNs)encounter difficulties in capturing global contextual information.In addition,they are computationally expensive,which restricts their usability in resource-limited environments.To tackle these issues,we present the Cloud Vision Transformer(CloudViT),a lightweight model that integrates CNNs with Transformers.The integration enables an effective balance between local and global feature extraction.To be specific,CloudViT comprises two innovative modules:Feature Extraction(E_Module)and Downsampling(D_Module).These modules are able to significantly reduce the number of model parameters and computational complexity while maintaining translation invariance and enhancing contextual comprehension.Overall,the CloudViT includes 0.93×10^(6)parameters,which decreases more than ten times compared to the SOTA(State-of-the-Art)model CloudNet.Comprehensive evaluations conducted on the HBMCD and SWIMCAT datasets showcase the outstanding performance of CloudViT.It achieves classification accuracies of 98.45%and 100%,respectively.Moreover,the efficiency and scalability of CloudViT make it an ideal candidate for deployment inmobile cloud observation systems,enabling real-time cloud image classification.The proposed hybrid architecture of CloudViT offers a promising approach for advancing ground-based cloud image classification.It holds significant potential for both optimizing performance and facilitating practical deployment scenarios.展开更多
The exponential growth of the Internet of Things(IoT)has revolutionized various domains such as healthcare,smart cities,and agriculture,generating vast volumes of data that require secure processing and storage in clo...The exponential growth of the Internet of Things(IoT)has revolutionized various domains such as healthcare,smart cities,and agriculture,generating vast volumes of data that require secure processing and storage in cloud environments.However,reliance on cloud infrastructure raises critical security challenges,particularly regarding data integrity.While existing cryptographic methods provide robust integrity verification,they impose significant computational and energy overheads on resource-constrained IoT devices,limiting their applicability in large-scale,real-time scenarios.To address these challenges,we propose the Cognitive-Based Integrity Verification Model(C-BIVM),which leverages Belief-Desire-Intention(BDI)cognitive intelligence and algebraic signatures to enable lightweight,efficient,and scalable data integrity verification.The model incorporates batch auditing,reducing resource consumption in large-scale IoT environments by approximately 35%,while achieving an accuracy of over 99.2%in detecting data corruption.C-BIVM dynamically adapts integrity checks based on real-time conditions,optimizing resource utilization by minimizing redundant operations by more than 30%.Furthermore,blind verification techniques safeguard sensitive IoT data,ensuring privacy compliance by preventing unauthorized access during integrity checks.Extensive experimental evaluations demonstrate that C-BIVM reduces computation time for integrity checks by up to 40%compared to traditional bilinear pairing-based methods,making it particularly suitable for IoT-driven applications in smart cities,healthcare,and beyond.These results underscore the effectiveness of C-BIVM in delivering a secure,scalable,and resource-efficient solution tailored to the evolving needs of IoT ecosystems.展开更多
Combining the characteristics of the course“Comprehensive Training of E-Commerce Live Streaming,”this paper embeds the CDIO(Conceive-Design-Implement-Operate)method into the live streaming training process,carries o...Combining the characteristics of the course“Comprehensive Training of E-Commerce Live Streaming,”this paper embeds the CDIO(Conceive-Design-Implement-Operate)method into the live streaming training process,carries out the virtual scene“e-commerce live streaming”course design and project-based teaching reform that integrates teaching training with learning effects,and establishes a set of cross-professional student live streaming training procedures guided by the CDIO engineering method.The training results show that the CDIO practical teaching model supported by data feedback plays an important role and significance in improving students’learning effects,and also provides some new experiences for integrating engineering thinking into the construction of new liberal arts.展开更多
This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification metho...This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.展开更多
Space target imaging simulation technology is an important tool for space target detection and identification,with advantages that include high flexibility and low cost.However,existing space target imaging simulation...Space target imaging simulation technology is an important tool for space target detection and identification,with advantages that include high flexibility and low cost.However,existing space target imaging simulation technologies are mostly based on target magnitudes for simulations,making it difficult to meet image simulation requirements for different signal-to-noise ratio(SNR)needs.Therefore,design of a simulation method that generates target image sequences with various SNRs based on the optical detection system parameters will be important for faint space target detection research.Addressing the SNR calculation issue in optical observation systems,this paper proposes a ground-based detection image SNR calculation method using the optical system parameters.This method calculates the SNR of an observed image precisely using radiative transfer theory,the optical system parameters,and the observation environment parameters.An SNR-based target sequence image simulation method for ground-based detection scenarios is proposed.This method calculates the imaging SNR using the optical system parameters and establishes a model for conversion between the target’s apparent magnitude and image grayscale values,thereby enabling generation of target sequence simulation images with corresponding SNRs for different system parameters.Experiments show that the SNR obtained using this calculation method has an average calculation error of<1 dB when compared with the theoretical SNR of the actual optical system.Additionally,the simulation images generated by the imaging simulation method show high consistency with real images,which meets the requirements of faint space target detection algorithm research and provides reliable data support for development of related technologies.展开更多
Verification and validation(V&V)is a helpful tool for evaluating simulation errors,but its application in unsteady cavitating flow remains a challenging issue due to the difficulty in meeting the requirement of an...Verification and validation(V&V)is a helpful tool for evaluating simulation errors,but its application in unsteady cavitating flow remains a challenging issue due to the difficulty in meeting the requirement of an asymptotic range.Hence,a new V&V approach for large eddy simulation(LES)is proposed.This approach offers a viable solution for the error estimation of simulation data that are unable to satisfy the asymptotic range.The simulation errors of cavitating flow around a projectile near the free surface are assessed using the new V&V method.The evident error values are primarily dispersed around the cavity region and free surface.The increasingly intense cavitating flow increases the error magnitudes.In addition,the modeling error magnitudes of the Dynamic Smagorinsky-Lilly model are substantially smaller than that of the Smagorinsky-Lilly model.The present V&V method can capture the decrease in the modeling errors due to model enhancements,further exhibiting its applicability in cavitating flow simulations.Moreover,the monitoring points where the simulation data are beyond the asymptotic range are primarily dispersed near the cavity region,and the number of such points grows as the cavitating flow intensifies.The simulation outcomes also suggest that the re-entrant jet and shedding cavity collapse are the chief sources of vorticity motions,which remarkably affect the simulation accuracy.The results of this study provide a valuable reference for V&V research.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
This study introduces a novel concept,biological in vivo three-dimensional(3D)dose distribution verification,aimed at investigating how respiratory motion affects the efficacy of lung cancer radiotherapy,representing ...This study introduces a novel concept,biological in vivo three-dimensional(3D)dose distribution verification,aimed at investigating how respiratory motion affects the efficacy of lung cancer radiotherapy,representing an evolution from the current standard of rigid-body dose distribution verification.A 3D ex vivo biological lung motion simulation device(3D-BioLungEx)was designed to replicate human respiration.A radiotherapy plan of the patient was copied to the porcine lung,which was driven by 3D-BioLungEx to simulate various respiratory patterns that occur during treatment.To ensure anatomical consistency with the patient’s lung structure,during transmission,skin,skeleton,and organs were adjusted according to CT images of the porcine lung.The patient’s radiotherapy plan was then adapted to the porcine lung using the Monaco treatment planning system(TPS).Next,an iterative optimization and scatter inversion-based dose distribution retro-analysis algorithm(IOSI-BLDose)was developed to calculate the dose distribution during treatment.Gamma passing rates were used to quantify discrepancies between this dose distribution and that of the radiotherapy plan.When respiratory conditions were replicated,the passing rate reached up to 93.61%,while irregular breathing dropped it to 70%-90%,primarily due to amplitude changes.However,cycle variations had minimal impact.Compared to conventional rigid-body dose distribution verification,our method provides real-time biological feedback and more effectively captures motion-induced deviations.Accordingly,our biological in vivo 3D dose distribution verification has potential for improving treatment precision and enabling adaptive radiotherapy in clinical practice.展开更多
systematic verification and validation(V&V)of our previously proposed momentum source wave generation method is performed.Some settings of previous numerical wave tanks(NWTs)of regular and irregular waves have bee...systematic verification and validation(V&V)of our previously proposed momentum source wave generation method is performed.Some settings of previous numerical wave tanks(NWTs)of regular and irregular waves have been optimized.The H2-5 V&V method involving five mesh sizes with mesh refinement ratio being 1.225 is used to verify the NWT of regular waves,in which the wave height and mass conservation are mainly considered based on a Lv3(H s=0.75 m)and a Lv6(H s=5 m)regular wave.Additionally,eight different sea states are chosen to validate the wave height,mass conservation and wave frequency of regular waves.Regarding the NWT of irregular waves,five different sea states with significant wave heights ranging from 0.09 m to 12.5 m are selected to validate the statistical characteristics of irregular waves,including the profile of the wave spectrum,peak frequency and significant wave height.Results show that the verification errors for Lv3 and Lv6 regular wave on the most refined grid are−0.018 and−0.35 for wave height,respectively,and−0.14 and for−0.17 mass conservation,respectively.The uncertainty estimation analysis shows that the numerical error could be partially balanced out by the modelling error to achieve a smaller validation error by adjusting the mesh size elaborately.And the validation errors of the wave height,mass conservation and dominant frequency of regular waves under different sea states are no more than 7%,8% and 2%,respectively.For a Lv3(H_(s)=0.75 m)and a Lv6(H_(s)=5 m)regular wave,simulations are validated on the wave height in wave development section for safety factors FS≈1 and FS≈0.5-1,respectively.Regarding irregular waves,the validation errors of the significant wave height and peak frequency are both lower than 2%.展开更多
The scroll expander,as the core component of the micro-compressed air energy storage and power generation system,directly affects the output efficiency of the system.Meanwhile,the scroll profile plays a central role i...The scroll expander,as the core component of the micro-compressed air energy storage and power generation system,directly affects the output efficiency of the system.Meanwhile,the scroll profile plays a central role in determining the output performance of the scroll expander.In this study,in order to investigate the output characteristics of a variable cross-section scroll expander,numerical simulation and experimental studies were con-ducted by using Computational Fluid Dynamics(CFD)methods and dynamic mesh techniques.The impact of critical parameters on the output performance of the scroll expander was analyzed through the utilization of the control variable method.It is found that increasing the inlet pressure and temperature within a certain range can improve the output power of the scroll expander.However,the increase in temperature and meshing clearance leads to a decline in the overall output performance of the scroll expander,leading to a decrease in volumetric efficiency by 8.43%and 12.79%,respectively.The experiments demonstrate that under equal inlet pressure conditions,increasing the inlet temperature elevates both the rotational speed and torque output of the scroll expander.Specifically,compared to operating at normal temperatures,the output torque increases by 21.8%under high-temperature conditions.However,the rate of speed and torque variation decreases as a consequence of enlarged meshing clearance,resulting in increased internal leakage and reduction in isentropic efficiency.展开更多
In order to evaluate the precipitation forecast performance of mesoscale numerical model in Northeast China,mesoscale model in Liaoning Province and T213 model,and improve the ability to use their forecast products fo...In order to evaluate the precipitation forecast performance of mesoscale numerical model in Northeast China,mesoscale model in Liaoning Province and T213 model,and improve the ability to use their forecast products for forecasters,the synoptic verifications of their 12 h accumulated precipitation forecasts of 3 numerical modes from May to August in 2008 were made on the basis of different systems impacting weather in Liaoning Province.The time limitations were 24,36,48 and 60 h.The verified contents included 6 aspects such as intensity and position of precipitation center,intensity,location,scope and moving velocity of precipitation main body.The results showed that the three models had good forecasting capability for precipitation in Liaoning Province,but the cupacity of each model was obviously different.展开更多
This paper introduces a novel verification development platform for the passive UHF RFID tag,which is compatible with the ISO/IEC 18000-6B standard,operating in the 915MHz ISM band. This platform efficiently reduces t...This paper introduces a novel verification development platform for the passive UHF RFID tag,which is compatible with the ISO/IEC 18000-6B standard,operating in the 915MHz ISM band. This platform efficiently reduces the design and development time and cost, and implements a fast prototype design of the passive UHF RFID tag. It includes the RFID analog front end and the tag control logic, which is implemented in an Altera ACEX FPGA. The RFID analog front end, which is fabricated using a Chartered 0.35μm two-poly four-metal CMOS process, contains a local oscillator, power on reset circuit, matching network and backscatter, rectifier, regu- lator,AM demodulator, etc. The platform achieves rapid, flexible and efficient verification and development, and can also be fit for other RFID standards after changing the tag control logic in FPGA.展开更多
基金supported by the Innovation and Development Special Project of the China Meteorological Administration(Grant No.CXFZ2024J058)the Guangdong Province Basic and Applied Basic Research Foundation Meteorological Joint Fund Project(Grant No.2024A1515510036)+1 种基金the National Key R&D Program of China(Grant No.2022YFC3004101)the Technical Innovation Team Project of Guangzhou Meteorological Satellite Ground Station(Grant No.CXTD202401).
文摘FY-3G is the first polar-orbiting satellite equipped with a precipitation measurement radar(PMR)operating at Ku-andKa-band frequencies in China.In this study,we compare the reflectivity data from the FY-3G PMR Ku product and groundbasedradars(GRs)during 2024.Also,the FY-3G PMR is used as a third-party reference to evaluate the reflectivityconsistency among different GRs.The FY-3G PMR and GRs share similarities in their general distribution,characteristics,and intensity of reflectivity in strong precipitation cloud systems,though the former presents less detailed system structure.Systematic deviations between the FY-3G PMR and GRs and between GRs are comparable,albeit the reflectivity of the FY-3G PMR is generally slightly stronger than that of GRs(especially X-band GRs),with a mean bias ranging from 0.7 to 1.7dB.S-band GRs exhibit the smallest systematic deviation(STD=3.09 dB)from the FY-3G PMR,whereas the X-band GRsshow the largest(STD=3.61 dB),indirectly indicating the highest internal consistency among S-band GRs and the lowestamong X-band GRs.Besides,both S-and C-band GRs display similar deviations when paired with the FY-3G PMR as wellas when paired with their adjacent S/C-band GRs,suggesting good consistency between these two bands.In contrast,XbandGRs exhibit relatively poor consistency with S-band GRs and the FY-3G PMR,showing a deviation ranging from 3.0to 4.6 dB.
基金Supported by National Science and Technology Major Project(Chang’E-3 Active Particle-induced X-ray Spectrometer)
文摘The Active Particle-induced X-ray Spectrometer（APXS） is one of the payloads on board the Yutu rover of the Chang＇E-3 mission. In order to assess the instrumental performance of APXS, a ground verification test was performed for two unknown samples（basaltic rock, mixed powder sample）. In this paper, the details of the experiment configurations and data analysis method are presented. The results show that the elemental abundance of major elements can be well determined by the APXS with relative deviations 〈15 wt.%（detection distance=30 mm,acquisition time=30 min）. The derived detection limit of each major element is inversely proportional to acquisition time and directly proportional to detection distance, suggesting that the appropriate distance should be 〈50 mm.
基金funded by the National Key Research and Development Program of China(Grant No.2023YFB3907500)the National Natural Science Foundation(Grant No.42330602)the“Fengyun Satellite Remote Sensing Product Validation and Verification”Youth Innovation Team of the China Meteorological Administration(Grant No.CMA2023QN12)。
文摘The Global Precipitation Measurement(GPM)dual-frequency precipitation radar(DPR)products(Version 07A)are employed for a rigorous comparative analysis with ground-based operational weather radar(GR)networks.The reflectivity observed by GPM Ku PR is compared quantitatively against GR networks from CINRAD of China and NEXRAD of the United States,and the volume matching method is used for spatial matching.Additionally,a novel frequency correction method for all phases as well as precipitation types is used to correct the GPM Ku PR radar frequency to the GR frequency.A total of 20 GRs(including 10 from CINRAD and 10 from NEXRAD)are included in this comparative analysis.The results indicate that,compared with CINRAD matched data,NEXRAD exhibits larger biases in reflectivity when compared with the frequency-corrected Ku PR.The root-mean-square difference for CINRAD is calculated at 2.38 d B,whereas for NEXRAD it is 3.23 d B.The mean bias of CINRAD matched data is-0.16 d B,while the mean bias of NEXRAD is-2.10 d B.The mean standard deviation of bias for CINRAD is 2.15 d B,while for NEXRAD it is 2.29 d B.This study effectively assesses weather radar data in both the United States and China,which is crucial for improving the overall consistency of global precipitation estimates.
基金supported by Zhengzhou PM_(2.5)and O_(3)Collaborative Control and Monitoring Project(No.20220347A)the 2020 National Supercomputing Zhengzhou Center Innovation Ecosystem Construction Technology Project(No.201400210700).
文摘Improving the accuracy of anthropogenic volatile organic compounds(VOCs)emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution.In this study,an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km×3 km spatial resolution based on the emission factormethod.The 2019 VOCs emission in Henan Provincewas 1003.5 Gg,while industrial process source(33.7%)was the highest emission source,Zhengzhou(17.9%)was the city with highest emission and April and August were the months with the more emissions.High VOCs emission regions were concentrated in downtown areas and industrial parks.Alkanes and aromatic hydrocarbons were the main VOCs contribution groups.The species composition,source contribution and spatial distribution were verified and evaluated through tracer ratio method(TR),Positive Matrix Factorization Model(PMF)and remote sensing inversion(RSI).Results show that both the emission results by emission inventory(EI)(15.7 Gg)and by TRmethod(13.6 Gg)and source contribution by EI and PMF are familiar.The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R-value of 0.73.The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable.
文摘Kinship verification is a key biometric recognition task that determines biological relationships based on physical features.Traditional methods predominantly use facial recognition,leveraging established techniques and extensive datasets.However,recent research has highlighted ear recognition as a promising alternative,offering advantages in robustness against variations in facial expressions,aging,and occlusions.Despite its potential,a significant challenge in ear-based kinship verification is the lack of large-scale datasets necessary for training deep learning models effectively.To address this challenge,we introduce the EarKinshipVN dataset,a novel and extensive collection of ear images designed specifically for kinship verification.This dataset consists of 4876 high-resolution color images from 157 multiracial families across different regions,forming 73,220 kinship pairs.EarKinshipVN,a diverse and large-scale dataset,advances kinship verification research using ear features.Furthermore,we propose the Mixer Attention Inception(MAI)model,an improved architecture that enhances feature extraction and classification accuracy.The MAI model fuses Inceptionv4 and MLP Mixer,integrating four attention mechanisms to enhance spatial and channel-wise feature representation.Experimental results demonstrate that MAI significantly outperforms traditional backbone architectures.It achieves an accuracy of 98.71%,surpassing Vision Transformer models while reducing computational complexity by up to 95%in parameter usage.These findings suggest that ear-based kinship verification,combined with an optimized deep learning model and a comprehensive dataset,holds significant promise for biometric applications.
基金the financial support of the Natural Science Foundation of Hubei Province,China (Grant No.2022CFB770)。
文摘In the foundry industries,process design has traditionally relied on manuals and complex theoretical calculations.With the advent of 3D design in casting,computer-aided design(CAD)has been applied to integrate the features of casting process,thereby expanding the scope of design options.These technologies use parametric model design techniques for rapid component creation and use databases to access standard process parameters and design specifications.However,3D models are currently still created through inputting or calling parameters,which requires numerous verifications through calculations to ensure the design rationality.This process may be significantly slowed down due to repetitive modifications and extended design time.As a result,there are increasingly urgent demands for a real-time verification mechanism to address this issue.Therefore,this study proposed a novel closed-loop model and software development method that integrated contextual design with real-time verification,dynamically verifying relevant rules for designing 3D casting components.Additionally,the study analyzed three typical closed-loop scenarios of agile design in an independent developed intelligent casting process system.It is believed that foundry industries can potentially benefit from favorably reduced design cycles to yield an enhanced competitive product market.
基金funded by the National Natural Science Foundation of China Youth Fund(Grant No.62304022)Science and Technology on Electromechanical Dynamic Control Laboratory(China,Grant No.6142601012304)the 2022e2024 China Association for Science and Technology Innovation Integration Association Youth Talent Support Project(Grant No.2022QNRC001).
文摘Metal Additive Manufacturing(MAM) technology has become an important means of rapid prototyping precision manufacturing of special high dynamic heterogeneous complex parts. In response to the micromechanical defects such as porosity issues, significant deformation, surface cracks, and challenging control of surface morphology encountered during the selective laser melting(SLM) additive manufacturing(AM) process of specialized Micro Electromechanical System(MEMS) components, multiparameter optimization and micro powder melt pool/macro-scale mechanical properties control simulation of specialized components are conducted. The optimal parameters obtained through highprecision preparation and machining of components and static/high dynamic verification are: laser power of 110 W, laser speed of 600 mm/s, laser diameter of 75 μm, and scanning spacing of 50 μm. The density of the subordinate components under this reference can reach 99.15%, the surface hardness can reach 51.9 HRA, the yield strength can reach 550 MPa, the maximum machining error of the components is 4.73%, and the average surface roughness is 0.45 μm. Through dynamic hammering and high dynamic firing verification, SLM components meet the requirements for overload resistance. The results have proven that MEM technology can provide a new means for the processing of MEMS components applied in high dynamic environments. The parameters obtained in the conclusion can provide a design basis for the additive preparation of MEMS components.
基金Supported by the National Natural Science Foundation of China(62462036,62462037)Key Project of Jiangxi Provincial Natural Science Foundation(20242BAB26017)Academic and Major Disciplines in Jiangxi Province Technical Leader Training Project(20232BCJ22013)。
文摘Edit distance is an algorithm to measure the difference between two strings,usually represented as the minimum number of editing operations required to transform one string into another.The edit distance algorithm involves complex dependencies and constraints,making state management and verification work tedious.This paper proposes a derivation and verification method that avoids directly handling dependencies and constraints by proving the equivalence between the edit distance algorithm and existing functional modeling.First,the derivation process of edit distance algorithm mainly includes 1)describing problem specifications,2)inductively deducing recursive relations,3)formally constructing loop invariants using the optimization theory(memorization technology and optimal decision table)and properties(optimal substructure property and subproblems overlapping property)of the edit distance algorithm,4)generating the Minimalistic Imperative Programming Language(IMP)code based on the recursive relations.Second,the problem specification,loop invariants,and generated IMP code are input into Verification Condition Generator(VCG),which automatically generate five verification conditions,and then the correctness of edit distance algorithm is verified in the Isabelle/HOL theorem prover.The method utilizes formal technologies and theorem prover to complete the derivation and verification of the edit distance algorithm,and it can be applied to linear and nonlinear dynamic programming problems.
基金funded by Innovation and Development Special Project of China Meteorological Administration(CXFZ2022J038,CXFZ2024J035)Sichuan Science and Technology Program(No.2023YFQ0072)+1 种基金Key Laboratory of Smart Earth(No.KF2023YB03-07)Automatic Software Generation and Intelligent Service Key Laboratory of Sichuan Province(CUIT-SAG202210).
文摘Accurate cloud classification plays a crucial role in aviation safety,climate monitoring,and localized weather forecasting.Current research has been focusing on machine learning techniques,particularly deep learning based model,for the types identification.However,traditional approaches such as convolutional neural networks(CNNs)encounter difficulties in capturing global contextual information.In addition,they are computationally expensive,which restricts their usability in resource-limited environments.To tackle these issues,we present the Cloud Vision Transformer(CloudViT),a lightweight model that integrates CNNs with Transformers.The integration enables an effective balance between local and global feature extraction.To be specific,CloudViT comprises two innovative modules:Feature Extraction(E_Module)and Downsampling(D_Module).These modules are able to significantly reduce the number of model parameters and computational complexity while maintaining translation invariance and enhancing contextual comprehension.Overall,the CloudViT includes 0.93×10^(6)parameters,which decreases more than ten times compared to the SOTA(State-of-the-Art)model CloudNet.Comprehensive evaluations conducted on the HBMCD and SWIMCAT datasets showcase the outstanding performance of CloudViT.It achieves classification accuracies of 98.45%and 100%,respectively.Moreover,the efficiency and scalability of CloudViT make it an ideal candidate for deployment inmobile cloud observation systems,enabling real-time cloud image classification.The proposed hybrid architecture of CloudViT offers a promising approach for advancing ground-based cloud image classification.It holds significant potential for both optimizing performance and facilitating practical deployment scenarios.
基金supported by King Saud University,Riyadh,Saudi Arabia,through Researchers Supporting Project number RSP2025R498.
文摘The exponential growth of the Internet of Things(IoT)has revolutionized various domains such as healthcare,smart cities,and agriculture,generating vast volumes of data that require secure processing and storage in cloud environments.However,reliance on cloud infrastructure raises critical security challenges,particularly regarding data integrity.While existing cryptographic methods provide robust integrity verification,they impose significant computational and energy overheads on resource-constrained IoT devices,limiting their applicability in large-scale,real-time scenarios.To address these challenges,we propose the Cognitive-Based Integrity Verification Model(C-BIVM),which leverages Belief-Desire-Intention(BDI)cognitive intelligence and algebraic signatures to enable lightweight,efficient,and scalable data integrity verification.The model incorporates batch auditing,reducing resource consumption in large-scale IoT environments by approximately 35%,while achieving an accuracy of over 99.2%in detecting data corruption.C-BIVM dynamically adapts integrity checks based on real-time conditions,optimizing resource utilization by minimizing redundant operations by more than 30%.Furthermore,blind verification techniques safeguard sensitive IoT data,ensuring privacy compliance by preventing unauthorized access during integrity checks.Extensive experimental evaluations demonstrate that C-BIVM reduces computation time for integrity checks by up to 40%compared to traditional bilinear pairing-based methods,making it particularly suitable for IoT-driven applications in smart cities,healthcare,and beyond.These results underscore the effectiveness of C-BIVM in delivering a secure,scalable,and resource-efficient solution tailored to the evolving needs of IoT ecosystems.
基金phased research achievement of the Major Project of Philosophy and Social Sciences Research in Jiangsu Universities“Research on the Intervention Mechanism of Short Video Addiction”(2024SJZD145)。
文摘Combining the characteristics of the course“Comprehensive Training of E-Commerce Live Streaming,”this paper embeds the CDIO(Conceive-Design-Implement-Operate)method into the live streaming training process,carries out the virtual scene“e-commerce live streaming”course design and project-based teaching reform that integrates teaching training with learning effects,and establishes a set of cross-professional student live streaming training procedures guided by the CDIO engineering method.The training results show that the CDIO practical teaching model supported by data feedback plays an important role and significance in improving students’learning effects,and also provides some new experiences for integrating engineering thinking into the construction of new liberal arts.
基金supported in part by the Doctoral Initiation Fund of Nanchang Hangkong University(No.EA202403107)Jiangxi Province Early Career Youth Science and Technology Talent Training Project(No.CK202403509).
文摘This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.
基金supported by Open Fund of National Key Laboratory of Deep Space Exploration(NKDSEL2024014)by Civil Aerospace Pre-research Project of State Administration of Science,Technology and Industry for National Defence,PRC(D040103).
文摘Space target imaging simulation technology is an important tool for space target detection and identification,with advantages that include high flexibility and low cost.However,existing space target imaging simulation technologies are mostly based on target magnitudes for simulations,making it difficult to meet image simulation requirements for different signal-to-noise ratio(SNR)needs.Therefore,design of a simulation method that generates target image sequences with various SNRs based on the optical detection system parameters will be important for faint space target detection research.Addressing the SNR calculation issue in optical observation systems,this paper proposes a ground-based detection image SNR calculation method using the optical system parameters.This method calculates the SNR of an observed image precisely using radiative transfer theory,the optical system parameters,and the observation environment parameters.An SNR-based target sequence image simulation method for ground-based detection scenarios is proposed.This method calculates the imaging SNR using the optical system parameters and establishes a model for conversion between the target’s apparent magnitude and image grayscale values,thereby enabling generation of target sequence simulation images with corresponding SNRs for different system parameters.Experiments show that the SNR obtained using this calculation method has an average calculation error of<1 dB when compared with the theoretical SNR of the actual optical system.Additionally,the simulation images generated by the imaging simulation method show high consistency with real images,which meets the requirements of faint space target detection algorithm research and provides reliable data support for development of related technologies.
基金Supported by the National Key R&D Program of China(2022YFB3303501)the National Natural Science Foundation of China(Project Nos.52176041 and 12102308)the Fundamental Research Funds for the Central Universities(Project Nos.2042023kf0208 and 2042023kf0159).
文摘Verification and validation(V&V)is a helpful tool for evaluating simulation errors,but its application in unsteady cavitating flow remains a challenging issue due to the difficulty in meeting the requirement of an asymptotic range.Hence,a new V&V approach for large eddy simulation(LES)is proposed.This approach offers a viable solution for the error estimation of simulation data that are unable to satisfy the asymptotic range.The simulation errors of cavitating flow around a projectile near the free surface are assessed using the new V&V method.The evident error values are primarily dispersed around the cavity region and free surface.The increasingly intense cavitating flow increases the error magnitudes.In addition,the modeling error magnitudes of the Dynamic Smagorinsky-Lilly model are substantially smaller than that of the Smagorinsky-Lilly model.The present V&V method can capture the decrease in the modeling errors due to model enhancements,further exhibiting its applicability in cavitating flow simulations.Moreover,the monitoring points where the simulation data are beyond the asymptotic range are primarily dispersed near the cavity region,and the number of such points grows as the cavitating flow intensifies.The simulation outcomes also suggest that the re-entrant jet and shedding cavity collapse are the chief sources of vorticity motions,which remarkably affect the simulation accuracy.The results of this study provide a valuable reference for V&V research.
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(No.62371243)National Key Research and Development Program of China(No.2025YFC2427600)+4 种基金the Jiangsu Provincial Key Research and Development Program Social Development Project(No.BE2022720)the Natural Science Foundation of Jiangsu Province(No.BK20231190)Jiangsu Provincial Medical Key Discipline Cultivation Unit of Oncology Therapeutics(Radiotherapy)(No.JSDW202237)Changzhou Social Development Program(Nos.CE20235063 and CJ20244020)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.JX13614239).
文摘This study introduces a novel concept,biological in vivo three-dimensional(3D)dose distribution verification,aimed at investigating how respiratory motion affects the efficacy of lung cancer radiotherapy,representing an evolution from the current standard of rigid-body dose distribution verification.A 3D ex vivo biological lung motion simulation device(3D-BioLungEx)was designed to replicate human respiration.A radiotherapy plan of the patient was copied to the porcine lung,which was driven by 3D-BioLungEx to simulate various respiratory patterns that occur during treatment.To ensure anatomical consistency with the patient’s lung structure,during transmission,skin,skeleton,and organs were adjusted according to CT images of the porcine lung.The patient’s radiotherapy plan was then adapted to the porcine lung using the Monaco treatment planning system(TPS).Next,an iterative optimization and scatter inversion-based dose distribution retro-analysis algorithm(IOSI-BLDose)was developed to calculate the dose distribution during treatment.Gamma passing rates were used to quantify discrepancies between this dose distribution and that of the radiotherapy plan.When respiratory conditions were replicated,the passing rate reached up to 93.61%,while irregular breathing dropped it to 70%-90%,primarily due to amplitude changes.However,cycle variations had minimal impact.Compared to conventional rigid-body dose distribution verification,our method provides real-time biological feedback and more effectively captures motion-induced deviations.Accordingly,our biological in vivo 3D dose distribution verification has potential for improving treatment precision and enabling adaptive radiotherapy in clinical practice.
基金supported by the National Key R&D Program of China(Grant No.2022YFB3303500).
文摘systematic verification and validation(V&V)of our previously proposed momentum source wave generation method is performed.Some settings of previous numerical wave tanks(NWTs)of regular and irregular waves have been optimized.The H2-5 V&V method involving five mesh sizes with mesh refinement ratio being 1.225 is used to verify the NWT of regular waves,in which the wave height and mass conservation are mainly considered based on a Lv3(H s=0.75 m)and a Lv6(H s=5 m)regular wave.Additionally,eight different sea states are chosen to validate the wave height,mass conservation and wave frequency of regular waves.Regarding the NWT of irregular waves,five different sea states with significant wave heights ranging from 0.09 m to 12.5 m are selected to validate the statistical characteristics of irregular waves,including the profile of the wave spectrum,peak frequency and significant wave height.Results show that the verification errors for Lv3 and Lv6 regular wave on the most refined grid are−0.018 and−0.35 for wave height,respectively,and−0.14 and for−0.17 mass conservation,respectively.The uncertainty estimation analysis shows that the numerical error could be partially balanced out by the modelling error to achieve a smaller validation error by adjusting the mesh size elaborately.And the validation errors of the wave height,mass conservation and dominant frequency of regular waves under different sea states are no more than 7%,8% and 2%,respectively.For a Lv3(H_(s)=0.75 m)and a Lv6(H_(s)=5 m)regular wave,simulations are validated on the wave height in wave development section for safety factors FS≈1 and FS≈0.5-1,respectively.Regarding irregular waves,the validation errors of the significant wave height and peak frequency are both lower than 2%.
基金funded by the National Key Research and Development Program of China(No.2024YFE0208100).
文摘The scroll expander,as the core component of the micro-compressed air energy storage and power generation system,directly affects the output efficiency of the system.Meanwhile,the scroll profile plays a central role in determining the output performance of the scroll expander.In this study,in order to investigate the output characteristics of a variable cross-section scroll expander,numerical simulation and experimental studies were con-ducted by using Computational Fluid Dynamics(CFD)methods and dynamic mesh techniques.The impact of critical parameters on the output performance of the scroll expander was analyzed through the utilization of the control variable method.It is found that increasing the inlet pressure and temperature within a certain range can improve the output power of the scroll expander.However,the increase in temperature and meshing clearance leads to a decline in the overall output performance of the scroll expander,leading to a decrease in volumetric efficiency by 8.43%and 12.79%,respectively.The experiments demonstrate that under equal inlet pressure conditions,increasing the inlet temperature elevates both the rotational speed and torque output of the scroll expander.Specifically,compared to operating at normal temperatures,the output torque increases by 21.8%under high-temperature conditions.However,the rate of speed and torque variation decreases as a consequence of enlarged meshing clearance,resulting in increased internal leakage and reduction in isentropic efficiency.
文摘In order to evaluate the precipitation forecast performance of mesoscale numerical model in Northeast China,mesoscale model in Liaoning Province and T213 model,and improve the ability to use their forecast products for forecasters,the synoptic verifications of their 12 h accumulated precipitation forecasts of 3 numerical modes from May to August in 2008 were made on the basis of different systems impacting weather in Liaoning Province.The time limitations were 24,36,48 and 60 h.The verified contents included 6 aspects such as intensity and position of precipitation center,intensity,location,scope and moving velocity of precipitation main body.The results showed that the three models had good forecasting capability for precipitation in Liaoning Province,but the cupacity of each model was obviously different.
文摘This paper introduces a novel verification development platform for the passive UHF RFID tag,which is compatible with the ISO/IEC 18000-6B standard,operating in the 915MHz ISM band. This platform efficiently reduces the design and development time and cost, and implements a fast prototype design of the passive UHF RFID tag. It includes the RFID analog front end and the tag control logic, which is implemented in an Altera ACEX FPGA. The RFID analog front end, which is fabricated using a Chartered 0.35μm two-poly four-metal CMOS process, contains a local oscillator, power on reset circuit, matching network and backscatter, rectifier, regu- lator,AM demodulator, etc. The platform achieves rapid, flexible and efficient verification and development, and can also be fit for other RFID standards after changing the tag control logic in FPGA.
