The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical m...The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.展开更多
At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-laye...At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.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
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
The huge impact kinetic energy cannot be quickly dissipated by the energy-absorbing structure and transferred to the other vehicle through the car body structure,which will cause structural damage and threaten the liv...The huge impact kinetic energy cannot be quickly dissipated by the energy-absorbing structure and transferred to the other vehicle through the car body structure,which will cause structural damage and threaten the lives of the occupants.Therefore,it is necessary to understand the laws of energy conversion,dissipation and transfer during train collisions.This study proposes a multi-layer progressive analysis method of energy flow during train collisions,considering the characteristics of the train.In this method,the train collision system is divided into conversion,dissipation,and transfer layers from the perspective of the train,collision interface,and car body structure to analyze the energy conversion,dissipation and transfer characteristics.Taking the collision process of a rail train as an example,a train collision energy transfer path analysis model was established based on power flow theory.The results show that when the maximum mean acceleration of the vehicle meets the standard requirements,the jerk may exceed the allowable limit of the human body,and there is a risk of injury to the occupants of a secondary collision.The decay rate of the collision energy along the direction of train operation reaches 79%.As the collision progresses,the collision energy gradually converges in the structure with holes,and the structure deforms when the gathered energy is greater than the maximum energy the structure can withstand.The proposed method helps to understand the train collision energy flow law and provides theoretical support for the train crashworthiness design in the future.展开更多
The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging at...The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems.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
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
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
In practical engineering construction,multi-layered barriers containing geomembranes are extensively applied to retard the migration of pollutants.However,the associated analytical theory on pollutants diffusion still...In practical engineering construction,multi-layered barriers containing geomembranes are extensively applied to retard the migration of pollutants.However,the associated analytical theory on pollutants diffusion still needs to be further improved.In this work,general analytical solutions are derived for one-dimensional diffusion of degradable organic contaminant(DOC)in the multi-layered media containing geomembranes under a time-varying concentration boundary condition,where the variable substitution and separated variable approaches are employed.These analytical solutions with clear expressions can be used not only to study the diffusion behaviors of DOC in bottom and vertical composite barrier systems,but also to verify other complex numerical models.The proposed general analytical solutions are then fully validated via three comparative analyses,including comparisons with the experimental measurements,an existing analytical solution,and a finite-difference solution.Ultimately,the influences of different factors on the composite cutoff wall’s(CCW,which consists of two soil-bentonite layers and a geomembrane)service performance are investigated through a composite vertical barrier system as the application example.The findings obtained from this investigation can provide scientific guidance for the barrier performance evaluation and the engineering design of CCWs.This application example also exhibits the necessity and effectiveness of the developed analytical solutions.展开更多
Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanism...Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.展开更多
This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi...This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.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
Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed ...Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed satellites,ground users now can be covered by multiple visible satellites,but also face complex handover issues with such massive high-mobility satellites in multi-layer.The end-to-end routing is also affected by the handover behavior.In this paper,we propose an intelligent handover strategy dedicated to multi-layer LEO mega-constellation networks.Firstly,an analytic model is utilized to rapidly estimate the end-to-end propagation latency as a key handover factor to construct a multi-objective optimization model.Subsequently,an intelligent handover strategy is proposed by employing the Dueling Double Deep Q Network(D3QN)-based deep reinforcement learning algorithm for single-layer constellations.Moreover,an optimal crosslayer handover scheme is proposed by predicting the latency-jitter and minimizing the cross-layer overhead.Simulation results demonstrate the superior performance of the proposed method in the multi-layer LEO mega-constellation,showcasing reductions of up to 8.2%and 59.5%in end-to-end latency and jitter respectively,when compared to the existing handover strategies.展开更多
基金National Natural Science Foundation of China(52175237)。
文摘The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.
基金supported by the National Key Research and Development Program of China(No.2022YFB3404700)the National Natural Science Foundation of China(Nos.52105313 and 52275299)+2 种基金the Research and Development Program of Beijing Municipal Education Commission,China(No.KM202210005036)the Natural Science Foundation of Chongqing,China(No.CSTB2023NSCQ-MSX0701)the National Defense Basic Research Projects of China(No.JCKY2022405C002).
文摘At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.
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 by the National Natural Science Foundation of China(Grant No.52172409)Postdoctoral Innovation Talents Support Program(Grant No.BX20240298)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.2682024GF023)Heilongjiang Province Postdoctoral Foundation Project(Grant No.LBH-Z23041).
文摘The huge impact kinetic energy cannot be quickly dissipated by the energy-absorbing structure and transferred to the other vehicle through the car body structure,which will cause structural damage and threaten the lives of the occupants.Therefore,it is necessary to understand the laws of energy conversion,dissipation and transfer during train collisions.This study proposes a multi-layer progressive analysis method of energy flow during train collisions,considering the characteristics of the train.In this method,the train collision system is divided into conversion,dissipation,and transfer layers from the perspective of the train,collision interface,and car body structure to analyze the energy conversion,dissipation and transfer characteristics.Taking the collision process of a rail train as an example,a train collision energy transfer path analysis model was established based on power flow theory.The results show that when the maximum mean acceleration of the vehicle meets the standard requirements,the jerk may exceed the allowable limit of the human body,and there is a risk of injury to the occupants of a secondary collision.The decay rate of the collision energy along the direction of train operation reaches 79%.As the collision progresses,the collision energy gradually converges in the structure with holes,and the structure deforms when the gathered energy is greater than the maximum energy the structure can withstand.The proposed method helps to understand the train collision energy flow law and provides theoretical support for the train crashworthiness design in the future.
基金Nourah bint Abdulrahman University for funding this project through the Researchers Supporting Project(PNURSP2025R319)Riyadh,Saudi Arabia and Prince Sultan University for covering the article processing charges(APC)associated with this publication.Special acknowledgement to Automated Systems&Soft Computing Lab(ASSCL),Prince Sultan University,Riyadh,Saudi Arabia.
文摘The growing incidence of cyberattacks necessitates a robust and effective Intrusion Detection Systems(IDS)for enhanced network security.While conventional IDSs can be unsuitable for detecting different and emerging attacks,there is a demand for better techniques to improve detection reliability.This study introduces a new method,the Deep Adaptive Multi-Layer Attention Network(DAMLAN),to boost the result of intrusion detection on network data.Due to its multi-scale attention mechanisms and graph features,DAMLAN aims to address both known and unknown intrusions.The real-world NSL-KDD dataset,a popular choice among IDS researchers,is used to assess the proposed model.There are 67,343 normal samples and 58,630 intrusion attacks in the training set,12,833 normal samples,and 9711 intrusion attacks in the test set.Thus,the proposed DAMLAN method is more effective than the standard models due to the consideration of patterns by the attention layers.The experimental performance of the proposed model demonstrates that it achieves 99.26%training accuracy and 90.68%testing accuracy,with precision reaching 98.54%on the training set and 96.64%on the testing set.The recall and F1 scores again support the model with training set values of 99.90%and 99.21%and testing set values of 86.65%and 91.37%.These results provide a strong basis for the claims made regarding the model’s potential to identify intrusion attacks and affirm its relatively strong overall performance,irrespective of type.Future work would employ more attempts to extend the scalability and applicability of DAMLAN for real-time use in intrusion detection systems.
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 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 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Project(2023YFC3707800)supported by the National Key Research and Development Program of China。
文摘In practical engineering construction,multi-layered barriers containing geomembranes are extensively applied to retard the migration of pollutants.However,the associated analytical theory on pollutants diffusion still needs to be further improved.In this work,general analytical solutions are derived for one-dimensional diffusion of degradable organic contaminant(DOC)in the multi-layered media containing geomembranes under a time-varying concentration boundary condition,where the variable substitution and separated variable approaches are employed.These analytical solutions with clear expressions can be used not only to study the diffusion behaviors of DOC in bottom and vertical composite barrier systems,but also to verify other complex numerical models.The proposed general analytical solutions are then fully validated via three comparative analyses,including comparisons with the experimental measurements,an existing analytical solution,and a finite-difference solution.Ultimately,the influences of different factors on the composite cutoff wall’s(CCW,which consists of two soil-bentonite layers and a geomembrane)service performance are investigated through a composite vertical barrier system as the application example.The findings obtained from this investigation can provide scientific guidance for the barrier performance evaluation and the engineering design of CCWs.This application example also exhibits the necessity and effectiveness of the developed analytical solutions.
基金supported by Fundamental Research Funds for the Central Universities(No.lzujbky-2024-05)Innovation Foundation of Provincial Education Department of Gansu(2024B-005)+2 种基金Scientific Department of Gansu(24CXGA083,24CXGA024,JK2024-28,JK2024-32 and 23CXJA0007)Industrial Support Plan Project of Provincial Education Department of Gansu(2025CYZC-003 and CYZC-2024-10)the Hunan Natural Science Foundation Science and Education Joint Fund Project(2022JJ60109).
文摘Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.
基金Projects(42477162,52108347,52178371,52168046,52178321,52308383)supported by the National Natural Science Foundation of ChinaProjects(2023C03143,2022C01099,2024C01219,2022C03151)supported by the Zhejiang Key Research and Development Plan,China+6 种基金Project(LQ22E080010)supported by the Exploring Youth Project of Zhejiang Natural Science Foundation,ChinaProject(LR21E080005)supported by the Outstanding Youth Project of Natural Science Foundation of Zhejiang Province,ChinaProject(2022M712964)supported by the Postdoctoral Science Foundation of ChinaProject(2023AFB008)supported by the Natural Science Foundation of Hubei Province for Youth,ChinaProject(202203)supported by Engineering Research Centre of Rock-Soil Drilling&Excavation and Protection,Ministry of Education,ChinaProject(202305-2)supported by the Science and Technology Project of Zhejiang Provincial Communication Department,ChinaProject(2021K256)supported by the Construction Research Founds of Department of Housing and Urban-Rural Development of Zhejiang Province,China。
文摘This study proposes a general imperfect thermal contact model to predict the thermal contact resistance at the interface among multi-layered composite structures.Based on the Green-Lindsay(GL)thermoelastic theory,semi analytical solutions of temperature increment and displacement of multi-layered composite structures are obtained by using the Laplace transform method,upon which the effects of thermal resistance coefficient,partition coefficient,thermal conductivity ratio and heat capacity ratio on the responses are studied.The results show that the generalized imperfect thermal contact model can realistically describe the imperfect thermal contact problem.Accordingly,it may degenerate into other thermal contact models by adjusting the thermal resistance coefficient and partition coefficient.
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supported by the National Natural Science Foundation of China(No.62401597)Natural Science Foundation of Hunan Province,China(No.2024JJ6469)the Research Project of National University of Defense Technology,China(No.ZK22-02).
文摘Low Earth Orbit(LEO)mega-constellation networks,exemplified by Starlink,are poised to play a pivotal role in future mobile communication networks,due to their low latency and high capacity.With the massively deployed satellites,ground users now can be covered by multiple visible satellites,but also face complex handover issues with such massive high-mobility satellites in multi-layer.The end-to-end routing is also affected by the handover behavior.In this paper,we propose an intelligent handover strategy dedicated to multi-layer LEO mega-constellation networks.Firstly,an analytic model is utilized to rapidly estimate the end-to-end propagation latency as a key handover factor to construct a multi-objective optimization model.Subsequently,an intelligent handover strategy is proposed by employing the Dueling Double Deep Q Network(D3QN)-based deep reinforcement learning algorithm for single-layer constellations.Moreover,an optimal crosslayer handover scheme is proposed by predicting the latency-jitter and minimizing the cross-layer overhead.Simulation results demonstrate the superior performance of the proposed method in the multi-layer LEO mega-constellation,showcasing reductions of up to 8.2%and 59.5%in end-to-end latency and jitter respectively,when compared to the existing handover strategies.
