This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic diff...This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic differential equations.Then we obtain a comparison theorem in one-dimensional situation.展开更多
Differential Code Bias(DCB)is the time delays between two different GNSS signals,which is crucial for GNSS positioning.Previous studies have shown that it can be significantly affected by the flex power operations in ...Differential Code Bias(DCB)is the time delays between two different GNSS signals,which is crucial for GNSS positioning.Previous studies have shown that it can be significantly affected by the flex power operations in satellites.This study proposes a 15-min short-term DCB estimation method to analyze flex power's impact on DCB variations.The method jointly estimates satellite DCB,receiver DCB,and ionospheric parameters using over 300 MGEX stations.We examined three representative flex power events in 2024,achieving average internal RMS values of 0.042 ns and 0.0068 ns for inter-frequency and intra-frequency scenarios respectively.Results show that intra-frequency DCB exhibits clear shift biases synchronized with flex power state transitions while maintaining stability within 0.20 ns during nontransition periods.No definitive impact on inter-frequency DCB was observed at current estimation precision levels.展开更多
The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location re...The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.展开更多
With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods...With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods are deficient,failing to reasonably allocate the privacy budget for non-outlier location points and ignoring the critical location information that may be contained in the outlier points,leading to decreased data availability and privacy exposure problems.To address these problems,this paper proposes a Mix Location Privacy Preservation Method Based on Differential Privacy with Clustering(MLDP).The method first utilizes the DBSCAN clustering algorithm to classify location points into non-outliers and outliers.For non-outliers,the scoring function is designed by combining geographic information and semantic information,and the privacy budget is allocated according to the heat intensity of the hotspot area;for outliers,the scoring function is constructed to allocate the privacy budget based on their correlation with the hotspot area.By comprehensively considering the geographic information,semantic information,and correlation with hotspot areas of the location points,a reasonable privacy budget is assigned to each location point,andfinallynoise is added throughthe Laplacemechanismto realizeprivacyprotection.Experimental results on tworeal trajectory datasets,Geolife and T-Drive,show that the MLDP approach significantly improves data availability while effectively protecting location privacy.Compared with the comparison methods,the maximum available data ratio of MLDP is 1.Moreover,compared with the RandomNoise method,its execution time is 0.056–0.061 s longer,and the logRE is 0.12951–0.62194 lower;compared with KemeansDP,QTK-DP,DPK-F,IDP-SC,and DPK-Means-up methods,it saves 0.114–0.296 s in execution time,and the logRE is 0.01112–0.38283 lower.展开更多
The support vector machine,a widely used binary classification method,may expose sensitive information during training.To address this,the authors propose a personalized differential privacy method that extends differ...The support vector machine,a widely used binary classification method,may expose sensitive information during training.To address this,the authors propose a personalized differential privacy method that extends differential privacy.Specifically,the authors introduce personalized differentially private support vector machines to meet different individuals'privacy requirements,using a reweighting strategy and the Laplace mechanism.Theoretical analysis demonstrates that the proposed methods simultaneously satisfy the requirements of personalized differential privacy and ensure model prediction accuracy at these privacy levels.Extensive experiments demonstrate that the proposed methods outperform the existing methods.展开更多
Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its...Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its reactivity.Accurately quantifying the phenolic hydroxyl content in PPO is essential but challenging.In this study,we proposed a method for measuring the phenolic hydroxyl content of PPO using differential UV absorption spectroscopy.In alkaline solutions,the phenolic hydroxyl in PPO completely ionizes to form phenoxide ions,leading to a significant increase in UV absorbance at approximately 250 and 300 nm.Notably,the differential UV absorbance at approximately 300 nm was directly proportional to the phenolic hydroxyl concentration.Using 2,6-dimethylphenol as a standard,a calibration curve was established to relate the phenolic hydroxyl concentration to differential UV absorbance at approximately 300 nm,providing a precise and straightforward method for phenolic hydroxyl quantification in PPO with distinct advantages over conventional techniques.展开更多
In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order relia...In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.展开更多
[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing method...[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing methods still suffer from poor edge/corner sensitivity,misjudgment due to fixed thresholds,and limited ability to extract position information.This work proposes a wireless power transfer-foreign object detection(WPT-FOD)method based on channel differential response and a dynamic-threshold corner-enhancement strategy,aiming to improve detection sensitivity,localization accuracy,and robustness without altering the overall coil layout.[Method]A multi-channel detection coil array is designed,and the self-inductance disturbance response of each channel coil is modeled.A channel-difference mapping mechanism is introduced to build a 2-D sensitivity matrix to characterize spatial position correlation.A corner-enhancement algorithm is developed to weight and amplify the collaborative response of adjacent channels,and a dynamic threshold adjustment mechanism is integrated to adapt to varying interference levels.Validation is carried out on a self-built 64-channel FOD platform by moving a typical metallic foreign object across central,edge,and corner regions,and by conducting comparative tests under different interference intensities.[Result]When a typical metallic foreign object moves to corner regions,the self-inductance disturbance of the detection coil increases from less than 0.02μH to more than 0.06μH,significantly enhancing the discrimination capability at corners.Under varying interference strengths,the dynamic threshold mechanism reduces the number of false positives from 13 to 2,demonstrating good environmental adaptability and stability.[Conclusion]By combining channel differential response,corner enhancement,and dynamic thresholding,the proposed WPT-FOD effectively mitigates edge/corner blind spots and fixed-threshold misjudgment,while providing localization capability and robustness.It markedly improves the accuracy of metallic foreign object detection in WPT systems and offers a feasible path and method reference for the safe application and engineering deployment of WPT systems.展开更多
By investigating the evolution of shale gas generation,storage,adjustment and accumulation under different structural settings in superimposed basins,this study elucidates the differential accumulation mechanisms of s...By investigating the evolution of shale gas generation,storage,adjustment and accumulation under different structural settings in superimposed basins,this study elucidates the differential accumulation mechanisms of shale gas.An improved evaluation method of shale gas content evolution in superimposed basins is proposed.This method incorporates the coupling effect of key geological factors such as temperature,pressure,organic matter abundance,maturity,and pore characteristics on the content and occurrence state of shale gas,as well as the configuration relationship between shale gas generation and storage throughout geological history.Using this approach,the gas evolution histories of the Longmaxi Formation shales in wells N201 and PY1 are reconstructed under varying geological conditions.The Longmaxi Formation shales in these wells are dominated by typeⅠkerogen,with original total organic carbon(TOC_(o))contents of 6.20 wt% and 4.92 wt%,respectively,indicating differences in the initial material basis for gas generation.At the maximum burial depth of approximately 5000 m,the Longmaxi Formation shale in well N201 exhibits a formation pressure coefficient of 2.05,an organic matter maturity of 2.2%,and organic pores accounting for 68%of the total porosity.The gas generation quantity(Q_(g))reaches 19.24 m^(3)/t,while the gas storage capacity(Q_(s))is 4.30 m^(3)/t.The actual total gas content(Q_(a)),constrained by Q_(s),is 4.30 m^(3)/t,with free gas comprising 94%.Following relatively moderate tectonic uplift,the Q_(a) in well N201 decreases to 4.03 m^(3)/t,with free gas accounting for 63%.In contrast,the Longmaxi Formation shale in well PY1 reached a maximum burial depth of 6300 m,associated with a formation pressure coefficient of 1.62,organic matter maturity of 2.5%,and organic pore proportion of 67%.Here,Q_(g) is 16.87 m^(3)/t,and both Q_(s) and Q_(a) are 3.65 m^(3)/t,with free gas accounting for 98%.After intense tectonic uplift,Q_(a) declines to 2.72 m^(3)/t,and the proportion of free gas drops to51%.Finally,a four-stage differential accumulation model of shale gas is established:Slow gas generation and only adsorbed gas occur in stageⅠ,which is primarily controlled by TOC content;both adsorbed gas and free gas present in stageⅡ,with free gas becoming dominant;rapid gas generation and free gas predominance are controlled by temperature and porosity in stageⅢ;and gas adjustment and accumulation are primarily controlled by temperature and pressure in stageⅣ.展开更多
Selective Laser Melting(SLM),an advanced metal additive manufacturing technology,offers high precision and personalized customization advantages.However,selecting reasonable SLM parameters is challenging due to comple...Selective Laser Melting(SLM),an advanced metal additive manufacturing technology,offers high precision and personalized customization advantages.However,selecting reasonable SLM parameters is challenging due to complex relationships.This study proposes a method for identifying the optimal process window by combining the simulation model with an optimization algorithm.JAYA is guided by the principle of preferential behavior towards best solutions and avoidance of worst ones,but it is prone to premature convergence thus leading to insufficient global search.To overcome limitations,this research proposes a Differential Evolution-framed JAYA algorithm(DEJAYA).DEJAYA incorporates four key enhancements to improve the flexibility of the original algorithm,which include DE framework design,horizontal crossover operator,longitudinal crossover operator,and global greedy strategy.The effectiveness of DEJAYA is rigorously evaluated by a suite of 23 distinct benchmark functions.Furthermore,the numerical simulation establishes AlSi10Mg single-track formation models,and DEJAYA successfully identified the optimal process window for this problem.Experimental results validate that DEJAYA effectively guides SLM parameter selection for AlSi10Mg.展开更多
Dear Editor,This letter addresses the critical challenge of preserving privacy in graph learning without compromising on data utility.Differential privacy(DP)is emerging as an effective method for privacy-preserving g...Dear Editor,This letter addresses the critical challenge of preserving privacy in graph learning without compromising on data utility.Differential privacy(DP)is emerging as an effective method for privacy-preserving graph learning.However,its application often diminishes data utility,especially for nodes with fewer neighbors in graph neural networks(GNNs).展开更多
Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that devi...Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.展开更多
The main purpose of this paper is to try to find all entire solutions of the Fermat type difference-differential equation[p1(z)f(z+c)]^(2)+[p2(z)f(z)+p3(z)f′(z)]^(2)=p(z);or[p1(z)f(z)]^(2)+[p2(z)f′(z)+p3(z)f(z+c)]^(...The main purpose of this paper is to try to find all entire solutions of the Fermat type difference-differential equation[p1(z)f(z+c)]^(2)+[p2(z)f(z)+p3(z)f′(z)]^(2)=p(z);or[p1(z)f(z)]^(2)+[p2(z)f′(z)+p3(z)f(z+c)]^(2)=p(z)or[p1(z)f′(z)]^(2)+[p2(z)f(z+c)+p3(z)f(z)]^(2)=p(z);where c is a nonzero complex number,p1;p2 and p3 are polynomials in C satisfying p1p3■0;and p is a nonzero irreducible polynomial in C.展开更多
This paper presents an explicit difference scheme with accuracy and branching stability for solving onedimensional parabolic type equation by the method of undetermined parameters and its truncation error is O(△t4+△...This paper presents an explicit difference scheme with accuracy and branching stability for solving onedimensional parabolic type equation by the method of undetermined parameters and its truncation error is O(△t4+△x4). The stability condition is r=a△t/△x2<1/2.展开更多
A family of high_order accuracy explicit difference schemes for solving 2_dimension parabolic P.D.E. are constructed. Th e stability condition is r=Δt/Δx 2=Δt/Δy 2【1/2 and the truncation err or is O(Δt 3+Δx...A family of high_order accuracy explicit difference schemes for solving 2_dimension parabolic P.D.E. are constructed. Th e stability condition is r=Δt/Δx 2=Δt/Δy 2【1/2 and the truncation err or is O(Δt 3+Δx 4).展开更多
In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error...In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.展开更多
Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,curr...Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.展开更多
In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction o...In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction on the entire coefficients associated with Petrenko's deviation of the above equation,we obtain some results and partially address a question posed byⅠ.Laine and C.C.Yang.Furthermore,for the entire solutions f(z)of the difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=F(z),where Aj(z)(j=0,…,n),F(z)are entire functions,we discover a close relationship between the measure of common transcendental directions associated with classical difference operators of f(z)and Petrenko's deviations of the coefficients.展开更多
Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health pla...Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health planning and risk reduction.Most existing approaches rely on a single threshold temperature(e.g.,35℃of daily max temperature),applied uniformly to the entire population.However,this one-size-fits-all assumption overlooks substantial differences in heat sensitivity across population subgroups.In this study,we address this limitation by quantifying subgroup-specific temperature-mortality relationships and using corresponding minimum mortality temperatures(MMTs)to assess heat exposure.Results show that the population-wide MMT was 27.5℃,but it varied greatly across population subgroups.The elderly population(≥65)had an MMT of 24.6℃,much lower than the 28.6℃observed in younger individuals(<65).Females also exhibited a lower MMT that males(25℃versus 28.2℃).However,educational attainment did not significantly affect MMT.Using a uniform MMT resulted in substantial underestimation of heat exposure,ranging from 25.3%in 1990 to 13.9%in 2020,reflecting demographic shifts over time.Spatially,nearly half of the city experienced underestimated heat risk,especially in central and northeastern regions where heat-vulnerable populations are concentrated.These findings underscore the need for more nuanced heat exposure assessments that account for demographic and spatial variability,paving the way for targeted public health interventions to protect the most vulnerable urban populations.展开更多
At the start of the new year,Cao Xiucheng,Chairman of Henan No.2 Textile Machinery Co.,Ltd.,was on his way to visit clients when he kept receiving urgent calls from the Xinyang production base regarding order scheduli...At the start of the new year,Cao Xiucheng,Chairman of Henan No.2 Textile Machinery Co.,Ltd.,was on his way to visit clients when he kept receiving urgent calls from the Xinyang production base regarding order scheduling.It turned out that since the end of 2025,the company had successively secured bulk spindle orders from overseas clients in Bangladesh and other countries,coupled with continuous urgent requests for orders from domestic manufacturers.Faced with such a production peak right at the beginning of the year,Mr.Cao Xiucheng admitted,“It was truly unexpected.”展开更多
基金Supported by the National Natural Science Foundation of China(12001074)the Research Innovation Program of Graduate Students in Hunan Province(CX20220258)+1 种基金the Research Innovation Program of Graduate Students of Central South University(1053320214147)the Key Scientific Research Project of Higher Education Institutions in Henan Province(25B110025)。
文摘This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic differential equations.Then we obtain a comparison theorem in one-dimensional situation.
基金the funds from the Key Laboratory of Smart Earth(KF2023YB01-07)Shanghai Collaborative Innovation Fund(XTCX-KJ-2024-17)the National Natural Science Foundation of China(42388102,62303311,and 62231010)。
文摘Differential Code Bias(DCB)is the time delays between two different GNSS signals,which is crucial for GNSS positioning.Previous studies have shown that it can be significantly affected by the flex power operations in satellites.This study proposes a 15-min short-term DCB estimation method to analyze flex power's impact on DCB variations.The method jointly estimates satellite DCB,receiver DCB,and ionospheric parameters using over 300 MGEX stations.We examined three representative flex power events in 2024,achieving average internal RMS values of 0.042 ns and 0.0068 ns for inter-frequency and intra-frequency scenarios respectively.Results show that intra-frequency DCB exhibits clear shift biases synchronized with flex power state transitions while maintaining stability within 0.20 ns during nontransition periods.No definitive impact on inter-frequency DCB was observed at current estimation precision levels.
基金supported by the Natural Science Foundation of Fujian Province of China(2025J01380)National Natural Science Foundation of China(No.62471139)+3 种基金the Major Health Research Project of Fujian Province(2021ZD01001)Fujian Provincial Units Special Funds for Education and Research(2022639)Fujian University of Technology Research Start-up Fund(GY-S24002)Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare(GY-H-24179).
文摘The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.
基金supported in part by the National Natural Science Foundation of China(Grant No.61971291)the Basic Scientific Research Project of the Liaoning Provincial Department of Education(LJ212410144013)+2 种基金the Leading Talent of the‘Xing Liao Ying Cai Plan’(XLYC2202013)the Shenyang Natural Science Foundation(22-315-6-10)the Guangxuan Scholar of Shenyang Ligong University(SYLUGXXZ202205).
文摘With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods are deficient,failing to reasonably allocate the privacy budget for non-outlier location points and ignoring the critical location information that may be contained in the outlier points,leading to decreased data availability and privacy exposure problems.To address these problems,this paper proposes a Mix Location Privacy Preservation Method Based on Differential Privacy with Clustering(MLDP).The method first utilizes the DBSCAN clustering algorithm to classify location points into non-outliers and outliers.For non-outliers,the scoring function is designed by combining geographic information and semantic information,and the privacy budget is allocated according to the heat intensity of the hotspot area;for outliers,the scoring function is constructed to allocate the privacy budget based on their correlation with the hotspot area.By comprehensively considering the geographic information,semantic information,and correlation with hotspot areas of the location points,a reasonable privacy budget is assigned to each location point,andfinallynoise is added throughthe Laplacemechanismto realizeprivacyprotection.Experimental results on tworeal trajectory datasets,Geolife and T-Drive,show that the MLDP approach significantly improves data availability while effectively protecting location privacy.Compared with the comparison methods,the maximum available data ratio of MLDP is 1.Moreover,compared with the RandomNoise method,its execution time is 0.056–0.061 s longer,and the logRE is 0.12951–0.62194 lower;compared with KemeansDP,QTK-DP,DPK-F,IDP-SC,and DPK-Means-up methods,it saves 0.114–0.296 s in execution time,and the logRE is 0.01112–0.38283 lower.
基金supported by the National Key R&D Program of China under Grant No.2023YFA1008702the National Natural Science Foundation of China under Grant No.12571300。
文摘The support vector machine,a widely used binary classification method,may expose sensitive information during training.To address this,the authors propose a personalized differential privacy method that extends differential privacy.Specifically,the authors introduce personalized differentially private support vector machines to meet different individuals'privacy requirements,using a reweighting strategy and the Laplace mechanism.Theoretical analysis demonstrates that the proposed methods simultaneously satisfy the requirements of personalized differential privacy and ensure model prediction accuracy at these privacy levels.Extensive experiments demonstrate that the proposed methods outperform the existing methods.
基金the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01072)the Institute of Zhejiang University-Quzhou for their financial support。
文摘Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its reactivity.Accurately quantifying the phenolic hydroxyl content in PPO is essential but challenging.In this study,we proposed a method for measuring the phenolic hydroxyl content of PPO using differential UV absorption spectroscopy.In alkaline solutions,the phenolic hydroxyl in PPO completely ionizes to form phenoxide ions,leading to a significant increase in UV absorbance at approximately 250 and 300 nm.Notably,the differential UV absorbance at approximately 300 nm was directly proportional to the phenolic hydroxyl concentration.Using 2,6-dimethylphenol as a standard,a calibration curve was established to relate the phenolic hydroxyl concentration to differential UV absorbance at approximately 300 nm,providing a precise and straightforward method for phenolic hydroxyl quantification in PPO with distinct advantages over conventional techniques.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities of China(No.23D110316)。
文摘In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.
文摘[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing methods still suffer from poor edge/corner sensitivity,misjudgment due to fixed thresholds,and limited ability to extract position information.This work proposes a wireless power transfer-foreign object detection(WPT-FOD)method based on channel differential response and a dynamic-threshold corner-enhancement strategy,aiming to improve detection sensitivity,localization accuracy,and robustness without altering the overall coil layout.[Method]A multi-channel detection coil array is designed,and the self-inductance disturbance response of each channel coil is modeled.A channel-difference mapping mechanism is introduced to build a 2-D sensitivity matrix to characterize spatial position correlation.A corner-enhancement algorithm is developed to weight and amplify the collaborative response of adjacent channels,and a dynamic threshold adjustment mechanism is integrated to adapt to varying interference levels.Validation is carried out on a self-built 64-channel FOD platform by moving a typical metallic foreign object across central,edge,and corner regions,and by conducting comparative tests under different interference intensities.[Result]When a typical metallic foreign object moves to corner regions,the self-inductance disturbance of the detection coil increases from less than 0.02μH to more than 0.06μH,significantly enhancing the discrimination capability at corners.Under varying interference strengths,the dynamic threshold mechanism reduces the number of false positives from 13 to 2,demonstrating good environmental adaptability and stability.[Conclusion]By combining channel differential response,corner enhancement,and dynamic thresholding,the proposed WPT-FOD effectively mitigates edge/corner blind spots and fixed-threshold misjudgment,while providing localization capability and robustness.It markedly improves the accuracy of metallic foreign object detection in WPT systems and offers a feasible path and method reference for the safe application and engineering deployment of WPT systems.
基金funded by the Sinopec Science and Technology Project(No.P23132)the AAPG Foundation Grants-inAid Program(No.18644937)。
文摘By investigating the evolution of shale gas generation,storage,adjustment and accumulation under different structural settings in superimposed basins,this study elucidates the differential accumulation mechanisms of shale gas.An improved evaluation method of shale gas content evolution in superimposed basins is proposed.This method incorporates the coupling effect of key geological factors such as temperature,pressure,organic matter abundance,maturity,and pore characteristics on the content and occurrence state of shale gas,as well as the configuration relationship between shale gas generation and storage throughout geological history.Using this approach,the gas evolution histories of the Longmaxi Formation shales in wells N201 and PY1 are reconstructed under varying geological conditions.The Longmaxi Formation shales in these wells are dominated by typeⅠkerogen,with original total organic carbon(TOC_(o))contents of 6.20 wt% and 4.92 wt%,respectively,indicating differences in the initial material basis for gas generation.At the maximum burial depth of approximately 5000 m,the Longmaxi Formation shale in well N201 exhibits a formation pressure coefficient of 2.05,an organic matter maturity of 2.2%,and organic pores accounting for 68%of the total porosity.The gas generation quantity(Q_(g))reaches 19.24 m^(3)/t,while the gas storage capacity(Q_(s))is 4.30 m^(3)/t.The actual total gas content(Q_(a)),constrained by Q_(s),is 4.30 m^(3)/t,with free gas comprising 94%.Following relatively moderate tectonic uplift,the Q_(a) in well N201 decreases to 4.03 m^(3)/t,with free gas accounting for 63%.In contrast,the Longmaxi Formation shale in well PY1 reached a maximum burial depth of 6300 m,associated with a formation pressure coefficient of 1.62,organic matter maturity of 2.5%,and organic pore proportion of 67%.Here,Q_(g) is 16.87 m^(3)/t,and both Q_(s) and Q_(a) are 3.65 m^(3)/t,with free gas accounting for 98%.After intense tectonic uplift,Q_(a) declines to 2.72 m^(3)/t,and the proportion of free gas drops to51%.Finally,a four-stage differential accumulation model of shale gas is established:Slow gas generation and only adsorbed gas occur in stageⅠ,which is primarily controlled by TOC content;both adsorbed gas and free gas present in stageⅡ,with free gas becoming dominant;rapid gas generation and free gas predominance are controlled by temperature and porosity in stageⅢ;and gas adjustment and accumulation are primarily controlled by temperature and pressure in stageⅣ.
文摘Selective Laser Melting(SLM),an advanced metal additive manufacturing technology,offers high precision and personalized customization advantages.However,selecting reasonable SLM parameters is challenging due to complex relationships.This study proposes a method for identifying the optimal process window by combining the simulation model with an optimization algorithm.JAYA is guided by the principle of preferential behavior towards best solutions and avoidance of worst ones,but it is prone to premature convergence thus leading to insufficient global search.To overcome limitations,this research proposes a Differential Evolution-framed JAYA algorithm(DEJAYA).DEJAYA incorporates four key enhancements to improve the flexibility of the original algorithm,which include DE framework design,horizontal crossover operator,longitudinal crossover operator,and global greedy strategy.The effectiveness of DEJAYA is rigorously evaluated by a suite of 23 distinct benchmark functions.Furthermore,the numerical simulation establishes AlSi10Mg single-track formation models,and DEJAYA successfully identified the optimal process window for this problem.Experimental results validate that DEJAYA effectively guides SLM parameter selection for AlSi10Mg.
基金supported by the National Key Research and Development Program of China(2023YFF0612900,2023YFF0612902)the Natural Science Foundation of Beijing,China(4254086)+3 种基金the National Natural Science Foundation of China(62472032)the Open Project Funding of Key Laboratory of Mobile Application Innovation and Governance Technology,Ministry of Industry and Information Technology(2023IFS080601-K)the Beijing Institute of Technology Research Fund Program for Young Scholarsthe Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)。
文摘Dear Editor,This letter addresses the critical challenge of preserving privacy in graph learning without compromising on data utility.Differential privacy(DP)is emerging as an effective method for privacy-preserving graph learning.However,its application often diminishes data utility,especially for nodes with fewer neighbors in graph neural networks(GNNs).
基金supported in part by the National Natural Science Foundation of China(No.52467008)Gansu Provincial Depatment of Education Youth Doctoral Suppo Project(2024QB-051).
文摘Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.
基金Supported by the National Natural Science Foundation of China(11871260,11761050)the Jiangxi Natural Science Foundation(#20232ACB201005)+1 种基金the Shandong Natural Science Foundation(#ZR2024MA024)Doctoral Startup Fund of Jiangxi Science and Technology Normal University(#2021BSQD30).
文摘The main purpose of this paper is to try to find all entire solutions of the Fermat type difference-differential equation[p1(z)f(z+c)]^(2)+[p2(z)f(z)+p3(z)f′(z)]^(2)=p(z);or[p1(z)f(z)]^(2)+[p2(z)f′(z)+p3(z)f(z+c)]^(2)=p(z)or[p1(z)f′(z)]^(2)+[p2(z)f(z+c)+p3(z)f(z)]^(2)=p(z);where c is a nonzero complex number,p1;p2 and p3 are polynomials in C satisfying p1p3■0;and p is a nonzero irreducible polynomial in C.
文摘This paper presents an explicit difference scheme with accuracy and branching stability for solving onedimensional parabolic type equation by the method of undetermined parameters and its truncation error is O(△t4+△x4). The stability condition is r=a△t/△x2<1/2.
文摘A family of high_order accuracy explicit difference schemes for solving 2_dimension parabolic P.D.E. are constructed. Th e stability condition is r=Δt/Δx 2=Δt/Δy 2【1/2 and the truncation err or is O(Δt 3+Δx 4).
文摘In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant(No.51677058).
文摘Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.
基金Supported by the National Natural Science Foundation of China(Grant No.11661043)and the ScienceTechnology Research Project of Jiangxi Provincial Department of Education(Grant No.GJJ2200320).
文摘In this paper,the growth characteristic of meromorphic solutions for the following difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=0 with no dominating coefficient is studied.By imposing certain restriction on the entire coefficients associated with Petrenko's deviation of the above equation,we obtain some results and partially address a question posed byⅠ.Laine and C.C.Yang.Furthermore,for the entire solutions f(z)of the difference equation An(z)f(z+n)+…+A1(z)f(z+1)+A0(z)f(z)=F(z),where Aj(z)(j=0,…,n),F(z)are entire functions,we discover a close relationship between the measure of common transcendental directions associated with classical difference operators of f(z)and Petrenko's deviations of the coefficients.
基金supported by the National Natural Science Foundation of China(Grant No.42225104)CAS Project for Young Scientists in Basic Research(Grant No.YSBR-086).
文摘Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health planning and risk reduction.Most existing approaches rely on a single threshold temperature(e.g.,35℃of daily max temperature),applied uniformly to the entire population.However,this one-size-fits-all assumption overlooks substantial differences in heat sensitivity across population subgroups.In this study,we address this limitation by quantifying subgroup-specific temperature-mortality relationships and using corresponding minimum mortality temperatures(MMTs)to assess heat exposure.Results show that the population-wide MMT was 27.5℃,but it varied greatly across population subgroups.The elderly population(≥65)had an MMT of 24.6℃,much lower than the 28.6℃observed in younger individuals(<65).Females also exhibited a lower MMT that males(25℃versus 28.2℃).However,educational attainment did not significantly affect MMT.Using a uniform MMT resulted in substantial underestimation of heat exposure,ranging from 25.3%in 1990 to 13.9%in 2020,reflecting demographic shifts over time.Spatially,nearly half of the city experienced underestimated heat risk,especially in central and northeastern regions where heat-vulnerable populations are concentrated.These findings underscore the need for more nuanced heat exposure assessments that account for demographic and spatial variability,paving the way for targeted public health interventions to protect the most vulnerable urban populations.
文摘At the start of the new year,Cao Xiucheng,Chairman of Henan No.2 Textile Machinery Co.,Ltd.,was on his way to visit clients when he kept receiving urgent calls from the Xinyang production base regarding order scheduling.It turned out that since the end of 2025,the company had successively secured bulk spindle orders from overseas clients in Bangladesh and other countries,coupled with continuous urgent requests for orders from domestic manufacturers.Faced with such a production peak right at the beginning of the year,Mr.Cao Xiucheng admitted,“It was truly unexpected.”
