Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic...Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.展开更多
We incorporate a non-Markovian feedback mechanism into the simulated bifurcation method for dynamical solvers addressing combinatorial optimization problems.By reinjecting a portion of dissipated kinetic energy into e...We incorporate a non-Markovian feedback mechanism into the simulated bifurcation method for dynamical solvers addressing combinatorial optimization problems.By reinjecting a portion of dissipated kinetic energy into each spin in a history-dependent and trajectory-informed manner,the method effectively suppresses early freezing induced by inelastic boundaries and enhances the system's ability to explore complex energy landscapes.Numerical results on the maximum cut(MAX-CUT)instances of fully connected Sherrington–Kirkpatrick(SK)spin glass models,including the 2000-spin K_(2000)benchmark,demonstrate that the non-Markovian algorithm significantly improves both solution quality and convergence speed.Tests on randomly generated SK instances with 100 to 1000 spins further indicate favorable scalability and substantial gains in computational efficiency.Moreover,the proposed scheme is well suited for massively parallel hardware implementations,such as field-programmable gate arrays,providing a practical and scalable approach for solving large-scale combinatorial optimization problems.展开更多
The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu...The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remain...Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remains an urgent issue to be resolved for the commercialization.Defect passivation emerged as a viable approach to enhance the operational stability of the solar devices.Herein,phenylthiourea(PhTu)derivatives are selected as effective passivation agents to enhance the optoelectronic properties of printed methylammonium lead iodide(MAPbI_(3))films.It is demonstrated that incorporating a small amount of 1-(4-carboxyphenyl)-2-thiourea(PhTu-COOH)significantly reduces the trap-state density and leads to longer carrier lifetime of the perovskite films.As a result,the inverted solar device made of Ph Tu-COOH-modified MAPbI_(3) perovskite film shows remarkably improved efficiency(from 17.29%to 20.22%)and obviously increased open-circuit voltage(V_(OC))(from 1.043 to 1.143 V),as compared with the pristine device.Moreover,the Ph Tu-COOH-modified PSCs exhibit enhanced operational stability due to the significantly reduced trap-state density.Finally,the optimized solar module fabricated with an active area of 11.28 cm^(2) delivers a high PCE of 17.07%with negligible V_(OC)loss,demonstrating the feasibility of the blade-coating method for large-area perovskite film deposition.展开更多
Coal-derived hard carbon(HC)represents a promising anode material for sodium-ion batteries owing to its cost-effectiveness and high carbon yield.However,conventional carbonization induces excessive graphitization,yiel...Coal-derived hard carbon(HC)represents a promising anode material for sodium-ion batteries owing to its cost-effectiveness and high carbon yield.However,conventional carbonization induces excessive graphitization,yielding insufficient interlayer spacing(d_(002)<0.37 nm)and underdeveloped closed pores.Herein,we propose a dynamic crystallization control strategy through carbothermal shock treatment(1300°C,30 s)that decouples thermodynamic and kinetic constraints.This method precisely modulates graphite domain ordering kinetics,producing short-range ordered structures with expanded interlayer spacing(d_(002)=0.385 nm)and homogeneously distributed closed nanopores.Through combined in situ characterization and first-principles calculations,we elucidate a three-stage crystallization mechanism:(i)amorphous carbon transformation,(ii)open-pore collapse,and(iii)pseudo-graphitic ordering.The optimized HC achieves record performance with 88.6%initial Coulombic efficiency and 204 mA h g^(−1)plateau capacity,while its optimal interlayer spacing lowers Na+diffusion barriers to enable exceptional rate capability(221 mA h g^(−1)at 0.5C after 300 cycles).Practical pouch cells maintain 85%capacity retention after 100 cycles at−20°C and deliver 284 Wh kg^(−1)energy density.This work establishes a kinetic regulation paradigm for graphitization-prone precursors,advancing the rational design of high-performance HC anodes.展开更多
Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite...Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.展开更多
With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electro...With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electronic instruments.Therefore,the design and preparation of electromagnetic absorbing composites represent an efficient approach to mitigate the current hazards of electromagnetic radiation.However,traditional electromagnetic absorbers are difficult to satisfy the demands of actual utilization in the face of new challenges,and emerging absorbents have garnered increasing attention due to their structure and performance-based advantages.In this review,several emerging composites of Mxene-based,biochar-based,chiral,and heat-resisting are discussed in detail,including their synthetic strategy,structural superiority and regulation method,and final optimization of electromagnetic absorption ca-pacity.These insights provide a comprehensive reference for the future development of new-generation electromagnetic-wave absorption composites.Moreover,the potential development directions of these emerging absorbers have been proposed as well.展开更多
The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness dimin...The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness diminishes in few-shot reasoning scenarios due to the low data efficiency of conventional supervised fine-tuning,which leads to excessive communication overhead.To address this,we propose Language-Empowered Split Fine-Tuning(LESFT),a framework that integrates split architectures with a contrastive-inspired fine-tuning paradigm.LESFT simultaneously learns frommultiple logically equivalent but linguistically diverse reasoning chains,providing richer supervisory signals and improving data efficiency.This process-oriented training allows more effective reasoning adaptation with fewer samples.Extensive experiments demonstrate that LESFT consistently outperforms strong baselines such as SplitLoRA in task accuracy.LESFT consistently outperforms strong baselines on GSM8K,CommonsenseQA,and AQUA_RAT,with the largest gains observed on Qwen2.5-3B.These results indicate that LESFT can effectively adapt large language models for reasoning tasks under the computational and communication constraints of edge environments.展开更多
In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In additi...In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.展开更多
Primordial germ cells(PGCs)are the stem-cell population of adult animal gametes,which develop into sperm or eggs.It can be propagated in vitro and injected into the host chicken for genome editing to obtain germline c...Primordial germ cells(PGCs)are the stem-cell population of adult animal gametes,which develop into sperm or eggs.It can be propagated in vitro and injected into the host chicken for genome editing to obtain germline chimeric chicken.However,it has the limitation that the host embryo contains endogenous PGCs,which raises complications,resultantly donor PGCs fail to compete,and transmission efficiency reduced.Therefore,to increase the transmission efficiency,we generated a novel sterile chicken with the inducible elimination of endogenous PGCs in the host.This is the first study that applied the herpes simplex virus thymidine kinase(HSV-TK)cell ablation system in avian.CRISPR/Cas9-mediated homology-directed repair was performed to localize the HSV-TK suicide gene to the last exon of the deleted in azoospermialike(DAZL)gene,and ganciclovir(GCV)was added to induce the apoptosis in the germ cells of the host embryo.The sterilized host embryo introduced genome-edited PGCs to produce chimeric chicken carrying exogenous germ cells only.It was observed that the germline transmission efficiency was 100%achieved,and the obtained chicks were purely from donor breeds.The technologies established in the current study have important applications in germplasm conservation and gene editing in chicken.展开更多
Rapidly improving infertile croplands and enhancing their soil organic carbon(SOC)pool necessitate substantial organic materials incorporation.Converting loose crop straw into granulated form facilitates uniform incor...Rapidly improving infertile croplands and enhancing their soil organic carbon(SOC)pool necessitate substantial organic materials incorporation.Converting loose crop straw into granulated form facilitates uniform incorporation within the plough soil layer.As an innovative soil amelioration approach,the efficiency and patterns of SOC accumulation remain unclear.Two field experiments were conducted in infertile subtropical upland and paddy soils with 0,30,60,and 90 Mg ha^(-1)granulated straw incorporation.After one year,SOC accumulation efficiency from straw input remained stable in upland(30.8–37.5%)with increasing amounts of straw incorporation,while declined from 60.0 to 38.3%in paddy.In both croplands,the contributions of lignin phenols to SOC increased with increasing straw incorporation,while the contributions from amino sugars remained constant at higher straw input levels.Subsequently,the ratios of lignin phenols to amino sugars increased with increasing straw incorporation,indicating faster plant residue accumulation compared to microbial necromass,as the granulation approach limited microbial involvement in straw transformation.Thus,single-time incorporation of substantial granulated straw presents an effective agricultural strategy for rapid amelioration of infertile croplands.展开更多
In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical propert...In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks.展开更多
Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different e...Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different edge devices varies significantly.As a result,communication overhead increases,which further slows down the convergence process.To address this challenge,we propose a simple yet effective federated learning framework that improves consistency among edge devices.The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates.In parallel,a global momentum is applied during model aggregation,enabling faster convergence while preserving personalization.This strategy enables efficient propagation of the estimated global update direction to all participating edge devices and maintains alignment in local training,without introducing extra memory or communication overhead.We conduct extensive experiments on benchmark datasets such as Cifar100 and Tiny-ImageNet.The results confirm the effectiveness of our framework.On CIFAR-100,our method reaches 55%accuracy with 37 fewer rounds and achieves a competitive final accuracy of 65.46%.Even under extreme non-IID scenarios,it delivers significant improvements in both accuracy and communication efficiency.The implementation is publicly available at https://github.com/sjmp525/CollaborativeComputing/tree/FedCCM(accessed on 20 October 2025).展开更多
In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhausti...In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle(ORC)systems forwaste heat recovery fromdiesel engines.Thestudy assessed the performance of five candidateworking fluids—R11,R123,R113,R245fa,and R141b—under a range of operating conditions,specifically varying overheat temperatures and evaporation pressures.The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency,net output power,and thermal efficiency.R245fa showed an outstanding net output power of 30.39 kW at high overheat conditions,outperforming R11,which is significant for high-temperature waste heat recovery.At lower temperatures,R11 and R113 demonstrated higher exergetic efficiencies,with R11 reaching a peak exergetic efficiency of 7.4%at an evaporation pressure of 10 bar and an overheat of 10℃.The study also revealed that controlling the overheat and optimizing the evaporation pressure are crucial for enhancing the net output power of the ORC system.Specifically,at an evaporation pressure of 30 bar and an overheat of 0℃,R113 exhibited the lowest exergetic destruction of 544.5 kJ/kg,making it a suitable choice for minimizing irreversible losses.These findings are instrumental for understanding the performance of ORC systems in waste heat recovery applications and offer valuable insights for the design and operation of more efficient and environmentally friendly diesel engine systems.展开更多
Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting d...Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting density and N rate,and their relationships with grain yield,radiation use efficiency(RUE),and N use efficiency for grain production(NUEg)in rice.A two-year field experiment was conducted with two hybrid varieties under three N levels,0 kg ha^(-1)(N1),90 kg ha^(-1)(N2)and 180 kg ha^(-1)(N3),and two planting densities,22.2 hills m-2(D1)and 33.3 hills m^(-2)(D2).Results showed 3.4%higher yield and 4.4%higher NUEg under N2D2 compared with N3D1.The extinction coefficient for N(K_(N))and light(K_(L))and their ratio(K_(N)/K_(L))at heading stage were significantly influenced by N rate,planting density,and their interaction.K_(N)decreased with the increase of N input or planting density.Compared to N1,K_(N)decreased by 43.5 and 58.8%under N2 and N3,respectively,while K_(N)under D2 decreased by 16.0%compared to D1.Higher K_(L)and K_(N)/K_(L)values occurred under low N rates,with opposite trends under high N rates.Increased planting density led to decreased K_(L)and K_(N)/K_(L)values.N2D2 demonstrated higher K_(L)and K_(N),and thus comparable K_(N)/K_(L),compared to N3D1.Correlation analysis revealed K_(L)negatively correlated with RUE,while K_(N)and K_(N)/K_(L)positively correlated with NUEg.These findings indicate that increasing planting density under reduced N input could maintain rice yield while enhancing resource use efficiency through regulation of canopy light and N distribution.展开更多
Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic effici...Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.展开更多
Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are o...Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are often effective for stabilization but may not directly optimize long-term performance.To address this limitation,this study develops an integrated framework that combines optimal control principles with reinforcement learning for a single-link robotic manipulator.The proposed scheme adopts an actor–critic structure,where the critic network approximates the value function associated with the Hamilton–Jacobi–Bellman equation,and the actor network generates near-optimal control signals in real time.This dual adaptation enables the controller to refine its policy online without explicit system knowledge.Stability of the closed-loop system is analyzed through Lyapunov theory,ensuring boundedness of the tracking error.Numerical simulations on the single-link manipulator demonstrate that themethod achieves accurate trajectory followingwhile maintaining lowcontrol effort.The results further showthat the actor–critic learning mechanism accelerates convergence of the control policy compared with conventional optimization-based strategies.This work highlights the potential of reinforcement learning integrated with optimal control for robotic manipulators and provides a foundation for future extensions to more complex multi-degree-of-freedom systems.The proposed controller is further validated in a physics-based virtual Gazebo environment,demonstrating stable adaptation and real-time feasibility.展开更多
In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a ...In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.展开更多
This paper investigates the edge-based dynamic event-triggered inverse optimal formation control problem for multiple quadrotor unmanned aerial vehicles(QUAVs) with attitude constraints. To improve communication effic...This paper investigates the edge-based dynamic event-triggered inverse optimal formation control problem for multiple quadrotor unmanned aerial vehicles(QUAVs) with attitude constraints. To improve communication efficiency, an edge-based dynamic event-triggered mechanism is developed for the communication channels between neighboring QUAVs. However, this edge-based dynamic event-triggered communication(DETC) may cause discontinuities in the reference signals. To solve this problem, a distributed estimator is designed for each QUAV to obtain the leader's output signals. Considering the safety of QUAV formation flying, this paper designs a function transformation method that constrains the attitudes of the QUAVs to a strictly safe region. Furthermore, an inverse optimal control strategy is proposed based on the backstepping methodology. This scheme not only minimizes the cost function but also avoids the necessity of solving the Hamilton-Jacobi-Bellman equation. Finally, the stability of the QUAV systems is proven using Lyapunov theory, and the effectiveness of the proposed control method is verified through simulation.展开更多
基金funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-01264).
文摘Automated essay scoring(AES)systems have gained significant importance in educational settings,offering a scalable,efficient,and objective method for evaluating student essays.However,developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology,diglossia,and the scarcity of annotated datasets.This paper presents a hybrid approach to Arabic AES by combining text-based,vector-based,and embeddingbased similarity measures to improve essay scoring accuracy while minimizing the training data required.Using a large Arabic essay dataset categorized into thematic groups,the study conducted four experiments to evaluate the impact of feature selection,data size,and model performance.Experiment 1 established a baseline using a non-machine learning approach,selecting top-N correlated features to predict essay scores.The subsequent experiments employed 5-fold cross-validation.Experiment 2 showed that combining embedding-based,text-based,and vector-based features in a Random Forest(RF)model achieved an R2 of 88.92%and an accuracy of 83.3%within a 0.5-point tolerance.Experiment 3 further refined the feature selection process,demonstrating that 19 correlated features yielded optimal results,improving R2 to 88.95%.In Experiment 4,an optimal data efficiency training approach was introduced,where training data portions increased from 5%to 50%.The study found that using just 10%of the data achieved near-peak performance,with an R2 of 85.49%,emphasizing an effective trade-off between performance and computational costs.These findings highlight the potential of the hybrid approach for developing scalable Arabic AES systems,especially in low-resource environments,addressing linguistic challenges while ensuring efficient data usage.
基金supported by the National Key Research and Development Program of China(Grant No.2024YFA1408500)the National Natural Science Foundation of China(Grant Nos.12174028 and 12574115)the Open Fund of the State Key Laboratory of Spintronics Devices and Technologies(Grant No.SPL-2408)。
文摘We incorporate a non-Markovian feedback mechanism into the simulated bifurcation method for dynamical solvers addressing combinatorial optimization problems.By reinjecting a portion of dissipated kinetic energy into each spin in a history-dependent and trajectory-informed manner,the method effectively suppresses early freezing induced by inelastic boundaries and enhances the system's ability to explore complex energy landscapes.Numerical results on the maximum cut(MAX-CUT)instances of fully connected Sherrington–Kirkpatrick(SK)spin glass models,including the 2000-spin K_(2000)benchmark,demonstrate that the non-Markovian algorithm significantly improves both solution quality and convergence speed.Tests on randomly generated SK instances with 100 to 1000 spins further indicate favorable scalability and substantial gains in computational efficiency.Moreover,the proposed scheme is well suited for massively parallel hardware implementations,such as field-programmable gate arrays,providing a practical and scalable approach for solving large-scale combinatorial optimization problems.
文摘The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant No.62205103)the Natural Science Foundation of Hunan Province(Grant No.2023JJ40216)the Elite Youth Program by the Department of Education of Hunan Province(Grant No.24B0663)。
文摘Although the certified power conversion efficiency(PCE)of single-junction perovskite solar cells(PSCs)has achieved a high level of 27%,approaching the single-crystalline silicon solar cells,the device stability remains an urgent issue to be resolved for the commercialization.Defect passivation emerged as a viable approach to enhance the operational stability of the solar devices.Herein,phenylthiourea(PhTu)derivatives are selected as effective passivation agents to enhance the optoelectronic properties of printed methylammonium lead iodide(MAPbI_(3))films.It is demonstrated that incorporating a small amount of 1-(4-carboxyphenyl)-2-thiourea(PhTu-COOH)significantly reduces the trap-state density and leads to longer carrier lifetime of the perovskite films.As a result,the inverted solar device made of Ph Tu-COOH-modified MAPbI_(3) perovskite film shows remarkably improved efficiency(from 17.29%to 20.22%)and obviously increased open-circuit voltage(V_(OC))(from 1.043 to 1.143 V),as compared with the pristine device.Moreover,the Ph Tu-COOH-modified PSCs exhibit enhanced operational stability due to the significantly reduced trap-state density.Finally,the optimized solar module fabricated with an active area of 11.28 cm^(2) delivers a high PCE of 17.07%with negligible V_(OC)loss,demonstrating the feasibility of the blade-coating method for large-area perovskite film deposition.
基金supported by the Key Laboratory of Sichuan Province for Lithium Resources Comprehensive Utilization and New Lithium Based Materials for Advanced Battery Technology(LRMKF202405)the National Natural Science Foundation of China(52402226)the Natural Science Foundation of Sichuan Province(2024NSFSC1016).
文摘Coal-derived hard carbon(HC)represents a promising anode material for sodium-ion batteries owing to its cost-effectiveness and high carbon yield.However,conventional carbonization induces excessive graphitization,yielding insufficient interlayer spacing(d_(002)<0.37 nm)and underdeveloped closed pores.Herein,we propose a dynamic crystallization control strategy through carbothermal shock treatment(1300°C,30 s)that decouples thermodynamic and kinetic constraints.This method precisely modulates graphite domain ordering kinetics,producing short-range ordered structures with expanded interlayer spacing(d_(002)=0.385 nm)and homogeneously distributed closed nanopores.Through combined in situ characterization and first-principles calculations,we elucidate a three-stage crystallization mechanism:(i)amorphous carbon transformation,(ii)open-pore collapse,and(iii)pseudo-graphitic ordering.The optimized HC achieves record performance with 88.6%initial Coulombic efficiency and 204 mA h g^(−1)plateau capacity,while its optimal interlayer spacing lowers Na+diffusion barriers to enable exceptional rate capability(221 mA h g^(−1)at 0.5C after 300 cycles).Practical pouch cells maintain 85%capacity retention after 100 cycles at−20°C and deliver 284 Wh kg^(−1)energy density.This work establishes a kinetic regulation paradigm for graphitization-prone precursors,advancing the rational design of high-performance HC anodes.
基金supported in part by the National Natural Science Foundation of China under Grants 62025110,62271093sponsored by Natural Science Foundation of Chongqing,China,under Grant CSTB2023NSCQ-LZX0108.
文摘Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.
基金supported by the Surface Project of Local De-velopment in Science and Technology Guided by Central Govern-ment(No.2021ZYD0041)the National Natural Science Founda-tion of China(Nos.52377026 and 52301192)+3 种基金the Natural Science Foundation of Shandong Province(No.ZR2019YQ24)the Taishan Scholars and Young Experts Program of Shandong Province(No.tsqn202103057)the Special Financial of Shandong Province(Struc-tural Design of High-efficiency Electromagnetic Wave-absorbing Composite Materials and Construction of Shandong Provincial Tal-ent Teams)the“Sanqin Scholars”Innovation Teams Project of Shaanxi Province(Clean Energy Materials and High-Performance Devices Innovation Team of Shaanxi Dongling Smelting Co.,Ltd.).
文摘With the increasing complexity of the current electromagnetic environment,excessive microwave radi-ation not only does harm to human health but also forms various electromagnetic interference to so-phisticated electronic instruments.Therefore,the design and preparation of electromagnetic absorbing composites represent an efficient approach to mitigate the current hazards of electromagnetic radiation.However,traditional electromagnetic absorbers are difficult to satisfy the demands of actual utilization in the face of new challenges,and emerging absorbents have garnered increasing attention due to their structure and performance-based advantages.In this review,several emerging composites of Mxene-based,biochar-based,chiral,and heat-resisting are discussed in detail,including their synthetic strategy,structural superiority and regulation method,and final optimization of electromagnetic absorption ca-pacity.These insights provide a comprehensive reference for the future development of new-generation electromagnetic-wave absorption composites.Moreover,the potential development directions of these emerging absorbers have been proposed as well.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant 62276109The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through the Research Group Project number(ORF-2025-585).
文摘The personalized fine-tuning of large languagemodels(LLMs)on edge devices is severely constrained by limited computation resources.Although split federated learning alleviates on-device burdens,its effectiveness diminishes in few-shot reasoning scenarios due to the low data efficiency of conventional supervised fine-tuning,which leads to excessive communication overhead.To address this,we propose Language-Empowered Split Fine-Tuning(LESFT),a framework that integrates split architectures with a contrastive-inspired fine-tuning paradigm.LESFT simultaneously learns frommultiple logically equivalent but linguistically diverse reasoning chains,providing richer supervisory signals and improving data efficiency.This process-oriented training allows more effective reasoning adaptation with fewer samples.Extensive experiments demonstrate that LESFT consistently outperforms strong baselines such as SplitLoRA in task accuracy.LESFT consistently outperforms strong baselines on GSM8K,CommonsenseQA,and AQUA_RAT,with the largest gains observed on Qwen2.5-3B.These results indicate that LESFT can effectively adapt large language models for reasoning tasks under the computational and communication constraints of edge environments.
基金supported by the 2024 Research Fund of University of Ulsan.
文摘In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.
基金supported by the National Key R&D Program of China(2021YFD1300100)Guangxi Key R&D Program,China(AB21220005)+1 种基金Reproductive Medicine,Guangxi Medical and Health Key Discipline Construction Project of the Affiliated Hospitalthe National Natural Science Foundation of China(32360180)。
文摘Primordial germ cells(PGCs)are the stem-cell population of adult animal gametes,which develop into sperm or eggs.It can be propagated in vitro and injected into the host chicken for genome editing to obtain germline chimeric chicken.However,it has the limitation that the host embryo contains endogenous PGCs,which raises complications,resultantly donor PGCs fail to compete,and transmission efficiency reduced.Therefore,to increase the transmission efficiency,we generated a novel sterile chicken with the inducible elimination of endogenous PGCs in the host.This is the first study that applied the herpes simplex virus thymidine kinase(HSV-TK)cell ablation system in avian.CRISPR/Cas9-mediated homology-directed repair was performed to localize the HSV-TK suicide gene to the last exon of the deleted in azoospermialike(DAZL)gene,and ganciclovir(GCV)was added to induce the apoptosis in the germ cells of the host embryo.The sterilized host embryo introduced genome-edited PGCs to produce chimeric chicken carrying exogenous germ cells only.It was observed that the germline transmission efficiency was 100%achieved,and the obtained chicks were purely from donor breeds.The technologies established in the current study have important applications in germplasm conservation and gene editing in chicken.
基金financially supported by the National Key R&D Program of China(2021YFD1901203 and 2021YFD1901204)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA0440404)+2 种基金the National Natural Science Foundation of China(42377348)the Science Foundation for Distinguished Young Scholars of Hunan Province,China(2024JJ2052)the Natural Science Foundation of Guangxi,China(2025GXNSFAA069337)。
文摘Rapidly improving infertile croplands and enhancing their soil organic carbon(SOC)pool necessitate substantial organic materials incorporation.Converting loose crop straw into granulated form facilitates uniform incorporation within the plough soil layer.As an innovative soil amelioration approach,the efficiency and patterns of SOC accumulation remain unclear.Two field experiments were conducted in infertile subtropical upland and paddy soils with 0,30,60,and 90 Mg ha^(-1)granulated straw incorporation.After one year,SOC accumulation efficiency from straw input remained stable in upland(30.8–37.5%)with increasing amounts of straw incorporation,while declined from 60.0 to 38.3%in paddy.In both croplands,the contributions of lignin phenols to SOC increased with increasing straw incorporation,while the contributions from amino sugars remained constant at higher straw input levels.Subsequently,the ratios of lignin phenols to amino sugars increased with increasing straw incorporation,indicating faster plant residue accumulation compared to microbial necromass,as the granulation approach limited microbial involvement in straw transformation.Thus,single-time incorporation of substantial granulated straw presents an effective agricultural strategy for rapid amelioration of infertile croplands.
基金support from the National Natural Science Foundation of China(Grant Nos.42277161 and 42230709).
文摘In rock engineering,natural cracks in rock masses subjected to external loads tend to initiate and propagate,leading to potential safety hazards.To investigate the effect of cracking behavior on the mechanical properties of rocks,the cracking processes of pre-cracked rocks have been extensively studied using numerical modeling methods.The peridynamics(PD)exhibits advantages over other numerical methods due to the absence of the requirements for remeshing and external crack growth criterion.However,for modeling pre-cracked rock cracking processes under impact,current PD implementations lack generally applicable rock constitutive models and impact contact models,which leads to difficulties in determining rock material parameters and efficiently calculating impact loads.This paper proposes a non-ordinary state-based peridynamics(NOSBPD)modeling method integrating the Drucker-Prager(DP)plasticity model and an efficient contact model to address the above problems.In the proposed method,the Drucker-Prager plasticity model is integrated into the NOSBPD,thereby equipping NOSBPD with the capability to accurately characterize the nonlinear stress-strain relationship inherent in rocks.An efficient contact model between particles and meshes is designed to calculate the impact loads,which is essentially a coupling method of PD with the finite element method(FEM).The effectiveness of the proposed NOSBPD modeling method is verified by comparison with other numerical methods and experiments.Experimental results indicate that the proposed method can effectively and accurately predict the 3D cracking processes of pre-cracked cracks under impact loading,and the maximum principal stress is the key driver behind wing crack formation in pre-cracked rocks.
基金supported by the National Natural Science Foundation of China(62462040)the Yunnan Fundamental Research Projects(202501AT070345)the Major Science and Technology Projects in Yunnan Province(202202AD080013).
文摘Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different edge devices varies significantly.As a result,communication overhead increases,which further slows down the convergence process.To address this challenge,we propose a simple yet effective federated learning framework that improves consistency among edge devices.The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates.In parallel,a global momentum is applied during model aggregation,enabling faster convergence while preserving personalization.This strategy enables efficient propagation of the estimated global update direction to all participating edge devices and maintains alignment in local training,without introducing extra memory or communication overhead.We conduct extensive experiments on benchmark datasets such as Cifar100 and Tiny-ImageNet.The results confirm the effectiveness of our framework.On CIFAR-100,our method reaches 55%accuracy with 37 fewer rounds and achieves a competitive final accuracy of 65.46%.Even under extreme non-IID scenarios,it delivers significant improvements in both accuracy and communication efficiency.The implementation is publicly available at https://github.com/sjmp525/CollaborativeComputing/tree/FedCCM(accessed on 20 October 2025).
基金funded by the Huaiyin Institute of Technology—Institute of Smart Energy.
文摘In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle(ORC)systems forwaste heat recovery fromdiesel engines.Thestudy assessed the performance of five candidateworking fluids—R11,R123,R113,R245fa,and R141b—under a range of operating conditions,specifically varying overheat temperatures and evaporation pressures.The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency,net output power,and thermal efficiency.R245fa showed an outstanding net output power of 30.39 kW at high overheat conditions,outperforming R11,which is significant for high-temperature waste heat recovery.At lower temperatures,R11 and R113 demonstrated higher exergetic efficiencies,with R11 reaching a peak exergetic efficiency of 7.4%at an evaporation pressure of 10 bar and an overheat of 10℃.The study also revealed that controlling the overheat and optimizing the evaporation pressure are crucial for enhancing the net output power of the ORC system.Specifically,at an evaporation pressure of 30 bar and an overheat of 0℃,R113 exhibited the lowest exergetic destruction of 544.5 kJ/kg,making it a suitable choice for minimizing irreversible losses.These findings are instrumental for understanding the performance of ORC systems in waste heat recovery applications and offer valuable insights for the design and operation of more efficient and environmentally friendly diesel engine systems.
基金supported by the Hubei Provincial Science and Technology Project,China(2025CSA039)the National Natural Science Foundation of China(32001467)。
文摘Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting density and N rate,and their relationships with grain yield,radiation use efficiency(RUE),and N use efficiency for grain production(NUEg)in rice.A two-year field experiment was conducted with two hybrid varieties under three N levels,0 kg ha^(-1)(N1),90 kg ha^(-1)(N2)and 180 kg ha^(-1)(N3),and two planting densities,22.2 hills m-2(D1)and 33.3 hills m^(-2)(D2).Results showed 3.4%higher yield and 4.4%higher NUEg under N2D2 compared with N3D1.The extinction coefficient for N(K_(N))and light(K_(L))and their ratio(K_(N)/K_(L))at heading stage were significantly influenced by N rate,planting density,and their interaction.K_(N)decreased with the increase of N input or planting density.Compared to N1,K_(N)decreased by 43.5 and 58.8%under N2 and N3,respectively,while K_(N)under D2 decreased by 16.0%compared to D1.Higher K_(L)and K_(N)/K_(L)values occurred under low N rates,with opposite trends under high N rates.Increased planting density led to decreased K_(L)and K_(N)/K_(L)values.N2D2 demonstrated higher K_(L)and K_(N),and thus comparable K_(N)/K_(L),compared to N3D1.Correlation analysis revealed K_(L)negatively correlated with RUE,while K_(N)and K_(N)/K_(L)positively correlated with NUEg.These findings indicate that increasing planting density under reduced N input could maintain rice yield while enhancing resource use efficiency through regulation of canopy light and N distribution.
基金funded by the Department of Education of Liaoning Province and was supported by the Basic Scientific Research Project of the Department of Education of Liaoning Province(Grant No.LJ222411632051)and(Grant No.LJKQZ2021085)Natural Science Foundation Project of Liaoning Province(Grant No.2022-BS-222).
文摘Virtual power plant(VPP)integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions,promote the consumption of renewable energy,and improve economic efficiency.In this paper,aiming at the uncertainty of distributed wind power and photovoltaic output,considering the coupling relationship between power,carbon trading,and green cardmarket,the optimal operationmodel and bidding scheme of VPP in spot market,carbon trading market,and green card market are established.On this basis,through the Shapley value and independent risk contribution theory in cooperative game theory,the quantitative analysis of the total income and risk contribution of various distributed resources in the virtual power plant is realized.Moreover,the scheduling strategies of virtual power plants under different risk preferences are systematically compared,and the feasibility and accuracy of the combination of Shapley value and independent risk contribution theory in ensuring fair income distribution and reasonable risk assessment are emphasized.A comprehensive solution for virtual power plants in the multi-market environment is constructed,which integrates operation strategy,income distribution mechanism,and risk control system into a unified analysis framework.Through the simulation of multi-scenario examples,the CPLEXsolver inMATLAB software is used to optimize themodel.The proposed joint optimization scheme can increase the profit of VPP participating in carbon trading and green certificate market by 29%.The total revenue of distributed resources managed by VPP is 9%higher than that of individual participation.
基金supported in part by the National Science and Technology Council under Grant NSTC 114-2221-E-027-104.
文摘Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering,particularly when both precision and efficiency must be ensured.Conventional control methods are often effective for stabilization but may not directly optimize long-term performance.To address this limitation,this study develops an integrated framework that combines optimal control principles with reinforcement learning for a single-link robotic manipulator.The proposed scheme adopts an actor–critic structure,where the critic network approximates the value function associated with the Hamilton–Jacobi–Bellman equation,and the actor network generates near-optimal control signals in real time.This dual adaptation enables the controller to refine its policy online without explicit system knowledge.Stability of the closed-loop system is analyzed through Lyapunov theory,ensuring boundedness of the tracking error.Numerical simulations on the single-link manipulator demonstrate that themethod achieves accurate trajectory followingwhile maintaining lowcontrol effort.The results further showthat the actor–critic learning mechanism accelerates convergence of the control policy compared with conventional optimization-based strategies.This work highlights the potential of reinforcement learning integrated with optimal control for robotic manipulators and provides a foundation for future extensions to more complex multi-degree-of-freedom systems.The proposed controller is further validated in a physics-based virtual Gazebo environment,demonstrating stable adaptation and real-time feasibility.
基金supported by the National Natural Science Foundation of China under Grant 62472264the Natural Science Distinguished Youth Foundation of Shandong Province under Grant ZR2025QA13。
文摘In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.
基金supported by the National Natural Science Foundation of China (Grant Nos.62573134,62473100,62433018)the Guangdong Basic and Applied Basic Research Foundation(Grant Nos.2025A1515060017,2025A1515011436,2025B1515020065,2025A1515011789)the Guangzhou Basic and Applied Basic Research Project (Grant No.2025A04J3534)。
文摘This paper investigates the edge-based dynamic event-triggered inverse optimal formation control problem for multiple quadrotor unmanned aerial vehicles(QUAVs) with attitude constraints. To improve communication efficiency, an edge-based dynamic event-triggered mechanism is developed for the communication channels between neighboring QUAVs. However, this edge-based dynamic event-triggered communication(DETC) may cause discontinuities in the reference signals. To solve this problem, a distributed estimator is designed for each QUAV to obtain the leader's output signals. Considering the safety of QUAV formation flying, this paper designs a function transformation method that constrains the attitudes of the QUAVs to a strictly safe region. Furthermore, an inverse optimal control strategy is proposed based on the backstepping methodology. This scheme not only minimizes the cost function but also avoids the necessity of solving the Hamilton-Jacobi-Bellman equation. Finally, the stability of the QUAV systems is proven using Lyapunov theory, and the effectiveness of the proposed control method is verified through simulation.
