App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While t...App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.展开更多
In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimizatio...In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.展开更多
Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,th...Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm.The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control.Then,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy.Precise pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid voltage.Additionally,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee algorithm.These operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load transients.This strategy effectively mitigated transient voltage and current surges during mode transitions.Consequently,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid inverter.The enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability.展开更多
Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longe...Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.展开更多
The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,...The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.展开更多
In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law t...In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law that brings the output voltage to the desired level. Due to infinite switching occurring at the desired level, we enhanced the switching control law by allowing a sizeable output voltage ripple. We derived mathematical models that allow one to choose the desired switching frequency. In practice, the existence of the non-ideal properties of the Zeta converter results in steady-state output voltage error. By analyzing the power loss in the zeta converter, we proposed an improved switching control law that eliminates the steady-state output voltage error. The effectiveness of the proposed method is illustrated with simulation results.展开更多
Nitrogen (N) is a crucial nutrient vital for the growth and productivity of maize. However, excessive nitrogen application can result in numerous environmental and ecological problems, such as water pollution, biodive...Nitrogen (N) is a crucial nutrient vital for the growth and productivity of maize. However, excessive nitrogen application can result in numerous environmental and ecological problems, such as water pollution, biodiversity loss, and greenhouse gas emissions. Therefore, breeding maize hybrids resilient to low nitrogen conditions is crucial for sustainable agriculture, especially under low nitrogen conditions. Consequently, this study aimed to evaluate the combining ability and heterosis of maize lines, recognize promising hybrids, and study gene action controlling key traits under low and recommended N stress conditions. The half-diallel mating design hybridized seven maize inbreds, resulting in 21 F1 hybrids. These hybrids, along with two high-yielding commercial hybrids (SC10 and TWC310), were evaluated in field trials under recommended (290 kg/ha) and low N (166 kg N/ha) conditions. Significant variations were observed among assessed hybrids for all measured traits, with non-additive gene action being predominant for grain yield and its related characteristics under recommended and low N conditions. Inbred lines P105 and P106 were recognized as effective combiners for earliness, with P105 also excelling in shorter plant height and lower ear placement. In addition, P101, P102, and P104 were identified as good combiners for increasing grain yield and related attributes under low N conditions. The crosses P105 × P106 and P106 × P107 demonstrated outstanding heterotic effects for earliness, while hybrids P101 × P102 and P102 × P104 exhibited remarkable heterotic effects for grain yield low nitrogen stress conditions. These promising hybrids could be considered for commercial use after further evaluation. Strong positive correlations were found between grain yield and ear height, plant height, number of kernels per row, and 1000-grain weight, highlighting their importance for indirect selection to enhance the grain yield of maize under low N stress conditions.展开更多
Hybrid entangled states(HESs),which involve different particles with various degrees of freedom,have garnered significant attention and been applied in a wide range of quantum technologies.However,similar to other cat...Hybrid entangled states(HESs),which involve different particles with various degrees of freedom,have garnered significant attention and been applied in a wide range of quantum technologies.However,similar to other categories of entanglement,maximally HESs inevitably degrade to mixed states due to the environmental noise and operational imperfections.To address the degradation problem,measurement-based entanglement purification offers a feasible and robust solution alternative to conventional gate-based purification methods.In this paper,we propose a measurement-based hybrid entanglement purification protocol(MB-HEPP)for a certain kind of HES which consists of polarization photons and coherent states.We extend our methodology to several conditions,such as the multi-copy and multi-party scenarios,and the photon-loss condition.Compared with previous HEPPs,this protocol has several advantages.First,it does not depend on post-selection and the purified HESs can be retained for further application.Second,it does not require the Bell state measurement,but only uses the parity check with conventional linear optical elements,which makes it have the higher success probability and more feasible.Our MB-HEPP has potential applications in future heterogeneous quantum networks.展开更多
Existing chaotic encryption schemes primarily focus on single types of images,making the design of hybrid image encryption schemes more suitable for practical applications.In this paper,a hyperchaotic map with a spher...Existing chaotic encryption schemes primarily focus on single types of images,making the design of hybrid image encryption schemes more suitable for practical applications.In this paper,a hyperchaotic map with a spherical attractor is proposed,which is constructed using spherical coordinates.Dynamical analyses reveal that the hyperchaotic map exhibits global hyperchaos and high complexity,making it capable of generating more complex chaotic sequences suitable for image encryption.A hybrid encryption scheme based on a hyperchaotic map is proposed for two-dimensional(2D)images,three-dimensional(3D)models,and 3D point clouds.Firstly,the pixels of 2D image and the coordinate data of 3D image are fused into a plaintext cube,which is combined with Hash-512 to obtain the initial value of the hyperchaotic map.Chaotic sequences are utilized for cube space internal confusion and dynamic cross-diffusion.The encrypted images demonstrate high information entropy,and the test results show that the encryption scheme effectively protects the images.The proposed hybrid image encryption scheme provides an efficient solution for securing various types of images.展开更多
Within the SILVARSTAR project,a user-friendly frequency-based hybrid prediction tool has been developed to assess the environmental impact of railway-induced vibration.This tool is integrated in existing noise mapping...Within the SILVARSTAR project,a user-friendly frequency-based hybrid prediction tool has been developed to assess the environmental impact of railway-induced vibration.This tool is integrated in existing noise mapping software.Following modern vibration standards and guidelines,the vibration velocity level in a building in each frequency band is expressed as the sum of a force density(source term),line source transfer mobility(propagation term)and building correction factor(receiver term).A hybrid approach is used that allows for a combination of experimental data and numerical predictions,providing increased flexibility and applicability.The train and track properties can be selected from a database or entered as numerical values.The user can select soil impedance and transfer functions from a database,pre-computed for a wide range of parameters with state-of-the-art models.An experimental database of force densities,transfer functions,free field vibration and input parameters is also provided.The building response is estimated by means of building correction factors.Assumptions within the modelling approach are made to reduce computation time but these can influence prediction accuracy;this is quantified for the case of a nominal intercity train running at different speeds on a ballasted track supported by homogeneous soil of varying stiffness.The paper focuses on the influence of these parameters on the compliance of the track–soil system and the free field response.We also demonstrate the use and discuss the validation of the vibration prediction tool for the case of a high-speed train running on a ballasted track in Lincent(Belgium).展开更多
The deepwater subsea wellhead(SW)system is the foundation for the construction of oil and gas wells and the crucial channel for operation.During riser connection operation,the SW system is subjected to cyclic dynamic ...The deepwater subsea wellhead(SW)system is the foundation for the construction of oil and gas wells and the crucial channel for operation.During riser connection operation,the SW system is subjected to cyclic dynamic loads which cause fatigue damage to the SW system,and continuously accumulated fatigue damage leads to fatigue failure of the SW system,rupture,and even blowout accidents.This paper proposes a hybrid Bayesian network(HBN)-based dynamic reliability assessment approach for deepwater SW systems during their service life.In the proposed approach,the relationship between the accumulation of fatigue damage and the fatigue failure probability of the SW system is predicted,only considering normal conditions.The HBN model,which includes the accumulation of fatigue damage under normal conditions and the other factors affecting the fatigue of the SW system,is subsequently developed.When predictive and diagnostic analysis techniques are adopted,the dynamic reliability of the SW system is achieved,and the most influential factors are determined.Finally,corresponding safety control measures are proposed to improve the reliability of the SW system effectively.The results illustrate that the fatigue failure speed increases rapidly when the accumulation fatigue damage is larger than 0.45 under normal conditions and that the reliability of the SW system is larger than 94%within the design life.展开更多
Hybrid systems consisting of superconducting circuits and magnon systems are a promising platform for quantum technology.However,realizing high-fidelity magnon state preparation and manipulation remains an outstanding...Hybrid systems consisting of superconducting circuits and magnon systems are a promising platform for quantum technology.However,realizing high-fidelity magnon state preparation and manipulation remains an outstanding challenge due to the complexity of interactions and noise sources in hybrid systems.Here,we propose a coherence-preserving magnon state manipulation scheme.By engineering a superconducting-magnon coupling pulse and combining it with dynamical decoupling pulses,we design a composite pulse sequence.We demonstrate the manipulation and preparation of non-classical states of magnons with a fidelity of up to 98%under realistic conditions.These designs significantly improve the fidelity of manipulation and robustness to noise in hybrid systems compared to existing schemes.These results pave the way for practical applications of quantum magnonics platforms.展开更多
Single-photon sensors are novel devices with extremely high single-photon sensitivity and temporal resolution.However,these advantages also make them highly susceptible to noise.Moreover,single-photon cameras face sev...Single-photon sensors are novel devices with extremely high single-photon sensitivity and temporal resolution.However,these advantages also make them highly susceptible to noise.Moreover,single-photon cameras face severe quantization as low as 1 bit/frame.These factors make it a daunting task to recover high-quality scene information from noisy single-photon data.Most current image reconstruction methods for single-photon data are mathematical approaches,which limits information utilization and algorithm performance.In this work,we propose a hybrid information enhancement model which can significantly enhance the efficiency of information utilization by leveraging attention mechanisms from both spatial and channel branches.Furthermore,we introduce a structural feature enhance module for the FFN of the transformer,which explicitly improves the model's ability to extract and enhance high-frequency structural information through two symmetric convolution branches.Additionally,we propose a single-photon data simulation pipeline based on RAW images to address the challenge of the lack of single-photon datasets.Experimental results show that the proposed method outperforms state-of-the-art methods in various noise levels and exhibits a more efficient capability for recovering high-frequency structures and extracting information.展开更多
This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model...This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model follows a“three-stage”and“two-subject”framework,incorporating a structured design for teaching content and assessment methods before,during,and after class.Practical results indicate that this approach significantly enhances teaching effectiveness and improves students’learning autonomy.展开更多
In this paper,we propose a sub-6GHz channel assisted hybrid beamforming(HBF)for mmWave system under both line-of-sight(LOS)and non-line-of-sight(NLOS)scenarios without mmWave channel estimation.Meanwhile,we resort to ...In this paper,we propose a sub-6GHz channel assisted hybrid beamforming(HBF)for mmWave system under both line-of-sight(LOS)and non-line-of-sight(NLOS)scenarios without mmWave channel estimation.Meanwhile,we resort to the selfsupervised approach to eliminate the need for labels,thus avoiding the accompanied high cost of data collection and annotation.We first construct the dense connection network(DCnet)with three modules:the feature extraction module for extracting channel characteristic from a large amount of channel data,the feature fusion module for combining multidimensional features,and the prediction module for generating the HBF matrices.Next,we establish a lightweight network architecture,named as LDnet,to reduce the number of model parameters and computational complexity.The proposed sub-6GHz assisted approach eliminates mmWave pilot resources compared to the method using mmWave channel information directly.The simulation results indicate that the proposed DCnet and LDnet can achieve the spectral efficiency that is superior to the traditional orthogonal matching pursuit(OMP)algorithm by 13.66% and 10.44% under LOS scenarios and by 32.35% and 27.75% under NLOS scenarios,respectively.Moreover,the LDnet achieves 98.52% reduction in the number of model parameters and 22.93% reduction in computational complexity compared to DCnet.展开更多
The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to case...The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.展开更多
This paper examines the transport analysis,including both heat transfer and mass transfer,in hybrid nanofluid flow containing gyrotactic microorganisms towards a curved oscillatory surface.The influence of magnetic fi...This paper examines the transport analysis,including both heat transfer and mass transfer,in hybrid nanofluid flow containing gyrotactic microorganisms towards a curved oscillatory surface.The influence of magnetic fields is also inspected in terms of their physical characteristics.To depict the phenomena of transport,modified versions of both Fick's and Fourier's laws are used.Additionally,the characteristics of both heterogeneous and homogeneous chemical reactions are also incorporated.Utilizing a curvilinear coordinate system,the flow problem is formulated as partial differential equations(PDEs)for momentum,concentration,microorganism field,and energy.An analytical solution to the obtained flow equations is achieved utilizing the homotopy analysis method(HAM).The effects of significant flow parameters on the pressure and microorganism fields,velocity,oscillation velocity,concentration,and temperature distributions are shown via graphs.Furthermore,the variations in skin friction,mass transfer rate,heat transfer rate,and local motile number due to different involved parameters are presented in tables and are analyzed in detail.Graphical results indicate that the curves of velocity and temperature fields are enhanced as the values of the solid volume fraction variables increase.It is also verified that the concentration rate field decreases as the values of the homogeneous reaction strength parameter and the radius of curvature parameter increase,and it increases with the Schmidt number and the heterogeneous reaction strength parameter.Tabular outcomes show a favorable response of the motile number to advanced values of the Peclet number,the Schmidt number,the microorganism difference parameter,and the bio-convective Lewis number.展开更多
This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates.One plate remains stationary,while the other moves downward at a squeezing veloci...This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates.One plate remains stationary,while the other moves downward at a squeezing velocity.The space between these plates contains a Darcy-Forchheimer porous medium.A mixture of water-based fluid with gold(Au)and silicon dioxide(Si O2)nanoparticles is formulated.In contrast to the conventional Fourier's heat flux equation,this study employs the Cattaneo-Christov heat flux equation.A uniform magnetic field is applied perpendicular to the flow direction,invoking magnetohydrodynamic(MHD)effects.Further,the model accounts for Joule heating,which is the heat generated when an electric current passes through the fluid.The problem is solved via NDSolve in MATHEMATICA.Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow,energy transport,and skin friction.The findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies.It is observed that the squeezing motion generates additional pressure gradients within the fluid,which enhances the flow rate but reduces the frictional drag.Consequently,the fluid is pushed more vigorously between the plates,increasing the flow velocity.As the fluid experiences higher flow rates due to the increased squeezing effect,it spends less time in the region between the plates.The thermal relaxation,however,abruptly changes the temperature,leading to a decrease in the temperature fluctuations.展开更多
Fluid flow through porous spaces with variable porosity has wide-range applications,notably in biomedical and thermal engineering,where it plays a vital role in comprehending blood flow dynamics within cardiovascular ...Fluid flow through porous spaces with variable porosity has wide-range applications,notably in biomedical and thermal engineering,where it plays a vital role in comprehending blood flow dynamics within cardiovascular systems,heat transfer and thermal management systems improve efficiency using porous materials with variable porosity.Keeping these important applications in view,in current study blood-based hybrid nanofluid flow has considered on a convectively heated sheet.The sheet exhibits the properties of a porous medium with variable porosity and extends in both the x and y directions.Blood has used as base fluid in which the nanoparticles of Cu and Cu O have been mixed.Thermal radiation,space-dependent,and thermal-dependent heat sources have been incorporated into the energy equation,while magnetic effects have been integrated into the momentum equations.Dimensionless variables have employed to transform the modeled equations into dimensionless form and facilitating their solution using bvp4c approach.It has concluded in this study that,both the primary and secondary velocities augmented with upsurge in variable porous factor and declined with escalation in stretching ratio,Casson,magnetic,and slip factors along x-and y-axes.Thermal distribution has grown up with upsurge in Casson factor,magnetic factor,thermal Biot number,and thermal/space-dependent heat sources while has retarded with growth in variable porous and stretching ratio factors.The findings of this investigation have been compared with the existing literature,revealing a strong agreement among present and established results that ensured the validation of the model and method used in this work.展开更多
基金supported by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant no.(GPIP:13-612-2024).
文摘App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.
基金sponsored by R&D Program of Beijing Municipal Education Commission(KM202410009013).
文摘In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.
基金received funding from the Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX23_1633)2023 University Student Innovation and Entrepreneurship Training Program(202311463009Z)+1 种基金Changzhou Science and Technology Support Project(CE20235045)Open Project of Jiangsu Key Laboratory of Power Transmission&Distribution Equipment Technology(2021JSSPD12).
文摘Uneven power distribution,transient voltage,and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes.In response to these issues,this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm.The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control.Then,it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy.Precise pre-synchronization is achieved by regulating the virtual current to zero and aligning the photovoltaic storage hybrid inverter with the grid voltage.Additionally,two novel operators,learning and emotional behaviors are introduced to enhance the optimization precision of the chimpanzee algorithm.These operators ensure high-precision and high-reliability optimization of the droop control parameters for photovoltaic storage hybrid inverters.A Simulink model was constructed for simulation analysis,which validated the optimized control strategy’s ability to evenly distribute power under load transients.This strategy effectively mitigated transient voltage and current surges during mode transitions.Consequently,seamless and efficient switching between gridconnected and island modes was achieved for the photovoltaic storage hybrid inverter.The enhanced energy utilization efficiency,in turn,offers robust technical support for grid stability.
基金supported by a Horizontal Project on the Development of a Hybrid Energy Storage Simulation Model for Wind Power Based on an RT-LAB Simulation System(PH2023000190)the Inner Mongolia Natural Science Foundation Project and the Optimization of Exergy Efficiency of a Hybrid Energy Storage System with Crossover Control for Wind Power(2023JQ04).
文摘Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources.This paper proposes a wind-solar hybrid energy storage system(HESS)to ensure a stable supply grid for a longer period.A multi-objective genetic algorithm(MOGA)and state of charge(SOC)region division for the batteries are introduced to solve the objective function and configuration of the system capacity,respectively.MATLAB/Simulink was used for simulation test.The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system,with a combination of a 300 Ah lithium battery,a 200 Ah lead-acid battery,and a water storage tank,the proposed strategy reduces the system construction cost by approximately 18,000 yuan.Additionally,the cycle count of the electrochemical energy storage systemincreases from4515 to 4660,while the depth of discharge decreases from 55.37%to 53.65%,achieving shallow charging and discharging,thereby extending battery life and reducing grid voltage fluctuations significantly.The proposed strategy is a guide for stabilizing the grid connection of wind and solar power generation,capability allocation,and energy management of energy conservation systems.
基金supported by the State Grid Corporation of China Science and Technology Project,grant number 52270723000900K.
文摘The new energy power generation is becoming increasingly important in the power system.Such as photovoltaic power generation has become a research hotspot,however,due to the characteristics of light radiation changes,photovoltaic power generation is unstable and random,resulting in a low utilization rate and directly affecting the stability of the power grid.To solve this problem,this paper proposes a coordinated control strategy for a newenergy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit.Firstly,the variational mode decomposition algorithm is used to separate the high and low frequencies of the power signal,which is conducive to the rapid and accurate suppression of the power fluctuation of the energy storage system.Secondly,the fuzzy control algorithm is introduced to balance the power between energy storage.In this paper,the actual data is used for simulation,and the simulation results show that the strategy realizes the effective suppression of the bus voltage fluctuation and the accurate control of the internal state of the energy storage unit,effectively avoiding problems such as overshoot and over-discharge,and can significantly improve the stability of the photovoltaic power generation systemand the stability of the Direct Current bus.It is of great significance to promote the development of collaborative control technology for photovoltaic hybrid energy storage units.
文摘In this paper, we proposed an output voltage stabilization of a DC-DC Zeta converter using hybrid control. We modeled the Zeta converter under continuous conduction mode operation. We derived a switching control law that brings the output voltage to the desired level. Due to infinite switching occurring at the desired level, we enhanced the switching control law by allowing a sizeable output voltage ripple. We derived mathematical models that allow one to choose the desired switching frequency. In practice, the existence of the non-ideal properties of the Zeta converter results in steady-state output voltage error. By analyzing the power loss in the zeta converter, we proposed an improved switching control law that eliminates the steady-state output voltage error. The effectiveness of the proposed method is illustrated with simulation results.
基金Princess Nourah bint Abdulrahman University Research Supporting Project Number PNURSP2025R241,Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Nitrogen (N) is a crucial nutrient vital for the growth and productivity of maize. However, excessive nitrogen application can result in numerous environmental and ecological problems, such as water pollution, biodiversity loss, and greenhouse gas emissions. Therefore, breeding maize hybrids resilient to low nitrogen conditions is crucial for sustainable agriculture, especially under low nitrogen conditions. Consequently, this study aimed to evaluate the combining ability and heterosis of maize lines, recognize promising hybrids, and study gene action controlling key traits under low and recommended N stress conditions. The half-diallel mating design hybridized seven maize inbreds, resulting in 21 F1 hybrids. These hybrids, along with two high-yielding commercial hybrids (SC10 and TWC310), were evaluated in field trials under recommended (290 kg/ha) and low N (166 kg N/ha) conditions. Significant variations were observed among assessed hybrids for all measured traits, with non-additive gene action being predominant for grain yield and its related characteristics under recommended and low N conditions. Inbred lines P105 and P106 were recognized as effective combiners for earliness, with P105 also excelling in shorter plant height and lower ear placement. In addition, P101, P102, and P104 were identified as good combiners for increasing grain yield and related attributes under low N conditions. The crosses P105 × P106 and P106 × P107 demonstrated outstanding heterotic effects for earliness, while hybrids P101 × P102 and P102 × P104 exhibited remarkable heterotic effects for grain yield low nitrogen stress conditions. These promising hybrids could be considered for commercial use after further evaluation. Strong positive correlations were found between grain yield and ear height, plant height, number of kernels per row, and 1000-grain weight, highlighting their importance for indirect selection to enhance the grain yield of maize under low N stress conditions.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12175106 and 92365110)the Postgraduate Research and Practice Innovation Program of Jiangsu Province(Grant No.KYCX23-1028)。
文摘Hybrid entangled states(HESs),which involve different particles with various degrees of freedom,have garnered significant attention and been applied in a wide range of quantum technologies.However,similar to other categories of entanglement,maximally HESs inevitably degrade to mixed states due to the environmental noise and operational imperfections.To address the degradation problem,measurement-based entanglement purification offers a feasible and robust solution alternative to conventional gate-based purification methods.In this paper,we propose a measurement-based hybrid entanglement purification protocol(MB-HEPP)for a certain kind of HES which consists of polarization photons and coherent states.We extend our methodology to several conditions,such as the multi-copy and multi-party scenarios,and the photon-loss condition.Compared with previous HEPPs,this protocol has several advantages.First,it does not depend on post-selection and the purified HESs can be retained for further application.Second,it does not require the Bell state measurement,but only uses the parity check with conventional linear optical elements,which makes it have the higher success probability and more feasible.Our MB-HEPP has potential applications in future heterogeneous quantum networks.
基金Project supported by the Basic Scientific Research Projects of Department of Education of Liaoning Province,China(Grant No.LJ212410152049)the Technological Innovation Projects in the field of artificial intelligence of Liaoning Province,China(Grant No.2023JH26/10300011)。
文摘Existing chaotic encryption schemes primarily focus on single types of images,making the design of hybrid image encryption schemes more suitable for practical applications.In this paper,a hyperchaotic map with a spherical attractor is proposed,which is constructed using spherical coordinates.Dynamical analyses reveal that the hyperchaotic map exhibits global hyperchaos and high complexity,making it capable of generating more complex chaotic sequences suitable for image encryption.A hybrid encryption scheme based on a hyperchaotic map is proposed for two-dimensional(2D)images,three-dimensional(3D)models,and 3D point clouds.Firstly,the pixels of 2D image and the coordinate data of 3D image are fused into a plaintext cube,which is combined with Hash-512 to obtain the initial value of the hyperchaotic map.Chaotic sequences are utilized for cube space internal confusion and dynamic cross-diffusion.The encrypted images demonstrate high information entropy,and the test results show that the encryption scheme effectively protects the images.The proposed hybrid image encryption scheme provides an efficient solution for securing various types of images.
基金the project SILVARSTAR funded from the Shift2Rail Joint Undertaking under the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 101015442。
文摘Within the SILVARSTAR project,a user-friendly frequency-based hybrid prediction tool has been developed to assess the environmental impact of railway-induced vibration.This tool is integrated in existing noise mapping software.Following modern vibration standards and guidelines,the vibration velocity level in a building in each frequency band is expressed as the sum of a force density(source term),line source transfer mobility(propagation term)and building correction factor(receiver term).A hybrid approach is used that allows for a combination of experimental data and numerical predictions,providing increased flexibility and applicability.The train and track properties can be selected from a database or entered as numerical values.The user can select soil impedance and transfer functions from a database,pre-computed for a wide range of parameters with state-of-the-art models.An experimental database of force densities,transfer functions,free field vibration and input parameters is also provided.The building response is estimated by means of building correction factors.Assumptions within the modelling approach are made to reduce computation time but these can influence prediction accuracy;this is quantified for the case of a nominal intercity train running at different speeds on a ballasted track supported by homogeneous soil of varying stiffness.The paper focuses on the influence of these parameters on the compliance of the track–soil system and the free field response.We also demonstrate the use and discuss the validation of the vibration prediction tool for the case of a high-speed train running on a ballasted track in Lincent(Belgium).
基金financially supported by the National Natural Science Foundation of China(Grant No.52071337)the Research Initiation Funds of Zhejiang University of Science and Technology(Grant No.F701102N06)+2 种基金the High-tech Ship Research Projects Sponsored by MIIT(Grant No.CBG2N21-4-2-5)the National Key Research and Development Program of China(Grant No.2022YFC2806300)the Marine Economy Development(Six Marine Industries)Special Foundation of the Department of Natural Resources of Guangdong Province(Grant No.GDNRC[2023]50).
文摘The deepwater subsea wellhead(SW)system is the foundation for the construction of oil and gas wells and the crucial channel for operation.During riser connection operation,the SW system is subjected to cyclic dynamic loads which cause fatigue damage to the SW system,and continuously accumulated fatigue damage leads to fatigue failure of the SW system,rupture,and even blowout accidents.This paper proposes a hybrid Bayesian network(HBN)-based dynamic reliability assessment approach for deepwater SW systems during their service life.In the proposed approach,the relationship between the accumulation of fatigue damage and the fatigue failure probability of the SW system is predicted,only considering normal conditions.The HBN model,which includes the accumulation of fatigue damage under normal conditions and the other factors affecting the fatigue of the SW system,is subsequently developed.When predictive and diagnostic analysis techniques are adopted,the dynamic reliability of the SW system is achieved,and the most influential factors are determined.Finally,corresponding safety control measures are proposed to improve the reliability of the SW system effectively.The results illustrate that the fatigue failure speed increases rapidly when the accumulation fatigue damage is larger than 0.45 under normal conditions and that the reliability of the SW system is larger than 94%within the design life.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12304401 and 11974336)the National Key Research and Development Program of China(Grant No.2017YFA0304100)。
文摘Hybrid systems consisting of superconducting circuits and magnon systems are a promising platform for quantum technology.However,realizing high-fidelity magnon state preparation and manipulation remains an outstanding challenge due to the complexity of interactions and noise sources in hybrid systems.Here,we propose a coherence-preserving magnon state manipulation scheme.By engineering a superconducting-magnon coupling pulse and combining it with dynamical decoupling pulses,we design a composite pulse sequence.We demonstrate the manipulation and preparation of non-classical states of magnons with a fidelity of up to 98%under realistic conditions.These designs significantly improve the fidelity of manipulation and robustness to noise in hybrid systems compared to existing schemes.These results pave the way for practical applications of quantum magnonics platforms.
文摘Single-photon sensors are novel devices with extremely high single-photon sensitivity and temporal resolution.However,these advantages also make them highly susceptible to noise.Moreover,single-photon cameras face severe quantization as low as 1 bit/frame.These factors make it a daunting task to recover high-quality scene information from noisy single-photon data.Most current image reconstruction methods for single-photon data are mathematical approaches,which limits information utilization and algorithm performance.In this work,we propose a hybrid information enhancement model which can significantly enhance the efficiency of information utilization by leveraging attention mechanisms from both spatial and channel branches.Furthermore,we introduce a structural feature enhance module for the FFN of the transformer,which explicitly improves the model's ability to extract and enhance high-frequency structural information through two symmetric convolution branches.Additionally,we propose a single-photon data simulation pipeline based on RAW images to address the challenge of the lack of single-photon datasets.Experimental results show that the proposed method outperforms state-of-the-art methods in various noise levels and exhibits a more efficient capability for recovering high-frequency structures and extracting information.
基金2024 Anqing Normal University University-Level Key Project(ZK2024062D)。
文摘This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model follows a“three-stage”and“two-subject”framework,incorporating a structured design for teaching content and assessment methods before,during,and after class.Practical results indicate that this approach significantly enhances teaching effectiveness and improves students’learning autonomy.
基金supported in part by the National Natural Science Foundation of China under Grants 62325107,62341107,62261160650,and U23A20272in part by the Beijing Natural Science Foundation under Grant L222002.
文摘In this paper,we propose a sub-6GHz channel assisted hybrid beamforming(HBF)for mmWave system under both line-of-sight(LOS)and non-line-of-sight(NLOS)scenarios without mmWave channel estimation.Meanwhile,we resort to the selfsupervised approach to eliminate the need for labels,thus avoiding the accompanied high cost of data collection and annotation.We first construct the dense connection network(DCnet)with three modules:the feature extraction module for extracting channel characteristic from a large amount of channel data,the feature fusion module for combining multidimensional features,and the prediction module for generating the HBF matrices.Next,we establish a lightweight network architecture,named as LDnet,to reduce the number of model parameters and computational complexity.The proposed sub-6GHz assisted approach eliminates mmWave pilot resources compared to the method using mmWave channel information directly.The simulation results indicate that the proposed DCnet and LDnet can achieve the spectral efficiency that is superior to the traditional orthogonal matching pursuit(OMP)algorithm by 13.66% and 10.44% under LOS scenarios and by 32.35% and 27.75% under NLOS scenarios,respectively.Moreover,the LDnet achieves 98.52% reduction in the number of model parameters and 22.93% reduction in computational complexity compared to DCnet.
基金supported by the National Natural Science Foundation of China(No.12305344)the 2023 Anhui university research project of China(No.2023AH052179).
文摘The off situ accurate reconstruction of the core neutron field is an important step in realizing real-time reactor monitoring.The existing off situ reconstruction method of the neutron field is only applicable to cases wherein a single region changes at a specified location of the core.However,when the neutron field changes are complex,the accurate identification of the individual changed regions becomes challenging,which seriously affects the accuracy and stability of the neutron field recon-struction.Therefore,this study proposed a dual-task hybrid network architecture(DTHNet)for off situ reconstruction of the core neutron field,which trained the outermost assembly reconstruction task and the core reconstruction task jointly such that the former could assist the latter in the reconstruction of the core neutron field under core complex changes.Furthermore,to exploit the characteristics of the ex-core detection signals,this study designed a global-local feature upsampling module that efficiently distributed the ex-core detection signals to each reconstruction unit to improve the accuracy and stability of reconstruction.Reconstruction experiments were performed on the simulation datasets of the CLEAR-I reactor to verify the accuracy and stability of the proposed method.The results showed that when the location uncertainty of a single region did not exceed nine and the number of multiple changed regions did not exceed five.Further,the reconstructed ARD was within 2%,RD_(max)was maintained within 17.5%,and the number of RD≥10%was maintained within 10.Furthermore,when the noise interference of the ex-core detection signals was within±2%,although the average number of RD≥10%increased to 16,the average ARD was still within in 2%,and the average RD_(max)was within 22%.Collectively,these results show that,theoretically,the DTHNet can accurately and stably reconstruct most of the neutron field under certain complex core changes.
文摘This paper examines the transport analysis,including both heat transfer and mass transfer,in hybrid nanofluid flow containing gyrotactic microorganisms towards a curved oscillatory surface.The influence of magnetic fields is also inspected in terms of their physical characteristics.To depict the phenomena of transport,modified versions of both Fick's and Fourier's laws are used.Additionally,the characteristics of both heterogeneous and homogeneous chemical reactions are also incorporated.Utilizing a curvilinear coordinate system,the flow problem is formulated as partial differential equations(PDEs)for momentum,concentration,microorganism field,and energy.An analytical solution to the obtained flow equations is achieved utilizing the homotopy analysis method(HAM).The effects of significant flow parameters on the pressure and microorganism fields,velocity,oscillation velocity,concentration,and temperature distributions are shown via graphs.Furthermore,the variations in skin friction,mass transfer rate,heat transfer rate,and local motile number due to different involved parameters are presented in tables and are analyzed in detail.Graphical results indicate that the curves of velocity and temperature fields are enhanced as the values of the solid volume fraction variables increase.It is also verified that the concentration rate field decreases as the values of the homogeneous reaction strength parameter and the radius of curvature parameter increase,and it increases with the Schmidt number and the heterogeneous reaction strength parameter.Tabular outcomes show a favorable response of the motile number to advanced values of the Peclet number,the Schmidt number,the microorganism difference parameter,and the bio-convective Lewis number.
文摘This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates.One plate remains stationary,while the other moves downward at a squeezing velocity.The space between these plates contains a Darcy-Forchheimer porous medium.A mixture of water-based fluid with gold(Au)and silicon dioxide(Si O2)nanoparticles is formulated.In contrast to the conventional Fourier's heat flux equation,this study employs the Cattaneo-Christov heat flux equation.A uniform magnetic field is applied perpendicular to the flow direction,invoking magnetohydrodynamic(MHD)effects.Further,the model accounts for Joule heating,which is the heat generated when an electric current passes through the fluid.The problem is solved via NDSolve in MATHEMATICA.Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow,energy transport,and skin friction.The findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies.It is observed that the squeezing motion generates additional pressure gradients within the fluid,which enhances the flow rate but reduces the frictional drag.Consequently,the fluid is pushed more vigorously between the plates,increasing the flow velocity.As the fluid experiences higher flow rates due to the increased squeezing effect,it spends less time in the region between the plates.The thermal relaxation,however,abruptly changes the temperature,leading to a decrease in the temperature fluctuations.
基金supported via funding from Prince Sattam bin Abdulaziz University(Grant No.PSAU/2024/R/1446)。
文摘Fluid flow through porous spaces with variable porosity has wide-range applications,notably in biomedical and thermal engineering,where it plays a vital role in comprehending blood flow dynamics within cardiovascular systems,heat transfer and thermal management systems improve efficiency using porous materials with variable porosity.Keeping these important applications in view,in current study blood-based hybrid nanofluid flow has considered on a convectively heated sheet.The sheet exhibits the properties of a porous medium with variable porosity and extends in both the x and y directions.Blood has used as base fluid in which the nanoparticles of Cu and Cu O have been mixed.Thermal radiation,space-dependent,and thermal-dependent heat sources have been incorporated into the energy equation,while magnetic effects have been integrated into the momentum equations.Dimensionless variables have employed to transform the modeled equations into dimensionless form and facilitating their solution using bvp4c approach.It has concluded in this study that,both the primary and secondary velocities augmented with upsurge in variable porous factor and declined with escalation in stretching ratio,Casson,magnetic,and slip factors along x-and y-axes.Thermal distribution has grown up with upsurge in Casson factor,magnetic factor,thermal Biot number,and thermal/space-dependent heat sources while has retarded with growth in variable porous and stretching ratio factors.The findings of this investigation have been compared with the existing literature,revealing a strong agreement among present and established results that ensured the validation of the model and method used in this work.
