Catastrophic failure in engineering structures of island reefs would occur when the tertiary creep initiates in coral reef limestone with a transition from short-to long-term load.Due to the complexity of biological s...Catastrophic failure in engineering structures of island reefs would occur when the tertiary creep initiates in coral reef limestone with a transition from short-to long-term load.Due to the complexity of biological structures,the underlying micro-behaviors involving time-dependent deformation are poorly understood.For this,an abnormal phenomenon was observed where the axial and lateral creep deformations were mutually independent by a series of triaxial tests under constant stress and strain rate conditions.The significantly large lateral creep deformation implies that the creep process cannot be described in continuum mechanics regime.Herein,it is hypothesized that sliding mechanism of crystal cleavages dominates the lateral creep deformation in coral reef limestone.Then,approaches of polarizing microscope(PM)and scanning electronic microscope(SEM)are utilized to validate the hypothesis.It shows that the sliding behavior of crystal cleavages combats with conventional creep micro-mechanisms at certain condition.The former is sensitive to time and strain rate,and is merely activated in the creep regime.展开更多
A pseudospectral method with symplectic algorithm for the solution of time-dependent Schrodinger equations （TDSE） is introduced. The spatial part of the wavefunction is discretized into sparse grid by pseudospectral...A pseudospectral method with symplectic algorithm for the solution of time-dependent Schrodinger equations （TDSE） is introduced. The spatial part of the wavefunction is discretized into sparse grid by pseudospectral method and the time evolution is given in symplectic scheme. This method allows us to obtain a highly accurate and stable solution of TDSE. The effectiveness and efficiency of this method is demonstrated by the high-order harmonic spectra of one-dimensional atom in strong laser field as compared with previously published work. The influence of the additional static electric field is also investigated.展开更多
With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic...With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential equation.The results in this paper depend on all the oceanic variable coefficients in that equation.展开更多
The VRP is classified as an NP-hard problem. Hence exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. To ge...The VRP is classified as an NP-hard problem. Hence exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. To get solutions in determining routes which are realistic and very close to the actual solution, we use heuristics and metaheuristics which are of the combinatorial optimization type. A literature review of VRPTW, TDVRP, and a metaheuristic such as the genetic algorithm was conducted. In this paper, the implementation of the VRPTW and its extension, the time-dependent VRPTW (TDVRPTW) has been carried out using the model as well as metaheuristics such as the genetic algorithm (GA). The algorithms were implemented, using Matlab and HeuristicLab optimization software. A plugin was developed using Visual C# and DOT NET framework 4.5. Results were tested using Solomon’s 56 benchmark instances classified into groups such as C1, C2, R1, R2, RC1, RC2, with 100 customer nodes, 25 vehicles and each vehicle capacity of 200. The results were comparable to the earlier algorithms developed and in some cases the current algorithm yielded better results in terms of total distance travelled and the average number of vehicles used.展开更多
In this paper, we present a new algorithm of the time-dependent shortest path problem with time windows. Give a directed graph , where V is a set of nodes, E is a set of edges with a non-negative transit-time function...In this paper, we present a new algorithm of the time-dependent shortest path problem with time windows. Give a directed graph , where V is a set of nodes, E is a set of edges with a non-negative transit-time function . For each node , a time window ?within which the node may be visited and ?, is non-negative of the service and leaving time of the node. A source node s, a destination node d and a departure time?t0, the time-dependent shortest path problem with time windows asks to find an s, d-path that leaves a source node s at a departure time t0;and minimizes the total arrival time at a destination node d. This formulation generalizes the classical shortest path problem in which ce are constants. Our algorithm of the time windows gave the generalization of the ALT algorithm and A* algorithm for the classical problem according to Goldberg and Harrelson [1], Dreyfus [2] and Hart et al. [3].展开更多
The field of diffusion micro structural magnetic resonance(MR)aims to probe timedependent diffusion,i.e.,an ensemble-averaged mean-squared displacement that is not linear in time.This time-dependence contains rich inf...The field of diffusion micro structural magnetic resonance(MR)aims to probe timedependent diffusion,i.e.,an ensemble-averaged mean-squared displacement that is not linear in time.This time-dependence contains rich information about the surrounding microenvironment.MR methods to measure time-dependent diffusion quantitatively,however,require either non-standard pulse sequences,such as oscillating gradients,or make non-physical assumptions,such as infinitely narrow gradient pulses.Here,we argue that standard spin echo and stimulated echo MR sequences can be used to probe directly.In particular,we propose a framework in which the log-signal ratio obtained from a pair of measurements with different inter-pulse spacingΔis proportional to the MSD between these twoΔvalues along the gradient direction x:-.The framework is quantitative for short,finite-duration gradient pulses and under the Gaussian phase approximation(GPA).To validate the framework,we consider onedimensional diffusion between impermeable,parallel planes,as well as periodicallyspaced,permeable planes.Excellent agreement is obtained between the estimation and the ground truth in the regime where the GPA is expected to hold.Importantly,the GPA can be made to hold for any underlying microstructure,making the proposed framework widely applicable.展开更多
This article first outlines the fundamental definitions of Mycoplasma pneumoniae and the basic principles of antibiotics. It then analyzes and discusses the progress in antibiotic application and time-eff ect studies ...This article first outlines the fundamental definitions of Mycoplasma pneumoniae and the basic principles of antibiotics. It then analyzes and discusses the progress in antibiotic application and time-eff ect studies for neonatal pneumonia treatment, specifically comparing conventional antibiotic therapy with stepwise treatment regimens, and contrasting monotherapy with penicillin, monotherapy with cephalosporins, and combination therapy. Finally, it offers a prospective outlook on antibiotic application and time-effect research in neonatal pneumonia treatment, aiming to provide valuable reference for further scholarly investigations.展开更多
Heat transfers at the interface of adjacent saturated soil primarily through the soil particles and the water in the voids.The presence of water induces the contraction of heat flow lines at the interface,leading to t...Heat transfers at the interface of adjacent saturated soil primarily through the soil particles and the water in the voids.The presence of water induces the contraction of heat flow lines at the interface,leading to the emergence of the thermal contact resistance effect.In this paper,four thermal contact models were developed to predict the thermal contact resistance at the interface of multilayered saturated soils.Based on the theory of thermal-hydro-mechanical coupling,semi-analytical solutions of thermal consolidation subjected to time-dependent heating and loading were obtained by employing Laplace transform and its inverse transformation.Thermal consolidation characteristics of multilayered saturated soils under four different thermal contact models were discussed,and the effects of thermal resistance coefficient,partition thermal contact coefficient,and temperature amplitude on the thermal consolidation process were investigated.The outcomes indicate that the general thermal contact model results in the most pronounced thermal gradient at the interface,which can be degenerated to the other three thermal contact models.The perfect thermal contact model overestimates the deformation of the saturated soil during the thermal consolidation.Moreover,the effect of temperature on consolidation properties decreases gradually with increasing interfacial contact thermal resistance.展开更多
The Zagros Basin in southwestern Iran is a significant source of coal,with numerous coal mines operating in the region.Ensuring the stability of coal mines is crucial for safe and efficient mining operations.This stud...The Zagros Basin in southwestern Iran is a significant source of coal,with numerous coal mines operating in the region.Ensuring the stability of coal mines is crucial for safe and efficient mining operations.This study investigates the time-varying response of rocks and roof resistance in coal mines in the Zagros Mountains using a novel approach that combines numerical simulation,relaxation testing,and rock displacement studies.The results show that rocks exhibit significant time-dependent behavior,with changes in rock mechanical properties over time.A comprehensive viscoelastic-plastic model is devel-oped to accurately describe the time-varying strain-softening response of rocks and simulate laboratory tests.The model integrates the Burgers and strain-softening models,simulating stress relaxation curves and rock displacement over time.The study reveals that the rock mass displays significant nonlinear behavior,with changes in rock mechanical properties over time.The findings of this study highlight the importance of considering the time-varying response of rocks and roof resistance in coal mine stability analysis.The results provide valuable insights into the time-dependent behavior of rock mass in coal mines in Iran,which can inform mining practices and mitigate potential hazards.Results in this study can contribute to developing strategies for improving roof stability and reducing the likelihood of roof collapses.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
Local and parallel finite element algorithms based on two-grid discretization for the time-dependent convection-diffusion equations are presented. These algorithms are motivated by the observation that, for a solution...Local and parallel finite element algorithms based on two-grid discretization for the time-dependent convection-diffusion equations are presented. These algorithms are motivated by the observation that, for a solution to the convection-diffusion problem, low frequency components can be approximated well by a relatively coarse grid and high frequency components can be computed on a fine grid by some local and parallel proce- dures. Hence, these local and parallel algorithms only involve one small original problem on the coarse mesh and some correction problems on the local fine grid. One technical tool for the analysis is the local a priori estimates that are also obtained. Some numerical examples are given to support our theoretical analvsis.展开更多
We present a fully time-dependent quantum wave packet evolution method for investigating molecular dynamics in intense laser fields.This approach enables the simultaneous treatment of interactions among multiple elect...We present a fully time-dependent quantum wave packet evolution method for investigating molecular dynamics in intense laser fields.This approach enables the simultaneous treatment of interactions among multiple electronic states while simultaneously tracking their time-dependent electronic,vibrational,and rotational dynamics.As an illustrative example,we consider neutral H_(2)molecules and simulate the laser-induced excitation dynamics of electronic and rotational states in strong laser fields,quantitatively distinguishing the respective contributions of electronic dipole transitions(within the classical-field approximation)and non-resonant Raman processes to the overall molecular dynamics.Furthermore,we precisely evaluate the relative contributions of direct tunneling ionization from the ground state and ionization following electronic excitation in the strong-field ionization of H_(2).The developed methodology shows strong potential for performing high-precision theoretical simulations of electronic-vibrational-rotational state excitations,ionization,and dissociation dynamics in molecules and their ions under intense laser fields.展开更多
In recent years,numerous recurrent neural network(RNN)models have been reported for solving time-dependent nonlinear optimization problems.However,few existing RNN models simultaneously involve nonlinear equality cons...In recent years,numerous recurrent neural network(RNN)models have been reported for solving time-dependent nonlinear optimization problems.However,few existing RNN models simultaneously involve nonlinear equality constraints,direct discretization,and noise suppression.This limitation presents challenges when existing models are applied to practical engineering problems.Additionally,most current discrete-time RNN models are derived from continuous-time models,which may not perform well for solving essentially discrete problems.To handle these issues,a robust direct-discretized RNN(RDD-RNN)model is proposed to efficiently realize time-dependent optimization constrained by nonlinear equalities(TDOCNE)in the presence of various time-dependent noises.Theoretical analyses are provided to reveal that the proposed RDD-RNN model possesses excellent convergence and noise-suppressing capability.Furthermore,numerical experiments and manipulator control instances are conducted and analyzed to validate the superior robustness of the proposed RDD-RNN model under various time-dependent noises,particularly quadratic polynomial noise.Eventually,small target detection experiments further demonstrate the practicality of the RDD-RNN model in image processing applications.展开更多
In this paper, Homotopy Analysis method with Genetic Algorithm is presented and used to obtain an analytical solution for the time-dependent Emden-Fowler type of equations and wave-type equation with singular behavior...In this paper, Homotopy Analysis method with Genetic Algorithm is presented and used to obtain an analytical solution for the time-dependent Emden-Fowler type of equations and wave-type equation with singular behavior at x = 0. The advantage of this single global method employed to present a reliable framework is utilized to overcome the singularity behavior at the point x = 0 for both models. The method is demonstrated for a variety of problems in one and higher dimensional spaces where approximate-exact solutions are obtained. The results obtained in all cases show the reliability and the efficiency of this method.展开更多
Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting...Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious an...Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.展开更多
We present a forward-modeling investigation of time-dependent ground magnetometric resistivity （MMR） anomalies associated with transient leachate transport in groundwater systems. Numerical geo-electrical models are...We present a forward-modeling investigation of time-dependent ground magnetometric resistivity （MMR） anomalies associated with transient leachate transport in groundwater systems. Numerical geo-electrical models are constructed based on the hydrological simulation results of leachate plumes from a highly conceptualized landfill system and the resultant MMR responses are computed using a modified finite difference software MMR2DFD. Three transmitter configurations （i.e., single source, MMR-TE, and MMR-TM modes） and two hydrological models （i.e., uniform and faulted porous media） are considered. Our forward modeling results for the uniform porous medium indicates that the magnetic field components perpendicular to the dominant current flow contain the most information of the underground targets and the MMR-TE mode is an appropriate configuration for detecting contaminant plumes. The modeling experiments for the faulted porous medium also confirm that the MMR method is capable of mapping and monitoring the extent of contaminant plumes in aroundwater systems.展开更多
The strip with a time-dependent tension moves, namely a harmonically varying tension about a constant initial tension. The nonlinear vibration model of moving strip between two mills with time-dependent tension was es...The strip with a time-dependent tension moves, namely a harmonically varying tension about a constant initial tension. The nonlinear vibration model of moving strip between two mills with time-dependent tension was established. Approximate solutions were obtained using the method of multiple scales. Depending on the variation of the tension, three distinct cases arise： frequency away from zero or two times the natural frequency; frequency close to zero; frequency close to two times the natural frequency. For frequency close to zero and away from zero and two times the natural frequency, the system is always stable. For frequency close to two times the natural frequency, the stability is analyzed respectively when the trivial solution exists and the nontrivial solution exists. Numerical simulation was made on some 1660 mm tandem rolling mill, and the stable regions and unstable regions for parametric resonance are determined with different cases. The rolling speed and the thickness of strip have strong influences on the stability of principle parametric resonances. But the distance between two mills has little influence on the stability of principle parametric resonances.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.41877267,41877260)the Priority Research Program of the Chinese Academy of Science(Grant No.XDA13010201).
文摘Catastrophic failure in engineering structures of island reefs would occur when the tertiary creep initiates in coral reef limestone with a transition from short-to long-term load.Due to the complexity of biological structures,the underlying micro-behaviors involving time-dependent deformation are poorly understood.For this,an abnormal phenomenon was observed where the axial and lateral creep deformations were mutually independent by a series of triaxial tests under constant stress and strain rate conditions.The significantly large lateral creep deformation implies that the creep process cannot be described in continuum mechanics regime.Herein,it is hypothesized that sliding mechanism of crystal cleavages dominates the lateral creep deformation in coral reef limestone.Then,approaches of polarizing microscope(PM)and scanning electronic microscope(SEM)are utilized to validate the hypothesis.It shows that the sliding behavior of crystal cleavages combats with conventional creep micro-mechanisms at certain condition.The former is sensitive to time and strain rate,and is merely activated in the creep regime.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 10374119 and 10674154）, and The 0ne- Hundred-Talents Project of Chinese Academy of Science.Acknowledgments We gratefully acknowledge Professor Ding P Z and Professor Liu X S for their hospitality and help in symplectic algorithm.
文摘A pseudospectral method with symplectic algorithm for the solution of time-dependent Schrodinger equations （TDSE） is introduced. The spatial part of the wavefunction is discretized into sparse grid by pseudospectral method and the time evolution is given in symplectic scheme. This method allows us to obtain a highly accurate and stable solution of TDSE. The effectiveness and efficiency of this method is demonstrated by the high-order harmonic spectra of one-dimensional atom in strong laser field as compared with previously published work. The influence of the additional static electric field is also investigated.
基金financially supported by the Scientific Research Foundation of North China University of Technology(Grant Nos.11005136024XN147-87 and 110051360024XN151-86).
文摘With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this paper.Using symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential equation.The results in this paper depend on all the oceanic variable coefficients in that equation.
文摘The VRP is classified as an NP-hard problem. Hence exact optimization methods may be difficult to solve these problems in acceptable CPU times, when the problem involves real-world data sets that are very large. To get solutions in determining routes which are realistic and very close to the actual solution, we use heuristics and metaheuristics which are of the combinatorial optimization type. A literature review of VRPTW, TDVRP, and a metaheuristic such as the genetic algorithm was conducted. In this paper, the implementation of the VRPTW and its extension, the time-dependent VRPTW (TDVRPTW) has been carried out using the model as well as metaheuristics such as the genetic algorithm (GA). The algorithms were implemented, using Matlab and HeuristicLab optimization software. A plugin was developed using Visual C# and DOT NET framework 4.5. Results were tested using Solomon’s 56 benchmark instances classified into groups such as C1, C2, R1, R2, RC1, RC2, with 100 customer nodes, 25 vehicles and each vehicle capacity of 200. The results were comparable to the earlier algorithms developed and in some cases the current algorithm yielded better results in terms of total distance travelled and the average number of vehicles used.
文摘In this paper, we present a new algorithm of the time-dependent shortest path problem with time windows. Give a directed graph , where V is a set of nodes, E is a set of edges with a non-negative transit-time function . For each node , a time window ?within which the node may be visited and ?, is non-negative of the service and leaving time of the node. A source node s, a destination node d and a departure time?t0, the time-dependent shortest path problem with time windows asks to find an s, d-path that leaves a source node s at a departure time t0;and minimizes the total arrival time at a destination node d. This formulation generalizes the classical shortest path problem in which ce are constants. Our algorithm of the time windows gave the generalization of the ALT algorithm and A* algorithm for the classical problem according to Goldberg and Harrelson [1], Dreyfus [2] and Hart et al. [3].
基金supported by the intramural research program(IRP)of the Eunice Kennedy Shriver National Institute of Child Health and Human Development。
文摘The field of diffusion micro structural magnetic resonance(MR)aims to probe timedependent diffusion,i.e.,an ensemble-averaged mean-squared displacement that is not linear in time.This time-dependence contains rich information about the surrounding microenvironment.MR methods to measure time-dependent diffusion quantitatively,however,require either non-standard pulse sequences,such as oscillating gradients,or make non-physical assumptions,such as infinitely narrow gradient pulses.Here,we argue that standard spin echo and stimulated echo MR sequences can be used to probe directly.In particular,we propose a framework in which the log-signal ratio obtained from a pair of measurements with different inter-pulse spacingΔis proportional to the MSD between these twoΔvalues along the gradient direction x:-.The framework is quantitative for short,finite-duration gradient pulses and under the Gaussian phase approximation(GPA).To validate the framework,we consider onedimensional diffusion between impermeable,parallel planes,as well as periodicallyspaced,permeable planes.Excellent agreement is obtained between the estimation and the ground truth in the regime where the GPA is expected to hold.Importantly,the GPA can be made to hold for any underlying microstructure,making the proposed framework widely applicable.
文摘This article first outlines the fundamental definitions of Mycoplasma pneumoniae and the basic principles of antibiotics. It then analyzes and discusses the progress in antibiotic application and time-eff ect studies for neonatal pneumonia treatment, specifically comparing conventional antibiotic therapy with stepwise treatment regimens, and contrasting monotherapy with penicillin, monotherapy with cephalosporins, and combination therapy. Finally, it offers a prospective outlook on antibiotic application and time-effect research in neonatal pneumonia treatment, aiming to provide valuable reference for further scholarly investigations.
基金Projects(U24B20113,42477162) supported by the National Natural Science Foundation of ChinaProject(2025C02228) supported by the Primary Research and Development Plan of Zhejiang Province,China。
文摘Heat transfers at the interface of adjacent saturated soil primarily through the soil particles and the water in the voids.The presence of water induces the contraction of heat flow lines at the interface,leading to the emergence of the thermal contact resistance effect.In this paper,four thermal contact models were developed to predict the thermal contact resistance at the interface of multilayered saturated soils.Based on the theory of thermal-hydro-mechanical coupling,semi-analytical solutions of thermal consolidation subjected to time-dependent heating and loading were obtained by employing Laplace transform and its inverse transformation.Thermal consolidation characteristics of multilayered saturated soils under four different thermal contact models were discussed,and the effects of thermal resistance coefficient,partition thermal contact coefficient,and temperature amplitude on the thermal consolidation process were investigated.The outcomes indicate that the general thermal contact model results in the most pronounced thermal gradient at the interface,which can be degenerated to the other three thermal contact models.The perfect thermal contact model overestimates the deformation of the saturated soil during the thermal consolidation.Moreover,the effect of temperature on consolidation properties decreases gradually with increasing interfacial contact thermal resistance.
文摘The Zagros Basin in southwestern Iran is a significant source of coal,with numerous coal mines operating in the region.Ensuring the stability of coal mines is crucial for safe and efficient mining operations.This study investigates the time-varying response of rocks and roof resistance in coal mines in the Zagros Mountains using a novel approach that combines numerical simulation,relaxation testing,and rock displacement studies.The results show that rocks exhibit significant time-dependent behavior,with changes in rock mechanical properties over time.A comprehensive viscoelastic-plastic model is devel-oped to accurately describe the time-varying strain-softening response of rocks and simulate laboratory tests.The model integrates the Burgers and strain-softening models,simulating stress relaxation curves and rock displacement over time.The study reveals that the rock mass displays significant nonlinear behavior,with changes in rock mechanical properties over time.The findings of this study highlight the importance of considering the time-varying response of rocks and roof resistance in coal mine stability analysis.The results provide valuable insights into the time-dependent behavior of rock mass in coal mines in Iran,which can inform mining practices and mitigate potential hazards.Results in this study can contribute to developing strategies for improving roof stability and reducing the likelihood of roof collapses.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金supported by the National Natural Science Foundation of China (No. 10871156)the Program for New Century Excellent Talents in University (No. NCET-06-0829)
文摘Local and parallel finite element algorithms based on two-grid discretization for the time-dependent convection-diffusion equations are presented. These algorithms are motivated by the observation that, for a solution to the convection-diffusion problem, low frequency components can be approximated well by a relatively coarse grid and high frequency components can be computed on a fine grid by some local and parallel proce- dures. Hence, these local and parallel algorithms only involve one small original problem on the coarse mesh and some correction problems on the local fine grid. One technical tool for the analysis is the local a priori estimates that are also obtained. Some numerical examples are given to support our theoretical analvsis.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFA1602502)the National Natural Science Foundation of China(Grant No.12450404)。
文摘We present a fully time-dependent quantum wave packet evolution method for investigating molecular dynamics in intense laser fields.This approach enables the simultaneous treatment of interactions among multiple electronic states while simultaneously tracking their time-dependent electronic,vibrational,and rotational dynamics.As an illustrative example,we consider neutral H_(2)molecules and simulate the laser-induced excitation dynamics of electronic and rotational states in strong laser fields,quantitatively distinguishing the respective contributions of electronic dipole transitions(within the classical-field approximation)and non-resonant Raman processes to the overall molecular dynamics.Furthermore,we precisely evaluate the relative contributions of direct tunneling ionization from the ground state and ionization following electronic excitation in the strong-field ionization of H_(2).The developed methodology shows strong potential for performing high-precision theoretical simulations of electronic-vibrational-rotational state excitations,ionization,and dissociation dynamics in molecules and their ions under intense laser fields.
基金supported in part by the National Key Research and Development Program of China(2023YFC3011100)the National Natural Science Foundation of China(62476294)+1 种基金the Science and Technology Planning Project of Guangdong Province,China(2021B1212040017)the Guangdong Basic and Applied Basic Research Foundation(2025A1515010377,2023A1515110697).
文摘In recent years,numerous recurrent neural network(RNN)models have been reported for solving time-dependent nonlinear optimization problems.However,few existing RNN models simultaneously involve nonlinear equality constraints,direct discretization,and noise suppression.This limitation presents challenges when existing models are applied to practical engineering problems.Additionally,most current discrete-time RNN models are derived from continuous-time models,which may not perform well for solving essentially discrete problems.To handle these issues,a robust direct-discretized RNN(RDD-RNN)model is proposed to efficiently realize time-dependent optimization constrained by nonlinear equalities(TDOCNE)in the presence of various time-dependent noises.Theoretical analyses are provided to reveal that the proposed RDD-RNN model possesses excellent convergence and noise-suppressing capability.Furthermore,numerical experiments and manipulator control instances are conducted and analyzed to validate the superior robustness of the proposed RDD-RNN model under various time-dependent noises,particularly quadratic polynomial noise.Eventually,small target detection experiments further demonstrate the practicality of the RDD-RNN model in image processing applications.
文摘In this paper, Homotopy Analysis method with Genetic Algorithm is presented and used to obtain an analytical solution for the time-dependent Emden-Fowler type of equations and wave-type equation with singular behavior at x = 0. The advantage of this single global method employed to present a reliable framework is utilized to overcome the singularity behavior at the point x = 0 for both models. The method is demonstrated for a variety of problems in one and higher dimensional spaces where approximate-exact solutions are obtained. The results obtained in all cases show the reliability and the efficiency of this method.
基金National Key Research and Development Program of China,No.2023YFC3006704National Natural Science Foundation of China,No.42171047CAS-CSIRO Partnership Joint Project of 2024,No.177GJHZ2023097MI。
文摘Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金the National Key Research and Development Program of China(Grant No.2022YFF0711400)which provided valuable financial support and resources for my research and made it possible for me to deeply explore the unknown mysteries in the field of lunar geologythe National Space Science Data Center Youth Open Project(Grant No.NSSDC2302001),which has not only facilitated the smooth progress of my research,but has also built a platform for me to communicate and cooperate with experts in the field.
文摘Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.
基金Supported by the Program to Sponsor Teams for Innovation in the Construction of Talent Highlands in Guangxi Institutions of Higher Learning (Grant No. 200508)Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry (Grant No. 200889016).
文摘We present a forward-modeling investigation of time-dependent ground magnetometric resistivity （MMR） anomalies associated with transient leachate transport in groundwater systems. Numerical geo-electrical models are constructed based on the hydrological simulation results of leachate plumes from a highly conceptualized landfill system and the resultant MMR responses are computed using a modified finite difference software MMR2DFD. Three transmitter configurations （i.e., single source, MMR-TE, and MMR-TM modes） and two hydrological models （i.e., uniform and faulted porous media） are considered. Our forward modeling results for the uniform porous medium indicates that the magnetic field components perpendicular to the dominant current flow contain the most information of the underground targets and the MMR-TE mode is an appropriate configuration for detecting contaminant plumes. The modeling experiments for the faulted porous medium also confirm that the MMR method is capable of mapping and monitoring the extent of contaminant plumes in aroundwater systems.
基金Item Sponsored by National Natural Science Foundation of China (50875231)Great Natural Science Foundation of Hebei Province of China (E2006001038)
文摘The strip with a time-dependent tension moves, namely a harmonically varying tension about a constant initial tension. The nonlinear vibration model of moving strip between two mills with time-dependent tension was established. Approximate solutions were obtained using the method of multiple scales. Depending on the variation of the tension, three distinct cases arise： frequency away from zero or two times the natural frequency; frequency close to zero; frequency close to two times the natural frequency. For frequency close to zero and away from zero and two times the natural frequency, the system is always stable. For frequency close to two times the natural frequency, the stability is analyzed respectively when the trivial solution exists and the nontrivial solution exists. Numerical simulation was made on some 1660 mm tandem rolling mill, and the stable regions and unstable regions for parametric resonance are determined with different cases. The rolling speed and the thickness of strip have strong influences on the stability of principle parametric resonances. But the distance between two mills has little influence on the stability of principle parametric resonances.
