Time-varying Characteristics Research Articles

Sensor-Based Human Activity Recognition Based on Multi-Stream Time-Varying Features With ECA-Net Dimensionality Reduction

Sensor-Based Human Activity Recognition Based on Multi-Stream Time-Varying Features With ECA-Net Dimensionality Reduction

Research on the Mechanism of Dynamic Monitoring of Undergraduate Students’ Learning Situation and Adaptive Adjustment of Teaching Mode--Based on the Perspective of Educational Evaluation Reform

Abstract Dynamic monitoring of undergraduate learning is a tool for the accurate pulse of education and teaching, and an in-depth study of the quality monitoring data of students’ learning can discover the hidden problems and shortboards in education and teaching. The article utilizes information technology to build a dynamic monitoring platform for undergraduates. Then, it establishes an accurate teaching model for undergraduates with the assistance of this platform. The SHAP interpretable model is used to obtain the online learning behavior characteristics of undergraduates, and the LSTM autocoder is used to construct the time-varying feature sequence of undergraduates’ learning behavior, which is inputted into the LSTM model to establish the undergraduate learning situation early warning model. Taking the data of students’ online behavioral characteristics as an example, the validation of the importance of undergraduate learning behavioral characteristics and early warning is carried out, and the effect of the precise teaching model is also analyzed. The SHAP value of undergraduate students taking online tests is 0.969, which significantly impacts their online learning behavior. The accuracy of undergraduate students’ learning alert was 0.822, which was about 3.53% higher than the FWTS-CNN model with sub-optimal performance, and the results of the learning adaptability retest were 3.24 points higher than the initial test results. From the perspective of educational evaluation reform, combining undergraduate students’ learning dynamic monitoring data can enable adaptive adjustment of teaching content and mode.

Multi-source microwave heating temperature uniformity study based on adaptive dynamic programming

Abstract In view of the multi-physical field coupling and time-varying characteristics of the microwave heating medium process, how to dynamically plan the state characteristics of multiple microwave sources and optimize the material temperature uniformity becomes the focus of this article. To this end, first, algebraic graph theory is used to construct the multiple microwave sources as a multi-agent system, and a perfect communication topology is established to ensure the transfer and sharing of information. Second, according to the real-time temperature distribution of the material, an event-triggered adaptive dynamic planning algorithm is used to co-operate with the power input of the multiple microwave sources to ensure that no new hot spots are generated during the optimization of the temperature distribution using the self-organizing properties of the medium. Finally, a numerical calculation model for optimizing a mixture of integer and continuous variables is solved using the finite-element method. The experimental and numerical results show that this article improves the temperature uniformity by 32.4–73.5% and the heating efficiency by 14.3–39.4% compared to the generic heating model, and the feasibility of the method is verified by the different shapes of the heated material.

Numerical analysis of plasma channel characteristics and dynamic effects on molten pool in electrical discharge machining

The plasma channel provides the fundamental energy source and acting forces for material removal in electrical discharge machining (EDM). At present, the research on the characteristics of plasma channel is still in the exploratory stage. In this study, to clearly understand the characteristics of plasma channel and its dynamic effects on molten material, the transient mathematical model of plasma channel is first attempted and computed based on magneto-hydrodynamics (MHD). The breakdown process of plasma channel, as well as its inherent characteristics (heat flux, electromagnetic force and expansion pressure) are studied, based on which the dynamic effects of thermal input and force actions on anode molten pool are analyzed. Results show that the plasma channel sequentially experiences diabolo-shaped, lantern-shaped and finally stabilized horn-shaped stages, and the diameter expansion is nearly completed within 2μs which is independent of discharge current. The plasma channel presents time-variant characteristics in terms of heat flux distribution and energy distribution ratio into electrodes and gap dielectric. The electromagnetic force and expansion pressure not only determine the geometry evolution of plasma channel but also provide acting forces, which influence the distribution of hydrostatic pressure in molten pool and shear force on the interface. For preliminary verification purpose, the appearance of plasma channel is observed by high-speed photography, and the dimensions between simulation and experimental craters are compared. The feasibility of established plasma channel model is confirmed to a certain extent by showing an approximated channel appearance, as well as the maximal deviations of 10.8 % and 8.9 % in diameter and depth, respectively.

A time-varying copula approach for describing seasonality in multivariate ocean data

Characterizing multivariate ocean variables is quite critical for reliability design and risk assessment of marine structures. A robust, precise, and practical multivariate statistic model is necessary for comprehending ocean characteristics. As the time-varying characteristics exist in the ocean data, it is unreasonable to employ a simple constant statistical model to characterize all the multivariate data at one time. Therefore, in this paper, a time-varying copula approach is developed for modeling time-varying multivariate ocean data. Considering climate variations, a time-varying formula for return period and environment contour is also derived. The developed approach is demonstrated based on a site-specific ocean dataset collected from a buoy on the US coast. The climate effects associated with the multivariate ocean variables are characterized. The developed time-varying copula approach is also compared to the conventional copula and the conditional model in estimating the return period. The results showed that the time-varying model is helpful to explore the most critical environmental conditions for marine structures.

Linkage Analysis of Business Administration and Organisational Effectiveness of Enterprises Applying the ARMA Model

Abstract In this paper, we first study the ARMA model and its derivative models, smooth the non-stationary time series by order difference, and estimate the coefficients of the ARMA model by the method of moment estimation. Then, hypothesis testing is conducted based on serial correlation of the relationship between corporate business administration and organizational effectiveness. In the process of hypothesis testing, the empirical likelihood method is used to test the serial correlation of the residual terms under weak hypotheses, which is then extended to apply to the test case where the residual terms contain finite and infinite variances. Finally, based on the model, we assessed the level of business administration and organizational effectiveness of Enterprise H, explored the correlation between the two, and analyzed the linkage effect between business administration and organizational effectiveness. The results show that there is a significant positive correlation between the dimensions of business administration and organizational effectiveness of enterprises, r=0.754-0.864, P<0.01. The correlation coefficients between the two fluctuate between 0.4 and 0.8 for a long period of time, with significant time-varying characteristics.

Chip formation mechanism in milling metallic glasses based on Drucker-Prager (D-P) constitutive model

In this paper, further in-depth research on chip formation mechanism is conducted on the cutting of metallic glasses. The study of chips contributes to a better understanding of the machining nature of materials, which is of significant importance for improving product quality, reducing energy consumption, and resource utilization. This paper employs a combination of simulation and experimental methods, wihch not only analyzes the mechanism of chip formation in depth, but also investigates the time-varying characteristics of cutting forces. The results indicate that, when comparing simulation with experiments, the average error in cutting forces is 7.62%, and the chip morphology is also quite similar. Observations in the simulation show that as the cutting thickness increases from 7.96 μm to 23.87 μm, the free surface of the chip exhibits serrated features, and the main shear zone of the chip becomes clearer. Cutting forces exhibit periodic variations, with alternating peaks and valleys representing the formation of shear zones in the chip. In the experiment, observed chips displays a wrinkled free surface and a smooth non-free surface, with some chip edges exhibiting a burr phenomenon. By selecting appropriate machining parameters, the generation of secondary shear bands on the free surface was effectively reduced. By observing the chip morphology, it is found that the chip formation is accompanied by the material removal of plasticity and brittleness, which is the result of the combined action of heat, stress, and free volume. It should be considered to lower temperature to reduce the phenomenon of chip adhesion, providing guidance for further optimizing the cutting process of metallic glass. This paper can provide to readers further understanding of the chip formation mechanism in milling metal glass.

Characteristic Quantity Analysis of Single-Phase Contact Tree Ground Fault of Distribution Network Overhead Lines

When the overhead line passes through the forest area, the conductor may contact the line to induce the tree-contact single-phase-to-ground fault (TSF), and the persistence of TSF may induce wildfires, bringing serious consequences. However, the amount of TSF electrical features is weak, and traditional protection devices cannot operate effectively, so it is urgent to obtain typical characteristics of TSF. In this study, the simulation experiment is carried out for the tree-contact single-phase-to-ground fault. Firstly, the relativity between fault and characteristics like zero-sequence voltage, zero-sequence current, and differential current are analyzed theoretically. Then, the simulation experiment platform of TSF is built, and the time-varying fault characteristics are acquired. The experimental results show that the average value of the zero-sequence voltage, the amplitude of the power-frequency component of the zero-sequence current, and the amplitude of the power-frequency component of the first and end differential current can accurately reflect the fault current development trend of the single-phase contact tree fault of the conductor, and can be used as the typical characteristic quantity of TSF. The results of this study are helpful for further understanding the fault characteristics of TSF and provide theoretical support for the identification and protection design of TSF.

Meteorological to Agricultural Drought Propagation Time Analysis and Driving Factors Recognition Considering Time-Variant Characteristics

Meteorological to Agricultural Drought Propagation Time Analysis and Driving Factors Recognition Considering Time-Variant Characteristics

Research on roll temperature compensation of variable domain fuzzy controller based on improved cat swarm optimization

In the hot rolling process, the hot crown of the roll is determined by the roll temperature and the temperature distribution. Furthermore, the hot crown is an important factor, which causes variation in the strip gage along the plane perpendicular to the rolling direction, affecting the strip quality. However, the roll temperature response has the characteristics of nonlinearity, hysteresis and time-varying, which makes it difficult to control accurately by classical control theory and method. In order to accurately control the rolling temperature, a variable universe fuzzy controller based on improved cat swarm optimization (ICSO-VUFC) was established. Firstly, a dynamic mixture ratio and an improved tracking mode were used to improve the optimization capability of the cat swarm. In comparison with the conventional cat swarm optimization (CSO) controller, the proposed process showed better optimization performance. Secondly, a simulation analysis based on MATLAB was employed to compare the ICSO-VUFC with the conventional fuzzy controller (C-FC) and the fuzzy controller based on the improved cat swarm optimization (ICSO-FC). The results reveal that the ICSO-VUFC exhibits the best dynamic and steady performance. Finally, the temperature control accuracy of the rolled regions during different rolling passes under the three fuzzy controllers was examined and compared. The results show that the ICSO-VUFC exhibits the highest control accuracy and stability with a temperature error range of ±4 °C. Through the analysis of the strip crown, it can be seen that the control accuracy of the strip crown can be effectively improved by using ICSO-VUFC to control the roll temperature distribution.

Calculation method for composite modulus of flexible pile composite foundation for high-speed railway under post-work settlement source

The flexible pile composite foundation (FPCF) in deep soft soil regions often experiences post-work settlement, leading to rail irregularities in the high-speed railway (HSR). However, few studies have identified the characteristics of post-work settlement sources (PWSS) for FPCF. Hence, a calculation method for the composite modulus under the PWSS has yet to be established. Based on a full-scale field test of the FPCF for a high-speed railway (HSR), this study analysed the time-varying characteristics of the settlement and location of the PWSS. By analysing the properties of soft soil materials and the additional stress on FPCF, the formation mechanisms of PWSS were revealed. A 3D finite element model (FEM) of the FPCF-subgrade-ballastless track system was established, and the settlement curve was input at the location of the PWSS. The rationality of the numerical results was first verified through a scale-model experiment. Subsequently, based on the computational results of typical settlement transfer processes, it was found that settlement undergoes fast settlement, transitional following settlement, and following settlement during its transfer from the underlying layer to the rail. During the settlement transfer process, the reinforcement zone and embankment significantly reduced the settlement irregularities, which made the settlement of the ballastless track follow that of the subgrade bed. The pile compression modulus primarily regulated the rail amplitude, whereas the area replacement ratio primarily regulated the rail wavelength. Finally, based on the settlement transfer results, a method for determining the composite modulus was proposed, and a formula for calculating the composite modulus was derived. This formula contributes to a faster analysis of the influence of the PWSS of the FPCF on rail smoothness.

Climate risk performance and returns integration of Chinese listed energy companies

Traditional energy and new energy stock returns are becoming more closely related under the energy transition constraint. In this paper, the core correlation between traditional energy stock returns and new energy stock returns in China is portrayed using the minimum spanning tree (MST) approach and the integration characteristics of energy companies are dynamically analyzed. On this basis, we identify the impact of climate factors on the integration of energy markets by constructing a GARCH-MIDAS model with three dimensions: climate concern, climate physical risk, and climate policy. We find that returns are more likely to be transmitted within traditional energy industries and new energy industries, and firms with the same characteristics tend to form clusters. In a dynamic context, the degree of energy system integration has significant time-varying characteristics and is susceptible to unforeseen events, market policies, and supply-demand relationships. In addition, there is heterogeneity in the effect of climate concern on the integration between traditional energy and new energy markets, and the effects of both climate physical risk and climate policy on the integration of the energy system are significantly negative.

Time-varying characteristics of saturated hydraulic conductivity in grassed swales based on the ensemble Kalman filter algorithm —A case study of two long-running swales in Netherlands

Saturated hydraulic conductivity (Ks) of the filler layer in grassed swales are varying in the changing environment. In most of the hydrological models, Ks is assumed as constant or decrease with a clogging factor. However, the Ks measured on site cannot be the input of the hydrological model directly. Therefore, in this study, an Ensemble Kalman Filter (EnKF) based approach was carried out to estimate the Ks of the whole systems in two monitored grassed swales at Enschede and Utrecht, the Netherlands. The relationship between Ks and possible influencing factors (antecedent dry period, temperature, rainfall, rainfall duration, total rainfall and seasonal factors) were studied and a Multivariate nonlinear function was established to optimize the hydrological model. The results revealed that the EnKF method was satisfying in the Ks estimation, which showed a notable decrease after long-term operation, but revealed a recovery in summer and winter. After the addition of Multivariate nonlinear function of the Ks into hydrological model, 63.8% of the predicted results were optimized among the validation events, and compared with constant Ks. A sensitivity analysis revealed that the effect of each influencing factors on the Ks varies depending on the type of grassed swale. However, these findings require further investigation and data support.

The Time-Varying Variation Characteristics of Methane during Nitrogen Injection Process: An Experimental Study on Bituminous Coals

The existing research on CH4 displacement by N2 mainly focuses on the gas injection displacement mechanism and the factors affecting displacement efficiency. And most of them are theoretical analyses at the model level or multifactor analyses at the simulation test level, while there are few targeted physical simulation tests and quantitative analyses. Given the above problems, the experiment system was used to study the gas migration evolution law and time-varying characteristics of CH4 displacement by N2 in coal under different injection pressures. The experimental results show that the whole process of CH4 displacement by N2 can be divided into three stages: stage I (original equilibrium stage); stage II (dynamic balance stage); stage III (new equilibrium stage). The concentration of CH4 and N2 presents an opposite variation trend, and the variation rate of CH4 and N2 increased first and then decreased. The breakthrough time was 50 minutes, 45 minutes, 35 minutes, 25 minutes, and 20 minutes, respectively, under different injection pressures. The displacement efficiency increased with the injection pressures, while the replacement ratio decreased with the injection pressures. The maximum flow rate of CH4 was 0.085 mL/min, 0.110 mL/min, 0.130 mL/min, 0.222 mL/min, and 0.273 mL/min, respectively, under different injection pressures. The accumulated production of CH4 was 3.59 mL, 3.91 mL, 4.39 mL, 5.58 mL, and 5.94 mL, respectively, under different injection pressures. The effective injection pressure range was 1.6~2 MPa. This research can provide a reference for the theoretical research of N2-ECBM-related technology in low permeability reservoirs and the selection of injection pressure in the field technology implementation.

Dynamics of nonlinear beam-propeller system with different numbers of blades

The dynamics of elastic systems coupled with rotating bladed-rotors is rich and complex, and the blade number may have an influence on the in-vacuo system dynamics. This paper aims to model its nonlinear dynamics in-vacuo and study the effects of blade number on its dynamics. To this end, a nonlinear model consisting of a nonlinear inextensible beam, a motor assembly and a rotating propeller is developed. This model is linearized, and modal analyses are performed with different blade numbers. It is validated numerically and experimentally that a two-bladed propeller introduces time-varying characteristics, while the system is time-invariant with more than two blades. For the two-bladed case, frequencies in the non-rotating condition split into two frequency loci with increasing rotational speed; while with more than two blades, one frequency in the non-rotating condition increases and the other in the same pair decreases with increasing speed. A structural instability due to frequency lock-in is identified in two-bladed configuration, while not identified with more than two blades. The static deformation using the nonlinear model is calculated and validated against the experiment. In the stable speed range, the frequency response functions calculated using the nonlinear and linearized models do not show notable differences. In the unstable speed range with two-bladed propeller, the nonlinear model is consistent with the experiment in terms of unstable frequencies and bounded steady-state oscillations. The system vibration in the unstable speed range features forward whirling pattern, in which the beam vibration is close to the first bending pattern.

Dynamic stiffness matrix perturbation theory for time-varying structural analysis

Matrix perturbation theory (MPT) is widely used in sensitivity analysis and reanalysis of structural eigenvalue problems when small changes are imposed on parameters. However, the conventional MPT based on the finite element method is only applicable to the cases with small parameter variations, and it is difficult to avoid cumulative errors caused by multi-step perturbations. A key issue for the application of MPT is how to evaluate the error of perturbation solution and correct the results during the process of multi-step perturbation solution. By invoking the dynamic stiffness method (DSM), Wittrick-Williams algorithm, and the precise integration method (PIM), in this paper, we propose an improved method with controllable accuracy, self-checking and elimination of accumulated errors, referred to as the dynamic stiffness matrix perturbation theory (DSMPT). In present method, the rationality of the results can be estimated preliminarily according to dynamic stiffness equation, which is not present in the original MPT, can greatly enhance the accuracy of the perturbation results and evaluate the errors. Case studies prove that the DSMPT combined with PIM provides a convenient way to realize accuracy self-inspection and rectification of the perturbation results, and the maximum relative error of eigenvalue and response can be controlled to be smaller than 0.2% and 0.025%, respectively. Besides, DSMPT can also be applied to the analysis of coupled and nonlinear dynamic system with time-varying modal characteristics. Finally, a thermally-induced vibration analysis of tensegrity modules during space deployment is taken as an example to further illustrate the advancements of the DSMPT in solving time-varying dynamic problems. Results show that the DSMPT effectuate an almost sixfold reduction in computational time.

CNN neural network temporal feature storage structure fusion for the visible channel equalization algorithm

The visible light communication channel has time-varying characteristics and is difficult to predict. This paper proposes an equalization algorithm based on the structure of a convolutional neural network (CNN), combining time series feature length and long short-term memory (LSTM), and adding a residual structure. It can be seen that the equalization coefficient vector of the optical channel is a time series, which can reflect the noise characteristics of the channel and has storage characteristics. The equalizer algorithm can accurately learn the complex channel characteristics and calculate the compensation coefficient according to the channel characteristics. It can also restore the original transmission signal. At the same time, this paper also examines the compensation method of the receiver in the mobile state. The long-term memory parameters of LSTM are used to represent the sequence causality in the memory channel, and CNN and residual structure are used to refine the results and improve the accuracy of the reconstruction. The simulation results show that the algorithm can effectively eliminate the influence of the fading characteristics of the visible optical channel, improve the bit error rate performance of system transmission, solve the overall problem of channel corruption, and precisely restore the original transmission signal with fast convergence speed. In addition, this method can achieve a better balance between performance and complexity compared to the traditional contention balancing method, which proves the potential and effectiveness of the proposed channel balancing method.

Numerical study of the axial compression strength for nano-reinforced filament-wound riser considering curing residual stress

The present study is dedicated to the numerical analysis of progressive failure damage in multiangle nano-reinforced filament wound risers, with due consideration for process-induced residual stresses. Utilizing a multi-model coupling strategy, we introduce an integrated methodology predicated upon the time-varying material characteristics at a macroscopic scale. Initially, the process-induced residual stresses are anticipated via a sequential coupled numerical simulation methodology based on the time-varying attributes of the material. Subsequently, the curing residual stresses serve as the initial stress for the composite wound riser to prognosticate its axial compressive strength, grounded in the progressive damage model. Finally, the multiparametric effects on the strength properties of the composite risers are further investigated to reveal the intrinsic mechanism. The numerical findings evince that curing-induced residual stress retards both fiber and matrix failure while augmenting the axial compressive strength of the composite riser. Furthermore, the escalation in nanoparticle content diminishes the process-induced residual stresses. Additionally, the incorporation of 5 % nanoparticles yields an enhancement in the strength of the composite risers by approximately 16.26 % relative to those devoid of nanoparticles.

The dynamic causality between Chinese and ASEAN stock markets

COVID-19 has caused severe shocks to the Chinese and ASEAN stock markets. This paper investigates the relationship between the Chinese and ASEAN stock markets using the bootstrap rolling-window causality test. The results show that there is a bidirectional Granger causality relationship between the Chinese and ASEAN stock markets with time-varying characteristics. Before the COVID-19 outbreak, the interaction between the Chinese and ASEAN stock markets was mainly positive. After the COVID-19 outbreak, during the off-peak period, the interaction between the Chinese and ASEAN stock markets was positive or negative at different periods; during the peak period of the epidemic, the ASEAN stock markets had negative impacts on the Chinese stock market. In addition, the relationship between the Chinese and ASEAN stock markets was enhanced during COVID-19. According to the interaction mechanism, economic and political factors would affect the relationship between the Chinese and ASEAN stock markets, but major events such as COVID-19 have a greater impact. Therefore, macroeconomic policy should play a positive role in the stock market.

Time-varying traffic load model of expressway based on long-term monitored data from multiple regions — A case in central and eastern China

Traffic load is one of the main loads borne by highway transportation infrastructure, which seriously impacts the safe operation of the bridge and road. Due to the change in the external environment and government policy, the traffic load has obvious time-varying characteristics, which is the key to establishing the real traffic load model. The two main time-varying factors of traffic load are the growth of traffic volume and the evolution of vehicle weight. In the long-term research work, there is a lack of research based on continuous monitoring data for the above two factors. Therefore, this paper carries out a study on the time-varying traffic load model of expressways based on long-term monitored data from multiple regions. Firstly, the data sources of monitored 18 expressways in central and eastern China are introduced. Secondly, the Logistic model is selected as the basic model to study the growth laws of expressways from different provinces; meanwhile, the evolution of vehicle weight distribution is also analyzed and a simplified model is established accordingly. Finally, a case study of a newly opened eight-lane expressway is operated to characterize the influence of time-varying vehicles. The results show that the traffic volume and vehicle weight distribution change significantly with the increase of service time. The Logistic model and liner model are appropriate to characterize the evolution model of the traffic volume and vehicle weight distribution separately. The time-varying characteristics of traffic load have a significant impact on the standard fatigue traffic load model and the cumulative equivalent axle loads. The research results could provide a reference for the establishment of time-varying traffic load standard models for highways and the revision of related standards. At the same time, it could provide technical support for the full life-cycle investigation and design of the road and bridge infrastructure.