Search results

The purpose of this paper is to investigate the literature on the treatment of primary pupils and inspecting the role of environmental psychology, e-learning, learning style and school design on the behavior of students in elementary schools.

A questionnaire was designed to evaluate the components of the model. Experts with significant experiences in the field of students’ behavior revised the surveys. Data were collected from 400 teachers of the elementary schools in Iran. The SMART-PLS 3.2 and SPSS 22 software package were used in the field of questionnaires’ statistical analysis.

Findings confirmed the suggested model’s validity for elementary students’ behavior assessment. The consequences of this research illustrated the effect of environmental psychology on the behavior of elementary students. In addition, the authors were concluded that intention to e-learning has a significant role in developing the action and behavior of the elementary students. Moreover, the learning style has an affirmative and considerable impact on the behavior of elementary students. Finally, school design has an affirmative and significant effect on the manner of the elementary students.

The consequences of this research have provided some traces about the basic perspectives, which have to be in the center of attention of administrators. For instance, school design and learning style sound to be a decisive mechanism for improving action and learning behavior. In addition, educational leaders may use the findings to evaluate their school facilities and define where developments will have the most significant impact or planners may use the results to assist architects in the design and construction of new educational services.

This study builds a valuable contribution by focusing on pupil environmental psychology, e-learning, learning style and school design in elementary schools by enlightening the connection between them and students’ manner.

In public health emergencies, seeking confirmed cases’ activity trajectory information (CCATI) is crucial to the public’s efforts to combat the epidemic. The public can stabilize their sentiments and mitigate the risk of cross-infection by obtaining CCATI. We investigated the factors influencing users' intentions to seek CCATI to enhance the government’s risk communication capabilities and improve information platform services.

We analyzed how information ecological factors affect the intention to seek CCATI through perceived value. Data was collected from 429 Chinese citizens during the fourth wave of the coronavirus disease 2019 (COVID-19) pandemic. We used the structural equation model technology and bootstrap mediation effect test to examine the model.

Information understandability, information relevance, perceived severity and perceived vulnerability directly and positively affect the intention of seeking CCATI. While, the above relationships are also partially mediated by emotional value and functional value. Social support directly and negatively affects the intention of seeking CCATI, while the relationship is also partially mediated by emotional value and functional value. Curiosity directly and positively affects the intention of seeking CCATI, while the relationship is also partially mediated by emotional value. The relationship between the quality of the search service and the intention of seeking CCATI is not significant, instead, it is fully mediated by functional value. The influence effect of information relevance on the intention of seeking CCATI is the greatest, followed by perceived vulnerability. The mediating effect of functional value is higher than emotional value.

The findings may help governments enhance their risk communication capabilities and improve epidemic prevention and control measures, enhancing the appeal of information platforms.

We focused on CCATI, an area with limited scholarly attention. We analyzed CCATI-seeking factors using an information ecology theory, introducing perceived value as a mediator, thus offering novel perspectives and models.

This paper aims to improve performance prediction and to acquire more detailed flow structures so as to analyze the turbulence in complex rotor-stator flow.

Hydraulic retarder as typical fluid machinery was numerically investigated by using hybrid Reynolds-averaged Navier–Stokes (RANS)/large eddy simulation (LES) models CIDDES Algebraic Wall-Modeled Large Eddy Simulation (LES) (WMLES) S-Ω and dynamic hybrid RANS/LES (DHRL). The prediction results were compared and analyzed with a RANS model shear stress transport (SST) k-omega which was a recommended choice in engineering.

The numerical results were verified by experiment and indicated that the predicted values for three hybrid turbulence models were more accurate. Then, the transient flow field was further analyzed visually in terms of turbulence statistics, Reynolds number, pressure-streamline, vortex structure and eddy viscosity ratio. The results indicated that HRL approaches could capture unsteady flow phenomena.

This study achieves both in performance prediction improvement and better flow mechanism understanding. The computational fluid dynamics (CFD) could be used instead of flow visualization to a certain extent. The improved CFD method, the fine computational grid and the reasonable simulation settings jointly enhance the application of CFD in the rotor-stator flow.

The improvement was quite encouraging compared with the reported literatures, contributing to the CFD playing a more important role in the flow machinery. DHRL provided the detailed explanation of flow transport between rotor and stator, which was not reported before. Through it, the flow mechanism can be better understood.

The paper aims to construct a method to simulate the relationship between the parameters of soil properties and the area of sliding mass of the true slip surface of a landslide.

The smoothed particle hydrodynamics (SPH) algorithm is used to calibrate a response surface function which is adopted to quantify the area of sliding mass of the true slip surface for each failure sample in Monte Carlo simulation. The proposed method is illustrated through a homogeneous and a heterogeneous cohesive soil slope.

The comparison of the results between the proposed method and the traditional method using the slip surface with minimum factor of safety (FS_min) to quantify the failure consequence has shown that the landslide risk tends to be attributed to a variety of risk sources, and that the use of a slip surface with FS_min to quantify the consequence of a landslide underestimates the landslide risk value. The difference of the risk value between the proposed method and the traditional method increases dramatically as the uncertainty of soil properties becomes significant.

A geotechnical engineer could use the proposed method to perform slope failure analysis.

The failure consequence of a landslide can be rationally predicted using the proposed method.

This study aims to improve the accuracy of hyperspectral estimation of soil organic matter content.

Based on the uncertainty in spectral estimation, 76 soil samples collected in Zhangqiu District, Jinan City, Shandong Province, were studied in this paper. First, the spectral transformation of the spectral data after denoising was carried out by means of 11 transformation methods such as reciprocal and square, and the estimation factor was selected according to the principle of maximum correlation. Secondly, the grey weighted distance was used to calculate the grey relational degree between the samples to be estimated and the known patterns, and the local linear regression estimation model of soil organic matter content was established by using the pattern samples closest to the samples to be identified. Thirdly, the models were optimized by gradually increasing the number of modeling samples and adjusting the decision coefficient, and a comprehensive index was constructed to determine the optimal predicted value. Finally, the determination coefficient and average relative error are used to evaluate the validity of the model.

The results show that the maximum correlation coefficient of the seven estimated factors selected is 0.82; the estimation results of 14 test samples are of high accuracy, among which the determination coefficient R² = 0.924, and the average relative error is 6.608%.

Studies have shown that it is feasible and effective to estimate the content of soil organic matter by using grey correlation local linear regression model.

The paper succeeds in realizing both the soil organic matter hyperspectral grey relation estimating pattern based on the grey relational theory and the estimating pattern by using the local linear regression.

This study aims to analyze passenger service quality in Beijing West Railway Station from the perspective of passengers, to better understand the current service quality and obtain the areas of weakness for improvement.

The research investigates the passenger experience of service in Beijing West Railway Station by using a questionnaire survey. The service quality (SERVQUAL) evaluation method is used to analyze the survey data, and it divides the passenger service into 5 attributes with 20 indicators. This research uses the Likert five-level scale method to process data and calculates the SERVQUAL value and weight difference of each attribute to evaluate the passenger service. Therefore, the deficiencies have been pointed out, so the station manager can improve the passenger service accordingly.

It is indicated that among the five studied attributes, Beijing West Railway Station has the smallest service quality value in terms of timeliness, which means this part needs the largest improvement. To the five attributes, each lacks in station security check, ticketing efficiency, station identification accuracy, emergency processing of train delays and the restroom environment, respectively.

The research can provide specific suggestions for the optimization of the passenger service of Beijing West Railway Station, and provide reference information for the formulation of policies.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

The differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array.

The authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array.

This paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance.

In this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.

This study aims to analyze the influence of farmers’ degree of participation in collective action on their adoption decisions and waiting time regarding soil and water conservation (SWC) measures.

The Probit model and Generalized Propensity Score Match method are used to assess the effect of the degree of participation in collective action on farmers’ adoption decisions and waiting time for implementing SWC measures.

The findings reveal that farmers’ engagement in collective action positively influences the decision-making process regarding terrace construction, water-saving irrigation and afforestation measures. However, it does not significantly impact the decision-making process for plastic film and ridge-furrow tillage practices. Notably, collective action has the strongest influence on farmers’ adoption decisions regarding water-saving irrigation technology, with a relatively smaller influence on the adoption of afforestation and terrace measures. Moreover, the results suggest that participating in collective action effectively reduces the waiting time for terrace construction and expedites the adoption of afforestation and water-saving irrigation technology. Specifically, collective action has a significantly negative effect on the waiting time for terrace construction, followed by water-saving irrigation technology and afforestation measures.

The results of this study underscore the significance of fostering mutual assistance and cooperation mechanisms among farmers, as they can pave the way for raising funds and labor, cultivating elite farmers, attracting skilled labor to rural areas, enhancing the adoption rate and expediting the implementation of terraces, water-saving irrigation technology and afforestation measures.

Drawing on an evaluation of farmers’ degree of participation in collective action, this paper investigates the effect of participation on their SWC adoption decisions and waiting times, thereby offering theoretical and practical insights into soil erosion control in the Loess Plateau.

The purpose of this paper is to analyze the time-dependent reliability of harmonic drive.

The transient finite element analysis (FEA) of harmonic drive is established to calculate the stress under different loads. Combined with the residual strength model and random variables, the time-dependent reliability model of harmonic drive is deduced by the stochastic perturbation method and Edgeworth series. Based on accelerated life tests, the degradation parameters are estimated by maximizing likelihood function. Under variable load, the key stress from transient FEA is transformed into probability density function by kernel density estimation, and the residual strength model is modified by adding adjustment factors to deal with strength degradation under different loads.

The critical position of stress concentration from transient FEA is consistent with the fatigue fracture position at the accelerated life test sample. Compared with the time-dependent reliability method with equivalent circular-shell static stress or empirical degradation parameters, the proposed method has the smallest prediction error of failure life. Under variable load, the state function should be expanded to second-order series for avoiding error items relevant to variance. The failure life expectation under random variable load is smaller than that under constant load.

The time-dependent reliability method of harmonic drive is firstly proposed under constant and variable load. The transient FEA of harmonic drive is established to calculate the stress for strength analysis. The accelerated life test of harmonic drive is conducted for degradation parameters estimation. The adjustment factor is added to the residual strength model for strength degradation under different loads.