Search results

Express freight transportation is in rapid development currently. Owing to the higher speed of express freight train, the deformation of the bridge deck worsens the railway line condition under the action of wind and train moving load when the train runs over a long-span bridge. Besides, the blunt car body of vehicle has poor aerodynamic characteristics, bringing a greater challenge on the running stability in the crosswind.

In this study, the aerodynamic force coefficients of express freight vehicles on the bridge are measured by scale model wind tunnel test. The dynamic model of the train-long-span steel truss bridge coupling system is established, and the dynamic response as well as the running safety of vehicle are evaluated.

The results show that wind speed has a significant influence on running safety, which is mainly reflected in the over-limitation of wheel unloading rate. The wind speed limit decreases with train speed, and it reduces to 18.83 m/s when the train speed is 160 km/h.

This study deepens the theoretical understanding of the interaction between vehicles and bridges and proposes new methods for analyzing similar engineering problems. It also provides a new theoretical basis for the safety assessment of express freight trains.

This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat transfer.

A brief review of current research on supercritical aviation kerosene is presented in views of the surrogate model of hydrocarbon fuels, chemical cracking mechanism of hydrocarbon fuels, thermo-physical properties of hydrocarbon fuels, turbulence models, flow characteristics and thermal performances, which indicates that more efforts need to be directed into these topics. Therefore, supercritical thermal transport of n-decane is then computationally investigated in the condition of thermal pyrolysis, while the ASPEN HYSYS gives the properties of n-decane and pyrolysis products. In addition, the one-step chemical cracking mechanism and SST k-ω turbulence model are applied with relatively high precision.

The existing surrogate models of aviation kerosene are limited to a specific scope of application and their thermo-physical properties deviate from the experimental data. The turbulence models used to implement numerical simulation should be studied to further improve the prediction accuracy. The thermal-induced acceleration is driven by the drastic density change, which is caused by the production of small molecules. The wall temperature of the combustion chamber can be effectively reduced by this behavior, i.e. the phenomenon of heat transfer deterioration can be attenuated or suppressed by thermal pyrolysis.

The issues in numerical studies of supercritical aviation kerosene are clearly revealed, and the conjugation mechanism between thermal pyrolysis and convective heat transfer is initially presented.

The service sector is the key driver of a country’s economic growth. The quality of service is more important for the survival of any organization. It is the interactive process by which the organization understands the customer and satisfies their needs. The main purpose of this study is to identify the factors influencing service quality in ocean freight forwarding and to study the association between the factors.

This research uses a deductive approach, which understands the theory first and collects the data. A questionnaire is designed to collect the data. The sampling technique used is two-stage sampling. First, the freight forwarders are selected and then the customers, importers and exporters are selected randomly. Likert scales are used to measure quality factors such as tangibility, reliability, responsibility, value, empathy and assurance. The association of factors is empirically evaluated. The SPSS tool is used for the correlation analysis.

An extensive review of the literature has been done to study and identify these service quality factors influencing customer satisfaction and loyalty. The result of this extensive literature review revealed that tangibility, responsiveness, reliability, trust, empathy and value are the service quality. It has been proved that there exists a significant association between the service quality factors and is positively related to the customer satisfaction.

Some studies have examined the freight forwarders’ service quality, but not specifically related to any dimension. This study attempts to bring together the five dimensions of SERVQUAL scale and the value dimension evaluating the cost, freight charges, safety and security criteria in the industry and examines the association between the quality factors and customer satisfaction.

This study aims to examine the causal factors of customer motivation, trust and loyalty, influencing the level of repurchase intentions of local tourists travelling during pandemic COVID-19 crisis in Thailand.

The population of this study comprised all Thai local tourists travelling in Thailand. Using simple random sampling of local tourists on travel in Thailand, quantitative data were collected from 500 tourists as the sampling, representing Northern Thailand, North-Eastern Thailand, Central Thailand, Southern Thailand and Bangkok. Path analysis, including correlation matrix and factor confirmation, was used to test the causal factors influencing the level of repurchase intentions.

Motivation trust, customer trust, customer loyalty and repurchase intentions of Thai domestic tourism were on a high level. In addition, there were positive influences of customer motivation, trust and loyalty on the level of repurchase intentions by local tourists travelling in Thailand.

The study results demonstrate that the social exchange theory can be used to explain the influences of customer motivation, customer trust and loyalty on repurchase intentions of domestic Thai tourism.

The purpose of this paper is to promote the theoretical innovation of socialist economics with Chinese characteristics in these areas.

We must “excavate new materials, discover new problems, propose new ideas, and construct new theories from the practice of China’s reform and development.”

Giving full play to the government’s role in realizing optimal allocation of resources required for the public economy to better exert its control, influence and guidance, and at least assume the following three responsibilities. The first is to iron out the economic cycle. The second is to lead the industry to upgrade. The third is to ensure national economic security.

Some deep-rooted issues still need to be further studied in order to establish the scientific and practical nature of the socialist economics with Chinese characteristics. For instance, why is the theory of a socialist economy with Chinese characteristics summarized from the development practice in China a scientific theory?

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. Leveraging current train operation data, these models enable swift and precise predictions, addressing challenges posed by train delays in high-speed rail networks during unforeseen events.

This paper proposes CBLA-net, a neural network architecture for predicting late arrival times. It combines CNN, Bi-LSTM, and attention mechanisms to extract features, handle time series data, and enhance information utilization. Trained on operational data from the Beijing-Tianjin line, it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.

This study evaluates our model's predictive performance using two data approaches: one considering full data and another focusing only on late arrivals. Results show precise and rapid predictions. Training with full data achieves a MAE of approximately 0.54 minutes and a RMSE of 0.65 minutes, surpassing the model trained solely on delay data (MAE: is about 1.02 min, RMSE: is about 1.52 min). Despite superior overall performance with full data, the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals. For enhanced adaptability to real-world train operations, training with full data is recommended.

This paper introduces a novel neural network model, CBLA-net, for predicting train delay times. It innovatively compares and analyzes the model's performance using both full data and delay data formats. Additionally, the evaluation of the network's predictive capabilities considers different scenarios, providing a comprehensive demonstration of the model's predictive performance.

The purpose of this paper is to artificially construct a functional surface with self-propulsion flow characteristics for the directional transportation of propellant in surface tension tanks.

In this study, a method to enhance the propulsion efficiency by using functional surfaces of self-propulsion performance was proposed. Superhydrophilic wedged-groove with the superhydrophobic background was fabricated and the self-propulsion capacity was verified.

It is found that the self-propulsion capacity is related to the divergence angle of the wedged-groove in the hydrophilic area, and the velocity of the droplets on the deflector plate is the largest with the divergence angle of 4°; the temperature gradient field formed by the condensing device at the nozzle can accelerate the droplet outflow from the tank.

Realization of this idea provides an accurate control strategy for the complex flow process of propellant in plate surface tension tanks, which could enhance the efficiency of the tension tank significantly.

This study examines the relationship between emotional intelligence, self-efficacy and organizational commitment, focusing on the mediating role of self-efficacy in the relationship between emotional intelligence and organizational commitment.

The authors used an online survey to collect data for this purpose. The sample consisted of 145 employees of different organizations in Kosovo. To test the hypothetical model, a mediation analysis was conducted using PROCESS Model Type 4.

The results show that emotional intelligence is positively related to self-efficacy and that self-efficacy is positively related to organizational commitment. Furthermore, the results of the mediation analysis confirm that the relationship between emotional intelligence and organizational commitment is mediated by self-efficacy.

For future research, the authors recommend using the sub-dimensions of the above variables to test this model, and multiple models could be formulated. At the same time, the survey can be applied to managers to examine their emotional intelligence and to determine whether emotional intelligence influences their organizational commitment through self-efficacy. Consistent with the findings of this study, managers and executives in organizations should consider the emotional intelligence of their employees and that the employees with higher emotional intelligence have higher self-efficacy and can perform better.

This study extends the current literature in organizational behavior and provides a comprehensive understanding of the relationship between emotional intelligence, self-efficacy and organizational commitment. This study was also conducted in a developing country context, which can always lead to different results than studies conducted in developed countries.