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Distributed temperature sensing (DTS) can identify locations and factors of seepage in embankments. Inspired by the classical transient hot-wire method (THW), the focus of this paper is to investigate the feasibility and propose a calibrated method of seepage velocity monitoring using the optical fiber DTS.

According to the definition and the measurement of thermal conductivity, the nominal thermal conductivity, which comprehensively reflects the influence of heat transfer and seepage factors, is proposed and the corresponding solution is also derived. Then, a flume testing platform of an embankment seepage monitoring system composed of the optical fiber heat-up subsystem, the seepage controlling subsystem and the optical fiber DTS subsystem is designed and built. Meanwhile, the data processing and assistant analysis subsystem (DPAAS) is also developed to effectively acquire the experimental data of concerned locations and obtain the corresponding nominal thermal conductivity under various seepage conditions. Based on these setups, a series of laboratory flume experiments are carried out under controlled velocities and heating powers.

The plots of recorded temperature rise versus natural logarithm of time allow the calculation of nominal thermal conductivities, and then the seepage velocity monitoring model particular to the experimental setup is successfully established with satisfactory precision.

Considering the complexity of water flow in embankments, a seepage flume that matches the natural system, allowing for larger experimental model scales, various water temperatures, various engineering materials and a wider range of seepage velocities, should be investigated in future.

The combined THW and DTS method provides promising potential in real-time seepage monitoring of embankment dams with the help of the developed DPAAS.

In this work, we performed a flume testing of seepage velocity monitoring platform using optical fiber distributed-temperature sensing for embankments based on the transient hot-wire method. Through the testing of data, the seepage velocity monitoring model particular to the experimental setup was established. The results presented here are very encouraging and demonstrate that the DTS system can be used to monitor the temperature and the seepage factors in field applications.

The purpose of this paper is to improve opening performance of bi-directional rotation gas face seals by investigating the hydrodynamic effect of non-closed elliptical grooves.

A model of non-closed elliptical groove bi-directional rotation gas face seal is developed. The distribution of lubricating film pressure is obtained by solving gas Reynolds equations with the finite difference method. The program iterates repeatedly until the convergence criterion on the opening force is satisfied, and the sealing performance is finally obtained.

Non-closed elliptical groove presents much stronger hydrodynamic effect than the closed groove because of drop of the gas resistance flowing into grooves. Besides, the non-closed elliptical groove presents significant hydrodynamic effect under bi-directional rotation conditions, and an increase of over 40 per cent is obtained for the opening force at seal pressure 4.5 MPa, as same level as the unidirectional spiral groove gas seal. In the case of bi-directional rotation, the value of the inclination angle is recommended to set as 90° presenting a structure symmetry so as to keep best opening performance for both positive and reverse rotation.

A model of non-closed elliptical groove bi-directional rotation gas face seal is established. The hydrodynamic mechanism of this gas seal is illustrated. Parametric investigation of inclination angle and integrity rate is presented for the non-closed elliptical groove bi-directional rotation gas face seal.

Online learning is increasingly popular, and educational platforms provide a wealth of courses. Improving course sales is the key to promoting sustainable development of online course platforms. However, limited research has explored the marketing of online courses. We study how to drive online course sales by leveraging teacher information.

We performed an empirical study. We collected data through a crawler and image recognition from Tencent classroom.

Our results show that providing teacher information and profile images helps promote online course sales. However, detailed course descriptions weaken the positive impact of teachers' profile images on online course sales. Furthermore, our study shows an inverted U-shaped relationship between the intensity of smiling in teacher profile photos and online course sales, and teacher descriptions negatively moderate this relationship.

Our study contributes to the research on online course sales and extends the context of the research on smiling as well as the studies of visual and textual information.

The results have practical implications for online course sellers and platforms.

Existing scholarly efforts have explored online courses mainly from an education perspective. More research is needed to advance the understanding of online course sales. Our study advances research in the marketing of online courses.

This study aims to provide a critical reflection of the application of image recognition techniques in visual information mining in hospitality and tourism.

This study begins by reviewing the progress of image recognition and advantages of convolutional neural network-based image recognition models. Next, this study explains and exemplifies the mechanisms and functions of two relevant image recognition applications: object recognition and facial recognition. This study concludes by providing theoretical and practical implications and potential directions for future research.

After this study presents different potential applications and compares the use of image recognition with traditional manual methods, the main findings of this critical reflection revolve around the feasibility of the described techniques.

Knowledge on how to extract valuable visual information from large-scale user-generated photos to infer the online behavior of consumers and service providers and its influence on purchase decisions and firm performance is crucial to business practices in hospitality and tourism.

Visual information plays a crucial role in online travel agencies and peer-to-peer accommodation platforms from the side of sellers and buyers. However, extant studies relied heavily on traditional manual identification with small samples and subjective judgment. With the development of deep learning and computer vision techniques, current studies were able to extract various types of visual information from large-scale datasets with high accuracy and efficiency. To the best of the authors’ knowledge, this study is the first to offer an outlook of image recognition techniques for mining visual information in hospitality and tourism.

The purpose of this paper is to find the specific competitive industries in emerging industries of strategic importance of each province in China in order to provide references for industrial cultivation and development.

This paper uses quantitative analysis methods on RCA and R&D efficiency.

Different provinces have specific competitive emerging industries of strategic importance. Taking biotechnology, equipment manufacturing, and new generation of information technology industry as examples, this paper finds: for the advanced equipment manufacturing industry, Shaanxi, Sichuan, Guizhou, Tianjin, Liaoning, Heilongjiang and Jiangxi provinces have obvious characteristics and relatively high R&D efficiency; for bio‐technology, Jiangsu, Henan, Jiangxi, Hunan, Zhejiang and Shandong provinces have obvious characteristics and relatively high R&D efficiency; and for the next generation of the information technology industry, Jiangsu, Guangdong, Fujian, Beijing, Tianjin and Shanghai provinces have obvious characteristics and relatively high R&D efficiency.

This study is limited by lack of industrial comprehensiveness so that more statistical data about emerging industry of strategic importance is needed for more in‐depth analysis.

The identification of specific competitive emerging industry of strategic importance of each province will give managers and policy makers train of thought for the cultivation and development of strategic emerging industry and make future policies more targeted.

The paper contributes to the research on the differentiated cultivation and development tactics of strategic emerging industry by, respectively, finding out the specific competitive emerging industries of each province in China.

The purpose of this paper is to elicit a conceptual understanding of the moderating effect of trustworthiness on the relationship between organisational culture and employee creativity.

This study is theoretical in nature and draws conceptual insights from an integration of theoretical and conceptual underpinnings: the competing values framework, trustworthiness from the integrative model of organisational trust and the componential theory of individual creativity.

Trustworthiness plays a major role in influencing the degree at which managers engender employee creativity. This study postulates that clan and adhocracy organisational culture dimensions have a positive impact on employee creativity, while market and hierarchy organisational culture dimensions have negative impacts on employee creativity. Employee creativity would be engendered if organisational cultures are tailored towards improving the ability of employees. Engendering of employee creativity is contingent on an acceptable degree of benevolence and integrity expressed between managers and their respective employees.

By integrating several methodological underpinnings to produce a multidimensional model for engendering employee creativity, from the lens of a supportive organisational culture, this study offers novel insights for both managerial practice and actions.

The purpose of this paper is to study the insulation structure optimization method of multiwinding high-frequency transformer (HFT).

This paper takes 100 kW, 10 kHz multiwinding HFT as the research object. First, the distribution of electric field strength within the core window of multiwinding HFT with different winding configurations is simulated by the electrostatic field finite element method. The symmetrical hybrid winding structure with minimum electric field strength is selected as the insulation design. To reduce the electric field strength at the end region of the winding, the electrostatic ring and angle ring are designed based on the response surface method.

The optimal results show that the maximum electric field strength can be reduced by 15.4%, and the low voltage stress can be achieved.

The above research provides guidance and basis for the optimal design of insulation structure of multiwinding HFT.