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The purpose of this paper is to investigate the effects of surface topography, including surface roughness, circumferential waviness and radial taper, on hydrodynamic performance of liquid film seals considering cavitation.

A mathematical model of liquid film seals with surface topography was established based on the mass-conservative algorithm. Liquid film governing equation was discretized by the finite control volume method and solved by the Gauss–Seidel relaxation iterative algorithm, and the hydrodynamic performance parameters of liquid film seals were obtained considering surface roughness, circumferential waviness and radial taper separately.

The results indicate that the values of load-carrying capacity and frication torque are affected by the surface topography in varying degrees, but the effect is limited.

The results presented in the study are expected to aid in determining the optimum value of structural parameters for the optimum seal performance because of the realistic model which considers both surface topography and cavitation.

Attention is one of the most important factors to affect the academic performance of students. Effectively analyzing students' attention in class can promote teachers' precise teaching and students' personalized learning. To intelligently analyze the students' attention in classroom from the first-person perspective, this paper proposes a fusion model based on gaze tracking and object detection. In particular, the proposed attention analysis model does not depend on any smart equipment.

Given a first-person view video of students' learning, the authors first estimate the gazing point by using the deep space–time neural network. Second, single shot multi-box detector and fast segmentation convolutional neural network are comparatively adopted to accurately detect the objects in the video. Third, they predict the gazing objects by combining the results of gazing point estimation and object detection. Finally, the personalized attention of students is analyzed based on the predicted gazing objects and the measurable eye movement criteria.

A large number of experiments are carried out on a public database and a new dataset that is built in a real classroom. The experimental results show that the proposed model not only can accurately track the students' gazing trajectory and effectively analyze the fluctuation of attention of the individual student and all students but also provide a valuable reference to evaluate the process of learning of students.

The contributions of this paper can be summarized as follows. The analysis of students' attention plays an important role in improving teaching quality and student achievement. However, there is little research on how to automatically and intelligently analyze students' attention. To alleviate this problem, this paper focuses on analyzing students' attention by gaze tracking and object detection in classroom teaching, which is significant for practical application in the field of education. The authors proposed an effectively intelligent fusion model based on the deep neural network, which mainly includes the gazing point module and the object detection module, to analyze students' attention in classroom teaching instead of relying on any smart wearable device. They introduce the attention mechanism into the gazing point module to improve the performance of gazing point detection and perform some comparison experiments on the public dataset to prove that the gazing point module can achieve better performance. They associate the eye movement criteria with visual gaze to get quantifiable objective data for students' attention analysis, which can provide a valuable basis to evaluate the learning process of students, provide useful learning information of students for both parents and teachers and support the development of individualized teaching. They built a new database that contains the first-person view videos of 11 subjects in a real classroom and employ it to evaluate the effectiveness and feasibility of the proposed model.

This study explores how sharing platforms achieve platform loyalty through various operation management strategies.

A multiple case study method has been conducted in two Chinese sharing economy industries: ride- and bike-sharing. Data were collected through 30 semi-structured interviews with managers from four platform companies (DiDi, Uber China, ofo and Mobike). Individual case studies were developed from the triangulation of all existing data. Concurrent with the development of these individual case studies was a cross-case analysis. Emerging patterns have been identified and compared to previous findings in the literature to build upon and modify the existing knowledge base and to formulate a series of propositions.

Platform asset characteristics and mergers and acquisitions affect supply network readiness and operational capacity, respectively, and this effect would consequently contribute to achieving platform loyalty through user satisfaction. Moreover, externality, as a moderator, may influence the strength of the relationship between satisfaction and platform loyalty.

The proposed theoretical model provides an overarching framework for sharing platform companies to design and operate their businesses while carefully examining the situations, contexts and actions of users and other stakeholders and choosing an appropriate strategic mechanism to drive platform growth.

This study is one of the first to empirically explain how firms in a sharing economy sector could gain platform loyalty by adopting an expectation–confirmation theory perspective.

This paper aims to examine how ethical leadership alleviates knowledge contribution loafing among engineering designers through the mediating effect of knowledge-based psychological ownership and the moderating effect of emotion regulation strategies.

This study adopts a questionnaire survey to obtain 344 valid sample from engineering designers and uses partial least squares-structural equation modeling to analyze data.

The results demonstrate that ethical leadership is a key factor to alleviate knowledge contribution loafing. Knowledge-based psychological ownership is a main factor causing knowledge contribution loafing and mediates the influence of ethical leadership on knowledge contribution loafing. Furthermore, cognitive reappraisal (a response-focused emotion regulation strategy) moderates the relationship between ethical leadership and knowledge contribution loafing, and the effect of ethical leadership on knowledge contribution loafing is stronger when cognitive reappraisal is high.

Engineering design organizations may inspire ethical leadership and pay attention to psychological state of designers. Leaders may help designers overcome knowledge-based psychological ownership by the influence of ethical leadership. During the process of knowledge interaction, designers may adopt cognitive reappraisal strategy consciously.

This study addresses the knowledge gap that ethical leadership affects knowledge contribution loafing with knowledge-based psychological ownership as the intermediary. This study also advances the literature on leadership and emotion regulation and extends the scope of social learning theory in knowledge management domain through examining the moderate role of emotion regulation strategies.

Knowledge contribution loafing as one of the major obstacles to knowledge sharing among designers in engineering design firms impedes better achievement of engineering design. The purpose of this paper is to examine different types of ethical climate impacts on knowledge contribution loafing among designers through the mediating effect of knowledge leadership.

By adopting a quantitative research design, data were collected using a survey questionnaire from 352 designers in engineering design firms. The data were analyzed using the partial-least squares structural equation modeling approach to test hypotheses.

Ethical climate is an important factor to affect knowledge contribution loafing among designers, and three types of ethical climate (self-interest, social responsibility and law/professional codes) have different degrees of influence on knowledge contribution loafing. In addition, knowledge leadership can alleviate knowledge contribution loafing, and it is a mediator between ethical climate and knowledge contribution loafing.

Engineering design firms should cultivate and strengthen the role of social responsibility, law/professional codes and knowledge leadership and reduce the influence of self-interest to mitigate the negative of knowledge contribution loafing among designers.

By identifying ethical climate as a novel influence factor for knowledge contribution loafing, this research further highlights the role of different types of ethical climate in an engineering design context. Moreover, it delves deeply into the issue around different types of ethical climate affect knowledge contribution loafing among designers through the role of knowledge leadership. This broadens the understanding of how ethical climate affects knowledge contribution loafing among designers in the engineering design organizations and enriches knowledge management literatures in engineering design industry.

This paper aims to study the attitude control problem with mutating orbital rate and actuator fading.

To avoid malicious physical attacks and hide itself, the spacecraft may irregularly switch its orbit altitude within a specific range, which will bring about variations in orbital rate, thereby causing mutations in the attitude dynamics model. The actuator faults will also cause changes in system dynamics. Both factors affect the control performance. First, this paper determines the potential switching orbits. Then under different conditions, design controllers that can accommodate actuator faults according to the statistical law of actuator fading.

This paper, to the best of the authors’ knowledge, for the first time, introduces the Markovian jump framework to model the possible unexpected mutating of orbital rate and actuator fading of spacecraft and then designs a novel control policy to solve the attitude control problem.

This paper also provides the algorithm design processes in detail. A comparative numerical simulation is given to verify the effectiveness of the proposed algorithm.

This is an early solution for spacecraft attitude control with dynamics model mutations.

With the development of location-based services and mobile phones, local retailing stores have the opportunity to send location-based advertisings (LBAs) to consumers at a right time and right place. However, knowledge about the influence of LBAs on consumers’ store patronage is limited. The purpose of this paper is to understand how the content of LBAs influences consumers’ store patronage intention. In particular, the paper investigates the influence of perceived accuracy and transaction cost reduction from the content of LBAs on consumers’ store patronage intention through the emotional reactions of pleasure and arousal.

This study developed a theoretical model to examine how the content of LBAs influences the store patronage intention of consumers. Empirical data were collected from 351 undergraduate and graduate students. The partial least squares technique was used to test the research model.

Perceived accuracy and transaction cost reduction from the content of LBAs have a significant influence on the store patronage intention of consumers through pleasure and arousal. Brand image and purchase plan are control variables.

Knowledge about the influence of LBAs on consumer store patronage is limited. This study provides empirical evidence about how perceived accuracy and transaction cost reduction from the content of LBAs affect the emotional reactions of consumers and then determine their store patronage intention.

The purpose of this paper is to develop a trading and pricing method of expansion option (EO) model to solve expansion problems of build-operate-transfer (BOT) freeway project.

This paper proposes an ex ante mechanism through trading the EO to avoid the transaction costs. By editing the paths generated from binomial option pricing model, this paper establishes an American real option binomial lattice model and evaluates the value of EO. Data are collected from Liaoning province in China and the model is practiced in the context of a BOT freeway in Liaoning province.

Supported by empirical evidence, this study finds out that there exists a minimum price at which the government can sell the EO and a maximum price that the private sector is willing to pay. When the minimum price is negative, the government should transfer the EO to the private sector free of charge to avoid the transaction costs. Otherwise, the government should sell the EO at a reasonable price to protect public interests.

The study can be used for the government to reducing the transaction costs. By using the trading EO model, the government can sell its share of the EO to the private sector to manage its resources efficiently.

This paper builds a trading EO model to solve expansion problems instead of renegotiations. In addition to reducing the transaction costs for the whole society, trading EO can also raise the respective payoffs of both public and private sectors. An EO trading framework and algorithm is further developed. It realized an American option model, making the owner can exercise the option whenever he wants. Thus, the whole model is adapted to best fit BOT highway practice.

The micro‐satellite clusters have been discussed for several years, however, there is not a common framework about its software, and various researches distributed at different domains. In order to conduct the future work well, the purpose of this paper is to systematically describe micro‐satellite clusters' characteristics, clusters software model, and present a distributed testbed to shorten test process, and minimize the development cost.

The cluster characteristics and model is summarized through analyzing the past satellite cluster programs. Then the ground test system is designed to shorten micro‐satellite's development period, improve its reliability.

The clusters' characteristics are discussed, such as coverage, scalability, fault tolerance, low cost, etc. The clusters' data flow and on‐board software architecture are presented according to properties of clusters. Finally, the distributed testbed that focuses on future on‐board software and hardware technologies that aim to rapid design, build, integration, test, deployment, and operation of the future micro‐satellite is designed.

The presentation of software architecture of cluster member can improve the micro‐satellite's development, and the distributed testbed can improve the ground test efficiency, especially, when the micro‐satellite quantity is big.