Search results

Friction and wear are very important factors in predicting the performance of journal bearings, particularly under heavy load in start-up processes. However, there are few relevant studies on the numerical model. This study aims to establish a transient-mixed lubrication model to predict the performance of journal bearings, focusing on the friction and wear behavior under heavy load during start-up.

The average Reynold equation, three-dimensional energy equation, shear stress model for friction and Archard model for wear are coupled in the transient model by finite difference method. The linear wear simulation method is bought out to reduce the update times and the calculation time.

The different start-up accelerations and linear wear times set are compared and discussed, which indicates a reasonable start-up acceleration is necessary for journal bearings under heavy load during start-up, and setting linear wear times is an effective method to reduce the simulation time significantly. Furthermore, the wear profile in the start-up process spreads in both the clearance and circumferential directions, but mainly in the clearance direction, which increases the minimum film thickness and affects the friction performance.

This study is of great significance for the numerical prediction of the transient performance of journal bearings during start-up considering friction and wear.

In today’s digital era, talent recruitment can help address the growing shortage of skilled labor in the construction industry and promote sustainable growth. While existing research has explored the association between talent acquisition and local labor productivity or economic progress, the impact on construction growth deserves further study. This study aims to (1) explore the influence of talent recruitment on the growth of the construction industry and (2) analyze whether different regional characteristics shape the differential impact of talent acquisition on construction growth.

This research employs a quantitative approach, focusing on 35 major cities in China. A panel data regression model is utilized to analyze annual data from 2013 to 2018, considering variables like the construction talent recruitment index, value added in construction, gross regional product per capita and others. The study also examines regional heterogeneity and conducts robustness tests to validate the findings.

The results reveal a positive and significant correlation between talent recruitment and construction industry growth. This correlation is more pronounced in economically advanced and infrastructure-rich regions. The study also finds that factors like capital investment, educational attainment and housing prices significantly contribute to industry growth. Talent recruitment not only transforms local labor market dynamics but also drives demand for construction services, promoting industry growth through economies of scale.

This research constructs a new measurement for talent recruitment and provides new insights into the pivotal role of talent recruitment in the sustainable growth of the construction industry. It underscores the need for construction firms to tailor talent acquisition policies to their specific circumstances and regional developmental conditions. The findings offer practical guidance for driving regional growth within the sector, emphasizing the importance of talent recruitment as a key yet previously underappreciated factor in industry development.

This study aims to examine the impact of boardroom diversity on the financial stability of Chinese financial listed firms. Boardroom diversity is quantified in the following aspects: relation-oriented diversity and task-oriented diversity.

Panel data on Chinese financial listed firms between 1998 and 2017 are used in this study. Panel regression is used to analyze the firm data for fixed effects and robust standard errors.

Task-oriented diversity of the board increases financial stability. Regarding the impact of boardroom diversity on firm risk, the results reveal that task-oriented diversity of the board reduces firm risk, which supports the predictions of this research. Regarding the moderating effect of state ownership on the relationship between boardroom diversity (task- and relation-oriented diversity) and financial stability, the results show that state ownership enhances the positive impact of the board’s task-oriented diversity on financial stability.

Task-oriented diversity of the board enhances the financial stability of Chinese financial listed firms. As existing studies on bank boards in China are limited, the findings of this research can be used when crafting policy initiatives to enhance financial stability.

To the best of the authors’ knowledge, this study is the first to examine the effect of boardroom diversity, particularly task- and relation-oriented diversity, on financial stability. It provides empirical support that boardroom diversity positively affects the financial stability of Chinese financial listed firms. This research also offers empirical evidence that state ownership enhances the positive impact of the board’s task-oriented diversity on financial stability.

Revealing research data’s production and use, the status of research data management (RDM) and researchers’ service requirements in universities of Central China; this study aims to investigate the feasibility of university libraries in providing RDM services without any supporting policies from governments or funding agencies.

Using a stratified sampling method, faculties and graduate students from 11 universities were investigated. Four pilot subjects at Wuhan University (WHU) were chosen for whom a pilot RDM platform was to be constructed.

Research data at Chinese universities are small, sporadic and discontinuous. Such data are intensively or dispersedly under researcher’s management, with some unresolved problems regarding data security, data sharing and utilisation efficiency. Researchers’ needs for data services are strong. University libraries in China can develop RDM systems and provide related services. To realise this, more work should be done on service mechanism, service promotion, software development and staff training.

The user survey covered 11 universities in central China, which may not reveal the real RDM status of researcher in different areas of China.

The practice at WHU could provide reference to other university libraries in China or other developing countries.

The practice at WHU could provide reference to other university libraries in China or other developing countries.

The user survey is designed to be as comprehensive as possible and cover 902 researchers from 11 different types of Chinese universities. The practice at WHU is one of the first RDM initiatives led by university library in China.

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Peer instruction has been widely adopted as an instructional method in higher education. However, due to students' different preconceptions, the authors argued that peer instruction is not a panacea in international business education when students' prior knowledge extensively varies. The paper aims to discuss these issues.

In this experimental study, the authors focused on three conditions of an introductory statistics course: individual problem solving, peer instruction, and peer instruction with hints.

The authors have found students in peer instruction with hints class did not only outperform in the final exam, but also achieved the highest frequency of successful conceptual changes in comparison with their counterparts in the other two classes.

Providing instructional hints to improve the effectiveness of peer instruction may shed light on classroom instruction in higher education.

As for international business education, this was a unique exploration to capture students' conceptual changes using clickers. The authors believed this research paper will help the education practitioners to know their business students better.

This paper aims to propose an innovative building information modelling (BIM)-based framework for multi-objective and dynamic temporary construction site layout design (SLD), which uses a hybrid approach of systematic layout planning (SLP) and mathematical modelling.

The hybrid approach, which follows a step-by-step process for site layout planning, is designed to facilitate both qualitative and quantitative data collection and processing. BIM platform is usedto facilitate the determination of the required quantitative data, while the qualitative data are generated through knowledge-based rules.

The multi-objective layout model represents two important aspects: layout cost and adjacency score. The result shows that the model meets construction managers’ requirements in not only saving cost but also assuring the preferences of temporary facility relationships. This implies that the integration of SLP and mathematical layout modelling is an appropriate approach to deliver practical multi-objective SLD solutions.

The proposed framework is expected to serve as a solution, for practical application, which takes the advantage of technologies in data collection and processing. Besides, this paper demonstrates, by using numerical experimentation and applying Microsoft Excel Solver for site layout optimisation, how to reduce the complexity in mathematical programming for construction managers.

The original contribution of this paper is the attempt of developing a framework in which all data used for the site layout modelling are collected and processed using a systematic approach, instead of being predetermined, as in many previous studies.

In this chapter, we explore the dark side of the metaverse and the need for user protection. While the metaverse offers multiple opportunities it also poses significant risks for users, such as privacy concerns, addiction, harassment, and cyberbullying. First, we discuss the various threats that users may encounter such as online harassment, assaults, cyberbullying, hate speech, identity theft, and virtual property theft. As per the Center for Countering Digital Hate, an incident of violation occurs every seven minutes within VRChat, a popular virtual reality game. The level of misconduct in the metaverse can surpass the extent of internet harassment. Virtual reality gaming has been associated with various health issues like sleep deprivation, and insomnia as well as mental health concerns such as depression, anger, and anxiety. We examine how these issues may impact user’s physical and mental health. The sensors and devices used in the metaverse collect a vast amount of user biometric data and spatial data. Interactions between users and metaverse could be leaked. We examine different methods that improve user protection, including everyone from enhanced security protocols via the application of privacy-enhanced technology to several avatars, two-factor authentication, and user educational and awareness programs. Moreover, we explore how the newest technologies, like blockchain and artificial intelligence, play a role in making user safety more important. We finished the course with the study of the case of Second Life, the virtual reality gaming platform, and pointing out some of the problems that exist within it.