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The purpose of this paper is to report the design and evaluation of an inter-university collaborative project entitled “Blended learning for building student-teachers’ capacity to learn and teach science-related interdisciplinary subjects.” The project is a response of the science education faculty of three Hong Kong tertiary institutes to the challenge of catering to the diversity of academic backgrounds among student-teachers.

E-learning modules have been produced covering four content domains of science. These modules are designed based on the 5E learning model and are delivered to students using the learning management system provided by Moodle. The design of the modules is iterative, based on the evaluation of three consecutive rounds of trials through student surveys, and focus group interviews with students and course lecturers.

The evaluation findings indicate positive outcomes for certain attributes such as conceptual understanding, eagerness and confidence in learning science, and metacognitive reflection on students’ own learning. There are challenges to be met in relation to instructional design to cater for the diversity of student abilities, and enhance motivation in self-directed learning.

The project indicates the ways to develop students’ basic science knowledge in a mixed-ability setting through the design of self-directed e-learning modules blended with their major courses and possible measures to address the limitations of such design.

The study represents a conscious effort for the science teacher education faculty of different universities to pull together to tackle a perennial teaching and learning problem. The findings provide important insights into possible ways to blend e-learning with face-to-face learning approaches to better cater to the needs of science learners with mixed abilities to prepare them for interdisciplinary teaching.

Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the actual signal acquisition is usually hindered by certain restrictions, such as the limited number of signal channels. The purpose of this study is to fulfill the weakness of the existed BSS method.

To deal with this problem, this paper proposes a blind source extraction (BSE) method for bearing fault diagnosis based on empirical mode decomposition (EMD) and temporal correlation. First, a single-channel undetermined BSS problem is transformed into a determined BSS problem using the EMD algorithm. Then, the desired fault signal is extracted from selected intrinsic mode functions with a multi-shift correlation method.

Experimental results prove the extracted fault signal can be easily identified through the envelope spectrum. The application of the proposed method is validated using simulated signals and rolling element bearing signals of the train axle.

This paper proposes an underdetermined BSE method based on the EMD and the temporal correlation method for rolling element bearings. A simulated signal and two bearing fault signal from the train rolling element bearings show that the proposed method can well extract the bearing fault signal. Note that the proposed method can extract the periodic fault signal for bearing fault diagnosis. Thus, it should be helpful in the diagnosis of other rotating machinery, such as gears or blades.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

This paper aims to review the research on accounting professionalisation in China to develop insights into how the research is developing, offer a critique of the research to date and outline future research directions and opportunities.

This paper adopts a methodological approach of systematic literature review, as suggested by Tranfield et al. (2003) and Denyer and Tranfield (2009), to identify, select and analyse the extant literature on the Chinese public accounting profession. In total, 68 academic works were included in the review process.

This paper finds that the extant literature has produced fruitful insights into the processes and underlying motivation of accounting professionalisation in China, demonstrating that the Chinese experience has differed, to a large extent, from the hitherto mainly Anglo-American-dominated understandings of accounting professionalisation. However, due to the lack of common theoretical vernacular and an agreed upon focus, the extant literature illustrates a fragmented and contradictory picture, making attempts to accumulate prior knowledge in the field increasingly difficult.

This paper focusses only on research published in English. Consequently, the scope of review has been limited as some works published in languages other than English may be excluded.

This paper provides one of the pioneering exercises to systematically review the research on accounting professionalisation in China. It explores significant issues arising from the analysis and provides several suggestions for furthering the research effort in this field.

Money laundering continues to emerge as a transnational phenomenon that has harmful consequences for the global economy and society. Despite the theoretical and practical magnitude of money laundering, international business (IB) research on the topic is scarce and scattered across multiple disciplines. Accordingly, this study aims to advance an integrated understanding of money laundering from the IB perspective.

The authors conduct a systematic review of relevant literature and qualitatively analyze the content of 57 studies published on the topic during the past two decades.

The authors identify five streams (5Cs) of research on money laundering in the IB context: the concept, characteristics, causes, consequences and controls. The analysis further indicates six theoretical approaches used in the past research. Notably, normative standards and business and economics theories are dominant in the extant research.

The authors review the literature on an under-researched but practically significant phenomenon and found potential for advancing its theoretical foundations. Hence, the authors propose a 5Cs framework and a future agenda for research and practice by introducing 21 future research questions and two plausible theories to help study the phenomenon more effectively in the future.

In practical terms, the study extends the understanding of the money laundering phenomenon and subsequently helps mitigating the problem of money laundering in the IB environment, along with its harmful economic and societal impacts.

The authors offer an integrative view on money laundering in the IB context. Additionally, the authors emphasize wider discussions on money laundering as a form of mega-corruption.

The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.

This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.

This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.

The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a growing demand for developing a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method.

This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents.

By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment.

This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.

In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors, and learners all over the world can get access to these courses via the internet. However, faced with massive courses, learners often waste much time finding courses they like. This paper aims to explore the problem that how to make accurate personalized recommendations for MOOC users.

This paper proposes a multi-attribute weight algorithm based on collaborative filtering (CF) to select a recommendation set of courses for target MOOC users.

The recall of the proposed algorithm in this paper is higher than both the traditional CF and a CF-based algorithm – uncertain neighbors’ collaborative filtering recommendation algorithm. The higher the recall is, the more accurate the recommendation result is.

This paper reflects the target users’ preferences for the first time by calculating separately the weight of the attributes and the weight of attribute values of the courses.

This paper aims to analyse the asymmetric impacts of world oil price on macroeconomic variables in Vietnam, including domestic oil price, inflation and output growth.

The mixed data sampling (MIDAS) approach is employed to examine the impact of world oil price changes on macroeconomic variables as the former is high-frequency data (daily), and the latter is low-frequency data, usually monthly or quarterly.

Changes in world oil price cause asymmetric impacts on domestic oil price and inflation, but no significant effects on output growth. In terms of magnitude, a positive change in world oil price causes a stronger effect than a negative change in world oil price. In terms of timing, a positive change in world oil price causes a slow pass-through impact on domestic oil price and inflation. Meanwhile, domestic oil price and inflation decrease quickly following a negative change in world oil price.

This study investigates the asymmetric impact of oil price on the Vietnam economy in terms of both magnitude and timing, which is not explored by previous studies. In addition, it exploits daily information of oil price changes to analyse macroeconomic variables in lower frequency by employing MIDAS approach.

This paper aims to assess how enterprise resource planning (ERP) performance of Korean small and medium enterprises in manufacturing differs according to different levels of business process reengineering (BPR), information strategic planning (ISP) and ERP customization.

A questionnaire survey was carried out in this research. Responses from 96 small and medium manufacturing companies that have adopted ERP systems were analyzed.

The results of this study suggest that ISP and BPR implementation are positively correlated to ERP performance.

While consulting and customization costs have positive impacts on ERP performance, the level of customization does not influence performance. As one of the pioneering studies that investigate the impact of BPR, ISP and ERP customization on small and medium manufacturing companies, this research contributes to both theory and practice.