Search results

The purpose of this paper is to analyse the personalised and social characteristics of open knowledge management in higher education based on social tagging in the Web 2.0 environment.

Through the function of annotation in social tagging, the paper analyses its personalised characteristics of recognising the preferences of participants, and its personalised‐social characteristics of enriching content from all kinds of aspects; through the function of association of social tagging, it analyses its social characteristics of social networking, and its social‐personalised characteristics of collaborative acquisition or recommendation.

In the process of online information and open knowledge organisation and acquisition based on the annotation function of social tagging in the Web 2.0 environment, the personalised participation of individuals will lead to social results for everyone; however, in the process of online information and open knowledge creation and sharing based on the association function of social tagging, social and collaborative sharing among participants will help with personalised knowledge allocation.

In open knowledge management in higher education, the characteristics of personalisation and sociability based on social tagging will help to personalise the organisation and acquisition of knowledge, and help with social creation and sharing of knowledge.

Wiki is a new form of information production and organization, which has become one of the most important knowledge resources. In recent years, with the increase of users in wikis, “free rider problem” has been serious. In order to motivate editors to contribute more to a wiki system, it is important to fully understand their contribution behavior. The purpose of this paper is to explore the law of dynamic contribution behavior of editors in wikis.

After developing a dynamic model of contribution behavior, the authors employed both the metrological and clustering methods to process the time series data. The experimental data were collected from Baidu Baike, a renowned Chinese wiki system similar to Wikipedia.

There are four categories of editors: “testers,” “dropouts,” “delayers” and “stickers.” Testers, who contribute the least content and stop contributing rapidly after editing a few articles. After editing a large amount of content, dropouts stop contributing completely. Delayers are the editors who do not stop contributing during the observation time, but they may stop contributing in the near future. Stickers, who keep contributing and edit the most content, are the core editors. In addition, there are significant time-of-day and holiday effects on the number of editors’ contributions.

By using the method of time series analysis, some new characteristics of editors and editor types were found. Compared with the former studies, this research also had a larger sample. Therefore, the results are more scientific and representative and can help managers to better optimize the wiki systems and formulate incentive strategies for editors.

This paper aims to examine the relationship between the main decisions for designing distribution centers (DCs) and the contextual characteristics of the distribution networks.

Experts were surveyed and responses analyzed quantitatively through multivariate data techniques. This study considered four contextual characteristics that were deemed as influential for DC design: types of routes in the distribution network, quantity of DCs, distribution network levels and company size.

This paper evidenced which decisions are affected by each contextual characteristic encompassed in this study. This paper identified that the characteristic types of route in the distribution network must be carefully considered, as it had the greatest amount of associations with the decisions for designing a DC.

Despite its importance, most studies on design of DCs disregard the effect of the context in which DCs are inserted. This research provides arguments to support decision-making process of DCs design, increasing assertiveness of their planning. This work fulfills a literature gap by empirically examining the effect of contextual variables on the decisions related to DC design. Regarding practice, this paper addressed a fundamental issue for managers looking to design a DC, as it evidenced how contextual characteristics impact the decision-making.

The purpose of this paper is to review available technologies, analyse their features, propose a new approach of 3D sand mould printing based on line forming, introduce the manufacturing principle and show advantages of this approach, especially for larger parts with large Z steps in the build, such as 2 mm stepwise.

This paper introduces 3D sand mould printing, compares and analyses technological process and existing fabrication approaches among available technologies first. Then, a new approach of 3D sand mould printing is proposed to improve build speed. In addition, the proposed system will be analysed or benchmarked against existing systems.

A new approach based on line forming of sand mould printing is put forward by reviewing and analysing available technologies, to improve build speed from the aspect of basic moulding movement instead of optimization of moulding methods and process parameters. The theoretical calculation and analysis shows that build speed can be improved greatly, and it is more suitable for the manufacture of large-scale casting’s sand mould when considering dimensional accuracy and printing error, as well as uniformity of each layer.

The specific implement scheme of line forming and nozzle’s specific structure of this new approach need further study.

Much higher build speed of 3D sand mould printing with new approach brings evident implication for moulds companies and manufacturing industry, having a far-reaching influence on the development of national economy.

This paper reviews available technologies and presents a new approach of 3D sand mould printing for the first time. Analysis of the new approach shows that this new method of sand mould printing can boost build speed greatly. So, its application prospect is great.

In recent years, there has been a tremendous increase in the number of applicants seeking placements in undergraduate architecture programs. It is important during the selection phase of admission at universities to identify new intakes who possess the capability to succeed. Admission variable (i.e. prior academic achievement) is one of the most important criteria considered during the selection process. This paper aims to investigates the efficacy of using data mining techniques to predict the academic performance of architecture students based on information contained in prior academic achievement.

The input variables, i.e. prior academic achievement, were extracted from students’ academic records. Logistic regression and support vector machine (SVM) are the data mining techniques adopted in this study. The collected data were divided into two parts. The first part was used for training the model, while the other part was used to evaluate the predictive accuracy of the developed models.

The results revealed that SVM model outperformed the logistic regression model in terms of accuracy. Taken together, it is evident that prior academic achievement is a good predictor of academic performance of architecture students.

Although the factors affecting academic performance of students are numerous, the present study focuses on the effect of prior academic achievement on academic performance of architecture students.

The developed SVM model can be used as a decision-making tool for selecting new intakes into the architecture program at Nigerian universities.