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This paper aims to show how implementing new information technology has expanded the role of librarians as educators and how this role has matched the evolution of new technology.

The paper looks at librarians' approaches to their role as educators and explores ways of most effectively implementing changes. By reviewing the literature and taking the old discourse around library education and information literacy, the paper reflects on the changing role of librarians in an era of greater access to technology, including Web 2.0.

Collaboration with faculty was found to be an essential feature of the most successful stories. Teaching students and faculty to use new information technologies may have become one of the major roles of librarians.

This paper demonstrates that the continual evolution of the web is causing a move from e‐libraries to mobile libraries, and that the educational role of the librarians must encompass this trend, and to anticipate similar future developments.

This study aims to explore the effects of corporate governance structure and resources on foreign direct investment (FDI) commitment and firm performance.

The data are collected from high-tech firms listed by the Taiwan Stock Exchange. All selected 137 firms have complete FDI and other required data during 2007-2009. The mean values of the variables during the three-year period were used for analysis.

The results indicate that both chief executive officer (CEO) duality and government shareholding affect a firm’s FDI; and the higher the management shareholding ratio, the lower the return on equity. Moreover, a large ownership of substantial shareholders can enhance a firm’s performance; and higher institutional ownership can lead to higher firm performance.

This study analyses the limited data from 137 high-tech firms in Taiwan during the three-year period of 2007-2009. Further analyses of other industries, countries and time periods are needed to generalize the conclusions.

A firm with CEO duality should increase the ratio of government holding to mitigate the influence of CEO on FDI decisions. When a firm’s performance is poor, the ratio of managerial holdings should be reduced; conversely, the firm could attract more holdings from domestic securities and funds to improve performance.

This study provides guidelines for shareholders to analyze governance structure and formulate their investment strategies. Corporate policymakers may use these as the principles for designing a corporate governance structure that could engender optimal firm performance.

In order to improve the efficiency and reliability of simulation analysis for composite riveting structures in engineering products, a comparative study was conducted on different forms of riveting simulation methods.

Five different rivent simulation models were established using the finite element method, including rigid element CE, flexible element Rbe3 and beam element, and their results were future compared and analyzed.

Under the given technical parameters, the simulation method of Rbe3 (with holes) + beam can meet the analysis requirements of complex engineering products in terms of the rationality of rivet load distribution, calculation error and relatively efficient modeling.

This study proposes a simulation method for the riveting structure of carbon fiber composite materials for engineering applications. This method can satisfy the simulation analysis requirements of transportation vehicles in terms of modeling time, computational efficiency and accuracy. The research can provide technical support for the riveting process and mechanical analysis between carbon fiber composite components in transportation products.

Powder bed additive manufacturing has recently seen substantial growth, yet consistently producing high-quality parts remains challenging. Recoating streaking is a common anomaly that impairs print quality. Several data-driven models for automatically detecting this anomaly have been proposed, each with varying effectiveness. However, comprehensive comparisons among them are lacking. Additionally, these models are often tailored to specific data sets. This research addresses this gap by implementing and comparing these anomaly detection models for recoating streaking in a reproducible way. This study aims to offer a clearer, more objective evaluation of their performance, strengths and weaknesses. Furthermore, this study proposes an improvement to the Line Profiles detection model to broaden its applicability, and a novel preprocessing step was introduced to enhance the models’ performances.

All found anomaly detection models have been implemented along with several preprocessing steps. Additionally, a new universal benchmarking data set has been constructed. Finally, all implemented models have been evaluated on this benchmarking data set and the effect of the different preprocessing steps was studied.

This comparison shows that the improved Line Profiles model established it as the most efficient detection approach in this study’s benchmark data set. Furthermore, while most state-of-the-art neural networks perform very well off the shelf, this comparison shows that specialised detection models outperform all others with the correct preprocessing.

This comparison gives new insights into different recoater streaking (RCS) detection models, showcasing each one with its strengths and weaknesses. Furthermore, the improved Line Profiles model delivers compelling performance in detecting RCS.