Research interdisciplinarity: STEM versus non-STEM.

Research collaboration among interdisciplinary teams has become a common trend in recent days. However, there is a lack of evidence in literature regarding which disciplines play dominant roles in interdisciplinary research settings. It is also unclear whether the dominant role of disciplines vary between STEM (Science, Technology, Engineering, and Mathematics) and non-STEM focused research. This study considers metadata of the research projects funded by the Australian Research Council Discovery Grant Project scheme. Applying network analytics, this study investigates the contribution of individual disciplines in the successfully funded projects. It is noted that the disciplines Engineering, Biological Sciences and Technology appear as the principal disciplines in interdisciplinary research having a STEM focus. By contrast, non-STEM interdisciplinary research is led by three disciplines-Studies in Human Societies, Language, Communication and Culture, and History and Archaeology. For projects entailing interdisciplinarity between STEM and non-STEM disciplines, the STEM discipline of Medical and Health Sciences and the non-STEM disciplines of Psychology and Cognitive Science and Studies in Human Societies appear as the leading contributors. Overall, the network-based visualisation reveals that research interdisciplinarity is implemented in a heterogeneous way across STEM and non-STEM disciplines, and there are gaps in inter-disciplinary collaborations among some disciplines.

A model-based approach for bridging virtual and physical sensor nodes in a hybrid simulation framework.

The Model Based Design (MBD) approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs) are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL) simulation.