Search results

Information is scarce on healthcare managers' understanding of simulation educators' impact on clinical work. Therefore, the aim of this study was to explore healthcare managers' perceptions of the significance of clinically active simulation educators for the organisation.

Healthcare managers were invited to be interviewed in a semi-structured manner. Inductive thematic analysis was used to identify and analyse patterns of notions describing the managers' perceptions of simulation educators' impact as co-workers on their healthcare organisations.

The identified relevant themes for the healthcare unit were: (1) value for the manager, (2) value for the community and (3) boundaries. Simulation educators were perceived to be valuable gatekeepers of evidence-based knowledge and partners in leadership for educational issues. Their most prominent value for the community was establishing a reflective climate, facilitating open communication and thereby improving the efficacy of teamwork. Local tradition, economy, logistics and staffing of the unit during simulation training were suggested to have possible negative impacts on simulation educators' work.

The findings might have implications for the implementation and support of simulation training programs.

Healthcare managers appreciated both the personal value of simulation educators and the effect of their work for their own unit. Local values were prioritised versus global. Simulation training was valued as an educational tool for continual professional development, although during the interviews, the managers did not indicate the importance of employment of pedagogically competent and experienced staff.

The study provided new insights about how simulation educators as team members affect clinical practice.

Students completing their tertiary education at a university may be equipped with theoretical knowledge with little to no practical experience. In order to bridge this gap in practical skills, a computer simulation was developed based on the e-filing platform of the South African Revenue Services (SARS). Students were exposed to this self-developed computer simulation to answer the question: to what extent will the e-filing simulation improve students' confidence to practically apply their theoretical knowledge?

The research applied a pre–post questionnaire research method to gauge the students' ability to apply their theoretical knowledge to a practical scenario before and after the simulation.

From the results, it is apparent that the students were inspired with confidence in getting to terms with the application of their theoretical knowledge in a real-life scenario. The computer simulation provided the platform for learning to take place in a practical environment without the risk of errors that would translate into real financial consequences.

The contribution of this research can be found in a teaching intervention that may support the training of future tax professionals in practical application skills. The contribution can be extended to the enhancement of education in the field of taxation, particularly with the results' showing that the students experienced high levels of increased confidence in their application of theoretical knowledge to real-life scenarios.

The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.

This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.

The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.

This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.

Most of the 3D printing machines do not comply with the requirements of on-site, large-scale multi-story building construction. This paper aims to propose the conceptualization of a tower crane (TC)-based 3D printing controlled by artificial intelligence (AI) as the first step towards a large 3D printing development for multi-story buildings. It also aims to overcome the most important limitation of additive manufacturing in the construction industry (the build volume) by exploiting the most important machine used in the field: TCs. It assesses the technology feasibility by investigating the accuracy reached in the printing process.

The research is composed of three main steps: firstly, the TC-based 3D printing concept is defined by proposing an aero-pendulum extruder stabilized by propellers to control the trajectory during the extrusion process; secondly, an AI-based system is defined to control both the crane and the extruder toolpath by exploiting deep reinforcement learning (DRL) control approach; thirdly the proposed framework is validated by simulating the dynamical system and analysing its performance.

The TC-based 3D printer can be effectively used for additive manufacturing in the construction industry. Both the TC and its extruder can be properly controlled by an AI-based control system. The paper shows the effectiveness of the aero-pendulum extruder controlled by AI demonstrated by simulations and validation. The AI-based control system allows for reaching an acceptable tolerance with respect to the ideal trajectory compared with the system tolerance without stabilization.

In related literature, scientific investigations concerning the use of crane systems for 3D printing and AI-based systems for control are completely missing. To the best of the authors’ knowledge, the proposed research demonstrates for the first time the effectiveness of this technology conceptualized and controlled with an intelligent DRL agent.

The results provide the first step towards the development of a new additive manufacturing system for multi-storey constructions exploiting the TC-based 3D printing. The demonstration of the conceptualization feasibility and the control system opens up new possibilities to activate experimental research for companies and research centres.