Probabilistic priority assessment of nurse calls

Current nurse call systems are very static. Call buttons are fixed to the wall, and systems do not account for various factors specific to a situation. We have developed a software platform, the ontology-based Nurse Call System (oNCS), which supports the transition to mobile and wireless nurse call buttons and uses an intelligent algorithm to address nurse calls. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff and patients into account by using an ontology. This article describes a probabilistic extension of the oNCS that supports a more sophisticated nurse call algorithm by dynamically assigning priorities to calls based on the risk factors of the patient and the kind of call. The probabilistic oNCS is evaluated through implementation of a prototype and simulations, based on a detailed dataset obtained from 3 nursing departments of Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls among nurses, and the assignment of priorities to calls are compared for the oNCS and the current nurse call system. Additionally, the performance of the system and the parameters of the priority assignment algorithm are explored. The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the probabilistic oNCS significantly improves the assignment of nurses to calls. Calls generally result in a nurse being present more quickly, the workload distribution among the nurses improves, and the priorities and kinds of calls are taken into account

Participatory design of a continuous care ontology : towards a user-driven ontology engineering methodology

The patient room of the future would be able to sense the needs and preferences of the patients and nurses and adapt itself accordingly by combining all the heterogeneous data offered by the different technologies. This goal can be achieved by developing a context-aware framework, which exploits and integrates the heterogeneous data by utilizing a continuous care ontology. The existing ontology engineering methodologies are rather extreme in their choices to include domain experts. On the one hand, there are methodologies that only discuss the scope, use and requirements of the ontology with the domain experts. On the other hand, there are approaches in which the ontology is completely constructed by the domain experts by providing them with user-friendly and collaborative tools. In this paper, a participatory ontology engineering methodology is presented that finds a middle ground between these two extremes. The methodology actively involves social scientists, ontology engineers and stakeholders. The stakeholders participate in each step of the ontology life cycle without having to construct the ontology themselves or attribute a large amount of their time. The applicability of the methodology is illustrated by presenting the co-created continuous care ontology

Extreme ultraviolet detection using AlGaN-on-Si inverted Schottky photodiodes

We report on the fabrication of aluminum gallium nitride (AlGaN) Schottky diodes for extreme ultraviolet (EUV) detection. AlGaN layers were grown on silicon wafers by molecular beam epitaxy with the conventional and inverted Schottky structure, where the undoped, active layer was grown before or after the n-doped layer, respectively. Different current mechanisms were observed in the two structures. The inverted Schottky diode was designed for the optimized backside sensitivity in the hybrid imagers. A cut-off wavelength of 280 nm was observed with three orders of magnitude intrinsic rejection ratio of the visible radiation. Furthermore, the inverted structure was characterized using a EUV source based on helium discharge and an open electrode design was used to improve the sensitivity. The characteristic He I and He II emission lines were observed at the wavelengths of 58.4 nm and 30.4 nm, respectively, proving the feasibility of using the inverted layer stack for EUV detectio