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Control methods based on global positioning systems (GPS) are reported in multiple literatures recently, which achieve a fixed frequency operation of the microgrid and therefore has the tremendous benefit that any problems related to frequency instability are eliminated. However, the possible interruption of GPS timing signals may cause current circulating and finally leads to instability of the microgrid, yet it is largely neglected in literatures. This paper presents an angle synchronizing mechanism which utilizes the timing signal from GPS satellites and an auxiliary frequency droop loop to ensure synchronization during GPS offline events. Smooth transfer is guaranteed between primary and auxiliary control loops with discrete control architecture. Also, to allow microgrid using GPS-based control to work in tandem with the bulk power system or another frequency droop microgrid, an extra synchronization algorithm is proposed. The viability and performance of the proposed control structure is validated by case studies.

The passivation of iron and steel (DIN 1623) was studied by integral and depth selective conversion electron Mossbauer spectroscopy and Auger electron spectroscopy. Thickness and phase composition of the passive layer formed in sulphate solution and in a phosphate buffer were determined in dependence on the anodic potential and the duration of the passivating procedure. The experimental results lead to the conclusion that not the whole oxidic layer is responsible for the passivity but only a very thin intermediate layer formed between the cubic substrate and the rhombic oxide (γ-FeOOH) cover.

Effective access control techniques are in demand, as electronically assisted healthcare services require the patient’s sensitive health records. In emergency situations, where the patient’s well-being is jeopardized, different healthcare actors associated with emergency cases should be granted permission to access Electronic Health Records (EHRs) of patients. The research objective of our study is to develop machine learning techniques based on patients’ time sequential health metrics and integrate them with an Attribute Based Access Control (ABAC) mechanism. We propose an ABAC mechanism that can yield access to sensitive EHRs systems by applying prognostic context handlers where contextual information, is used to identify emergency conditions and permit access to medical records. Specifically, we use patients’ recent health history to predict the health metrics for the next two hours by leveraging Long Short Term Memory (LSTM) Neural Networks (NNs). These predicted health metrics values are evaluated by our personalized fuzzy context handlers, to predict the criticality of patients’ status. The developed access control method provides secure access for emergency clinicians to sensitive information and simultaneously safeguards the patient’s well-being. Integrating this predictive mechanism with personalized context handlers proved to be a robust tool to enhance the performance of the access control mechanism to modern EHRs System.

The paper comprises a systematic experimental investigation into the influence of AC test source parameters on the leakage current pulses, voltage fluctuations and flashover voltages of polluted insulators. The test techniques include both salt-and clean-fog methods, while the test insulators comprise long-rod and cap and pin strings of different lengths as well as support columns.