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ObjectiveSecondary data are a significant resource for in‐depth epidemiologic and public health research. It also allows for effective quality control and clinical outcomes measurement. To illustrate the value of structured diagnostic entry, a use case was developed to quantify adherence to current practice guidelines for managing chronic moderate periodontitis (CMP).MethodsSix dental schools using the same electronic health record (EHR) contribute data to a dental data repository (BigMouth) based on the i2b2 data‐warehousing platform. Participating institutions are able to query across the full repository without being able to back trace specific data to its originating institution. At each of the three sites whose data are included in this analysis, the Dental Diagnostic System (DDS) terminology was used to document diagnoses in the clinics. We ran multiple queries against this multi‐institutional database, and the output was validated by manually reviewing a subset of patient charts.ResultsOver the period under study, 1,866 patients were diagnosed with CMP. Of these, 15 percent received only periodontal prophylaxis treatment, 20 percent received only periodontal maintenance treatment, and only 41 percent received periodontal maintenance treatment in combination with other AAP guideline treatments.ConclusionsOur results showed that most patients with CMP were not treated according to the AAP guidelines. On the basis of this use case, we conclude that the availability and habitual use of a structured diagnosis in an EHR allow for the aggregation and secondary analyses of clinical data to support downstream analyses for quality improvement and epidemiological assessments.

The control of grid‐connected inverters is recently executed with digital microprocessors due to the advances in digital signal processing technology. However, the digital realisation has a drawback of the phase lag induced by the time‐delay. This phase lag challenges the stability and robustness of the controller of the inverters. In view of the challenge, this paper presents a comprehensive review of time‐delay compensation techniques employed in both model‐free (MF), and model‐based (MB) controls of an inverter in grid connection. MF techniques mainly use proportional‐integral, and proportional resonance controllers with some techniques to reduce time‐delay. Meanwhile, for MB, this paper discusses the commonly used control techniques, which are the Smith predictor, modified Smith predictor, deadbeat controller and model predictive controller. Several related techniques from the literature that have been adopted to mitigate the delays are tabulated comprehensively, and critical issues regarding the MF and MB techniques are also discussed. Finally, this paper presents a hypothesis on which technique is superior at present and suggests a hybrid technique from the MF and MB techniques to give readers a direction for further research.

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This paper presents a robust H∞ control technique for an islanded microgrid in the presence of sudden changes in load conditions. The proposed microgrid scheme consists of a parallel connected inverter with distributed generations. When the load is suddenly changed the frequency deviates from its nominal value. The objective is to design a robust frequency droop controller in order to achieve the frequency at nominal values without using any secondary controller and communication systems while improving power sharing accuracy. Small signal modeling of the power system is designed for the formulation of the problem and the H∞ optimal linear matrix inequality technique is applied in order to achieve the objectives. The proposed controller has been tested with the MATLAB/ SimPowerSytem toolbox.

Discrete-time dynamic systems demonstrate quite exciting possibilities from the perspective of control as compared with the continuous-time counterpart. Interesting properties of discrete-time dynamic systems include the possibility to algebraically determine previously unknown system parameters by simply measuring the present inputs and outputs of the system. Additionally, achieving a finite settling time with zero steady-state error is only achievable in discrete-time dynamic systems. Deadbeat current control (DBCC) has been used to achieve a finite settling time, especially in grid-connected inverter applications. However, there is no comprehensive study on reviewing or evaluating existing control approaches, to the authors' best knowledge. This paper systematically examined the existing methods by paying attention to four key research issues: 1) research evidences indicating the adoption of DBCC in grid-connected inverter applications (GCIAs), 2) the types of deadbeat control approaches adopted in GCIAs, 3) the best approach in terms of stability especially regarding grid-impedance variation, and 4) the barriers that might prevent the wide adoption of DBCC in GCIAs. Finally, this paper presents a hypothesis based on the simulated results on which approach is superior at present to give readers a direction for further research classification on deadbeat control.INDEX TERMS Deadbeat control, grid-connected inverter, current control, renewable energy sources.

The future of power systems depends on the microgrid (MG) which includes distribution generators utilizing Renewable Energy Resources (RERs) and storage facilities. Decentralized control techniques are more reliable and stable in comparison with centralized controlled techniques. In this paper, a decentralized control strategy is presented for an islanded AC MG system. The control strategy includes improved droop control and virtual impedance. Control strategy with PI controllers to control the voltage and current is implemented to two Voltage Source Inverter (VSI) distribution generation units connected in parallel through a Point of Common Coupling (PCC). Circulating current and power-sharing deviations caused by the mismatched line impedance were taken into account. The proposed control scheme was tested in MATLAB/Simulink. Power-sharing accuracy and circulating current suppression were obtained by implementing the proposed virtual impedance-based decentralized control strategy.

<span>A wireless sensor network (WSN) composed by a large number of sensor nodes that are insufficient in terms of processing power, storage and energy. The principal tasks of nodes is gathering and transmitting data collected to the base station (BS). Consequently the major essential criteria for designing a WSN are the network lifetime. In this paper an efficient GAF routing protocol for gathered data is introduced. It proposes an energy-efficient routing in WSN based on the basic version. In this system sensor nodes are distributed using Gaussian law and an active leader is elected for each virtual grid to reduce the energy dissipated using an optimized weighted sum model where maximum remaining energy and minimum distance criteria are considered. Moreover routing data is based on transmission range for enhancing the energy efficiency during data routing. The experimental results shows that the proposed EE-GAF produces better performance than the existing GAF basic and optimized-GAF routing protocol in terms of number of dead node  and energy consumption. It is obviously proves that the proposed EE-GAF can improve the network lifetime</span>